We investigate the representation of individual supercells and intriguing tornado-like vortices in a simplified, locally refined global atmosphere model. The model, featuring grid stretching, can locally enhance the model resolution and reach cloud-resolving scales with modest computational resources. Given a conditionally unstable sheared environment, the model can simulate supercells realistically, with a near-ground vortex and funnel cloud at the center of a rotating updraft reminiscent of a tornado. An analysis of the Eulerian vertical vorticity budget suggests that the updraft core of the supercell tilts horizontal vorticity into the tornado-like vortex, which is then amplified through vertical stretching by the updraft. Results suggest that the simulated vortex is dynamically similar to observed tornadoes, as well as those simulated in modeling studies at much higher horizontal resolution. Lastly, we discuss the prospects for the study of cross-scale interactions involving supercells.
Judt, Falko, Daniel Klocke, Rosimar Rios-Berrios, Benoit Vanniere, Florian Ziemen, Ludovic Auger, Joachim Biercamp, Christopher S Bretherton, Xi Chen, Peter Düben, Cathy Hohenegger, Marat Khairoutdinov, Chihiro Kodama, Luis Kornblueh, Shian-Jiann Lin, Masuo Nakano, Philipp Neumann, William M Putman, Niklas Röber, Malcolm J Roberts, Masaki Satoh, Ryosuke Shibuya, Bjorn Stevens, Pier Luigi Vidale, Nils Wedi, and Linjiong Zhou, June 2021: Tropical cyclones in global storm-resolving models. Journal of the Meteorological Society of Japan. Ser. II, 99(3), DOI:10.2151/jmsj.2021-029579-602. Abstract
Recent progress in computing and model development has initiated the era of global storm-resolving modeling, and with it the potential to transform weather and climate prediction. Within the general theme of vetting this new class of models, the present study evaluates nine global-storm resolving models in their ability to simulate tropical cyclones (TCs). Results indicate that, broadly speaking, the models produce realistic TCs and remove longstanding issues known from global models such as the deficiency in accurately simulating TC intensity. However, TCs are strongly affected by model formulation, and all models suffer from unique biases regarding the number of TCs, intensity, size, and structure. Some models simulated TCs better than others, but no single model was superior in every way. The overall results indicate that global storm-resolving models can open a new chapter in TC prediction, but they need to be improved to unleash their full potential.
We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL ‐ the AM4 atmosphere model, MOM6 ocean code, LM4 land model and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0o (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1o to 0.25o. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM 4 models, but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time‐mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM 4 models.
We present the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short‐to‐medium‐range and subseasonal‐to‐seasonal prediction, global‐to‐regional convective‐scale hurricane and contiguous U.S. precipitation forecasts, and global cloud‐resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3‐based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13‐km SHiELD demonstrates steadily improved large‐scale prediction skill and precipitation prediction skill. SHiELD and the coarser‐resolution S‐SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden‐Julian Oscillation. The global‐to‐regional nested configurations T‐SHiELD (tropical Atlantic) and C‐SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium‐range prediction of convective storms.
Motivated by the use of the GFDL microphysics scheme in the FV3GFS, the all-sky radiance assimilation framework has been expanded to include precipitating hydrometeors. Adding precipitating hydrometeors allows the assimilation of precipitation-affected radiance in addition to cloudy radiance. In this upgraded all-sky framework, the five hydrometeors, including cloud liquid water, cloud ice, rain, snow and graupel, are the new control variables, replacing the original cloud water control variable. The Community Radiative Transfer Model (CRTM) was interfaced with the newly added precipitating hydrometeors. Sub-grid cloud variability was considered by using the average cloud overlap scheme. Multiple scattering radiative transfer was activated in the upgraded framework. Radiance observations from the Advanced Microwave Sounding Unit-A (AMSU-A) and the Advanced Technology Microwave Sounder (ATMS) over ocean were assimilated in all-sky approach. This new constructed all-sky framework shows neutral to positive impact on overall forecast skill. Improvement was found in 500 hPa geopotential height forecast in both Northern and Southern Hemispheres. Temperature forecast was also improved at 850 hPa in the Southern Hemisphere and the Tropics.
We use the fvGFS model developed at the Geophysical Fluid Dynamics Laboratory (GFDL) to demonstrate the potential of the upcoming United States Next Generation Global Prediction System for hurricane prediction. The fvGFS retrospective forecasts initialized with the European Centre for Medium‐Range Weather Forecasts (ECMWF) data showed much‐improved track forecasts for the 2017 Atlantic hurricane season compared to the best performing ECMWF operational model. The fvGFS greatly improved the ECMWF's poor track forecast for Hurricane Maria (2017). For Hurricane Irma (2017), a well‐predicted case by the ECMWF model, the fvGFS produced even lower 5‐day track forecast errors. The fvGFS also showed better intensity prediction than both the United States and the ECMWF operational models, indicating the robustness of its numerical algorithms.
A new global model using the GFDL nonhydrostatic Finite-Volume Cubed-Sphere Dynamical Core (FV3) coupled to physical parameterizations from the National Centers for Environmental Prediction's Global Forecast System (NCEP/GFS) was built at GFDL, named fvGFS. The modern dynamical core, FV3, has been selected for National Oceanic and Atmospheric Administration’s Next Generation Global Prediction System (NGGPS) due to its accuracy, adaptability, and computational efficiency, which brings a great opportunity for the unification of weather and climate prediction systems.
The performance of tropical cyclone (TC) forecasts in the 13-km fvGFS is evaluated globally based on 363 daily cases of 10-day forecasts in 2015. Track and intensity errors of TCs in fvGFS are compared to those in the operational GFS. The fvGFS outperforms the GFS in TC intensity prediction for all basins. For TC track prediction, the fvGFS forecasts are substantially better over the northern Atlantic basin and the northern Pacific Ocean than the GFS forecasts. An updated version of the fvGFS with the GFDL 6-category cloud microphysics scheme is also investigated based on the same 363 cases. With this upgraded microphysics scheme, fvGFS shows much improvement in TC intensity prediction over the operational GFS. Besides track and intensity forecasts, the performance of TC genesis forecast is also compared between the fvGFS and operational GFS. In addition to evaluating the hit/false alarm ratios, a novel method is developed to investigate the lengths of TC genesis lead times in the forecasts. Both versions of fvGFS show higher hit ratios, lower false alarm ratios and longer genesis lead times than those of the GFS model in most of the TC basins.
We demonstrate that two‐way nesting significantly improves the structure of simulated hurricane in an atmospheric general circulation model. Two sets of 30‐day hindcast experiments are conducted, one with the global‐uniform‐resolution (approximately 25‐km nominal horizontal resolution) and the other with a regionally refined two‐way nest (approximately 8 km over the tropical North Atlantic). The increase in the horizontal resolution on the nested grid improves the representation of storm intensity and intensification rate. When normalized by the radius of maximum wind (RMW), composite hurricane structures are generally similar in both simulations and compare well to observations. However, the hurricanes in the globally uniform configuration have much larger RMWs than observed, while those in the two‐way‐nested configuration have more realistic RMWs. We also find that the representation of the RMW has a critical impact on the simulation of inertial stability and boundary‐layer convergence in the inner‐core region. The more realistic inner‐core size (indicated by RMW) and structure are possible reasons for the improved intensification rates in the two‐way‐nested configuration.
We investigate the monthly prediction of North Atlantic hurricane and especially major hurricane activity based on the Geophysical Fluid Dynamics Laboratory High‐Resolution Atmospheric Model (HiRAM). We compare the performance of two versions of HiRAM: a globally‐uniform 25‐km grid and the other with an 8‐km interactive nest over the tropical North Atlantic. Both grid configurations show skills in predicting anomalous monthly hurricane frequency and accumulated cyclone energy (ACE). Particularly the 8‐km nested model shows improved skills in predicting major hurricane frequency and ACE. The skill in anomalous monthly hurricane occurrence prediction arises from the accurate prediction of zonal wind shear anomalies in the Main Development Region, which in turn arises from the SST anomalies persisted from the initialization time. The enhanced resolution on the nested grid permits a better representation of hurricanes and especially intense hurricanes, thereby showing the ability and the potential for prediction of major hurricanes on subseasonal timescales.
We describe GFDL's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the pre‐industrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasi‐periodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.
Understanding the root causes of forecast errors and occasional very poor forecasts is essential but difficult. In this paper we investigate the relative importance of initial conditions and model formulation for medium‐range errors in 500‐hPa geopotential height. The question is addressed by comparing forecasts produced with ECMWF‐IFS and NCEP‐GFS forecasting systems, and with the GFDL‐fvGFS model initialised with ECMWF and NCEP initial conditions. This gives two pairs of configurations that use the same initial conditions but different models, and one pair with the same model but different initial conditions. The first conclusion is that the initial conditions play the major role for differences between the configurations in terms of the average root‐mean‐square error for both northern and southern hemispheres as well as Europe and the contiguous U.S (CONUS), while the model dominates the systematic errors. A similar conclusion is also found by verifying precipitation over low latitudes and the CONUS. The day‐to‐day variations of 500‐hPa geopotential height scores are exemplified by one case of a forecast bust over Europe, where the error is found to be dominated by initial errors. The results are generalised by calculating correlations between errors integrated over Europe, CONUS and a region in southeastern Pacific respectively from the different configurations. For Europe and southeast Pacific, the correlations in the medium‐range are highest between the pairs that use the same initial conditions, while over CONUS it is for the pair with the same model. This suggests different mechanisms behind the day‐to‐day variability of the score for these regions. Over CONUS the link is made to the propagation of troughs over the Rockies, and the result suggests that the large differences in parameterisations of orographic drag between the models plays a role.
Satoh, Masaki, Bjorn Stevens, Falko Judt, Marat Khairoutdinov, and Shian-Jiann Lin, et al., September 2019: Global Cloud-Resolving Models. Current Climate Change Reports, 5(3), DOI:10.1007/s40641-019-00131-0. Abstract
Purpose of Review
Global cloud-resolving models (GCRMs) are a new type of atmospheric model which resolve nonhydrostatic accelerations globally with kilometer-scale resolution. This review explains what distinguishes GCRMs from other types of models, the problems they solve, and the questions their more commonplace use is raising.
Recent Findings
GCRMs require high-resolution discretization over the sphere but can differ in many other respects. They are beginning to be used as a main stream research tool. The first GCRM intercomparison studies are being coordinated, raising new questions as to how best to exploit their advantages.
Summary
GCRMs are designed to resolve the multiscale nature of moist convection in the global dynamics context, without using cumulus parameterization. Clouds are simulated with cloud microphysical schemes in ways more comparable to observations. Because they do not suffer from ambiguity arising from cumulus parameterization, as computational resources increase, GCRMs are the promise of a new generation of global weather and climate simulations.
Surface layer (SL) variables [e.g., 2‐m temperature (T2) and 10‐m wind (U10)] are diagnosed by applying the flux‐profile relationships based on Monin‐Obukhov similarity theory to the lowest model height (LMH). This assumes that the LMH is in the SL, which is approximately the bottom 10% of the boundary layer, but atmospheric general circulation models rarely satisfy this in stable boundary layers (SBLs). To assess errors in the diagnostic variables due to the LMH solely linked to the diagnostic algorithm, offline tests of the flux‐profile relationships are performed with LMH from a few meters to 60 m for three SBL regimes: weakly stable, very stable, and transition stability regimes. The results show that T2 and U10 are underestimated by O(0.1–1 °C) and O(0.1–1 m s−1), respectively, if the LMH is higher than the SL height. The stronger the SL stability is, the larger the temperature biases are. The negative wind biases increase with the surface stress. Based on these findings, we analyze the impacts of the LMH on the climatologies of the diagnostic parameters in the GFDL AM4.0/LM4.0. The results show reduced negative biases in T2 and U10 by lowering the LMH. The decrease of the overall bias over land is mainly due to the sensitivity of the diagnostic method to the LMH in SBLs, as shown in the offline tests. The overall increase in T2 and U10 over the oceans results from the increase in the actual near‐surface temperature and wind rather than from the diagnostic method.
Stevens, Bjorn, Masaki Satoh, Ludovic Auger, Joachim Biercamp, Christopher S Bretherton, Xi Chen, Peter Düben, Falko Judt, Marat Khairoutdinov, Daniel Klocke, Chihiro Kodama, Luis Kornblueh, Shian-Jiann Lin, Philipp Neumann, William M Putman, Niklas Röber, Ryosuke Shibuya, Benoit Vanniere, Pier Luigi Vidale, Nils Wedi, and Linjiong Zhou, September 2019: DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains. Progress in Earth and Planetary Science, 6, 61, DOI:10.1186/s40645-019-0304-z. Abstract
A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period. Eight of these employed a tiling of the sphere that was uniformly less than 5 km. By resolving the transient dynamics of convective storms in the tropics, global storm-resolving models remove the need to parameterize tropical deep convection, providing a fundamentally more sound representation of the climate system and a more natural link to commensurately high-resolution data from satellite-borne sensors. The models and some basic characteristics of their output are described in more detail, as is the availability and planned use of this output for future scientific study. Tropically and zonally averaged energy budgets, precipitable water distributions, and precipitation from the model ensemble are evaluated, as is their representation of tropical cyclones and the predictability of column water vapor, the latter being important for tropical weather.
Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.
With a GFDL coupled model, the subseasonal prediction of wintertime (December‐February) surface air temperature (SAT) is investigated through the analysis of 11‐year hindcasts. Significant subseasonal week 3‐5 correlation skill exists over a large portion of the global land domain, and the predictability originates primarily from the eight most predictable SAT modes. The first three modes, identified as the El Niño‐Southern Oscillation mode, the North Atlantic Oscillation (NAO) mode, and the Eurasia Meridional Dipole (EMD) mode, can be skillfully predicted more than 5 weeks in advance. The NAO and EMD modes are strongly correlated with the initial stratospheric polar vortex strength, highlighting the role of stratosphere in subseasonal prediction. Interestingly, the Madden‐Julian Oscillation is not essential for the subseasonal land SAT prediction in the Northern Hemisphere extratropics. The spatial correlation skill exhibits considerable intraseasonal and interannual fluctuations, indicative of the importance to identify the time window of opportunity for subseasonal prediction.
Understanding the predictability limit of day-to-day weather phenomena such as midlatitude winter storms and summer monsoonal rainstorms is crucial to numerical weather prediction (NWP). This predictability limit is studied using unprecedented high-resolution global models with ensemble experiments of the European Center for Medium Range Weather Forecasting (ECMWF, 9-km operational model) and identical-twin experiments of the US next-generation global prediction system (NGGPS, 3-km). Results suggest that predictability limit for mid-latitude weather may indeed exist and is intrinsic to the underlying dynamical system and instabilities even if the forecast model and the initial conditions are nearly perfect. Currently, a skillful forecast lead time of midlatitude instantaneous weather is around 10 days, which serves as the practical predictability limit. Reducing the current-day initial-condition uncertainty by an order of magnitude extends the deterministic forecast lead times of day-to-day weather by up to 5 days, with much less scope for improving prediction of small-scale phenomena like thunderstorms. Achieving this additional predictability limit can have enormous socioeconomic benefits but requires coordinated efforts by the entire community to design better numerical weather models, to improve observations, and to make better use of observations with advanced data assimilation and computing techniques.
Zhang, F, M Minamide, R G Nystrom, X Chen, Shian-Jiann Lin, and Lucas Harris, July 2019: Improving Harvey forecasts with next-generation weather satellites. Bulletin of the American Meteorological Society, 100(7), DOI:10.1175/BAMS-D-18-0149.1. Abstract
The experimental forecasts initialized with the ensemble assimilation of the all-sky radiances—from the next-generation satellite (GOES-16)—has demonstrated its potential in more accurate prediction of Hurricane Harvey (2017) before its rapid intensification.
Hurricane Harvey brought catastrophic destruction and historical flooding to the Gulf Coast region in late August 2017. Guided by numerical weather prediction models, operational forecasters at NOAA provided outstanding forecasts of Harvey’s future path and potential for record flooding days in advance. These forecasts were valuable to the public and emergency managers in protecting lives and property. The current study shows the potential for further improving Harvey’s analysis and prediction through advanced ensemble assimilation of high-spatiotemporal all-sky infrared radiances from the newly-launched, next-generation geostationary weather satellite, GOES-16. Although findings from this single-event study should be further evaluated, the results highlight the potential improvement in hurricane prediction that is possible via sustained investment in advanced observing systems, such as those from weather satellites, comprehensive data assimilation methodologies that can more effectively ingest existing and future observations, higher-resolution weather prediction models with more accurate numerics and physics, and high-performance computing facilities that can perform advanced analysis and forecasting in a timely manner.
Zhang, C, Ming Xue, Timothy A Supinie, F Kong, N Snook, K W Thomas, K Brewster, Y Jung, Lucas Harris, and Shian-Jiann Lin, March 2019: How Well Does an FV3-based Model Predict Precipitation at a Convection-Allowing Resolution? Results from CAPS Forecasts for the 2018 NOAA Hazardous Weather Testbed with Different Physics Combinations. Geophysical Research Letters, 46(6), DOI:10.1029/2018GL081702. Abstract
The Geophysical Fluid Dynamics Laboratory (GFDL) Finite‐Volume Cubed‐Sphere (FV3) numerical forecast model was chosen in late 2016 by the National Weather Service (NWS) to serve as the dynamic core of the Next‐Generation Global Prediction System (NGGPS). The operational Global Forecasting System (GFS) physics suite implemented in FV3, however, was not necessarily suitable for convective‐scale prediction. We implemented several advanced physics schemes from the Weather Research and Forecasting (WRF) model within FV3 and ran 10 forecasts with combinations of five planetary boundary layer and two microphysics (MP) schemes, with an ~3.5‐km convection‐allowing grid two‐way nested within am ~13‐km grid spacing global grid during the 2018 Spring Forecasting Experiment at National Oceanic and Atmospheric Administration (NOAA)'s Hazardous Weather Testbed. Objective verification results show that the Thompson MP scheme slightly outperforms the National Severe Storms Laboratory MP scheme in precipitation forecast skill, while no planetary boundary layer scheme clearly stands out. The skill of FV3 is similar to that of the more‐established WRF at a similar resolution. These results establish the viability of the FV3 dynamic core for convective‐scale forecasting as part of the single‐core unification of the NWS modeling suite.
The variable-resolution version of a Finite-Volume Cubed-Sphere Dynamical Core (FV3)-based global model improves the prediction of convective-scale features while maintaining skillful global forecasts.
The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new variable-resolution global model with the ability to represent convective-scale features that serves as a prototype of the Next Generation Global Prediction System (NGGPS). The goal of this prediction system is to maintain the skill in large-scale features while simultaneously improving the prediction skill of convectively-driven mesoscale phenomena. This paper demonstrates the new capability of this model in convective-scale prediction relative to the current operational Global Forecast System (GFS). This model uses the stretched-grid functionality of the Finite-Volume Cubed-Sphere Dynamical Core (FV3) to refine the global 13-km uniform-resolution model down to 4-km convection-permitting resolution over the Contiguous United States (CONUS), and implements the GFDL single-moment six-category cloud microphysics to improve the representation of moist processes.
Statistics gathered from two years of simulations by the GFS and select configurations of the FV3-based model are carefully examined. The variable-resolution FV3-based model is shown to possess global forecast skill comparable with that of the operational GFS while quantitatively improving skill and better representing the diurnal cycle within the high-resolution area compared to the uniform mesh simulations. Forecasts of the occurrence of extreme precipitation rates over the Southern Great Plains are also shown to improve with the variable-resolution model. Case studies are provided of a squall line and a hurricane to demonstrate the effectiveness of the variable-resolution model to simulate convective-scale phenomena.
Chen, Xi, Shian-Jiann Lin, and Lucas Harris, September 2018: Towards an unstaggered finite‐volume dynamical core with a fast Riemann solver: 1D linearized analysis of dissipation, dispersion, and noise control. Journal of Advances in Modeling Earth Systems, 10(9), DOI:10.1029/2018MS001361. Abstract
Many computational fluid dynamics codes use Riemann solvers on an unstaggered grid for finite volume methods, but this approach is computationally expensive compared to existing atmospheric dynamical cores equipped with hyper‐diffusion or other similar relatively simple diffusion forms. We present a simplified Low Mach number Approximate Riemann Solver (LMARS), made computationally efficient through assumptions appropriate for atmospheric flows: low Mach number, weak discontinuities, and locally‐uniform sound speed. This work will examine the dissipative and dispersive properties of LMARS using Von Neumann linearized analysis to the one‐dimensional linearized shallow water equations. We extend these analyses to higher‐order methods by numerically solving the Fourier‐transformed equations. It is found that the pros and cons due to grid staggering choices diminish with high‐order schemes.
The linearized analysis is limited to modal, smooth solutions using simple numerical schemes, and cannot analyze solutions with discontinuities. To address this problem, this work presents a new idealized test of a discontinuous wave packet, a single Fourier mode modulated by a discontinuous square‐wave. The experiments include studies of well‐resolved and (near) grid‐scale wave profiles, as well as the representation of discontinuous features and the results are validated against the Von Neumann analysis. We find the higher‐order LMARS produces much less numerical noise than do inviscid unstaggered and especially staggered schemes while retaining accuracy for better‐resolved modes.
Hazelton, Andrew T., Lucas Harris, and Shian-Jiann Lin, April 2018: Evaluation of Tropical Cyclone Structure Forecasts in a High-Resolution Version of the Multiscale GFDL fvGFS Model. Weather and Forecasting, 33(2), DOI:10.1175/WAF-D-17-0140.1. Abstract
A nested version of the FV3 dynamical core with GFS physics (fvGFS) is capable of tropical cyclone (TC) prediction across multiple space and time scales, from subseasonal prediction to high-resolution structure and intensity forecasting. Here, a version of fvGFS with 2 km resolution covering most of the North Atlantic is evaluated for its ability to simulate TC track, intensity, and fine-scale structure. TC structure is evaluated through comparison of forecasts with 3-dimensional Doppler radar from P-3 flights by NOAA’s Hurricane Research Division (HRD), and structural metrics evaluated include the 2-km radius of maximum wind (RMW), slope of the RMW, depth of the TC vortex, and horizontal vortex decay rate.
7 TCs from the 2010-2016 seasons are evaluated, including 10 separate model runs and 38 individual flights. The model had some success in producing rapid intensification (RI) forecasts for Earl, Edouard, and Matthew. fvGFS successfully predicts RMW in the 25-50 km range, but tends to have a small bias at very large radii and a large bias at very small radii. The wind peak also tends to be somewhat too sharp, and the vortex depth occasionally has a high bias, especially for storms that are observed to be shallow. Composite radial wind shows that the boundary layer tends to be too deep, although the outflow structure aloft is relatively consistent with observations. These results highlight the utility of structural evaluation of TC forecasts, and also show the promise of fvGFS for forecasting TCs.
The 2017 Atlantic hurricane season had several high-impact tropical cyclones (TCs), including multiple cases of rapid intensification (RI). A high-resolution nested version of the GFDL fvGFS model (HifvGFS) was used to conduct hindcasts of all Atlantic TCs between August 7 and October 15.
HifvGFS showed promising track forecast performance, with similar error patterns and skill compared to the operational GFS and HWRF models. Some of the larger track forecast errors were associated with the erratic tracks of Jose and Lee. A case study of Maria found that although the track forecasts were generally skillful, a right-of-track bias was noted in some cases associated with initialization and prediction of ridging north of the storm.
The intensity forecasts showed large improvement over the GFS and global fvGFS models, but were somewhat less skillful than HWRF. The largest negative intensity forecast errors were associated with the RI of Irma, Lee, and Maria, while the largest positive errors were found with recurving cases that were generally weakening. The structure forecasts were also compared with observations, and HifvGFS was found to generally have wind radii larger than observations. Detailed examination of the forecasts of Hurricanes Harvey and Maria showed that HifvGFS was able to predict the structural evolution leading to RI in some cases, but was not as skillful with other RI cases. One case study of Maria suggested that inclusion of ocean coupling could significantly reduce the positive bias seen during and after recurvature.
Motivated by increasing demand in the community for intraseasonal predictions of weather extremes, predictive skill of tropical cyclogenesis is investigated in this study based on a global coupled model system. Limited intraseasonal cyclogenesis prediction skill with a high false alarm rate is found when averaged over about 600 tropical cyclones (TCs) over global oceans from 2003 to 2013, particularly over the North Atlantic (NA). Relatively skillful genesis predictions with more than one-week lead time are only evident for about 10 percent of the total TCs. Further analyses suggest that TCs with relatively higher genesis skill are closely associated with the Madden-Julian Oscillation (MJO) and tropical synoptic waves, with their geneses strongly phase-locked to the convectively active region of the MJO and low-level cyclonic vorticity associated with synoptic-scale waves. Moreover, higher cyclogenesis prediction skill is found for TCs that formed during the enhanced periods of strong MJO episodes than those during weak or suppressed MJO periods. All these results confirm the critical role of the MJO and tropical synoptic waves for intraseasonal prediction of TC activity.
Tropical cyclogenesis prediction skill in this coupled model is found to be closely associated with model predictability of several large-scale dynamical and thermo-dynamical fields. Particularly over the NA, higher predictability of low-level relative vorticity, mid-level humidity, and vertical zonal wind shear are evident along a tropical belt from the West Africa coast to Caribbean Seas, in accord with more predictable cyclogenesis over this region. Over the extratropical NA, large-scale variables exhibit less predictability due to influences of extratropical systems, leading to poor cyclogenesis predictive skill.
In this two-part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part I, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode – with prescribed sea surface temperatures (SSTs) and sea ice distribution – is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top-of-atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part II, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
In Part II of this two-part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part I. Part II provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.
Freychet, N, A Duchez, C-H Wu, C-A Chen, H-H Hsu, J Hirschi, A Forryan, B Sinha, A L New, T Graham, M B Andrews, C Tu, and Shian-Jiann Lin, February 2017: Variability of hydrological extreme events in East Asia and their dynamical control: a comparison between observations and two high-resolution global climate models. Climate Dynamics, 48(3-4), DOI:10.1007/s00382-016-3108-5. Abstract
This work investigates the variability of extreme weather events (drought spells, DS15, and daily heavy rainfall, PR99) over East Asia. It particularly focuses on the large scale atmospheric circulation associated with high levels of the occurrence of these extreme events. Two observational datasets (APHRODITE and PERSIANN) are compared with two high-resolution global climate models (HiRAM and HadGEM3-GC2) and an ensemble of other lower resolution climate models from CMIP5. We first evaluate the performance of the high resolution models. They both exhibit good skill in reproducing extreme events, especially when compared with CMIP5 results. Significant differences exist between the two observational datasets, highlighting the difficulty of having a clear estimate of extreme events. The link between the variability of the extremes and the large scale circulation is investigated, on monthly and interannual timescales, using composite and correlation analyses. Both extreme indices DS15 and PR99 are significantly linked to the low level wind intensity over East Asia, i.e. the monsoon circulation. It is also found that DS15 events are strongly linked to the surface temperature over the Siberian region and to the land-sea pressure contrast, while PR99 events are linked to the sea surface temperature anomalies over the West North Pacific. These results illustrate the importance of the monsoon circulation on extremes over East Asia. The dependencies on of the surface temperature over the continent and the sea surface temperature raise the question as to what extent they could affect the occurrence of extremes over tropical regions in future projections.
The Tropical Cyclones (TC) that form over the warm waters in the Gulf of Mexico region pose a major threat to the surrounding coastal communities. Skillful sub-seasonal prediction of TC activity is important for early preparedness and reducing the TC damage in this region. In this study, we evaluate the performance of a 25-km resolution Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) in simulating the modulation of the TC activity in the Gulf of Mexico and western Caribbean Sea by the Intraseasonal Oscillation (ISO) based on multi-year retrospective seasonal predictions. We demonstrate that the HiRAM faithfully captures the observed influence of ISO on TC activity over the region of interest, including the formation of tropical storms and (major) hurricanes, as well as the landfalling storms. This is likely because of the realistic representation of the large-scale anomalies associated with boreal summer ISO over Northeast Pacific in HiRAM, especially the enhanced (reduced) moisture throughout the troposphere during the convectively enhanced (suppressed) phase of ISO. The reasonable performance of HiRAM suggests its potential for the subseasonal prediction of regional TC risk.
This study explores the role of the stratosphere as a source of seasonal predictability of surface climate over Northern Hemisphere extra-tropics both in the observations and climate model predictions. A suite of numerical experiments, including climate simulations and retrospective forecasts, are set up to isolate the role of the stratosphere in seasonal predictive skill of extra-tropical near surface land temperature. We show that most of the lead-0 month spring predictive skill of land temperature over extra-tropics, particularly over northern Eurasia, stems from stratospheric initialization. We further reveal that this predictive skill of extra-tropical land temperature arises from skillful prediction of the Arctic Oscillation (AO). The dynamical connection between the stratosphere and troposphere is also demonstrated by the significant correlation between the stratospheric polar vortex and sea level pressure anomalies, as well as the migration of the stratospheric zonal wind anomalies to the lower troposphere.
The modon, a pair of counter-rotating vortices propelling one another along a straight line, is an idealization of some observed large- and small-scale atmospheric and oceanic processes (e.g., twin cyclones), providing a challenging nonlinear test for fluid-dynamics solvers (known as “dynamical cores”). We present an easy-to-setup test of colliding modons suitable for both shallow-water and three-dimensional dynamical cores on the sphere. Two pairs of idealized modons are configured to collide, exchange vortices, and depart in opposite directions, repeating indefinitely in the absence of ambient rotation. This test is applicable to both hydrostatic and nonhydrostatic dynamical cores and particularly challenging for refined grids on the sphere, regardless of solution methodology or vertical coordinate.
We applied this test to three popular dynamical cores, used by three different general circulation models: the spectral element core of the Community Atmosphere Model, the Geophysical Fluid Dynamics Laboratory (GFDL) spectral core, and the GFDL finite-volume cubed-sphere core, FV3. Tests with a locally-refined grid and nonhydrostatic dynamics were also performed with FV3. All cores tested were able to capture the propagation, collision, and exchange of the modons, albeit the rate at which the modon was diffused varied between the three cores and showed a strong dependence on the strength of hyper-diffusion.
An analytic Schmidt transformation is used to create locally-refined global model grids capable of efficient climate simulation with grid-cell-widths as small as 10 km in the GFDL HIRAM model. This method of grid stretching produces a grid which varies very gradually into the region of enhanced resolution without changing the topology of the model grid and does not require radical changes to the solver. AMIP integrations were carried out with two grids stretched to 10 km minimum grid-cell width: one centered over east Asia and the western Pacific warm pool, and the other over the continental United States. Robust improvements to orographic precipitation, the diurnal cycle of warm-season continental precipitation, and tropical cyclone maximum intensity were found in the region of enhanced resolution, compared to 25-km uniform-resolution HiRAM. The variations in grid size were not found to create apparent grid artifacts, and in some measures the global-mean climate improved in the stretched-grid simulations. In the enhanced-resolution regions, the number of tropical cyclones was reduced, but the fraction of storms reaching hurricane intensity increased, compared to a uniform-resolution simulation. This behavior was also found in a stretched-grid perpetual-September aquaplanet simulation with 12-km resolution over a part of the tropics. Furthermore, the stretched-grid aquaplanet simulation was also largely free of grid artifacts except for an artificial Walker-type circulation, and simulated an ITCZ in its unrefined region more resembling that of higher-resolution Aquaplanet simulations, implying that the unrefined region may also be improved in stretched-grid simulations. The improvements due to stretching are attributable to improved resolution as these stretched-grid simulations were sparingly tuned.
Skillful seasonal forecasting of tropical cyclone (TC; wind speed ≥17.5 m s−1) activity is challenging, even more so when the focus is on major hurricanes (wind speed ≥49.4 m s−1), the most intense hurricanes (Category 4–5; wind speed ≥58.1 m s−1), and landfalling TCs. Here we show that a 25-km resolution global coupled model (HiFLOR) developed at the Geophysical Fluid Dynamics Laboratory (GFDL) has improved skill in predicting the frequencies of major hurricanes and Category 4–5 hurricanes in the North Atlantic, and landfalling TCs over the United States and Caribbean Islands a few months in advance, relative to its 50-km resolution predecessor climate model (FLOR). HiFLOR also shows significant skill in predicting Category 4–5 hurricanes in the western North Pacific and eastern North Pacific, while both models show comparable skills in predicting basin-total and landfalling TC frequency in the basins. The improved skillful forecasts of basin-total TCs, major hurricanes, and Category 4–5 hurricane activity in the North Atlantic by HiFLOR are obtained mainly by improved representation of the TCs and their response to climate from the increased horizontal resolution, rather than improvements in large-scale parameters.
This study aims to assess whether, and the extent to which, an increase in atmospheric resolution in versions of the Geophysical Fluid Dynamics Laboratory (GFDL) High-Resolution Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) with 50 km and HiFLOR with 25 km improves the simulation of the El Niño Southern Oscillation-tropical cyclone (ENSO-TC) connections in the western North Pacific (WNP). HiFLOR simulates better ENSO-TC connections in the WNP including TC track density, genesis and landfall than FLOR in both long-term control experiments and sea surface temperature (SST)- and sea surface salinity (SSS)-restoring historical runs (1971-2012). Restoring experiments are performed with SSS and SST restored to observational estimates of climatological SSS and interannually-varying monthly SST. In the control experiments of HiFLOR, an improved simulation of the Walker circulation arising from more realistic SST and precipitation is largely responsible for its better performance in simulating ENSO-TC connections in the WNP. In the SST-restoring experiments of HiFLOR, more realistic Walker circulation and steering flow during El Niño/La Niña are responsible for the improved simulation of ENSO-TC connections in the WNP. The improved simulation of ENSO-TC connections with HiFLOR arises from a better representation of SST and better responses of environmental large-scale circulation to SST anomalies associated with El Niño/La Niña. A better representation of ENSO-TC connections in HiFLOR can benefit the seasonal forecasting of TC genesis, track and landfall, improve our understanding of the interannual variation of TC activity, and provide better projection of TC activity under climate change.
Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the inter-model spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, we use a developmental version of the next generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the CMIP5 model ensemble. We demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere/land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and our current inability to find a clear observational constraint that favors one version of our model over the others, the implications of this ability to engineer climate sensitivity needs to be considered when estimating the uncertainty in climate projections.
A new high-resolution Geophysical Fluid Dynamics Laboratory (GFDL) coupled model (HiFLOR) has been developed and used to investigate potential skill in simulation and prediction of tropical cyclone (TC) activity. HiFLOR comprises of high-resolution (~25-km mesh) atmosphere and land components and a more moderate-resolution (~100-km mesh) sea ice and ocean components. HiFLOR was developed from the Forecast Oriented Low Resolution Ocean model (FLOR) by decreasing the horizontal grid spacing of the atmospheric component from 50-km to 25-km, while leaving most of the sub-gridscale physical parameterizations unchanged. Compared with FLOR, HiFLOR yields a more realistic simulation of the structure, global distribution, and seasonal and interannual variations of TCs, and a comparable simulation of storm-induced cold wakes and TC-genesis modulation induced by the Madden Julian Oscillation (MJO). Moreover, HiFLOR is able to simulate and predict extremely intense TCs (categories 4 and 5) and their interannual variations, which represents the first time a global coupled model has been able to simulate such extremely intense TCs in a multi-century simulation, sea surface temperature restoring simulations, and retrospective seasonal predictions.
The hindcasts of the Geophysical Fluid Dynamics Laboratory (GFDL) High-Resolution Atmospheric Model (HiRAM), which skillfully predicted the interannual variability of Atlantic tropical cyclone (TC) frequency, were analyzed to investigate what key circulation systems a model must capture in order to skillfully predict TCs. The HiRAM reproduced the leading EOF mode (M1) of the interannual variability of the Atlantic Hadley circulation and its impacts on environmental conditions. M1 represents the variability of the ITCZ intensity and width, and the predictability of Atlantic TCs can be explained by the lag correlation between M1 and SST in preceding months. Although the ITCZ displacement was not well predicted by the HiRAM, it does not affect the prediction of the basin-wide hurricane count. The analyses suggest that the leading mode of the variability of the regional Hadley circulation can serve as a useful metric to evaluate the performance of global models in TC seasonal prediction.
While tropical cyclone (TC) prediction, in particular TC genesis, remains very challenging, accurate prediction of TCs is critical for timely preparedness and mitigation. Using a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the authors studied the predictability of two destructive landfall TCs, Hurricane Sandy in 2012 and Super Typhoon Haiyan in 2013. Results demonstrate that the geneses of these two TCs are highly predictable with the maximum prediction lead-time reaching 11 days. The “beyond weather time scale” predictability of tropical cyclogenesis is primarily attributed to the model’s skillful prediction of the intraseasonal Madden-Julian Oscillation (MJO) and the westward propagation of easterly waves. Meanwhile, the landfall location and time can be predicted one week ahead for Sandy’s U.S landfall, and two weeks ahead for Haiyan’s landing in the Philippines. The success in predicting Sandy and Haiyan, together with low false alarms, indicates the potential using the GFDL coupled model for operational extended-range predictions of TCs.
Based on a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the Madden-Julian Oscillation (MJO) prediction skill in boreal wintertime (November-April) is evaluated by analyzing 11 years (2003-2013) of hindcast experiments. The initial conditions are obtained by applying a simple nudging technique towards observations. Using the real-time multivariate MJO (RMM) index as a predictand, we demonstrated that the MJO prediction skill can reach out to 27 days before the anomaly correlation coefficient (ACC) decreases to 0.5. The MJO forecast skill also shows relatively larger contrasts between target strong and weak cases (32 vs 7 days) than that between initially strong and weak cases (29 vs 24 days). Meanwhile, the strong dependence on target phases is found, as opposed to the relative skill independence from different initial phases. The MJO prediction skill is also shown to be about 29 days during DYNAMO/CINDY (Dynamics of the MJO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011) field campaign period. This model’s potential predictability, the upper bound of prediction skill, extends out to 42 days, revealing a considerable unutilized predictability and a great potential for improving current MJO prediction.
This study examines two sets of high-resolution coupled model forecasts starting from no-tropical cyclone (TC) and correct-TC-statistics initial conditions to understand the role of TC events on climate prediction. While the model with no-TC initial conditions can quickly spin up TCs within a week, the initial conditions with a corrected TC distribution can produce more accurate forecast of sea surface temperature up to one and half months and maintain larger ocean heat content up to 6 months due to enhanced mixing from continuous interactions between initialized and forecasted TCs and the evolving ocean states. The TC-enhanced tropical ocean mixing strengthens the meridional heat transport in the Southern Hemisphere driven primarily by Southern Ocean surface Ekman fluxes but weakens the Northern Hemisphere poleward transport in this model. This study suggests a future plausible initialization procedure for seamless weather-climate prediction when individual convection-permitting cyclone initialization is incorporated into this TC-statistics-permitting framework.
Fan, Yalin, Shian-Jiann Lin, Stephen M Griffies, and Mark A Hemer, May 2014: Simulated Global Swell and Wind Sea Climate and Their responses to Anthropogenic Climate Change at the End of the 21st Century. Journal of Climate, 27(10), DOI:10.1175/JCLI-D-13-00198.1.
A two-way nested-grid version of the Geophysical Fluid Dynamics Laboratory High Resolution Atmosphere Model (HiRAM) has been developed which uses simple methods for providing nested-grid boundary conditions and mass-conserving nested-to-global communication. Nested-grid simulations over the Maritime Continent and over North America were performed, each at two different resolutions: a 110-km mean grid-cell-width refined by a factor of three, and a 50-km mean grid-cell-width refined by a factor of two. Nested grid simulations were compared against uniform-resolution simulations, and against reanalyses, to determine the effect of grid nesting on both the modeled global climate and on the simulation of small-scale features.
Orographically-forced precipitation was robustly found to be simulated with more detail and greater realism in a nested grid simulation compared with when only the coarse grids were simulated alone. Tropical precipitation biases were reduced in the Maritime continent region when a nested grid was introduced. Both results were robust to changes in the nested grid parameterization tunings. In North America, cold-season orographic precipitation was improved by nesting, but precipitation biases in the central and eastern United States were little changed. Improving the resolution through nesting also allowed for more intense rainfall events, greater Kelvin-wave activity, and stronger tropical cyclones. Nested grid boundary artifacts were more pronounced when a one-way, noninteractive nested grid was used.
When observations are assimilated into a high-resolution coupled model, a traditional scheme that preferably projects observations to correct large scale background tends to filter out small scale cyclones. Here we separately process the large scale background and small scale perturbations with low-resolution observations for reconstructing historical cyclone statistics in a cyclone-permitting model. We show that by maintaining the interactions between small scale perturbations and successively-corrected large scale background, a model can successfully retrieve the observed cyclone statistics that in return improve estimated ocean states. The improved ocean initial conditions together with the continuous interactions of cyclones and background flows are expected to reduce model forecast errors. Combined with convection-permitting cyclone initialization, the new high-resolution model initialization along with the progressively-advanced coupled models should contribute significantly to the ongoing research on seamless weather-climate predictions.
Retrospective seasonal predictions of tropical cyclones (TCs) in the three major ocean basins of the Northern Hemisphere are performed from 1990 to 2010 using the Geophysical Fluid Dynamics Laboratory High-Resolution Atmospheric Model at 25-km resolution. Atmospheric states are initialized for each forecast, with the sea surface temperature anomaly (SSTA) persisted from that at the starting time during the 5-month forecast period (July-November). Using a 5-member ensemble, it is shown that the storm counts of both tropical storm (TS) and hurricane categories are highly predictable in the North Atlantic basin during the 21-year period. The correlations between the 21-year observed and model predicted storm counts are 0.88 and 0.89 for hurricanes and TSs, respectively. The prediction in the eastern North Pacific is skillful, but it is not as outstanding as that in the North Atlantic. The persisted SSTA assumption appears to be less robust for the western North Pacific, contributing to less skillful predictions in that region. The relative skill in the prediction of storm counts is shown to be consistent with the quality of the predicted large-scale environment in the three major basins.
Finally, we show that intensity distribution of TCs can be captured well by our model if the central sea-level pressure were used as the threshold variable instead of the commonly used 10-meter wind speed. This demonstrated the feasibility of using the 25-km resolution HiRAM, a general circulation model designed initially for long-term climate simulations, to study the impacts of climate change on the intensity distribution of TCs.
Chen, Xi, N Andronova, B van Leer, Joyce Penner, J P Boyd, Christiane Jablonowski, and Shian-Jiann Lin, July 2013: A control-volume model of the compressible Euler equations with a vertical Lagrangian Coordinate. Monthly Weather Review, 141(7), DOI:10.1175/MWR-D-12-00129.1. Abstract
Accurate and stable numerical discretization of the equations for the non-hydrostatic atmosphere is required, for example, to resolve interactions between clouds and aerosols in the atmosphere. Here we present a modification of the hydrostatic control-volume approach for solving the non-hydrostatic Euler equations with a Lagrangian vertical coordinate. A scheme with low numerical diffusion is achieved by introducing a low Mach number approximate Riemann solver (LMARS) for atmospheric flows. LMARS is a flexible way to ensure stability for finite volume numerical schemes in both Eulerian and vertical Lagrangian configurations. This new approach is validated on test cases using a 2D (x-z) configuration.
Surface wind (U10) and significant wave height (Hs) response to global warming are investigated using a coupled atmosphere-wave model by perturbing the sea surface temperatures (SSTs) with anomalies generated by WGCM CMIP-3 coupled models that use the IPCC/AR4/A1B scenario late in the 21st century.
Several consistent changes were observed across all four realizations for the seasonal means: robust increase of U10 and Hs in the Southern Ocean for both the austral summer and winter due to the poleward shift of the jet stream; a dipole pattern of the U10 and Hs with increases in the northeast sector and decreases at the mid-latitude during the boreal winter in the North Atlantic due to the more frequent occurrence of the positive phases of NAO; and strong decrease of U10 and Hs at the tropical western Pacific Ocean during the austral summer, which might be caused by the joint effect of the weakening of the Walker circulation and the large hurricane frequency decrease in the South Pacific.
Changes of the 99th percentile U10 and Hs are twice as strong as changes in the seasonal means, and the maximum changes are mainly dominated by the changes in hurricanes. Robust strong decreases of U10 and Hs in the South Pacific are obtained due to the large hurricane frequency decrease, while the results in the Northern Hemisphere basins differ among the models. An additional sensitivity experiment suggests that the qualitative response of U10 and Hs is not affected by using SST anomalies only and maintaining the radiative forcing unchanged (using 1980 values) as in this study.
A nested-grid model is constructed using the Geophysical Fluid Dynamics Laboratory Finite-Volume dynamical core on the cubed sphere. The use of a global grid avoids the need for externally-imposed lateral boundary conditions, and the use of the same governing equations and discretization on the global and regional domains prevents inconsistencies that may arise when these differ between grids. A simple interpolated nested-grid boundary condition is used, and two-way updates use a finite-volume averaging method. Mass conservation is achieved in two-way nesting by simply not updating the mass field.
Despite the simplicity of the nesting methodology, the distortion of the large-scale flow by the nested grid is such that the increase in global error norms is a factor of two or less in shallow-water test cases. The effect of a nested grid in the tropics on the zonal means and eddy statistics of an idealized Held-Suarez climate integration is minor, and artifacts due to the nested grid are comparable to those at the edges of the cubed-sphere grid and decrease with increasing resolution. The baroclinic wave train in a Jablonowski-Williamson test case was preserved in a nested-grid simulation while fine-scale features were represented with greater detail in the nested-grid region. We also found that lee vortices could propagate out of the nested region and onto a coarse grid which by itself could not produce vortices. Finally, we discuss how concurrent integration of the nested and coarse grids can be significantly more efficient than when integrating the two grids sequentially.
Wang, X, Y Liu, Guoxiong Wu, Shian-Jiann Lin, and Qing Bao, January 2013: The Application of Flux-Form Semi-Lagrangian Transport Scheme in a Spectral Atmosphere Model. Advances in Atmospheric Sciences, 30(1), DOI:10.1007/s00376-012-2039-2. Abstract
A flux-form semi-Lagrangian transport scheme (FFSL) was implemented in a spectral atmospheric GCM developed and used at IAP/LASG. Idealized numerical experiments show that the scheme is good at shape preserving with less dissipation and dispersion, in comparison with other conventional schemes. Importantly, FFSL can automatically maintain the positive definition of the transported tracers, which was an underlying problem in the previous spectral composite method (SCM). To comprehensively investigate the impact of FFSL on GCM results, we conducted sensitive experiments. Three main improvements resulted: first, rainfall simulation in both distribution and intensity was notably improved, which led to an improvement in precipitation frequency. Second, the dry bias in the lower troposphere was significantly reduced compared with SCM simulations. Third, according to the Taylor diagram, the FFSL scheme yields simulations that are superior to those using the SCM: a higher correlation between model output and observation data was achieved with the FFSL scheme, especially for humidity in lower troposphere. However, the moist bias in the middle and upper troposphere was more pronounced with the FFSL scheme. This bias led to an over-simulation of precipitable water in comparison with reanalysis data. Possible explanations, as well as solutions, are discussed herein.
This study describes a 29-year (1981 to 2009) global ocean surface gravity wave simulation generated by a coupled atmosphere-wave model using NOAA/GFDL’s High Resolution Atmosphere Model (HIRAM) and the WAVEWATCH III surface wave model developed and used operationally at NOAA/NCEP. Extensive evaluation of monthly mean significant wave height (SWH) against in situ buoys, satellite altimeter measurements, and ERA-40 reanalysis show very good agreements in terms of magnitude, spatial distribution, and scatter. The comparisons with satellite altimeter measurements indicate that the SWH low bias in ERA-40 reanalysis has been improved in our model simulations. The model fields show strong response to the NAO in the North Atlantic and the SOI in the Pacific Ocean that are well connected with the atmospheric responses. For the NAO in winter, the strongest subpolar wave responses are found near the Northern Europe coast and the coast of Labrador rather than in the central Northern Atlantic where the wind response is strongest. Similarly, for the SOI in the Pacific Ocean, the wave responses are strongest in the northern Bering Sea and the Antarctic coast.
High resolution global climate models (GCM) have been increasingly utilized for simulations of the global number and distribution of tropical cyclones (TCs), and how they might change with changing climate. In contrast, there is a lack of published studies on the sensitivity of TC genesis to parameterized processes in these GCMs.The uncertainties in these formulations might be an important source of uncertainty in the future projections of TC statistics.
In this study, we investigate the sensitivity of the global number of TCs in present-day simulations using the Geophysical Fluid Dynamics Laboratory HIgh Resolution Atmospheric Model (GFDL HIRAM) to alterations in physical parameterizations. Two parameters are identified to be important in TC genesis frequency in this model. They are the horizontal cumulus mixing rate which controls the entrainment into convective cores within the convection parameterization, and the strength of the damping of the divergent component of the horizontal flow. The simulated global number of TCs exhibits non-intuitive response to incremental changes of both parameters. As the cumulus mixing rate increases, the model produces non-monotonic response in global TC frequency with an initial sharp increase and then decrease. However, storm mean intensity rises montonically with the mixing rate. As the strength of the divergence damping increases, the model produces a continuous increase of global number of TCs and hurricanes with little change in storm mean intensity. Mechanisms for explaining these non-intuitive responses are discussed.
A newly developed global model, the Geophysical Fluid Dynamics Laboratory (GFDL)
High-Resolution Atmospheric Model (HiRAM) which is designed for both weather predictions
and climate-change simulations, is used to predict the tropical cyclone activity at 25-km
resolution. Assuming the persistence of the sea surface temperature anomaly during the forecast
period, we show that the inter-annual variability of seasonal prediction for hurricane counts in
the North Atlantic basin is highly predictable during the past decade (2000-2010). A remarkable
correlation of 0.96 between the observed and model predicted hurricane counts is achieved. The
root mean square error of the predicted hurricane number is less than 1 per year after correcting
the model’s negative bias. The predictive skill of the model in the tropics is further supported by
the successful prediction of a Madden-Julian Oscillation event initialized 7-day in advance of its
onset.
The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol-cloud interactions, chemistry-climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical-system component of earth-system models and models for decadal prediction in the near-term future, for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model.
Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud-droplet activation by aerosols, sub-grid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with eco-system dynamics and hydrology.
Most basic circulation features in AM3 are simulated as realistically, or more so, than in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks and the intensity distributions of precipitation remain problematic, as in AM2.
The last two decades of the 20th century warm in CM3 by .32°C relative to 1881-1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of .56°C and .52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol cloud interactions, and its warming by late 20th century is somewhat less realistic than in CM2.1, which warmed .66°C but did not include aerosol cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud-aerosol interactions to limit greenhouse gas warming in a way that is consistent with observed global temperature changes.
This paper describes a forecasting configuration of the Geophysical Fluid Dynamics Laboratory (GFDL) High-resolution Atmospheric model (HiRAM). HiRAM represents an early attempt in unifying, within a global modeling framework, the capabilities of GFDL's low-resolution climate models for IPCC-type climate change assessments and high-resolution limited-area models for hurricane predictions.
In this study, the potential of HiRAM as a forecasting tool is investigated by applying the model to near-term and intraseasonal hindcasting of tropical cyclones (TCs) in the Atlantic basin from 2006 – 2009. Results demonstrate that HiRAM provides skillful near-term forecasts of TC track and intensity relative to their respective benchmarks from t = 48 hr through t = 144 hr. At the intraseasonal timescale, a simple HiRAM ensemble provides skillful forecasts of 21-day Atlantic basin TC activity at a 2-day lead time. It should be noted that the methodology used to produce these hindcasts is applicable in a real-time forecasting scenario.
While the initial experimental results appear promising, the HiRAM forecasting system requires various improvements in order to be useful in an operational setting. These modifications currently under development include a data assimilation system for forecast initialization, increased horizontal resolution to better resolve the vortex structure, 3-D ocean model coupling, and wave model coupling. An overview of these ongoing developments are provided, and the specifics of each will be described in subsequent papers.
A global atmospheric model with roughly 50 km horizontal grid spacing is used to simulate the interannual variability of tropical cyclones using observed sea surface temperatures (SSTs) as the lower boundary condition. The model's convective parameterization is based on a closure for shallow convection, with much of the deep convection allowed to occur on resolved scales. Four realizations of the period 1981–2005 are generated. The correlation of yearly Atlantic hurricane counts with observations is greater than 0.8 when the model is averaged over the four realizations, supporting the view that the random part of this annual Atlantic hurricane frequency (the part not predictable given the SSTs) is relatively small (< 2 hurricanes/yr). Correlations with observations are lower in the East, West and South Pacific (roughly 0.6, 0.5 and 0.3) and insignificant in the Indian ocean. The model trends in Northern Hemisphere basin-wide frequency are consistent with the observed trends in the IBTrACS database. The model generates an upward trend of hurricane frequency in the Atlantic and downward trends in the East and West Pacific over this time frame. The model produces a negative trend in the Southern Hemisphere that is larger than that in the IBTrACS.
The same model is used to simulate the response to the SST anomalies generated by coupled models in the CMIP3 archive, using the late 21st century in the A1B scenario. Results are presented for SST anomalies computed by averaging over 18 CMIP3 models and from individual realizations from three models. A modest reduction of global and Southern Hemisphere hurricane frequency is obtained in each case, but the results in individual Northern Hemisphere basins differ among the models. The vertical shear in the Atlantic Main Development Region (MDR) and the difference between the MDR SST and the tropical mean SST are well correlated with the model's Atlantic storm frequency, both for interannual variability and for the intermodel spread in global warming projections.
Law, R M., W Peters, C Aulagnier, D J Bergmann, Songmiao Fan, and Shian-Jiann Lin, et al., 2008: TransCom model simulations of hourly atmospheric CO2: Experimental overview and diurnal cycle results for 2002. Global Biogeochemical Cycles, 22, GB3009, DOI:10.1029/2007GB003050. Abstract
A
forward atmospheric transport modeling experiment has been coordinated by
the TransCom group to investigate synoptic and diurnal variations in CO2 .
Model simulations were run for biospheric, fossil, and air-sea exchange of
CO2
and for SF6
and radon for 2000–2003. Twenty-five models or model variants participated
in the comparison. Hourly concentration time series were submitted for 280
sites along with vertical profiles, fluxes, and meteorological variables at
100 sites. The submitted results have been analyzed for diurnal variations
and are compared with observed CO2 in 2002. Mean summer diurnal cycles vary widely in amplitude across models.
The choice of sampling location and model level account for part of the
spread suggesting that representation errors in these types of models are
potentially large. Despite the model spread, most models simulate the
relative variation in diurnal amplitude between sites reasonably well. The
modeled diurnal amplitude only shows a weak relationship with vertical
resolution across models; differences in near-surface transport simulation
appear to play a major role. Examples are also presented where there is
evidence that the models show useful skill in simulating seasonal and
synoptic changes in diurnal amplitude.
Patra, Prabir K., Songmiao Fan, and Shian-Jiann Lin, et al., December 2008: TransCom model simulations of hourly atmospheric CO2 : Analysis of synoptic-scale variations for the period 2002-2003. Global Biogeochemical Cycles, 22, GB4013, DOI:10.1029/2007GB003081. Abstract
The
ability to reliably estimate CO2
fluxes from current in situ atmospheric CO2
measurements and future satellite CO2
measurements is dependent on transport model performance at synoptic and
shorter timescales. The TransCom continuous experiment was designed to
evaluate the performance of forward transport model simulations at hourly,
daily, and synoptic timescales, and we focus on the latter two in this
paper. Twenty-five transport models or model variants submitted hourly time
series of nine predetermined tracers (seven for CO2 )
at 280 locations. We extracted synoptic-scale variability from daily
averaged CO2
time series using a digital filter and analyzed the results by comparing
them to atmospheric measurements at 35 locations. The correlations between
modeled and observed synoptic CO2
variabilities were almost always largest with zero time lag and
statistically significant for most models and most locations. Generally, the
model results using diurnally varying land fluxes were closer to the
observations compared to those obtained using monthly mean or daily average
fluxes, and winter was often better simulated than summer. Model results at
higher spatial resolution compared better with observations, mostly because
these models were able to sample closer to the measurement site location.
The amplitude and correlation of model-data variability is strongly model
and season dependent. Overall similarity in modeled synoptic CO2
variability suggests that the first-order transport mechanisms are fairly
well parameterized in the models, and no clear distinction was found between
the meteorological analyses in capturing the synoptic-scale dynamics.
Atlas, R, and Shian-Jiann Lin, et al., 2007: Improving hurricane prediction through innovative global modeling In Extending the Horizons: Advances in Computing, Optimization, and Decision Technologies, Springer, 1-14. Abstract
Current global and regional models incorporating both in situ and remotely
sensed observations have achieved a high degree of skill in forecasting the
movement of hurricanes. Nevertheless, significant improvements in the
prediction of hurricane landfall and intensification are still needed. To
meet these needs, research on new observing systems, data assimilation
techniques, and better models is being performed. These include the Hurricane
Weather Research and Forecasting regional model development by
NOAA, as well as the development of an advanced "seamless'' global
weather and climate model, as a collaborative project involving both
NOAA and NASA. This latter model, when completed, will be used to
improve short and extended range forecasts of hurricanes, as well as to determine
the relationship between global climate change and long-term
variations in hurricane frequency and intensity, more accurately than is
possible today. As a starting point for the seamless global weather and
climate model, the horizontal resolution of the previously developed finite
volume General Circulation Model has been increased to 1/12 degrees (approximately
9 km) in a series of successive steps. This was made possible by
advances in both computing and optimization technologies.
Putman, William M., and Shian-Jiann Lin, 2007: Finite-volume transport on various cubed-sphere grids. Journal of Computational Physics, 227(1), 55-78. Abstract PDF
The performance of a multidimensional finite-volume transport scheme is evaluated on the cubed-sphere geometry. Advection tests with prescribed winds are used to evaluate a variety of cubed-sphere projections and grid modifications including the gnomonic and conformal mappings, as well as two numerically generated grids by an elliptic solver and spring dynamics. We explore the impact of grid non-orthogonality on advection tests over the corner singularities of the cubed-sphere grids, using some variations of the transport scheme, including the piecewise parabolic method with alternative monotonicity constraints. The advection tests revealed comparable or better accuracy to those of the original latitudinal–longitudinal grid implementation. It is found that slight deviations from orthogonality on the modified cubed-sphere (quasi-orthogonal) grids do not negatively impact the accuracy. In fact, the more uniform version of the quasi-orthogonal cubed-sphere grids provided better overall accuracy than the most orthogonal (and therefore, much less uniform) conformal grid. It is also shown that a simple non-orthogonal extension to the transport equation enables the use of the highly non-orthogonal and computationally more efficient gnomonic grid with acceptable accuracy.
Collins, William D., Philip J Rasch, B A Boville, J J Hack, J R McCaa, D L W Briegleb, C M Bitz, Shian-Jiann Lin, and M Zhang, 2006: The formulation and atmospheric simulation of the Community Atmosphere Model Version 3 (CAM3). Journal of Climate, 19(11), DOI:10.1175/JCLI3760.1. Abstract
A new version of the Community Atmosphere Model (CAM) has been developed and released to the climate community. CAM Version 3 (CAM3) is an atmospheric general circulation model that includes the Community Land Model (CLM3), an optional slab ocean model, and a thermodynamic sea ice model. The dynamics and physics in CAM3 have been changed substantially compared to implementations in previous versions. CAM3 includes options for Eulerian spectral, semi-Lagrangian, and finite-volume formulations of the dynamical equations. It supports coupled simulations using either finite-volume or Eulerian dynamics through an explicit set of adjustable parameters governing the model time step, cloud parameterizations, and condensation processes. The model includes major modifications to the parameterizations of moist processes, radiation processes, and aerosols. These changes have improved several aspects of the simulated climate, including more realistic tropical tropopause temperatures, boreal winter land surface temperatures, surface insolation, and clear-sky surface radiation in polar regions. The variation of cloud radiative forcing during ENSO events exhibits much better agreement with satellite observations. Despite these improvements, several systematic biases reduce the fidelity of the simulations. These biases include underestimation of tropical variability, errors in tropical oceanic surface fluxes, underestimation of implied ocean heat transport in the Southern Hemisphere, excessive surface stress in the storm tracks, and offsets in the 500-mb height field and the Aleutian low.
The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved.
Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2° latitude × 2.5° longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1° in latitude and longitude, with meridional resolution equatorward of 30° becoming progressively finer, such that the meridional resolution is 1/3° at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments.
The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic.
Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/).
Manuscript received 8 December 2004, in final form 18 March 2005
Rasch, Philip J., D B Coleman, Natalie M. Mahowald, D L Williamson, Shian-Jiann Lin, B A Boville, and Peter G Hess, 2006: Characteristics of atmospheric transport using three numerical formulations for atmospheric dynamics in a single GCM framework. Journal of Climate, 19(11), DOI:10.1175/JCLI3763.1. Abstract
This study examines the sensitivity of a number of important archetypical tracer problems to the numerical method used to solve the equations of tracer transport and atmospheric dynamics. The tracers' scenarios were constructed to exercise the model for a variety of problems relevant to understanding and modeling the physical, dynamical, and chemical aspects of the climate system. The use of spectral, semi-Lagrangian, and finite volume (FV) numerical methods for the equations is explored. All subgrid-scale physical parameterizations were the same in all model simulations.
The model behavior with a few short simulations with passive tracers is explored, and with much longer simulations of radon, SF6, ozone, a tracer designed to mimic some aspects of a biospheric source/sink of CO2, and a suite of tracers designed around the conservation laws for thermodynamics and mass in the model.
Large differences were seen near the tropopause in the model, where the FV core shows a much reduced level of vertical and meridional mixing. There was also evidence that the subtropical subsidence regions are more isolated from Tropics and midlatitudes in the FV core than seen in the other model simulations. There are also big differences in the stratosphere, particularly for age of air in the stratosphere and ozone. A comparison with estimated age of air from CO2 and SF6 measurements in the stratosphere suggest that the FV core is behaving most realistically.
A neutral biosphere (NB) test case is used to explore issues of diurnal and seasonal rectification of a tracer with sources and sinks at the surface. The sources and sinks have a zero annual average, and the rectification is associated with temporal correlations between the sources and sinks, and transport. The test suggests that the rectification is strongly influenced by the resolved-scale dynamics (i.e., the dynamical core) and that the numerical formulation for dynamics and transport still plays a critical role in the distribution of NB-like species. Since the distribution of species driven by these processes have a strong influence on the interpretation of the “missing sink” for CO2 and the interpretation of climate change associated with anthropogenic forcing herein, these issues should not be neglected.
The spectral core showed the largest departures from the predicted nonlinear relationship required by the equations for thermodynamics and mass conservations. The FV and semi-Lagrangian dynamics (SLD) models both produced errors a factor of 2 lower. The SLD model shows a small but systematic bias in its ability to maintain this relationship that was not present in the FV simulation.
The results of the study indicate that for virtually all of these problems, the model numerics still have a large role in influencing the model solutions. It was frequently the case that the differences in solutions resulting from varying the numerics still exceed the differences in the simulations resulting from significant physical perturbations (like changes in greenhouse gas forcing). This does not mean that the response of the system to physical changes is not correct. When results are consistent using different numerical formulations for dynamics and transport it lends confidence to one's conclusions, but it does indicate that some caution is required in interpreting the results.
The results from this study favor use of the FV core for tracer transport and model dynamics. The FV core is, unlike the others, conservative, less diffusive (e.g., maintains strong gradients better), and maintains the nonlinear relationships among variables required by thermodynamic and mass conservation constraints more accurately.
Shen, B-W, R Atlas, O Reale, Shian-Jiann Lin, Tong Lee, J Chang, and J-D Chern, 2006: The 0.125 degree finite-volume general circulation model on the NASA Columbia supercomputer: Preliminary simulations of mesoscale vortices. Geophysical Research Letters, 33, L05801, DOI:10.1029/2005GL024594. Abstract
The NASA Columbia supercomputer was ranked second on the TOP500 List in November, 2004. Such a quantum jump in computing power provides unprecedented opportunities to conduct ultra-high resolution simulations with the finite-volume General Circulation Model (fvGCM). During 2004, the model was run in realtime experimentally at 0.25 degree resolution producing remarkable hurricane forecasts (Atlas et al., 2005). In 2005, the horizontal resolution was further doubled, which makes the fvGCM comparable to the first mesoscale resolving General Circulation Model at the Earth Simulator Center (Ohfuchi et al., 2004). Nine 5-day 0.125 degree simulations of three hurricanes in 2004 are presented first for model validation. Then it is shown how the model can simulate the formation of the Catalina eddies and Hawaiian lee vortices, which are generated by the interaction of the synoptic-scale flow with surface forcing, and have never been reproduced in a GCM before.
Shen, B-W, R Atlas, O Reale, Shian-Jiann Lin, J-D Chern, J Chang, C Henze, and J-L Li, 2006: Hurricane forecasts with a global mesoscale-resolving model: Preliminary results with Hurricane Katrina (2005). Geophysical Research Letters, 33, L13813, DOI:10.1029/2006GL026143. Abstract
It is known that General Circulation Models (GCMs) have insufficient resolution to accurately simulate hurricane near-eye structure and intensity. The increasing capabilities of high-end computers have changed this. The mesoscale-resolving finite-volume GCM (fvGCM) has been experimentally deployed on the NASA Columbia supercomputer, and its performance is evaluated in this study by choosing hurricane Katrina as an example. In late August 2005, Katrina underwent two stages of rapid intensification, and became the sixth most intense hurricane in the Atlantic. Six 5-day simulations of Katrina at both 0.25° and 0.125° show comparable track forecasts but the 0.125° runs provide much better intensity forecasts, producing the center pressure with errors of only ±12 hPa. In the runs examined in this study, the 0.125° simulates better near-eye wind distributions and a more realistic average intensification rate. To contribute to the ongoing research on the effects of disabling convection parameterization (CP), we present promising results by comparing 0.125° runs with disabled CPs against runs with enabled CPs.
Sud, Y C., D Mocko, and Shian-Jiann Lin, 2006: Performance of two cloud-radiation parameterization schemes in the finite volume general circulation model for anomalously wet May and June 2003 over the continental United States and Amazonia. Journal of Geophysical Research, 111, D06201, DOI:10.1029/2005JD006246. Abstract
An objective assessment of the impact of a new cloud scheme, called Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRAS) (together with its radiation modules), on the finite volume general circulation model (fvGCM) was made with a set of ensemble forecasts that invoke performance evaluation over both weather and climate timescales. The performance of McRAS (and its radiation modules) was compared with that of the National Center for Atmospheric Research Community Climate Model (NCAR CCM3) cloud scheme (with its NCAR physics radiation). We specifically chose the boreal summer months of May and June 2003, which were characterized by an anomalously wet eastern half of the continental United States as well as northern regions of Amazonia. The evaluation employed an ensemble of 70 daily 10-day forecasts covering the 61 days of the study period. Each forecast was started from the analyzed initial state of the atmosphere and spun-up soil moisture from the first-day forecasts with the model. Monthly statistics of these forecasts with up to 10-day lead time provided a robust estimate of the behavior of the simulated monthly rainfall anomalies. Patterns of simulated versus observed rainfall, 500-hPa heights, and top-of-the-atmosphere net radiation were recast into regional anomaly correlations. The correlations were compared among the simulations with each of the schemes. The results show that fvGCM with McRAS and its radiation package performed discernibly better than the original fvGCM with CCM3 cloud physics plus its radiation package. The McRAS cloud scheme also showed a reasonably positive response to the observed sea surface temperature on mean monthly rainfall fields at different time leads. This analysis represents a method for helpful systematic evaluation prior to selection of a new scheme in a global model.
Atlas, R, and Shian-Jiann Lin, et al., February 2005: Hurricane forecasting with the high-resolution NASA finite volume general circulation model. Geophysical Research Letters, 32, L03807, DOI:10.1029/2004GL021513. Abstract
A high-resolution finite volume general circulation model (fvGCM), resulting from a development effort of more than ten years, is now being run operationally at the NASA Goddard Space Flight Center and Ames Research Center. The model is based on a finite volume dynamical core with terrain-following Lagrangian control volume discretization and performs efficiently on massive parallel architectures. The computational efficiency allows simulations at a resolution of a quarter of a degree, which is double the resolution currently adopted by most global models in operational weather centers. Such fine global resolution brings us closer to overcoming a fundamental barrier in global atmospheric modeling for both weather and climate, because tropical cyclones can be more realistically represented. In this work, preliminary results are shown. Fifteen simulations of four Atlantic tropical cyclones in 2002 and 2004, chosen because of varied difficulties presented to numerical weather forecasting, are performed. The fvGCM produces very good forecasts of these tropical systems, adequately resolving problems like erratic track, abrupt recurvature, intense extratropical transition, multiple landfall and reintensification, and interaction among vortices.
Putman, William M., Shian-Jiann Lin, and B-W Shen, September 2005: Cross-Platform Performance of a Portable Communication Module and the NASA Finite Volume General Circulation Model. International Journal of High Performance Computing Applications, 19(3), DOI:10.1177/1094342005056101. Abstract
The National Aeronautics and Space Administration (NASA) finite-volume general circulation model (fvGCM) is a global atmospheric model, originally developed for long-term climate simulations. Recently, the NASA fvGCM has been applied in a variety of weather prediction applications, including hurricane and winter storm forecasts. Achieving efficient throughput on a variety of computational platforms is essential to meet the needs of the climate and weather prediction community. We have developed a scalable and portable climate/weather prediction system by applying a portable communication module within a fast numerical algorithm that exceeds the current community demands for computational performance on a variety of high performance computing platforms. The low-level communication module, Mod_Comm, simplifies interprocess communication within GCMs and provides an efficient means of communicating between decomposed global domains using a variety of single-threaded and multithreaded data communication paradigms (MPI-1, MPI-2, SHMEM, and MLP). Mod_Comm has been implemented within the NASA fvGCM and the Community Atmosphere Model (CAM) at the National Center for Atmospheric Research. It is shown that the optimal choice of data communication paradigm varies from system to system, and can have a significant impact on the overall model performance. Performance studies with the NASA fvGCM reveal substantial improvements in the computational performance when using this low-level communication module, throughput improvements of 40% or more have been observed on various platforms including the SGI Altix 3700, SGI Origin 3000, Compaq AlphaServerSC, IBM SP, and Cray.
Lin, Shian-Jiann, 2004: A "vertically Lagrangian" finite-volume dynamical core for global models. Monthly Weather Review, 132(10), 2293-2307. Abstract PDF
A finite-volume dynamical core with a terrain-following Lagrangian control-volume discretization is described. The vertically Lagrangian discretization reduces the dimensionality of the physical problem from three to two with the resulting dynamical system closely resembling that of the shallow water system. The 2D horizontal-to-Lagrangian-surface transport and dynamical processes are then discretized using the genuinely conservative flux-form semi-Lagrangian algorithm. Time marching is split-explicit, with large time steps for scalar transport, and small fractional steps for the Lagrangian dynamics, which permits the accurate propagation of fast waves. A mass, momentum, and total energy conserving algorithm is developed for remapping the state variables periodically from the floating Lagrangian control-volume to an Eulerian terrain-following coordinate for dealing with "physical parameterizations" and to prevent severe distortion of the Lagrangian surfaces. Deterministic baroclinic wave-growth tests and long-term integrations using the Held–Suarez forcing are presented. Impact of the monotonicity constraint is discussed.
Lin, Shian-Jiann, R Atlas, and K-S Yeh, 2004: Global Weather Prediction and High-End Computing at NASA. Computing in Science and Engineering, 6(1), 29-35. Abstract PDF
The authors demonstrate the current capabilities of NASA's finite-volume General Circulation Model in high-resolution global weather prediction and discuss its development path in the foreseeable future. This model is a prototype of a future NASA Earth-modeling system intended to unify development activities across various disciplines within NASA's Earth Science Enterprise.
Ma, J, and Shian-Jiann Lin, et al., October 2004: Interannual variability of stratospheric trace gases: The role of extratropical wave driving. Quarterly Journal of the Royal Meteorological Society, 130(602), DOI:10.1256/qj.04.28. Abstract
The interannual variability of methane and ozone from a 35-year middle atmosphere climate model simulation with no interannual variations in external forcing or chemistry is examined. The internal dynamics in the model produces large tracer interannual variability, particularly in polar regions. During winter and spring the interannual standard deviation in the polar lower-middle stratosphere is about 30% of the climatological mean for methane and 15% for ozone. Global-scale, coherent interannual variations in temperature, residual circulation, and tracers are correlated with variability in the extratropical wave forcing. Statistically significant positive correlations between wave driving and polar tracer tendencies, including column ozone, occur from autumn to spring in both hemispheres. These positive correlations imply that interannual variations in polar tracers are dominated by variations in the horizontal eddy transport and not by variations in residual mean descent rates.
Coy, L, I Stajner, A Da Silva, J Joiner, R B Rood, S Pawson, and Shian-Jiann Lin, 2003: High-frequency planetary waves in the Polar middle atmosphere as seen in a data assimilation system. Journal of the Atmospheric Sciences, 60(24), 2975-2992. Abstract PDF
The 4-day wave often dominates the large-scale wind, temperature, and constituent variability in the high-latitude Southern Hemisphere winter near the stratopause. This study examines the winter Southern Hemisphere vortex of 1998 using 4-times-daily output from a data assimilation system to focus on the polar 2-day, wavenumber-2 component of the 4-day wave. The data assimilation system products are from a test version of the finite volume data assimilation system (fvDAS) being developed at the Goddard Space Flight Center (GSFC) and include an ozone assimilation system. Results show that the polar 2-day wave in temperature and ozone dominates over other planetary-scale disturbances during July 1998 at 70°S. The period of the quasi-2-day wave is somewhat shorter than 2 days (about 1.7 days) during July 1998 with an average perturbation temperature amplitude for the month of over 2.5 K. The 2-day wave propagates more slowly than the zonal mean zonal wind, consistent with Rossby wave theory, and has Eliassen–Palm (EP) flux divergence regions associated with regions of negative horizontal potential vorticity gradients, as expected from linear instability theory. Results for the assimilation-produced ozone mixing ratio show that the 2-day wave represents a major source of ozone variation in this region. The ozone wave in the assimilation system is in good agreement with the wave seen in the Polar Ozone and Aerosol Measurement (POAM) ozone observations for the same time period. Some differences from linear instability theory are noted, as well as spectral peaks in the ozone field, not seen in the temperature field, that may be a consequence of advection.
Lin, Shian-Jiann, 2003: NASA's high-end atmospheric model for climate and weather predictions. Earth Observation Magazine, 12(2), 14-18.
Yeh, K-S, Shian-Jiann Lin, and R B Rood, September 2002: Applying Local Discretization Methods in the NASA Finite-Volume General Circulation Model. Computing in Science and Engineering, 4(5), 49-54. Abstract
The general circulation model, developed at the NASA Goddard Space Flight Center for climate simulations and other meteorological applications, emphasizes conservative and monotonic transport and achieves sufficient accuracy for the global consistency of climate processes.
Chang, Y, and Shian-Jiann Lin, et al., 2001: The Climate of the FVCCM-3 Model, NASA Technical Report Series on Global Modeling and Data Assimilation, Vol. 20, Greenbelt, MD: NASA/Goddard Space Flight Center, 124pp.
Ginoux, Paul, Mian Chin, I Tegen, J M Prospero, B Holben, O Dubovik, and Shian-Jiann Lin, 2001: Sources and distributions of dust aerosols simulated with the GOCART model. Journal of Geophysical Research, 106(D17), 20,255-20,273. Abstract PDF
The global distribution of dust aerosol is simulated with the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. In, this model all topographic lows with bare ground surface are assumed to have accumulated sediments which are potential dust sources. The uplifting of dust particles is expressed as a function of surface wind speed and wetness. The GOCART model is driven by the assimilated meteorological fields from the Goddard Earth Observing System Data Assimilation System (GEOS DAS) which facilitates direct comparison with observations. The model includes seven size classes of mineral dust ranging from 0.1-6 mum radius. The total annual emission is estimated to be between 1604 and 1960 Tg yr(-1) in a 5-year simulation. The model has been evaluated by comparing simulation results with ground-based measurements and satellite data. The evaluation has been performed by comparing surface concentrations, vertical distributions, deposition rates, optical thickness, and size distributions. The comparisons show that the model results generally agree with the observations without the necessity of invoking any contribution from anthropogenic disturbances to soils. However, the model overpredicts the transport of dust from the Asian sources to the North Pacific. This discrepancy is attributed to an overestimate of small particle emission from the Asian sources.
Rotman, D, and Shian-Jiann Lin, et al., January 2001: Global Modeling Initiative assessment model: Model description, integration, and testing of the transport shell. Journal of Geophysical Research, 106(D2), 1669-1691. Abstract
We describe the three-dimensional global stratospheric chemistry model developed under the NASA Global Modeling Initiative (GMI) to assess the possible environmental consequences from the emissions of a fleet of proposed high-speed civil transport aircraft. This model was developed through a unique collaboration of the members of the GMI team. Team members provided computational modules representing various physical and chemical processes, and analysis of simulation results through extensive comparison to observation. The team members' modules were integrated within a computational framework that allowed transportability and simulations on massively parallel computers. A unique aspect of this model framework is the ability to interchange and intercompare different submodules to assess the sensitivity of numerical algorithms and model assumptions to simulation results. In this paper, we discuss the important attributes of the GMI effort and describe the GMI model computational framework and the numerical modules representing physical and chemical processes. As an application of the concept, we illustrate an analysis of the impact of advection algorithms on the dispersion of a NOy-like source in the stratosphere which mimics that of a fleet of commercial supersonic transports (high-speed civil transport (HSCT)) flying between 17 and 20 km.
Xue, Ming, and Shian-Jiann Lin, March 2001: Numerical equivalence of advection in flux and advective forms and quadratically conservative high-order advection schemes. Monthly Weather Review, 129(3), 561-565. Abstract
In finite-difference representations of the conservation equations, the flux form of the advection terms is often
preferred to the advective form because of the immediate conservation of advected quantity. The scheme can
be designed to further conserve higher-order moments, for example, the kinetic energy, which is important to
the suppression of nonlinear instability. It is pointed out here that in most cases an advective form that is
numerically equivalent to the flux form can be found, for schemes based on centered difference. This is also
true for higher-order schemes and is not restricted to a particular grid type. An advection scheme that is fourthorder
accurate in space for uniform advective flows is proposed that conserves both first and second moments
of the advected variable in a nonhydrostatic framework. The role of the elastic correction term in addition to
the pure flux term in compressible nonhydrostatic models is also discussed.
Chin, Mian, and Shian-Jiann Lin, et al., October 2000: Atmospheric sulfur cycle simulated in the global model GOCART: Model description and global properties. Journal of Geophysical Research, 105(D20), 24,671-24,687. Abstract
The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model is used to simulate the atmospheric sulfur cycle. The model uses the assimilated meteorological data from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). Global sulfur budgets from a 6-year simulation for SO2, sulfate, dimethylsulfide (DMS), and methanesulfonic acid (MSA) are presented in this paper. In a normal year without major volcanic perturbations, about 20% of the sulfate precursor emission is from natural sources (biogenic and volcanic), and 80% is anthropogenic; the same sources contribute 33% and 67%, respectively, to the total sulfate burden. A sulfate production efficiency of 0.41–0.42 is estimated in the model, an efficiency which is defined as a ratio of the amount of sulfate produced to the total amount of SO2 emitted and produced in the atmosphere. This value indicates that less than half of the SO2 entering the atmosphere contributes to the sulfate production, the rest being removed by dry and wet depositions. In a simulation for 1990 we estimate a total sulfate production of 39 Tg S yr−1, with 36% and 64% from in-air and in-cloud oxidation, respectively, of SO2. We also demonstrate that major volcanic eruptions, such as the Mount Pinatubo eruption in 1991, can significantly change the sulfate formation pathways, distributions, abundance, and lifetime. Comparison with other models shows that the parameterizations for wet removal or wet production of sulfate are the most critical factors in determining the burdens of SO2 and sulfate. Therefore a priority for future research should be to reduce the large uncertainties associated with the wet physical and chemical processes.
Chin, Mian, and Shian-Jiann Lin, et al., April 1998: Processes controlling dimethylsulfide over the ocean: Case studies using a 3-D model driven by assimilated meteorological fields. Journal of Geophysical Research, 103(D7), 8341-8353. Abstract
This study investigates the processes that influence dimethylsulfide (DMS) concentrations over the ocean using a global three-dimensional chemistry and transport model (CTM). The model is driven by assimilated meteorological data from the Goddard Earth Observing System Data Assimilation System (GEOS-I DAS). Results from the model are compared with DMS measurements from two marine sites, a ship cruise, and an aircraft campaign. When observed seawater DMS concentrations and meteorological conditions are used, the model reproduces the observed daily and diurnal variations of DMS concentrations at a tropical Pacific station. The model also predicts the observed changes of DMS concentrations across the Atlantic, although it overestimates the DMS level by a factor of 2. The calculated vertical DMS concentrations off Tasmania are more than 4 times higher than the measured data. The model simulates day-to-day fluctuations and interannual variations observed at Amsterdam Island but underpredicts the magnitude of the variations. Sensitivities for DMS concentrations to the parameters used in DMS emission, oxidation, boundary layer mixing, and cloud convective transport are tested. The limitations of the current model in interpreting the observations are due to (1) the uncertainties in parameterization of DMS emission from the ocean, (2) the simplistic boundary layer mixing scheme, (3) the inaccurate spatial distribution and intensity of deep convective clouds in the GEOS-I DAS, and (4) the uncertainties in DMS oxidation rates.
Lin, Shian-Jiann, October 1998: Reply to comments by T. Janjić on ‘A finite-volume integration method for computing pressure gradient force in general vertical coordinates’ (July B, 1997, 123, 1749–1762). Quarterly Journal of the Royal Meteorological Society, 124(551), 2531-2533.
Lin, Shian-Jiann, 1998: The flux-form semi-Lagrangrian transport scheme and its applications in atmospheric models In MPI Workshop on Conservative Transport Schemes, Hamburg, Germany, Max Planck Institute for Meteorology, Report No. 265, 54-64.
Lin, Shian-Jiann, and R B Rood, October 1997: An explicit flux-form semi-lagrangian shallow-water model on the sphere. Quarterly Journal of the Royal Meteorological Society, 123(544), 2477-2498. Abstract
A global shallow-water model based on the flux-form semi-lagrangian scheme is described. the mass-conserving flux-form semi-Lagrangian scheme is a multidimensional semi-Lagrangian extension of the higher order Godunov-type finite-volume schemes (e.g., the piece-wise parabolic method). Unlike the piece-wise parabolic methodology, neither directional splitting nor a Riemann solver is involved. A reverse engineering procedure is introduced to achieve the goal of consistent transport of the absolute vorticity and the mass, and hence, the potential vorticity. Gravity waves are treated explicitly, in a manner that is consistent with the forward-in-time flux-form semi-Lagrangian transport scheme. Due to the finite-volume nature of the flux-form semi-lagrangian scheme and the application of the monotonicity constraint, which can be regarded as a subgrid-scale flux parametrization, essentially noise-free solutions are obtained without additional diffusion. Two selected shallow-water test cases proposed by Williamson et al. (1992) and a stratospheric vortex erosion simulation are presented. Discussions on the accuracy and computational efficiency are given based on the comparisons with a Eulerian spectral model and two advective-form semi-implicit semi-Lagrangian models.
Lin, Shian-Jiann, July 1997: A finite-volume integration method for computing pressure gradient force in general vertical coordinates. Quarterly Journal of the Royal Meteorological Society, 123(542), 1749-1762. Abstract
A finite-volume integration method is proposed for computing the pressure gradient force in general vertical coordinates. It is based on fundamental physical principles in the discrete physical space, rather than on the common approach of transforming analytically the pressure gradient terms in differential form from the vertical physical (i.e., height or pressure) coordinate to one following the bottom topography. The finite-volume discretization is compact, involving only the four vertices of the finite volume. The accuracy of the method is evaluated statically in a two-dimensional environment and dynamically in three-dimensional dynamical cores for general circulation models. The errors generated by the proposed method are demonstrated to be very low in these tests.
Lyster, P M., and Shian-Jiann Lin, et al., July 1997: Parallel Implementation of a Kalman Filter for Constituent Data Assimilation. Monthly Weather Review, 125(7), 1674-1686. Abstract
A Kalman filter for the assimilation of long-lived atmospheric chemical constituents was developed for two-dimensional transport models on isentropic surfaces over the globe. Since the Kalman filter calculates the error covariances of the estimated constituent field, there are five dimensions to this problem, x1, x2, and time, where x1 and x2 are the positions of two points on an isentropic surface. Only computers with large memory capacity and high floating point speed can handle problems of this magnitude.
This article describes an implementation of the Kalman filter for distributed-memory, message-passing parallel computers. To evolve the forecast error covariance matrix, an operator decomposition and a covariance decomposition were studied. The latter was found to be scalable and has the general property, of considerable practical advantage, that the dynamical model does not need to be parallelized. Tests of the Kalman filter code examined variance transport and observability properties. This code is being used currently to assimilate constituent data retrieved by limb sounders on the Upper Atmosphere Research Satellite.
Allen, D J., and Shian-Jiann Lin, et al., December 1996: Transport-induced interannual variability of carbon monoxide determined using a chemistry and transport model. Journal of Geophysical Research, 101(D22), 28,655-28,669. Abstract
Transport-induced interannual variability of carbon monoxide (CO) is studied during 1989–1993 using the Goddard chemistry and transport model (GCTM) driven by assimilated data. Seasonal changes in the latitudinal distribution of CO near the surface and at 500 hPa are captured by the model. The annual cycle of CO is reasonably well simulated at sites of widely varying character. Day to day fluctuations in CO due to synoptic waves are reproduced accurately at remote North Atlantic locations. By fixing the location and magnitude of chemical sources and sinks, the importance of transport-induced variability is investigated at CO-monitoring sites. Transport-induced variability can explain 1991–1993 decreases in CO at Mace Head, Ireland, and St. David's Head, Bermuda, as well as 1991–1993 increases in CO at Key Biscayne, Florida. Transport-induced variability does not explain decreases in CO at southern hemisphere locations. The model calculation explains 80–90% of interannual variability in seasonal CO residuals at Mace Head, St. David's Head, and Key Biscayne and at least 50% of variability in detrended seasonal residuals at Ascension Island and Guam. Upper tropospheric interannual variability during October is less than 8% in the GCTM. Exceptions occur off the western coast of South America, where mixing ratios are sensitive to the strength of an upper tropospheric high, and just north of Madagascar, where concentrations are influenced by the strength of offshore flow from Africa.
Lin, Shian-Jiann, and R B Rood, September 1996: Multidimensional Flux-Form Semi-Lagrangian Transport Schemes. Monthly Weather Review, 124(9), 2046-2070. Abstract
n algorithm for extending one-dimensional, forward-in-time, upstream-biased, flux-form transport schemes (e.g., the van Leer scheme and the piecewise parabolic method) to multidimensions is proposed. A method is also proposed to extend the resulting Eulerian multidimensional flux-form scheme to arbitrarily long time steps. Because of similarities to the semi-Lagrangian approach of extending time steps, the scheme is called flux-form semi-Lagrangian (FFSL). The FFSL scheme can be easily and efficiently implemented on the sphere. Idealized tests as well as realistic three-dimensional global transport simulations using winds from data assimilation systems are demonstrated. Stability is analyzed with a von Neuman approach as well as empirically on the 2D Cartesian plane. The resulting algorithm is conservative and upstream biased. In addition, it contains monotonicity constraints and conserves tracer correlations, therefore representing the physical characteristics of constituent transport.
Chao, W C., and Shian-Jiann Lin, May 1994: Tropical Intraseasonal Oscillation, Super Cloud Clusters, and Cumulus Convection Schemes. Journal of the Atmospheric Sciences, 51(10), 1282-1297. Abstract
A new framework for interpreting the origin of the tropical intraseasonal oscillation (TISO), which avoids the speed and scale selection problems in the previous theories, is proposed in this study. In this interpretation TISO is viewed as an oscillation driven by an eastward moving convective region. This convective region consists of one or more super cloud clusters originating in the Indian Ocean and terminating in mid-Pacific, and is then followed by another convective region arising in the Indian Ocean in a period of 40–50 days. Additionally, a formal analogy is pointed out between super cloud clusters and the middle-latitude baroclinic wave packets.
This study includes a simulation of TISO in a 2D model to support our interpretation. Experiments were conducted with four different convection schemes. The authors advocate that the successful simulation of TISO depends on the successful simulation of super cloud clusters, which in turn depends on the successful simulation of the life cycle of cloud clusters, which further in turn depends on the choice of cumulus convection scheme. What makes a cumulus convection scheme successful in simulating TISO is discussed.
Lin, Shian-Jiann, et al., July 1994: A Class of the van Leer-type Transport Schemes and Its Application to the Moisture Transport in a General Circulation Model. Monthly Weather Review, 122(7), 1575-1593. Abstract
A generalized form of the second-order van Leer transport scheme is derived. Several constraints to the implied subgrid linear distribution are discussed. A very simple positive-definite scheme can be derived directly from the generalized form. A monotonic version of the scheme is applied to the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) for the moisture transport calculations, replacing the original fourth-order center-differencing scheme. Comparisons with the original scheme are made in idealized tests as well as in a summer climate simulation using the full GLA GCM. A distinct advantage of the monotonic transport scheme is its ability to transport sharp gradients without producing spurious oscillations and unphysical negative mixing ratio. Within the context of low-resolution climate simulations, the aforementioned characteristics are demonstrated to be very beneficial in regions where cumulus convection is active. The model-produced precipitation pattern using the new transport scheme is more coherently organized both in time and in space, and correlates better with observations. The side effect of the filling algorithm used in conjunction with the original scheme is also discussed, in the context of idealized tests.
The major weakness of the proposed transport scheme with a local monotonic constraint is its substantial implicit diffusion at low resolution. Alternative constraints are discussed to counter this problem.
Lin, Shian-Jiann, and R T Pierrehumbert, February 1993: Is the Midlatitude Zonal Flow Absolutely Unstable?Journal of the Atmospheric Sciences, 50(4), 505-517. Abstract
An analysis is performed of the growth and propagation of unstable baroclinic wave packets in relatively realistic midlatitude zonal currents. The absolute growth rates are calculated, incorporating the effects of both Ekman friction and barotropic shear. It is found that these effects do not alter earlier conclusions (based on simpler models)that a finite easterly low-level wind is required for absolute instability in models with continuous shear. Ekman friction exacerbates the situation, shifting the absolute instability threshold from essentially zero surface wind to negative surface wind. While absolute instability of the midlatitude terrestrial jets thus seems unlikely, the conclusion stands that the atmosphere is at least near the boundary of absolute instability, especially under conditions prevailing in the oceanic storm tracks. In consequence, slow-moving short waves with growth rates below the maximum normal-mode growth rate typically contribute more to the amplification of wave packets as they cross a finite length baroclinic zone than the faster-growing but faster-growing most-unstable mode. For oceanic storm track conditions, a disturbance can amplify by a factor of several hundred during its time in a typical zonally localized baroclinic zone, even though the flow is not absolutely unstable. A measure of linear growth that is more revealing than normal-mode growth rate is proposed, which could be suitable for diagnostic studies. Consequences of the results for the nature of the storm tracks are discussed.
Lin, Shian-Jiann, September 1992: Contour Dynamics of Tornado-like Vortices. Journal of the Atmospheric Sciences, 49(18), 1745-1756. Abstract
Contour dynamics (CD) is applied to study the mechanism responsible for the breakup of an isolated tornado-like vortex into multiple vortices, the nonlinear interaction between a tornado and its parent storm, and the impact of tornadoes, which are subgrid features in any existing prediction model, on the more resolvable storm-scale motion.The genesis of the multiple vortex via the linear and eventually nonlinear barotropic/inertial instability of an observed tornado's mean tangential wind profile is studied in unprecedented detail using a high-resolution CD model. The most unstable eigenmodes obtained from the linear stability analyses were used as the initial perturbations to initialize the CD model. Despite that multiple vortices at the fully nonlinear stage bear little resemblance to the linear eigenmode structure, it is found that normal-mode barotropic/inertial instability can, indeed, trigger the formation of these vortices. In addition, the number of the secondary vortices identified in the fully nonlinear phase is found to be equal to the most unstable azimuthal wavenumber.The interaction between a tornado and its environment (the parent storm) is studied using highly idealized initial conditions. The formation of the hook-echo-like flow pattern by the outside air spiraling in is revealed in the high-resolution CD simulations. It is found that the rotation of the parent storm may be strongly influenced by the feedback from the tornado.
Lin, Shian-Jiann, and R T Pierrehumbert, 1988: Does Ekman friction suppress baroclinic instability?Journal of the Atmospheric Sciences, 45(20), 2920-2933. Abstract PDF
The effect of Ekman friction on baroclinic instability is reexamined in order to address questions raised by Farrell concerning the existence of normal mode instability in the atmosphere. As the degree of meridional confinement is central to the result, a linearized two-dimensional (latitude-height) quasi- geostrophic model is used to obviate the arbitrariness inherent in choosing a channel width in one-dimensional (vertical shear only) models. The two-dimensional eigenvalue problem was solved by pseudospectral method using rational Chebyshev expansions in both vertical and meridional directions. It is concluded that the instability can be eliminated only by the combination of strong Ekman friction with weak large-scale wind shear. Estimates of Ekman friction based on a realistic boundary-layer model indicate that such conditions can prevail over land when the boundary layer is neutrally stratified. For values of Ekman friction appropriate to the open ocean, friction can reduce the growth rate of the most unstable mode by at most a factor of two but cannot eliminate the instability.
By reducing the growth rate and shifting the most unstable mode to lower zonal wavenumbers, viscous effects make the heat and momentum fluxes of the most unstable mode deeper and less meridionally confined than in the inviscid case. Nevertheless, linear theory still underestimates the penetration depth of the momentum fluxes, as compared to observations and nonlinear numerical models.
Lin, Shian-Jiann, and R T Pierrehumbert, April 1987: Richardson criteria for stratified vortex motions under gravity - Comment. Physics of Fluids, 30(4), DOI:10.1063/1.866277.
