In this paper, U.S. landfalling tropical cyclone (TC) activity is projected for the late twenty-first century using a two-step dynamical downscaling framework. A regional atmospheric model, is run for 27 seasons, to generate tropical storm cases. Each storm case is -resimulated (up to 15 days) using the higher-resolution Geophysical Fluid Dynamics Laboratory hurricane model. Thirteen CMIP3 or CMIP5 climate change scenarios are explored. Robustness of projections is assessed using statistical significance tests and comparing changes across models. The proportion of TCs making U.S. landfall increases for the warming scenarios, due, in part, to an increases in the percentage of TC genesis near the U.S. coast and a change in climatological steering flows favoring more U.S. landfall events. The increases in U.S. landfall proportion leads to an increase in U.S. landfalling category 4–5 hurricane frequency, averaging about + 400% across the models; 10 of 13 models/ensembles project an increase (which is statistically significant in three of 13 models). We have only tentative confidence in this latter increase, which occurs despite a robust decrease in Atlantic basin category 1–5 hurricane frequency, no robust change in Atlantic basin category 4–5 and U.S. landfalling category 1–5 hurricane frequency, and no robust change in U.S. landfalling hurricane intensities. Rainfall rates, averaged within a 100-km radius of the storms, are projected to increase by about 18% for U.S. landfalling TCs. Important caveats to the study include low correlation (skill) for interannual variability of modeled vs. observed U.S. TC landfall frequency and model bias of excessive TC genesis near and east of the U.S. east coast in present-day simulations.
The GFDL hurricane modelling system, initiated in the 1970s, has progressed from a research tool to an operational system over four decades. This system is still in use today in research and operations, and its evolution will be briefly described. This study used an idealized version of the 2014 GFDL model to test its sensitivity across a wide range of three environmental factors that are often identified as key factors in tropical cyclone (TC) evolution: SST, atmospheric stability (upper air thermal anomalies), and vertical wind shear (westerly through easterly). A wide range of minimum central pressure intensities resulted (905 to 980hPa). The results confirm that a scenario (e.g., global warming) in which the upper troposphere warms relative to the surface will have less TC intensification than one with a uniform warming with height. TC rainfall is also investigated for the SST-stability parameter space. Rainfall increases for combinations of SST increase and increasing stability similar to global warming scenarios, consistent with climate change TC downscaling studies with the GFDL model. The forecast system’s sensitivity to vertical shear was also investigated. The idealized model simulations showed weak disturbances dissipating under strong easterly and westerly shear of 10 m s-1. A small bias for greater intensity under easterly sheared versus westerly sheared environments was found at lower values of SST. The impact of vertical shear on intensity was different when a strong vortex was used in the simulations. In this case none of the initial disturbances weakened, and most intensified to some extent.
Global projections of intense tropical cyclone activity are derived from the Geophysical Fluid Dynamics Laboratory (GFDL) HiRAM (50 km grid) atmospheric model and the GFDL Hurricane Model using a two-stage downscaling procedure. First, tropical cyclone genesis is simulated globally using the HiRAM atmospheric model. Each storm is then downscaled into the GFDL Hurricane Model, with horizontal grid-spacing near the storm of 6 km, and including ocean coupling (e.g., ‘cold wake’ generation). Simulations are performed using observed sea surface temperatures (SSTs) (1980-2008); for a “control run” with 20 repeating seasonal cycles; and for a late 21st century projection using an altered SST seasonal cycle obtained from a CMIP5/RCP4.5 multi-model ensemble. In general agreement with most previous studies, projections with this framework indicate fewer tropical cyclones globally in a warmer late-21st-century climate, but also an increase in average cyclone intensity, precipitation rates, and in the number and occurrence-days of very intense category 4-5 storms. While these changes are apparent in the globally averaged tropical cyclone statistics, they are not necessarily present in each individual basin. The inter-basin variation of changes in most of the tropical cyclone metrics we examined is directly correlated to the variation in magnitude of SST increases between the basins. Finally, the framework is shown capable of reproducing both the observed global distribution of outer storm size--albeit with a slight high bias--and its inter-basin variability. Projected median size is found to remain nearly constant globally, with increases in most basins offset by decreases in the Northwest Pacific.
In this extended abstract, we report on progress in two areas of research at GFDL relating to Indian Ocean regional climate and climate change. The first topic is an assessment of regional surface temperature trends in the Indian Ocean and surrounding region. Here we illustrate the use of a multi-model approach (CMIP3 or CMIP5 model ensembles) to assess whether an anthropogenic warming signal has emerged in the historical data, including identification of where the observed trends are consistent or not with current climate models. Trends that are consistent with All Forcing runs but inconsistent with Natural Forcing Only runs are ones which we can attribute, at least in part, to anthropogenic forcing.
A high-resolution regional atmospheric model is used to simulate present-day western North Pacific (WNP) tropical cyclone (TC) activity and investigate the projected changes for the late 21st century. Compared to observations, the model can realistically simulate many basic features of the WNP TC activity climatology, such as the TC genesis location, track, and lifetime. A number of spatial and temporal features of observed TC interannual variability are captured, although observed variations in basin-wide TC number are not. A relatively well-simulated feature is the contrast of years when the Asian summer monsoon trough extends eastward (retreats westward), more (fewer) TCs form within the southeastern quadrant of the WNP, and the corresponding TC activity is above (below) normal over most parts of the WNP east of 125°E. Future projections with the Coupled Model Intercomparison Project 3 (CMIP3) A1B scenario show a weak tendency for decreases in the number of WNP TCs, and of increases in the more intense TCs; these simulated changes are significant at the 80% level. The present-day simulation of intensity is limited to storms of intensity less than about 55 m s-1. There is also a weak (80% significance level) tendency for projected WNP TC activity to shift poleward under global warming. A regional-scale feature is a projected increase of the TC activity north of Taiwan, which would imply an increase in TCs making landfall in North China, the Korean Peninsula and parts of Japan. However, given the weak statistical significance found for the simulated changes, an assessment of the robustness of such regional-scale projections will require further study.
Twenty-first-century projections of Atlantic climate change are downscaled to explore the robustness of potential changes in hurricane activity. Multimodel ensembles using the phase 3 of the Coupled Model Intercomparison Project (CMIP3)/Special Report on Emissions Scenarios A1B (SRES A1B; late-twenty-first century) and phase 5 of the Coupled Model Intercomparison Project (CMIP5)/representative concentration pathway 4.5 (RCP4.5; early- and late-twenty-first century) scenarios are examined. Ten individual CMIP3 models are downscaled to assess the spread of results among the CMIP3 (but not the CMIP5) models. Downscaling simulations are compared for 18-km grid regional and 50-km grid global models. Storm cases from the regional model are further downscaled into the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model (9-km inner grid spacing, with ocean coupling) to simulate intense hurricanes at a finer resolution.
A significant reduction in tropical storm frequency is projected for the CMIP3 (−27%), CMIP5-early (−20%) and CMIP5-late (−23%) ensembles and for 5 of the 10 individual CMIP3 models. Lifetime maximum hurricane intensity increases significantly in the high-resolution experiments—by 4%–6% for CMIP3 and CMIP5 ensembles. A significant increase (+87%) in the frequency of very intense (categories 4 and 5) hurricanes (winds ≥ 59 m s−1) is projected using CMIP3, but smaller, only marginally significant increases are projected (+45% and +39%) for the CMIP5-early and CMIP5-late scenarios. Hurricane rainfall rates increase robustly for the CMIP3 and CMIP5 scenarios. For the late-twenty-first century, this increase amounts to +20% to +30% in the model hurricane’s inner core, with a smaller increase (~10%) for averaging radii of 200 km or larger. The fractional increase in precipitation at large radii (200–400 km) approximates that expected from environmental water vapor content scaling, while increases for the inner core exceed this level.
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.
Several recent models suggest that the frequency of Atlantic tropical cyclones could decrease as the climate warms. However, these models are unable to reproduce storms of category 3 or higher intensity. We explored the influence of future global warming on Atlantic hurricanes with a downscaling strategy by using an operational hurricane-prediction model that produces a realistic distribution of intense hurricane activity for present-day conditions. The model projects nearly a doubling of the frequency of category 4 and 5 storms by the end of the 21st century, despite a decrease in the overall frequency of tropical cyclones, when the downscaling is based on the ensemble mean of 18 global climate-change projections. The largest increase is projected to occur in the Western Atlantic, north of 20°N.
Atlantic tropical cyclone activity has trended upward in recent decades. The increase coincides with favorable changes in local sea surface temperature and other environmental indices, principally associated with vertical shear and the thermodynamic profile. The relative importance of these environmental factors has not been firmly established. A recent study using a high-resolution dynamical downscaling model has captured both the trend and interannual variations in Atlantic storm frequency with considerable fidelity. In the present work, this downscaling framework is used to assess the importance of the large-scale thermodynamic environment relative to other factors influencing Atlantic tropical storms.
Separate assessments are done for the recent multidecadal trend (1980–2006) and a model-projected global warming environment for the late 21st century. For the multidecadal trend, changes in the seasonal-mean thermodynamic environment (sea surface temperature and atmospheric temperature profile at fixed relative humidity) account for more than half of the observed increase in tropical cyclone frequency, with other seasonal-mean changes (including vertical shear) having a somewhat smaller combined effect. In contrast, the model’s projected reduction in Atlantic tropical cyclone activity in the warm climate scenario appears to be driven mostly by increased seasonal-mean vertical shear in the western Atlantic and Caribbean rather than by changes in the SST and thermodynamic profile.
Increasing sea surface temperatures in the tropical Atlantic Ocean and measures of Atlantic hurricane activity have been reported to be strongly correlated since at least 1950 (refs 1, 2, 3, 4, 5), raising concerns that future greenhouse-gas-induced warming6 could lead to pronounced increases in hurricane activity. Models that explicitly simulate hurricanes are needed to study the influence of warming ocean temperatures on Atlantic hurricane activity, complementing empirical approaches. Our regional climate model of the Atlantic basin reproduces the observed rise in hurricane counts between 1980 and 2006, along with much of the interannual variability, when forced with observed sea surface temperatures and atmospheric conditions7. Here we assess, in our model system7, the changes in large-scale climate that are projected to occur by the end of the twenty-first century by an ensemble of global climate models8, and find that Atlantic hurricane and tropical storm frequencies are reduced. At the same time, near-storm rainfall rates increase substantially. Our results do not support the notion of large increasing trends in either tropical storm or hurricane frequency driven by increases in atmospheric greenhouse-gas concentrations.
In
this study, a new modeling framework for simulating Atlantic hurricane
activity is introduced. The model is an 18-km-grid nonhydrostatic regional
model, run over observed specified SSTs and nudged toward observed
time-varying large-scale atmospheric conditions (Atlantic domain wavenumbers
0–2) derived from the National Centers for Environmental Prediction (NCEP)
reanalyses. Using this “perfect large-scale model” approach for 27 recent
August–October seasons (1980–2006), it is found that the model successfully
reproduces the observed multidecadal increase in numbers of Atlantic
hurricanes and several other tropical cyclone (TC) indices over this period.
The correlation of simulated versus observed hurricane activity by year
varies from 0.87 for basin-wide hurricane counts to 0.41 for U.S.
landfalling hurricanes. For tropical storm count, accumulated cyclone
energy, and TC power dissipation indices the correlation is 0.75, for major
hurricanes the correlation is 0.69, and for U.S. landfalling tropical
storms, the correlation is 0.57. The model occasionally simulates hurricanes
intensities of up to category 4 (942 mb) in terms of central pressure,
although the surface winds (< 47 m s-1 ) do not exceed category-2
intensity. On interannual time scales, the model reproduces the observed
ENSO-Atlantic hurricane covariation reasonably well. Some notable aspects of
the highly contrasting 2005 and 2006 seasons are well reproduced, although
the simulated activity during the 2006 core season was excessive. The
authors conclude that the model appears to be a useful tool for exploring
mechanisms of hurricane variability in the Atlantic (e.g., shear versus
potential intensity contributions). The model may be capable of making
useful simulations/projections of pre-1980 or twentieth-century Atlantic
hurricane activity. However, the reliability of these projections will
depend on obtaining reliable large-scale atmospheric and SST conditions from
sources external to the model.
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
for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented. The atmosphere model, known as AM2, includes a new gridpoint dynamical core, a prognostic cloud scheme, and a multispecies aerosol climatology, as well as components from previous models used at GFDL. The land model, known as LM2, includes soil sensible and latent heat storage, groundwater storage, and stomatal resistance. The performance of the coupled model AM2–LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations. Particular focus is given to the model's climatology and the characteristics of interannual variability related to E1 Niño– Southern Oscillation (ENSO).
One AM2–LM2 integration was performed according to the prescriptions of the second Atmospheric Model Intercomparison Project (AMIP II) and data were submitted to the Program for Climate Model Diagnosis and Intercomparison (PCMDI). Particular strengths of AM2–LM2, as judged by comparison to other models participating in AMIP II, include its circulation and distributions of precipitation. Prominent problems of AM2– LM2 include a cold bias to surface and tropospheric temperatures, weak tropical cyclone activity, and weak tropical intraseasonal activity associated with the Madden–Julian oscillation.
An ensemble of 10 AM2–LM2 integrations with observed SSTs for the second half of the twentieth century permits a statistically reliable assessment of the model's response to ENSO. In general, AM2–LM2 produces a realistic simulation of the anomalies in tropical precipitation and extratropical circulation that are associated with ENSO.
Vitart, Frederic, Jeffrey L Anderson, Joseph J Sirutis, and Robert E Tuleya, 2001: Sensitivity of tropical storms simulated by a general circulation model to changes in cumulus parameterization. Quarterly Journal of the Royal Meteorological Society, 127(571), 25-51. Abstract PDF
A number of recent studies have examined the statistics of tropical storms simulated by general circulation models (GCMs) forced by observed sea surface temperatures. Many GCMs have demonstrated an ability to simulate some aspects of the observed interannual variability of tropical storms, in particular, variability in storm frequency. This has led to nascent attempts to use GCMs as part of programs to produce operational seasonal forecasts of tropical-storm numbers.
In this study, the sensitivity of the statistics of GCM-simulated tropical storms to changes in the model's physical parameterization is examined. After preliminary results indicated that these statistics were most sensitive to details of the convective parameterization, GCM simulations with identical dynamical cores but different convective parameterizations were created. The parameterizations examined included moist convective adjustment, two variants of the Arakawa-Schubert scheme, and several variants of the relaxed Arakawa-Schubert (RAS) scheme; the impact of including a shallow-convection parameterization was also examined.
The simulated tropical -storm frequency, intensity, structure, and interannual variability were all found to exhibit significant sensitivities to changes in convective parameterization. A particularly large sensitivity was found when the RAS and Arakawa-Schubert parameterizations were modified to place restrictions on the production of deep convection.
Climatologies of the GCM tropical atmosphere and composites of tropical storms were examined to address the question of whether the tropical-storm statistics were directly impacted on by changes in convection associated with tropical storms, or if they were indirectly affected by parameterization-induced changes in the tropical mean atmosphere. A number of results point to the latter being the primary cause. A regional hurricane model , initialized with mean states from the GCM simulation climatologies, is used to further investigate this point. Particularly compelling is the fact that versions of the RAS scheme that produce significantly less realistic simulations of tropical storms nevertheless produce a much more realistic interannual variability of storms, apparently due to an improved tropical mean climate.
A careful analysis of the background convective available potential energy (CAPE) is used to suggest that this quantity is particularly relevant to the occurrence of tropical storms in the low-resolution GCMs, although this may not be the case with observations. If the tropical CAPE is too low, tropical storms in the low-resolution GCMs cannot form with realistic frequency.
Sirutis, Joseph J., 1996: Recent changes to the convective parameterization schemesin the GFDL spectral model In Research Activities in Atmospheric and Oceanic Modelling, CAS/JSC Working Group on Numerical Experimentation, Report No. 23 WMO/TD No. 734, World Meteorological Organization, 4.41-4.42.
Sirutis, Joseph J., and Anthony Rosati, 1996: The impact of cumulus convection parameterization in coupled air-sea models In 11th Conference on Numerical Weather Prediction, Boston, MA, American Meteorological Society, 348-350.
Miyakoda, Kikuro, Joseph J Sirutis, Anthony Rosati, C Tony Gordon, Richard G Gudgel, William F Stern, Jeffrey L Anderson, and A Navarra, 1995: Atmospheric parameterizations in coupled air-sea models used for forecasts of ENSO In Proceedings of the International Scientific Conference on the Tropical Ocean Global Atmosphere (TOGA) Programme, WCRP-91, WMO/TD No. 717, Geneva, Switzerland, World Meteorological Organization, 802-806. Abstract
In order to investigate the feasibility of seasonal forecasts, a prediction system is developed. Here the main theme is the study of atmospheric physics parameterization for coupled air-sea modeling. The oceanic GCM uses 1 degree global grid with a finer resolution in the equatorial belt. The atmospheric GCM has the spectral T30 representation, which includes all of the usual physics parameterizations. Using a first version of the model (Coupled Model I) and a set of appropriate initial conditions, the capability of El Niño and La Niña forecasting with a 13 month lead time was tested, resulting in successful forecasts of the 1982/83 and 1988/89 events (Rosati et al., 1995b). However, longer runs of this system have revealed a sizable systematic error in simulations with a tendency to cool most of the world ocean, particularly the western tropical Pacific, and also without an adequate annual cycle of the SST in the eastern tropical Pacific.
In order to improve some of these features, particularly the ENSO phenomena, various versions of the atmospheric parameterizations and mountain representation are incorporated into the atmospheric GCM, and the model simulations are examined. The experiments are divided into two steps: one is with the uncoupled atmospheric model, and the other is with the coupled model. In the first step, five year simulations are carried out with the observed SST prescribed, and the results are compared with observations, which enables one to make the critical validation of the model. The second step is to couple the atmospheric and oceanic models, and integrate them from a January 1982 initial condition for 7 years, and also for another initial condition, i.e., January, 1988 for 13 months.
Compared with the boundary forced simulation, the coupling process introduces more degree of freedom, with increase of the sensitivity as well as the complexity considerably. In particular, the El Niño simulation is sensitive to any change of physics. For this reason, the objective of the simulation is focused only on the equatorial Pacific process and secondly the Indian monsoon, as opposed to the overall improvement of the general circulation. In other words, the approach is close to that of mechanistic modeling with specific targets rather than that of a GCM with broader objectives. The research is proceeding in two directions. One is: investigating the model's sensitivity for El Niño and La Niña processes to variation in a coupling parameter. The second is: after a number of trial-and-error experiments on various combinations of the parameterizations, the second atmospheric model, i.e., Model II, is selected. It is shown that Coupled Model II performs substantially better in some aspects but worse in other aspects than Coupled Model I. The improvement is found in the SST: warming occurs not only over the equatorial Pacific but also over the whole globe. The SST increase is achieved by the strong effect of the cumulus convection. On the other hand, some deficiencies remain the same in both models, i.e., the large positive errors of the SST in the eastern oceans, the lack of an annual cycle of the SST in the eastern equatorial Pacific, and the failure in forecast of the second El Niño. In summary, the prediction of the Southern Oscillation has been achieved by the two models for a full first cycle but not for the second cycle .
Miyakoda, Kikuro, and Joseph J Sirutis, 1990: Subgrid scale physics in 1-month forecasts. Part II: Systematic error and blocking forecasts. Monthly Weather Review, 118(5), 1065-1081. Abstract PDF
The capability of blocking prediction is investigated with respect to four models of different subgrid scale parameterization packages, which were described in Part 1. In order to assess the capability, blocking indices are defined, and threat and bias scores are set up for the predicted blocking index against the observation. Applying this evaluation scheme to the dataset of one-month forecasts for eight January cases, we conduct a study on the performance of blocking simulation.
First, it is immediately disclosed that the systematic biases in this forecast set are overwhelmingly large, so that the blocking index has to be adjusted to this bias. One of the major issues, suggested by Tibaldi and Molteni, is whether the systematic bias is generated by the failure of blocking forecasts. Overall, this study supports this assertion, despite the different definitions of blocking. The study also reveals that the A-model is inferior to the other three models, such as the E-model, with regard to blocking forecasts. The reason for this is that the E-model, for example, which includes turbulence closure parameterization, appears to provide an adequate conversion of low-frequency eddy potential to kinetic energy, and thereby produces a more reasonable amount of standing eddies related to the persistent ridges. It is also pointed out that the blocking activity in the winter Northern Hemisphere is manifested by a distinct subpolar peak in the meridional distribution of standing eddy kinetic energy. The E-model tends to generate a well-defined peak of this energy distribution. All models are deficient in expanding the zonal mean westerlies to higher latitudes, particularly the A-model. In this connection, a hypothesis is postulated on a precondition for blocking: the upstream westerlies prior to the onset have to be displaced relatively at lower latitude. In the successful cases of blocking forecasts, the upstream westerlies at 40° - 60°N are relatively weaker than those in the unsuccessful cases.
Miyakoda, Kikuro, Joseph J Sirutis, Anthony Rosati, and J Derber, 1990: Experimental forecasts with an air-sea model: Preliminary results In Air-Sea Interaction in Tropical Western Pacific, Beijing, China, China Ocean Press, 417-432. Abstract
An air-sea model has been applied to the seasonal forecasting problem for a single case beginning 1 October 1979. The model consists of an atmospheric model and a global 1° x 1° resolution oceanic model, with a higher latitudinal resolution in the equatorial zone. The initial conditions are obtained by the 4-dimensional data assimilation system for the atmosphere and the ocean. The experiments reveal that strong air-sea interaction is evident, manifested in a close connection between the predicted sea temperature and the sea level pressure anomaly patterns. There is a certain degree of predictive skill up to 5 months for the ocean and beyond 9 months for the atmosphere. However, the systematic bias in the sea temperature prediction is pronounced.
Sirutis, Joseph J., and Kikuro Miyakoda, 1990: Subgrid scale physics in 1-month forecasts. Part I: Experiment with four parameterization packages. Monthly Weather Review, 118(5), 1043-1064. Abstract PDF
Four packages of subgrid scale (SGS) physics parameterization are tested by including them in a general circulation model and by applying the four models to 1-month forecasts. The four models are formulated by accumulatively increasing the elaboration and the sophistication of the physics. The first is the reference model (the A-physics); the second model (the E-physics) uses the Monin-Obukhov similarity theory for the fluxes of surface boundary layer, the turbulence closure scheme for the fluxes in the entire atmosphere, and subsurface soil heat conduction; the third model (the F-physics) replaces the cumulus parameterization by the Arakawa-Schubert method; and the fourth model (the FM-physics) enhances the SGS orography. One-month integrations are performed for eight January cases, with each case consisting of three different forecasts. Originally, the forecast performance was expected to be a stepwise improvement with the elaboration of the SGS physics from the A to the FM, but the forecast results do not show up in such a simple way. The impact of these processes on the 1-month integration is subtle and yet significant. The superiority of the F-model over the A- and the E-models is evident in the last 10 days of the 1-month forecasts, though the performance of the E-model is consistently good, in comparison with the other models, in terms of root-mean-square (rms) error of geopotential height. It is likely that 80% condensation criterion in the E (instead of 100%) is at least partly responsible for the forecast deterioration in the last 10 days, compared with the F. The FM-model gives the lowest rms error, but the predicted transient eddies are extremely low, probably due to the excessively enhanced orography. The simulated global precipitation patterns are presented for the different models, and the drawbacks are discussed. The F- and the FM-models produce spatially smooth distribution of tropical rainfall. The 30-day forecast performance appears to be more sensitive to the initial conditions, rather than the SGS physics. The systematic errors in all of the models are substantial in magnitude, though they vary with the SGS physics.
Miyakoda, Kikuro, and Joseph J Sirutis, 1989: A proposal of moist turbulence closure scheme, and the rationalization of Arakawa-Schubert cumulus parameterization. Meteorology and Atmospheric Physics, 40, 110-122. Abstract
Subgrid-scale parameterizations related to moist process are discussed. In the first half of the paper, a turbulence closure scheme, including the effect of condensation, is proposed. In this parameterization, the subgrid-scale transfer is limited within a single vertical layer of a model per each time step, and the specification of condensation is of yes-or-no type. Therefore, the scheme is suited for a mesoscale circulation model.
In the second half of this paper, the bounded derivative method of Kreiss (1980) is applied to the formulation of parameterizations. One example is the derivation of various hierarchical versions in turbulence closure schemes, such as Mellor and Yamada (1974). Another example is an interpretation of the key assumption in Arakawa-Schubert (1974) theory of cumulus convection, i.e., the equilibrium of "cloud-work function".
Sirutis, Joseph J., and Kikuro Miyakoda, 1989: Forecast experiments of the 1982-83 El Niño with a coupled air-sea model In Proceedings of the 14th Annual Climate Diagnostics Workshop, Springfield, VA, NTIS, 35-40.
This is the report of the 30-day forecast experiment conducted at GFDL. The first part is a summary of 8 January case studies, using a finite difference GCM without the anomalous boundary forcings of sea surface temperature (SST). The experiment reveals that the forecast skill of 10-day mean variables is marginal at the end of a month, but that the removal of systematic bias (climate drift) from the original forecasts raises the skill scores appreciably, producing useful one-month prognoses. However, the climate drift is alarmingly large; for example, the forecast error for the 500 mb geopotential height due to the drift is 64% of the total root mean square error. The second part of the paper discusses the forecasts incorporating the observed SST instead of the climatological SST. A series of forecasts was carried out for the most dramatic El Niño event of January 1983. In this study, forecasts were improved for the tropics by using the observed SST, whereas the impact for the extratropics was not beneficial. Four possible causes for the adverse effect of tropical SST were examined, i.e., the cumulus parameterization, the accuracy of SST, the initialization, and the tropical land surface condition. Preliminary investigations suggest that the forecast tropical divergence fields are quite different from those observed, in particular with respect to the components of large scale divergence associated with the 40-50 day oscillation. It is likely that the current initialization of the GFDL forecast system is deficient in treating this distinct tropical oscillation.
A series of one-month forecasts were carried out for eight January cases, using a particular prediction model and prescribing climatological sea-surface temperature as the boundary condition. Each forecast is a stochastic prediction that consists of three individual integrations. These forecasts start with observed initial conditions derived from datasets of three meteorological centers. The forecast skill was assessed with respect to time means of variables based on the ensemble average of three forecasts. The time of space filter is essential to suppress unpredictable components of atmospheric variabilities and thereby to make an attempt at extending the limit of predictability. The circulation patterns of the three individual integrations tend to be similar to each other on the one-month time scale, implying that forecasts for the 10 day (or 20 day) means are not fully stochastic.The overall results indicate that the 10-day mean height prognoses resemble observations very well in the first ten days, and then start to lose similarity to real states, and yet there is some recognizable skill in the last ten days of the month. The main interests in this study are the feasibility of one-month forecasts, the adequacy of initial conditions produced by a particular data assimilation, and the growth of stochastic uncertainty. An outstanding problem turns out to be a considerable degree of systematic error included in the prediction model, which is now known to be "climate drift". Forecast errors are largely due to the model's systematic bias. Thus, forecast skill scores are substantially raised if the final prognoses are adjusted for the model's known climatic drift.
Stern, William F., R T Pierrehumbert, Joseph J Sirutis, Jeff J Ploshay, and Kikuro Miyakoda, 1986: Recent developments in the GFDL extended-range forecasting system In Short- and Medium-Range Numerical Weather Prediction, Collection of papers presented at the WMO/IUGG NWP Symposium, World Meteorological Organization, 359-363. Abstract
An assessment is made of the areas of focus for improving extended-range forecasting. Two topics currently being researched involve the reduction of systematic error by improving a GCM's accuracy and the refinement of the transition between the data assimilation phase and the forecasting phase.
Subgrid-scale orographic parameterizations have been the subject of recent model improvement activities. Results are shown for an envelope orography with an N48L9 gridpoint model and using a mountain gravity wave drag scheme with an R42L18 spectral model. In both cases there is an encouraging reduction in the systematic errors.
Proper initialization of tropical features, i.e., 40-50 day waves, may be crucial for extended-range predictions in the extra-tropics as well as the tropics. Using a continuous data assimilation scheme the 40-50 day oscillations in the tropics appear to be well maintained from the assimilation to the forecast phase. However, the assimilation system underestimates precipitation and evaporation rates.
Miyakoda, Kikuro, Joseph J Sirutis, and Jeff J Ploshay, 1985: Monthly forecast experiment: preliminary report In Numerical Long-Range Forecast Evaluation Numerical Long-Range Forecasting Errors Monthly Forecasts, Washington, DC, National Academy Press, 292-296. Abstract
An experiment on monthly forecasts with eight winter cases was conducted by using a 1980 general circulation model that incorporates a set of subgrid-scale physics characterized by Mellor-Yamada turbulence closure (hierarchy level 2.5), the Monin-Obukhov parameterization for the layer next to the ground surface, Manabe's cumulus parameterization, and the soil heat conduction. The cases are for January from 1977 to 1983; they include the extraordinarily severe winter of 1977 and the most pronounced El Niño year of 1983. Graphs show correlation coefficients of 500-mb geopotential height anomalies (the deviation from climatology) and of the 1000-mb geopotential height anomalies between the predictions and observations for the Northern Hemispheric domain (90-25 degrees N). The study indicates that the 10- or 20- day height prognoses resemble the observations well in the first 10 days and then rapidly lose the similarity; yet there is some recognized skill, although marginal in the last 10 or 20 days of the month. The skill scores for the 1000-mb level are consistently better than those for the 500-mb level. This feature appears opposite to that for the daily weather forecasts and may suggest how forecast errors propagate in the vertical.
This is a progress report and follow-up of "Three cases of one-month GCM forecasts" (Caverly, et al., 1981). Each case includes an ensemble of three individual integrations, starting with three different initial conditions produced at GFDL, NMC, and ECMWF and prescribing the climatological sea surface temperature as the lower boundary condition. Monthly forecasts with the N48L9-F model and examples of verification statistics are presented. The experiment with four winter cases indicates that there is some skill in the mean height prognosis.
January 1977 was a month noted for its extraordinary weather over North America. The winter was dominated by two persistent large amplitude ridges positioned over the west coast of North America and the Icelandic region of the Atlantic Ocean. A very intense trough reached deep into the eastern United States and caused one of the coldest Januaries on record. One-month integrations of various GCMs were conducted in order to test their ability to simulate this blocking event. Reasonably high resolution finite difference and spectral models available at GFDL were used. Each GCM was integrated from three different analyses of the initial conditions. For some models, a fairly accurate forecast was obtained and considerable skill was recognized in the simulation of the 30-day evolution in terms of the 5-day or 10-day mean flow fields, including the period of record breaking coldness over the eastern United States. The main conclusion is that proper treatment of the subgrid-scale processes as well as sufficient spatial resolution are essential for the simulations of this phenomenon as an initial value problem. Weak zonal wind poleward of about 40 degrees N and upstream of the blocking ridge appears to be crucial for the successful simulation of the sustained blocking ridge.
The GATE analysis was repeated utilizing the full GATE data set in the delayed mode and a revised four-dimensional analysis procedure. The reulting maps were compared with maps of other authors. Based on the new analysis, macroscale circulation features for the tropical African continent and Atlantic Ocean region were calculated, and other characteristic phenomena of this area were investigated. The easterly waves, in particular, were studied with respect to their formation, propagation, associated condensation, and possible conversion to hurricanes. It was possible to trace nine distinct easterly waves throughout their entire life history, and the analyzed tracks of these easterly waves agreed quite well with the subjective analyses of Sadler and Oda (1978). The time sequences of precipitation over the GATE A/B-array obtained by the present analysis and by satellite estimates were compared with some success.
Miyakoda, Kikuro, and Joseph J Sirutis, 1977: Comparative intergrations of global models with various parameterized processes of subgrid-scale vertical transports: Description of the parameterizations. Beiträge zur Physik der Atmosphäre, 50, 445-487. Abstract
The effects of the parameterization of the vertical eddy transport on the general circulation were studied comparatively by including various schemes in a global finite difference model. Models with different combinations of parameterization schemes for the surface layer transfer, the planetary boundary layer processes and the cumulus convection were discussed. For the surface layer, two versions of the treatments were considered; they are Prandtl's aerodynamical method and the Monin-Obukhov version for constant-flux layer, which includes the effect related to the Richardson number. For the turbulent transfer processes in the rest of the PBL as well as the free atmosphere, the mixing length approach for neutral thermal stratification, the Mellor-Yamada's turbulence closure models, and the mixed layer method of Randall-Arakawa are included. For the ensemble cumulus convection, one scheme is the moist convective adjustment of Manabe et al. (1965) and the other is the scheme based on the recent theory of Arakawa et al. (1974).
The preliminary numerical results of these experiments have revealed that the turbulent closure model of a certain hierarchy level performed satisfactorily, and that the resulting vertical structure of tropical cumulus clouds and the horizontal rain distribution were different between the UCLA version of cumulus convection and the moist convective adjustment. The UCLA scheme of cumulus convection produced a deeper penetrative convection than the moist convective adjustment, and the distribution of rainfall relative to trough and ridge of tropical trade wind easterlies was also different between the two schemes.
Miyakoda, Kikuro, L Umscheid, D H Lee, Joseph J Sirutis, R Lusen, and F Pratte, 1976: The near-real-time, global, four-dimensional analysis experiment during the GATE period, Part I. Journal of the Atmospheric Sciences, 33(4), 561-591. Abstract PDF
Global upper air and surface data for the entire GATE period from 15 June to 24 September 1974, were collected by the Data Assimilation Branch of NMC and mailed to GFDL. After processing these data, a four-dimensional analysis technique was applied for the entire GATE period, using a global numerical model. For a selected period, several different versions of the data processing scheme were tested. The resulting analyses were compared with each other and with the objective analysis of NMC in Washington, DC, and ANMRC in Melbourne. Overall, the analyses for the extratropics were satisfactory for the Northern Hemisphere, and to a lesser extent, for the Southern Hemisphere, though flow patterns are somewhat excessively smoothed. The analyses for the tropics were not of the same quality as those for the erxtratropics, and yet they were much improved compared with those of several years ago. A noteworthy point is that tropical cyclones were successfully represented in several cases.