Coupled ocean and prescribed sea surface temperature (SST) experiments are performed to investigate the drivers of Northern Hemisphere (NH) midlatitude winter circulation and blocking changes in warmer climates. In coupled experiments, a historical simulation is compared to a simulation following an end of the twenty-first-century shared socioeconomic pathway (SSP5-8.5) emission scenario. The SSP5-8.5 simulation yields poleward-shifted jets and an enhanced stationary wave pattern compared to the historical simulation. In terms of blocking, a reduction is found across North America and over the Pacific Ocean with the suggestion of more blocking over parts of Eurasia. Separately, prescribed SST experiments are performed decomposing the SSP5-8.5 SST response into a uniform warming component plus a spatially dependent change in SST pattern. SSP5-8.5 changes in circulation are primarily driven by a uniform warming of SST. Uniform warming is also found to account for most of the SSP5-8.5 blocking reduction over North America and the Pacific Ocean, but not over Eurasia. El Niño–like changes to the SST pattern also yield less blocking over the Pacific and North America. However, adding the responses of uniform and pattern experiments yields a nonlinear overreduction of blocking compared to the SSP5-8.5 experiment. Regional analyses of block energetics suggest that much of the reductions in blocking in warming simulations are driven by decreased baroclinic conversion in some regions and enhanced dissipation from diabatic sources in others.
The diurnal cycle of precipitation and precipitation variances at different time scales are analyzed in this study based on multiple high-resolution 3-h precipitation datasets. The results are used to evaluate nine CMIP6 models and a series of GFDL-AM4.0 model simulations, with the goal of examining the impact of SST diurnal cycle, varying horizontal resolutions, and different microphysics schemes on these two precipitation features. It is found that although diurnal amplitudes are reasonably simulated, models generally generate too early diurnal peaks over land, with a diurnal phase peaking around noon instead of the observed late afternoon (or early evening) peak. As for precipitation variances, irregular subdaily fluctuations dominate the total variance, followed by variance of daily mean precipitation and variance associated with the mean diurnal cycle. While the spatial and zonal distributions of precipitation variances are generally captured by the models, significant biases are present in tropical regions, where large mean precipitation biases are observed. The comparisons based on AM4.0 model simulations demonstrate that the inclusion of ocean coupling, adoption of a new microphysics scheme, and increasing of horizontal resolution have limited impacts on these two simulated features, emphasizing the need for future investigation into these model deficiencies at the process level. Conducting routine examinations of these metrics would be a crucial first step toward better simulation of precipitation intermittence in future model development. Last, distinct differences in these two features are found among observational datasets, highlighting the urgent need for a detailed evaluation of precipitation observations, especially at subdaily time scales, as model evaluation heavily relies on high-quality observations.
Marine cloud brightening is a proposal to counteract global warming by increasing sea salt aerosol emissions. In theory, this increases the cloud droplet number concentration of subtropical marine stratocumulus decks, increasing cloud brightness and longevity. However, this theoretical progression remains uncertain in coupled climate models, especially the response of liquid water path and cloud fraction to aerosol seeding. We use the GFDL CM4 climate model to simulate marine cloud brightening following the published G4sea-salt protocol, in which sea salt aerosol emissions are uniformly increased over 30 S–30 N in addition to standard forcings from a SSP2-4.5 future warming scenario. The perturbed radiative and cloud responses are temporally stable though spatially heterogeneous, and direct scattering by the added sea salt predominates over changes to cloud reflectance. In fact, feedbacks in the coupled simulation lead to a net warming, rather than cooling, response by clouds.
We describe the model performance of a new global coupled climate model configuration, CM4-MG2. Beginning with the Geophysical Fluid Dynamics Laboratory's fourth-generation physical climate model (CM4.0), we incorporate a two-moment Morrison-Gettelman bulk stratiform microphysics scheme with prognostic precipitation (MG2), and a mineral dust and temperature-dependent cloud ice nucleation scheme. We then conduct and analyze a set of fully coupled atmosphere-ocean-land-sea ice simulations, following Coupled Model Intercomparison Project Phase 6 protocols. CM4-MG2 generally captures CM4.0's baseline simulation characteristics, but with several improvements, including better marine stratocumulus clouds off the west coasts of Africa and North and South America, a reduced bias toward “double” Intertropical Convergence Zones south of the equator, and a stronger Madden-Julian Oscillation (MJO). Some degraded features are also identified, including excessive Arctic sea ice extent and a stronger-than-observed El Nino-Southern Oscillation. Compared to CM4.0, the climate sensitivity is reduced by about 10% in CM4-MG2.
We describe the third version of the Geophysical Fluid Dynamics Laboratory cloud microphysics scheme (GFDL MP v3) implemented in the System for High-resolution prediction on Earth-to-Local Domains (SHiELD). Compared to the GFDL MP v2, the GFDL MP v3 is entirely reorganized, optimized, and modularized into functions. The particle size distribution (PSD) of all hydrometeor categories is redefined to better mimic observations, and the cloud droplet number concentration (CDNC) is calculated from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2) aerosol data. In addition, the GFDL MP has been redesigned so all processes use the redefined PSD to ensure overall consistency and easily permit the introduction of new PSDs and microphysical processes. A year's worth of global 13-km, 10-day weather forecasts were performed with the new GFDL MP. Compared to the GFDL MP v2, the GFDL MP v3 significantly improves SHiELD's predictions of geopotential height, air temperature, and specific humidity in the Troposphere, as well as the high, middle and total cloud fractions and the liquid water path. The predictions are improved even further by the use of reanalysis aerosol data to calculate CDNC, and also by using the more realistic PSD available in GFDL MP v3. However, the upgrade of the GFDL MP shows little impact on the precipitation prediction. Degradations caused by the new scheme are discussed and provide a guide for future GFDL MP development.
A two-moment Morrison-Gettelman bulk cloud microphysics with prognostic precipitation (MG2), together with a mineral dust and temperature-dependent ice nucleation scheme, have been implemented into the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4.0 (AM4.0). We refer to this configuration as AM4-MG2. This paper describes the configuration of AM4-MG2, evaluates its performance, and compares it with AM4.0. It is shown that the global simulations with AM4-MG2 compare favorably with observations and reanalyses. The model skill scores are close to AM4.0. Compared to AM4.0, improvements in AM4-MG2 include (a) better coastal marine stratocumulus and seasonal cycles, (b) more realistic ice fraction, and (c) dominant accretion over autoconversion. Sensitivity tests indicate that nucleation and sedimentation schemes have significant impacts on cloud liquid and ice water fields, but higher horizontal resolution (about 50 km instead of 100 km) does not.
Tebaldi, Claudia, Kevin Debeire, Veronika Eyring, Erich Fischer, John C Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B Tokarska, George C Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald A Meehl, Richard H Moss, Susanne E Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin R Dix, Silvio Gualdi, Huan Guo, and Jasmin G John, et al., March 2021: Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6. Earth System Dynamics, 12(1), DOI:10.5194/esd-12-253-2021253-293. Abstract
The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.
We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.
Simulation of coupled carbon‐climate requires representation of ocean carbon cycling, but the computational burden of simulating the dozens of prognostic tracers in state‐of‐the‐art biogeochemistry ecosystem models can be prohibitive. We describe a six‐tracer biogeochemistry module of steady‐state phytoplankton and zooplankton dynamics in Biogeochemistry with Light, Iron, Nutrients and Gas (BLING version 2) with particular emphasis on enhancements relative to the previous version and evaluate its implementation in Geophysical Fluid Dynamics Laboratory's (GFDL) fourth‐generation climate model (CM4.0) with ¼° ocean. Major geographical and vertical patterns in chlorophyll, phosphorus, alkalinity, inorganic and organic carbon, and oxygen are well represented. Major biases in BLINGv2 include overly intensified production in high‐productivity regions at the expense of productivity in the oligotrophic oceans, overly zonal structure in tropical phosphorus, and intensified hypoxia in the eastern ocean basins as is typical in climate models. Overall, while BLINGv2 structural limitations prevent sophisticated application to plankton physiology, ecology, or biodiversity, its ability to represent major organic, inorganic, and solubility pumps makes it suitable for many coupled carbon‐climate and biogeochemistry studies including eddy interactions in the ocean interior. We further overview the biogeochemistry and circulation mechanisms that shape carbon uptake over the historical period. As an initial analysis of model historical and idealized response, we show that CM4.0 takes up slightly more anthropogenic carbon than previous models in part due to enhanced ventilation in the absence of an eddy parameterization. The CM4.0 biogeochemistry response to CO2 doubling highlights a mix of large declines and moderate increases consistent with previous models.
Loeb, Norman G., Hailan Wang, Richard P Allan, Timothy Andrews, Kyle Armour, Jason N S Cole, J-L Dufresne, Piers M Forster, Andrew Gettelman, Huan Guo, T Mauritsen, Yi Ming, and David J Paynter, et al., March 2020: New Generation of Climate Models Track Recent Unprecedented Changes in Earth's Radiation Budget Observed by CERES. Geophysical Research Letters, 47(5), DOI:10.1029/2019GL086705. Abstract
We compare top‐of‐atmosphere (TOA) radiative fluxes observed by the Clouds and the Earth's Radiant Energy System (CERES) and simulated by seven general circulation models forced with observed sea‐surface temperature (SST) and sea‐ice boundary conditions. In response to increased SSTs along the equator and over the eastern Pacific (EP) following the so‐called global warming “hiatus” of the early 21st century, simulated TOA flux changes are remarkably similar to CERES. Both show outgoing shortwave and longwave TOA flux changes that largely cancel over the west and central tropical Pacific, and large reductions in shortwave flux for EP low‐cloud regions. A model's ability to represent changes in the relationship between global mean net TOA flux and surface temperature depends upon how well it represents shortwave flux changes in low‐cloud regions, with most showing too little sensitivity to EP SST changes, suggesting a “pattern effect” that may be too weak compared to observations.
Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Most dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of wind erosion threshold (Vthreshold) over dry and sparsely-vegetated surface. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land-atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and seasonal cycle of DOD are better captured over the dust belt (i.e. North Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycle as well as dust forecasting.
GFDL's new CM4.0 climate model has high transient and equilibrium climate sensitivities near the middle of the upper half of CMIP5 models. The CMIP5 models have been criticized for excessive sensitivity based on observations of present‐day warming and heat uptake and estimates of radiative forcing. An ensemble of historical simulations with CM4.0 produces warming and heat uptake that are consistent with these observations under forcing that is at the middle of the assessed distribution. Energy budget‐based methods for estimating sensitivities based on these quantities underestimate CM4.0's sensitivities when applied to its historical simulations. However, we argue using a simple attribution procedure that CM4.0's warming evolution indicates excessive transient sensitivity to greenhouse gases. This excessive sensitivity is offset prior to recent decades by excessive response to aerosol and land use changes.
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.
The clouds in southern hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of AM4, a model GFDL will utilize for CMIP6, the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low-levels (again by differing amounts), especially in the post-cold frontal (PCF) region, when compared to observations. Focusing on only the models, their differences in high and mid-level clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.
This study describes the performance of two Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric general circulation models (AGCMs) in simulating the climatologies of planetary boundary layer (PBL) parameters, with a particular focus on the diurnal cycles. The two models differ solely in the PBL parameterization: one uses a prescribed K-profile PBL (KPP) scheme with an entrainment parameterization, and the other employs a turbulence kinetic energy (TKE) scheme. The models are evaluated through the comparison to the reanalysis ensemble, which is generated from ERA-20C, ERA-Interim, NCEP-CFSR and NASA-MERRA, and the following systematic biases are identified. The models exhibit wide-spread cold biases in the high latitudes, and the biases are smaller when the KPP scheme is used. The diurnal cycle amplitudes are underestimated in most dry regions, and the model with the TKE scheme simulates larger amplitudes. For the near-surface winds, the models underestimate both the daily means and the diurnal amplitudes. The differences between the models are relatively small compared to the biases.
The role of the PBL schemes in simulating the PBL parameters is investigated through the analysis of vertical profiles. The Sahara, which is suitable for focusing on the role of vertical mixing in dry PBLs, is selected for a detailed analysis. It reveals that compared to the KPP scheme, the heat transport is weaker with the TKE scheme in both convective and stable PBLs due to weaker vertical mixing, resulting in larger diurnal amplitudes. Lack of non-local momentum transport from the nocturnal low-level jets to the surfaces appears to explain the underestimation of the near-surface winds in the models.
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.
Jing, X, K Suzuki, and Huan Guo, et al., November 2017: A Multimodel Study on Warm Precipitation Biases in Global Models Compared to Satellite Observations. Journal of Geophysical Research: Atmospheres, 122(21), DOI:10.1002/2017JD027310. Abstract
The cloud-to-precipitation transition process in warm clouds simulated by state-of-the-art global climate models (GCMs), including both traditional climate models and a high-resolution model, is evaluated against A-Train satellite observations. The models and satellite observations are compared in the form of the statistics obtained from combined analysis of multiple-satellite observables that probe signatures of the cloud-to-precipitation transition process. One common problem identified among these models is the too-frequent occurrence of warm precipitation. The precipitation is found to form when the cloud particle size and the liquid water path (LWP) are both much smaller than those in observations. The too-efficient formation of precipitation is found to be compensated for by errors of cloud microphysical properties, such as underestimated cloud particle size and LWP, to an extent that varies among the models. However, this does not completely cancel the precipitation formation bias. Robust errors are also found in the evolution of cloud microphysical properties from nonprecipitating to drizzling and then to raining clouds in some GCMs, implying unrealistic interaction between precipitation and cloud water. Nevertheless, auspicious information is found for future improvement of warm precipitation representations: the adoption of more realistic autoconversion scheme in the high-resolution model improves the triggering of precipitation, and the introduction of a sophisticated subgrid variability scheme in a traditional model improves the simulated precipitation frequency over subtropical eastern ocean. However, deterioration in other warm precipitation characteristics is also found accompanying these improvements, implying the multisource nature of warm precipitation biases in GCMs.
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.
CLUBB (Cloud Layers Unified by Binormals) is a higher-order closure (HOC) method with an assumed joint probability density function (PDF) for the subgrid variations in vertical velocity, temperature, and moisture. CLUBB has been implemented in the GFDL climate model AM3-CLUBB and successfully unifies the treatment of shallow convection, resolved clouds, and planetary boundary layer (PBL). In this study, we further explore the possibility for CLUBB to unify the deep convection in a new configuration referred as AM3-CLUBB+. AM3-CLUBB+ simulations with prescribed sea surface temperature are discussed. Cloud, radiation, and precipitation fields compare favorably with observations and reanalyses. AM3-CLUBB+ successfully captures the transition from stratocumulus to deep convection and the modulated response of liquid water path to aerosols. Simulations of tropical variability and the Madden-Julian oscillation (MJO) are also improved. Deficiencies include excessive tropical water vapor and insufficient ice clouds in the mid-latitudes.
Pan, Fang, X Huang, L Larrabee Strow, and Huan Guo, November 2015: Linear trends and closures of 10-year observations of AIRS stratospheric channels. Journal of Climate, 28(22), DOI:10.1175/JCLI-D-15-0418.1. Abstract
The AIRS (Atmospheric Infrared Sounder) Level-1b radiances have been shown to be well calibrated (~0.3K or higher) and have little secular drift (~4mK/year) since its operation started in September 2002. We study the linear trends of 10 years (2003-2012) of AIRS global-mean radiances in the CO2 ν2 band that are sensitive to emissions from the stratosphere (stratospheric channels). AIRS lower-stratospheric channels have a cooling trend of no more than 0.23K/decade while its middle-stratospheric channels consistently show a statistically significant cooling trend as large as 0.58K/decade. The 95% confidence interval for the trend is ~±0.20K/decade. Two sets of synthetic AIRS radiances are computed using the PCRTM (Principle Component-based Radiative Transfer Model), one based on a free-running GFDL AM3 model over the same period and one based on ERA-interim reanalysis. The GFDL AM3 simulations overestimate the cooling trends in the middle-upper-stratospheric channels while slightly underestimate in the lower-stratospheric channels. The synthetic radiances based on ERA-interim reanalysis, on the opposite, have statistically significant positive trends at virtually all stratospheric channels. This confirms the challenge to GCM modeling and reanalysis community for a better simulation or assimilation of the stratospheric climate. We show that the linear trends in AIRS radiances can be reproduced to a large extent by the spectral radiative kernel technique and the trends from the AIRS L2 temperature retrievals and from the change of CO2. This suggests a closure between AIRS L1 radiances and L2 retrievals and potential merit of AIRS data in the studies of stratosphere changes.
Ban-Weiss, G A., Ling Jin, Susanne E Bauer, R Bennartz, Xiaoping Liu, Kai Zhang, Yi Ming, Huan Guo, and J H Jiang, September 2014: Evaluating clouds, aerosols, and their interactions in three global climate models using satellite simulators and observations. Journal of Geophysical Research: Atmospheres, 119(18), DOI:10.1002/2014JD021722. Abstract
Accurately representing aerosol-cloud interactions in global climate models is challenging. As parameterizations evolve, it is important to evaluate their performance with appropriate use of observations. In this investigation we compare aerosols, clouds, and their interactions in three global climate models (GFDL-AM3, NCAR-CAM5, GISS-ModelE2) to MODIS satellite observations. Modeled cloud properties are diagnosed using a MODIS simulator. Cloud droplet number concentrations (N) are computed identically from satellite-simulated and MODIS-observed values of liquid cloud optical depth and droplet effective radius. We find that aerosol optical depth (τa) simulated by models is similar to observations in many regions around the globe. For N, AM3 and CAM5 capture the observed spatial pattern of higher values in coastal marine stratocumulus versus remote ocean regions, though modeled values in general are higher than observed. Aerosol-cloud interactions were computed as the sensitivity of ln(N) to ln(τa) for coastal marine liquid clouds near South Africa (SAF) and Southeast Asia (SEA) where τa varies in time. AM3 and CAM5 are more sensitive than observations, while the sensitivity for ModelE2 is statistically insignificant. This widely used sensitivity could be subject to misinterpretation due to the confounding influence of meteorology on both aerosols and clouds. A simple framework for assessing the sensitivity of ln(N) to ln(τa) at constant meteorology illustrates that observed sensitivity can change from positive to statistically insignificant when including the confounding influence of relative humidity. Satellite-simulated versus standard model values of N from CAM5 are compared in SAF; standard model values are significantly lower with a bias of 83 cm−3.
A unified turbulence and cloud parameterization based on multi-variate probability density functions (PDFs) has been incorporated into the GFDL atmospheric general circulation model AM3. This PDF-based parameterization not only predicts sub-grid variations in vertical velocity, temperature, and total water, which bridge sub-grid scale processes (such as aerosol activation and cloud microphysics) and grid-scale dynamic and thermodynamic fields, but also unifies the treatment of planetary boundary layer (PBL), shallow convection, and cloud macrophysics. This parameterization is the “Cloud Layers Unified By Binormals” (CLUBB) parameterization. With the incorporation of CLUBB in AM3, coupled with a two-moment cloud microphysical scheme, AM3-CLUBB allows for a more physically-based and self-consistent treatment of aerosol activation, cloud micro- and macro-physics, PBL, and shallow convection.
The configuration and performance of AM3-CLUBB are described. Cloud and radiation fields, as well as most basic climate features, are modeled realistically. Relative to AM3, AM3-CLUBB improves the simulation of coastal stratocumulus, a longstanding deficiency in GFDL models, and their seasonal cycle, especially at higher horizontal resolution, but global skill scores deteriorate slightly. Through sensitivity experiments, we show that (1) the two-moment cloud microphysics helps relieve the deficiency of coastal stratocumulus; (2) using the CLUBB sub-grid cloud water variability in the cloud microphysics has a considerable positive impact on global cloudiness; and (3) the impact of adjusting CLUBB parameters is to improve the overall agreement between model and observations.
Successful simulation of aerosol indirect effects in climate models requires parameterizations that capture the full range of cloud-aerosol interactions, including positive and negative liquid water path (LWP) responses to increasing aerosol concentrations, as suggested by large eddy simulations (LESs). A parameterization based on multi-variate probability density functions with dynamics (MVD PDFs) has been incorporated into the single-column version of GFDL AM3, extended to treat aerosol activation, and coupled with a two-moment microphysics scheme. We use it to explore cloud-aerosol interactions. In agreement with LESs, our single-column simulations produce both positive and negative LWP responses to increasing aerosol concentrations, depending on precipitation and free atmosphere relative humidity. We have conducted sensitivity tests to vertical resolution and droplet sedimentation parameterization. The dependence of sedimentation on cloud droplet size is essential to capture the full LWP responses to aerosols. Further analyses reveal that the MVD PDFs are able to represent changes in buoyancy profiles induced by sedimentation as well as enhanced entrainment efficiency with aerosols comparable to LESs.
Guo, Huan, Jean-Christophe Golaz, Leo J Donner, D P Schanen, and B M Griffin, October 2010: Multi-variate probability density functions with dynamics for cloud droplet activation in large-scale models: Single column tests. Geoscientific Model Development, 3(2), DOI:10.5194/gmd-3-475-2010. Abstract
Successful simulation of cloud-aerosol interactions (indirect aerosol effects) in climate models requires relating grid-scale aerosol, dynamic, and thermodynamic fields to small-scale processes like aerosol activation. A turbulence and cloud parameterization, based on multi-variate probability density functions of sub-grid vertical velocity, temperature, and moisture, has been extended to treat aerosol activation. Multi-variate probability density functions with dynamics (MVD PDFs) offer a solution to the problem of the gap between the resolution of climate models and the scales relevant for aerosol activation and a means to overcome the limitations of diagnostic estimates of cloud droplet number concentration based only on aerosol concentration.
Incorporated into the single-column version of GFDL AM3, the MVD PDFs successfully simulate cloud properties including precipitation for cumulus, stratocumulus, and cumulus-under-stratocumulus. The extension to treat aerosol activation predicts droplet number concentrations in good agreement with large eddy simulations (LES). The droplet number concentrations from the MVD PDFs match LES results more closely than diagnostic relationships between aerosol concentration and droplet concentration.
In the single-column model simulations, as aerosol concentration increases, droplet concentration increases, precipitation decreases, but liquid water path can increase or decrease.
Guo, Huan, Joyce Penner, Michael Herzog, and Shang-Ping Xie, 2007: Investigation of the first and second aerosol indirect effects using data from the May 2003 Intensive Operational Period at the Southern Great Plains. Journal of Geophysical Research, 112, D15206, DOI:10.1029/2006JD007173. Abstract
The Active Tracer High-Resolution Atmospheric Model is used to examine the aerosol indirect effect (AIE) for a spring continental stratus cloud on the basis of data collected during the 17 May 2003 Aerosol Intensive Operation Period (AIOP) at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains site. Model results for our base case, which uses observed aerosol concentrations, agree reasonably well with the available observations, giving confidence that the basic model is reasonable. Sensitivity tests are performed to explore the response of the clouds to changes in the aerosol number concentration and surface fluxes. During the major part of the simulation, from 0630 through 1400 local standard time (LST), an increase in the aerosol number concentration (Na ) results in a decrease of the mean cloud droplet size and an increase of the cloud liquid water path (LWP) until aerosol number concentration levels reach 1200 cm-3. Further increases in aerosol concentration do not increase the liquid water path because the depletion of cloud water by precipitation is negligible above this number concentration. After 1400 LST, the liquid water path decreases when aerosols increase as long as N a < 600 cm-3 and remains unchanged for higher aerosol concentrations. The decrease of LWP is associated with the evaporative cooling below cloud base which leads to more condensation of water vapor, a result that is consistent with afternoon satellite observations of the response of continental clouds to increases in droplet concentrations. A sensitivity test with a stronger surface latent flux increases both the cloud geometrical thickness and cloud water content. On the other hand, a sensitivity test with a stronger surface sensible heat flux leads to a higher cloud base and a shallower and drier cloud. The response of the cloud geometrical thickness to changes in surface sensible heat flux dominates that of the cloud water content. The cloud fraction is also reduced at the end of the simulation time period. Because the surface heat fluxes will likely change when aerosol and droplet number concentrations change, these sensitivity tests show that a fully coupled simulation with a land surface model will be needed to fully assess the response of the cloud to changing aerosol concentrations. Nevertheless, since the thermodynamic boundary layer profiles do not change significantly when aerosol concentrations are changed, our results for changing aerosol concentrations are qualitatively correct.
Guo, Huan, Joyce Penner, Michael Herzog, and Hanna Pawlowska, January 2007: Examination of the aerosol indirect effect under contrasting environments during the ACE-2 experiment. Atmospheric Chemistry and Physics, 7(2), DOI:10.5194/acp-7-535-2007. Abstract
The Active Tracer High-resolution Atmospheric Model (ATHAM) has been adopted to examine the aerosol indirect effect in contrasting clean and polluted cloudy boundary layers during the Second Aerosol Characterization Experiment (ACE-2). Model results are in good agreement with available in-situ observations, which provides confidence in the results of ATHAM.
Sensitivity tests have been conducted to examine the response of the cloud fraction (CF), cloud liquid water path (LWP), and cloud optical depth (COD) to changes in aerosols in the clean and polluted cases. It is shown for two cases that CF and LWP would decrease or remain nearly constant with an increase in aerosols, a result which shows that the second aerosol indirect effect is positive or negligibly small in these cases. Further investigation indicates that the background meteorological conditions play a critical role in the response of CF and LWP to aerosols. When large-scale subsidence is weak as in the clean case, the dry overlying air above the cloud is more efficiently entrained into the cloud, and in so doing, removes cloud water more efficiently, and results in lower CF and LWP when aerosol burden increases. However, when the large-scale subsidence is strong as in the polluted case, the growth of the cloud top is suppressed and the entrainment drying makes no significant difference when aerosol burden increases. Therefore, the CF and LWP remain nearly constant.
In both the clean and polluted cases, the COD tends to increase with aerosols, and the total aerosol indirect effect (AIE) is negative even when the CF and LWP decrease with an increase in aerosols. Therefore, the first AIE dominates the response of the cloud to aerosols.
Bates, T S., T L Anderson, T Baynard, T Bond, Olivier Boucher, Gregory R Carmichael, C Erlick, Huan Guo, Larry W Horowitz, S Howell, S Kulkarni, H Maring, A McComiskey, Ann M Middlebrook, K Noone, C D O'Dowd, J Ogren, Joyce Penner, P K Quinn, A R Ravishankara, D L Savoie, Krishna M Achuta Rao, Y Shinozuka, Y Tang, R J Weber, and Y Wu, 2006: Aerosol direct radiative effects over the northwest Atlantic, northwest Pacific, and North Indian Oceans: estimates based on in-situ chemical and optical measurements and chemical transport modeling. Atmospheric Chemistry and Physics, 6(6), 1657-1732. Abstract PDF
The largest uncertainty in the radiative forcing of climate change over the industrial era is that due to aerosols, a substantial fraction of which is the uncertainty associated with scattering and absorption of shortwave (solar) radiation by anthropogenic aerosols in cloud-free conditions (IPCC, 2001). Quantifying and reducing the uncertainty in aerosol influences on climate is critical to understanding climate change over the industrial period and to improving predictions of future climate change for assumed emission scenarios. Measurements of aerosol properties during major field campaigns in several regions of the globe during the past decade are contributing to an enhanced understanding of atmospheric aerosols and their effects on light scattering and climate. The present study, which focuses on three regions downwind of major urban/population centers (North Indian Ocean (NIO) during INDOEX, the Northwest Pacific Ocean (NWP) during ACE-Asia, and the Northwest Atlantic Ocean (NWA) during ICARTT), incorporates understanding gained from field observations of aerosol distributions and properties into calculations of perturbations in radiative fluxes due to these aerosols. This study evaluates the current state of observations and of two chemical transport models (STEM and MOZART). Measurements of burdens, extinction optical depth (AOD), and direct radiative effect of aerosols (DRE – change in radiative flux due to total aerosols) are used as measurement-model check points to assess uncertainties. In-situ measured and remotely sensed aerosol properties for each region (mixing state, mass scattering efficiency, single scattering albedo, and angular scattering properties and their dependences on relative humidity) are used as input parameters to two radiative transfer models (GFDL and University of Michigan) to constrain estimates of aerosol radiative effects, with uncertainties in each step propagated through the analysis. Constraining the radiative transfer calculations by observational inputs increases the clear-sky, 24-h averaged AOD (34±8%), top of atmosphere (TOA) DRE (32±12%), and TOA direct climate forcing of aerosols (DCF – change in radiative flux due to anthropogenic aerosols) (37±7%) relative to values obtained with "a priori" parameterizations of aerosol loadings and properties (GFDL RTM). The resulting constrained clear-sky TOA DCF is −3.3±0.47, −14±2.6, −6.4±2.1 Wm−2 for the NIO, NWP, and NWA, respectively. With the use of constrained quantities (extensive and intensive parameters) the calculated uncertainty in DCF was 25% less than the "structural uncertainties" used in the IPCC-2001 global estimates of direct aerosol climate forcing. Such comparisons with observations and resultant reductions in uncertainties are essential for improving and developing confidence in climate model calculations incorporating aerosol forcing.
