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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

On the Correspondence Between Atmosphere-Only and Coupled Simulations for Radiative Feedbacks and Forcing From CO 2

Atmosphere-only experiments are widely used to investigate climate feedbacks simulated in more computationally expensive fully coupled global climate model simulations. We confirm that this remains a valid approach by comparing the radiative feedbacks and forcing between coupled and atmosphere-only simulations for the latest models taking part in the 6th phase of the Coupled Model Intercomparison Project (CMIP6). For global-mean cloud feedbacks, we find a better than previously known correspondence between these experiments, which applies even to the response of individual cloud properties (amount, altitude, and optical depth) and holds even when considering atmosphere-only simulations of only 1 yr duration. For regional cloud feedbacks, the correspondence between the two experiments is generally present at every geographic location except for the tropical Pacific but takes longer experiments to reveal. For the lapse rate and surface albedo feedbacks, the correspondence between the two experiments is weaker due to the non-uniform warming pattern and loss of sea ice in the coupled experiment. For the across-model relationship between 4xCO 2 effective radiative forcing and feedback, we find a different behavior across experiments in CMIP6 than in CMIP5, casting doubt on the physical significance of previous results that highlighted an anti-correlation between the two quantities. Overall, these results confirm the utility of atmosphere-only experiments particularly to study cloud feedbacks, which are the dominant source of inter-model spread in climate sensitivity.

58 GEOSCIENCES↗
NASA NTRS1998

GCM Simulations of Cirrus Clouds and Cloud Feedbacks

Cirrus clouds are a particularly uncertain component of general circulation model (GCM simulations of long-term climate change for a variety of reasons: (1) They encompass a wide range of optical thicknesses and altitudes, from thin tropopause cirrus to thick anvil cirrus that descend to the freezing level, and thus can exert both positive and negative forcing and feedback on the climate; (2) The dynamical processes that create them are poorly resolved in climate GCMs and different in the tropics and midlatitudes; (3) Predictions of their formation and microphysical properties depend on the accuracy of dynamical transports of small concentrations of water vapor to and within the upper troposphere; (4) The relative humidity conditions at which they form depends on the nature and concentration of nucleating particles and is poorly understood; (5) They are more difficult to observe than other cloud types, and hence their parameterization is more loosely constrained by available data. We will illustrate the potential sensitivity of the perturbed climate to uncertainties in cirrus cloud formulation. We will also examine the processes that form cirrus in climate models and discuss the accuracy with which climate GCMs represent these processes. We will also discuss ways in which GCM grid-scale parameterizations might be derived from cloud-scale observations. Finally, we will emphasize the types of global observations needed to constrain parameterizations of cirrus in climate GCMs.

DelGenio, Anthony D.↗
DOE OSTI2020

A Regime-Oriented Approach to Observationally Constraining Extratropical Shortwave Cloud Feedbacks

The extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m -2 per kelvin SST increase (35°–75°N) and 1.2–1.9 W m -2 per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks

58 GEOSCIENCES↗
NASA NTRS2018

Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗
NASA NTRS1992

Empirical determination of the effects of clouds on the Earth's Radiation Budget over the Pacific Ocean

The main objectives of this research has been to learn how clouds interact with the Earth's Radiation Budget (ERB). This broad goal has been approached in three distinct ways. The first has been to analyze the direct effect cloud amount has on the radiative components of the ERB. The second has been to investigate the indirect effects clouds and water vapor may have on the climate as a feedback mechanism. And finally an attempt has been made to simulate the findings in a simple radiative-convective climate model. This report will summarize these three phases of the research.

Ziskin, Daniel↗
NASA NTRS2019

The Role of Thermodynamic Phase Shifts in Cloud Optical Depth Variations with Temperature

We present a novel method that identifies the contributions of thermodynamic phase shifts and processes governing supercooled liquid and ice clouds to cloud optical depth variations with temperature using MODIS observations. Our findings suggest that thermodynamic phase shifts outweigh the net influence of processes governing supercooled liquid and ice clouds in causing increases in mid-latitudinal cold cloud optical depth with temperature. Cloud regime analysis suggests that dynamical conditions appear to have less influence on the contribution of thermodynamic phase shifts to cloud optical depth variations with temperature. Thermodynamic phase shifts also contribute more to increases in cloud optical depth during colder seasons due to the enhanced optical thickness contrast between liquid and ice clouds. The results of this study highlight the importance of thermodynamic phase shifts in explaining cold cloud optical depth increases with temperature in the current climate and may elucidate their role in the cloud optical depth feedback.

cloud optical depth↗
NASA NTRS2022

Constraining Clouds and Convective Parameterizations in A Climate Model Using Paleoclimate Data

Cloud and convective parameterizations strongly influence uncertainties in equilibrium climate sensitivity. We provide a proof-of-concept study to constrain these parameterizations in a perturbed parameter ensemble of the atmosphere-only version of the Goddard Institute for Space Studies Model E2.1 simulations by evaluating model biases in the present-day runs using multiple satellite climatologies and by comparing simulated δ 18 O of precipitation (δ 18 O p ), known to be sensitive to parameterization schemes, with a global database of speleothem δ 18 O records covering the Last Glacial Maximum (LGM), mid-Holocene (MH) and pre-industrial (PI) periods. Relative to modern interannual variability, paleoclimate simulations show greater sensitivity to parameter changes, allowing for an evaluation of model uncertainties over a broader range of climate forcing and the identification of parts of the world that are parameter sensitive. Certain simulations reproduced absolute δ 18 O p values across all time periods, along with LGM and MH δ 18 O p anomalies relative to the PI, better than the default parameterization. No single set of parameterizations worked well in all climate states, likely due to the non-stationarity of cloud feedbacks under varying boundary conditions. Future work that involves varying multiple parameter sets simultaneously with coupled ocean feedbacks will likely provide improved constraints on cloud and convective parameterizations.

cloud and convective parameterization↗
NASA NTRS1982

Low-latitude cloudiness and climate feedback - Comparative estimates from satellite data

Three studies of the relative albedo to the IR components of cloud amount feedback are reviewed, and an approach to the seasonal variability in low-level cloud numbers is presented. Comparisons are made and uncertainties calculated for the predictions of cloud amounts from satellite data sets for outgoing IR flux. IR data is used directly for a linear regression analysis and seasonal and latitudinal variations are considered in terms of monthly-annual means for particular latitude zones. Investigations of NOAA-NESS satellite data revealed that cirrus clouds are transparent in the 10.5-12.5 microns range and cloud albedos decrease at wavelengths greater than 0.7 micron, which suggests a possibility of cloud-sky and clear-sky albedo comparisons at 0.5-0.7 micron. The inclusion of Rayleigh scattering and atmospheric water vapor absorption of sunlight is recommended to test the effects on observed contracts.

Cess, R. D.↗
NASA NTRS2011

An Estimate of Low-Cloud Feedbacks from Variations of Cloud Radiative and Physical Properties with Sea Surface Temperature on Interannual Time Scales

Simulations of climate change have yet to reach a consensus on the sign and magnitude of the changes in physical properties of marine boundary layer clouds. In this study, the authors analyze how cloud and radiative properties vary with SST anomaly in low-cloud regions, based on five years (March 2000 - February 2005) of Clouds and the Earth s Radiant Energy System (CERES) -- Terra monthly gridded data and matched European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological reanalaysis data. In particular, this study focuses on the changes in cloud radiative effect, cloud fraction, and cloud optical depth with SST anomaly. The major findings are as follows. First, the low-cloud amount (-1.9% to -3.4% /K) and the logarithm of low-cloud optical depth (-0.085 to -0.100/K) tend to decrease while the net cloud radiative effect (3.86 W/m(exp 2)/ K) becomes less negative as SST anomalies increase. These results are broadly consistent with previous observational studies. Second, after the changes in cloud and radiative properties with SST anomaly are separated into dynamic, thermodynamic, and residual components, changes in the dynamic component (taken as the vertical velocity at 700 hPa) have relatively little effect on cloud and radiative properties. However, the estimated inversion strength decreases with increasing SST, accounting for a large portion of the measured decreases in cloud fraction and cloud optical depth. The residual positive change in net cloud radiative effect (1.48 W/m(exp 2)/ K) and small changes in low-cloud amount (-0.81% to 0.22% /K) and decrease in the logarithm of optical depth (-0.035 to -0.046/ K) with SST are interpreted as a positive cloud feedback, with cloud optical depth feedback being the dominant contributor. Last, the magnitudes of the residual changes differ greatly among the six low-cloud regions examined in this study, with the largest positive feedbacks (approximately 4 W/m(exp 2)/ K) in the southeast and northeast Atlantic regions and a slightly negative feedback (-0.2 W/m(exp 2)/ K) in the south-central Pacific region. Because the retrievals of cloud optical depth and/or cloud fraction are difficult in the presence of aerosols, the transport of heavy African continental aerosols may contribute to the large magnitudes of estimated cloud feedback in the two Atlantic regions.

Eitzen, Zachary A.↗
NASA NTRS2019

The Cumulus and Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both spaceborne and large-eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies Sc, broken Sc, Cu under Sc, Cu with stratiform outflow and Cu. To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent, vertical variability and horizontal continuity, which is separately applied to both CALIPSO and combined CloudSat–CALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and Sc–Cu transition case studies. Then, the global statistics are compared against those from existing passive- and active-sensor satellite observations. Our results indicate that the cloud optical thickness – as used in passive-sensor observations – is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. Using clustering-derived datasets shows better results although one cannot completely separate cloud types with such an approach. On the contrary, classifying Cu and Sc clouds and the transition between them based on their geometrical shape and spatial heterogeneity leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, ship-based and field campaigns. Furthermore, we show that our method improves existing Sc–Cu classifications by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection and stratocumulus clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ (last access: 5 November 2019) and on the zenodo website at https://zenodo.org/record/2667637 (last access: 5 November 2019).

Cesana, Gregory V.↗
NASA NTRS2012

Arctic PBL Cloud Height and Motion Retrievals from MISR and MINX

How Arctic clouds respond and feedback to sea ice loss is key to understanding of the rapid climate change seen in the polar region. As more open water becomes available in the Arctic Ocean, cold air outbreaks (aka. off-ice flow from polar lows) produce a vast sheet of roll clouds in the planetary boundary layer (PBl). The cold air temperature and wind velocity are the critical parameters to determine and understand the PBl structure formed under these roll clouds. It has been challenging for nadir visible/IR sensors to detect Arctic clouds due to lack of contrast between clouds and snowy/icy surfaces. In addition) PBl temperature inversion creates a further problem for IR sensors to relate cloud top temperature to cloud top height. Here we explore a new method with the Multiangle Imaging Spectro-Radiometer (MISR) instrument to measure cloud height and motion over the Arctic Ocean. Employing a stereoscopic-technique, MISR is able to measure cloud top height accurately and distinguish between clouds and snowy/icy surfaces with the measured height. We will use the MISR INteractive eXplorer (MINX) to quantify roll cloud dynamics during cold-air outbreak events and characterize PBl structures over water and over sea ice.

Wu, Dong L.↗
NASA NTRS2015

The Influence of Sea Ice on Arctic Low Cloud Properties and Radiative Effects

The Arctic is one of the most climatically sensitive regions of the Earth. Climate models robustly project the Arctic to warm 2-3 times faster than the global mean surface temperature, termed polar warming amplification (PWA), but also display the widest range of surface temperature projections in this region. The response of the Arctic to increased CO2 modulates the response in tropical and extra-tropical regions through teleconnections in the atmospheric circulation. An increased frequency of extreme precipitation events in the northern mid-latitudes, for example, has been linked to the change in the background equator-to-pole temperature gradient implied by PWA. Understanding the Arctic climate system is therefore important for predicting global climate change. The ice albedo feedback is the primary mechanism driving PWA, however cloud and dynamical feedbacks significantly contribute. These feedback mechanisms, however, do not operate independently. How do clouds respond to variations in sea ice? This critical question is addressed by combining sea ice, cloud, and radiation observations from satellites, including CERES, CloudSAT, CALIPSO, MODIS, and microwave radiometers, to investigate sea ice-cloud interactions at the interannual timescale in the Arctic. Cloud characteristics are strongly tied to the atmospheric dynamic and thermodynamic state. Therefore, the sensitivity of Arctic cloud characteristics, vertical distribution and optical properties, to sea ice anomalies is computed within atmospheric dynamic and thermodynamic regimes. Results indicate that the cloud response to changes in sea ice concentration differs significantly between atmospheric state regimes. This suggests that (1) the atmospheric dynamic and thermodynamic characteristics and (2) the characteristics of the marginal ice zone are important for determining the seasonal forcing by cloud on sea ice variability.

Taylor, Patrick C.↗
NASA NTRS2014

Climate Sensitivity in the Anthropocene

Climate sensitivity in its most basic form is defined as the equilibrium change in global surface temperature that occurs in response to a climate forcing, or externally imposed perturbation of the planetary energy balance. Within this general definition, several specific forms of climate sensitivity exist that differ in terms of the types of climate feedbacks they include. Based on evidence from Earth's history, we suggest here that the relevant form of climate sensitivity in the Anthropocene (e.g. from which to base future greenhouse gas (GHG) stabilization targets) is the Earth system sensitivity including fast feedbacks from changes in water vapour, natural aerosols, clouds and sea ice, slower surface albedo feedbacks from changes in continental ice sheets and vegetation, and climate-GHG feedbacks from changes in natural (land and ocean) carbon sinks. Traditionally, only fast feedbacks have been considered (with the other feedbacks either ignored or treated as forcing), which has led to estimates of the climate sensitivity for doubled CO2 concentrations of about 3 C. The 2×CO2 Earth system sensitivity is higher than this, being approx. 4-6 C if the ice sheet/vegetation albedo feedback is included in addition to the fast feedbacks, and higher still if climate-GHG feedbacks are also included. The inclusion of climate-GHG feedbacks due to changes in the natural carbon sinks has the advantage of more directly linking anthropogenic GHG emissions with the ensuing global temperature increase, thus providing a truer indication of the climate sensitivity to human perturbations. The Earth system climate sensitivity is difficult to quantify due to the lack of palaeo-analogues for the present-day anthropogenic forcing, and the fact that ice sheet and climate-GHG feedbacks have yet to become globally significant in the Anthropocene. Furthermore, current models are unable to adequately simulate the physics of ice sheet decay and certain aspects of the natural carbon and nitrogen cycles. Obtaining quantitative estimates of the Earth system sensitivity is therefore a high priority for future work.

Anthropocene↗
NASA NTRSDate not supplied

An Observationally-Based Determination of the Arctic Sea Ice-Cloud Feedback Since 2000: Isolating the Arctic Cloud Response to Sea Ice Loss

Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.

Patrick C Taylor↗
DOE OSTI2025

Nonlocal, Pattern-Aware Response and Feedback Framework for Regional Climate Response

We devise a pattern-aware feedback framework for representing the forced climate response using a suite of Green’s function experiments with solar radiation perturbations. By considering the column energy balance, a comprehensive linear response function (CLRF) for important climate variables and feedback quantities such as moist static energy, sea surface temperature, albedo, cloud optical depth, and lapse rate is learned from Green’s function data. The learned CLRF delineates the effects of the energy diffusion in both the ocean and atmosphere and the pattern-aware feedbacks from the aforementioned radiatively active processes. The CLRF can then be decomposed into forcing–response mode pairs, which are in turn used to construct a reduced-order model describing the dominant dynamics of climate responses. These mode pairs capture nonlocal effects and teleconnections in the climate and thus make the reduced-order model apt for capturing regional features of climate response. A key observation is that the CLRF captures the polar-amplified response as the most excitable mode of the climate system, and this mode is explainable in the data-learned pattern-aware feedback framework. The reduced-order model can be used for predicting the response for a given forcing and for reconstructing the forcing from a given response; we demonstrate these capabilities for multiple independent forcing scenarios.

Feedback↗
NASA NTRSDate not supplied

Modeling the Water Cycle With the NASA Ames FV3-Based Mars Global Climate Model

It is widely recognized that water ice clouds critically affect the current weather and climate of Mars. Simulating clouds and the water cycle in climate models remains challenging, however, due to the highly sensitive nature of cloud formation to several microphysical parameters that are not well known for Mars and the strong radiative feedbacks that can occur. We have recently ported our cloud microphysics package from the NASA Ames Legacy Mars Global Climate Model (MGCM) to our new MGCM based on the NOAA/GFDL cubed-sphere finite volume (FV3) dynamical core. Here we report on the status of our water cycle simulations and show how our reference simulation compares to observations.

M A Kahre↗
NASA NTRS2022

Extratropical Shortwave Cloud Feedbacks in the Context of the Global Circulation and Hydrological Cycle

Shortwave (SW) cloud feedback (SW FB ) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs in the Sixth Coupled Model Intercomparison Project (CMIP6) exceed 5K, above the fifth assessment report (AR5) ‘likely’ maximum (4.5K) due to extratropical SW FB ’s that are more positive than those simulated in previous generation CMIP5 GCMs. Here we show that across 57 GCMs Southern Ocean SW FB can be predicted from the sensitivity of column-integrated liquid water mass LWP) to moisture convergence and to surface temperature. The response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean SW FB — inconsistent with extreme ECS.

extratropical cloud response↗
DOE OSTI2023

A Process Model for ITCZ Narrowing under Warming Highlights Clear-Sky Water Vapor Feedbacks and Gross Moist Stability Changes in AMIP Models

Tropical areas with mean upward motion—and as such the zonal-mean intertropical convergence zone (ITCZ)—are projected to contract under global warming. To understand this process, a simple model based on dry static energy and moisture equations is introduced for zonally symmetric overturning driven by sea surface temperature (SST). Processes governing ascent area fraction and zonal mean precipitation are examined for insight into Atmospheric Model Intercomparison Project (AMIP) simulations. Bulk parameters governing radiative feedbacks and moist static energy transport in the simple model are estimated from the AMIP ensemble. Uniform warming in the simple model produces ascent area contraction and precipitation intensification—similar to observations and climate models. Contributing effects include stronger water vapor radiative feedbacks, weaker cloud-radiative feedbacks, stronger convection-circulation feedbacks, and greater poleward moisture export. The simple model identifies parameters consequential for the inter-AMIP-model spread; an ensemble generated by perturbing parameters governing shortwave water vapor feedbacks and gross moist stability changes under warming tracks inter-AMIP-model variations with a correlation coefficient ~0.46. Here, the simple model also predicts the multimodel mean changes in tropical ascent area and precipitation with reasonable accuracy. Furthermore, the simple model reproduces relationships among ascent area precipitation, ascent strength, and ascent area fraction observed in AMIP models. A substantial portion of the inter-AMIP-model spread is traced to the spread in how moist static energy and vertical velocity profiles change under warming, which in turn impact the gross moist stability in deep convective regions—highlighting the need for observational constraints on these quantities.

54 ENVIRONMENTAL SCIENCES↗