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Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

For the Community Atmosphere Model version 6 (CAM6), an adjustment is needed to conserve dry air mass. This adjustment exposes an inconsistency in how CAM6’s energy budget incorporates water—in CAM6 water in the vapor phase has energy, but condensed phases of water do not. When water vapor condenses, only its latent energy is retained in the model, while its remaining internal, potential, and kinetic energy are lost. A global fixer is used in the default CAM6 model to maintain global energy conservation, but locally the energy tendency associated with water changing phase violates the divergence theorem. This error in energy tendency is intrinsically tied to the water vapor tendency, and reaches its highest values in regions of heavy rainfall, where the error can be as high as 40 W m−2 annually averaged. Several possible changes are outlined within this manuscript that would allow CAM6 to satisfy the divergence theorem locally. These fall into one of two categories: 1) modifying the surface flux to balance the local atmospheric energy tendency and 2) modifying the local atmospheric tendency to balance the surface plus top-of-atmosphere energy fluxes. To gauge which aspects of the simulated climate are most sensitive to this error, the simplest possible change—where condensed water still does not carry energy and a local energy fixer is used in place of the global one—is implemented within CAM6. Comparing this experiment with the default configuration of CAM6 reveals precipitation, particularly its variability, to be highly sensitive to the energy budget formulation. Significance Statement This study examines and explains spurious regional sources and sinks of energy in a widely used climate model. These energy errors result from not tracking energy associated with water after it transitions from the vapor phase to either liquid or ice. Instead, the model used a global fixer to offset the energy tendency related to the energy sources and sinks associated with condensed water species. We replace this global fixer with a local one to examine the model sensitivity to the regional energy error and find a large sensitivity in the simulated hydrologic cycle. This work suggests that the underlying thermodynamic assumptions in the model should be revisited to build confidence in the model-simulated regional-scale water and energy cycles.

Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.

This work documents version two of the Department of Energy's Energy Exascale Earth System Model (E3SM). E3SMv2 is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid-latitudes and 30 km at the equator and poles. The model performance is evaluated with Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate has many realistic features of the climate system, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3K. In E3SMv2, ECS is reduced to 4.0K which is now within the plausible range based on a recent World Climate Research Program assessment. However, a number of important biases remain including a weak Atlantic Meridional Overturning Circulation, deficiencies in the characteristics and spectral distribution of tropical atmospheric variability, and a significant underestimation of the observed warming in the second half of the historical period. An analysis of single-forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol-related forcing.

Tropical rainfall exhibits a prominent annual cycle, with characteristic amplitude and phase representing the range between wet and dry seasons and their onset timing, respectively. Previous studies note enhanced amplitude over ocean and delayed phase over land in model projections of global warming, underpinned by first-order physical principles. However, it is unclear whether these changes have emerged in observations. Here we use gridded precipitation datasets to report a seasonal delay of 4.1 ± 1.1 and 4.2 ± 0.9 days (P

It is well documented that over the tropical oceans, column-integrated precipitable water (pw) and precipitation (P) have a nonlinear relationship. In this study moisture budget analysis is used to examine this P–pw relationship in a normalized precipitable water framework. It is shown that the parameters of the nonlinear relationship depend on the vertical structure of moisture convergence. Specifically, the precipitable water values at which precipitation is balanced independently by evaporation versus by moisture convergence define a critical normalized precipitable water, pwnc. This is a measure of convective inhibition that separates tropical precipitation into two regimes: a local evaporation-controlled regime with widespread drizzle and a precipitable water–controlled regime. Most of the 17 CMIP6 historical simulations examined here have higher pwnc compared to ERA5, and more frequently they operate in the drizzle regime. When compared to observations, they overestimate precipitation over the high-evaporation oceanic regions off the equator, thereby producing a “double ITCZ” feature, while underestimating precipitation over the large tropical landmasses and over the climatologically moist oceanic regions near the equator. The responses to warming under the SSP585 scenario are also examined using the normalized precipitable water framework. It is shown that the critical normalized precipitable water value at which evaporation versus moisture convergence balance precipitation decreases as a result of the competing dynamic and thermodynamic responses to warming, resulting in an increase in drizzle and total precipitation. Statistically significant historical trends corresponding to the thermodynamic and dynamic changes are detected in ERA5 and in low-intensity drizzle precipitation in the PERSIANN precipitation dataset.

Realistic simulation of the Earth’s mean state climate remains a major challenge and yet it is crucial for predicting the climate system in transition. Deficiencies in models’ process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections as well as incorrect attribution of the physical mechanisms governing the past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and longstanding biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when running as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback as well as the fidelity of the simulated base climate state are important for constraining the climate in the past and future.

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110-km grid spacing), ocean and sea ice (60km in the midlatitudes and 30km at the equator and poles), and river transport (55km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima simulations consisting of a long preindustrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between preindustrial (1850) and present day, the trajectory of the warming diverges from observations in the second half of the twentieth century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERFari+aci=−1.65W/m2) and high equilibrium climate sensitivity (ECS=5.3K).

Convective Quasi-Equilibrium (CQE) may be a useful framework for understanding the precipitation minus evaporation (P − E) response to CO2-induced warming. To explore this proposition, a suite of aquaplanet simulations with a slab ocean from the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP) is analyzed. A linear relationship between P − E and the curvature of sub-cloud moist entropy, a criterion for the onset of a tropical direct overturning circulation under CQE conditions, is shown to exist across many of the TRACMIP simulations. Furthermore, this linear relationship is a skillful predictor of changes in P − E in response to CO2-induced warming. The curvature metric also shows improvement in predicting P − E changes compared to the simpler method of relating P − E directly to the sub-cloud moist entropy field or a simple ‘wet-get-wetter’ type null hypothesis, especially on seasonal and shorter timescales. Using fixed relative humidity in the curvature metric and sub-cloud moist entropy degrades their ability to predict P − E changes, implying that both temperature and relative humidity changes in the boundary layer are important for characterizing future precipitation changes. To understand why the curvature metric is a skillful predictor of hydrological changes, a moist static energy (MSE) budget analysis is performed for a subset of the TRACMIP models. MSE divergence by transient eddies, which is well parameterized as a downgradient diffusive process, has a similar spatiotemporal structure to the curvature term, suggesting transient eddies are an important component to understanding the linear relationship between the curvature term and P − E.

Author(s): Burrows, SM; Maltrud, M; Yang, X; Zhu, Q; Jeffery, N; Shi, X; Ricciuto, D; Wang, S; Bisht, G; Tang, J; Wolfe, J; Harrop, BE; Singh, B; Brent, L; Baldwin, S; Zhou, T; Cameron-Smith, P; Keen, N; Collier, N; Xu, M; Hunke, EC; Elliott, SM; Turner, AK; Li, H; Wang, H; Golaz, JC; Bond-Lamberty, B; Hoffman, FM; Riley, WJ; Thornton, PE; Calvin, K; Leung, LR | Abstract: This paper documents the biogeochemistry configuration of the Energy Exascale Earth System Model (E3SM), E3SMv1.1-BGC. The model simulates historical carbon cycle dynamics, including carbon losses predicted in response to land use and land cover change, and the responses of the carbon cycle to changes in climate. In addition, we introduce several innovations in the treatment of soil nutrient limitation mechanisms, including explicit dependence on phosphorus availability. The suite of simulations described here includes E3SM contributions to the Coupled Climate-Carbon Cycle Model Intercomparison Project and other projects, as well as simulations to explore the impacts of structural uncertainty in representations of nitrogen and phosphorus limitation. We describe the model spin-up and evaluation procedures, provide an overview of results from the simulation campaign, and highlight key features of the simulations. Cumulative warming over the twentieth century is similar to observations, with a midcentury cold bias offset by stronger warming in recent decades. Ocean biomass production and carbon uptake are underpredicted, likely due to biases in ocean transport leading to widespread anoxia and undersupply of nutrients to surface waters. The inclusion of nutrient limitations in the land biogeochemistry results in weaker carbon fertilization and carbon-climate feedbacks than exhibited by other Earth System Models that exclude those limitations. Finally, we compare with an alternative representation of terrestrial biogeochemistry, which differs in structure and in initialization of soil phosphorus. While both configurations agree well with observational benchmarks, they differ significantly in their distribution of carbon among different pools and in the strength of nutrient limitations.

In this study, we analyze the realism with which tropical cyclones (TCs) are simulated in the fully coupled low‐ and high‐resolution Energy Exascale Earth System Model (E3SM) version 1, with a focus on the latter. Compared to the low‐resolution (grid spacing of ∼1°), the representation of TCs improves considerably in the high‐resolution configuration (grid spacing of ∼0.25°). Significant improvements are found in the global TC frequency, TC lifetime maximum intensities, and the relative distribution of TCs among the different basins. However, at both resolutions, spurious TC activity is found in some basins, notably in the subtropical regions. Contrasting the simulated large‐scale TC environment with observations reveals that the model environment is unrealistically conducive for TC development in those regions. Further analysis indicates that these biases are likely related to those in thermodynamic potential intensity, caused by systematic SST biases, and vertical wind shear in the coupled model. TC‐ocean interaction is also examined in the high‐resolution configuration of the model. The salient features of the ocean's response to TC‐induced mixing and the ocean's impact on TC intensification are well‐reproduced. Finally, an evaluation of the influence of El Niño Southern Oscillation (ENSO) on TCs in the high‐resolution configuration of the model reveals that the ENSO‐TC relationship in the model has the right sign and is significant for the North Atlantic and Northwest Pacific, albeit weaker than in observations. In summary, the high‐resolution configuration of the E3SM model simulates TC activity reasonably and hence could be a useful tool for TC‐related research.

A large set of Green’s function-type experiments is performed with q-flux forcings mimicking the effects of the ocean heat uptake (OHU) to examine the global surface air temperature (SAT) sensitivities to the location of the forcing. The result of the experiments confirms the earlier notion derived from experiments with different model complexities that the global mean SAT is far more sensitive to the oceanic forcing from high latitudes than the tropics. Remarkably, no matter in which latitude the q-flux forcings are placed, the SAT response is always characterized by a feature of polar amplification, implicating that it is intrinsic to our climate system. Considerable zonal asymmetry is also present in the efficacy of the tropical OHU, with the tropical eastern Pacific being much more efficient than the Indian Ocean and tropical Atlantic in driving global SAT warming by exciting the leading neutral mode of the SAT that projects strongly onto global mean warming. Using a radiative kernel, feedback analysis is also conducted to unravel the underlying processes responsible for the spatial heterogeneity in the global OHU efficacy, the polar amplification structures, and the tropical altruism of sharing the warmth with remote latitudes. Warming “altruism” for a q flux at a given latitude is also investigated in terms of the ratio of the induced remote latitudes versus the directly forced local warming. It is found that the tropics are much more altruistic than higher latitudes because of the high-energy transport efficiency of the Hadley circulation.

The nonhydrostatic Model for Prediction Across Scales (NH‐MPAS) provides a global framework to achieve high resolution using regional mesh refinement. Previous studies using the hydrostatic version of MPAS (H‐MPAS) with the physics parameterizations of Community Atmosphere Model version 4 (CAM4) found notable resolution‐dependent behaviors. This study revisits the resolution sensitivity using NH‐MPAS with both CAM4 and CAM5 physics. A series of aqua‐planet simulations at global quasiuniform resolutions and global variable resolution with a regional mesh refinement over the tropics are analyzed, with a primary focus on the distinct characteristics of NH‐MPAS in simulating precipitation, clouds, and large‐scale circulation features compared to H‐MPAS‐CAM4. The resolution sensitivity of total precipitation and column integrated moisture in NH‐MPAS is smaller than that in H‐MPAS‐CAM4. This contributes importantly to the reduced resolution sensitivity of large‐scale circulation features such as the intertropical convergence zone and Hadley circulation in NH‐MPAS compared to H‐MPAS. In addition, NH‐MPAS shows almost no resolution sensitivity in the simulated westerly jet, in contrast to the obvious poleward shift in H‐MPAS with increasing resolution, which is partly explained by differences in the hyperdiffusion coefficients used in the two models that influence wave activity. With the reduced resolution sensitivity, simulations in the refined region of the NH‐MPAS global variable resolution configuration exhibit zonally symmetric features that are more comparable to the quasiuniform high‐resolution simulations than those from H‐MPAS that displays zonal asymmetry in simulations inside the refined region. Overall, NH‐MPAS with CAM5 physics shows less resolution sensitivity compared to CAM4.

Author(s): Rasch, PJ; Xie, S; Ma, PL; Lin, W; Wang, H; Tang, Q; Burrows, SM; Caldwell, P; Zhang, K; Easter, RC; Cameron-Smith, P; Singh, B; Wan, H; Golaz, JC; Harrop, BE; Roesler, E; Bacmeister, J; Larson, VE; Evans, KJ; Qian, Y; Taylor, M; Leung, LR; Zhang, Y; Brent, L; Branstetter, M; Hannay, C; Mahajan, S; Mametjanov, A; Neale, R; Richter, JH; Yoon, JH; Zender, CS; Bader, D; Flanner, M; Foucar, JG; Jacob, R; Keen, N; Klein, SA; Liu, X; Salinger, AG; Shrivastava, M; Yang, Y | Abstract: The Energy Exascale Earth System Model Atmosphere Model version 1, the atmospheric component of the Department of Energy's Energy Exascale Earth System Model is described. The model began as a fork of the well-known Community Atmosphere Model, but it has evolved in new ways, and coding, performance, resolution, physical processes (primarily cloud and aerosols formulations), testing and development procedures now differ significantly. Vertical resolution was increased (from 30 to 72 layers), and the model top extended to 60 km (~0.1 hPa). A simple ozone photochemistry predicts stratospheric ozone, and the model now supports increased and more realistic variability in the upper troposphere and stratosphere. An optional improved treatment of light-absorbing particle deposition to snowpack and ice is available, and stronger connections with Earth system biogeochemistry can be used for some science problems. Satellite and ground-based cloud and aerosol simulators were implemented to facilitate evaluation of clouds, aerosols, and aerosol-cloud interactions. Higher horizontal and vertical resolution, increased complexity, and more predicted and transported variables have increased the model computational cost and changed the simulations considerably. These changes required development of alternate strategies for tuning and evaluation as it was not feasible to “brute force” tune the high-resolution configurations, so short-term hindcasts, perturbed parameter ensemble simulations, and regionally refined simulations provided guidance on tuning and parameterization sensitivity to higher resolution. A brief overview of the model and model climate is provided. Model fidelity has generally improved compared to its predecessors and the CMIP5 generation of climate models.

The effect of cloud radiation interactions on cloud properties is examined in the context of a limited domain cloud-resolving model. The atmospheric cloud radiative effect (ACRE) influences the areal extent of tropical high clouds in two distinct ways. The first is through direct radiative destabilization of the elevated cloud layers, mostly as a result of longwave radiation heating the cloud bottom and cooling the cloud top. The second effect is radiative stabilization, whereby cloud radiative heating of the atmospheric column stabilizes the atmosphere to deep convection. In limited area domain simulations, the stabilizing (or indirect) effect is the dominant role of the cloud radiative heating, thus reducing the cloud cover in simulations where ACRE is included compared to those where it is removed. Direct cloud radiative heating increases high cloud fraction, decreases mean cloud optical depth, and increases cloud top temperature. The indirect cloud radiative heating decreases high cloud fraction, but also decreases mean cloud optical depth and increases cloud top temperature. The combination of these effects increases the top-of-atmosphere cloud radiative effect. In mock-Walker circulation experiments, the decrease in high cloud amount owing to radiative stabilization tends to cancel out the increase in high cloud amount owing to the destabilization within the cloud layer. The changes in cloud optical depth and cloud top pressure, however, are similar to those produced in the limited area domain simulations. This article is protected by copyright. All rights reserved.

The relationship between the tropical circulation and cloud radiative effect is investigated. Output from the Clouds On–Off Klimate Intercomparison Experiment (COOKIE) is used to examine the impact of cloud radiative effects on circulation and climate. In aquaplanet simulations with a fixed SST pattern, the cloud radiative effect leads to an equatorward contraction of the intertropical convergence zone (ITCZ) and a reduction of the double ITCZ problem. It is shown that the cloud radiative heating in the upper troposphere increases the temperature, weakens CAPE, and inhibits the onset of convection until it is closer to the equator, where SSTs are higher. Precipitation peaks at higher values in a narrower band when the cloud radiative effects are active, compared to when they are inactive, owing to the enhancement in moisture convergence. Additionally, cloud–radiation interactions strengthen the mean meridional circulation and consequently enhance the moisture convergence. Although the mean tropical precipitation decreases, the atmospheric cloud radiative effect has a strong meridional gradient, which supports stronger poleward energy flux and speeds up the Hadley circulation. Cloud radiative heating also enhances cloud water path (liquid plus ice), which, combined with the reduction in precipitation, suggests that the cloud radiative heating reduces precipitation efficiency in these models.

Reanalysis data and radiation budget data are used to calculate the role of the atmospheric cloud radiative effect in determining the magnitude of horizontal export of energy by the tropical atmosphere. Because tropical high clouds result in net radiative heating of the atmosphere, they increase the requirement for the atmosphere to export energy from convective regions. Increases in upper-tropospheric water vapor associated with convection contribute about a fifth of the atmospheric radiative heating anomaly associated with convection. Over the warmest tropical oceans, the radiative effect of convective clouds and associated water vapor is roughly two-thirds the value of the atmospheric energy transport. Cloud radiative heating and atmospheric heat transport increase at the same rate with increasing sea surface temperature, suggesting that the increased energy export is supplied by the radiative heating associated with convective clouds. The net cloud radiative effect at the top of the atmosphere is insensitive to changes in SST over the warm pool. Principal component analysis of satellite-retrieved cloud data reveals that the insensitivity of the net cloud radiative effect to SST is the result of changes in cloud amount offsetting changes in cloud optical thickness and cloud-top height. While increasing upward motion makes the cloud radiative effect more negative, that decrease is offset by reductions in outgoing longwave radiation owing to increases in water vapor.

A cloud-resolving model is used to test the hypothesis that radiative cooling by water vapor emission is the primary control on the temperature of tropical anvil clouds. The temperature of ice clouds in the simulation can be increased or decreased by changing only the emissivity of water vapor in the upper troposphere. The effect of the model’s fixed ozone profile on stability creates a pressure-dependent inhibition of convection, leading to a small warming in cloud-top temperature as SST is increased. Increasing stratospheric water vapor also warms the cloud-top temperature slightly. Changing the latent heat of fusion reduces the cloud fraction at high altitudes, but does not significantly change temperature at which cloud fraction peaks in the upper troposphere. The relationship between radiatively driven horizontal mass convergence and cloud fraction that causes cloud temperature to be insensitive to surface temperature is preserved when a large model domain is used so that convection aggregates in a small part of the model domain.