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To improve cloud feedback understanding and simulation, observations have been used to quantify the rate of change of cloud radiative properties as a function of specific environmental metrics (or cloud controlling factors; CCFs). The study focuses on low‐level cloud dominated regions during 2006–2010. For each ocean gridpoint, Spearman's rank correlation coefficients of daily mean observed cloud fraction versus (a) 10‐m wind, (b) sensible heat flux (SHF), (c) sea surface temperature, (d) estimated inversion strength (EIS), (e) 850 hPa vertical velocity, and (f) the M parameter (∆θskin800hPa ${\increment}{\theta }_{\text{skin}}^{800\text{hPa}}$) are sorted to identify the dominant CCFs in both extratropics (30°–60°N/S) and subtropics (30°S–30°N). A novel map for visualizing dominant CCFs for low‐level cloud fraction reveals that: ∆θskin800hPa ${\increment}{\theta }_{\text{skin}}^{800\text{hPa}}$ dominates in the subtropical stratocumulus regions while 10‐m winds dominate in shallow cumulus regions but in the extratropics, a different inversion structure diagnostic (EIS) dominates, while SHF dominates in western boundary current areas. Plain Language Summary: Clouds in the lower levels of the atmosphere cover up to 80% of the oceans in some specific areas within the ±30° latitude band (i.e., the subtropics regions) but also cover a large portion of the mid‐latitude oceans (i.e., the extratropics). In the subtropics, cloud cover has been found to depend principally on sea surface temperature and the stability or thermal structure of the lower levels of the troposphere. Using satellite observations and reanalysis data, we test whether these relationships are found everywhere, and importantly, we find that these dependencies are not uniform across the global oceans. Where cloud cover is large, stability is the strongest driver of cloud cover, but the atmospheric vertical structure of this stability most strongly correlated with the clouds differs between the subtropics and extratropics. Where cloud cover is relatively small, near surface wind speed has the strongest relationship with cloud cover in the subtropics, while at higher latitudes and more specifically in the western boundary current regions, air‐sea energy exchanges (i.e., sensible heat flux) dominate. These regionally varying relationships are depicted with a novel map of dominant cloud controlling factors. This map can help with evaluation and development of climate models. Key Points: A novel map of dominant controlling factors for low‐level oceanic cloud fraction reveals regionally varying patternsSubtropical and extratropical low clouds depend on stability, but the dominant stability metric varies by region, challenging modelsSurface wind speed dominates in cumulus‐dominated regions, sensible heat fluxes dominate in western boundary current regions in winter [ABSTRACT FROM AUTHOR]

Shortwave (SW) cloud feedback (SWFB) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report "likely" maximum (4.5K) due to extratropical SWFB's that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean SWFB 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 SWFB— inconsistent with extreme ECS. Plain Language Summary: As the climate warms, moisture convergence into the extratropics strengthens, increasing cloudiness, reflected sunlight, and precipitation. Increased cloudiness in response to moisture convergence is affected by how efficiently clouds condense from water vapor relative to how efficiently precipitation depletes them. Simulations where clouds form efficiently cannot reflect much more sunlight in the extratropics because they are already very cloudy and bright. Observations constrain both the sensitivity of reflected sunlight to cloud and of cloud to moisture. Combining these constraints with constraints on other cloud regimes rules out extremely small and large future warming. Key Points: Enhanced moisture convergence with warming creates a negative extratropical cloud feedbackCloud source and sink efficiency set the extratropical cloud responseConstraint by observations suggests a weakly negative feedback‐ and a moderate effective climate sensitivity [ABSTRACT FROM AUTHOR]

The next‐generation global climate model from the NASA Goddard Institute for Space Studies, GISS‐E3, contains many improvements to resolution and physics that allow for improved representation of tropical cyclones (TCs) in the model. This study examines the properties of TCs in two different versions of E3 at different points in its development cycle, run for 20 years at 0.5° resolution, and compares these TCs with observations, the previous generation GISS model, E2, and other climate models. E3 shares many TC biases common to global climate models, such as having too few tropical cyclones, but is much improved from E2. E3 produces strong enough TCs that observation‐based wind speed thresholds can now be used to detect and track them, and some storms now reach hurricane intensity; neither of these was true of E2. Model development between the first and second versions of E3 further increased the number and intensity of TCs and reduced TC count biases globally and in most regions. One‐year sensitivity tests to changes in various microphysical and dynamical tuning parameters are also examined. Increasing the entrainment rate for the more strongly entraining plume in the convection scheme increases the number of TCs (though also affecting other climate variables, and in some cases increasing biases). Variations in divergence damping did not have a strong effect on simulated TC properties, contrary to expectations based on previous studies. Overall, the improvements in E3 make it more credible for studies of TC activity and its relationship to climate. Plain Language Summary: Tropical cyclones, storms known as hurricanes, typhoons, or cyclones in different parts of the world, are one of the most dangerous natural hazards, and it is an important question whether they will get more powerful or common in our changing climate. Global climate models, used by scientists to study climate change, can simulate tropical cyclones, but in the models these storms tend to be weaker and less numerous than in the real world, and this is especially true for the previous generation climate model developed by NASA, known as GISS‐E2. We analyzed tropical cyclones in the newest version of this model, GISS‐E3, running at its highest resolution, in which the world is divided into grid boxes about 50 km wide. We found that the new version has more and stronger cyclones than the old version. While the storms are still weaker and less numerous than in the real world, GISS‐E3 now simulates storms strong enough that they would be called hurricanes instead of tropical storms, and it is comparable to its peer climate models in its representation of tropical cyclones. Key Points: The new NASA GISS‐E3 global climate model at 0.5° resolution simulates more realistic tropical cyclone activity versus the E2 versionHurricane intensity storms are now simulated, and the average storms are comparable to other 0.5° climate modelsTropical cyclone counts in E3 are very sensitive to convective plume entrainment rates but not to divergence damping coefficients [ABSTRACT FROM AUTHOR]

Partitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, "rimed ice," to the original four‐class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity. Key Points: Graupel is added to a convective microphysics scheme for global climate modelsNew convective ice particle terminal velocity schemes are implemented and convective snow is allowed to detrainVertical distribution of ice mass in the midtroposphere and upper troposphere is improved [ABSTRACT FROM AUTHOR]

Simulations of the CMIP6 historical period 1850–2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to greenhouse gas forcing than their CMIP5 predecessors (GISS‐E2) but warm less during recent decades due to a forcing reduction that is attributed to greater longwave opacity in the GISS‐E2.1 pre‐industrial simulations. This results in an atmosphere less sensitive to increases in opacity from rising greenhouse gas concentrations, demonstrating the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found previously in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin. Plain Language Summary: Measurements show clear evidence of warming over the twentieth century and up to the present day. Our anticipation of future change comes from computer models of climate. These are based upon well‐established physical principles like Newton's laws of motion and radiative transfer theory; the models are closely related to those used for weather forecasting. We can never predict the weather on a particular day, 50 years in the future, but we can calculate whether that future decade will be warmer than our present climate. Part of our confidence in such a forecast comes from testing a climate model's ability to reproduce warming and other changes measured over the past century. We use observations of atmospheric composition and the sunlight received by our planet to calculate how the model responds to their changes. The climate model of the NASA Goddard Institute for Space Studies, GISS‐E2.1, closely follows changes measured in the ocean and atmosphere as the concentrations of greenhouse gases and other pollutants rise. This agreement suggests that future warming by greenhouse gases will be reliably predicted by GISS‐E2.1. This suggests that the warming we already experience is due to our consumption of fossil fuels that has led to the increase of carbon dioxide and other greenhouse gases in the atmosphere over the past two centuries. Key Points: Tropospheric warming and ocean heat uptake by 2014 are smaller in GISS‐E2.1 and closer to observed trends than in its CMIP5 predecessorGISS‐E2.1 climate sensitivity is higher than in CMIP5 GISS‐E2, but forcing by greenhouse gases is smallerAtmospheric trends vary among model configurations with the storage of heat beneath the thermocline [ABSTRACT FROM AUTHOR]

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 (358-758) 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 0.8-1.6Wm-2 per kelvin SST increase (358-758N) and 1.2-1.9Wm-2 per kelvin SST increase (358-758S). 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. [ABSTRACT FROM AUTHOR]

Model calibration (or "tuning") is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target. [ABSTRACT FROM AUTHOR]

Partitioning of convective ice into precipitating and detrained condensate presents a challenge for GCMs since partitioning depends on the strength and microphysics of the convective updraft. It is an important issue because detrainment of ice from updrafts influences the development of stratiform anvils, impacts radiation, and can affect GCM climate sensitivity. Recent studies have shown that the CM1P5 configurations of the Goddard Institute for Space Studies (GISS) GCM simulated upper-tropospheric ice water content (IWC) that exceeded an estimated upper bound by a factor of 2. Partly in response to this bias, a new GCM parameterization of convective cloud ice has been developed that incorporates new ice particle fall speeds and convective outflow particle size distributions (PSDs) from the NASA African Monsoon Multidisciplinary Analyses (NAMMA), NASA Tropical Composition Cloud and Climate Coupling (TC4), DOE ARM-NASA Midlatitude Continental Convective Clouds Experiment (MC3E), and DOE ARM Small Particles in Cirrus (SPARTICUS) field campaigns The new parameterization assumes a normalized gamma PSD with two novel developments: no explicit assumption for particle habit in the calculation of mass distributions, and a formulation for translating ice particle fall speeds as a function of maximum diameter intofall speeds as a function of melted-equivalent diameter. Two parameters (particle volume- and projected area-weighted equivalent diameter) are diagnosed as a function of temperature and IWC in the convective plume, and these parameters constrain the shape and scale of the normalized gamma PSD. The diagnosed fall speeds and PSDs are combined with the GCM's parameterized convective updraft vertical velocity to partition convective updraft condensate into precipitating and detrained components. A 5-yr prescribed sea surface temperature GCM simulation shows a 30%-50% decrease in upper-tropospheric deep convective IWC, bringing the tropical and global mean ice water path into closer agreement with CloudSat best estimates. [ABSTRACT FROM AUTHOR]