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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]

We utilize ocean 10‐m wind speed (U10m) from the microwave Multi‐sensor Advanced Climatology data set to examine the coupling between convective cloud and precipitation processes, synoptic state, and U10m and to evaluate the representation of U10m in global climate models (GCMs). We find that midlatitude U10m is underestimated by GCMs relative to observations. We examine two potential mechanisms to explain this model behavior: cold pool formation in cold air outbreaks (CAOs) associated with downdrafts that enhance U10m and sea surface temperature (SST) gradients affecting U10m through thermally forced surface winds at regional scales. When the effects of the CAO index (M) and SST gradients on U10m are accounted for, a relationship between GCM horizontal resolution and U10m appears. The strongest correlation between resolution and U10m is over the western boundary currents characterized by frequent CAOs atop strong SST gradients which drives the strongest surface fluxes on Earth. Plain Language Summary: Surface wind drives the exchange of momentum and energy between the atmosphere and ocean, forcing movement of ocean surface water that impacts the circulation responsible for transporting heat and carbon. It is thus important to study how well global climate models (GCMs) simulate near surface winds. Here, we show an underestimation of ocean surface wind in the latest‐generation of GCMs and examine how an underestimation of ocean surface winds covaries with biases in surface temperature and fine‐scale precipitation‐driven circulations. We show the effect of model horizontal grid resolution on the wind speed bias and analyze surface wind speed bias occurrence in western boundary currents. Key Points: Coupled model intercomparison project (CMIP6) models underestimate midlatitude ocean surface wind speed compared to spaceborne microwave radiometersSimulated ocean surface wind speed bias scales with model resolution at a magnitude strongly influenced by meteorologyOcean surface wind speed bias is most correlated with resolution in western boundary currents [ABSTRACT FROM AUTHOR]

The Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988-2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) intercalibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2, and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and the monthly mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, correcting for a CLWP bias (based on matchups to clear-sky MODIS scenes), and constructing a total (cloud + rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e., CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from −15% (e.g., global oceanic stratocumulus decks) to +5%-10% (e.g., portions of the higher latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Sciences Data and Information Services Center. [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]

The Goddard profiling algorithm (GPROF) uses Bayesian probability theory to retrieve rainfall over the global oceans. A critical component of GPROF and most Bayes theorem-based retrieval frameworks is the specification of uncertainty in the observations being utilized to retrieve the parameter of interest. In the case of GPROF, for any sensor, uncertainties in microwave brightness temperatures (Tbs) arise from radiative transfer model errors, satellite sensor noise and/or degradation, and nonlinear, scene-dependent Tb offsets added during sensor intercalibration procedures. All mentioned sources impact sensors in a varying fashion, in part because of sensor-dependent fields of view. It is found that small errors in assumed Tb uncertainty (ranging from 0.57 K at 10 GHz to 2.29 K at 85 GHz) lead to a 3.6% change in the retrieved global-average oceanic rainfall rate, and 10%-20% (20%-40%) shifts in the pixel-level (monthly) frequency distributions for given rainfall bins. A mathematical expression describing the sensitivity of retrieved rainfall to uncertainty is developed here. The strong global sensitivity is linked to rainfall variance scaling systematically as Tb varies. For ocean scenes, the same emission-dominated rainfall-Tb physics used in passive microwave rainfall retrieval is also responsible for the substantial underestimation (overestimation) of global rainfall if uncertainty is overestimated (underestimated). Proper uncertainties are required to quantify variability in surface rainfall, assess long-term trends, and provide robust rainfall benchmarks for general circulation model evaluations. The implications for assessing global and regional biases in active versus passive microwave rainfall products, and for achieving rainfall product agreement among a constellation of orbiting microwave radiometers [employed in the Global Precipitation Measurement (GPM) mission], are also discussed. [ABSTRACT FROM AUTHOR]

Utilizing data from the Quick Scatterometer (QuikSCAT), a new observational parameter related to mesoscale cold pool activity [termed cold pool kinetic energy (CPKE)] is developed and investigated. CPKE and the Climate Prediction Center (CPC) morphing technique (CMORPH) rainfall product (both scaled to 2.25°) are geolocated to 25 tropical island radiosonde sites. CPKE and radiosonde-derived nondilute CAPE, entraining CAPE (ECAPE), saturation fraction, and a new measure of convective inhibition (that takes into account stable layers above the LFC) are investigated with respect to rainfall time tendencies. Over the life cycle of rainfall, the composite temporal evolutions of CPKE and convective inhibition are quantitatively similar, but slightly out of phase. The maximum in CPKE precedes the maximum in convective inhibition by 3-6 h, thus allowing for an oscillation in the ratio of convective inhibition to CPKE relative to maximum rainfall. This ratio falls below unity at the time rainfall begins increasing and averages to near unity over the entire life cycle. These results imply a lagged, coupled relationship between CPKE and convective inhibition during rainfall. The rapid increase in rainfall occurs when saturation fraction and ECAPE exceed approximately 70% and 280 J kg-1, respectively, consistent with previously noted thresholds for deep convection transition. However, since similar thermodynamic conditions are found before the increase in rainfall, observations support a hypothesis that the onset time for transition from light to heavy rainfall occurs when triggering energy (as captured in CPKE) approaches and exceeds convective inhibition. The observed onset and time scale for CAPE depletion by convection is nearly equivalent to the initial temporal appearance and time duration (6-12 h) that CPKE exceeds convective inhibition. [ABSTRACT FROM AUTHOR]

A K-means clustering algorithm was used to classify Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) scenes within 1° square patches over the tropical (15°S–15°N) oceans. Three cluster centroids or “regimes” that minimize the Euclidean distance metric in a five-dimensional space of standardized variables were sought [convective surface rainfall rate; ratio of convective rain to total rain; and fractions of convective echo profiles with tops in three fixed height ranges (<5, 5–9, and >9 km)]. Independent cluster computations in adjacent ocean basins return very similar clusters in terms of PR echo-top distributions, rainfall, and diabatic heating profiles. The clusters consist of shallow convection (SHAL cluster), with a unimodal distribution of PR echo tops and composite diabatic heating rates of ∼2 K day−1 below 3 km; midlevel convection (MID-LEV cluster), with a bimodal distribution of PR echo tops and ∼5 K day−1 heating up to about 7 km; and deeper convection (DEEP cluster), with a multimodal distribution of PR echo tops and >20 K day−1 heating from 5 to 10 km. Each contributes roughly 20%–40% in terms of total tropical rainfall, but with MID-LEV clusters especially enhanced in the Indian and Atlantic sectors, SHAL relatively enhanced in the central and east Pacific, and DEEP most prominent in the western Pacific. While the clusters themselves are quite similar in rainfall and heating, specific cloud types defined according to the PR echo top and surface rainfall rate are less similar and exhibit systematic differences from one cluster to another, implying that the degree to which precipitation structures are similar decreases when one considers individual precipitating clouds as repeating tropical structures instead of larger-scale cluster ensembles themselves. [ABSTRACT FROM AUTHOR]

In light of the upcoming launch of the Global Precipitation Measurement (GPM) mission, a parametric retrieval algorithm of the nonraining parameters over the global oceans is developed with the ability to accommodate all currently existing and planned spaceborne microwave window channel sensors and imagers. The physical retrieval is developed using all available sensor channels in a full optimal estimation inversion. This framework requires that retrieved parameters be physically consistent with all observed satellite radiances regardless of the sensor being used. The retrieval algorithm has been successfully applied to the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), the Special Sensor Microwave Imager (SSM/I), and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) with geophysical parameter retrieval results comparable to independent studies using sensor-optimized algorithms. The optimal estimation diagnostics characterize the retrieval further, providing errors associated with each of the retrieved parameters, indicating whether the retrieved state is physically consistent with observed radiances, and yielding information on how well simulated radiances agree with observed radiances. This allows for the quantitative assessment of potential calibration issues in either the model or sensor. In addition, there is an expected, consistent response of these diagnostics based on the scene being observed, such as in the case of a raining scene, allowing for the emergence of a rainfall detection scheme providing a new capability in rainfall identification for use in passive microwave rainfall and cloud property retrievals. [ABSTRACT FROM AUTHOR]

Aerosol‐cloud interactions (ACI) in warm clouds are the primary source of uncertainty in effective radiative forcing (ERF) during the historical period and, by extension, inferred climate sensitivity. The ERF due to ACI (ERFaci) is composed of the radiative forcing due to changes in cloud microphysics and cloud adjustments to microphysics. Here, we examine the processes that drive ERFaci using a perturbed parameter ensemble (PPE) hosted in CAM6. Observational constraints on the PPE result in substantial constraints in the response of cloud microphysics and macrophysics to anthropogenic aerosol, but only minimal constraint on ERFaci. Examination of cloud and radiation processes in the PPE reveal buffering of ERFaci by the interaction of precipitation efficiency and radiative susceptibility. Plain Language Summary: Uncertainty in predicting future global temperature inferred from the historical record of warming is dominated by how much the warming due to greenhouse gases has been offset by the cooling due to aerosols. Aerosols are small liquid and solid particles that play an important role in cloud formation. The majority of cooling from aerosols is through reflecting incoming solar radiation back to space by cloud. In this study, we constrain an ensemble of possible global model configurations with observations of cloud properties and radiation to reduce uncertainty in the response of clouds and ultimately radiation to anthropogenic aerosol. While observations substantially reduce the uncertainty in both changes in the number of droplets and amount of liquid cloud, the constraint on aerosol cooling is minimal. We argue that the relatively weak constraint is because large changes in cloudiness are accompanied by small change in reflected sunlight due to increased cloudiness. Key Points: Models with lower precipitation efficiency result in larger mean‐state liquid water path (LWP) and larger adjustments in LWP to aerosolLarger mean‐state LWP coincides with lower albedo susceptibility to LWPThe combination of these processes results in buffering of the radiative effect of LWP adjustments [ABSTRACT FROM AUTHOR]

The new TROPESS (TRopospheric Ozone and its Precursors from Earth System Sounding) profile retrievals of carbon monoxide (CO) from the Cross-track Infrared Sounder (CrIS) are evaluated against Measurement of Pollution in the Troposphere (MOPITT) CO version 9 data. Comparison results that were adjusted to common a priori constraints in the retrieval processes have improved agreement between the two data sets over direct comparisons. TROPESS-CrIS CO profiles are within 5 % of MOPITT but have higher concentrations in the lower troposphere and lower concentrations in the upper troposphere. For the intense western US wildfire events in September 2020, we compare CO fields simulated by the GISS climate model to the two satellite CO observations. We show intermediate steps of the comparison process to illustrate the evaluation of model simulations by deriving the "retrieved" model CO profiles as they would be observed by the satellite. This includes the application of satellite level-2 data along with their corresponding diagnostic operators provided in the TROPESS-CrIS and MOPITT products. The process allows a diagnosis of potential model improvements in modeling fire emissions and pollution transport. [ABSTRACT FROM AUTHOR]

Using 10 years of satellite‐borne radar and lidar observations coupled with a novel method for automated occlusion identification, composite transects of cloud and precipitation across occluded thermal ridges of extratropical cyclones are, for the first time, constructed. These composites confirm that occluded sectors are characterized by the most extensive cloud cover and heaviest precipitation in any of the frontal regions of the cyclone. Hydrometeor frequency in occluded sectors is sensitive to the cyclone's ascent strength but not to the mean precipitable water in the cyclone's environment. This result is in contrast to the strong relationships between hydrometeor frequency and both precipitable water and ascent strength as previously reported in warm frontal regions. In both hemispheres, cloud and precipitation increase with the maximum value of the equivalent potential temperature at 700 hPa within the occluded thermal ridge, until a threshold is reached. For very large values of maximum equivalent potential temperature, hydrometeors become less frequent while precipitation rates increase. It is suggested that this conjunction is a by‐product of an increase in the frequency of convection in those instances. While in the Northern Hemisphere occluded sectors exhibit deeper and wider cloud structures than their Southern Hemisphere counterparts, their hydrometeor occurrence frequencies are less. The differences in maximum equivalent potential temperature of the thermal ridges in both hemispheres does not appear to explain the more frequent hydrometeors in the Southern Hemisphere. These relationships offer new perspectives on the interplay between cloud processes and cyclone evolution, as well as new observational constraints for process evaluation of Earth system models. [ABSTRACT FROM AUTHOR]

This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi-dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface). [ABSTRACT FROM AUTHOR]

Marine cold-air outbreaks (CAOs) occur in the postfrontal sector of midlatitude storms, usually accompanied by dry intrusions (DIs) shaping the free-tropospheric (FT) air aloft. Substantial rain initiates overcast to broken regime transitions in marine boundary layer (MBL) cloud decks that form where cold air first meets relatively high sea surface temperatures. An exemplary CAO in the northwest Atlantic shows earlier transitions (corresponding to reduced extents of overcast clouds) closer to the low pressure center. We hypothesize that gradients in the meteorological pattern imposed by the prevailing DI induced a variability in substantial rain onset and thereby transition. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MBL trajectories to show that postfrontal trajectories closer to the low pressure center are more favorable to rain formation (and thereby cloud transitions) because of 1) weaker FT subsidence rates, 2) greater FT humidity, 3) stronger MBL winds, and 4) a colder MBL with reduced lower-tropospheric stability. LES confirms the observed variability in transitions, with substantial rain appearing earlier where there is swifter reduction of cloud condensation nucleus (CCN) concentration and increase of liquid water path (LWP). Prior to substantial rain, CCN budgets indicate dominant loss terms from FT entrainment and hydrometeor collisions. LWP-enhancing cloud thickness increases more rapidly for weaker large-scale subsidence that enables faster MBL deepening. Mere MBL warming and moistening cannot explain cloud thickness increases. The generality of such a DI-imposed cloud transition pattern merits further investigation with more cases that may additionally be convoluted by onshore aerosol gradients. Significance Statement: Cold-air outbreaks (CAOs) lead to marine boundary layer (MBL) clouds that commonly undergo rain-initiated overcast to broken cloud regime transitions that can drastically impact reflected solar radiation. We aim to better understand what mechanisms control these transitions. For a CAO event in the northwest Atlantic that shows earlier transitions closer to the low pressure center, we find the transition timing to be largely governed by the coinciding dry intrusion that imposes an inhomogeneous large-scale meteorological pattern onto the overlying free troposphere and thereby affects MBL rain formation. Our findings update conceptual understanding of extratropical cyclones and motivate analyzing observations and conducting simulations for more postfrontal cases through a Lagrangian perspective as done here for one case, to assess the generality of our findings. [ABSTRACT FROM AUTHOR]

A novel automated scheme for identifying occluded mid‐latitude cyclones from gridded datasets is described and employed to construct a limited climatology of such storms as well as composites of their thermodynamic and kinematic structures. The climatology (2006–2017) is derived from the MERRA‐2 reanalysis and reveals differences in the distribution of occlusions between the hemispheres. Northern Hemisphere occlusions are most frequent in winter (DJF) and are found poleward of the mean tropopause‐level jets in both the Atlantic and Pacific basins. In the Southern Hemisphere, however, occlusions are most frequent during autumn (MAM) and are almost never found equatorward of 40∘S$$ {40}^{\circ}\mathrm{S} $$. Using the identification scheme, wintertime occlusions are stratified based upon the value of 700 hPa θe$$ {\theta}_{\mathrm{e}} $$ (equivalent potential temperature) in their characteristic thickness ridges. Composites of six groups of occlusions, based upon this distinction, are constructed for each hemisphere. The composites reveal notable differences in the thermodynamic structures among these six groups with more poleward (lower θe$$ {\theta}_{\mathrm{e}} $$ or "colder") storms exhibiting shallower, less developed thermal structures as compared to their lower‐latitude (higher θe$$ {\theta}_{\mathrm{e}} $$ or "warmer") counterparts. These differences are attended by contrasts in the intensity of upward vertical motions in the occluded sectors of the various composite storms implying that "warm" storms are associated with greater latent heat release than "colder" storms. It is suggested that these coincident differences between "cold" and "warm" storms provide further evidence of the fundamental importance of latent heat release to the development of occluded thermal structures. [ABSTRACT FROM AUTHOR]

In this study, observed cloud liquid water path (LWP) trends from the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) dataset (1988-2014) are compared to trends computed from the temporally coincident records of 16 global climate models (GCMs) participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). For many regions, observed trend magnitudes are several times larger than the corresponding model mean trend magnitudes. Muted model mean trends are thought to be the result of cancellation effects arising from differing interannual variability characteristics and differences in model physics-dynamics. In most regions, the majority of modeled trends were statistically consistent with the observed trends. This was thought to be because of large estimated errors in both the observations and the models due to interannual variability. Over the southern oceans (south of 40°S latitude), general agreement between the observed trend and virtually all GCM trends is also found (about 1-2 g m−2 decade−1). Observed trends are also compared to those from the Atmospheric Model Intercomparison Project (AMIP). Like the CMIP5 models, the majority of modeled AMIP trends were statistically consistent with the observed trends. It was also found that, in regions where the AMIP model mean time series better captures observed interannual variability, it tends to better capture the magnitude of the observed trends. [ABSTRACT FROM AUTHOR]

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates toin situobservations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. ‘climate method’) demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45–88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1° × 1° spatial/1 month temporal resolution, and highest associated with a 3° × 3° spatial/3 month temporal resolution). The second framework (i.e. ‘weather method’) explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50% of the daily uncertainty variability, with only limited dependence on the regions of interest. [ABSTRACT FROM PUBLISHER]

An unphysical checkerboard pattern is identified in E3SMv2 and E3SM-MMF that is detectable across a wide range of timescales, from instantaneous snapshots to multi-year averages. A detection method is developed to quantify characteristics of the checkerboard signal by cataloguing all possible configurations of the eight adjacent neighbors for each cell on the model's cubed sphere grid using daily mean data. The checkerboard pattern is only found in cloud-related quantities, such as precipitation and liquid water path. Instances of pure and partial checkerboard are found to occur more often in E3SMv2 and E3SM-MMF when compared to satellite data regridded to the model grid. Continuous periods of partial checkerboard state are found to be more persistent in both models compared to satellite data, with E3SM-MMF exhibiting more persistence than E3SMv2. The checkerboard signal in E3SMv2 is found to be a direct consequence of the recently added deep convective trigger condition based on dynamically generated CAPE (DCAPE). In E3SM-MMF the checkerboard signal is found to be associated with the "trapping" of cloud-scale fluctuations within the embedded cloud-resolving model. Solutions to remedy this issue are discussed. [ABSTRACT FROM AUTHOR]

Column water vapor (CWV) is studied using data from the Dynamics of the Madden-Julian Oscillation (DYNAMO) field experiment. A distinctive moist mode in tropical CWV probability distributions motivates the work. The Lagrangian CWV tendency (LCT) leaves together the compensating tendencies from phase change and vertical advection, quantities that cannot be measured accurately by themselves, to emphasize their small residual, which governs evolution. The slope of LCT versus CWV suggests that the combined effects of phase changes and vertical advection act as a robust positive feedback on CWV variations, while evaporation adds a broadscale positive tendency. Analyzed diabatic heating profiles become deeper and stronger as CWV increases. Stratiform heating is found to accompany Lagrangian drying at high CWV, but its association with deep convection makes the mean LCT positive at high CWV. Lower-tropospheric wind convergence is found in high-CWV air masses, acting to shrink their area in time. When ECMWF heating profile indices and S-Pol and TRMM radar data are binned jointly by CWV and LCT, bottom-heavy heating associated with shallow and congestus convection is found in columns transitioning through Lagrangian moistening into the humid, high-rain-rate mode of the CWV distribution near 50-55 mm, while nonraining columns and columns with widespread stratiform precipitation are preferentially associated with Lagrangian drying. Interpolated sounding-array data produce substantial errors in LCT budgets, because horizontal advection is inaccurate without satellite input to constrain horizontal gradients. [ABSTRACT FROM AUTHOR]

Life cycles of deep convective raining systems are documented through use of a Lagrangian tracking algorithm applied to high-resolution Climate Prediction Center morphing technique (CMORPH) rainfall data, permitting collocation with related environmental ancillary fields and the International Satellite Cloud Climatology Project (ISCCP) cloud states (Rossow et al. 2005). System life cycles are described in terms of propagation speed, duration, and dominant cloud structures. Tracked systems are usually associated with the ISCCP weather state 1 (WS1) deep convection cloud state and an independent, microwave-based deep convective precipitation regime developed here. The distribution and characteristics of tracked systems are found to be similar between ocean basins in terms of system speed and duration, with westward-propagating systems predominant in every basin. The effects that these systems have on environmental parameters are assessed, stratified according to their average propagation speed and by ocean basin. Regardless of system speed the net effect on the environment is similar, with the largest difference being how quickly changes occur, with net surface radiation decreasing about 150 W m−2 and total precipitable water perturbed by 5-7 kg m−2; sea surface temperature (SST) drops 0.2°-0.3°C over 24 h, with system speed affecting how long SSTs remain depressed. The observed drop in SST is partly caused by the presence of widespread, optically thick clouds that greatly decrease the net surface radiative flux. Quick changes in SSTs caused by tracked systems are captured by buoys but not represented well in gridded SST products, as these regions remain largely under the precipitating cloud cover associated with these systems. [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]

An unphysical checkerboard pattern is identified in E3SMv2 and E3SM-MMF that is detectable across a wide range of time scales, from instantaneous snapshots to multi-year averages. A detection method is developed to quantify characteristics of the checkerboard signal by cataloguing all possible configurations of the 8 adjacent neighbors for each cell on the model’s cubed sphere grid using daily mean data. The checkerboard pattern is only found in cloud related quantities, such as precipitation and liquid water path. Instances of pure and partial checkerboard are found to occur more often in E3SMv2 and E3SM-MMF when compared to satellite data regridded to the model grid. Continuous periods of partial checkerboard state are found to be more persistent in both models compared to satellite data, with E3SM-MMF exhibiting more persistence than E3SMv2. The checkerboard signal in E3SMv2 is found to be a direct consequence of the recently added deep convective trigger condition based on dynamically generated CAPE (DCAPE). In E3SM-MMF the checkerboard signal is found to be associated with the "trapping" of cloud scale fluctuations within the embedded CRM. Solutions to remedy this issue are discussed. [ABSTRACT FROM AUTHOR]

Raindrop size distribution (DSD) retrievals from two years of data gathered by the Tropical Rainfall Measuring Mission (TRMM) satellite and processed with a combined radar-radiometer algorithm over the oceans equatorward of 35° are examined for relationships with variables describing properties of the vertical precipitation profile, mesoscale organization, and background environment. In general, higher freezing levels and relative humidities (tropical environments) are associated with smaller reflectivity-normalized median drop size ( εϵDSD) than in the extratropics. Within the tropics, the smallest εϵDSD values are found in large, shallow convective systems where warm rain formation processes are thought to be predominant, whereas larger sizes are found in the stratiform regions of organized deep convection. In the extratropics, the largest εϵDSD values are found in the scattered convection that occurs when cold, dry continental air moves over the much warmer ocean after the passage of a cold front. These relationships are formally attributed to variables describing the large-scale environment, mesoscale organization, and profile characteristics via principal component (PC) analysis. The leading three PCs account for 23% of the variance in εϵDSD at the individual profile level and 45% of the variance in 1°-gridded mean values. The geographical distribution of εϵDSD is consistent with many of the observed regional reflectivity-rainfall ( Z- R) relationships found in the literature as well as discrepancies between the TRMM radar-only and radiometer-only precipitation products. In particular, midlatitude and tropical regions near land tend to have larger drops for a given reflectivity, whereas the smallest drops are found in the eastern Pacific Ocean intertropical convergence zone. [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]

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]

Using multiple independent satellite and reanalysis datasets, we compare relationships between mesoscale convective system (MCS) precipitation intensity Pmax, environmental moisture, large-scale vertical velocity, and system radius among tropical continental and oceanic regions. A sharp, nonlinear relationship between column water vapor and Pmax emerges, consistent with nonlinear increases in estimated plume buoyancy. MCS Pmax increases sharply with increasing boundary layer and lower free tropospheric (LFT) moisture, with the highest Pmax values originating from MCSs in environments exhibiting a peak in LFT moisture near 750 hPa. MCS Pmax exhibits strikingly similar behavior as a function of water vapor among tropical land and ocean regions. Yet, while the moisture–Pmax relationship depends strongly on mean tropospheric temperature, it does not depend on sea surface temperature over ocean or surface air temperature over land. Other Pmax-dependent factors include system radius, the number of convective cores, and the large-scale vertical velocity. Larger systems typically contain wider convective cores and higher Pmax, consistent with increased protection from dilution due to dry air entrainment and reduced reevaporation of precipitation. In addition, stronger large-scale ascent generally supports greater precipitation production. Last, temporal lead–lag analysis suggests that anomalous moisture in the lower–middle troposphere favors convective organization over most regions. Overall, these statistics provide a physical basis for understanding environmental factors controlling heavy precipitation events in the tropics, providing metrics for model diagnosis and guiding physical intuition regarding expected changes to precipitation extremes with anthropogenic warming. [ABSTRACT FROM AUTHOR]

This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7–3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks. Plain Language Summary: This paper describes the latest iteration of the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) climate model, which will be used for understanding historical climate change and to make projections for the future. We compare the model output to a wide range of observations over the recent era (1979–2014) and show that there has been a significant increase in how well the model performs compared to the previous version from 2014, particularly in the Southern Ocean, though some persistent biases remain. The model has a temperature response to the increase of carbon dioxide that is slightly higher than previous versions but is well within the range expected from observational and past climate constraints. Key Points: GISS‐E2.1 is an updated climate model version for use within the CMIP6 projectAtmospheric composition is calculated consistently in all model versionsResults demonstrate a significant improvement in skill in a climate model without changes to atmospheric resolution [ABSTRACT FROM AUTHOR]

This study provides observational evidence for feedbacks that amplify the short-term hydrological response associated with the warm phase of the El Niño-Southern Oscillation. Our analyses make use of a comprehensive set of independent satellite observations collected over decades to show that much larger local changes to cloud (~50%/K) and precipitation (~60%/K) occur than would be expected from the guidance of Clausius-Clapeyron theory (~7%/K). This amplification comes from atmospheric feedbacks involving shifts in the patterns of latent and radiative heating that mutually act on the dynamics enhancing changes to the hydrological cycle. We also confirm the existence of an opposing negative flux feedback at the ocean surface, driven largely by solar radiation changes, that opposes the surface warming. Estimates of the strength of this and other feedback factors associated with warming in the Niño3 region are provided from observations. These observations are also used to examine comparative processes and feedbacks in model experiments from the Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project. [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]

Both the Goddard Profiling Algorithm (GPROF) and European Centre for Medium-Range Weather Forecasts (ECMWF) one-dimensional + four-dimensional variational analysis (1D+4D-Var) rainfall retrievals are inversion algorithms based on Bayes' theorem. Differences stem primarily from the a priori information. The GPROF uses an observationally generated a priori database whereas ECMWF 1D-Var uses the model forecast first guess (FG) fields. The relative similarity in the two approaches means that comparisons can shed light on the differences that are produced by the a priori information. Case studies have found that differences can be classified into four categories based upon the agreement in the brightness temperatures ( Tbs) and in the microphysical properties of cloud water path (CWP) and rainwater path (RWP) space. A category of special interest is when both retrievals converge to similar Tb through minimization procedures but produce different CWP and RWP. The similarity in T b can be attributed to comparable total water path (TWP) between the two retrievals while the disagreement in the microphysics is caused by their different degrees of constraint of the cloud/rain ratio by the observations. This situation occurs frequently and takes up 46.9% in the 1 month 1D-Var retrievals examined. The two retrievals produce similar spatial patterns but with different magnitude. The allocation of a large amount of CWP in the 1D-Var retrieval seems to be related to the stratiform portion of rain, which is produced by the large-scale condensation scheme. To attain better-constrained cloud/rain ratios and improved retrieval quality, this study suggests the implementation of higher microwave frequency channels in the 1D-Var algorithm. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

In mid-August 2017, a massive smoke plume originating over northern Canada was tracked during its transport to Europe, over the North Pole, and around the world. The impact of this smoke on the aerosol load of the lower stratosphere has recently been compared to that of a moderate volcanic eruption. We conducted simulations of the smoke plume using the NASA GISS ModelE coupled chemistry climate model to understand the chemical evolution and radiative impacts of the smoke at the surface, using the event as a natural experiment with which to better understand direct aerosol effects. Above boundary-layer smoke injection and emissions with daily temporal resolution were required to deliver smoke to high altitudes and to capture its synoptic transport relative to satellite retrievals of trace gases and aerosols. By comparing experiments with and without the extreme fire emissions, we estimated daytime cooling at the surface of 5-10 °C under the thickest parts of the plume for several days. This surface cooling was consistent with discrepancies between operational weather forecasts and observed surface temperature. [ABSTRACT FROM AUTHOR]