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Vertical velocities and microphysical processes within deep convection are intricately linked, having wide-ranging impacts on water and mass vertical transport, severe weather, extreme precipitation, and the global circulation. The goal of this research is to investigate the functional form of the relationship between vertical velocity (w) and microphysical processes that convert water vapor into condensed water (M) in deep convection. We examine an ensemble of high-resolution simulations spanning a range of tropical and midlatitude environments, a variety of convective organizational modes, and different model platforms and microphysics schemes. The results demonstrate that the relationship between w and M is robustly linear, with the slope of the linear fit being primarily a function of temperature and secondarily a function of supersaturation. The R2 of the linear fit is generally above 0.6 except near the freezing and homogeneous freezing levels. The linear fit is examined both as a function of local in-cloud temperature and environmental temperature. The results for in-cloud temperature are more consistent across the simulation suite, although environmental temperatures are more useful when considering potential observational applications. The linear relationship between w and M is substituted into the condensate tendency equation and rearranged to form a diagnostic equation for w. The performance of the diagnostic equation is tested in several simulations, and it is found to diagnose the storm-scale updraft speeds to within 1 m s−1 throughout the upper half of the clouds. Potential applications of the linear relationship between w and M and the diagnostic w equation are discussed.

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

The Orbiting Carbon Observatory 2 (OCO-2) carries a hyperspectral A-band sensor that can obtain information about cloud geometric thickness (H). The OCO2CLD-LIDAR-AUX product retrieved H with the aid of collocated CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar data to identify suitable clouds and provide a priori cloud top pressure (Ptop). This collocation is no longer possible, since CALIPSO's coordination flying with OCO-2 has ended, so here we introduce a new cloud flagging and a priori assignment using only OCO-2 data, restricted to ocean footprints where solar zenith angle <45∘. Firstly, a multi-layer perceptron network was trained to identify liquid clouds over the ocean with sufficient optical depth (τ>1) for a valid retrieval, and agreement with MODIS–CALIPSO (Moderate Resolution Imaging Spectroradiometer) is 90.0 %. Secondly, we developed a lookup table to simultaneously retrieve cloud τ, effective radius (re) and Ptop from A-band and CO2 band radiances, with the intention that these will act as the a priori state estimate in a future retrieval. Median Ptop difference vs. CALIPSO is 12 hPa with an inter-decile range of [-11,87]hPa, substantially better than the MODIS–CALIPSO range of [-83,81]hPa. The MODIS–OCO-2 τ difference is 0.8[-3.8,6.9], and re is -0.3[-2.8,2.1]µm. The τ difference is due to optically thick and horizontally heterogeneous cloud scenes. As well as an improved passive Ptop retrieval, this a priori information will allow for a purely OCO-2-based Bayesian retrieval of cloud droplet number concentration (Nd). Finally, our cloud flagging procedure may also be useful for future partial-column above-cloud CO2 abundance retrievals.

A technology revolution in Earth observation sensor design is occurring. This revolution in part is associated with the emergence of CubeSat platforms that have forced a de facto standardization on the volume and power into which sensors have to fit. The extent that small sensors can indeed provide similar or replacement capabilities compared to larger and more expensive counterparts has barely been demonstrated and any loss of capability of smaller systems weighed against the gains in costs and new potential capabilities offered by implementing them with a more distributed observing strategy also has not yet been embraced. This paper provides four examples of observations made with prototype miniaturized observing systems, including from CubeSats, that offer a glimpse of this emerging sensor revolution and a hint at future observing system design.

The recent successful space-borne demonstration of a miniaturized CubeSat precipitation radar is highlighted. The low cost of such a radar, together with the availability of small satellite, platforms to carry it, now make it feasible to consider employing a more distributed approach to observe important atmospheric processes that relate to precipitation. An approach to quantify the transport of water and air by deep convection is described based on a clustering of small radar satellites providing measurements seconds apart. This strategy now adds time as a new dimension for observing such processes. A mission concept, referred to as D-train, comprised of a train of three satellites 30, 90, and 120 s apart is described, and the expected performance of it for providing measures of convective transport is examined based on a large ensemble of simulations of convection with an advanced cloud-resolving model.

Recent changes to how clouds are represented in global models, especially over the Southern Ocean, resulted in increased climate warming. Correcting rain processes in a model shows improved cloud representation but leads to a greatly enhanced negative feedback, offsetting documented increases in model climate sensitivity.

This is a COSPAR roadmap to advance the frontiers of science through innovation and international collaboration using small satellites. The world of small satellites is evolving quickly and an opportunity exists to leverage these developments to make scientific progress. In particular, the increasing availability of low-cost launch and commercially available hardware provides an opportunity to reduce the overall cost of science missions. This in turn should increase flight rates and encourage scientists to propose more innovative concepts, leading to scientific breakthroughs. Moreover, new computer technologies and methods are changing the way data are acquired, managed, and processed. The large data sets enabled by small satellites will require a new paradigm for scientific data analysis. In this roadmap we provide several examples of long-term scientific visions that could be enabled by the small satellite revolution. For the purpose of this report, the term “small satellite” is somewhat arbitrarily defined as a spacecraft with an upper mass limit in the range of a few hundred kilograms. The mass limit is less important than the processes used to build and launch these satellites. The goal of this roadmap is to encourage the space science community to leverage developments in the small satellite industry in order to increase flight rates, and change the way small science satellites are built and managed. Five recommendations are made; one each to the science community, to space industry, to space agencies, to policy makers, and finally, to COSPAR.

Recent Arctic sea ice retreat has been quicker than in most general circulation model (GCM) simulations. Internal variability may have amplified the observed retreat in recent years, but reliable attribution and projection requires accurate representation of relevant physics. Most current GCMs do not fully represent falling ice radiative effects (FIREs), and here we show that the small set of Coupled Model Intercomparison Project Phase 5 (CMIP5) models that include FIREs tend to show faster observed retreat. We investigate this using controlled simulations with the CESM1-CAM5 model. Under 1pctCO2 simulations, including FIREs results in the first occurrence of an “ice-free” Arctic (monthly mean extent <1×106 km2) at 550 ppm CO2, compared with 680 ppm otherwise. Over 60–90∘ N oceans, snowflakes reduce downward surface shortwave radiation and increase downward surface longwave radiation, improving agreement with the satellite-based CERES EBAF-Surface dataset. We propose that snowflakes' equivalent greenhouse effect reduces the mean sea ice thickness, resulting in a thinner pack whose retreat is more easily triggered by global warming. This is supported by the CESM1-CAM5 surface fluxes and a reduced initial thickness in perennial sea ice regions by approximately 0.3 m when FIREs are included. This explanation does not apply across the CMIP5 ensemble in which inter-model variation in the simulation of other processes likely dominates. Regardless, we show that FIRE can substantially change Arctic sea ice projections and propose that better including falling ice radiative effects in models is a high priority.

This paper introduces the OCO2CLD-LIDAR-AUX product, which uses the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar and the Orbiting Carbon Observatory-2 (OCO-2) hyperspectral A-band spectrometer. CALIPSO provides a prior cloud top pressure (Ptop) for an OCO-2-based retrieval of cloud optical depth, Ptop and cloud geometric thickness expressed in hPa. Measurements are of single-layer liquid clouds over oceans from September 2014 to December 2016 when collocated data are available. Retrieval performance is best for solar zenith angles <45∘ and when the cloud phase classification, which also uses OCO-2's weak CO2 band, is more confident. The highest quality optical depth retrievals agree with those from the Moderate Resolution Imaging Spectroradiometer (MODIS) with discrepancies smaller than the MODIS-reported uncertainty. Retrieved thicknesses are consistent with a substantially subadiabatic structure over marine stratocumulus regions, in which extinction is weighted towards the cloud top. Cloud top pressure in these clouds shows a 4 hPa bias compared with CALIPSO which we attribute mainly to the assumed vertical structure of cloud extinction after showing little sensitivity to the presence of CALIPSO-identified aerosol layers or assumed cloud droplet effective radius. This is the first case of success in obtaining internal cloud structure from hyperspectral A-band measurements and exploits otherwise unused OCO-2 data. This retrieval approach should provide additional constraints on satellite-based estimates of cloud droplet number concentration from visible imagery, which rely on parameterization of the cloud thickness.

International audience; The direct measurement of Earth's energy imbalance (EEI) is one of the greatest challenges in climate research. The global mean EEI represents the integrated value of global warming and is tightly linked to changes in hydrological cycle and the habitability of our planet. Current space-born radiometers measure the individual radiative components of the energy balance with unprecedented stability, but with calibration errors too large to determine the absolute magnitude of global mean EEI as the components' residual. Best estimates of long-term EEI are currently derived from temporal changes in ocean heat content at ~0.7 Wm-2. To monitor EEI directly from space, we propose an independent approach based on accelerometry that measures non-gravitational forces, such as radiation pressure, acting on Earth orbiting spacecrafts. The concept of deriving EEI from radiation pressure has been considered in the past, and we provide analysis that shows today's capabilities are sufficiently accurate to answer the question: At what rate is our planet warming? To measure global mean EEI to within at least ±0.3 Wm-2 requires spacecraft(s) of near-spherical shape and well-characterized surface properties to reduce confounding effects. The proposed concept may provide the basis for a data record of global and zonal mean EEI on annual and potentially monthly time scales. It is not meant to replace existing concepts designed to measure energy balance components or ocean heat storage, but to complement these by providing an independent estimate of EEI for comparison and to anchor data products and climate models that lack energy balance closure.; La mesure directe du bilan énergétique de la Terre (EEI : Earth's Energy Imbalance) est l'un des plus grands défis de la recherche climatique. L'EEI moyen mondial représente la valeur intégrée du réchauffement climatique; sa variabilité spatiale et temporelle reflète la nature des transport de chaleur à travers le système climatique et les modes climatiques internes tels que l'ENSO. Ces transports de chaleur contrôlent les circulations atmosphériques et océaniques, et désormais le cycle de l'eau et l'habitabilité de notre planète. Les systèmes spatiaux actuels mesurent les composantes radiatives individuelles du bilan énergétique avec une précision et une stabilité sans précédent, mais les limites d'erreur sont trop grossières pour déterminer l'amplitude absolue de l'EEI moyen global ainsi que les résidus des contributeurs. Les meilleures estimations de l'IEE à long terme sont actuellement dérivées des changements de la teneur en chaleur des océans telle que mesurée in situ, mais sont affectées par des erreurs d'échantillonnage. Des méthodes alternatives sont nécessaires pour éviter l'imprécision de l'étalonnage radiométrique et l'échantillonnage incomplet in situ de l'océan. Pour suivre la valeur intégrée de l'EEI à partir de l'espace, nous proposons une approche basée sur l'accélérométrie qui mesure les forces non gravitationnelles, telles que la pression de radiation, agissant sur les satellites en orbite autour de la Terre. Le concept pour déduire l'EEI de la pression de radiation a été considéré dans le passé, et nous fournissons une analyse qui montre que les instruments d'aujourd'hui sont suffisamment précises pour enfin répondre à la question: à quel rythme notre planète se réchauffe-t-elle? Le concept proposé ne vise pas à remplacer les concepts existants conçus pour mesurer les composantes du bilan énergétique, mais à les compléter en fournissant une mesure directe de l'EEI responsable des changements climatiques de notre planète.

This paper introduces the aerosol, clouds, convection and precipitation (ACCP) program that is currently in the process of defining a number of measurement objectives for NASA that are to be implemented toward the end of the current decade. Since a (solar) visible-shortwave infrared (VSWIR) spectrometer is being considered as part of the ACCP architecture, illustrations of the different ways these measurements will contribute to this program and how these measurements can be expected to advance the science objectives of ACCP are highlighted. These contributions range from 1) constraining cloud radiative process and related estimates of radiative fluxes, 2) scene discrimination, 3) providing aerosol and cloud optical properties, and 4) providing other enhanced information such as the phase of water in clouds, and total column water vapor. The spectral measurements also offer new capabilities that will further enhance the ACCP science such as the discrimination of dust aerosol and the potential for the vertical profiling cloud droplet size in shallow clouds. The areas where the maturity of approaches is lacking is also highlighted as a way of emphasizing research topics to be a focus in the coming years.

The latest configuration of the Hadley Centre Global Environmental Model version 3 (HadGEM3) contains significant changes in the formulation of warm rain processes and aerosols. We evaluate the impacts of these changes in the simulation of warm rain formation processes using A-Train observations. We introduce a new model evaluation tool, quartile-based Contoured Frequency by Optical Depth Diagrams (CFODDs), in order to fill in some blind spots that conventional CFODDs have. Results indicate that HadGEM3 has weak linkage between the size of particle radius and warm rain formation processes, and switching to the new warm rain microphysics scheme causes more difference in warm rain formation processes than switching to the new aerosol scheme through reducing overly produced drizzle mode in HadGEM3. Finally, we run an experiment in which we perturb the second aerosol indirect effect (AIE) to study the rainfall-aerosol interaction in HadGEM3. Since the large changes in the cloud droplet number concentration (CDNC) appear in the AIE experiment, a large impact in warm rain diagnostics is expected. However, regions with large fractional changes in CDNC show a muted change in precipitation, arguably because large-scale constraints act to reduce the impact of such a big change in CDNC. The adjustment in cloud liquid water path to the AIE perturbation produces a large negative shortwave forcing in the midlatitudes.

The recently selected NASA mission Libera, named for the daughter of Ceres in Roman mythology, will provide continuity of the Clouds and the Earth’s Radiant Energy System (CERES) Earth radiation budget (ERB) observations from space.Seamless extension of the ERB climate data record is achieved by acquiring integrated radiances over the CERES FM6-heritage broad spectral bands in the shortwave (0.3 to 5 μm), longwave (5 to 50 μm) and total (0.3 to beyond 100 μm). To gain deeper insight into shortwave energy deposition, Libera adds a split-shortwave band (0.7 to 5 μm) that allows to provide deeper insight into shortwave energy deposition.Libera’s advanced detector technologies is based on vertically aligned black-carbon nanotubes with closed-loop electrical substitution radiometry to achieve radiometric uncertainty of approximately 0.2%. Additionally, a wide field-of-view camera is employed to provide scene context and explore pathways for separating future ERB missions from complex imagers.This presentation will summarize Libera’s attributes and mission goals, as well as some of the applications of the camera radiances, and the role of the additional split-shortwave channel that splits the shortwave band into its visible and near-IR contributions. This split is vital for the better understanding of shortwave absorption, feedbacks, and planetary albedo variability. The hemispheric symmetry of planetary albedo, as observed by CERES, is not achieved by most state-of-the-art climate models and is associated with long-standing biases in circulation and cloud properties. We will exemplify the study of processes relevant to albedo symmetry by means of CMIP6 simulations that provide the visible and near-IR fluxes.

The Orbiting Carbon Observatory-2 (OCO-2) carries a hyperspectral A-band sensor that can obtain information about cloud geometric thickness (H). The OCO2CLD-LIDAR-AUX product retrieved H with the aid of collocated CALIPSO lidar data to identify suitable clouds and provide a priori cloud-top pressure (Ptop). This collocation is no longer possible since CALIPSO's coordination flying with OCO-2 has ended, so here we introduce a new cloud flagging and a priori assignment using only OCO-2 data, restricted to ocean footprints where solar zenith angle 1) for a valid retrieval, and agreement with MODIS-CALIPSO is 90.0 %. Secondly, we developed a lookup table to simultaneously retrieve cloud τ, effective radius (re) and Ptop from A-band and CO2 band radiances. Median Ptop difference versus CALIPSO is 12 hPa with interdecile range [−11,87] hPa, substantially better than the MODIS-CALIPSO [−83,81] hPa. The MODIS-OCO-2 τ difference is 0.8 (−3.8,6.9) and re is −0.3 [−2.8,2.1] μm. The tau difference is due to optically thick and horizontally heterogeneous cloud scenes. As well as an improved passive Ptop retrieval, this a priori information will allow a purely OCO-2 based Bayesian retrieval of cloud droplet number concentration (Nd). Finally, our cloud flagging procedure may also be useful for future partial column above-cloud CO2 abundance retrievals.

A review of the progression of cloud physics from a subdiscipline of meteorology into the global science it is today is described. The discussion briefly touches on the important post‐war contributions of three key individuals who were instrumental in developing cloud physics into a global science. These contributions came on the heels of the post‐war weather modification efforts that influenced much of the early development of cloud physics. The review is centred on the properties of warm clouds primarily to limit the scope of the article and the connection between the early contributions to cloud physics and the current vexing problem of aerosol effects on cloud albedo is underlined. Progress toward estimating cloud properties from space and insights on warm cloud processes are described. Measurements of selected cloud properties, such as cloud liquid water path are now mature enough that multi‐decadal time series of these properties exist and this climatology is used to compare to analogous low‐cloud properties taken from global climate models. The too‐wet (and thus too bright) and the too‐dreary biases of models are called out underscoring the challenges we still face in representing warm clouds in Earth system models. We also provide strategies for using observations to constrain the indirect radiative forcing of the climate system.

Progress towards achieving a quantitative understanding of the exchanges of water between Earth's main water reservoirs is reviewed with emphasis on advances accrued from the latest advances in Earth Observation from space. These exchanges of water between the reservoirs are a result of processes that are at the core of important physical Earth-system feedbacks, which fundamentally control the response of Earth's climate to the greenhouse gas forcing it is now experiencing, and are therefore vital to understanding the future evolution of Earth's climate. The changing nature of global mean sea level (GMSL) is the context for discussion of these exchanges. Different sources of satellite observations that are used to quantify ice mass loss and water storage over continents, how water can be tracked to its source using water isotope information and how the waters in different reservoirs influence the fluxes of water between reservoirs are described. The profound influence of Earth's hydrological cycle, including human influences on it, on the rate of GMSL rise is emphasized. The many intricate ways water cycle processes influence water exchanges between reservoirs and thus sea-level rise, including disproportionate influences by the tiniest water reservoirs, are emphasized.

NASA’s Orbiting Carbon Observatory-2 (OCO-2) includes a hyperspectral (Dl~0.02 nm) oxygen A-band sensor, and the depth of its absorption features is related to the photon path length. Photon path length increases above a cloud if it is lower (i.e. higher Ptop), and within a cloud if its droplets are farther apart (i.e. lower N­d). This is a novel approach for retrieving Nd that is independent of MODIS-like retrievals, which take an a priori vertical cloud structure and assume that non-adiabatic processes such as precipitation or entrainment affect clouds uniformly. Our last product, OCO2CLD-LIDAR-AUX, used CALIPSO Ptop to help separate the above- and within-cloud path length. Here we show progress in an updated OCO-2 only retrieval of marine boundary layer clouds, including using neural networks for cloud identification and phase classification, additional retrieval of re, and how cloud vertical structure can bias retrieved Ptop and Nd. Successfully addressing this bias would provide a new and independent Nd retrieval that should capture changes due to non-adiabatic processes, and therefore provide a new test of aerosol cloud effects.

Recent Arctic sea ice retreat has been quicker than the projection in most general circulation model (GCM) simulations. Natural factors may have amplified this, but reliable attribution and projection requires accurate representation of relevant physical processes. In the meeting, we will present results indicating robust links between CloudSat-CALIPSO falling ice and Arctic sea ice melting from observations and global climate modelings. Most current GCMs don’t fully represent falling ice radiative effects (FIREs). We find that a small set of Coupled Model Intercomparison Project, phase 5 (CMIP5) models that include FIREs tend to show a faster Arctic sea ice retreat. We investigate this using controlled simulation with the CESM1-CAM5 model both in present-day and 1%CO2 scenarios. With FIREs, CESM1-CAM5 simulates more realistic present-day annual and seasonal variations of radiation and skin temperatures and Arctic sea ice coverage and thickness. Over 60—90 °N oceans, simulated radiative flux trends are similar but the current-day state differs substantially due to FIREs. Falling ice reduces downward shortwave and increase downward longwave, resulting in an improved agreement with the satellite-based CERES-EBAF surface dataset. Under 1pctCO2 simulations, including FIREs results in the first occurrence of an “ice free” Arctic (extent < 1×106 km2) in year 64, compared with year 91 otherwise. We propose that the equivalent greenhouse effects from falling ice results in fewer safe spaces in which sea ice can thicken during winter, resulting in a thinner pack whose retreat is more easily triggered by global warming. However, this explanation does not apply across the CMIP5 ensemble members. Our results therefore only apply to one model but we have shown that this can have substantial implications for Arctic sea ice projection. Given that falling ice interaction with radiation in reality, we propose that including FIREs in models is a high priority.

We use the Atmospheric Infrared Sounder (AIRS) version 6 ice cloud property and thermodynamic phase retrievals to quantify variability and 14-year trends in ice cloud frequency, ice cloud top temperature (Tci), ice optical thickness (τi) and ice effective radius (rei). The trends in ice cloud properties are shown to be independent of trends in information content and χ2. Statistically significant decreases in ice frequency, τi, and ice water path (IWP) are found in the SH and NH extratropics, but trends are of much smaller magnitude and statistically insignificant in the tropics. However, statistically significant increases in rei are found in all three latitude bands. Perturbation experiments consistent with estimates of AIRS radiometric stability fall significantly short of explaining the observed trends in ice properties, averaging kernels, and χ2 trends. Values of rei are larger at the tops of opaque clouds and exhibit dependence on surface wind speed, column water vapour (CWV) and surface temperature (Tsfc) with changes up to 4–5 µm but are only 1.9 % of all ice clouds. Non-opaque clouds exhibit a much smaller change in rei with respect to CWV and Tsfc. Comparisons between DARDAR and AIRS suggest that rei is smallest for single-layer cirrus, larger for cirrus above weak convection, and largest for cirrus above strong convection at the same cloud top temperature. This behaviour is consistent with enhanced particle growth from radiative cooling above convection or large particle lofting from strong convection.

Information content analysis is used to select channels for a marine liquid cloud retrieval using the high-spectral-resolution oxygen A-band instrument on NASA's Orbiting Carbon Observatory-2 (OCO-2). Desired retrieval properties are cloud optical depth, cloud-top pressure and cloud pressure thickness, which is the geometric thickness expressed in hectopascals. Based on information content criteria we select a micro-window of 75 of the 853 functioning OCO-2 channels spanning 763.5–764.6 nm and perform a series of synthetic retrievals with perturbed initial conditions. We estimate posterior errors from the sample standard deviations and obtain ±0.75 in optical depth and ±12.9 hPa in both cloud-top pressure and cloud pressure thickness, although removing the 10 % of samples with the highest χ2 reduces posterior error in cloud-top pressure to ±2.9 hPa and cloud pressure thickness to ±2.5 hPa. The application of this retrieval to real OCO-2 measurements is briefly discussed, along with limitations and the greatest caution is urged regarding the assumption of a single homogeneous cloud layer, which is often, but not always, a reasonable approximation for marine boundary layer clouds.

Most of the global climate models (GCMs) in the Coupled Model Intercomparison Project, phase 5 do not include precipitating ice (aka falling snow) in their radiation calculations. We examine the importance of the radiative effects of precipitating ice on simulated surface wind stress and sea surface temperatures (SSTs) in terms of seasonal variation and in the evolution of central Pacific El Niño (CP‐El Niño) events. Using controlled simulations with the CESM1 model, we show that the exclusion of precipitating ice radiative effects generates a persistent excessive upper‐level radiative cooling and an increasingly unstable atmosphere over convective regions such as the western Pacific and tropical convergence zones. The invigorated convection leads to persistent anomalous low‐level outflows which weaken the easterly trade winds, reducing upper‐ocean mixing and leading to a positive SST bias in the model mean state. In CP‐El Niño events, this means that outflow from the modeled convection in the central Pacific reduces winds to the east, allowing unrealistic eastward propagation of warm SST anomalies following the peak in CP‐El Niño activity. Including the radiative effects of precipitating ice reduces these model biases and improves the simulated life cycle of the CP‐El Niño. Improved simulations of present‐day tropical seasonal variations and CP‐El Niño events would increase the confidence in simulating their future behavior.

We perform a model-observation comparison and report on the state-of-the-art cloud liquid water content (CLWC) and path (CLWP) outputs from the present-day global climate models (GCMs) simulations in CMIP3/CMIP5, two other GCMs (UCLA and GEOS5) and two reanalyses (ECMWF Interim and MERRA) in comparison with two satellites observational datasets (CloudSat and MODIS). We use two different liquid water observation products from CloudSat and MODIS, for CLWP and their combined product for LWC with a method to remove the contribution from precipitating and convective core hydrometeors so that more meaningful model-observation comparisons can be made. Considering the CloudSat’s limitations of CLWC retrievals due to contamination from the precipitation and from radar clutter near the surface, an estimate CLWC is synergistically constructed using MODIS CLWP and CloudSat CLWC. The model-observation comparison shows that most of the CMIP3/CMIP5 annual mean CLWP values are overestimated by factors of 2 - 10 compared to observations globally. There are a number of CMIP5 models, including CSIRO, MPI, and the UCLA GCM that perform well compared to the other models. For the vertical structure of CLWC, significant systematic biases are found with many models biased significantly high above the mid-troposphere. In the tropics, systematic high biases occur at all levels above 700 hPa. Based on the Taylor diagram, the ensemble performance of CMIP5 CLWP simulation shows little or no improvement relative to CMIP3.

Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and fresh water availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human health, security, and infrastructure. However, the current climate observing system was not planned in a comprehensive, focused manner required to adequately address the full range of climate needs. A potential approach to planning the observing system of the future is presented in this paper. First, this paper proposes that priority be given to the most critical needs as identified within the World Climate Research Program as Grand Challenges. These currently include seven important topics: Melting Ice and Global Consequences; Clouds, Circulation and Climate Sensitivity; Carbon Feedbacks in the Climate System; Understanding and Predicting Weather and Climate Extremes; Water for the Food Baskets of the World; Regional Sea-Level Change and Coastal Impacts; and Near-term Climate Prediction. For each Grand Challenge, observations are needed for long-term monitoring, process studies and forecasting capabilities. Second, objective evaluations of proposed observing systems, including satellites, ground-based and in situ observations as well as potentially new, unidentified observational approaches, can quantify the ability to address these climate priorities. And third, investments in effective climate observations will be economically important as they will offer a magnified return on investment that justifies a far greater development of observations to serve society's needs.

Land skin temperature (Ts) is directly influenced by surface energy balance, in particular, radiative energy, which can be linked to model’s representation of radiative effects of hydrometeors in the atmosphere. This link is inferred by examining the changes of geographical distribution and seasonal cycle of surface radiation, surface turbulent fluxes and Ts between a pair of 140 years sensitivity experiments under 1% per year increase of atmospheric CO2. One is with radiative effects of falling ice (snow) hydrometeors on (SON) and the other off (NOS) using CESM1-CAM5 and the results are compared with CMIP5 models without these effects. For boreal winter, NOS relative to SON simulates less surface downward longwave and net flux (∼10–15 W m−2), resulting in colder Ts (∼2–3 K colder), over mid- and high latitudes, but more solar radiative flux, resulting in warmer Ts (∼1–3 K), over subtropical and tropical land. These differences between NOS and SON are amplified as the surface and the atmosphere become warmer. The results from CMIP5 ensemble generally match with those of NOS. Temporal correlation analysis indicates that the linkage between Ts and falling ice hydrometeor changes is through one between Ts and downward longwave and net fluxes at high latitudes, but strongly weakened by shortwave changes at low latitudes (and boreal summer). Relative to SON, land skin temperatures in NOS and CMIP5 are underestimated throughout the seasonal cycle but only slightly in summer.

This study evaluates changes in simulated Pacific climate between two ECMWF re-analyses; the ERA Interim (ERAI) and the newest ERA5. Changes in the Integrated Forecasting System (IFS) and possibly sea surface temperature result in greatly reduced discrepancies in ERA5’s ice water path (IWP), radiative fluxes and precipitation relative to satellite-based observational products. IWP shows the largest percentage change, increasing by over 300% from ERAI to ERA5, due to inclusion of falling ice (snow) that impacts radiative calculation. ERAI to ERA5 changes in high-cloud fraction are generally anticorrelated as expected with outgoing longwave radiation, with ERA5 having smaller longwave discrepancies versus CERES observations compared with ERAI. Reflected shortwave discrepancies are similarly reduced from ERAI to ERA5, which appears to be due to changes in both cloud fraction and optical depth. Finally, ERA5 also reduces a longstanding precipitation excess relative to the GPCP observational product in the southern trade winds region between the Southern Pacific and intertropical convergence zones. This appears to be related to cooler prescribed sea surface temperatures, thereby reducing local moisture supply via suppressing net latent heat flux and stronger surface trade-winds. Compared with GPCP and CERES, ERA5 shows similar geographic patterns of discrepancies to ERAI in terms of precipitation and top-of-atmosphere radiation, but their magnitudes are greatly reduced in ERA5.

Historical changes of global precipitation in the 20th century simulated by a climate model are investigated. The results simulated with alternate configurations of cloud microphysics are analyzed in the context of energy balance controls on global precipitation, where the latent heat changes associated with the precipitation change is nearly balanced with changes to atmospheric radiative cooling. The atmospheric radiative cooling is dominated by its clear-sky component, which is found to correlate with changes to both column water vapor and aerosol optical depth (AOD). The water vapor-dependent component of the clear-sky radiative cooling is then found to scale with global temperature change through the Clausius–Clapeyron relationship. This component results in a tendency of global precipitation increase with increasing temperature at a rate of approximately 2%K−1. Another component of the clear-sky radiative cooling, which is well correlated with changes to AOD, is also found to vary in magnitude among different scenarios with alternate configurations of cloud microphysics that controls the precipitation efficiency, a major factor influencing the aerosol scavenging process that can lead to different aerosol loadings. These results propose how different characteristics of cloud microphysics can cause different aerosol loadings that in turn perturb global energy balance to significantly change global precipitation. This implies a possible coupling of aerosol–cloud interaction with aerosol–radiation interaction in the context of global energy balance.

Spectra of reflected sunlight in the oxygen A-band contain information about cloud properties such as cloud top pressure, optical depth, and pressure thickness. Here we show, for the first time, that high-spectral-resolution A-band Orbiting Carbon Observatory-2 (OCO-2) spectra respond largely as simulated to the optical properties of water clouds over ocean during November 2015 (N = 184,318) using input cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and the Cloud-Aerosol Lidar with Orthogonal Polarization on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). In A-band continuum channels the standard deviation of simulated minus observed radiance is ±37%. Selecting horizontally homogeneous clouds to mitigate three-dimensional cloud effects and collocation error with the other satellites, the standard deviation of the residuals is reduced to ±18%. Using a look-up table developed from simulations, OCO-2's estimated cloud top pressure for low clouds (Ptop > 680 hPa) has a standard deviation of ±61 hPa relative to CALIPSO retrievals, and bias is dependent on assumed cloud pressure thickness, with our smallest value being −5 hPa. Versus MODIS optical depth, the standard deviation is ±9.0 and the bias is −2.0, although these shrink for clouds of τ