Since 2014, space agencies have launched advanced meteorological imagers into the geostationary (GEO) orbit encircling Earth's equator, known as the GEO-Ring. JMA, NOAA, and KMA launched imagers measuring 16 spectral bands with thermal resolutions of 2 km and full-disk coverage every 10 min. China Meteorological Administration's (CMA's) Fengyun-4A (FY-4A) series, launched in 2016, observes 14 bands with 4-km thermal resolution and 15-min full-disk scans. In 2022, EUMETSAT introduced the Meteosat Third Generation (MTG) imager, offering 16 channels, 2-km thermal resolution, and 10-min full-disk coverage. Together, these satellites provide near-global coverage with improved capabilities over earlier generations. The 10-12 common channels across the latest imagers enable retrieval of diverse atmospheric variables at high temporal resolution. These data represent a substantial advance beyond the early 1980s when the International Satellite Cloud Climatology Project (ISCCP) was first developed. The challenge facing any new GEO-Ring project, such as one being planned as part of a next generation of ISCCP (ISCCP-NG), is to define a new baseline from these measurements and processing methods to extract meaningful information for the scientific community in the coming decades. This paper outlines the design of a GEO-Ring radiance project to support a future ISCCP-NG and many other applications and emphasizes the benefits compared to the B1 and B3 data used in ISCCP.

NASA’s Investigation of Convective Updrafts (INCUS) aims to improve understanding of how, when, and why tropical convective storms form and why only some lead to extreme weather. Much of the vertical transport of water and air between Earth’s surface and the upper troposphere is facilitated by convective storms. This vertical transport of water and air, often referred to as convective mass flux (CMF), plays a critical role in Earth’s weather and climate system through its impacts on precipitation rates, detrainment and upper tropospheric moistening, high cloud feedbacks, and the large-scale circulation. Recent studies have also suggested that CMF may change with changing climates with subsequent implications for flood-producing rainfall, severe weather, and lightning. In spite of the critical role of this vertical transport of water and air within the weather and climate system, much is still not understood about the impacts of CMF on high cloud properties, precipitation rates, and the associated microphysical-dynamical feedbacks. Representation of CMF is also a major source of error in weather and climate models, thereby limiting our ability to predict the microphysical and dynamical properties of convective storms on weather through climate timescales.INCUS seeks to: (1) identify environmental factors controlling CMF in tropical storms; (2) explore the connection between CMF and high anvil clouds; (3) link CMF to storm type and intensity; and (4) evaluate these relationships in models. The INCUS observations will enhance our understanding and prediction of convective storm processes.The INCUS mission is the first to systematically measure rapidly changing CMF in tropical convection. It features three SmallSats in low Earth orbit, spaced 30 and 90 seconds apart, each with a Ka-band scanning radar (RainCube heritage). The middle satellite also carries a TEMPEST-D–based passive microwave radiometer. This setup captures radar observations at 30-, 90-, and 120-second intervals, enabling the use of time-differenced radar profiles to retrieve CMF. These observations will help quantify CMF intensity, vertical transport duration, and storm evolution. The radiometer provides insights into high anvil cloud properties and storm context. Together, these instruments will provide unprecedented 3D views of tropical convection.Extensive research is being conducted in support of the INCUS mission. This includes high-resolution storm simulations, storm tracking, forward modeling, adaptive ground radar scanning, and analysis of storm environments and anvil clouds. This talk will provide an overview of the INCUS mission architecture, time-differencing retrieval approach, and early research results supporting the INCUS science goals related to this session on atmospheric convection.

Abstract We assess the impact of hydrometeor radiative effects on tropical and subtropical Pacific air temperature anomalies (TAA) using Coupled Model Intercomparison Project Phase 6 (CMIP6) model simulations and satellite data. CMIP6 models are grouped by their treatment of frozen hydrometeors: SON2 (explicit cloud and falling ice), SON1 (simplified), and NOS (cloud ice only). Compared to SON2, SON1 and NOS produce upper‐tropospheric warm biases of 1–2K at 400–200 hPa. Explicit representation of falling ice in SON2 better captures a coupled cloud–radiation–circulation mechanism involving stronger wind stress, colder sea surface temperature, weaker convection in trade‐wind region, and reduced cloud‐radiation feedbacks, leading to improved simulated temperature structures. In contrast, simplified falling‐ice treatments in SON1 do not reproduce these improvements, highlighting the sensitivity of TAA to ice‐cloud radiative parameterizations. These findings emphasize the need for improved hydrometeor–radiation treatments in future climate models, to enhance climate projection reliability.

Global numerical weather models are starting to resolve atmospheric moist convection which comes with a critical need for observational constraints. One avenue for such constraints is spaceborne radar which tends to operate at three wavelengths, Ku, Ka, and W bands. Many studies of deep convection in the past have primarily leveraged the Ku band because it is less affected by attenuation and multiple scattering. However, future spaceborne radar missions might not contain a Ku-band radar, and thus, considering the view of convection from the Ka band or W band compared to the Ku band would be useful. This study examines a coincident dataset between the Global Precipitation Measurement (GPM) mission and CloudSat as well as the entire GPM record to compare convective characteristics across various wavelengths within deep convection. We find that W-band reflectivity Z tends to maximize near the Ku-band defined echo top, while the Ka band often maximizes 4-5 km below. The height of the maximum Z above the melting level for the W band does not linearly relate to the Ku-band maximum. However, using the full GPM record, the Ka-band 30-dBZ echo tops can be linearly related to the Ku-band 40-dBZ echo top with an R2 of 0.62 and a root-mean-squared error of about 1 km. The spatial distribution of echo tops from the Ka band corresponds well to the Ku-band echo tops, highlighting regions of relatively large ice water path. This paper suggests that Ka-band only missions, like NASA's Investigation of Convective Updrafts, should be able to characterize global convection in a similar manner to a Ku-band system. SIGNIFICANCE STATEMENT: There has been a long history of studying global storms using a Ku-band (2 cm, 13 GHz) spaceborne radar, most likely because of the least number of challenges (e.g., loss of signal) at the Ku band compared to the Ka band (8 mm, 35 GHz) and W band (3 mm, 89 GHz). However, each radar system offers different perspectives on hydrometeor profiles observed in deep convection that have remained largely unexplored, perspectives that provide insights into convective storm systems. Therefore, it is useful to know how storms measured at the Ka band and W band compare to storms measured at the Ku band. We find that many of the Ka-band convective properties can be linearly related to the Ku band, and thus, the Ka-band only mission designs should be suitable for studying convective storms.

The overarching goal of the NASA INvestigation of Convective UpdraftS (INCUS) mission is to enhance our understanding of why, when and where tropical convective storms form, and why only some of these storms produce extreme weather. Convective storms transport air and water between Earth's surface and the upper troposphere. This vertical transport of air and water - often referred to as convective mass flux (CMF) - plays a critical role in Earth's weather and climate system through its impacts on large-scale atmospheric circulations, upper tropospheric moistening and high cloud-radiative feedbacks, precipitation rates, and extreme weather. Potential changes to CMF with changing climates may significantly impact these processes. In spite of the critical role of this vertical transport of water and air, representation of CMF remains a major source of error in weather and climate models, thereby limiting our ability to accurately predict convective storms and their impacts in current and future climates. The observations obtained from INCUS will enhance our understanding of tropical convective storm processes and provide guidance for representing these processes in weather and climate models.

We investigate the influence of hydrometeor radiative effects on the winter (DJF) geopotential height anomaly (ZA) over the subtropical and tropical Pacific Oceans in both the Coupled Model Intercomparison Project phase 5 (CMIP5) and phase 6 (CMIP6) models, utilizing satellite observations from GPS radio occultation (RO). This study evaluates average ZA biases in historical climate simulations, focusing on the influence of how models calculate the radiative properties of frozen hydrometeors (cloud ice and falling ice). CMIP6 models are categorized based on their treatments of these radiative properties: separately (SON2), combined (SON1) and cloud ice only (NOS). NOS models exhibit overestimation of absolute ZA biases in the upper troposphere. In contrast, SON2 models reduce these biases by 30-80 m, while SON1 models show no such improvement compared to NOS. In fact, the spatially averaged ZA biases in SON1 are comparable to or larger than those in NOS, suggesting that the combined radiative effects of cloud ice and falling ice hydrometeors do not have the same impact as the separate treatment in SON2. These biases in CMIP6 also align with sensitivity tests conducted using CESM1-CAM5 and CESM2-CAM6, where turning off radiative effects of falling ice results in significantly larger ZA biases compared to simulations with these effects included. Overall, the progress from CMIP5 to CMIP6 remains somewhat limited, with improvements seen only in SON2 models. These findings suggest that independently treating cloud ice and falling ice radiative properties may be crucial for reducing variability among CMIP6 models and improving model accuracy.

This study investigates how deep convective clouds and their surrounding environments are represented in the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) simulations by comparing them with CloudSat observations across three tropical "chimney zones": Tropical Africa, Tropical Amazonia, and the Tropical Warm Pool (TWP). These regions, spanning a spectrum of land-ocean contrasts, exhibit distinct environmental and convective characteristics. While DYAMOND simulations capture environmental differences among the regions, biases persist in representing convective intensity and precipitation dynamics. The simulations overestimate convective intensity in the TWP, likely due to higher-than-realistic conversion efficiencies of potential energy to kinetic energy. Precipitation formation also deviates from observations, occurring at higher altitudes with weak vertical velocities, indicating misrepresentations in cloud microphysics and updraft dynamics. These findings highlight the need for improved coupling of cloud dynamics and microphysics in global models to better simulate deep convection and its environmental interactions.

Changes in “blue water”, which is the total supply of fresh water available for human extraction over land, are quite closely related to changes in runoff or equivalently precipitation minus evaporation, P − E $$ P-E $$ . This article examines how climate change-driven recent past and future changes in the regional water cycle relate to blue water availability and changes in human blue water demand. Although at the largest scales theoretical and numerical model predictions are in broad agreement with observations, at continental scales and below models predict large ranges of possible future P − E $$ P-E $$ and runoff especially at the scale of individual river catchments and for shorter timescale subseasonal floods and droughts. Nevertheless, it is expected that the occurrence and severity of floods will increase and that of droughts may increase, possibly compounded by human-driven non-climatic changes such as changes in land use, dam water impoundment, irrigation and extraction of groundwater. Contemporary assessments predict that increases in 21st century human water extraction in many highly-populated regions are unlikely to be sustainable given projections of future P − E $$ P-E $$ . To reduce uncertainty in future predictions, there is an urgent need to improve modeling of atmospheric, land surface and human processes and how these components are coupled. This should be supported by maintaining the observing network and expanding it to improve measurements of land surface, oceanic and atmospheric variables. This includes the development of satellite observations stable over multiple decades and suitable for building reanalysis datasets appropriate for model evaluation.

This study seeks to explore the relationship between upper ocean current (UOC) anomalies (above 200 meters) and surface wind stress (TAU), focusing on the influence of falling ice (snow) radiative effects (FIREs) over the tropical and subtropical Pacific regions. To achieve this, we conducted sensitivity experiments with the CESM1-CAM5 model, using the Coupled Model Intercomparison Project phase 5 (CMIP5) historical run setting, with FIREs turned off (NOS) and on (SON). The monthly ocean current and temperature of the ocean reanalysis from the NASA Estimating the Circulation and Climate of the Ocean (ECCO) project, which assimilates satellite and in situ measurements, serves as a reference for this study. The spatial patterns of the horizontal UOC anomaly (UOCA) differences between the NOS and SON experiments show a strong correlation with the TAU patterns across the studied domain. When compared to the experiments with NOS, the experiments with SON demonstrate an improvement in the annual mean UOC. The improvement in UOC can be attributed to the enhancements in TAU, specifically in the trade-wind regions. The enhancements in TAU play a significant role in influencing the UOCA patterns and contribute to the overall improvement observed in the experiments with SON. In SON, the average absolute bias of simulated UOCA over the study area is reduced by up to 30% compared to NOS against ECCO. Although biases in UOC are present over the southern and northern flanks of the equator in SON, the improvements in annual mean ocean currents are closely related to enhancements in TAU driven by the inclusion of FIREs. Notably, stronger ocean current magnitudes correspond to more significant changes in TAU due to Coriolis forces. When evaluating the ensemble mean absolute biases of UOC from the CMIP5 models, similarities to NOS, however, are limited over the South Pacific region.

NASA’s upcoming Libera mission is predominantly a continuity mission, aiming at the seamless continuation of the Earth Radiation Budget record maintained by CERES. It therefore provides CERES-characteristic measurements, but also innovative and added capability that allows to discern the visible (VIS) and near-IR (NIR) contributions to the deposition of shortwave radiation in the climate system. Main scientific areas and applications for Libera’s “split-shortwave” measurement are the improved understanding of processes that contribute to changes in shortwave absorption, a main contributor to sustained global climate change, and to study Earth’s albedo and hemispheric symmetry observed therein. Here, we use Earth System Model (ESM) output to characterize the variability in VIS and NIR irradiances and absorption under pre-industrial conditions and under abrupt 4xCO2 forcing. Similar to the NDVI, NIR/VIS ratios are indicative of the surface’s “greenness” and allow to track changes in surface cover and cloud effects. Global mean NIR and VIS irradiances elucidate on the role of surface albedo, water vapor and cloud feedbacks for curiously maintaining a NIR/VIS ratio near 0.8 for both the forced and unforced simulation. With multiple spectral shortwave missions on the way, approaches to exploit these novel datasets and to reduce uncertainty in observed and modeled radiative effects and feedbacks, is quintessential, especially because enhanced shortwave absorption will continue to play a major role in contributing to Earth’s energy gain currently observed and expected to increase under ongoing CO2 forcing.

This paper is concerned with how the diabatically-forced overturning circulations of the atmosphere, established by the deep convection within the tropical trough zone (TTZ), first introduced by Riehl and (Malkus) Simpson, in Contr Atmos Phys 52:287–305 (1979), fundamentally shape the distributions of tropical and subtropical cloudiness and the changes to cloudiness as Earth warms. The study first draws on an analysis of a range of observations to understand the connections between the energetics of the TTZ, convection and clouds. These observations reveal a tight coupling of the two main components of the diabatic heating, the cloud component of radiative heating, shaped mostly by high clouds formed by deep convection, and the latent heating associated with the precipitation. Interannual variability of the TTZ reveals a marked variation that connects the depth of the tropical troposphere, the depth of convection, the thickness of high clouds and the TOA radiative imbalance. The study examines connections between this convective zone and cloud changes further afield in the context of CMIP6 model experiments of climate warming. The warming realized in the CMIP6 SSP5-8.5 scenario multi-model experiments, for example, produces an enhanced Hadley circulation with increased heating in the zone of tropical deep convection and increased radiative cooling and subsidence in the subtropical regions. This impacts low cloud changes and in turn the model warming response through low cloud feedbacks. The pattern of warming produced by models, also influenced by convection in the tropical region, has a profound influence on the projected global warming.

This paper examines the "too bright" issue pertaining to non-planetary boundary layer (PBL) clouds over the South Pacific trade-wind region and its potential link to the falling ice radiative effects (FIREs). We run sensitivity experiments with CESM2-CAM6 (CESM2) global climate model with FIREs on (SON) and off (NOS). The model exhibits more in-cloud liquid water content (CLWC) and droplet above the PBL in NOS, leading to larger shortwave (SW) reflectivity at the top of the atmosphere than in SON over the trade wind regions. CMIP6 models are divided into three subsets: separately calculates the radiative effects of cloud ice and falling ice (SON2), combined (SON1) and without falling ice (NOS). SON2 models exhibit improved CLWC and SW reflectivity similar to CESM2-SON, while NOS and SON1 models are akin to CESM2-NOS owing to weaker surface wind stress and warmer ocean surface, caused by the lack of FIREs over the convective zones.

The presented research aims at refining the “Space Balls” mission concept, which is in its infancy of formulation and aims to obtain high-accuracy estimates of Earth’s Energy Imbalance (EEI), the globally and annually integrated net radiative flux at the top-of-the-atmosphere (TOA). The measurement of net radiative flux is facilitated through sensing radiation pressure accelerations acting on a (or multiple) near-spherical low-Earth orbiting spacecraft(s). While an accelerometer at the center of the spacecraft senses the non-gravitational orbit perturbations, the absorbing-reflecting spacecraft skin represents the detector itself, translating the impact of radiation pressure force into sensible accelerations. As with any observing system, this idea faces a multitude of technological and scientific challenges, such as related to the spacecraft characteristics themselves. The shape and thermo-optical properties are crucial for establishing a proportional relationship between impinging photons and the induced acceleration. Another difficulty arises from confounding forces and effects that may impede on radiation pressure acceleration, such as drag. To simulate and assess associated uncertainty, we develop a simulation environment based on Monte, a high-fidelity orbit navigation and mission design software. EEI represents the rate of planetary heat uptake in response to anthropogenic and natural radiative forcings and feedbacks and drives climate change as we see and feel it. Existing radiometers measure the incoming and outgoing radiative fluxes at TOA, but their uncertainties are too large to derive the residual net radiative flux with sufficient accuracy. This direct EEI measurement would be unprecedented and a vital piece in quantifying and better understanding global climate change. The overall feasibility of this approach has been demonstrated in the late 1970’s (Cactus accelerometer on Castor satellite), but a dedicated EEI mission does not exist to this day. The capabilities of accelerometers are now at a stage where this measurement might become feasible at the required accuracy and precision.

In 1979, Herbert Riehl and Joanne Simpson (Malkus) analytically estimated that 1600–2400 undilute convective cores vertically transport energy to the tropopause at any given time within a region where upper-tropospheric energy is only exported from the tropics. The focus of this paper is to update this estimate using modern satellite observations, compare hot tower frequency and intensity characteristics to all deep convective cores that reach the upper troposphere, and document hot tower spatiotemporal variability in relation to precipitation and high cloud properties within the tropical trough zone (between 13 °S and 19 °N). Cloud vertical profiles from CloudSat and CALIPSO measurements supply convective core diameters and proxies for intensity and convective activity, and these proxies are augmented with brightness temperature data from geostationary satellite observations, precipitation information from IMERG, and cloud radiative properties from CERES. Less than 35

A wide range of aerosol effects on precipitation have been proposed, from the scale of individual clouds to that of the globe.This presentation, based on the findings of an expert workshop under the umbrella of the GEWEX Aerosol Precipitation initiative, reviews the evidence and scientific consensus behind these effects and the underlying set of physical mechanisms, categorised into i) radiative effects via modification of radiative fluxes and the energy balance and ii) microphysical effects via modification of cloud droplets and ice crystals.There exists broad consensus and strong theoretical evidence that, because global mean precipitation is constrained by energetics and surface evaporation, aerosol radiative effects (aerosol-radiation interactions and aerosol-cloud interactions) act as drivers of precipitation changes. Likewise, aerosol radiative effects cause well-documented shifts of large-scale precipitation patterns, such as the Inter-Tropical Convergence Zone (ITCZ). The extent to which aerosol effects on precipitation are applicable at smaller scales and driven or buffered by compensating microphysical and dynamical mechanisms and budgetary constraints is less clear. Although there exists broad consensus and strong evidence that suitable aerosol perturbations increase cloud droplet numbers, reducing the efficiency of warm rain formation across cloud regimes, the overall aerosol effect on cloud microphysics and dynamics as well as the subsequent impact on local, regional and global precipitation is less constrained.This presentation provides a review of the physical mechanisms of aerosol effects on precipitation backed up by evidence from recent cloud-resolving and global modelling simulations as well as from satellite observations.

The direct measurement of Earth's radiative Energy Imbalance (EEI) from space is a challenge for state-of-the-art radiometric observing systems. Current spaceborne radiometers measure the individual shortwave (Solar incoming and Earth reflected solar radiation) and longwave (Earth emitted thermal radiation) components of Earth's energy balance with unprecedented stability, but with calibration errors that are too large to determine the absolute magnitude of global mean EEI or net radiative flux, respectively, as the components' residual. Best estimates of multi-year (2005–2020) EEI are derived from temporal changes in planetary heat content, predominantly ocean heat content, and amount to ~0.9 Wm −2 . To monitor EEI directly from space, we propose an independent approach based on accelerometry that measures non-gravitational radial accelerations induced by radiation pressure. To provide requirements for a near-spherical “Space Balls” spacecraft and mission design, we develop a simulation environment using JPL's Mission Analysis, Operations, and Navigation Toolkit Environment (MONTE) software libraries and present-day radiative fluxes from the Clouds and Earth's Radiant Energy System (CERES). At its current initial stage, the toolset allows us to simulate accelerations acting on a spherical spacecraft due to solar radiation pressure, Earth's reflected shortwave (albedo) and emitted longwave radiation, as well as due to aerodynamic force. Induced accelerations as well as their sensitivity to mean orbit altitude and spacecraft absorptivity agree well with back-of the-envelope calculations and previous simulations that assess the role of radiation pressure accelerations for orbital drift. Future investigations will expand the MONTE-based simulation environment with additional shape and confounding force models. Preliminary simulations with an integrated spacecraft dynamics model suggest that the main confounding accelerations for a non-perfect, faceted sphere are related to Yarkovsky, aerodynamic force and relativistic effects, which will have to be mitigated to facilitate a high-accuracy EEI measurement from space.

This study derives radiatively-active hydrometeors frequencies (HFs) from CloudSat-CALIPSO satellite data to evaluate cloud fraction in present-day simulations by CMIP5 models. Most CMIP5 models do not consider precipitating and/or convective hydrometeors but CESM1-CAM5 in CMIP5 has diagnostic snow and CESM2-CAM6 in CMIP6 has prognostic precipitating ice (snow) included. However, the models do not have snow fraction available for evaluation. Since the satellite-retrieved hydrometeors include the mixtures of floating, precipitating and convective ice and liquid particles, a filtering method is applied to produce estimates of cloud-only HF (or NPCHF) from the total radiatively-active HF (THF), which is the sum of NPCHF, precipitating ice HF and convective HF. The reference HF data for model evaluation include estimates of liquid-phase NPCHF from CloudSat radar-only data (2B-CWC) and ice-phase THF from CloudSat-CALIPSO 2C-ICE combined radar/lidar data. The model evaluation results show that cloud fraction from CMIP5 multi-model mean (MMM) is significantly underestimated (up to 30 %) against the total HF estimates, mainly below the mid-troposphere over the extratropics and in the upper-troposphere over the midlatitude lands and a few tropical convective regions. The CMIP5 cloud fraction biases are reduced dramatically when compared to the cloud-only HF estimates, but the area of overestimates expands from the tropical convective regions to mid-latitudes in the lower and upper troposphere. There is no CMIP5 standard output snow fraction available for comparison against CloudSat-CALIPSO estimate. The implications of these results show that hydrometeors frequency estimates from CloudSat-CALIPSO provide a reference for GCM’s cloud fraction from stratiform and convective form.

<p>Libera, NASA’s first Earth Venture Continuity Mission, is in preparation to provide seamless continuity to current Earth outgoing radiance measurements conducted and processed by the Clouds and Earth’s Radiant Energy System (CERES) project. Leveraging advanced detector technologies, Libera will measure the broadband total, longwave, and shortwave radiances akin to CERES and achieve radiometric uncertainty of approximately 0.2%. Beyond the crucial radiation budget continuity goal, Libera will carry a fourth radiometer in the shortwave near-infrared to advance our understanding of shortwave energy deposition in the climate system, such as related to the characterization of processes relevant for shortwave absorption, climate feedbacks, and Earth’s albedo variability with added insight into hemispheric albedo symmetry given the hemispheric differences in ocean, continent and cloud distributions. We use global model simulations and radiative transfer calculations as proxies for Libera’s future data record to demonstrate applications of the shortwave sub-band knowledge in climate science. Although Libera’s absolute accuracy is unprecedented, it is still insufficient to adequately close Earth’s energy budget. We will therefore discuss current and future avenues to indirectly and directly measure EEI from space. The latter is potentially feasible through sensing radiation pressure-induced accelerations acting on near-spherical spacecrafts, which under optimal conditions, are directly proportional to the net radiative flux experienced at the satellite’s location. This approach has been considered in the past, and the feasibility to achieve a measurement accuracy within 0.3 Wm<sup>-2</sup> is currently under investigation. </p> <p>  </p>

Abstract National Aeronautics and Space Administration's Investigations of Convective Updrafts (INCUS) mission aims to document convective mass flux through changes in the radar reflectivity (ΔZ) in convective cores captured by a constellation of three Ka‐band radars sampling the same convective cells over intervals of 30, 90, and 120 s. Here, high spatiotemporal resolution observations of convective cores from surface‐based radars that use agile sampling techniques are used to evaluate aspects of the INCUS measurement approach using real observations. Analysis of several convective cells confirms that large coherent ΔZ structure with measurable signal (>5 dB) can occur in less than 30 s and are correlated with underlying convective motions. The analysis indicates that the INCUS mission radar footprint and along track sampling are adequate to capture most of the desirable ΔZ signals. This unique demonstration of reflectivity time‐lapse provides the framework for estimating convective mass flux independent from Doppler techniques with future radar observations.

Understanding the complexities of cloud-sky radiative fluxes is crucial for improving numerical predictions of climate change. NASA’s upcoming Atmosphere Observing System (AOS) mission promises unprecedented observations that will present an opportunity to enhance our understanding of the role of clouds in modulating both Earth’s radiation budget and climate sensitivity. AOS will utilize a series of active (Radar, Lidar) and passive (Imaging multi-angle polarimeter) instruments. The active instruments will provide vertically resolved cloud and aerosol information over a narrow ground-track (shown in red in the Figure below), while the passive instruments will cover a much wider swath. The high spatial resolution of AOS (~1km) will allow us to study clouds at the process level. While this will give us the opportunity to gain new insights, it also provides an unprecedented challenge to deliver satellite products at such a high resolution at which horizontal photon transport cannot be neglected, leading to biases in traditional cloud retrieval algorithms. To estimate radiative fluxes over the whole swath, we propose to extrapolate the vertical information from the active instruments to the across-track passive observations using a scene construction algorithm. This algorithm is evaluated using data from Large-Eddy Simulations and synthetic imagery computed by radiative transfer models.