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DOE OSTI2025

Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels

Abstract. The cloud radiative kernel method is a popular approach to quantify cloud feedbacks and rapid cloud adjustments to increased CO2 concentrations and to partition contributions from changes in cloud amount, altitude, and optical depth. However, because this method relies on cloud property histograms derived from passive satellite sensors or produced by passive satellite simulators in models, changes in obscuration of lower-level clouds by upper-level clouds can cause apparent low-cloud feedbacks and adjustments, even in the absence of changes in lower-level cloud properties. Here, we provide a methodology for properly diagnosing the impact of changing obscuration on cloud feedbacks and adjustments and quantify these effects across climate models. Averaged globally and across global climate models, properly accounting for obscuration leads to weaker positive feedbacks from lower-level clouds and stronger positive feedbacks from upper-level clouds while simultaneously removing a mostly artificial anti-correlation between them. Given that the methodology for diagnosing cloud feedbacks and adjustments using cloud radiative kernels has evolved over several papers, and obscuration effects have only occasionally been considered in recent papers, this paper serves to establish recommended best practices and to provide a corresponding code base for community use.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

The Influence of Aerosols on the Shortwave Cloud Radiative Forcing from North Pacific Oceanic Clouds: Results from the Cloud Indirect Forcing Experiment (CIFEX)

Aerosols over the Northeastern Pacific Ocean enhance the cloud drop number concentration and reduce the drop size for marine stratocumulus and cumulus clouds. These microphysical effects result in brighter clouds, as evidenced by a combination of aircraft and satellite observations. In-situ measurements from the Cloud Indirect Forcing Experiment (CIFEX) indicate that the mean cloud drop number concentration in low clouds over the polluted marine boundary layer is greater by 53/cu cm compared to clean clouds, and the mean cloud drop effective radius is smaller by 4 microns. We link these in-situ measurements of cloud modification by aerosols, for the first time, with collocated satellite broadband radiative flux observations from the Clouds and the Earth's Radiant Energy System (CERES) to show that these microphysical effects of aerosols enhance the top-of-atmosphere cooling by -9.9+/-4.3 W/sq m for overcast conditions.

Wilcox, Eric M.↗

NASA NTRS2007

Influence of Aerosols on the Shortwave Cloud Radiative Forcing from North Pacific Oceanic Clouds: Results from the Cloud Indirect Forcing Experiment (CIFEX)

Aerosols over the Northeastern Pacific Ocean enhance the cloud drop number concentration and reduce the drop size for marine stratocumulus and cumulus clouds. These microphysical effects result in brighter clouds, as evidenced by a combination of aircraft and satellite observations. In-situ measurements from the Cloud Indirect Forcing Experiment (CIFEX) indicate that the mean cloud drop number concentration in low clouds over the polluted marine boundary layer is greater by 53 cm(sup -3) compared to clean clouds, and the mean cloud drop effective radius is smaller by 4 micrometers. We link these in-situ measurements of cloud modification by aerosols, for the first time, with collocated satellite broadband radiative flux observations from the Clouds and the Earth s Radiant Energy System to show that these microphysical effects of aerosols enhance the top-of-atmosphere cooling by -.9.9 plus or minus 4.3 W m(sup -2) for overcast conditions.

Wilcox, Eric M.↗

NASA NTRS2010

Observed Differences in Spectral Microphysical Retrievals from MODIS

The microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and physical processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud effective particle size are available using the heritage 3.7 an band from AVHRR as well as the 1.6 and 2.1 m shortwave IR bands. The MODIS cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using each of these spectral bands. It has been found that significant differences can occur between the three size retrievals, mainly for liquid water marine boundary layer clouds and especially in broken (low cloud fraction) regimes. In particular, for such regimes, effective radii derived from the MODIS 2.1 lim band can be substantially larger than retrievals from the Heritage 3.7 lam band. In this paper, we present global and regional results of the differences, including correlations, view angle dependencies, and algorithm sensitivities for the existing MODIS Collection 5 product.

Platnick, Steven E.↗

NASA NTRS2001

Observations of Three-Dimensional Radiative Effects that Influence Satellite Retrievals of Cloud Properties

This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.

Varnai, Tamas↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

CFD↗

NASA NTRS2019

Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC(4)RS

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satellite‐borne Moderate‐resolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 μm) in cloud‐free scenes. Since MODIS' resolution (500‐m pixels, 3‐ or 10‐km product) is too coarse for studying near‐cloud aerosol, we ported the Dark Target algorithm to the high‐resolution (~50‐m pixels) enhanced‐MODIS Airborne Simulator (eMAS), which flew on the high‐altitude ER‐2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5‐km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degraded‐resolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and ground‐based Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into near‐cloud and far‐from‐cloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clear‐cloud transition zone microphysics such as aerosol swelling. However, 3‐D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds.

aerosol retrieval algorithm↗

NASA NTRS1997

Absorption of Sunlight by Water Vapor in Cloudy Conditions: A Partial Explanation for the Cloud Absorption Anomaly

The atmospheric radiative transfer algorithms used in most global general circulation models underestimate the globally-averaged solar energy absorbed by cloudy atmospheres by up to 25 W/sq m. The origin of this anomalous absorption is not yet known, but it has been attributed to a variety of sources including oversimplified or missing physical processes in these models, uncertainties in the input data, and even measurement errors. Here, a sophisticated atmospheric radiative transfer model was used to provide a more comprehensive description of the physical processes that contribute to the absorption of solar radiation by the Earth's atmosphere. We found that the amount of sunlight absorbed by a cloudy atmosphere is inversely proportional to the solar zenith angle and the cloud top height, and directly proportional to the cloud optical depth and the water vapor concentration within the clouds. Atmospheres with saturated, optically-thick, low clouds absorbed about 12 W/sq m more than clear atmospheres. This accounts for about 1/2 to 1/3 of the anomalous ab- sorption. Atmospheres with optically thick middle and high clouds usually absorb less than clear atmospheres. Because water vapor is concentrated within and below the cloud tops, this absorber is most effective at small solar zenith angles. An additional absorber that is distributed at or above the cloud tops is needed to produce the amplitude and zenith angle dependence of the observed anomalous absorption.

Crisp, D.↗

NASA NTRS2018

Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗

NASA NTRS2018

Evaluation of a High-Resolution Numerical Weather Prediction Model’s Simulated Clouds Using Observations from CloudSat, GOES-13 and in Situ Aircraft

This study aimed to assess tropical cloud properties predicted by Environment and Climate Change Canada’s Global Environmental Multiscale (GEM)modelwhen run with the Milbrandt–Yau double-moment cloud microphysical scheme and one-way nesting that culminated at a (∼300 km)2 inner domain with 0.25 km horizontal grid spacing. The assessment utilized satellite and in situ data collected during the High Ice Water Content (HIWC) and High Altitude Ice Crystals (HAIC) projects for a mesoscale convective system on 16May 2015 over French Guiana.Data fromCloud- Sat’s cloud-profiling radar and GOES-13’s imager were compared to data either simulated directly by GEM or produced by operating on GEM’s cloud data with both the CFMIP (Cloud Feedback Model Intercomparison Project) Observation Simulator Package (COSP) instrument simulator and a three-dimensional Monte Carlo solar radiative transfer model. In situ observations were made from research aircraft – Canada’s National Research Council Convair-580 and the French SAFIRE Falcon-20 – whose flight paths were aligned with CloudSat’s ground-track. Spatial and temporal shifts of clouds simulated by GEM compared well to GOES-13 imagery. There are, however, differences between simulated and observed amounts of high and low cloud. While GEM did well at predicting ranges of ice-water content (IWC) near 11 km altitude (Falcon-20), it produces too much graupel and snow near 7 km (Convair-580). This produced large differences between CloudSat’s and COSP-generated radar reflectivities and two-way attenuations. On the other hand, CloudSat’s inferred values of IWC agree well with in situ samples at both altitudes. Generally, GEM’s visible reflectances exceeded GOES-13’s on account of having produced too much low-level liquid cloud. It is expected that GEM’s disproportioning of cloud hydrometeors will improve once it includes a better representation of secondary ice production.

Qu, Zhipeng↗

NASA NTRS2023

Comparison of Clouds and Cloud Feedback between AMIP5 and AMIP6

We examine the changes in clouds and cloud feedback between Phase 5 (AMIP5) and Phase 6 (AMIP6) of the Atmospheric Model Intercomparison Project. Each model is perturbed by uniformly increasing the sea surface temperature by 4 K. The simulated cloud fraction, the perturbed states and cloud radiative kernels are used to derive cloud feedback in the shortwave (SW), longwave (LW) and their sum (Net). Compared to AMIP5, the cloud fraction in AMIP6 increases by 9.1%, while the perturbation leads to a 0.25% decrease. The Net cloud feedback at the top of the atmosphere (TOA) is almost double (174%). Statistical tests support that this change is mainly due to an increase in the surface SW cloud feedback caused by optically thick, middle and low clouds. The contribution of the atmospheric Net component (12%) stems from the increase in the atmospheric LW cloud feedback, likely to play a role in weakening (strengthening) the northward (southward) meridional atmospheric energy transport, while the opposite is true for the surface LW and Net cloud feedback in the meridional oceanic energy transport. The substantial increase in cloud feedback at the TOA primarily contributes to the higher climate sensitivity. The cloud feedback spread in AMIP6 is comparable to that in AMIP5.

Clouds↗

DOE OSTI2026

Examining Cloud Feedback Components in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM)

Cloud feedback remains the main source of uncertainty in climate sensitivity estimated by global climate models (GCMs), largely because subgrid cloud responses are parameterized in GCMs due to their coarse resolution. Here, this study examines cloud feedback in the global 3.25-km Simple Cloud-Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM 3 km) through a pair of 1-yr atmosphere-only simulations with control and +4-K sea surface temperature perturbations. SCREAM 3 km produces a positive cloud feedback that falls within but at the upper end of the range of Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP phase 6 (CMIP6) models and expert judgment. The positive cloud feedback arises from positive contributions from both high- and low-level clouds, with increases in high-cloud altitude and decreases in low-cloud amount and optical depth playing key roles. The stronger-than-CMIP-average feedback is mainly attributable to the high-cloud altitude feedback, owing to cloud tops rising nearly isothermally in SCREAM 3 km. The positive low-cloud amount feedback is weaker in SCREAM than in GCMs because estimated inversion strength (EIS) increases more dramatically with warming. A coarser 12-km resolution version of SCREAM exhibits a weaker positive cloud feedback than SCREAM 3 km, mainly because its low-cloud-radiative flux is more sensitive to EIS, leading to a stronger negative low-cloud amount feedback. With this process-level assessment of cloud feedback, this study reveals where SCREAM aligns with and diverges from conventional GCMs and expert assessment, providing insights to inform further model improvement and future expert assessment.

Cloud radiative effects↗

NASA NTRS2011

Developing and Evaluating RGB Composite MODIS Imagery for Applications in National Weather Service Forecast Offices

Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.

Oswald, Hayden↗

NASA NTRS2013

Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.

Smith, William L., Jr.↗

DOE OSTI2026

Assessing Cloud and Precipitation Properties on Temporal and Spatial Scales Using LASSO Simulations over ENA

Low clouds and precipitation representation remain a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub-grid variability and scale-dependent sampling. This study evaluates the performance of preliminary simulations from the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), with a focus on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation simulated across closed-cell, open-cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA-2 reanalyses, we assess the representativeness of ground-based point observations by analyzing their correspondence to model-resolved spatial and temporal means. Results suggest that observational sampling of at least 6 hours is required to achieve consistency with domain-scale averages, in particular for observations that exhibit pronounced sub-grid heterogeneity, such as precipitation. ERA5-forced simulations exhibit improved spatial coherence and agreement with domain-averaged quantities when compared to MERRA-2 runs, with performance discrepancies largest for convective cloud conditions due to differences in forcing fidelity and temporal resolution. These findings highlight the importance of regime-aware model evaluation strategies and potentially demonstrate how LES can inform observation-model comparison practices and the development of cloud and precipitation parameterizations in ESMs.

Liang, Jiakun [University of Hawai'i at Manoa] (OR↗

NASA NTRS1987

Reflectivity of earth's surface and clouds in ultraviolet from satellite observations

The Total Ozone Mapping Spectrometer on board Nimbus 7 is used to infer the UV surface and cloud reflectance at 370 nm. Cloudless surface reflectivity was analyzed on a global basis for all surface types for several months. The UV surface reflectivity varies from 2 percent for some forest and grassland regions to 14 percent for some sandy desert areas. A notable exception is the large salt flats of Bolivia, which have a reflectivity of about 60 percent. Cloud reflectivity was also analyzed for clouds located at three levels in the atmosphere, as determined by the 11.5 micron channel of the Temperature Humidity Infrared Radiometer. Average cloud reflectivity at 370 nm ranges from 52 percent for low clouds (tops less than 2 km) to 76 percent for high clouds (tops greater than 7 km at the equator, decreasing to greater than 4 km at poles).

Eck, T. F.↗

NASA NTRS1992

Global patterns of cloud optical thickness variation with temperature

The International Satellite Cloud Climatology Project dataset is used to correlate variations of cloud optical thickness and cloud temperature in today's atmosphere. The analysis focuses on low clouds in order to limit the importance of changes in cloud vertical extent, particle size, and water phase. Coherent patterns of change are observed on several time and space scales. On the planetary scale, clouds in colder, higher latitudes are found to be optically thicker than clouds in warmer, lower latitudes. On the seasonal scale, winter clouds are, for the most part, optically thicker than summer clouds. The logarithmic derivative of cloud optical thickness with temperature is used to describe the sign and magnitude of the optical thickness-temperature correlation. The seasonal, latitudinal, and day-to-day variations of this relation are examined for Northern Hemisphere clouds in 1984. In cold continental clouds, optical thickness increases with temperature, consistent with the temperature variation of the adiabatic cloud water content. In warm continental and in almost all maritime clouds, however, optical thickness decreases with temperature.

Tselioudis, George↗