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Shortwave Broadband Irradiance Computations Using Cloud Properties Combined from CALIPSO, CloudSat, and MODIS

In this study, cloud properties measured from the CALIPSO, CloudSat, and MODIS (CCM) are used for top-of-atmosphere (TOA) shortwave (SW) broadband (BB) irradiance computations. The CALIPSO and CloudSat active sensors provide detailed cloud vertical profiles, but these occasionally miss parts of the cloud columns due to the full attenuation of sensor signals, surface clutter, or insensitivity to a certain range of cloud particle sizes. As a result, the CCM-merged cloud extinction coefficient profiles can be underestimated. Therefore, we compare the column-integrated visible scaled cloud optical depth (VSCOD) of the CCM-merged cloud extinction coefficient profile with the MODIS-estimated VSCOD and apply a scaling factor to the CCM-merged cloud extinction profile. The VSCOD is defined as a visible cloud optical depth multiplied by (1¬–asymmetry parameter). The SW irradiances are computed using the scaled CCM-merged cloud extinction coefficient and effective radius profiles. It is shown that the multi-sensor-combined cloud profiles significantly reduce positive TOA SW BB biases, compared to those with MODIS-derived cloud properties only. The improvement is more pronounced for optically thick clouds, where MODIS ice particle effective radius is largely underestimated.

Cloud↗
NASA NTRS1994

Tropical cirrus cloud radiative forcing: Sensitivity studies

We have performed one dimensional radiative transfer calculations to evaluate the impact of cirrus clouds on the tropical radiation budget. We investigate the sensitivity of solar and infrared fluxes to cloud optical depth, particle size distributions, and cloud height. If the observed solar cloud forcing in excess of 100 W/sq m is to be attributed to cirrus anvils alone, then the optical depth of these anvils must be at least 5 (assuming 50% cloud cover and an ice crystal effective radius of 15 microns). The net radiative forcing of cirrus near the tropical tropopause is positive (heating) for cloud optical depths less than about 16 and negative (cooling) for larger optical depths. If cirrus clouds alone are responsible for the equal and opposite shortwave and longwave cloud forcing in excess of 100 W/sq m observed by Earth Radiation Budget Experiment (ERBE), then the cirrus must typically take the form of deep, optically thick clouds with relatively small particles (radii of 10-20 microns) and cloud-tops well below the tropopause. The maintenance of this balance on monthly time scales can be attributed to a variety of correlations: The cloud cover of optically thick cirrus or thin cirrus overlying low-level stratus clouds could vary; or cirrus anvil height cloud increase along with a decrease in the ice crystal effective radius and an increase in optical depth. It would be of great interest to determine observationally which of these correlations is responsible for the observed lack of variation in cloud forcing.

Jensen, E. J.↗
NASA NTRS2006

Statistical Analyses of Satellite Cloud Object Data From CERES: Boundary-layer Cloud Objects During 1998 El Nino - Part 4

Three boundary-layer cloud object types, stratus, stratocumulus and cumulus, that occurred over the Pacific Ocean during January-August 1998, are identified from the CERES (Clouds and the Earth s Radiant Energy System) single scanner footprint (SSF) data from the TRMM (Tropical Rainfall Measuring Mission) satellite. This study emphasizes the differences and similarities in the characteristics of each cloud-object type between the tropical and subtropical regions and among different size categories and among small geographic areas. Both the frequencies of occurrence and statistical distributions of cloud physical properties are analyzed. In terms of frequencies of occurrence, stratocumulus clouds dominate the entire boundary layer cloud population in all regions and among all size categories. Stratus clouds are more prevalent in the subtropics and near the coastal regions, while cumulus clouds are relatively prevalent over open ocean and the equatorial regions, particularly, within the small size categories. The largest size category of stratus cloud objects occurs more frequently in the subtropics than in the tropics and has much larger average size than its cumulus and stratocumulus counterparts. Each of the three cloud object types exhibits small differences in statistical distributions of cloud optical depth, liquid water path, TOA albedo and perhaps cloud-top height, but large differences in those of cloud-top temperature and OLR between the tropics and subtropics. Differences in the sea surface temperature (SST) distributions between the tropics and subtropics influence some of the cloud macrophysical properties, but cloud microphysical properties and albedo for each cloud object type are likely determined by (local) boundary-layer dynamics and structures. Systematic variations of cloud optical depth, TOA albedo, cloud-top height, OLR and SST with cloud object sizes are pronounced for the stratocumulus and stratus types, which are related to systematic variations of the strength of inversion with cloud object sizes, produced by large-scale subsidence. The differences in cloud macrophysical properties over small regions are significantly larger than those of cloud microphysical properties and TOA albedo, suggesting a greater control of (local) large-scale dynamics and other factors on cloud object properties. When the three cloud object types are combined, the relative population among the three types is the most important factor for determining the cloud object properties in a Pacific transect where the transition of boundary-layer cloud types takes place.

Xu, Kuan-Man↗
NASA NTRS1989

Reflected fluxes for broken clouds over a Lambertian surface

Reflected fluxes are calculated for broken cloudiness (i.e., nonplane parallel) as a function of cloud cover, cloud optical depth, solar zenith angle and surface albedo. These calculations extend previous results for broken cloud reflected fluxes over a black surface. The present study demonstrates that not only radiances but also radiative fluxes over high albedo surfaces may be decreased by the presence of broken cloudiness. Conventional wisdom states that cloud radiances (brightnesses) are always greater than the background. While most cloud retrieval schemes are built around this assumption, it is incorrect for clouds over high albedo surfaces such as found in polar regions. However, the most startling and counterintuitive conclusion of this study is that nonabsorbing finite clouds over a highly reflecting surface will decrease the system albedo. As a result, surface absorption is increased, the result of multiple scattering between surface and cloud layer, controlled by cloud morphology and cloud optical thickness. A simple parameterization of the effects of cloud contamination upon retrieved albedo is given in terms of solar zenith angle, cloud optical depth, surface albedo, cloud cover, and plane-parallel cloud albedo. In this way, the effects of broken cloudiness are modeled in terms of easily computed plane-parallel values.

Welch, Ronald M.↗
NASA NTRS1999

Improving Pixel Level Cloud Optical Property Retrieval using Monte Carlo Simulations

The accurate pixel-by-pixel retrieval of cloud optical properties from space is influenced by radiative smoothing due to high order photon scattering and radiative roughening due to low order scattering events. Both are caused by cloud heterogeneity and the three-dimensional nature of radiative transfer and can be studied with the aid of computer simulations. We use Monte Carlo simulations on variable 1-D and 2-D model cloud fields to seek for dependencies of smoothing and roughening phenomena on single scattering albedo, solar zenith angle, and cloud characteristics. The results are discussed in the context of high resolution satellite (such as Landsat) retrieval applications. The current work extends the investigation on the inverse NIPA (Non-local Independent Pixel Approximation) as a tool for removing smoothing and improving retrievals of cloud optical depth. This is accomplished by: (1) Delineating the limits of NIPA applicability; (2) Exploring NIPA parameter dependences on cloud macrostructural features, such as mean cloud optical depth and geometrical thickness, degree of extinction and cloud top height variability. We also compare parameter values from empirical and theoretical considerations; (3) Examining the differences between applying NIPA on radiation quantities vs direct application on optical properties; (4) Studying the radiation budget importance of the NIPA corrections as a function of scale. Finally, we discuss fundamental adjustments that need to be considered for successful radiance inversion at non-conservative wavelengths and oblique Sun angles. These adjustments are necessary to remove roughening signatures which become more prominent with increasing absorption and solar zenith angle.

Oreopoulos, Lazaros↗
NASA NTRS2000

Raman Lidar Measurements of Water Vapor and Cirrus Clouds During The Passage of Hurricane Bonnie

The NASA/GSFC Scanning Raman Lidar (SRL) was stationed on Andros Island in the Bahamas during August - September, 1998 as a part of the third Convection and Moisture Experiment (CAMEX-3) which focussed on hurricane development and tracking. During the period August 21 - 24, hurricane Bonnie passed near Andros Island and influenced the water vapor and cirrus cloud measurements acquired by the SRL. Two drying signatures related to the hurricane were recorded by the SRL and other sensors. Cirrus cloud optical depths (at 351 nm) were also measured during this period. Optical depth values ranged from less than 0.01 to 1.5. The influence of multiple scattering on these optical depth measurements was studied. A correction technique is presented which minimizes the influences of multiple scattering and derives information about cirrus cloud optical and physical properties. The UV/IR cirrus cloud optical depth ratio was estimated based on a comparison of lidar and GOES measurements. Simple radiative transfer model calculations compared with GOES satellite brightness temperatures indicate that satellite radiances are significantly affected by the presence of cirrus clouds if IR optical depths are approximately 0.005 or greater. Using the ISCCP detection threshold for cirrus clouds on the GOES data presented here, a high bias of up to 40% in the GOES precipitable water retrieval was found.

Whiteman, D. N.↗
NASA NTRS2008

Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA-40 and ERA Interim) against CERES Tropical Deep Convective Cloud Object Observations

This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Center for Medium-range Weather Forecasts (ECMWF) operational analysis (EOA) and ECMWF Re-Analyses (ERA-40 and ERA Interim) are validated against those obtained from Earth Observing System satellite cloud object data for January-August 1998 and March 2000 periods. These properties include ice water path (IWP), cloud-top height and temperature, cloud optical depth and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud-object type for the January-August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The downgrade of data assimilation technique and the lack of snow water content information in ERA-40, not the coarser horizontal grid resolution, are also responsible for the disagreements with observed pdfs of cloud physical properties although the detection rates of cloud object occurrence are improved for small size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights with grid-cell dynamics. These conclusions will be rechecked using the ERA Interim data, due to recent changes in the ECMWF convective parameterization (Bechtold et al. 2004, 2008). Results from the ERA Interim will be presented at the meeting.

Xu, Kuan-Man↗
NASA NTRS2022

Above-Aircraft Cirrus Cloud and Aerosol Optical Depth From Hyperspectral Irradiances Measured By a Total-Diffuse Radiometer

This study develops the use of spectral total and diffuse irradiance measurements, made from a prototype hyperspectral total-diffuse sunshine pyranometer (SPN-S), to retrieve layer fine-mode aerosol (τ aer ) and total optical depths from airborne platforms. Additionally, we use spectral analysis in an attempt to partition the total optical depth into its τ aer and cirrus cloud optical depth (τ cld ) components in the absence of coarse-mode aerosols. Two retrieval methods are developed: one leveraging information in the diffuse irradiance and the other using spectral characteristics of the transmitted direct beam, with each approach best suited for specific cloud and aerosol conditions. The SPN-S has advantages over traditional sun photometer systems, including no moving parts and a low cost. However, a significant drawback of the instrument is that it is unable to measure the direct-beam irradiance as accurately as sun photometers. To compensate for the greater measurement uncertainty in the radiometric irradiances, these retrieval techniques employ ratioed inputs or spectral information to reduce output uncertainty. This analysis uses irradiance measurements from the SPN-S and the solar spectral flux radiometer (SSFR) aboard the National Aeronautics and Space Administration’s (NASA) P-3 aircraft during the 2018 deployment of the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP 2 Ex) mission to quantify above-aircraft cirrus τ cld and derive vertical profiles of layer τ aer . Validation of the τ aer retrieval is accomplished by comparison with co-located measurements of direct solar irradiance made by the Sky-Scanning Sun-Tracking Atmospheric Research (4STAR) and in situ measurements of aerosol optical depth. For the aggregated 2018 ORACLES results, regression between the SPN-S-based method and sun photometer τ aer values yields a slope of 0.96 with an R 2 of 0.96, while the root mean square error (RMSE) is 3.0 x 10 -2 . When comparing the retrieved τ aer to profiles of integrated in situ measurements of optical extinction, the slope, R 2 , and RMSE values for ORACLES are 0.90, 0.96, and 3.4 x 10 -2 , and for CAMP 2 Ex they are 0.94, 0.97, and 3.4 x 10 -2 , respectively. This paper is a demonstration of methods for deriving cloud and aerosol optical properties in environments where both atmospheric constituents may be present. With improvements to the low-cost SPN-S radiometer instrument, it may be possible to extend these methods to a broader set of sampling applications, such as ground-based settings.

spectral instrument (SPN-S)↗
DOE OSTI2023

TWST Cloud Properties (COD, droplet effective radius, and thermodynamic phase). SAIL, AMF2, 2022-2023.

The dataset consists of calibrated zenith shortwave spectral radiances (440-1700 nm) and cloud optical depth (COD) retrievals approximately every second. Retrievals of cloud droplet effective radius and thermodynamic phase are currently done offline, but some of these retrievals are included in the dataset. Effective radius and phase are included for days with periods of sufficiently high COD. Effective radius and phase retrievals in the data set were computed at approximately 5-10 second intervals to reduce computation time. The retrievals can be performed at the full sample rate. The field of view is 0.5 degree.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Statistical Analyses of Satellite Cloud Object Data from CERES: Comparison with Cloud-Resolving Model Simulations of Tropical Convective Clouds - Part III

The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium- and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Ni o) and March 2000 (weak La Ni a). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud top height while it overestimates the differences in the observed outgoing longwave radiation and cloud top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and in space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems.

Luo, Yali↗
NASA NTRS2009

Sensitivity of Photolysis Frequencies and Key Tropospheric Oxidants in a Global Model to Cloud Vertical Distributions and Optical Properties

Clouds affect tropospheric photochemistry through modification of solar radiation that determines photolysis frequencies. As a follow-up study to our recent assessment of the radiative effects of clouds on tropospheric chemistry, this paper presents an analysis of the sensitivity of such effects to cloud vertical distributions and optical properties (cloud optical depths (CODs) and cloud single scattering albedo), in a global 3-D chemical transport model (GEOS-Chem). GEOS-Chem was driven with a series of meteorological archives (GEOS1- STRAT, GEOS-3 and GEOS-4) generated by the NASA Goddard Earth Observing System data assimilation system. Clouds in GEOS1-STRAT and GEOS-3 have more similar vertical distributions (with substantially smaller CODs in GEOS1-STRAT) while those in GEOS-4 are optically much thinner in the tropical upper troposphere. We find that the radiative impact of clouds on global photolysis frequencies and hydroxyl radical (OH) is more sensitive to the vertical distribution of clouds than to the magnitude of column CODs. With random vertical overlap for clouds, the model calculated changes in global mean OH (J(O1D), J(NO2)) due to the radiative effects of clouds in June are about 0.0% (0.4%, 0.9%), 0.8% (1.7%, 3.1%), and 7.3% (4.1%, 6.0%), for GEOS1-STRAT, GEOS-3 and GEOS-4, respectively; the geographic distributions of these quantities show much larger changes, with maximum decrease in OH concentrations of approx.15-35% near the midlatitude surface. The much larger global impact of clouds in GEOS-4 reflects the fact that more solar radiation is able to penetrate through the optically thin upper-tropospheric clouds, increasing backscattering from low-level clouds. Model simulations with each of the three cloud distributions all show that the change in the global burden of ozone due to clouds is less than 5%. Model perturbation experiments with GEOS-3, where the magnitude of 3-D CODs are progressively varied from -100% to 100%, predict only modest changes (<5%) in global mean OH concentrations. J(O1D), J(NO2) and OH3 concentrations show the strongest sensitivity for small CODs and become insensitive at large CODs due to saturation effects. Caution should be exercised not to use in photochemical models a value for cloud single scattering albedo lower than about 0.999 in order to be consistent with the current knowledge of cloud absorption at the ultraviolet wavelengths.

Liu, Hongyu↗
DOE OSTI2022

Evaluating WRF-Solar EPS cloud mask forecast using the NSRDB

Improving the accuracy of day-ahead solar forecasts using numerical weather prediction models requires improving the forecasting of cloud occurrence and properties. Validating cloud forecasts is challenging because this requires evaluating different types of clouds over a wide variety of regions. This study analyzes the cloud occurrence (or cloud mask) over the contiguous United States (CONUS), predicted by the Weather Research and Forecasting-Solar Ensemble Prediction System (WRF-Solar EPS), to identify the strengths and limitations of the model in reproducing cloud fields. To enable the in-depth analysis of cloud mask forecasts covering CONUS, we use satellite observations from the National Solar Radiation Database (NSRDB). Two evaluation methods are implemented to consider all clouds and partially removed clouds from the 2-km NSRDB in evaluating the 9-km WRF-Solar EPS cloud mask. Cloud detection metrics as well as the frequency of cloud occurrence are used to quantify the monthly performance of WRF-Solar EPS. Mismatched cloud frequency (MCF) is used to assess the model's capability to predict different types of clouds, which are classified using three levels of cloud optical depth (COD) and cloud top height (CTH). The day-ahead forecasts covering the full year of 2018 demonstrate that WRF-Solar EPS produces MCFs ranging from 27%-46%, 13%-34%, and 8%-19% for thin, mid-thickness, and thick clouds, respectively. For three CTH levels, the model shows MCFs ranging from 19%-46%, 16%-33%, and 8%-27% for low-level, middle-level, and high-level clouds, respectively. This comprehensive characterization of model performance helps identify model weakness and will eventually lead to improvements in cloud and solar radiation forecasting.

14 SOLAR ENERGY↗
NASA NTRS2020

Uncertainties in CERES Top-of-Atmosphere Fluxes Caused by Changes in Accompanying Imager

The Clouds and the Earth’s Radiant Energy System (CERES) project provides observations of Earth’s radiation budget using measurements from CERES instruments on board the Terra, Aqua, Suomi National Polar-orbiting Partnership (S-NPP), and NOAA-20 satellites. The CERES top-of-atmosphere (TOA) fluxes are produced by converting radiance measurements using empirical angular distribution models, which are functions of cloud properties that are retrieved from imagers flying with the CERES instruments. As the objective is to create a long-term climate data record, not only calibration consistency of the six CERES instruments needs to be maintained for the entire time period, it is also important to maintain the consistency of other input data sets used to produce this climate data record. In this paper, we address aspects that could potentially affect the CERES TOA flux data quality. Discontinuities in imager calibration can affect cloud retrieval which can lead to erroneous flux trends. When imposing an artificial 0.6 per decade decreasing trend to cloud optical depth, which is similar to the trend difference between CERES Edition 2 and Edition 4 cloud retrievals, the decadal SW flux trend changed from −0.3 5 ± 0.18 Wm −2 to 0.61 ± 0.18 Wm −2 . This indicates that a 13% change in cloud optical depth results in about 1% change in the SW flux. Furthermore, different CERES instruments provide valid fluxes at different viewing zenith angle ranges, and including fluxes derived at the most oblique angels unique to S-NPP (>66 ∘ ) can lead to differences of 0.8 Wm −2 and 0.3 Wm −2 in global monthly mean instantaneous SW flux and LW flux. To ensure continuity, the viewing zenith angle ranges common to all CERES instruments (<66 ∘ ) are used to produce the long-term Earth’s radiation budget climate data record. The consistency of cloud properties retrieved from different imagers also needs to be maintained to ensure the TOA flux consistency.

Wenying Su↗
DOE OSTI2025

Marine and continental stratocumulus cloud microphysical properties obtained from routine ARM Cimel sunphotometer observations

This study investigates marine and continental stratocumulus (Sc) cloud properties obtained from an automated implementation of a multispectral photometer retrieval. Photometer methods simultaneously retrieve cloud optical depth (τ) and cloud droplet effective radius (r e ), with estimates for liquid water path (LWP) calculated on the availability of those quantities. These applied methods evaluate retrieved cloud properties for Sc identified during a recent 6 year period over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program sites in Oklahoma, USA (SGP) and in the Azores, Portugal (ENA). Modest agreement in key quantity retrievals is found between the routine photometer products and multisensor collocated profiling references. Cumulative breakdowns contingent on cloud thickness indicate increases in all retrieved quantities in thicker clouds, with larger discrepancies in the relative performance between the retrievals collected in the presence of drizzle. Under continental cloud conditions, the clouds of a similar thickness and r e to those sampled under marine conditions report a factor of 1.5 larger τ and LWP. An r 2 ≅0.65 is found between photometer τ retrievals and shadowband radiometer measurements, with photometer retrievals reporting a high (relative) bias. The τ intercomparisons indicate that variability between retrievals is a factor of three larger than errors reported from individual retrieval input perturbation tests. Photometer r e retrievals suggest a low r 2 (< 0.1) having a standard deviation ≅ 3 µm when compared to ARM baseline multi-sensor radar/radiometer references (accounting for offsets in the cloud droplet number concentration assumptions of the latter). However, photometer LWP calculations remain relatively unbiased in non-drizzling conditions, with errors O (50 g m −2 ) and r 2 ≅0.5 to collocated radiometer and interferometer references. Additional sensitivity tests for island influences on marine Sc properties suggest that while island-influenced winds may promote larger cloud LWP or thickness, the influence could be within retrieval method uncertainty and/or collocated instrument variability.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Cloud-Vegetation Interaction: Use of Normalized Difference Cloud Index for Estimation of Cloud Optical Thickness

A new technique to retrieve cloud optical depth for broken clouds above green vegetation using ground-based zenith radiance measurements is developed. By analogy with the Normalized Difference Vegetation Index NDVI), the Normalized Difference Cloud Index (NDCI) is defined as a ratio between the difference and the sum of two zenith radiances measured for two narrow spectral bands in the visible and near-IR regions. The very different spectral behavior of cloud liquid water drops and green vegetation is the key physics behind the NDCI. It provides extra tools to remove the radiative effects of the 3D cloud structure. Numerical calculations based on fractal clouds and real measurements of NDCI and cloud liquid water path confirm the improvements.

Marshak, A.↗
NASA NTRS2016

Application of the CERES Flux-by-Cloud Type Simulator to GCM Output

The CERES Flux By CloudType data product produces CERES top-of-atmosphere (TOA) fluxes by region and cloud type. Here, the cloud types are defined by cloud optical depth (t) and cloud top pressure (pc), with bins similar to those used by ISCCP (International Satellite Cloud Climatology Project). This data product has the potential to be a powerful tool for the evaluation of the clouds produced by climate models by helping to identify which physical parameterizations have problems (e.g., boundary-layer parameterizations, convective clouds, processes that affect surface albedo). Also, when the flux-by-cloud type and frequency of cloud types are simultaneously used to evaluate a model, the results can determine whether an unrealistically large or small occurrence of a given cloud type has an important radiative impact for a given region. A simulator of the flux-by-cloud type product has been applied to three-hourly data from the year 2008 from the UK Met Office HadGEM2-A model using the Langley Fu-Lour radiative transfer model to obtain TOA SW and LW fluxes.

Eitzen, Zachary↗
NASA NTRS2004

Cloud-Vegetation Radiative Interaction: What Can We Learn from it about Cloud Optical Properties?

Because of their radiative interactions, the vegetation canopy and the atmosphere are coupled together; each serves as a boundary condition to the radative transfer equations in the adjacent medium. To better understand radiative processes in these media we need an accurate description of their interactions. This presentation outlines a technique needed to describe interactions between vegetation and clouds and exploits it to retrieve cloud optical depth from ground-based radiance measurements. measurements of zenith radiance in the RED and NIR spectral regions. In addition to an algebraic combinations of spectral radiances such as Normalized Difference Cloud Index (NDCI) that can result in poor retrievals due to its insensitivity to cloud fraction, both RED and NIR radiances as points on the "RED vs. NIR" plane are proposed to be used for retrieval. The proposed method is applied to a multi-channel sunphotometer (as a part of AERONET) measurements at the ARM site in Oklahoma. In addition to cloud optical depth, the new method also infers a "radiatively effective" cloud fraction.

Marshak, Alexander↗
NASA NTRS2013

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations : Sensitivity Tests and Results - Part II

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Monte Carlo Bayesian inference↗