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NASA NTRS2012

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Yost, Christopher R.↗
NASA NTRS2006

Radiative Effect of Clouds on Tropospheric Chemistry in a Global Three-Dimensional Chemical Transport Model

Clouds exert an important influence on tropospheric photochemistry through modification of solar radiation that determines photolysis frequencies (J-values). We assess the radiative effect of clouds on photolysis frequencies and key oxidants in the troposphere with a global three-dimensional (3-D) chemical transport model (GEOS-CHEM) driven by assimilated meteorological observations from the Goddard Earth Observing System data assimilation system (GEOS DAS) at the NASA Global Modeling and Assimilation Office (GMAO). We focus on the year of 2001 with the GEOS-3 meteorological observations. Photolysis frequencies are calculated using the Fast-J radiative transfer algorithm. The GEOS-3 global cloud optical depth and cloud fraction are evaluated and generally consistent with the satellite retrieval products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Satellite Cloud Climatology Project (ISCCP). Results using the linear assumption, which assumes linear scaling of cloud optical depth with cloud fraction in a grid box, show global mean OH concentrations generally increase by less than 6% because of the radiative effect of clouds. The OH distribution shows much larger changes (with maximum decrease of approx.20% near the surface), reflecting the opposite effects of enhanced (weakened) photochemistry above (below) clouds. The global mean photolysis frequencies for J[O1D] and J[NO2] in the troposphere change by less than 5% because of clouds; global mean O3 concentrations in the troposphere increase by less than 5%. This study shows tropical upper tropospheric O3 to be less sensitive to the radiative effect of clouds than previously reported (approx.5% versus approx.20-30%). These results emphasize that the dominant effect of clouds is to influence the vertical redistribution of the intensity of photochemical activity while global average effects remain modest, again contrasting with previous studies. Differing vertical distributions of clouds may explain part, but not the majority, of these discrepancies between models. Using an approximate random overlap or a maximum-random overlap scheme to take account of the effect of cloud overlap in the vertical reduces the impact of clouds on photochemistry but does not significantly change our results with respect to the modest global average effect.

Liu, Hongyu↗
NASA NTRS1981

Infrared radiative transfer through a regular array of cuboidal clouds

Infrared radiative transfer through a regular array of cuboidal clouds is studied and the interaction of the sides of the clouds with each other and the ground is considered. The theory is developed for black clouds and is extended to scattering clouds using a variable azimuth two-stream approximation. It is shown that geometrical considerations often dominate over the microphysical aspects of radiative transfer through the clouds. For example, the difference in simulated 10 micron brightness temperature between black isothermal cubic clouds and cubic clouds of optical depth 10, is less than 2 deg for zenith angles less than 50 deg for all cloud fractions when viewed parallel to the array. The results show that serious errors are made in flux and cooling rate computations if broken clouds are modeled as planiform. Radiances computed by the usual practice of area-weighting cloudy and clear sky radiances are in error by 2 to 8 K in brightness temperature for cubic clouds over a wide range of cloud fractions and zenith angles. It is also shown that the lapse rate does not markedly affect the exiting radiances for cuboidal clouds of unit aspect ratio and optical depth 10.

HARSHVARDHAN↗
NASA NTRSDate not supplied

EPIC Cloud Observations with Oxygen Bands Over Snow, Ice and Sunglint Regions

Cloud detections over snow/ice surfaces and sunglint regions are challenging with passive remote sensing instrument due to lack of contract between cold/bright surfaces in the former and glint reflectance that could exceed that of cloudy sky in the latter. We developed novel cloud detection algorithms for these regions utilizing EPIC’s unique oxygen-bands. Over the snow and ice surfaces, a dynamic threshold scheme based on the ratios of two pairs of EPIC’s oxygen bands are developed to significantly improve the existing algorithm in these regions. Over the ocean, we improved the EPIC’s ocean cloud mask algorithm by implementing a dynamic reflectance threshold and supplemental A-band ratio test for cloud detection in the sun glint regions. The new ocean cloud mask algorithm improves the diurnal cycles of cloud fraction over ocean by reducing the artificial peak at local noon time in the glint center latitudes and reducing early morning and afternoon cloud fraction in most oceanic regions.

EPIC↗
NASA NTRS1987

Computation and analyses of averaged monthly zonal albedos at the top of the atmosphere using Nimbus-7 ERB observed data

The Nimbus-7 ERB experiment measures the Earth's albedo from a satellite in a fixed Sun synchronous orbit. The data is obtained at a fixed time of the day for each latitude observed. For Earth Radiation Budget studies it is normally assumed that the observed scene is invariant during the day and that the albedo varies only with the solar zenith angle. This paper presents a technique for computing mean zonal albedos as a function of the albedo (A sub s) of cloud free atmosphere, the albedo (A sub c) of cloudy atmosphere and of the cloud fractions. The values of A sub s and A sub c are obtained from radiation transfer theory and climatological values of the surface and cloud albedos. The albedos are a function of the solar zenith angle, latitude and solar declination. The cloud fractions are measured from the Nimbus-7 ERB albedos. The present study shows the importance of taking into account latitude variations in surface types and in cloud cover.

Dhuria, Harbans↗
NASA NTRS2010

Analyzing the Effect of Intraseasonal Meteorological Variability and Land Cover on Aerosol-Cloud Interactions During the Amazonian Biomass Burning Season

High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and pasture is not correlated with aerosol loading, supporting the assumption that temporal variation of column water vapor is primarily a function of the larger-scale meteorology. However, a difference in the response of cloud fraction to increasing AOD is observed between forest and pasture. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, are likely to have an impact on aerosol-cloud correlations between different land-cover types.

TenHoeve, J. E.↗
NASA NTRS2002

Evaluation of Methods to Estimate the Surface Downwelling Longwave Flux during Arctic Winter

Surface longwave radiation fluxes dominate the energy budget of nighttime polar regions, yet little is known about the relative accuracy of existing satellite-based techniques to estimate this parameter. We compare eight methods to estimate the downwelling longwave radiation flux and to validate their performance with measurements from two field programs in thc Arctic: the Coordinated Eastern Arctic Experiment (CEAREX ) conducted in the Barents Sea during the autumn and winter of 1988, and the Lead Experiment performed in the Beaufort Sea in the spring of 1992. Five of the eight methods were developed for satellite-derived quantities, and three are simple parameterizations based on surface observations. All of the algorithms require information about cloud fraction, which is provided from the NASA-NOAA Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) polar pathfinder dataset (Path-P): some techniques ingest temperature and moisture profiles (also from Path-P): one-half of the methods assume that clouds are opaque and have a constant geometric thickness of 50 hPa, and three include no thickness information whatsoever. With a somewhat limited validation dataset, the following primary conclusions result: (1) all methods exhibit approximately the same correlations with measurements and rms differences, but the biases range from -34 W sq m (16% of the mean) to nearly 0; (2) the error analysis described here indicates that the assumption of a 50-hPa cloud thickness is too thin by a factor of 2 on average in polar nighttime conditions; (3) cloud-overlap techniques. which effectively increase mean cloud thickness, significantly improve the results; (4) simple Arctic-specific parameterizations performed poorly, probably because they were developed with surface-observed cloud fractions; and (5) the single algorithm that includes an estimate of cloud thickness exhibits the smallest differences from observations.

Chiacchio, Marc↗
NASA NTRS2018

The Diurnal Cycle of Cloud Profiles over Land and Ocean Between 51degS and 51degN, Seen by the CATS Spaceborne Lidar from the International Space Station

We document, for the first time, how detailed vertical profiles of cloud fraction (CF) change diurnally between 51 deg S and 51 deg N, by taking advantage of 15 months of measurements from the Cloud-Aerosol Transport System (CATS) lidar on the non-sun-synchronous International Space Station (ISS). Over the tropical ocean in summer, we find few high clouds during daytime. At night they become frequent over a large altitude range (11-16 km between 22:00 and 04:00 LT). Over the summer tropical continents, but not over ocean, CATS observations reveal mid-level clouds (4-8 km above sea level or a.s.l.) persisting all day long, with a weak diurnal cycle (minimum at noon). Over the Southern Ocean, diurnal cycles appear for the omnipresent low-level clouds (minimum between noon and 15:00) and high-altitude clouds (minimum between 08:00 and 14:00). Both cycles are time shifted, with high-altitude clouds following the changes in low-altitude clouds by several hours. Over all continents at all latitudes during summer, the low-level clouds develop upwards and reach a maximum occurrence at about 2.5 km a.s.l. in the early afternoon (around 14:00). Our work also shows that (1) the diurnal cycles of vertical profiles derived from CATS are consistent with those from ground-based active sensors on a local scale, (2) the cloud profiles derived from CATS measurements at local times of 01:30 and 13:30 are consistent with those observed from CALIPSO at similar times, and (3) the diurnal cycles of low and high cloud amounts (CAs) derived from CATS are in general in phase with those derived from geostationary imagery but less pronounced. Finally, the diurnal variability of cloud profiles revealed by CATS strongly suggests that CALIPSO measurements at 01:30 and 13:30 document the daily extremes of the cloud fraction profiles over ocean and are more representative of daily averages over land, except at altitudes above 10 km where they capture part of the diurnal variability. These findings are applicable to other instruments with local overpass times similar to CALIPSO's, such as all the other A-Train instruments and the future Earth-CARE mission.

Noel, Vincent↗
NASA NTRS2005

Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

Luo, Yali↗
NASA NTRS1981

Local effects of partly cloudy skies on solar and emitted radiations

Solar radiation measurements are made on a routine basis. Global solar, atmospheric emitted, downwelled diffuse solar, and direct solar radiation measurement systems are fully operational with the first two in continuous operation. Fractional cloud cover measurements are made from GOES imagery or from ground based whole sky photographs. Normalized global solar irradiance values for partly cloudy skies were correlated to fractional cloud cover.

Whitney, D. A.↗
NASA NTRSDate not supplied

Development of a Consistent MODIS and VIIRS Cloud Detection Approach for CERES

A consistent cloud fraction record across various satellite platforms is essential for maintaining a long-term and stable climate data record of Earth's energy budget. With the Aqua satellite nearing the end of its operational lifetime, the continuation of this record relies on utilizing VIIRS observations from NOAA20 for cloud detection in NASA’s Clouds and Earth’s Radiant Energy System (CERES) project. However, integrating data from VIIRS and MODIS instruments poses challenges due to their distinct characteristics, such as varying spatial resolutions and different spectral channels. As a result, deriving consistent cloud properties from these two sensors without introducing artificial discontinuities in the time series remains a complex and challenging task. This paper will present progress toward developing a unified MODIS and VIIRS cloud mask using common channels to produce consistent cloud properties for CERES next edition (Ed5) Earth radiation budget data products. The fundamental approach taken in the CERES cloud mask is to compare the observed radiances to the expected background clear sky radiances. Therefore, one vital step is to compute clear sky radiances with a radiative transfer model that accurately accounts for satellite-specific, spectrally dependent surface reflectance, surface emission, and atmospheric absorption. Refined radiative transfer models and updated ancillary data inputs including surface emissivity maps, IGBP, snow and ice maps are incorporated into the processing framework to improve cloud detection consistency and accuracy. Pixel level cloud mask results and monthly global cloud fraction comparisons between MODIS and VIIRS will be presented to evaluate their consistency. Remaining challenges will be discussed. It is expected that this work will contribute consistent cloud properties for CERES that adequately bridges the MODIS and VIIRS imager data records.

CERES↗
NASA NTRS2022

Cloud Adjustments From Large-Scale Smoke–Circulation Interactions Strongly Modulate the Southeastern Atlantic Stratocumulus-to-Cumulus Transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (∼1–2 K) and greatly enhanced moisture (>2 g kg−1) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

southeast Atlantic Ocean↗
NASA NTRSDate not supplied

Parameterization of Vertical Cloud Distribution from C3M and MERRA Data Using ML Method

Clouds play a key role in regulating the hydrological cycle and the Earth's radiative energy budget. However, global climate models (GCMs) with a horizontal grid spacing on the order of 100 km have limitations in representing sub-grid cloud dynamics with spatial scales on the order of 1 km, leading to potential uncertainties in cloud radiative feedback on the global scale. In our research, we will leverage the capabilities of Deep Machine Learning (DML) methods to construct parameterizations of sub-grid volumetric cloud fraction (VCF), which is the frequency of occurrence on a grid volume accumulated in the horizontal and vertical directions. Our investigation delves into the intricate relationship between VCF obtained from the NASA CALIPSO-CloudSat-CERES-MODIS (CCCM) satellite observation data and 3-D MERRA-2 reanalysis meteorological profiling data (e.g., wind, relative humidity, temperature). Through a comprehensive one-year data training utilizing the Sequence to Sequence DML method, we have successfully disentangled the complicated cloud formation dynamics across diverse meteorological conditions through a day-to-day analysis framework. Preliminary findings reveal promising statistical agreements in geographical and vertical distributions and seasonal variations of volumetric cloud fraction between ML prediction and satellite measurements. These results underscore the aptitude of our DML model to discern underlying cloud physical processes and accurately represent sub-grid cloud formation dynamics. Additionally, we have also employed trained neural network to analyze uncertainties arising from errors in meteorological data, further enhancing the robustness of our VCF parameterization.

Shan Zeng↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11082-DND

Analysis of one decade of radar-lidar and Geostationary Operational Environmental Satellite (GOES) observations at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) site reveals that there is excellent agreement in the long-term mean cloud fractions (CF) derived from the surface and GOES data, and the CF is independent of temporal resolution and spatial scales for grid boxes of size 0.5o to 2.5°. When computed over a 0.5-hr (4-hr) period, cloud frequency of occurrence (FREQ) and amount when present (AWP) derived from the point surface data agree very well with the same quantities determined from GOES for a 0.5o (2.5o) region centered on the ARM SGP site. The values of FREQ (AWP) derived from the radar-lidar observations at a given altitude increase (decrease) as the averaging period increases from 5 min to 6 hours. Similarly, CF at a given altitude increases as the vertical resolution increases from 90 to 1000 m. The profiles of CF have distinct bimodal vertical distributions with a lower peak between 1 and 2 km and a higher one between 8 and 11 km. The 10-year mean total CF, 46.9%, varies seasonally from a summer minimum of 39.8% to a maximum of 54.6% during the winter. The annual mean CF is 1-2% less than that from previous studies, ~48-49%, because fewer clouds occurred during 2005 and 2006, especially during winter. The differences in single- and multi-layered CFs between this study and an earlier analysis can be explained by the different temporal resolutions used in the two studies where single-layered CFs decrease but multilayered CFs increase from a 5-min resolution to a 1-hr resolution. The vertical distribution of nighttime GOES high-cloud tops agrees well with surface observations, but during daytime, fewer high clouds are retrieved by the GOES analysis than seen from the surface observations. The frequencies of occurrence for both daytime and nighttime GOES low-cloud tops are significantly higher than surface observations, but the cloud fractions are in good agreement.

B Xi↗
NASA NTRS1990

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than does a global choice of a visible and/or infrared threshold. The classification also prevents erroneous estimates of large fractional cloudiness in areas of cloudfree snow and sea ice. The hybrid histogram-spatial coherence technique and the advantages of first classifying a scene in the polar regions are detailed. The complete Polar Cloud Pilot Data Set was analyzed and the results are presented and discussed.

Smith, William L.↗
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 NTRS2003

Inferring Cloud Properties from Passive Solar Sensors

The most common approach for retrieving cloud optical depth from ground-based observations uses downwelling fluxes measured by pyranometers and Multi-Filter Rotating Shadowband Radiometers (MFRSR). The key element in both retrieval techniques is the one-to-one mapping of the "observed" fluxes into cloud optical depth through plane-parallel radiative transfer. Both methods are expected to work well only for completely overcast clouds giving an effective optical depth for the whole sky. To infer cloud optical depth locally one can assume to use a narrow-field-of view radiometer that measures radiances instead of fluxes. However, lack of one-to-one relationships between radiance and cloud optical depth, prevents the direct use of radiances either. Here we discuss a new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (NIR) spectral regions. In addition to an algebraic combinations of spectral radiances such as Normalized Difference Cloud Index (NDCI) that largely removes nonuniqueness and the radiative effects of cloud inhomogeneity but 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 retrieval method is applied to a multi- channel sunphotometer (as a part of AERONET) measurements at the ARM site in Oklahoma. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and MFRSR. In addition to cloud optical depth, the new retrieval method also infers a "radiatively effective" cloud fraction.

Marshak, A.↗
NASA NTRS2004

The Liquid-Water Oscillation in Modeling Boundary-Layer Cumuli with Third-Order Turbulence Closure Models

A hierarchy of third-order turbulence closure models are used to simulate boundary-layer cumuli in this study. An unrealistically strong liquid-water oscillation (LWO) is found in the fully prognostic model, which predicts all third moments. The LWO propagates from cloud base to cloud top with a speed of 1 m/s. The period of the oscillation is about 1000 s. Liquid-water buoyancy terms in the third-moment equations contribute to the LWO. The LWO mainly affects the vertical profiles of cloud fraction, mean liquid-water mixing ratio and the fluxes of liquid-water potential temperature and total water, but has less impact on the vertical profiles of other second-moments and third-moments. In order to minimize the LWO, a moderate large diffusion coefficient and a large turbulent dissipation at its originating level are needed. However, this approach distorts the vertical distributions of cloud fraction and liquid-water mixing ratio. A better approach is to parameterize liquid-water buoyancy more reasonably. A minimally prognostic model, which diagnoses all third moments except for vertical velocity, is shown to produce better results, compared to a fully prognostic model.

Cheng, A.↗