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The Clouds and Earth’s Radiant Energy System (CERES) has been monitoring clouds and radiation since 2000 using algorithms developed before 2002 for CERES Edition 2 (Ed2) products. To improve cloud amount accuracy, CERES Edition 4 (Ed4) applies revised algorithms and input data to Terra and Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) radiances. The Ed4 cloud mask uses 5–7 additional channels, new models for clear-sky ocean and snow/ice-surface radiances, and revised Terra MODIS calibrations. Mean Ed4 daytime and nighttime cloud amounts exceed their Ed2 counterparts by 0.035 and 0.068. Excellent consistency between average Aqua and Terra cloud fraction is found over nonpolar regions. Differences over polar regions are likely due to unresolved calibration discrepancies. Relative to Ed2, Ed4 cloud amounts agree better with those from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). CALIPSO comparisons indicate that Ed4 cloud amounts are more than or as accurate as other available cloud mask systems. The Ed4 mask correctly identifies cloudy or clear areas 90%–96% of the time during daytime over nonpolar areas depending on the CALIPSO–MODIS averaging criteria. At night, the range is 88%–95%. Accuracy decreases over land. The polar day and night accuracy ranges are 90%–91% and 80%–81%, respectively. The mean Ed4 cloud fractions slightly exceed the average for seven other imager cloud masks. Remaining biases and uncertainties are mainly attributed to errors in Ed4 predicted clear-sky radiances. The resulting cloud fractions should help CERES produce a more accurate radiation budget and serve as part of a cloud property climate data record.

The energy balance equation of an atmospheric column indicates that two approaches are possible to compute regional net surface energy flux. The first approach is to use the sum of surface energy flux components Fnet,c and the second approach is to use net top-of-atmosphere (TOA) irradiance and horizontal energy transport by the atmosphere Fnet,t. When regional net energy flux is averaged over the global ocean, Fnet,c and Fnet,t are, respectively, 16 and 2 Wm–2, both larger than the ocean heating rate derived from ocean temperature measurements. The difference is larger than the estimated uncertainty of Fnet,t of 11 Wm–2. Larger regional differences between Fnet,c and Fnet,t exist over tropical ocean. The seasonal variability of energy flux components averaged between 45°N and 45°S ocean reveals that the surface provides net energy to the atmosphere from May to July. These two examples demonstrates that the energy balance can be used to assess the quality of energy flux data products.

An enzyme-based electrochemical biodetection system and its corresponding hand-held prototype were developed to monitor pesticide concentrations. By combining biocatalyzation and electrochemistry, the reaction rate of bioredox was transformed into a current signal. The relationship between pesticide concentration and current inhibition rate could therefore be deduced, and pesticide concentration could be determined from output current signals. Different methods were tried to immobilize enzyme onto the surfaces of platinum electrode and screen-printed carbon electrode (SPE). The best performance was obtained by electropolymerization, which provided sensitivity two times higher than the enzyme under a suspended condition. In order to increase sensitivity, the electron mediator, i.e. Prussian Blue (PB) “KFeIIIFeII(CN)6−” was pre-coated onto the electrode surface and gold nanoparticles were intermingled during enzyme immobilization. The system, therefore, had a detection limit as low as 1 μg/L with a pesticide incubation time of 10 min. Experimental data indicate that pH value, temperature, heavy metal ions and organic solvents exerted influences on sensor performance. Even though the applicable temperature range could be expanded to be 10–40 °C via compensation equations, a proper pretreatment was necessary to eliminate the effect of heavy metal ions, especially for copper ions. This micro-biodetector was successfully applied to determine the pesticide residue in tomato juice, and was proven to be serviceable as a general commodity for household use.

Global cloud-top height statistics of marine-boundary-layer clouds are derived from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Level 2 aerosol and cloud layer products. The boundary-layer lapse rate in the northeast region of the Pacific Ocean is investigated using sea surface temperature (SST) data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), cloud-top temperature data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and cloud-top height data from CALIPSO. Based on the lapse rate derived from the combined CALIPSO/MODIS/AMSR-E measurements, cloud-top heights in regions within CALIPSO tracks are derived from AMSR SST and MODIS cloud temperature to test the validity of this approach. For homogeneous low-level clouds, the results agree with the cloud-top height from the collocated CALIPSO cloud-top height measurements. These results suggest that the database of derived lapse rates from the combined measurements can be applied to study cloud-top height climate statistics using the MODIS and AMSR data when CALIPSO observations are not available.

Cloud droplet effective radius (DER) and liquid water path (LWP) are two key parameters for the quantitative assessment of cloud effects on the exchange of energy and water. Chang and Li presented an algorithm using multichannel measurements made at 3.7, 2.1, and 1.6 μm to retrieve a cloud DER vertical profile for improved cloud LWP estimation. This study applies the multichannel algorithm to the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data on the Aqua satellite, which also carries the Advanced Microwave Scanning Radiometer (AMSR-E) for measuring cloud LWP and precipitation. By analyzing one day of coincident MODIS and AMSR-E observations over the tropical oceans between 40°S and 40°N for overcast warm clouds (>273 K) having optical depths between 3.6 and 23, the effects of DER vertical variation on the MODIS-derived LWP are reported. It is shown that the LWP tends to be overestimated if the DER increases with height within the cloud and underestimated if the DER decreases with height within the cloud. Despite the uncertainties in both MODIS and AMSR-E retrievals, the result shows that accounting for the DER vertical variation reduces the mean biases and root-mean-square errors between the MODIS- and AMSR-E–derived LWPs. Besides, the manner in which the DER changes with height has the potential for differentiating precipitative and nonprecipitative warm clouds. For precipitating clouds, the DER at the cloud top is substantially smaller than the DER at the cloud base. For nonprecipitating clouds, however, the DER differences between the cloud top and the cloud base are much less.

Studies using International Satellite Cloud Climatology Project (ISCCP) data have reported decreases in cloud optical depth with increasing temperature, thereby suggesting a positive feedback in cloud optical depth as climate warms. The negative cloud optical depth and temperature relationships are questioned because ISCCP employs threshold assumptions to identify cloudy pixels that have included partly cloudy pixels. This study applies the spatial coherence technique to one month of Advanced Very High Resolution Radiometer (AVHRR) data over the Pacific Ocean to differentiate overcast pixels from the partly cloudy pixels and to reexamine the cloud optical depth–temperature relationships. For low-level marine stratus clouds studied here, retrievals from partly cloudy pixels showed 30%–50% smaller optical depths, 1°–4°C higher cloud temperatures, and slightly larger droplet effective radii, when they were compared to retrievals from the overcast pixels. Despite these biases, retrievals for the overcast and partly cloudy pixels show similar negative cloud optical depth–temperature relationships and their magnitudes agree with the ISCCP results for the midlatitude and subtropical regions. There were slightly negative droplet effective radius–temperature relationships, and considerable positive cloud liquid water content–temperature relationships indicated by aircraft measurements. However, cloud thickness decreases appear to be the main reason why cloud optical depth decreases with increasing temperature. Overall, cloud thickness thinning may explain why similar negative cloud optical depth–temperature relationships are found in both overcast and partly cloudy pixels. In addition, comparing the cloud-top temperature to the air temperature at 740 hPa indicates that cloud-top height generally rises with warming. This suggests that the cloud thinning is mainly due to the ascending of cloud base. The results presented in this study are confined to the midlatitude and subtropical Pacific and may not be applicable to the Tropics or other regions.

Cloud overlapping has been a major issue in climate studies owing to a lack of reliable information available over both oceans and land. This study presents the first near-global retrieval and analysis of single-layer and overlapped cloud vertical structures and their optical properties retrieved by applying a new method to the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Taking full advantage of the MODIS multiple channels, the method can differentiate cirrus overlapping lower water clouds from single-layer clouds. Based on newly retrieved cloud products using daytime Terra/MODIS 5-km overcast measurements sampled in January, April, July, and October 2001, global statistics of the frequency of occurrence, cloud-top pressure/temperature (Pc/Tc), visible optical depth (τVIS), and infrared emissivity (ɛ) are presented and discussed. Of all overcast scenes identified over land (ocean), the MODIS data show 61% (52%) high clouds (Pc < 500 hPa), 39% (48%) lower clouds (Pc > 500 hPa), and an extremely low occurrence (

The frequent occurrence of high cirrus overlapping low water cloud poses a major challenge in retrieving their optical properties from spaceborne sensors. This paper presents a novel retrieval method that takes full advantage of the satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The main objectives are identification of overlapped high cirrus and low water clouds and determination of their individual optical depths, top heights, and emissivities. The overlapped high cloud top is determined from the MODIS CO2-slicing retrieval and the underlying low cloud top is determined from the neighboring MODIS pixels that are identified as single-layer low clouds. The algorithm applies a dual-layer cloud radiative transfer model using initial cloud properties derived from the MODIS CO2-slicing channels and the visible (0.65 μm) and infrared (11 μm) window channels. An automated iterative procedure follows by adjusting the high cirrus and low water cloud optical depths until computed radiances from the dual-layer model match with observed radiances from both the visible and infrared channels. The algorithm is valid for both single-layer and dual-layer clouds with the cirrus optical depth

An angular dependence model (ADM) describes the anisotropy in the reflectance field. ADMs are a key element in determining the top-of-the-atmosphere (TOA) albedos and radiative fluxes. This study utilizes 1-yr satellite data from the Scanner for Radiation Budget (ScaRaB) for overcast scenes to examine the variation of ADMs with cloud properties. Using ScaRaB shortwave (SW) overcast radiance measurements, an SW mean overcast ADM, similar to the Earth Radiation Budget Experiment (ERBE) ADM, was generated. Differences between the ScaRaB and ERBE overcast ADMs lead to biases of ∼0.01–0.04 in mean albedos inferred from specific angular bins. The largest biases are in the backward scattering direction. Overcast ADMs for the visible (VIS) wavelength were also generated using ScaRaB VIS measurements. They are very similar to, but a little smaller at large viewing angles and a little larger at nadir, than the SW overcast ADMs. To evaluate the effect of cloud properties on ADMs, ScaRaB overcast observation...

Cloud properties retrieved from satellite data are used to diagnose aircraft icing threat in single layer and multilayered ice-over-liquid clouds. The algorithms are being applied in real time to the Geostationary Operational Environmental Satellite (GOES) data over the CONUS with multilayer data available over the eastern CONUS. METEOSAT data are also used to retrieve icing conditions over western Europe. The icing algorithm s methodology and validation are discussed along with future enhancements and plans. The icing risk product is available in image and digital formats on NASA Langley s Cloud and Radiation Products web site, http://wwwangler. larc.nasa.gov.

Differences between spatial coherence and infrared threshold derived cloud cover were used to estimate errors in cloud cover that arise through the application of thresholds to imagery data. The differences indicated that threshold errors could be predicted by assuming that the cloud cover at the scale of a typical satellite imagery pixel (4–8 km) is uniformly distributed between some small value δ (δ < 0.2) and 1 − δ. In this study, results were obtained for single-layered cloud systems from four oceanic regions. Cloud cover was analyzed for both (60 km)2 and (250 km)2 regions. Three distinct infrared thresholds were used: (1) a “cloud-free threshold” for which the threshold was set slightly below the radiance observed for cloud-free pixels in the region; (2) an “overcast threshold” for which the threshold was set just above the radiance observed for pixels that were overcast in the region, and (3) a “midpoint threshold” for which the threshold was set midway between the radiances observed for cloud-free and overcast pixels. For the cloud-free threshold, cloud cover was overestimated; for the overcast threshold, cloud cover was underestimated, and for the midpoint threshold there was relatively little difference between the threshold and spatial coherence derived cloud cover. Mean differences in cloud cover were as large as 0.25 for (60 km)2 regions and 0.18 for (250 km)2 regions. Mean and rms differences reached maximum values when the regional cloud cover was 0.5. The fraction of 4- to 8-km imager pixels that were neither cloud free nor overcast was approximately 0.5. Furthermore, when the regional cloud cover (60–250 km) was small, the cloud cover in partially covered imager pixels was also small; likewise, when the regional cloud cover was large, the cloud cover in partially covered imager pixels was also large. This connection between regional scale cloud cover and 4- to 8-km pixel scale cloud cover suggests a link between large-scale fields which govern the regional cloud cover and the small-scale disturbances to the large-scale fields, which must govern the pixel scale cloud fraction.

Upper troposphere cloud top heights (CTHs), restricted to cloud top pressures (CTPs) less than 500 hPa, inferred using four satellite retrieval methods applied to Twelfth Geostationary Operational Environmental Satellite (GOES-12) data are evaluated using measurements during the July August 2007 Tropical Composition, Cloud and Climate Coupling Experiment (TC4). The four methods are the single-layer CO2-absorption technique (SCO2AT), a modified CO2-absorption technique (MCO2AT) developed for improving both single-layered and multilayered cloud retrievals, a standard version of the Visible Infrared Solar-infrared Split-window Technique (old VISST), and a new version of VISST (new VISST) recently developed to improve cloud property retrievals. They are evaluated by comparing with ER-2 aircraft-based Cloud Physics Lidar (CPL) data taken during 9 days having extensive upper troposphere cirrus, anvil, and convective clouds. Compared to the 89% coverage by upper tropospheric clouds detected by the CPL, the SCO2AT, MCO2AT, old VISST, and new VISST retrieved CTPs less than 500 hPa in 76, 76, 69, and 74% of the matched pixels, respectively. Most of the differences are due to subvisible and optically thin cirrus clouds occurring near the tropopause that were detected only by the CPL. The mean upper tropospheric CTHs for the 9 days are 14.2 (+/- 2.1) km from the CPL and 10.7 (+/- 2.1), 12.1 (+/- 1.6), 9.7 (+/- 2.9), and 11.4 (+/- 2.8) km from the SCO2AT, MCO2AT, old VISST, and new VISST, respectively. Compared to the CPL, the MCO2AT CTHs had the smallest mean biases for semitransparent high clouds in both single-layered and multilayered situations whereas the new VISST CTHs had the smallest mean biases when upper clouds were opaque and optically thick. The biases for all techniques increased with increasing numbers of cloud layers. The transparency of the upper layer clouds tends to increase with the numbers of cloud layers.

[1] Passive satellite retrievals using conventional CO2 absorption techniques tend to systematically underestimate the upper transmissive cloud top heights (CTHs). These techniques are based on single-layer assumptions that the upper cloud occupies a geometrically thin layer above a cloud-free surface. This study presents a new modified CO2 absorption technique (MCO2AT) to improve the inference of transmissive CTHs in the upper troposphere above 600 hPa. The MCO2AT employs an iterative algorithm that starts with a single-layer CO2 absorption technique (SCO2AT) followed by an iterative procedure to retrieve an enhanced upper CTH based on inferred effective background radiances. Both techniques are applied to the 10.7 and 13.3 μm channel data of the Twelfth Geostationary Operational Environmental Satellite (GOES 12) imager and their retrievals of upper tropospheric CTHs are compared with two active sensing products: the ground-based Active Remotely Sensed Cloud Location (ARSCL) products from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site and the satellite-based Cloud Aerosol Lidar With Orthogonal Polarization (CALIOP) products. On average, the CTHs from MCO2AT and SCO2AT are lower than those from both of the active sensors by ∼1 and 2.4 km, respectively, possibly due to the different sensitivities and spatial resolutions between passive and active sensors. Preliminary validation of the new modified method is encouraging, especially the improvements for upper transmissive clouds in geometrically thick and/or multilayered cloud situations. The development of the modified method is particularly useful for sensors like the GOES 12, Meteosat-9, and others, which carry only one CO2 absorption channel at ∼13.3 μm.

An enhancement to NASA Langley’s Visible Infrared Solar‐infrared Split‐window Technique (VISST) is developed to identify and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice cloud phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, cloud optical depths are reduced, hence, cloud height is increased. Cloud effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real‐time retrievals at Langley.

Multi-platform and multi-sensor observations are employed to investigate the impact of mineral dust on cloud microphysical and precipitation processes in mesoscale convective systems. It is clearly evident that for a given convection strength,small hydrometeors were more prevalent in the stratiform rain regions with dust than in those regions that were dust free. Evidence of abundant cloud ice particles in the dust sector, particularly at altitudes where heterogeneous nucleation process of mineral dust prevails, further supports the observed changes of precipitation. The consequences of the microphysical effects of the dust aerosols were to shift the precipitation size spectrum from heavy precipitation to light precipitation and ultimately suppressing precipitation.

A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixellevel results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.

[1] The albedo of marine stratocumuli depends upon cloud liquid water content, droplet effective radius (re), and how these parameters vary with height. Using satellite data and shipborne data from the East Pacific Investigation of Climate (EPIC) Stratocumulus Study, this study investigates the cloud re vertical variation for drizzling and nondrizzling clouds. Visible/near-infrared retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the vertical profile of re. MODIS re observations and collocated shipborne scanning C-band precipitation radar data show that re generally increases with height in nondrizzling clouds, consistent with aircraft observations. It is found that in clouds with precipitation rates greater than a few hundredths of a mm h−1 the vertical gradient of re is significantly less than that in nondrizzling clouds and can become negative when the drizzle is heavier than approximately 0.1 mm h−1. High values of re at drizzling cloud base are consistent with estimates of the ratio of liquid water in the drizzle drops to that in the cloud droplets. C-band derived cloud base precipitation rates are found to be better correlated with re at cloud base than with re at cloud top, suggesting that passive remote sensing may be useful for drizzle detection.

At NASA Langley Research Center (LaRC), radiances from multiple satellites are analyzed in near real-time to produce cloud products over many regions on the globe. These data are valuable for many applications such as diagnosing aircraft icing conditions and model validation and assimilation. This paper presents an overview of the multiple products available, summarizes the content of the online database, and details web-based satellite browsers and tools to access satellite imagery and products.

[1] Computation of components of shortwave (SW) or solar irradiance in the surface-atmospheric system forms the basis of intercomparison between 16 radiative transfer models of varying spectral resolution ranging from line-by-line models to broadband and general circulation models. In order of increasing complexity the components are: direct solar irradiance at the surface, diffuse irradiance at the surface, diffuse upward flux at the surface, and diffuse upward flux at the top of the atmosphere. These components allow computation of the atmospheric absorptance. Four cases are considered from pure molecular atmospheres to atmospheres with aerosols and atmosphere with a simple uniform cloud. The molecular and aerosol cases allow comparison of aerosol forcing calculation among models. A cloud-free case with measured atmospheric and aerosol properties and measured shortwave radiation components provides an absolute basis for evaluating the models. For the aerosol-free and cloud-free dry atmospheres, models agree to within 1% (root mean square deviation as a percentage of mean) in broadband direct solar irradiance at surface; the agreement is relatively poor at 5% for a humid atmosphere. A comparison of atmospheric absorptance, computed from components of SW radiation, shows that agreement among models is understandably much worse at 3% and 10% for dry and humid atmospheres, respectively. Inclusion of aerosols generally makes the agreement among models worse than when no aerosols are present, with some exceptions. Modeled diffuse surface irradiance is higher than measurements for all models for the same model inputs. Inclusion of an optically thick low-cloud in a tropical atmosphere, a stringent test for multiple scattering calculations, produces, in general, better agreement among models for a low solar zenith angle (SZA = 30°) than for a high SZA (75°). All models show about a 30% increase in broadband absorptance for 30° SZA relative to the clear-sky case and almost no enhancement in absorptance for a higher SZA of 75°, possibly due to water vapor line saturation in the atmosphere above the cloud.

[1] Ground-based radiation measurements are frequently used for validating the performance of a model in simulating clouds. Such important questions are often raised as: (1) How well do the measurements represent model grid mean values?; (2) How much of model-observation differences can be attributed to inherent sampling errors?; and (3) What scale does modeling need to be performed in order to capture the cloud variation? We attempt to address these questions using surface solar irradiance data retrieved from the Geostationary Operational Environmental Satellite (GOES) and measured at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The satellite retrievals are used to mimic ground measurements with various spatial densities and temporal frequencies, from which the sampling errors of the ground observations are quantified and characterized. Most of the differences between point-specific measurements and area-mean satellite retrievals originate from ground sampling errors. We quantify these errors for different months, model grid sizes, and integration intervals. In March 2000, for example, the sampling error is 16 W m−2 for instantaneous irradiances averaged over an area of 10 × 10 km2. It increases to 46 and 64 W m−2 if the model grid size is enlarged to 200 × 200 km2 and 400 × 400 km2, respectively. The sampling uncertainties decrease rapidly as the time-averaging interval increases up to 24 hours and then level off to a relatively small and stable value. Averaging over periods greater than 5 days reduces the error to a magnitude of less than 15 W m−2 over all grid sizes. The sampling error also decreases as the number of ground stations increases inside a grid, but the most substantial reduction occurs as the number of ground sites increases from 1 to 2 or 3 for a grid size of 200 × 200 km2. This means that for computing grid-mean surface solar irradiance, there is no need for an overly dense network of observation stations.

[1] In July 2002 Canadian forest fires produced a major smoke episode that blanketed the east coast of the United States. Properties of the smoke aerosol were measured in situ from aircraft, complementing operational Aerosol Robotic Network (AERONET), and Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed aerosol retrievals. This study compares single scattering albedo and phase function derived from the in situ measurements and AERONET retrievals in order to evaluate their consistency for application to satellite retrievals of optical depth and radiative forcing. These optical properties were combined with MODIS reflectance observations to calculate optical depth. The use of AERONET optical properties yielded optical depths 2–16% lower than those directly measured by AERONET. The use of in situ–derived optical properties resulted in optical depths 22–43% higher than AERONET measurements. These higher optical depths are attributed primarily to the higher absorption measured in situ, which is roughly twice that retrieved by AERONET. The resulting satellite retrieved optical depths were in turn used to calculate integrated radiative forcing at both the surface and top of atmosphere. Comparisons to surface (Surface Radiation Budget Network (SURFRAD) and ISIS) and to satellite (Clouds and Earth Radiant Energy System CERES) broadband radiometer measurements demonstrate that the use of optical properties derived from the aircraft measurements provided a better broadband forcing estimate (21% error) than those derived from AERONET (33% error). Thus AERONET-derived optical properties produced better fits to optical depth measurements, while in situ properties resulted in better fits to forcing measurements. These apparent inconsistencies underline the significant challenges facing the aerosol community in achieving column closure between narrow and broadband measurements and calculations.

[1] Chang and Li [2002] proposed a new cloud microphysics retrieval technique that can estimate the vertical profile of droplet effective radius (DER) for water clouds using multispectral near-infrared (NIR) measurements. The underlying principle of the retrieval technique is that radiance measurements at distinct multi-NIR wavelengths possess different penetration depths inside the cloud and this conveys certain information on the DER vertical profile (DVP). However, this information is insufficient to retrieve any shape of DVP and thus a linear DVP was assumed. In this study, three DVPs are examined: (1) as in Chang and Li [2002], a linear DVP proportional to the in-cloud optical depth, (2) a linear DVP proportional to the height within the cloud, and (3) a DVP where the liquid water content (LWC) within the cloud varies linearly with height. The latter two assumptions are in closer conformity with in-situ observations. Algorithms that can retrieve both the DVP and cloud liquid water path (LWP) are presented. The cloud LWPs derived based on the retrieved DVPs are more sound than those obtained from assuming a vertical-constant DER profile. To enhance the DVP retrievals, a split-window technique is presented to better estimate the amount of above-cloud precipitable water (PW). The retrieval algorithms are applied to the MODIS Level-1B 1-km data and presently tested for two stratiform cloud cases observed over the north-central Oklahoma where independent cloud microphysics data are available from the United States Department of Energy's Atmospheric Radiation Measurement (ARM) Program. Good agreements in the retrieved DER profile, LWP, and above-cloud PW are found in a preliminary demonstration of the new approach. Sensitivity of the retrieved DER profile to uncertainties in the above-cloud PW and surface albedos is also discussed.

[1] This paper presents a satellite-based retrieval method for inferring the vertical variation of cloud droplet effective radius (DER) by utilizing multispectral near-infrared (NIR) measurements at 1.25, 1.65, 2.15, and 3.75 μm, available from the Moderate Resolution Imaging Spectrometer (MODIS) satellite observations. The method is based on the principle that these multispectral NIR measurements convey DER information from different heights within a cloud, which is sufficient to allow for the retrieval of a linear DER vertical profile. The method is applicable to low-level, nonprecipitating, stratiform clouds as their DER often increases monotonically from cloud bottom to cloud top. As such, an optimum linear DER profile can be derived by comparing multispectral NIR measurements to corresponding model values generated for a large set of linear DER profiles. The retrieval method was evaluated and compared to the conventional 3.7-μm retrieval method by applying both methods to some marine stratocumulus clouds with in situ observations of microphysical profiles. Capable of capturing the DER variation trend, the retrieved linear DER profiles showed large improvement over the conventional 3.75-μm retrievals. Mean differences between the linear DER retrievals and observed profiles were generally small for both cloud top and bottom (

This study examines the consistency and inconsistency in shortwave (SW) top-of-atmosphere (TOA) reflectances and albedos obtained from satellite measurements of the Earth Radiation Budget Experiment (ERBE) and radiation modeling based on cloud properties retrieved from the Advanced Very High Resolution Radiometer (AVHRR). The examination focuses on completely overcast scenes covered by low-level, single-layered, maritime stratus with uniform cloud-top heights as determined from AVHRR measurements at near nadir. A radiation model was then applied to the retrieved cloud optical depths, droplet effective radii, and top temperatures to compute the SW TOA reflectances and albedos that are compared with coincident ERBE observations. ERBEobserved and AVHRR-based modeled reflectances show excellent agreement in terms of both trend and magnitude, but the two albedos exhibit significant differences that have a strong dependence on cloud optical properties and solar zenith angle (SZA). To unravel the differences, two major factors, that is, scene identification and angular dependence model (ADM), involved in converting reflectance to albedo are examined. It is found that the dependence is mainly caused by the use of a single ERBE‐ADM for all overcast scenes, regardless of cloud optical properties. The mean difference in SW TOA flux is about 4‐12 W m22, depending on SZA, but individual differences may reach up to 40‐50 W m22 for persistent large or small cloud optical depths. Nearly all of the uniform low-level overcast scenes as determined by AVHRR are identified as mostly cloudy by ERBE, but the misidentification does not have any adverse effect on the albedo differences. In fact, replacing the ERBE mostly cloudy ADM with the overcast ADM exacerbates the albedo comparisons. The mean fluxes obtained with the two ADMs differ by ; 8Wm 22 at SZA 338 and by 30 W m22 at SZA 608.

Performances of two cloud property retrieval schemes are assessed by comparison with each other. The study is limited to liquid phase clouds, Two parameters are assessed: cloud optical depth in the visible band and broadband shortwave (SW) flux at the top-of-atmosphere (TOA). Retrievals are based on look-up tables for a variety of conditions using an adding-doubling code coupled with LOWTRAN-7 transmittance models. Comparisons of cloud optical depths retrieved from ground measurements with those from ISCCP DX data agree better than previously reported comparisons with the original ISCCP CX data. Likewise, good agreement is obtained between retrieved and inferred TOA SW fluxes. Differences fall within uncertainties of input parameters, as well as shortcomings in the use of a plane-parallel radiative transfer model and in the inversion schemes themselves.