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 GOES-
10/11/12, 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 pixel-level
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.
This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and
radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES)
and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat
radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and
passive datasets are compared to determine commonalities and differences in order to facilitate the development of a
3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint.
Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on
average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide
unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect
radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions
and for multi-layered cloud conditions.
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.
The micro- and macrophysical properties of clouds play a crucial role in Earth’s radiation budget. The NASA Clouds and Earth’s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.
The Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra, with its high horizontal resolution and frequent sampling over Arctic and Antarctic regions, provides unique data sets to study clouds and the surface energy balance over snow and ice surfaces. This paper describes a polar cloud mask using MODIS data. The daytime cloud and snow identification methods were developed using theoretical snow bi-directional reflectance models for the MODIS 1.6 and 3.75 micron channels. The model-based polar cloud mask minimizes the need for empirically adjusting the thresholds for a given set of conditions and reduces the error accrued from using single-value thresholds. During night, the MODIS brightness temperature differences (BTD) for 3.75 - 11, 3.75 - 12, 8.55 - 11, and 6.7 - 11 micron are used to detect clouds while snow and ice maps are used to determine snow and ice surfaces. At twilight, the combination of the 1.6 micron reflectance and the 3.75 - 11 micron BTD are used to detect clouds. Examples of the cloud mask results from daytime, nighttime, and twilight data show good agreement with visual interpretation of the imagery. Comparisons of the modeled and observed reflectances for clear snow areas reveal good agreement at 1.6 micron, but 10 - 35% overestimates of the 3.75 micron reflectance by the model. Over the Arctic, the modeled visible reflectance is significantly greater than the observed values. Better agreement is obtained over the Antarctic where snow melt is less significant.
The NASA CERES Project has developed a combined radiation and cloud property dataset using the CERES scanners and matched spectral data from high-resolution imagers, the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The diurnal cycle can be well-characterized over most of the globe using the combinations of TRMM, Aqua, and Terra data. The cloud properties are derived from the imagers using state-of-the-art methods and include cloud fraction, height, optical depth, phase, effective particle size, emissivity, and ice or liquid water path. These cloud products are convolved into the matching CERES fields of view to provide simultaneous cloud and radiation data at an unprecedented accuracy. Results are available for at least 3 years of VIRS data and 1 year of Terra MODIS data. The various cloud products are compared with similar quantities from climatological sources and instantaneous active remote sensors. The cloud amounts are very similar to those from surface observer climatologies and are 6-7% less than those from a satellite-based climatology. Optical depths are 2-3 times smaller than those from the satellite climatology, but are within 5% of those from the surface remote sensing. Cloud droplet sizes and liquid water paths are within 10% of the surface results on average for stratus clouds. The VIRS and MODIS retrievals are very consistent with differences that usually can be explained by sampling, calibration, or resolution differences. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.