Measurements
The MODerate-resolution Imaging Spectroradiometers (MODIS) aboard the NASA EOS platforms Terra and Aqua have provided 1-km narrowband measurements of Earth reflected and emitted radiation in 32 spectral bands since May 2002. For use with the Clouds and the Earth’s Radiant Energy System (CERES), the MODIS data are sampled at every fourth pixel and every other scan line so that the measured radiance is assumed to represent a 4 km x 2 km area. An array of 5 x 10 of these sampled pixels correspond to a CERES broadband radiometer footprint. Cloud properties from the CERES-MODIS algorithms are matched with the CERES broadband radiometer fluxes to study the Earth radiation system.
By assuming that a cloud will cause a deviation in one or more spectral radiances relative to those expected for a cloud-free scene, it is possible to detect cloudy pixels if a reasonable representation of the relevant clear-sky radiances is available. Cloud properties are retrieved by matching the observed radiances with those generated with a physical model of radiative transfer for a range of cloud phase, heights, optical depths, and hydrometeor sizes.
Local Observation Time and Length of Data Record
Terra, 10:30 AM and 10:30 PM ; 2000–2020
Aqua, 1:30 AM and 1:30 PM ; 2002–2020
Spatial Resolution
1 km at nadir, sampled
Cloud Detection
Sequence of multispectral spectral threshold tests against expected clear-sky radiances, relying heavily on the 0.65-µm reflectance and the 3.8- and 10.8-µm brightness temperatures with other channels used for more ambiguous radiance combinations. At night, the 12.0-µm brightness temperature is used in more of the logic since the solar reflectance channels are unavailable.
Retrieval Methodology
The Satellite ClOud and Radiation Property System (SatCORPS), developed at NASA Langley Research Center, is being used to determine cloud properties from Aqua and Terra MODIS, VIIRS, AVHRR, and geostationary satellite imager data. It operates in both near-real time and a posteriori modes and can be applied to any other satellite data having spectral complements similar to AVHRR.
The cloud properties, cloud effective temperature, CRE, COD, and cloud phase are determined using an iterative scheme that simultaneously matches 0.65 (snow-free) or 1.24 (snow), 3.7, and 10.8-µm radiances to parameterized estimates of radiances for a range of optical depths, cloud heights, particle sizes, and phase. At night, CT as well as thin-cloud COD and CRE are determined in a similar manner, but the 12.0-µm brightness temperature replaces the solar reflectance. CRE is also retrieved using the 2.13-µm channel. CT is estimated from the cloud effective temperature based on empirical relationships relying on COD and cloud phase. CZ and CP are determined from the temperature/pressure height profile, which is modified in the boundary layer to accommodate low-level inversions. CLWP and CIWP are proportional to the product of CRE and COD. Cloud properties and fractional coverage have been evaluated via comparisons with surface and aircraft observations as well as CloudSat and CALIPSO profiles.
Ancillary Input
- atmospheric T, O3, and H2O profiles, surface T from NASA GEOS-5.4 meteorological reanalysis data
- changes to MODIS calibrations
- black space cloud spectral reflectance lookup tables for liquid and ice clouds; single scattering properties of ice crystals are based on roughened hexagonal columns (Yang) based on DISORT radiative transfer
- spectral cloud emissivity parameterization coefficients based on DISORT radiative transfer
- normalized spectral bidirectional reflectance distribution functions for various surface types and ocean spectral reflectance parameterization
- spectral surface emissivities and albedos (monthly climatology) from AVHRR and MODIS data
- . surface type, snow cover, and water surface coverage
References
- Sun-Mack, P. Minnis, Y. Chen, D. R. Doelling, B. Scarino, C. O. Haney, and W. L. Smith, Jr., 2018: Calibration changes to Terra MODIS Collection-5 radiances for CERES Edition 4 cloud retrievals. IEEE Trans. Geosci. Remote Sens., 56, 6016-6032, doi:10.1109/TGRS.2018.2829902.
- Trepte, Q. Z., P. Minnis, S. Sun-Mack, C. R. Yost, Y. Chen, Z. Jin, F.-L. Chang, W. L. Smith, Jr., K. M. Bedka, and T. L. Chee, 2019: Global cloud detection for CERES Edition 4 using Terra and Aqua MODIS data. IEEE Trans. Geosci. Remote Sens., 57, 9410-9449, doi:10.1109/TGRS.2019.2926620.
- Minnis, P., S. Sun-Mack, C. R. Yost, Y. Chen, W. L. Smith, Jr., F.-L. Chang, P. W. Heck, R. F. Arduini, Q. Z. Trepte, K. Ayers, K. Bedka, S. Bedka, R. R. Brown, E. Heckert, G. Hong, Z. Jin, R. Palikonda, R. Smith, B. Scarino, D. A. Spangenberg, P. Yang, Y. Xie, and Y. Yi, 2020: CERES MODIS cloud product retrievals for Edition 4, Part I: Algorithm changes to CERES MODIS. IEEE Trans. Geosci. Remote Sens., 59, 2744-2780, doi:10.1109/TGRS.2020.3008866.
- Yost, C., P. Minnis, S. Sun-Mack, Y. Chen, and W. L. Smith, Jr., 2021: CERES MODIS cloud product retrievals for Edition 4, Part II: Comparisons to CloudSat and CALIPSO. IEEE Trans. Geosci. Remote Sens., 59, doi:10.1109/TGRS.2020.3015155.
CERES Data Website