Cumulus cloud base height estimation from high spatial resolutionLandsat data: a Hough transform approach

This study develops a semiautomated methodology for estimating cumulus cloud base heights using high-spatial-resolution Landsat multispectral scanner data. The approach employs a variety of image processing techniques to match cloud edges with their corresponding shadow edges. Cloud base height is then estimated by computing the separation between the corresponding generalized Hough transform reference points. Sixteen subregions, each 30 km×30 km in size, are selected for four Landsat scenes. Standard deviations of cloud base height within each of the subregion range from about 100 m to 150 m. Differences between cloud base heights computed using the Hough transform and a manual verification technique are small. It is estimated that cloud base height accuracies of 50-70 m may be possible using HIRIS and ASTER instruments in the Earth Observation Satellite (EOS) Global Climate Change program     

Application of deep convective cloud albedo observation to satellite-based study of the terrestrial atmosphere: monitoring the stability of spaceborne measurements and assessing absorption anomaly

An objective method is developed to monitor the stability of spaceborne instruments, aimed at distinguishing climate trend from instrument drift in satellite-based climate observation records. This method is based on four-years of Clouds and the Earth's Radiant Energy System (CERES) broadband observations of deep convective cloud systems with cloud-top temperature lower than 205 K and with large optical depths. The implementation of this method to the CERES instrument stability analysis reveals that the monthly albedo distributions are practically the same for deep convective clouds with CERES measurements acquired from both the Tropical Rainfall Measuring Mission and Terra satellite platforms, indicating that CERES instruments are well calibrated and stable during both missions. Furthermore, with a nonlinear regression neural network narrowband-broadband conversion, this instrument-stability monitoring method can also be applied to narrowband instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Scanner (VIRS). The results show that the drifts associated with both VIRS and MODIS instruments are less than 1% during a four-year period. Since the CERES albedo measurements are highly accurate, the absorptance of these opaque clouds can be reliably estimated. The absorptions of these clouds from observations are around 25%, whereas the absorptions from theory can be as low as 18%, depending on ice cloud microphysics.     

Clouds and the Earth's Radiant Energy System (CERES): algorithmoverview

The Clouds and the Earth's Radiant Energy System (CERES) is part of NASA's Earth Observing System (EOS), CERES objectives include the following. (1) For climate change analysis, provide a continuation of the Earth Radiation Budget Experiment (ERBE) record of radiative fluxes at the top-of-the-atmosphere (TOA), analyzed using the same techniques as the existing ERBE data. (2) Double the accuracy of estimates of radiative fluxes at TOA and the Earth's surface. (3) Provide the first long-term global estimates of the radiative fluxes within the Earth's atmosphere. (4) Provide cloud property estimates collocated in space and time that are consistent with the radiative fluxes from surface to TOA. In order to accomplish these goals, CERES uses data from a combination of spaceborne instruments: CERES scanners, which are an improved version of the ERBE broadband radiometers, and collocated cloud spectral imager data on the same spacecraft. The CERES cloud and radiative flux data products should prove extremely useful in advancing the understanding of cloud-radiation interactions, particularly cloud feedback effects on the Earth's radiation balance. For this reason, the CERES data should be fundamental to the ability to understand, detect, and predict global climate change. CERES results should also be very useful for studying regional climate changes associated with deforestation, desertification, anthropogenic aerosols, and ENSO events. This overview summarizes the Release 3 version of the planned CERES data products and data analysis algorithms. These algorithms are a prototype for the system that will produce the scientific data required for studying the role of clouds and radiation in the Earth's climate system