SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This Algorithm Basis (ATB) document describes the algorithms used to retrieve the Radiometic Camera-by-camera Cloud Mask (RCCM) within the MISR level 1B2 Geo-rectified Radiance Product.
The Hyperspectral Infrared Imager (HyspIRI) satellite includes a thermal infrared (TIR) multispectral scanner with seven spectral bands in the thermal infrared (TIR) between 7 and 12 μm and one band in the mid-infrared between 3 and 5 μm designed to measure hot targets. The TIR bands have a NEΔT of <0.2 K at 300K and all bands have a spatial scale of 60 m. The two primary Level-2 products that will be generated by HyspIRI TIR data are land surface temperature and emissivity. A critical aspect of minimizing uncertainties in these products and in generating global Level-3 products is an accurate and reliable cloud mask algorithm. This document describes the methodology behind developing the HyspIRI Cloud Mask Algorithm (HyCMA), and challenges associated with cloud detection. The HyCMA will derive its heritage from previously well established cloud mask algorithms such as the Landsat ACCAA, MODIS MOD35 and AVHRR.
This Algorithm Theoretical Basis (ATB) document describes the algorithms used to retrieve the cloud classification parameters of the MISR Level 2 Top-of-Atmosphere (TOA)/Cloud Product.
Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases
One of the main difficulties in detecting cirrus clouds and determining their correct altitude using satellite measurements is their nonblackness. In the present algorithm (Rossow et al., 1985) used by the International Satellite Cloud Climatology Project (ISCCP), the cirrus cloud emissivity is estimated from the derived cloud reflectance using a theoretical model relating visible (VIS, 0.65 micron) optical depth to infrared (IR, 10.5 micron) emissivity. At this time, it is unknown how accurate this approach is or how the derived cloud altitude relates to the physical properties of the cloud. The First ISCCP Regional Experiment (FIRE) presents opportunities for determining how the observed radiances depend on the cloud properties. During the FIRE Cirrus Intensive Field Observations (IFO, see Starr, 1987), time series of cloud thickness, height, and relative optical densities were measured from several surface-based lidars. Cloud microphysics and radiances at various wavelengths were also measured simultaneously over these sites from aircraft at specific times during the IFO (October 19 to November 2, 1986). Satellite-observed radiances taken simultaneously can be matched with these data to determine their relationships to the cirrus characteristics. The first step is taken toward relating all of these variables to the satellite observations. Lidar-derived cloud heights are used to determine cloud temperatures which are used to estimate cloud emissivities from the satellite IR radiances. These results are then correlated to the observed VIS reflectances for various solar zenith angles.
Thin cirrus clouds (optical depth (OD) < 03) are often undetected by standard cloud masking in satellite aerosol retrieval algorithms. However, the Mu]tiangle Imaging Spectroradiometer (MISR) aerosol retrieval has the potential to discriminate between the scattering phase functions of cirrus and aerosols, thus separating these components. Theoretical tests show that MISR is sensitive to cirrus OD within Max{0.05 1 20%l, similar to MISR's sensitivity to aerosol OD, and MISR can distinguish between small and large crystals, even at low latitudes, where the range of scattering angles observed by MISR is smallest. Including just two cirrus components in the aerosol retrieval algorithm would capture typical MISR sensitivity to the natural range of cinus properties; in situations where cirrus is present but the retrieval comparison space lacks these components, the retrieval tends to underestimate OD. Generally, MISR can also distinguish between cirrus and common aerosol types when the proper cirrus and aerosol optical models are included in the retrieval comparison space and total column OD is >-0.2. However, in some cases, especially at low latitudes, cirrus can be mistaken for some combinations of dust and large nonabsorbing spherical aerosols, raising a caution about retrievals in dusty marine regions when cirrus is present. Comparisons of MISR with lidar and Aerosol Robotic Network show good agreement in a majority of the cases, but situations where cirrus clouds have optical depths >0.15 and are horizontally inhomogeneous on spatial scales shorter than 50 km pose difficulties for cirrus retrieval using the MISR standard aerosol algorithm..