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- W2096670812 abstract "Determining the three-dimensional (3D) structure of clouds over large areas from satellites is a daunting task given the limitations of “seeing” through clouds and measuring their properties with satellite imager visible, infrared, and microwave data. One of the greatest problems in multi-layered cloud detection is detecting low-level clouds underneath thick high clouds. Typically, satellite imager-based multi-layered cloud detection methods require that the upper-level cloud is optically thin with an infrared (IR) emissivity of 0.85 or less. Thick ice clouds prohibit detection of low-level clouds when passive visible (VIS) and IR imager data are used (Pavlonis and Heidinger 2004). The addition of a microwave radiometer to that instrument complement can be used to detect low-level water clouds under thick ice clouds (Huang et al. 2005) but is very unreliable over land surfaces. Thus, when the thick ice clouds are present over land, the detection of low-level clouds is indeterminate using passive satellite data. Ceilometer data could help determine when those clouds are present but they are taken at a limited number of locations and require uncertain interpolation. High-temporal resolution numerical weather prediction analysis data provide a more continuous 3D picture of potential cloudiness that might be useful for filling out the low levels when the VIS-IR methods are unable to discriminate between single and multi-layered clouds. In this paper, a VIS-IR multi-layer cloud detection technique is applied to Geostationary Operational Environmental Satellite (GOES-8) over the Southern Great Plains (SGP) and compared with Atmospheric Radiation Measurement (ARM) SGP Active Remote Sensing of Cloud Layers (ARSCL) data (Clothiaux et al. 2000) and ceilometer data from the Automated Surface Observing System (ASOS). Numerical weather prediction data are used to estimate cloud-base height underneath high-level clouds and validated using the ASOS data. This study is the first step in a process that eventually will provide a more accurate set of vertically defined cloud properties over a large domain covering the SGP for use in single-column modeling and broadband heating rate profile studies." @default.
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- W2096670812 date "2005-01-01" @default.
- W2096670812 modified "2023-09-26" @default.
- W2096670812 title "Developing a Three-Dimensional Cloud Product over the ARM Sites Using Geostationary Meteorological Satellite Data" @default.
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