Global and Regional Cloud Properties Derived from MODIS Data
Bryan A. Baum, Shaima L. Nasiri, Peiqi Yang
Abstract
Bryan A. Baum, Shaima L. Nasiri, Peiqi Yang
Abstract
Current efforts to derive a global cloud climatology from satellite data generally suffer in situations involving multi-layered clouds. In fact, cloud properties are inferred for each imager pixel assuming only single cloud layer is present. Currently available satellite cloud climatologies provide a horizontal distribution of clouds, but need improvement in the description of the vertical distribution of clouds. The single cloud layer assumption is unfortunate because Atmospheric Radiation Measurement (ARM) observations show that clouds often occur in multiple layers simultaneously in a vertical column, i.e., cloud layers often overlap. Our goal is to work towards improving both satellite-derived and surfacederived cloud products under these complex conditions.
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Current efforts to derive a global cloud climatology from satellite data generally suffer in situations involving multi-layered clouds. In fact, cloud properties are inferred for each imager pixel assuming only single cloud layer is present. Currently available satellite cloud climatologies provide a horizontal distribution of clouds, but need improvement in the description of the vertical distribution of clouds. The single cloud layer assumption is unfortunate because Atmospheric Radiation Measurement (ARM) observations show that clouds often occur in multiple layers simultaneously in a vertical column, i.e., cloud layers often overlap. Our goal is to work towards improving both satellite-derived and surfacederived cloud products under these complex conditions.
Key concepts: Cloud computing, Satellite, Cloud height, Cloud top, Cloud fraction, Meteorology, Cloud cover, Environmental science