Abstract

Accurate environmental satellite observations and calculations of top‐of‐atmosphere infrared (IR) spectral radiances are required for the accurate retrieval of environmental data records (EDRs), including atmospheric vertical temperature and moisture profiles. For this reason it is important that systematic differences between observations and calculations under well‐characterized conditions be minimal, and because most sensors must scan the earth surface to facilitate global coverage, this should include unbiased agreement over the range of zenith angles encountered. This paper investigates the “clear‐sky observations” commonly used in such analyses, which include “cloud‐masked” data (as is typical from imagers), as well as “cloud‐cleared radiances” (as is typical from hyper/ultraspectral sounders). Here we derive simple physical conceptual models to examine quantitatively the longwave IR brightness temperature sensitivity arising from the increasing probability of cloudy fields‐of‐view with zenith angle, or alternatively from increased slant‐path through an aerosol layer. To model the angular effect of clouds, we apply previously derived probability of clear line‐of‐sight (PCLoS) models for single‐layer broken opaque clouds. We then generalize this approach to account for the impact of high, semitransparent (non‐opaque) cold clouds, by deriving analytical expressions for the mean slant‐paths through each of the idealized shapes under consideration. Our sensitivity analyses suggest that contamination by residual clouds and/or aerosols within clear‐sky observations can have a measurable concave‐up impact (i.e., an increasing positive bias symmetric over the scanning range) on the angular agreement of hypothetical “observations” with “calculations.” The magnitudes are typically on the order of couple tenths of a Kelvin or more depending on the residual absolute cloud fraction and optical depth (i.e., the degree of cloud contamination), the residual aerosol optical depth (i.e., the degree of aerosol contamination), the temperature difference between the surface and the residual cloud/aerosol layers, and the shape and vertical aspect ratio of the clouds.

Full Text
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