Graduate Thesis Or Dissertation
 

Modeled and observed longwave radiances at the top of the atmosphere

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/hq37vr34x

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  • One method of estimating the longwave radiative heating of the atmosphere is to combine satellite observations of emitted radiances with those computed from synoptic temperature and humidity profiles. Modeled and observed radiances are brought into agreement by altering cloud properties or even by adjusting the temperature and water vapor profiles. Here this strategy is examined in an exploratory study using global meteorological data sets and a radiative transfer model typical of those found in general circulation models. Calculated radiances are compared to those observed by the Earth Radiation Budget Satellite (ERBS). Input for the model is obtained from the National Meteorological Center (NMC) in the form of vertical profiles of temperature and relative humidity. The comparisons are limited to clear sky as deduced by ERBE algorithms, and additional filtering which requires homogeneous surface type for a 3 x 3 array of ERBS scanner fields of view. Observations are obtained from 60° N to 60° S that lie within 30 minutes of the NMC analysis time. Following the work of Ramanathan and Downey (1986), comparisons are separated into climatologically distinct groups as well as by satellite viewing angle. This separation is an attempt to distinguish between biases in the radiation model and those in the NMC data set. Results are presented for the months of July 1985, and January 1986. A comparison of the present radiation model's output with that obtained from a Geophysical Fluid Dynamics Laboratory (GFDL) model shows a bias of nearly 3% in the present model for a standard mid-latitude summer profile. Global results show a negative bias in the modeled values for nearly all scenes, except for nighttime desert. The nighttime desert bias may be a result of a skin-air temperature difference not resolved by the NMC analyses. The overall negative bias may be a result of an overestimation of water vapor for regions with low relative humidity.
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