Comparison of Model-Produced and Observed Microwave Radiances and Estimation of Background Error Covariances for Hydrometeor Variables within Hurricanes

Clark Amerault The Florida State University, Tallahassee, Florida

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Xiaolei Zou The Florida State University, Tallahassee, Florida

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Abstract

A radiative transfer model was updated to better simulate Special Sensor Microwave Imager (SSM/I)–observed brightness temperatures in areas of high ice concentration. The difference between the lowest observed and model-produced brightness temperatures at 85 GHz has been reduced from over 100 K to roughly 20 K. Probability distribution functions of model-produced and SSM/I-observed brightness temperatures show that the model overestimates the areas of precipitation, but overall matches the SSM/I observations quite well.

Estimates of vertical background error covariance matrices and their inverses were calculated for all hydrometeor variables (both liquid and frozen). For cloud and rainwater, the largest values in the matrices are located in the lower levels of the atmosphere, while the largest values in the cloud ice, snow, and graupel matrices are in the upper levels of the atmosphere. The inverse background matrices can be used as weightings for hydrometeor variables in assimilation experiments involving rain-affected observations.

Corresponding author address: Clark Amerault, Naval Research Laboratory, Marine Meteorology Division, 7 Grace Hopper Avenue, Stop 2, Monterey, CA 93943-5502. Email: amerault@nrlmry.navy.mil

Abstract

A radiative transfer model was updated to better simulate Special Sensor Microwave Imager (SSM/I)–observed brightness temperatures in areas of high ice concentration. The difference between the lowest observed and model-produced brightness temperatures at 85 GHz has been reduced from over 100 K to roughly 20 K. Probability distribution functions of model-produced and SSM/I-observed brightness temperatures show that the model overestimates the areas of precipitation, but overall matches the SSM/I observations quite well.

Estimates of vertical background error covariance matrices and their inverses were calculated for all hydrometeor variables (both liquid and frozen). For cloud and rainwater, the largest values in the matrices are located in the lower levels of the atmosphere, while the largest values in the cloud ice, snow, and graupel matrices are in the upper levels of the atmosphere. The inverse background matrices can be used as weightings for hydrometeor variables in assimilation experiments involving rain-affected observations.

Corresponding author address: Clark Amerault, Naval Research Laboratory, Marine Meteorology Division, 7 Grace Hopper Avenue, Stop 2, Monterey, CA 93943-5502. Email: amerault@nrlmry.navy.mil

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