Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part I: Improved Method and UncertaintiesSource: Journal of Applied Meteorology and Climatology:;2006:;volume( 045 ):;issue: 005::page 702Author:Olson, William S.
,
Kummerow, Christian D.
,
Yang, Song
,
Petty, Grant W.
,
Tao, Wei-Kuo
,
Bell, Thomas L.
,
Braun, Scott A.
,
Wang, Yansen
,
Lang, Stephen E.
,
Johnson, Daniel E.
,
Chiu, Christine
DOI: 10.1175/JAM2369.1Publisher: American Meteorological Society
Abstract: A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h?1 to 20% at 14 mm h?1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%?80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day?1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%?35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%?15% at 5 mm day?1, with proportionate reductions in latent heating sampling errors.
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contributor author | Olson, William S. | |
contributor author | Kummerow, Christian D. | |
contributor author | Yang, Song | |
contributor author | Petty, Grant W. | |
contributor author | Tao, Wei-Kuo | |
contributor author | Bell, Thomas L. | |
contributor author | Braun, Scott A. | |
contributor author | Wang, Yansen | |
contributor author | Lang, Stephen E. | |
contributor author | Johnson, Daniel E. | |
contributor author | Chiu, Christine | |
date accessioned | 2017-06-09T16:47:53Z | |
date available | 2017-06-09T16:47:53Z | |
date copyright | 2006/05/01 | |
date issued | 2006 | |
identifier issn | 1558-8424 | |
identifier other | ams-74302.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4216513 | |
description abstract | A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h?1 to 20% at 14 mm h?1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%?80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day?1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%?35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%?15% at 5 mm day?1, with proportionate reductions in latent heating sampling errors. | |
publisher | American Meteorological Society | |
title | Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part I: Improved Method and Uncertainties | |
type | Journal Paper | |
journal volume | 45 | |
journal issue | 5 | |
journal title | Journal of Applied Meteorology and Climatology | |
identifier doi | 10.1175/JAM2369.1 | |
journal fristpage | 702 | |
journal lastpage | 720 | |
tree | Journal of Applied Meteorology and Climatology:;2006:;volume( 045 ):;issue: 005 | |
contenttype | Fulltext |