http://www.cnr.it/ontology/cnr/individuo/prodotto/ID260216

Transitioning From CRD to CDRD in Bayesian Retrieval of Rainfall From Satellite Passive Microwave Measurements: Part 2. Overcoming Database Profile Selection Ambiguity by Consideration of Meteorological Control on Microphysics (Articolo in rivista)

Type

Articolo in rivista (Classe)
Prodotto della ricerca (Classe)

Label

Transitioning From CRD to CDRD in Bayesian Retrieval of Rainfall From Satellite Passive Microwave Measurements: Part 2. Overcoming Database Profile Selection Ambiguity by Consideration of Meteorological Control on Microphysics (Articolo in rivista) (literal)

Anno

2013-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

10.1109/TGRS.2013.2258161 (literal)

Alternative label

Daniele Casella, Giulia Panegrossi, Paolo Sanò, Stefano Dietrich, Alberto Mugnai, Eric A. Smith, Gregory J. Tripoli, Marco Formenton, Francesco Di Paola, Wing-Yee Hester Leung, and Amita V. Mehta (2013)
Transitioning From CRD to CDRD in Bayesian Retrieval of Rainfall From Satellite Passive Microwave Measurements: Part 2. Overcoming Database Profile Selection Ambiguity by Consideration of Meteorological Control on Microphysics
in IEEE transactions on geoscience and remote sensing; IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE,, PISCATAWAY, NJ 08855-4141 (Stati Uniti d'America)
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

Daniele Casella, Giulia Panegrossi, Paolo Sanò, Stefano Dietrich, Alberto Mugnai, Eric A. Smith, Gregory J. Tripoli, Marco Formenton, Francesco Di Paola, Wing-Yee Hester Leung, and Amita V. Mehta (literal)

Pagina inizio

4650 (literal)

Pagina fine

4671 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6527927 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

51 (literal)

Rivista

IEEE transactions on geoscience and remote sensing (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

22 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo

9 (literal)

Note

ISI Web of Science (WOS) (literal)
Scopu (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

D. Casella, G. Panegrossi, P. Sanò, S. Dietrich, and A. Mugnai are with the Institute of Atmospheric Sciences and Climate, Italian National Research Council, Rome 00133, Italy (e-mail: daniele.casella@artov.isac.cnr. it; g.panegrossi@isac.cnr.it; paolo.sano@artov.isac.cnr.it; stefano.dietrich@ artov.isac.cnr.it; alberto.mugnai@artov.isac.cnr.it). E.-A. Smith is with the Center for Research on the Changing Earth System, Tallahassee, FL 32312 USA (e-mail: easmith@crces.org). G. J. Tripoli is with the Department of Atmospheric and Oceanic Sciences, University of Wisconsin, Madison, WI 53706 USA (e-mail: tripoli@ aos.wisc.edu). M. Formenton was with ISAC-CNR, Rome, Italy. He is now with the Hawaii Institute of Geophysics and Planetology, University of Hawaii, Honolulu, HI 96822 USA (e-mail: marco.formenton@artov.isac.cnr.it). F. Di Paola is with the Institute of Methodologies for Environmental Analysis, Italian National Research Council, Tito Scalo 85050, Italy (e-mail: francesco.dipaola@imaa.cnr.it). W.-Y. H. Leung is with the Department of Meteorology, Stockholm University, Stockholm 106 91, Sweden (e-mail: wing@misu.su.se). A. V. Mehta is with Joint Center for Earth Systems Technology, University of Maryland, Baltimore, MD 21228 USA (e-mail: amita@radar.gsfc. nasa.gov). (literal)

Titolo

Transitioning From CRD to CDRD in Bayesian Retrieval of Rainfall From Satellite Passive Microwave Measurements: Part 2. Overcoming Database Profile Selection Ambiguity by Consideration of Meteorological Control on Microphysics (literal)

Abstract

A new cloud dynamics and radiation database (CDRD) precipitation retrieval algorithm for satellite passive microwave (PMW) radiometer measurements has been developed. It represents a modification to and an improvement upon the conventional cloud radiation database (CRD) algorithms, which have always been prone to ambiguity. This part 2 paper of a series describes the methodology of the algorithm and the modeling verification analysis involved in creating a synthetic CDRD database for the Europe/Mediterranean basin region. This is followed by a proof-of-concept analysis, which demonstrates that the underlying CDRD theory based on use of meteorological parameters for reducing retrieval ambiguity is valid. This paper uses a regional/mesoscale model, applied in cloud resolving model (CRM) mode, to produce a large set of numerical simulations of precipitating storms and extended precipitating systems. The simulations are used for selection of millions of meteorological/microphysical vertical profiles within which surface rainfall is identified. For each of these profiles, top-of-atmosphere brightness temperature (TB) vectors are calculated (the vector dimension associated with the number of relevant cm-mm wavelengths and polarizations), based on an elaborate radiative-transfer equation (RTE) model system (RMS) coupled to the CRM. This entire body of simulation information is organized into the CDRD database, then used as a priori knowledge to guide a physical Bayesian retrieval algorithm in obtaining rainfall and associated precipitation parameters from the PMW satellite observations. We first prove the physical validity of our CRM-RMS simulations, by showing that the simulated TBs are in close agreement with observations. Agreement is demonstrated using dual-channel-frequency TB manifold sections, which quantify the degree of overlap between the simulated and observed TBs extracted from the full manifolds. Nevertheless, the salient result of this paper is a pro- f that the underlying CDRD theory is valid, found by combining subdivisions of the invoked meteorological parameter ranges of values and showing that such meteorological partitioning associates itself with distinct microphysical profiles. It is then shown that these profiles give rise to similar TB vectors, proving the existence of ambiguity in a CRD-type algorithm. Finally, we show that the CDRD methodology provides significant improvements in reducing retrieval ambiguity and retrieval error, especially for land surface backgrounds where contrasts are typically small between the rainfall TB signatures and surface emission signatures. (literal)

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