Verification Study of CDRD and PNPR Passive Microwave Precipitation Retrieval Algorithms Using Spaceborne Precipitation Radars
| Autor: | Casella, D., Panegrossi, G., Marra, A. C., Sanò, P. , Petracca, M., Dietrich, S. |
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| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | Earth Observation for Water Cycle Science 2015, ESA ESRIN Frascati, 20-23 ottobre 2015 info:cnr-pdr/source/autori:Casella, D.; Panegrossi, G.; Marra, A. C.; Sanò, P., Petracca, M.; Dietrich, S.,/congresso_nome:Earth Observation for Water Cycle Science 2015/congresso_luogo:ESA ESRIN Frascati/congresso_data:20-23 ottobre 2015/anno:2015/pagina_da:/pagina_a:/intervallo_pagine |
| Popis: | The ongoing NASA/JAXA Global Precipitation Measuring mission (GPM) requires the full exploitation of the complete constellation of passive microwave (PMW) radiometers orbiting around the globe for global precipitation monitoring. In this context the coherence of the estimates of precipitation using different passive microwave radiometers is a crucial need. We have developed two different passive microwave precipitation retrieval algorithms: one is the Cloud Dynamics Radiation Database algorithm (CDRD), a physically ¬based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross¬- track scanning radiometers (i.e., NOAA and MetOp¬A/B AMSU-¬A/MHS, and NPP Suomi ATMS). The algorithms, originally created for application over Europe and the Mediterranean basin, and used operationally within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF, http://hsaf.meteoam.it), have been recently modified and extended to Africa and Southern Atlantic for application to the MSG full disk area. The two algorithms are based on the same physical foundation, i.e., the same cloud-radiation model simulations as a priori information in the Bayesian solver and as training dataset in the neural network approach, and they also use similar procedures for identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. In addition, similar procedures for the screening of not ¬precipitating pixels are used. A novel algorithm for the detection of precipitation in tropical/sub-tropical areas has been developed, applicable to all available PMW radiometers in the GPM constellation of satellites (including NPP Suomi ATMS, and GMI). A verification study over the African region on detection capabilities and retrievals from the CDRD and PNPR algorithms has been carried out using large datasets of coincidences with spaceborne precipitation radars (TRMM-PR for 2011-2012-2013, and GPM DPR for 2014). The results of this study aims at assessing the consistency and accuracy of precipitation retrievals from different sensors in different climatic regions and precipitation regimes. Results show a very good level of coherence of the precipitation estimates and patterns between the two algorithms exploiting different radiometers both for instantaneous precipitation and for daily/monthly means. Results also show an overall high correlation with respect to the spaceborne radars, with an overestimation over all surfaces. The novel precipitation detection algorithm shows a small rate of false alarms (also over arid/desert regions), and a superior detection capability in comparison with other widely used screening algorithms. Recent developments aimed at the full exploitation of the GPM constellation of satellites for optimal precipitation/drought monitoring will be also presented. |
| Databáze: | OpenAIRE |
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