Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloAssessment of Ground-Reference Data and Validation of the H-SAF Precipitation Products in Brazil
Anno di pubblicazione2018
FormatoElettronico
Autore/iLia Martins Costa do Amaral , Stefano Barbieri, Daniel Vila, Silvia Puca, Gianfranco Vulpiani, Giulia Panegrossi, Thiago Biscaro, Paolo Sanò, Marco Petracca, Anna Cinzia Marra, Marielle Gosset and Stefano Dietrich
Affiliazioni autoriLia Martins Costa do Amaral 1,* , Stefano Barbieri 2, Daniel Vila 1, Silvia Puca 3, Gianfranco Vulpiani 3, Giulia Panegrossi 4, Thiago Biscaro 1, Paolo Sanò 4, Marco Petracca 3, Anna Cinzia Marra 4, Marielle Gosset 5 and Stefano Dietrich 4 1 Weather Forecast Center and Climate Studies, National Institute for Space Research (CPTEC/INPE), São José dos Campos, SP 12227-010, Brazil 2 CETEMPS, University of L'Aquila, 67100 L'Aquila, Italy 3 Italian Civil Protection Department, 00189 Rome, Italy 4 Institute of Atmospheric Sciences and Climate (ISAC) National Research Council of Italy (CNR), 00133 Rome, Italy 5 Institute of Research for Development (IRD), 13572 Marseille, France
Autori CNR e affiliazioni
  • ANNA CINZIA MARRA
  • STEFANO DIETRICH
  • GIULIA PANEGROSSI
  • PAOLO SANO'
Lingua/e
  • inglese
AbstractThe uncertainties associated with rainfall estimates comprise various measurement scales: from rain gauges and ground-based radars to the satellite rainfall retrievals. The quality of satellite rainfall products has improved significantly in recent decades; however, such algorithms require validation studies using observational rainfall data. For this reason, this study aims to apply the H-SAF consolidated radar data processing to the X-band radar used in the CHUVA campaigns and apply the well established H-SAF validation procedure to these data and verify the quality of EUMETSAT H-SAF operational passive microwave precipitation products in two regions of Brazil (Vale do Paraíba and Manaus). These products are based on two rainfall retrieval algorithms: the physically based Bayesian Cloud Dynamics and Radiation Database (CDRD algorithm) for SSMI/S sensors and the Passive microwave Neural network Precipitation Retrieval algorithm (PNPR) for cross-track scanning radiometers (AMSU-A/AMSU-B/MHS sensors) and for the ATMS sensor. These algorithms, optimized for Europe, Africa and the Southern Atlantic region, provide estimates for the MSG full disk area. Firstly, the radar data was treated with an overall quality index which includes corrections for different error sources like ground clutter, range distance, rain-induced attenuation, among others. Different polarimetric and non-polarimetric QPE algorithms have been tested and the Vulpiani algorithm (hereafter, Rq2Vu15 ) presents the best precipitation retrievals when compared with independent rain gauges. Regarding the results from satellite-based algorithms, generally, all rainfall retrievals tend to detect a larger precipitation area than the ground-based radar and overestimate intense rain rates for the Manaus region. Such behavior is related to the fact that the environmental and meteorological conditions of the Amazon region are not well represented in the algorithms. Differently, for the Vale do Paraíba region, the precipitation patterns were well detected and the estimates are in accordance with the reference as indicated by the low mean bias values.
Lingua abstractinglese
Altro abstract-
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Pagine da1
Pagine a24
Pagine totali24
RivistaRemote sensing
Attiva dal 1988
Editore: University of Wollongong. - Wollongong, N.S.W.
Paese di pubblicazione: Australia
Lingua: inglese
ISSN: 1032-9714
Titolo chiave: Remote sensing
Titolo proprio: Remote sensing.
Titolo abbreviato: Remote sens.
Numero volume della rivista10
Fascicolo della rivista11
DOI10.3390/rs10111743
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)-
Parole chiaverain gauges, radar, quality index, satellite rainfall retrieval, validation
Link (URL, URI)https://www.mdpi.com/2072-4292/10/11/1743
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • ISAC — Istituto di scienze dell'atmosfera e del clima
Moduli/Attività/Sottoprogetti CNR
  • DTA.AD001.193.001 : H-SAF CDOP3
Progetti Europei-
Allegati
paper (documento privato )
Descrizione: pdf del paper
Tipo documento: application/pdf