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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 6, issue 11
Atmos. Meas. Tech., 6, 3181–3196, 2013
https://doi.org/10.5194/amt-6-3181-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 6, 3181–3196, 2013
https://doi.org/10.5194/amt-6-3181-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 22 Nov 2013

Research article | 22 Nov 2013

Validation of satellite OPEMW precipitation product with ground-based weather radar and rain gauge networks

D. Cimini1,2, F. Romano1, E. Ricciardelli1, F. Di Paola1, M. Viggiano1, F. S. Marzano2,3, V. Colaiuda2, E. Picciotti2,4, G. Vulpiani5, and V. Cuomo1,6 D. Cimini et al.
  • 1IMAA-CNR, C.da S.Loja, Tito Scalo, 85050 Potenza, Italy
  • 2CETEMPS, University of L'Aquila, Via Vetoio 1, 67100 L'Aquila, Italy
  • 3DIET, University of Rome, La Sapienza, Via Eudossiana 18, 00184 Rome, Italy
  • 4HIMET s.r.l., Strada Statale 17 OVEST, 36, 67100 L'Aquila, Italy
  • 5Department of Civil Protection, Via Vitorchiano 2, 00189 Rome, Italy
  • 6University of Basilicata, Via Nazario Sauro 85, 85100 Potenza, Italy

Abstract. The Precipitation Estimation at Microwave Frequencies (PEMW) algorithm was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) for inferring surface rain intensity (sri) from satellite passive microwave observations in the range from 89 to 190 GHz. The operational version of PEMW (OPEMW) has been running continuously at IMAA-CNR for two years. The OPEMW sri estimates, together with other precipitation products, are used as input to an operational hydrological model for flood alert forecast. This paper presents the validation of OPEMW against simultaneous ground-based observations from a network of 20 weather radar systems and a network of more than 3000 rain gauges distributed over the Italian Peninsula and main islands. The validation effort uses a data set covering one year (July 2011–June 2012). The effort evaluates dichotomous and continuous scores for the assessment of rain detection and quantitative estimate, respectively, investigating both spatial and temporal features. The analysis demonstrates 98% accuracy in correctly identifying rainy and non-rainy areas; it also quantifies the increased ability (with respect to random chance) to detect rainy and non-rainy areas (0.42–0.45 Heidke skill score) or rainy areas only (0.27–0.29 equitable threat score). Performances are better than average during summer, fall, and spring, while worse than average in the winter season. The spatial–temporal analysis does not show seasonal dependence except over the Alps and northern Apennines during winter. A binned analysis in the 0–15 mm h−1 range suggests that OPEMW tends to slightly overestimate sri values below 6–7 mm h−1 and underestimate sri above those values. With respect to rain gauges (weather radars), the correlation coefficient is larger than 0.8 (0.9). The monthly mean difference and standard deviation remain within ±1 and 2 mm h−1 with respect to rain gauges (respectively −2–0 and 4 mm h−1 with respect to weather radars).

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