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

Abstract

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, producing sri estimates feeding an operational hydrological model for forecasting flood alerts. This paper presents the validation of OPEMW against simultaneous ground-based observations obtained by a network of 20 weather radars and a network of more than 3000 rain gauges distributed over the Italian peninsula and main islands. The validation effort uses a data set spanning a one-year period (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, and it 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 for larger mean absolute difference over the Alps and northern Apennines during winter, attributable to residual effect of snow cover. 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 to underestimate sri above those values. Depending upon the ground reference (either rain gauges or weather radars), the mean difference is 0.8–2.8 mm h−1, with a standard deviation within 2.6–3.1 mm h−1 and correlation coefficient within 0.8–0.9. The monthly mean difference was shown to remain within ±1 mm h−1 with respect to rain gauges and within −2 mm h−1 with respect to weather radars, with 2–4 mm h−1 standard deviation.