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After 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough quality-controlled data to allow the first validation of their precipitation estimates over Spain. High-quality gauge data from the meteorological network of the Spanish Meteorological Agency (AEMET) are used here to validate Integrated Multisatellite Retrievals for GPM (IMERG) level 3 estimates of surface precipitation. While aggregated values compare notably well, some differences are found in specific locations. The research investigates the sources of these discrepancies, which are found to be primarily related to the underestimation of orographic precipitation in the IMERG satellite products, as well as to the number of available gauges in the GPCC gauges used for calibrating IMERG. It is shown that IMERG provides suboptimal performance in poorly instrumented areas but that the estimate improves greatly when at least one rain gauge is available for the calibration process. A main, generally applicable conclusion from this research is that the IMERG satellite-derived estimates of precipitation are more useful (r2 > 0.80) for hydrology than interpolated fields of rain gauge measurements when at least one gauge is available for calibrating the satellite product. If no rain gauges were used, the results are still useful but with decreased mean performance (r2 ≈ 0.65). Such figures, however, are greatly improved if no coastal areas are included in the comparison. Removing them is a minor issue in terms of hydrologic impacts, as most rivers in Spain have their sources far from the coast. [ABSTRACT FROM AUTHOR]

Deep convection is a threat to many human activities, with a great impact on aviation safety. On 7 July 2017, a widespread torrential precipitation event (associated with a cut-off low at mid-levels) was registered in the vicinity of Madrid, causing serious flight disruptions. During this type of episode, accurate short-term forecasts are key to minimizing risks to aviation. The aim of this research is to improve early warning systems by obtaining the best WRF model setup. In this paper, the aforementioned event was simulated. Various model configurations were produced using four different physics parameterizations, 3-km and 1-km domain resolutions, and 0.25° and 1° initial condition resolutions. Simulations were validated using data from 17 rain gauge stations. Two validation indices are proposed, accounting for the temporal behaviour of the model. Results show significant differences between microphysics parameterizations. Validation of domain resolution shows that improvement from 3 to 1 km is negligible. Interestingly, the 0.25° resolution for initial conditions produced poor results compared with 1°. This may be linked to a timing error, because precipitation was simulated further east than observed. The use of ensembles generated by combining different WRF model configurations produced reliable precipitation estimates. [ABSTRACT FROM AUTHOR]

ABSTRACT The study of weather extremes is critical because of their great impact on the environment, economy and society. The identification of areas at greater risk of extreme conditions, and of meteorological situations that give rise to such conditions, enhances the understanding of climate risks and helps establish measures to reduce adverse impacts. In the current paper, precipitation extreme events ( PEEs) in Spain between 1960 and 2011 were analysed. Thresholds for determining event severity were defined using 99th percentiles. First, regions of extreme weather risk were identified and then trends of extreme precipitation index were analysed using the Mann-Kendall test. To better understand atmospheric processes associated with extreme weather events in each season, synoptic-scale fields of events exceeding the 99th percentile were analysed. By applying non-hierarchical K-means clustering, we defined six large-scale atmospheric patterns that largely explain the spatiotemporal distribution of PEEs in the study area. PEEs on the western Iberian Peninsula mainly occurred with zonal flow, with a long Atlantic fetch generating moisture advection towards that area. On the eastern peninsula, the most important pattern for PEE production is characterized by a cutoff low at mid-levels together with easterly moisture flow. The relationship of PEEs with teleconnection patterns, such as the North Atlantic Oscillation ( NAO), Mediterranean Oscillation ( MO) and Western Mediterranean Oscillation ( WeMO), showed that nearly all the events over the southwestern peninsula were during the NAO- and MO-negative phases. However, on the Mediterranean coast, the negative WeMO phase had greater influence. By contrast, the northwestern peninsula and eastern Cantabrian coast showed weaker relationships between these indices and PEEs. The results show a clear ability to identify regions exposed to extreme precipitation hazards. The correct identification of synoptic patterns associated with each type of weather extreme will assist the prediction of such events, thereby providing useful information for decision making and warning systems. [ABSTRACT FROM AUTHOR]

Precipitation in southwestern France was analyzed. Monthly rainfall data from the Global Precipitation Climatology Centre (GPCC) were used to obtain three clusters of average precipitation from May through September for the period 1901–2010. We attempt to understand the role of hailfalls in total precipitation using three different variables related to hail, the number of hail days, hail frequency, and intensity. We examine trends via the Mann–Kendall test and periodicities by wavelet analysis. The results show cluster classification of precipitation to be somewhat consistent with hailpad networks in the study area. In the Pyrenees, there was a non-significant negative trend of precipitation and a substantial increase of hail days and intensity of hail, which were close to the limit of significance. Finally, a wavelet coherence analysis shows a strong influence of the North Atlantic Oscillation (NAO) in the Atlantic region. [ABSTRACT FROM AUTHOR]

Abstract: In order to identify hail into thunderstorms identified with radar data, different kinds of techniques are use based. This paper will evaluate some of these methodologies for the case of the Ebro valley (NE Spain), in order to obtain the best method to identify hail at surface. To achieve this end, an analysis of the 2004 and 2005 hail seasons has been undertaken using C-band radar, MM5 meteorological model outputs and ground observations provided by two hailpad networks. These data were integrated, identifying, characterizing and tracking the convective cells, and obtaining for each one different hail probability equations by means of various radar techniques. Kinetic energy flux was found to be the best parameter for distinguishing between hail and no-hail precipitation, although there was found to exist no significant difference between the various methods used. Moreover, the high correlations between radar parameters obtained by means of cell analyses led us to reduce the initial number of variables in new radar parameters. These new variables are defined and provide new improved models of the intensity of the storm. [Copyright &y& Elsevier]

This paper evaluates Integrated Multi-Satellite Retrievals from GPM (IMERG-F) over Europe for the period 2014–2018 in order to evaluate application of the retrievals to hydrology. IMERG-F is compared with a large pan-European precipitation dataset built on rain gauge stations, i.e., the ENSEMBLES OBServation (E-OBS) gridded dataset. Although there is overall agreement in the spatial distribution of mean precipitation (R2 = 0.8), important discrepancies are revealed in mountainous regions, specifically the Alps, Pyrenees, west coast of the British Isles, Scandinavia, the Iberian and Italian peninsulas, and the Adriatic coastline. The results show that the strongest contributors to poor performance are pixels where IMERG-F has no gauges available for adjustment. If rain gauges are available, IMERG-F yields results similar to those of the surface observations, although the performance varies by region. However, even accounting for gauge adjustment, IMERG-F systematically underestimates precipitation in the Alps and Scandinavian mountains. Conversely, IMERG-F overestimates precipitation in the British Isles, Italian Peninsula, Adriatic coastline, and eastern European plains. Additionally, the research shows that gauge adjustment worsens the spatial gradient of precipitation because of the coarse resolution of Global Precipitation Climatology Centre data. [ABSTRACT FROM AUTHOR]