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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]

The absence of systematic estimates of vertical transport of water by convective storms is one of the main causes of uncertainties in weather forecasting in the tropics, in severe weather forecasting, and in the climate-scale analysis and prediction of global circulation. The difficulty of providing such estimates lies in that the only instruments capable of providing such estimates at present, radiometers onboard satellites, operate at short wavelengths, and that makes difficult the retrievals. This paper describes a method capable of providing robust estimates of the maximum height of precipitation and the 3-D structure of condensed water in convective systems using a constellation of radiometers. Using hurricane Winston and the Global Precipitation Measurement (GPM) mission Core Observatory satellite dual precipitation radar as a reference, it is shown that the method is suitable to improve the parameterization of convection in numerical models. [ABSTRACT FROM AUTHOR]

Precipitation has often been used to gauge the performances of numerical weather and climate models, sometimes together with other variables such as temperature, humidity, geopotential, and clouds. Precipitation, however, is singular in that it can present a high spatial variability and probably the sharpest gradients among all meteorological fields. Moreover, its quantitative measurement is plagued with difficulties, and there are even notable differences among different reference datasets. Several additional issues sometimes lead to questions about its usefulness in model validation. This essay discusses the use of precipitation for model verification and validation and the crucial role of highly precise and reliable satellite estimates, such as those from NASA's Global Precipitation Mission Core Observatory. [ABSTRACT FROM AUTHOR]

Advances to space-based observing systems and data processing techniques have made precipitation datasets quickly and easily available via various data portals and widely used in Earth sciences. The increasingly lengthy time span of space-based precipitation data records has enabled cross discipline investigations and applications that would otherwise not be possible, revealing discoveries related to hydrological and land processes, climate, atmospheric composition, and ocean freshwater budget and proving a vital element in addressing societal issues. The purpose of this article is to demonstrate how the availability and continuity of precipitation data records from recent and upcoming space missions is transforming the ways that scientific and societal issues are addressed, in ways that would not be otherwise possible. [ABSTRACT FROM AUTHOR]

Abstract: This paper explores the many aspects of precipitation measurement that are relevant to providing an accurate global assessment of this important environmental parameter. Methods discussed include ground data, satellite estimates and numerical models. First, the methods for measuring, estimating, and modeling precipitation are discussed. Then, the most relevant datasets gathering precipitation information from those three sources are presented. The third part of the paper illustrates a number of the many applications of those measurements and databases, namely hydropower, data assimilation and validation of Regional Climate Models (RCM). The aim of the paper is to organize the many links and feedbacks between precipitation measurement, estimation and modeling, indicating the uncertainties and limitations of each technique in order to identify areas requiring further attention, and to show the limits within which datasets can be used. Special emphasis is put on the central role of the upcoming Global Precipitation Measurement (GPM) mission in precipitation science. [Copyright &y& Elsevier]

Abstract: This paper discusses the potential of Regional Climate Models (RCMs) as reanalysis tools by presenting a reconstruction of the European climate using several RCMs with diverse physical parameterizations. The use of RCMs is intended to increase the spatial resolution of the analysis provided by Global Models through dynamic downscaling. At the same time, the use of several models allows us to characterize the uncertainties, as these can be estimated from the spread of the ensemble. When the RCMs are nested in reanalyses instead of in a Global Model it is possible to create climatologies of unprecedented robustness for variables such as temperature, precipitation, wind speed, and humidity, among others. While these climatologies are subject to further improvement as methods and computing power evolve, they point the way forward to the development of atmospheric information products suitable for a variety of studies including education, agriculture, renewable energies and climate change research, biogeography, insurance, risk assessment, hydrology, and regional planning. [Copyright &y& Elsevier]

This paper presents an analysis of the precipitation climate signal in Europe emerging from a simulation of heterogeneous regional climate models (RCMs) using five observational datasets as the reference for present day climate conditions. Current climate simulations, as well as those from the A2 family of scenarios from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES-A2), from eight RCMs involved in the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE) project have been cross-compared with data from the Climate Research Unit (CRU), the Global Precipitation Climatology Project (GPCP), the Global Precipitation Climatology Centre (GPCC), the Climate Prediction Center (CPC), and the CPC Merged Analysis of Precipitation (CMAP) databases for Europe. The RCMs used are HIRHAM, the Climate High Resolution Model (CHRM), the Rossby Centre Atmosphere–Ocean (RCAO) model, the GKSS Climate Version of the Local Model (CLM), the Hadley Center RCM (HadRM3H), the Atmospheric Hydrostatic Regional Model (REMO), the Prognostic Model at the Mesoscale (PROMES), and the regional coupled ocean–atmosphere–ice model (RACMO). The comparison shows that the climate signal has to be interpreted depending on the reference data used. Although each validation dataset has its own relative merits and shortcomings, it is known that all of the datasets present variable uncertainties and error sources, which impedes consideration of a single dataset as the only valid representation of actual precipitation. Hence, it is suggested that a robust joint estimate of changes in future precipitation might include the uncertainties of both the RCMs and those of the observational datasets. After accounting for the difference between observed and simulated precipitation in the present climate, the analysis of such joint estimates reveals significant agreement in the climate signal for most of Europe. This lends confidence to the idea that the RCMs are able to correctly simulate future changes in precipitation. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) are dynamical downscaling tools aimed to improve the modelling of local physical processes. Ensembles of RCMs are widely used to improve the coarse-grain estimates of global climate models (GCMs) since the use of several RCMs helps to palliate uncertainties arising from different dynamical cores and numerical schemes methods. In this paper, we analyse the differences and similarities in the climate change response for an ensemble of heterogeneous RCMs forced by one GCM (HadAM3H), and one emissions scenario (IPCC's SRES-A2 scenario). As a difference with previous approaches using PRUDENCE database, the statistical description of climate characteristics is made through the spatial and temporal aggregation of the RCMs outputs into probability distribution functions (PDF) of monthly values. This procedure is a complementary approach to conventional seasonal analyses. Our results provide new, stronger evidence on expected marked regional differences in Europe in the A2 scenario in terms of precipitation and temperature changes. While we found an overall increase in the mean temperature and extreme values, we also found mixed regional differences for precipitation. [ABSTRACT FROM AUTHOR]

This paper analyzes the changes in the precipitation climatologies of Europe for the periods 1960–90 and 2070–2100 using a heterogeneous set of regional climate models (RCMs). The authors used the Climatic Research Unit (CRU) database to define a precipitation climatology for current climate conditions (1960–90), then compare the estimates with the RCMs’ simulations for the same period using spectral analysis. After the authors evaluated the performance of the models compared with validation data for current climate, they calculated the future climate spectra (2070–2100). Changes in the future climate have been evaluated in terms of differences in the phase and amplitude of the annual cycle with respect to present conditions. The results show that models provide consistent results and that under the A2 scenario (increased greenhouse gases conditions) precipitation climatologies in Europe are expected to suffer noticeable changes, the most important being a strengthening of the annual cycle in most of the Atlantic coastal areas of the continent. While total amounts of rainfall might undergo little change, the consequences of changes in the seasonal distribution of precipitation will strongly affect both ecosystems and human activities. Differences were also found in the probability distribution function (pdf) of precipitation, indicating an overall increase in the frequency of precipitation-related hazards in Europe. [ABSTRACT FROM AUTHOR]

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]

The convective rainfall rate from cloud physical properties (CRPh) algorithm for Meteosat second-generation satellites is a day-only precipitation algorithm developed at the Spanish Meteorological Agency (AEMET) for EUMETSAT' Satellite Application Facility in support of nowcasting and very short-range forecasting (NWC SAF). It is therefore mainly intended to provide input for monitoring and near-real-time forecasts for a few hours. This letter critically discusses the theoretical basis of the algorithm with special emphasis on the empirical values and assumptions in the microphysics of precipitation, and compares the qualitative performances of the CRPh with its antecessor, the convective rainfall rate algorithm (CRR), using an object-based method applied to a case-study. The analyses show that AEMET's CRPh is physically consistent and outperforms the CRR. The applicability of the algorithm for nowcasting and the challenges of improving the product to an all-day algorithm are also presented. [ABSTRACT FROM AUTHOR]

This paper presents a consensus estimate of the changes in oceanic precipitation off the coast of Europe under increasing greenhouse gas emissions. An ensemble of regional climate models (RCMs) and three gauge and satellite-derived observational precipitation datasets are compared. While the fit between the RCMs’ simulation of current climate and the observations shows the consistency of the future-climate projections, uncertainties in both the models and the measurements need to be considered to generate a consensus estimate of the potential changes. Since oceanic precipitation is one of the factors affecting the thermohaline circulation, the feedback mechanisms of the changes in the net influx of freshwater from precipitation are relevant not only for improving oceanic-atmospheric coupled models but also to ascertain the climate signal in a global warming scenario. [ABSTRACT FROM AUTHOR]

Precise estimates of precipitation are required for many environmental tasks, including water resources management, improvement of numerical model outputs, nowcasting and evaluation of anthropogenic impacts on global climate. Nonetheless, the availability of such estimates is hindered by technical limitations. Rain gauge and ground radar measurements are limited to land, and the retrieval of quantitative precipitation estimates from satellite has several problems including the indirectness of infrared-based geostationary estimates, and the low orbit of those microwave instruments capable of providing a more precise measurement but suffering from poor temporal sampling. To overcome such problems, data fusion methods have been devised to take advantage of synergisms between available data, but these methods also present issues and limitations. Future improvements in satellite technology are likely to follow two strategies. One is to develop geostationary millimeter-submillimeter wave soundings, and the other is to deploy a constellation of improved polar microwave sensors. Here, we compare both strategies using a simulated precipitation field. Our results show that spatial correlation and RMSE would be little affected at the monthly scale in the constellation, but that the precise location of the maximum of precipitation could be compromised; depending on the application, this may be an issue. [ABSTRACT FROM AUTHOR]