East Africa rainfall trends and variability 1983–2015 using three long-term satellite products

Daily time series from the Climate Prediction Center (CPC) Africa Rainfall Climatology version 2.0 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and Tropical Applications of Meteorology using SATellite (TAMSAT) African Rainfall Climatology And Time series version 2 (TARCAT) high-resolution long-term satellite rainfall products are exploited to study the spatial and temporal variability of East Africa (EA, 5S–20N, 28–52E) rainfall between 1983 and 2015. Time series of selected rainfall indices from the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices are computed at yearly and seasonal scales. Rainfall climatology and spatial patterns of variability are extracted via the analysis of the total rainfall amount (PRCPTOT), the simple daily intensity (SDII), the number of precipitating days (R1), the number of consecutive dry and wet days (CDD and CWD), and the number of very heavy precipitating days (R20). Our results show that the spatial patterns of such trends depend on the selected rainfall product, as much as on the geographic areas characterized by statistically significant trends for a specific rainfall index. Nevertheless, indications of rainfall trends were extracted especially at the seasonal scale. Increasing trends were identified for the October–November–December PRCPTOT, R1, and SDII indices over eastern EA, with the exception of Kenya. In March–April–May, rainfall is decreasing over a large part of EA, as demonstrated by negative trends of PRCPTOT, R1, CWD, and R20, even if a complete convergence of all satellite products is not achieved.This study was supported by the European Union’s Seventh Programme for research, technological development, and demonstration under Grant Agreement 603608 (eartH2Observe)

Pronóstico de engelamiento y ondas de montaña mediante modelos mesoescalares orientado a mejorar la seguridad aérea [Presentación]

Presentación realizada en el VI Simposio Nacional de Predicción "Memorial Antonio Mestre", celebrado en la sede central de AEMET en Madrid del 17 al 19 de septiembre de 2018

WRF hourly evaluation for extreme precipitation events

.Precipitation is one of the most relevant fields in atmospheric modeling because of its environmental, social and economic implications. However, precipitation validation from weather model outputs presents substantial challenges, such as measurement uncertainties, use of gridded datasets vs. direct observations, and the selection of statistical goodness-of-fit measures. The main difficulty of working with precipitation is that it can be spatially irregular, especially in extreme events. High temporal aggregation smooths the field and reduces verification uncertainty. For this reason, validations are usually focused on a daily scale. However, many extreme events occur on shorter periods, for which a sub-daily precipitation assessment is required. In this paper, hourly precipitation verification of the Weather Research and Forecasting (WRF) model is explored for 45 extreme precipitation events (EPEs) recorded in northeastern Spain. For this, stations with recorded EPEs were classified according to the hourly distribution of precipitation. WRF simulations were established considering three microphysics and two planetary boundary layer (PBL) parameterizations. Finally, several statistical goodness-of-fit measures and spatial and temporal precipitation distributions were used for evaluating WRF performance. The results showed that microphysics were more important than PBL parameterizations. Goddard and Thompson together with Mellor-Yamada-Nakanishi and Nino PBL gave better results for most of the analyzed characteristics. However, an optimal combination of parameterizations was not obtained for all EPEs, because event characteristics had important effects on model performance.S

East Africa precipitation variability during recent decades

Póster presentado en: 8th Ipwg and 5th Iwssm Joint Workshop celebrado en Bolonia, Italia, del 3 al 6 de octubre de 2016.Estimating space-time variability of precipitation is an important task in East Africa, considering the observed increased frequency of extreme events, drought episodes in particular. These events deeply affect the population with implications on agriculture and consequently food security. Daily accumulated precipitation time series from satellite retrieval algorithms, ARC, CHIRPS, TAMSAT, TMPA-3B42, and CMORPH are exploited to study the spatial and temporal variability of East Africa (EA – 5°S-20°N, 28°E-52°E) precipitation during last decades. The analysis is carried out by computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), e.g. CDD, CWD, SDII, PRCPTOT, and R1, at the yearly and seasonal scales. The purpose is to identify the occurrence of extreme events (droughts and floods), and extract precipitation spatial patterns of variation by trend analysis (Mann-Kendall technique). Prior to the analysis satellite time series are checked for the possible presence of inhomogeneities due to variations in rain gauge density and/or in the satellite retrieval algorithms

Pronóstico de engelamiento y ondas de montaña mediante modelos mesoescalares orientado a mejorar la seguridad aérea

Ponencia presentada en: VI Simposio Nacional de Predicción, celebrado en los servicios centrales de AEMET, en Madrid, del 17 al 19 de septiembre de 2018.La turbulencia y la formación de hielo en las aeronaves son dos de los fenómenos meteorológicos más peligrosos en la seguridad de la aviación. Por lo tanto, se recomienda encarecidamente evitar las áreas con alta probabilidad de episodios de formación de hielo a lo largo de las rutas de llegada a, y salida de, los aeropuertos. Este problema es relativamente común en el aeropuerto internacional Madrid-Barajas Adolfo Suárez (LEMD), por lo que es necesario caracterizar estos episodios y mejorar su pronóstico. En este trabajo se ha utilizado el modelo Weather Research and Forecasting (WRF) para la simulación de episodios de ondas de montaña previamente observados. También se han usado herramientas de teledetección tanto para la verificación de las salidas del modelo como para su aplicación al nowcasting o predicción en tiempo real. Esta información puede resultar de gran utilidad en la gestión de las operaciones aeroportuarias, con el objetivo de evitar áreas con riesgo de turbulencia y engelamiento

Evaluation of gridded rain‐gauge‐based precipitation datasets: impact of station density, spatial resolution, altitude gradient and climate

Gridded precipitation datasets have been developed for data assimilation and evaluation tasks of weather and climate models and for climate analyses. Gridded data uncertainty evaluation is crucial to understand the limitations and feasibility. The development of high‐resolution daily gridded precipitation datasets is desirable, but several factors need to be considered, namely rain gauge station availability, their spatial distribution, and orographic and climate characteristics of a study area. Quality assessment of gridded datasets can present difficulties when the influence of these factors is not thoroughly analysed. The main objective of this study was a detailed validation of precipitation grids based on four factors, that is, station density used for grid construction, grid spatial resolution, station altitude, and climate type. To this end, 18 grids were built using six spatial resolutions (0.01°, 0.025°, 0.05°, 0.1°, 0.2° and 0.4°) and three station densities (25, 50 and 75% of all available stations). Results indicate larger differences among the grids as a function of analysed factors. Station density was found to be the main factor, whereas grid spatial resolution had minor importance. However, the latter factor becomes more relevant in areas with strong altitude gradients and when a high station density is available. In addition, weak and moderate precipitation is overestimated on daily grids, whereas heavy precipitation cells are less frequent, reducing data variability. On the contrary, monthly and annual aggregates present less deviation from the observed distribution than daily comparisons. These findings question the applicability of the daily grid datasets for validation studies and climate analysis on a grid cell level.Funding came from projects LE240P18 (Consejería de Educación, Junta de Castilla y León) and CGL2016‐78702‐C2‐1‐R, PID2019‐108470RB‐C22, CGL2016‐80609‐R and PID2019‐108470RB‐C21 (Ministerio de Economía y Competitividad)

The contribution of rain gauges in the calibration of the IMERG product: results from the first validation over Spain

After 5 years in orbit, the Global Precipitation Measurement (GPM) mission has produced enough qualitycontrolled 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.Funding from projects CGL2013- 48367-P, CGL2016-78702-C2-1-R, CGL2016-80609-R (Ministerio de Economía y Competitividad), UNCM08-1E-086 (Ministerio de Ciencia e Innovación), and Development of Numerical Weather Prediction and Data Application Technique 1365002970/KMA2018-00721 (Korea Meteorological Administration) is gratefully acknowledged

Snowfall events in the Cantabrian Mountains of northwestern Spain: WRF multiphysics ensemble assessment based on ground and multi-satellite observations

[EN] Snowfall in elevated areas of the mid-latitudes has a strong impact on infrastructure, freshwater availability, and the climate system. The Cantabrian Mountains of the northwestern Iberian Peninsula are very vulnerable to climate change because of their moderate altitudes, which limits their snowfall. Monitoring snow events is essential for the evaluation of weather and climate prediction models. However, measurement networks are scarce in mountainous areas and have great uncertainties because of blizzards. In this study, a multiphysics ensemble of the Weather Research and Forecasting (WRF) model was designed using three microphysics and two planetary boundary layer (PBL) schemes to simulate nine snowfall events in the Cantabrian Mountains during autumn and winter 2021–2022. The WRF was validated using several snow characteristics, such as liquid water equivalent, snow cover, and snow depth. Liquid water equivalent was evaluated using snow-gauge networks and satellite products in an assessment of snow cover. In addition, a monitoring network of webcams and snow poles was implemented, improving the low density of snow observations in the mountains. The results showed good model performance for detection of snow cover and slight overestimation of liquid water equivalent and snow thickness, which may have been caused by under-catchment that is generally an effect of wind on the measurement systems and by snow compaction, respectively. Morrison microphysics and Mellor-Yamada-Nakanishi-Niino (MYNN PBL) yielded better results for liquid water equivalent at higher altitudes and output greater snow cover. The results help determine the best configurations for snow modelling in the study area to develop future studies of the spatiotemporal patterns of snow distribution.S

Numerical simulations of snowfall events: sensitivity analysis of physical parameterizations

Accurate estimation of snowfall episodes several hours or even days in advance is essential to minimize risks to transport and other human activities. Every year, these episodes cause severe traffic problems on the northwestern Iberian Peninsula. In order to analyze the influence of different parameterization schemes, 15 snowfall days were analyzed with the Weather Research and Forecasting (WRF) model, defining three nested domains with resolutions of 27, 9, and 3 km. We implemented four microphysical parameterizations (WRF Single‐Moment 6‐class scheme, Goddard, Thompson, and Morrison) and two planetary boundary layer schemes (Yonsei University and Mellor‐Yamada‐Janjic), yielding eight distinct combinations. To validate model estimates, a network of 97 precipitation gauges was used, together with dichotomous data of snowfall presence/absence from snowplow requests to the emergency service of Spain and observatories of the Spanish Meteorological Agency. The results indicate that the most accurate setting of WRF for the study area was that using the Thompson microphysical parameterization and Mellor‐Yamada‐Janjic scheme, although the Thompson and Yonsei University combination had greater accuracy in determining the temporal distribution of precipitation over 1 day. Combining the eight deterministic members in an ensemble average improved results considerably. Further, the root mean square difference decreased markedly using a multiple linear regression as postprocessing. In addition, our method was able to provide mean ensemble precipitation and maximum expected precipitation, which can be very useful in the management of water resources. Finally, we developed an application that allows determination of the risk of snowfall above a certain threshold.This paper was supported by the following grants: TEcoAgua, METEORISK PROJECT(RTC‐2014‐1872‐5), Granimetro(CGL2010‐15930) and MINECO(CGL2011‐25327, RTC‐2014‐1872‐5 and ESP2013‐47816‐C4‐4P), and LE220A11‐2 and LE003B009 awarded by the Junta de Castilla and León

Anomalías sinópticas y su relación con el incremento de granizo en 2006

Ponencia presentada en: VIII Congreso de la Asociación Española de Climatología celebrado en Salamanca entre el 25 y el 28 de septiembre de 2012.[ES]Las tormentas de granizo son uno de los riesgos meteorológicos más importantes del SW de Europa. Concretamente el Valle Medio del Ebro (VME) es el área que registra la mayor frecuencia de eventos de granizo de España, con unas pérdidas económicas de alrededor de 100 M€ anuales. El Grupo de Física de la Atmósfera (GFA) de la Universidad de León realiza campañas de investigación en el VME desde 2001 de forma continuada, registrando un promedio de 60 días de tormenta cada verano, mediante un radar meteorológico.[EN]Hailstorms are one of the principal risks in the SW of Europe. Specifically, the Mid-Ebro Valley (VME), is the area that has the greatest frequency of registered hail events in Spain, with economic losses of approximately 100 M€ annually. The Group for Atmospheric Physics (GFA) at the University of León has done research campaigns in the VME continuously since 2001, registering 60 storm days per year via meteorological radar.Este estudio ha sido financiado por los proyectos REN 2000-1210 CLI, REN 2003-09617-C02-01, CGL 2006-13372-C02-01, CGL 2010-15930 del Plan Nacional del I+D+i