No abstract

RESUMENLos productos que proveen estimaciones de lluvia derivadas de satélites son útiles para el monitoreo tanto ambiental como de sequías, y permiten además afrontar el problema de las observaciones derivadas de estaciones pluviométricas mal distribuidas, siempre y cuando su precisión sea conocida. Venezuela es altamente vulnerable a eventos climáticos extremos como sequías extensivas y crecientes rápidas, por lo tanto conocer las debilidades y fortalezas de las estimaciones de lluvias derivadas de satélites resulta útil para la planificación de los recursos hídricos. Las estimaciones mensuales de lluvia derivadas del producto Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS v.2) son contrastadas con los registros proveniente de estaciones climáticas , empleando métricas numéricas para evaluar su desempeño en la estimación de la cantidad de lluvia, y métricas categóricas para evaluar su capacidad de detección de eventos de lluvia. Los análisis aplicados consideran diferentes categorías de lluvia, la estacionalidad y el contexto espacial. Los resultados muestran que el producto CHIRPS v.2 sobreestima (subestima) los valores más bajos (altos) de lluvia, aunque en la mayoría de las métricas de habilidad muestra un buen desempeño. Este producto consigue un mejor desempeño durante la estación lluviosa (abril-septiembre), pero sobreestima significativamente la frecuencia de los eventos de lluvias. También muestra mejor desempeño global en regiones planas abiertas (p. ej., Los Llanos), donde la precipitación es influida por la actividad de la zona de convergencia intertropical y los sistemas convectivos locales.ABSTRACT Satellite-derived rainfall products are useful for both drought and environmental monitoring, and they also allow for tackling the problem of sparse, unevenly distributed and erratic rain gauge observations provided their accuracy is well known. Venezuela is a country highly vulnerable to extreme weather events such as extensive droughts and flash floods; therefore, an understanding of the strengths and weaknesses of satellite-based rainfall products is useful for the planning of water resources. Using numerical metrics in order to evaluate performance, monthly rainfall estimates, from the Climate Hazards Group InfraRed Precipitation and Stations (CHIRPS v.2) product, are compared to gauge data from the 1981-2007 interval and categorical metrics for assessing rain-detection skills. The analysis was performed considering different rainfall categories, seasonality, and spatial context. The results show that the satellite product CHIRPS v.2 overestimates (underestimates) low (high) monthly rainfall values; although on the majority of numerical metrics of skill shows a good performance. This product, on the other hand, achieves better performance during the rainy season (April-September), significantly overestimating, however, the rainfall-events frequency. The product also shows best overall performance over flat and open regions (e.g., Los Llanos), where precipitation is influenced by...

Northeast Brazil (NEB) has recently experienced one of its worst droughts in the last decades, with large losses on rainfed agriculture. Soil moisture is the main variable to monitor agricultural drought. The remote sensing approach for drought monitoring has been enriched with the launch of the Soil Moisture and Ocean Salinity (SMOS) in November 2009 by European Space Agency (ESA). In this work, the Soil Water Deficit Index (SWDI) was calculated using the SMOS L2 soil moisture in the NEB. The SMOS-derived SWDI data (SWDIS) were evaluated against the atmospheric water deficit (AWD) calculated from in situ observations. Comparisons were made at seven-day and 0.25 • scales, over the time-span of June 2010 to December 2013. It was found that the SWDIS has a reasonably good overall performance in terms of the drought-weeks detection (skill = 0.986) and capture of the upper soil moisture temporal dynamic (r = 0.652), implying that the SWDIS could be used to track agricultural droughts. Furthermore, SWDIS shows poor performance at sites located in mountains regions affected by severe droughts (−0.10 ≤ r ≤ 0.10). It is also noted that the vegetal cover/use, climate regime, and soil texture have little influence on the AWD-SWDIS coupling.

Severe droughts have caused serious impact on water supply and agriculture in São Francisco River Basin (SFRB), Brazil, especially during the rainy season. Observational evidence suggests that droughts in this region could be driven by some large‐scale ocean‐atmospheric patterns. This study provides a general description of linkage between the ocean‐atmospheric circulation patterns and the droughts during the rainy season (November–December), in the SFRB's upper sub‐basins. The NCEP reanalysis I and monthly gridded precipitation dataset of the Global Precipitation Climatology Centre from 1948 to 2010 were used. SPI was used as drought index. All analyses were performed in a domain that covered South America and southern‐tropical portions of the Atlantic and Pacific Oceans. Both the wind speed and vertical velocity fields at 200 hPa and specific humidity at 700 hPa were analysed. Results indicate that more extensive short‐duration droughts are linked to: (1) El Niño conditions highly concentrated inside the Niño 3.4 region; (2) ITCZ with a northernmost‐than‐normal position; (3) weaker‐than‐normal convective activity over the SFRB coupled to a weaker‐than‐normal upper‐level westerly jet stream. For decadal scale, the atmospheric anomalies patterns are best correlated to long‐duration extensive droughts than the oceanic anomalies patterns (r = −0.84 and −0.14, respectively). This suggests that droughts in SFRB are strongly dependent on large‐scale moisture transport and upper‐level atmospheric circulation.