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Rainfall in the moist Tropical Caribbean region (MTCR) in Costa Rica occurs practically throughout the year, with the quarters June–August (JJA) and December–February (DJF) concentrating over 70% of annual rainfall. On the other hand, in March–April and September–October, it rains below 100mm per month. This seasonal rainfall behavior makes the region ideal for producing bananas (Musa spp) and pineapple (Ananas comosus) for export (10% and 8% of total exports in 2021, respectively). A national-scale study determined that agriculture in the MTCR is one of the most vulnerable sectors to climate changes. However, the climate in this region has been poorly studied so far. This research analyzed the spatial and temporal variability of annual, monthly, and seasonal (DJF, JJA, SO) rainfall in the MTCR and how they change in the study period based on quality-checked series of daily rainfall from 28 weather stations in two periods: 1985‒2009 and 1997‒2019. The results show that rainfall regimes in the region are variable in space and throughout the year, with peaks occurring close to the mountain range and minimum values close to the coast. Trends were statistically significant in the period 1985‒2009 with a predominance of significant positive trends in DJF, and significant negative trends in SO. No significant trends (positive or negative) were observed in the period 1997–2019. JJA rainfall has uneven regional distribution and presents a positive and significant trend in the mountain region. This paper contributes to filling the knowledge gap in rainfall seasonality, variability, and trends in a region where banana and pineapple commercial plantations are fundamental to the country´s economy thus providing information to decision-making in the agri-food sector to reduce the negative impacts of changing rainfall regimes.

Under the current global warming trend, droughts are expected to increase, with serious implications for water resources management. This study analyzed the regional aspects of droughts in terms of streamflow deficiencies over the Andean rivers of Patagonia, Argentina. Based on the variable threshold level method, the main characteristics of streamflow droughts were obtained for the hydrological years 1962/63-2014/15, considering three different severity levels over 11 representative basins. Two distinct regional behaviors were identified in terms of temporal variations of streamflow drought duration and its cumulative deficit volume, dividing the study area into North and Central Patagonia. The effects of the Southern Annular Mode (SAM), the El Niño-Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) on the interannual and interdecadal variability of streamflow droughts were assessed through an empirical decomposition applied to the regional time series. These large-scale climatic oscillations have a distinct regional and temporal behavior in terms of the modulation of streamflow drought variability. Considering the interannual streamflow drought variability, the El Niño signal is more consistent and contributes with humid conditions, especially over North Patagonia. The multi-decadal component of the streamflow drought time series is linked to the upward trend in SAM, particularly over Central Patagonia. Fil: Rivera, Juan Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina Fil: Araneo, Diego Christian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina Fil: Penalba, Olga Clorinda. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: Villalba, Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina

This study aims to compare simulated soil moisture anomalies derived from different versions of the Global Land Data Assimilation System (GLDAS), the standardized precipitation index (SPI), and a new multisatellite surface soil moisture product over southern South America. The main motivation is the need for assessing the reliability of GLDAS variables to be used in the characterization of soil state and its variability at the regional scale. The focus is on the southeastern part of South America (SESA), which is part of the La Plata basin, one of the largest basins of the world, where agriculture is the main source of income. The results show that GLDAS data capture soil moisture anomalies and their variability, taking into account regional and seasonal dependencies and showing correspondence with other proxies used to characterize soil states. Over large portions of the domain, and particularly over SESA, the correlation with the SPI is very high, with GLDAS-2, version 2, exhibiting the highest values regardless of the season. Similar results were obtained by comparing the surface soil moisture anomalies from the GLDAS land surface model (LSM) against the satellite estimations for a shorter period of time. This work documents that the precipitation dataset used to force each LSM and the choice of the LSM are of major relevance for representing soil conditions in an adequate manner. The results are considered to support the use of GLDAS as an indicator of soil moisture states and for developing new soil moisture monitoring indices that can be applied, for example, in the context of agricultural production management. Fil: Spennemann, Pablo Cristian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos; Argentina Fil: Rivera, Juan Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Científico Tecnológico Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina Fil: Saulo, Andrea Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios de Clima y sus Impacto; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional; Argentina Fil: Penalba, Olga Clorinda. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y Los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

The importance of forecasting extreme wet and dry conditions from weeks to months in advance relies on the need to prevent considerable socioeconomic losses, mainly in regions of large populations and where agriculture is a key value for the economies, such as southern South America (SSA). To improve the understanding of the performance and uncertainties of seasonal soil moisture and precipitation forecasts over SSA, this study aims to 1) perform a general assessment of the Climate Forecast System, version 2 (CFSv2), soil moisture and precipitation forecasts against observations and soil moisture simulations based on GLDAS, version 2.0; 2) evaluate the ability of CFSv2 to represent wet and dry events through the forecasted standardized precipitation index (SPI) and standardized soil moisture anomalies (SSMA); and 3) analyze the capability of a statistical methodology (merging observations and forecasts) in representing a severe drought event. Results show that both SPI and SSMA forecast skill are regionally and seasonally dependent. In general, a fast degradation of the forecasts skill is observed as the lead time increases, resulting in almost no added value with regard to climatology at lead times longer than 3 months. Additionally, a better performance of the SSMA forecasts is observed compared to SPI calculated using three months of precipitation (SPI3), with a higher skill for dry events against wet events. The CFSv2 forecasts are able to represent the spatial patterns of the 2008/09 severe drought event, although it shows crucial limitations regarding the identification of drought onset, duration, severity, and demise, considering both meteorological (SPI) and agricultural (SSMA) drought conditions. Fil: Spennemann, Pablo Cristian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos; Argentina Fil: Rivera, Juan Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina Fil: Osman, Marisol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos; Argentina Fil: Saulo, Andrea Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos; Argentina Fil: Penalba, Olga Clorinda. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina

La Plata basin is one of the most important agricultural and hydropower-producing regions in the world. Extreme climate events such as cold and heat waves and frost events have a significant socioeconomic impact. This work analyzes the influence of the surface circulation in southern South America on daily maximum temperature TMAX and daily minimum temperature TMIN in southern La Plata basin. A Z test for the comparison of mean values and a Kolmogorov–Smirnov test for the comparison of distributions of TMAX and TMIN associated with each circulation pattern were performed. Specific daily surface circulation types are found to contribute to TMAX and TMIN anomalies and to have a predominant occurrence in the development of the extreme temperature events in the region. The TMAX spatial response to the regional low-level circulation is more homogenous and extended than is the response of TMIN.

La regionalización de diferentes variables climáticas ha sido llevada a cabo en diversas zonas del mundo, dado que para distintos propósitos es conveniente dividir espacialmente la climatología de una variable en un número de áreas cuasi-homogéneas. El objetivo de este trabajo es la obtención de una regionalización objetiva de las distintas variabilidades temporales de las cantidades de días secos en la República Argentina durante el trimestre de verano. Con el fin de lograr regiones con similar variabilidad temporal en las cantidades de días secos se exploraron dos métodos: Análisis de Componentes Principales (ACP) y el algoritmo de agrupamiento no-jerárquico de k-means. En base a una evaluación de los patrones espaciales, la regionalización obtenida mediante el método de k-means aplicado sobre las componentes principales rotadas más importantes, es más apropiada en comparación con la determinada por el método de ACP rotadas. Mediante este método, el territorio nacional presenta seis regiones principales: las regiones Centro- Este; Noreste; Centro y Sur Bonaerense; Noroeste; Centro-Oeste y Patagónica, las cuales son climáticamente coherentes.Objective regionalizations of different climatic variables have been performed in many regions of the World. For different purposes is convenient to make a spatial regionalization to find quasi-homogeneous climatic regions. The main objective of this work is to identify spatially homogeneous regions of dry days in Argentina with different temporal variabilities during summer season. In order to achieve regions with similar temporal variability in the amount of dry days, two methods are explored: principal component analysis (PCA) and k-means nonhierarchical cluster method. By means of a spatial patterns examination, the regionalization derived by k-means on the most important rotated principal components extracted is more adequate in comparison with the proposed by PCA method. Through this methodology, the country is divided in six main regions: Northeast region; Central-East region; Central and South Buenos Aires region; Northwest region; Central-West region; and Patagonia region, which are climatically consistent.

Water resources management and agriculture planning models require a statistical synthesis of some rainfall features, in particular those representing dry atmospheric conditions. The bigger the basin, the more important these features become, as is the case of the La Plata Basin (LPB). This paper focuses on the precipitation variability in the large LPB in South America, analysing the number of months per year with low rainfall and the sequences of months with low rainfall, their theoretical distributions and stability, which are needed as input for the models mentioned above. Long time series are used to analyse the low-frequency variability and the relative importance of decadal variability. Changes are evident in the number of months per year with low rainfall, with a decrease of about 20% in the period after 1970. Theoretical distribution models (binomial and geometric) are fitted to these empirical distributions, and the regional variability of the fitting parameters is shown. In practically the entire region, the goodness-of-fit of the two theoretical models considered is statistically satisfactory. The temporal variability of the parameters of the theoretical binomial (p) and geometric (α) distributions is analysed, in excluding sub-periods of 10 and 5 years, respectively. The results show low-frequency variability overlapped on a decadal variability, with low homogeneous regional behaviour. The distribution models have proven to be efficient for frequency adjustments of the rainfall properties studied. These results are an acceptable and necessary input to decision models in LPB. They also make it possible to infer effects of climate change. Copyright © 2008 Royal Meteorological Society