Search

The Gran Chaco ecoregion is South America’s largest remaining continuous stretch of dry forest. It has experienced intensive deforestation, mainly in the western part known as Dry Chaco, resulting in the highest rate of dry forest loss globally between 2000 and 2012. The replacement of natural vegetation with other land uses modifies the surface’s biophysical properties, affecting heat and water fluxes and modifying the regional climate. This study examines land use and land cover changes (LULCCs) in Dry Chaco from 2001 to 2015, their effects on local and non-local climate, and explores the potential impacts of future agricultural expansion in the region. To this end, Weather Research and Forecasting (WRF) model simulations are performed for two scenarios: the first one evaluates the observed land cover changes between 2001 and 2015 that covered 8 % of the total area of Dry Chaco; the second scenario assumes an intensive agricultural expansion within the Dry Chaco. In both scenarios, deforestation processes lead to decreases in LAI, increases in albedo, and reductions in stomatal resistance, reducing the net surface radiation and, correspondingly, a decrease in turbulent fluxes suggesting a decline in available energy in the boundary layer. The result is an overall weakening of the water cycle in the Dry Chaco and, most prominently, implies a reduction in precipitation. A feedback loop develops since dry soil absorbs significantly less solar radiation than moist soil. Finally, the simulations suggest that the Dry Chaco would intensify its aridity, extending the drier and hotter conditions into the Humid Chaco.

It is generally agreed that models that better simulate historical and current features of climate should also be the ones that more reliably simulate future climate. This article describes the ability of a selection of global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to represent the historical and current mean climate and its variability over northeastern Argentina, a region that exhibits frequent extreme events. Two types of simulations are considered: Long-term simulations for 1901-2005 in which the models respond to climate forcing (e.g. changes in atmospheric composition and land use) and decadal simulations for 1961-2010 that are initialized from observed climate states. Monthly simulations of precipitation and temperature are statistically evaluated for individual models and their ensembles. Subsets of models that best represent the region´s climate are further examined. First, models that have a Nash-Sutcliffe efficiency of at least 0.8 are taken as a subset that best represents the observed temperature fields and the mean annual cycle. Their temperature time series are in phase with observations (r > 0.92), despite systematic errors that if desired can be corrected by statistical methods. Likewise, models that have a precipitation Pearson correlation coefficient of at least 0.6 are considered that best represent regional precipitation features. GCMs are able to reproduce the annual precipitation cycle, although they underestimate precipitation amounts during the austral warm season (September through April) and slightly overestimate the cold season rainfall amounts. The ensembles for the subsets of models achieve the best evaluation metrics, exceeding the performance of the overall ensembles as well as those of the individual models. Fil: Lovino, Miguel Angel. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina Fil: Müller, Omar Vicente. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina Fil: Berbery, Ernesto H.. University of Maryland; Estados Unidos Fil: Muller, Gabriela Viviana. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina

Ponencia presentada en: XI Congreso de la Asociación Española de Climatología celebrado en Cartagena entre el 17 y el 19 de octubre de 2018. [ES]La variabilidad y los cambios en extremos climáticos afectan la región núcleo de cultivos de Argentina y pueden incrementar su vulnerabilidad ocasionando desastres sin precedentes. Este estudio investiga los cambios de largo período y la variabilidad interanual de los extremos climáticos diarios de precipitación y temperatura y evalúa en qué medida los reanálisis globales reproducen la variabilidad observada en el pasado reciente. Los datos incluyen observaciones con calidad controlada (1963-2013) y los reanálisis ERA-Interim y NCEP2 (1979-2011). Los extremos climáticos se caracterizan espacial y temporalmente con 11 índices de los propuestos por el Equipo de Expertos sobre Detección e Índices de Cambio Climático. Se aplicó un Análisis Espectral Singular para detectar los modos principales de las series temporales medias areales de los índices. Se ajustaron tendencias no-paramétricas lineales a las series temporales de cada índice para estimar la distribución espacial de los cambios medios. Los extremos de temperatura están cambiando hacia condiciones más cálidas. Los días cálidos han estado aumentando desde 1990 mientras que los días fríos han ido decreciendo. Las noches cálidas y frías muestran una señal de calentamiento significativa que parece estar estabilizándose en las últimas décadas. Los eventos de precipitación intensa aumentaron constantemente en la mayor parte de la región desde 1970. La cantidad máxima anual de precipitación en un día aumentó desde la década de 1970 hasta la del 2000, estabilizándose en años recientes. El reanálisis ERA-Interim puede reconocer los extremos de temperatura en tiempo y en espacio, mientras que el antiguo NCEP2 presenta errores sistemáticos. Ambos reanálisis reproducen la máxima precipitación anual en 5 días con grandes sesgos. Aunque se esperaría que los reanálisis agreguen información para extremos climáticos en áreas de observaciones escasas, aún deben usarse con mucha precaución y solo como complemento de las observaciones. [EN]Variability and changes in climate extremes affect the core crop region of Argentina and may increase its vulnerability leading to unprecedented disasters. This study investigates the long-term changes and interannual variability of daily temperature and precipitation climate extremes and assesses to what extent global reanalyses reproduce the observed variability in the recent past. Datasets include quality-controlled observations (1963-2013) and ERA-Interim and NCEP2 reanalyses (1979-2011). Climate extremes are characterized spatially and temporally by 11 indices proposed by the Expert Team on Climate Change Detection and Indices. A Singular Spectrum Analysis was applied to detect the leading modes of the area-averaged index time series. Nonparametric linear trends were fitted to each index time series to estimate the spatial distribution of mean changes. Temperature extremes are changing towards warmer conditions. Warm days has been increasing since 1990 while cold days has been decreasing. Warm and cold nights show a significant signal of warming that seems to be stabilizing in recent decades. Intense precipitation events in most of the region increased steadily since 1970. The annual maximum amount of 1-day precipitation events increased from the 1970s to the 2000s, stabilizing in recent years. The ERA-Interim reanalysis can recognize temperature extremes in time and space, while the older NCEP2 presents systematic biases. Both reanalyses reproduce the annual maximum 5-day precipitation with large biases. Although reanalyses would be expected to add information for climate extremes in areas of scarce observations, they still need to be used with great caution and only as a complement to observations. We appreciate the grant from the PRODACT 2018 of the Science and Technical Secretariat (FICH UNL). This research was carried out with support of Projects CRN3035 and CRN3095 of the Inter-American Institute for Global Change Research (IAI), which is supported by the US National Science Foundation. UNL Project C.A.I. + D. 2016 32/180 is also acknowledged.

Fil: Lovino, Miguel Ángel. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. Fil: García, Noberto Oscar. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina. The information regarding climate variability and extreme events (EE) and its impact on northeastern Argentina could help to assist decision-making and to achieve efficient climate risk management policies and practices. Precipitation and runoff series present a significant nonlinear trend, showing changes to wetter conditions from 1960 to 2000s and a trend reversal since 2005; together with oscillatory modes of 6.6 to 9 years. The largest and most intense wet extreme precipitation events (EPE) were recorded between 1970 and 2005, affecting agriculture and livestock productivity and impacting human settlements. On the other hand, the most severe droughts, which affected surface water resources and agricultural activities, occurred between 1901 and 1960. Our results suggest that the Central-West portion of the region is highly vulnerable to EPE. The EE of temperature indicate a change to warmer conditions, which would continue in the coming decades. This change might exacerbate the effects of heat islands, increase the problems of surface water quality and affect crop yields. In addition, heavy rainfall presents a continuous increase between 1963 and 2013, the maximum 5-day precipitation amount shows a cycle of 2 years and short-term dry events (intra-annual) rises from 1970. General Circulation Models (GCMs) show high skill in simulating medium temperatures at regional scales, although this models represent precipitation fields with dissimilar efficiencies. A statistical downscaling method allowed us to correct systematic errors of GCMs and to improve model efficiency. The downscale simulations of future climate indicate slightly positive variations of precipitation and increases of mean temperature. La información referente a la variabilidad y los eventos extremos climáticos (EE) y sus impactos en el nordeste argentino puede contribuir en la toma de decisiones y en la ejecución de políticas y prácticas de gestión de riesgos climáticos. La precipitación y los caudales presentan una tendencia hacia condiciones húmedas desde 1960, estabilizándose en 2000 y decayendo en 2005; junto a ciclos oscilatorios de 6.6 y 9 años. Un período de eventos extremos de precipitación (EPE) húmedos de gran duración e intensidad se registró entre 1970 y 2005, afectando la productividad agrícola-ganadera e impactando los asentamientos humanos; mientras que las sequías más severas ocurrieron entre 1901 y 1960, afectando los recursos hídricos superficiales y las actividades agrícolas. La zona más vulnerable a estos EPE es el centro-este de la región. Los EE de temperatura sugieren un cambio hacia condiciones más cálidas, que se continuaría en las décadas venideras, exacerbando los efectos de las islas de calor, favoreciendo los problemas de calidad del agua superficial y afectando los rendimientos de los cultivos. También se registra un continuo aumento de las precipitaciones intensas, ciclos de 2 años en la precipitación acumulada en 5 días y un incremento de los eventos secos intra-anuales. Los Modelos de Circulación General (GCMs) simulan aceptablemente la temperatura media regional, aunque con eficacias disimiles la precipitación. Un proceso de reducción estadístico de escala permitió corregir los errores sistemáticos y mejorar la eficiencia de los GCMs. Las simulaciones futuras indican leves aumentos de la precipitación y la temperatura. Consejo Nacional de Investigaciones Científicas y Técnicas