ABSTRACT: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 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.

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Abstract. This study examines the joint variability of precipitation, river streamflow and temperature over northeastern Argentina; advances the understanding of their links with global SST forcing; and discusses their impacts on water resources, agriculture and human settlements. The leading patterns of variability, and their nonlinear trends and cycles are identified by means of a principal component analysis (PCA) complemented with a singular spectrum analysis (SSA). Interannual hydroclimatic variability centers on two broad frequency bands: one of 2.5–6.5 years corresponding to El Niño Southern Oscillation (ENSO) periodicities and the second of about 9 years. The higher frequencies of the precipitation variability (2.5–4 years) favored extreme events after 2000, even during moderate extreme phases of the ENSO. Minimum temperature is correlated with ENSO with a main frequency close to 3 years. Maximum temperature time series correlate well with SST variability over the South Atlantic, Indian and Pacific oceans with a 9-year frequency. Interdecadal variability is characterized by low-frequency trends and multidecadal oscillations that have induced a transition from dryer and cooler climate to wetter and warmer decades starting in the mid-twentieth century. The Paraná River streamflow is influenced by North and South Atlantic SSTs with bidecadal periodicities. The hydroclimate variability at all timescales had significant sectoral impacts. Frequent wet events between 1970 and 2005 favored floods that affected agricultural and livestock productivity and forced population displacements. On the other hand, agricultural droughts resulted in soil moisture deficits that affected crops at critical growth stages. Hydrological droughts affected surface water resources, causing water and food scarcity and stressing the capacity for hydropower generation. Lastly, increases in minimum temperature reduced wheat and barley yields.

Abstract. The current study advances the documentation of dry episodes over Argentina’s Core Crop Region, where the production of major crops like wheat, corn, and soybean is most intense and represents the main contribution to the country’s Gross Domestic Product. Our analysis focuses on the properties of droughts that include their magnitude, frequency at different time scales, duration, and severity. It is of interest to assess the relationship between those properties and the crop yields. We analyzed 40 years of precipitation and soil moisture at resolutions suitable for regional studies. The analysis of precipitation and soil moisture anomalies is complemented with the corresponding standardized indices estimated at time scales of 3- and 6-months. Most droughts tend to occur for periods shorter than three months, but a few can extend up to one year and fewer even longer. However, if a multiyear drought experienced breaks, each period would be considered a separate case. Analysis of the frequency distribution indicates that cases of water deficit conditions are more common than instances of water excess. As relevant as the drought duration is its timing and severity. Even short dry spells may have large impacts if they occur at the time of the critical growth period of a given crop. In the core crop region, corn yield is the most sensitive to drought severity. For these reasons, the quantification of severity during the crop-sensitive months is an indicator of what crop yields could be on the next campaign.