1. Evaluation and selection of CMIP6 GCMs for the characterization of temperature and precipitation in Central-Western Argentina.
- Author
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Marianetti, Georgina, Rivera, Juan A., and Bettolli, María Laura
- Subjects
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CLIMATE extremes , *EXTREME value theory , *ATMOSPHERIC models , *WATER supply , *WINE districts - Abstract
Climate models are indispensable tools for decision-making, yet their efficacy in characterizing climatic conditions in regions of complex topography, such as Central-Western Argentina (CWA), remains challenging. Therefore, the main objective of this study was to evaluate mean and extreme values of temperature and precipitation simulations from a set of CMIP6 climate models in CWA. The mean values were compared against CRU TS 4.05 for the period 1950–2014; and the extreme values against ERA5 for the temperature and ERA5, CPC, and CHIRPS for the precipitation during 1981–2010. To evaluate the mean values, we considered several statistical metrics that accounted for the representation of the annual cycle, the long-term trends, and the spatial patterns, followed by a selection of the climate models that best represent the region. Subsequently, we analyzed 20 climate extreme indices using Taylor Diagrams and box-and-whiskers plots. The CMIP6 models tended to exhibit a wet bias over CWA, with temperature simulations warmer (colder) than observations over the Andes (Lowlands). Moreover, most models adequately captured the increase in temperature, as well as the increase in precipitation in the lowlands and its decrease in the Andes. From the set of 24 precipitation and 12 temperature simulations, we evaluated the performance for the representation of climate extremes, finding that most models had difficulties with the quantification of indices based on percentiles. This climate information can be valuable to obtain more accurate climate projections for CWA and to aid decision-making in a region with significant wine production and high reliance on water resources. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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