Capability of the SMHI-RCA4 RCM driven by the ERA-Interim reanalysis to simulate heat waves in Argentina.
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| Title: | Capability of the SMHI-RCA4 RCM driven by the ERA-Interim reanalysis to simulate heat waves in Argentina. |
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| Authors: | Collazo, Soledad1,2 scollazo@at.fcen.uba.ar, Lhotka, Ondřej3,4, Rusticucci, Matilde1,2, Kyselý, Jan3,5 |
| Source: | International Journal of Climatology. Jan2018, Vol. 38 Issue 1, p483-496. 14p. |
| Subject Terms: | *Heat waves (Meteorology), Atmospheric models, Southern oscillation, Meteorological stations, El Niño |
| Geographic Terms: | Argentina |
| Abstract: | ABSTRACT The aim of the work was to evaluate the capability of the SMHI-RCA4 regional climate model (RCM) driven by the ERA-Interim reanalysis to simulate heat waves in Argentina. Firstly, we evaluated simulations of summer daily maximum temperature (Tmax) against observed data from nine stations. The model showed a warm Tmax bias at six locations and the smallest and/or negative biases were located over regions with complex topography. Heat waves were defined based on exceedances of the daily 90th percentile of Tmax at individual stations. The model overestimated the intensity, duration, and number of heat waves at all locations, but more intense heat waves were underestimated. In particular, we analysed the extreme heat wave that occurred in November 1985 in northeastern Argentina and found out that a possible reason for its underestimation was an inaccurate simulation of the sea level pressure gradient in the region. The weaker pressure gradient in the model caused a reduction of the warm northerly advection. Finally, we studied how the parameters of heat waves varied among different phases of El Niño-Southern Oscillation (ENSO) for observed and modelled data. At five stations, the strongest heat waves occurred during La Niña years and were probably associated with the decrease in precipitation. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Climatology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
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