A Weather Type classification based on the CESM-LE over the Middle Americas

Abstract

Abstract. In this study, two classifications of 20 Weather Types (WTs) were used to identify large-scale and synoptic-scale patterns over the Middle Americas region (MAR) that comprises Mexico, intra-American seas, Central America, and northern South America. The Self-Organizing Maps (SOM) method was used to detect both classifications using standardized Mean Sea-Level Pressure (MSLP) anomalies from the ERA-Interim (ERA-I) reanalysis and the Community Earth System Model-Large Ensemble (CESM-LE) in the historical period and its future projection under an RCP8.5 scenario. The WTs obtained with the CESM-LE in the historical period were assigned to each day of the future projection. Averages of the days belonging to each WT of the historical period were compared between both classifications (ERA-I and CESM-LE) employing seasonal and monthly frequencies of occurrence, correspondence in days of occurrence, Pearson's spatial correlation, and position changes of high-pressure semi-permanent centers such as the North Atlantic Subtropical High (NASH) and the North Pacific High (NPH). From precipitation and MSLP, it was observed that WTs obtained with CESM-LE showed a marked seasonality in their temporal distribution, mainly in the wet period (May–October), similar to the ERA-I classification. Three characteristic phenomena of MAR were the North American Monsoon System (NAMS), the Mid-Summer Drought (MSD), and the Caribbean Low-Level Jet (CLLJ). The CESM-LE adequately represented these phenomena in the historical period compared with ERA-I. Regarding the future projection, the CESM-LE ensemble showed that the spatial patterns were very similar in the historical period. However, differences in precipitation between August and September decreased. To assess the effect of internal climate variability of the CESM-LE, we analyzed the spatial average of precipitation in two regions: NAMS and MSD, for the 34 members of the ensemble in the future projection. In the CLLJ region, differences between the historical and the future projection in terms of averages of the zonal-wind component and precipitation were less than 1 %. This analysis showed that the SOM technique detected the signal of climate change on a regional scale without being affected by the internal global variability of the model. Therefore, SOM emerged as a useful tool for the analysis of numerical experiments such as CESM-LE.