Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis

Abstract

Abstract. High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds – the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May–June and the other in August-September-October (ASO), separated by the mid-summer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 °C (around May). Then, the SST decreases to around 1 °C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 °C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

Observed (1970–1999) climate variability in Central America using a high-resolution meteorological dataset with implication to climate change studies

“…3d). It has been found in other studies that an index consisting of calculating the difference between the standardized values of ENSO indexes and TNA is a better predictor of precipitation in the region (Maldonado and Alfaro 2011;Maldonado et al 2013;Enfield and Alfaro 1999). In fact, the ENSO index Niño3.4 is highly correlated with P in most of the region (Fig.…”

“…Even with no significant changes in precipitation, warming trends in the region can still have severe consequences in the hydrology of the region, as increases in evapotranspiration can produce significant reductions in runoff and water availability (Hidalgo et al 2013). The contrast in SST between the Pacific and Atlantic Ocean as a good indicator of precipitation in most of the Central American region was suggested by Maldonado and Alfaro (2011);Maldonado et al (2013) and Enfield and Alfaro (1999) who attributed the correlations between SSTs and P to the strengthening or weakening of the trade winds. The strength of the rainfall response appears to depend on how SSTa in the tropical Atlantic and eastern Pacific combine.…”

“…In addition, the annual results found here suggest the possibility of producing higher-resolution seasonal forecasts that are based on these large-scale climate precursors (e.g. Alfaro 2007aAlfaro , 2007bMaldonado and Alfaro 2011;Maldonado et al 2013;Alfaro 2014;Fallas-López and Alfaro 2014) or to use the P and Tavg datasets to produce hydrological indexes to improve forecasts by including the hydrological Bmemory^of the land surface, with direct applications to the Regional Climate Outlook Forums in Central America (Donoso and Ramirez 2001;García-Solera and Ramírez 2012). The high-resolution Tavg dataset allowed a better characterization of the spatial patterns of annual trends in the region, and point to a widespread warming of Central America, with the exception of a few smaller areas that actually experienced cooling.…”

“…The use of the information of the contrast between Pacific and Caribbean SSTa to predict seasonal precipitation has been studied before (e.g. Maldonado et al 2013;Alfaro 2007b), but there are almost no studies linking temperature with this contrast (e.g. Alfaro 2007a; Alfaro 2000; Fallas-Lopéz and Alfaro 2014).…”

“…The AMO (Enfield et al 2001), which represents the smoothed SST variations in the North Atlantic, was also obtained from ESRL-PSD-NOAA. Alternatively, we included two composed indexes constructed using the difference and summation of the ENSO and TNA standardized index, as these indexes are known to be correlated with P and Tavg respectively in large parts of the region (Maldonado and Alfaro 2011;Maldonado et al 2013;Enfield and Alfaro 1999).…”