Abstract
High spatial resolution of precipitation (P) and average air temperature (Tavg) datasets are ideal for determining the spatial patterns associated with large-scale atmospheric and oceanic indexes, and climate change and variability studies, however such datasets are not usually available. Those datasets are particularly important for Central America because they allow the conception of climate variability and climate change studies in a region of high climatic heterogeneity and at the same time aid the decisionmaking process at the local scale (municipalities and districts). Tavg data from stations and complementary gridded datasets at 50 km resolution were used to generate a high-resolution (5 km grid) dataset for Central America from 1970 to 1999. A highresolution P dataset was used along with the new Tavg dataset to study climate variability and a climate change application. Consistently with other studies, it was found that the 1970-1999 trends in P are generally non-significant, with the exception of a few small locations. In the case of Tavg, there were significant warming trends in most of Central America, and cooling trends in Honduras and northern Panama. When the sea surface temperature anomalies between the Tropical Pacific and the Tropical Atlantic have different (same) sign, they are a good indicator of the sign of P (Tavg) annual anomalies. Even with non-significant trends in precipitation, the significant warming trends in Tavg in most of Central America can have severe consequences in the hydrology and water availability of the region, as the warming would bring increases in evapotranspiration, drier soils and higher aridity.
Highlights
High spatial resolution of precipitation (P) and average air temperature (Tavg) datasets are ideal for determining the spatial patterns associated with large-scale atmospheric and oceanic indexes, and for supporting climate change and variability studies
The drier areas of the Central American Dry Corridor (Hidalgo et al 2015), a region of relatively drier climatological conditions covering most of the Pacific slope of Guatemala, Honduras, El Salvador, Nicaragua and the north Pacific coast of Costa Rica can be identified in the precipitation normal patterns
The analysis of the 1970–1999 climate variability of high-resolution P and Tavg datasets allowed us to identify large-scale atmospheric and oceanic signals in the data. This helped to understand various aspects of climatic variability with more spatial precision. This is important in a region of complex topography such as the Central American isthmus
Summary
High spatial resolution of precipitation (P) and average air temperature (Tavg) datasets are ideal for determining the spatial patterns associated with large-scale atmospheric and oceanic indexes, and for supporting climate change and variability studies Those datasets are important for Central America because they allow the conception of climate variability and climate change studies in a region of high climatic heterogeneity and at the same time aid the decision-making process at the local scale (municipalities and districts). Temperature could still affect variability and especially trends on sensitive hydrological variables such as runoff and soil moisture through its influence on evapotranspiration (Imbach et al 2012; Hidalgo et al 2013) This is true for Central America, a tropical region with high temperatures and relatively low variability throughout the year. Some studies have suggested that the frequencies of extreme (high and low) P events are increasing (Aguilar et al 2005; IPCC 2007)
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