The Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset is used to examine projected changes in temperature and precipitation over the United States (U.S.), Central America and the Caribbean. The changes are computed using an ensemble of 31 models for three future time slices (2021–2040, 2041–2060, and 2080–2099) relative to the reference period (1995–2014) under three Shared Socioeconomic Pathways (SSPs; SSP1-2.6, SSP2-4.5, and SSP5-8.5). The CMIP6 ensemble reproduces the observed annual cycle and distribution of mean annual temperature and precipitation with biases between − 0.93 and 1.27 °C and − 37.90 to 58.45%, respectively, for most of the region. However, modeled precipitation is too large over the western and Midwestern U.S. during winter and spring and over the North American monsoon region in summer, while too small over southern Central America. Temperature is projected to increase over the entire domain under all three SSPs, by as much as 6 °C under SSP5-8.5, and with more pronounced increases in the northern latitudes over the regions that receive snow in the present climate. Annual precipitation projections for the end of the twenty-first century have more uncertainty, as expected, and exhibit a meridional dipole-like pattern, with precipitation increasing by 10–30% over much of the U.S. and decreasing by 10–40% over Central America and the Caribbean, especially over the monsoon region. Seasonally, precipitation over the eastern and central subregions is projected to increase during winter and spring and decrease during summer and autumn. Over the monsoon region and Central America, precipitation is projected to decrease in all seasons except autumn. The analysis was repeated on a subset of 9 models with the best performance in the reference period; however, no significant difference was found, suggesting that model bias is not strongly influencing the projections.

Abstract. Downscaling of climate model data is essential to most impact analysis. We compare two methods of statistical downscaling to produce continuous, gridded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km² per grid cell) resolution over the western U.S. We use NCEP/NCAR Reanalysis data from 1950–1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscaling (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA downscales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to generate daily values. The methods produce comparable skill in producing downscaled, gridded fields of precipitation and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit some skill in reproducing both observed wet and dry extremes and the difference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the reanalysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demonstrates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day correspondence of weather from the GCM needs to be reproduced for some applications. The ability to produce skillful downscaled daily data depends primarily on the ability of the climate model to show daily skill.

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Central America has suffered the impact of several extreme hydrometeorological events, among which drought stands out. This has had adverse effects of different kinds in the region known as the Central American Dry Corridor (CSC, in Spanish). The objective of this work was to describe the impacts that agriculture, livestock and economy of the CSC countries have suffered due to droughts: agricultural, hydrological and socioeconomic. A review of primary and secondary sources was carried out, such as scientific articles, press reports and studies reports from national and international institutions. The most recurrent impacts are at the level of basic grains and cattle, also due in part to the ENSO (El Niño-Southern Oscillation) phenomenon. Because the CSC is a region with high vulnerability to drought and other extreme hydrometeorological events, it is necessary to carry out an adequate characterization of the CSC taking as a baseline similar studies like this one, that orginate a discussion process for the design and implementation of strategies and anticipated public policies of adaptation and mitigation of the drought in the CSC and therefore, lead to improve the quality of life of its population.

Abstract. The mid-summer drought, veranillo or canícula, is a phenomenon experienced in many areas, including Mexico, Central America, and the Caribbean. It generally is experienced as reduced rainfall in July–August, in the middle of the typical rainy season (May–September). Many past studies have attempted to quantify changes in mid-summer drought characteristics during the recent past or for future climate projections. To do this, objective definitions of a mid-summer drought's occurrence, strength, and duration have been developed by many researchers. In this effort we adopt a recent set of definitions and examine the impact of varying these on the characterization of mid-summer droughts and the detected changes over the past 4 decades. We find the selection of a minimum intensity threshold has a dramatic effect on the results of both the area considered as experiencing a mid-summer drought and the changes detected in the recent historical record. The intensity chosen can affect both the magnitude and direction of changes reported in the recent observed record. Further, we find that the typical mid-summer drought pattern may not be occurring during the time it has historically; whether examining past or future changes or developing improved seasonal forecasts, the non-stationarity of its timing should be accommodated.