This study first assesses the performance of regional climate models in the Coordinated Regional Climate Downscaling Experiment (CORDEX) in reproducing observed extreme precipitation indices over the Greater Horn of Africa (GHA) region during 1989–2005. The study then assesses projected changes in these extremes during 2069–2098 compared to 1976–2005. The Regional Climate Model (RCM) simulations are made using two RCMs, with large-scale forcing from four CMIP5 Global limate Models(GCMs) under two Representative Concentration Pathways (RCP4.5 and RCP8.5). We found that RCM simulations have reasonably captured observed patterns of moderate precipitation extreme indices (MPEI). Pattern correlation coefficients between simulated and observed MPEI exceed 0.5 for all except the Simple Daily Intensity Index (SDII). However, significant overestimations or underestimations exist over localized areas in the region. Projected changes in Total annual Precipitation (PRCPTOT) and the annual number of heavy (>10 mm) and very heavy (>20 mm) precipitation days by 2069–2098 show a general north-south pattern, with decreases over the southern half and increases over the northern half of the GHA. These changes are often greatest over parts of Somalia, Eritrea, the Ethiopian highlands and southern Tanzania. Maximum one- and five-day precipitation totals over a year and SDII (ratio of PRCPTOT to rainy days) are projected to increase over a majority of the GHA, including areas where PRCPTOT is projected to decrease, suggesting fewer, but heavier rainy days in the future. Changes in the annual sum of daily precipitation above the 95th and 99th percentiles are statistically significant over a few locations, with the largest projected decrease/increase over Eritrea and northwestern Sudan/Somalia. Projected changes in Consecutive Dry Days (CDD) suggest longer periods of dryness over the majority of the GHA, except the central portions covering northern Uganda, southern South Sudan, southeastern Ethiopia and Somalia. Substantial increases in CDD are located over southern Tanzania and the Ethiopian highlands. The magnitude and the spatial extent of statistically-significant changes in all MPEI increase from RCP4.5 to RCP8.5, and the separation between positive and negative changes becomes clearer under RCP8.5.

Heatwaves cause excess mortality and physiological impacts on humans throughout the world, and climate change will intensify and increase the frequency of heat events. Many adaptation and mitigation studies use spatial distribution of highly vulnerable local populations to inform heat reduction and response plans. However, most available heat vulnerability studies focus on urban areas with high heat intensification by Urban Heat Islands (UHIs). Rural areas encompass different environmental and socioeconomic issues that require alternate analyses of vulnerability. We categorized Nebraska census tracts into four urbanization levels, then conducted factor analyses on each group and captured different patterns of socioeconomic vulnerabilities among resultant Heat Vulnerability Indices (HVIs). While disability is the major component of HVI in two urbanized classes, lower education, and races other than white have higher contributions in HVI for the two rural classes. To account for environmental vulnerability of HVI, we considered different land type combinations for each urban class based on their percentage areas and their differences in heat intensifications. Our results demonstrate different combinations of initial variables in heat vulnerability among urban classes of Nebraska and clustering of high and low heat vulnerable areas within the highest urbanized sections. Less urbanized areas show no spatial clustering of HVI. More studies with separation on urbanization level of residence can give insights into different socioeconomic vulnerability patterns in rural and urban areas, while also identifying changes in environmental variables that better capture heat intensification in rural settings.

The supercontinent Pangea dominated our planet from the Permian into the Jurassic. Paleomagnetic reconstructions have been used to estimate the latitudinal position of Pangea during this 100-million-year period. Atmospheric circulation, recorded by eolian sandstones in the southwestern United States, shows a broad sweep of northeasterly winds over their northernmost extent, curving to become northwesterly in the south: This evidence is consistent with paleomagnetic reconstructions of the region straddling the equator in the Early Permian but is at odds with its northward movement to about 20°N by the Early Jurassic. At least one of the following scenarios must be true: The latitude based on paleomagnetism is incorrect; the interpretation of how winds shaped the dunes is mistaken; the basic climate controls in the Jurassic were different from those of today; or the paleogeographic reconstructions available are insufficient to adequately reproduce the wind fields responsible for dune formation.

The climatic impact of changes in terrestrial albedo has been studied using numerous climate models, ranging from simple, one‐dimensional energy balance climate models to the most complex, three‐dimensional general circulation models of the atmosphere. In the majority of these studies, the land‐surface albedos have been prescribed both spatially and temporally from albedo observations. The effects of variations in albedo, due to such factors as the angular distribution of incident radiation and plant phenology (especially leaf emergence, senescence, and drop), cannot be deduced from these observation‐based albedos.To overcome the limitations of using observed land‐surface albedos in climate models, a model of radiation transfer in plant canopies was used to predict vegetation albedo. This model incorporates the optical properties of the vegetation and soil surface as well as the micro and macrostructure of the canopy. Because of the model's reliance on these physical properties of the land‐surface cover, it is able to account explicitly for albedo variations caused by factors both internal and external to the vegetation canopy.Using the physiognomic classification of natural vegetation developed by Küchler, representative canopy architectures for each of 31 vegetation types were developed for each month of the year. Monthly albedos were then simulated for each vegetation type under a range of irradiance distributions. When these results are compared with existing observations of plant canopy albedo, the degree of correspondence is, in many cases, quite good. Moreover, the dependence of albedo on irradiance distribution predicted by the model agrees well with established theory.Global maps of land‐surface albedo are produced for both clear‐sky and overcast conditions in January, April, July, and October using a simple solar radiation model to determine the incident radiation field. These maps are compared with previously compiled maps of land‐surface albedo. Large differences between the model‐ and observation‐based global albedo maps occur for each of the four months. However, the model reproduces many of the large‐scale features and seasonal trends evident in albedo observations.