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The Benguela Current, located off the west coast of southern Africa, is tied to a highly productive upwelling system**1. Over the past 12 million years, the current has cooled, and upwelling has intensified**2, 3, 4. These changes have been variously linked to atmospheric and oceanic changes associated with the glaciation of Antarctica and global cooling**5, the closure of the Central American Seaway**1, 6 or the further restriction of the Indonesian Seaway**3. The upwelling intensification also occurred during a period of substantial uplift of the African continent**7, 8. Here we use a coupled ocean-atmosphere general circulation model to test the effect of African uplift on Benguela upwelling. In our simulations, uplift in the East African Rift system and in southern and southwestern Africa induces an intensification of coastal low-level winds, which leads to increased oceanic upwelling of cool subsurface waters. We compare the effect of African uplift with the simulated impact of the Central American Seaway closure9, Indonesian Throughflow restriction10 and Antarctic glaciation**11, and find that African uplift has at least an equally strong influence as each of the three other factors. We therefore conclude that African uplift was an important factor in driving the cooling and strengthening of the Benguela Current and coastal upwelling during the late Miocene and Pliocene epochs.

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The increase in global mean temperatures resulting from climate change has wide reaching consequences for the earth's ecosystems and other natural systems. Many studies have been devoted to evaluating the distribution and effects of these changes. We go a step further and evaluate global changes to the heat index, a measure of temperature as perceived by humans. Heat index, which is computed from temperature and relative humidity, is more important than temperature for the health of humans and other animals. Even in cases where the heat index does not reach dangerous levels from a health perspective, it has been shown to be an important factor in worker productivity and thus in economic productivity. We compute heat index from dewpoint temperature and absolute temperature 2 m above ground from the ERA-Interim reanalysis dataset for the years 1979-2013. The data is provided aggregated to daily minima, means and maxima. Furthermore, the data is temporally aggregated to monthly and yearly values and spatially aggregated to the level of countries after being weighted by population density in order to demonstrate its usefulness for the analysis of its impact on human health and productivity. The resulting data deliver insights into the spatiotemporal development of near-ground heat index during the course of the past 3 decades. It is shown that the impact of changing heat index is unevenly distributed through space and time, affecting some areas differently than others. The likelihood of dangerous heat index events has increased globally. Also, heat index climate groups that would formerly be expected closer to the tropics have spread latitudinally to include areas closer to the poles. The data can serve in future studies as a basis for evaluating and understanding the evolution of heat index in the course of climate change, as well as its impact on human health and productivity.

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Multibeam data were measured during R/V SONNE cruise SO202 (INOPEX) along track lines of 6938 NM total length in the North Pacific and Bering Sea during transits and stationary work. Starting from Hokkaido (Japan) data were achieved east of the Kuril-Kamchatka Trench and south of the Aleutian Trench. The track crosses the Bowers Ridge, the continental margin of Alaska and the Umnak Plateau in the Bering Sea. Further data were gained in the North Pacific in the area of the Patton Seamounts, Gibson Seamount, Hess Rise and Shatsky Rise. The multibeam sonar system Simrad EM 120 from Kongsberg was operated using 191 beams and an aperture angle of 90° to 140° due to particular conditions. The refraction correction was achieved utilizing 6 CTD profiles measured during the cruise and one from cruise SO201. The quality of data might be reduced during bad weather periods. The dataset contains raw data that are not processed and thus may contain errors and blunders in depth and position.