771 resultados para Open Science Data Cloud


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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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Historical, i.e. pre-1957, upper-air data are a valuable source of information on the state of the atmosphere, in some parts of the World back to the early 20th century. However, to date reanalyses have only partially made use of these data, and only of observations made after 1948. Even for the period between 1948 (the starting year of the NCEP/NCAR reanalysis) and the International Geophysical Year in 1957 (the starting year of the ERA-40 reanalysis), when the global upper-air coverage reached more or less its current status, many observations have not been digitised until now. The Comprehensive Historical Upper-Air Network (CHUAN) already compiled a large collection of pre-1957 upper-air data. In the framework of the European project ERA-CLIM, significant amounts of additional upper-air data have been catalogued (> 1.3 mio station days), imaged (> 200,000 images) and digitised (> 700,000 station days) in order to prepare a new input dataset for upcoming reanalyses. The records cover large parts of the globe, focussing on so far less well covered regions such as the Tropics, the polar regions and the Oceans, and on very early upper-air data from Europe and the US. The total number of digitised/inventoried records is 61/101 for moving upper-air data, i.e. data from ships etc., and 735/1,783 for fixed upper-air stations. Here, we give a detailed description of the resulting dataset including the metadata and the quality checking procedures applied. The data will be included in the next version of CHUAN.

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The presented database contains time-referenced sea ice draft values from upward looking sonar (ULS) measurements in the Weddell Sea, Antarctica. The sea ice draft data can be used to infer the thickness of the ice. They were collected during the period 1990-2008. In total, the database includes measurements from 13 locations in the Weddell Sea and was generated from more than 3.7 million measurements of sea ice draft. The files contain uncorrected raw drafts, corrected drafts and the basic parameters measured by the ULS. The measurement principle, the data processing procedure and the quality control are described in detail. To account for the unknown speed of sound in the water column above the ULS, two correction methods were applied to the draft data. The first method is based on defining a reference level from the identification of open water leads. The second method uses a model of sound speed in the oceanic mixed layer and is applied to ice draft in austral winter. Both methods are discussed and their accuracy is estimated. Finally, selected results of the processing are presented.