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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Chris Funk</dc:contributor>
  <dc:contributor>Pete Peterson</dc:contributor>
  <dc:creator>Laura Harrison</dc:creator>
  <dc:date>2019</dc:date>
  <dc:description>Sparse gauge networks in Sub-Saharan Africa limit our ability to identify changing precipitation extremes with in situ observations. Given the potential for satellite and satellite-gauge precipitation products to help, we investigate how daily gridded gauge and satellite products compare for seven core climate change precipitation indices. According to a new gauge-only product, the Rainfall estimates on a Gridded Network (REGEN), there were notable changes in Sub-Saharan Africa precipitation characteristics between 1950 and 2013 in well-gauged areas. We examine these trends and how these vary for wet, intermediate, and dry areas. For a 31 year period of overlap we compare REGEN data, other gridded products, and three satellite products. Then for 1998-2013 we compare a set of twelve satellite products. Finally, we compare spatial patterns of 1983-2013 trends across all of Sub-Saharan Africa. 
Robust 1950-2013 trends indicate that in well-gauged areas extreme events became wetter, particularly in wet areas. Annual totals decreased due to fewer rain days. Since the 1980s were increases in average precipitation intensity and annual maximum 1-day totals. These trends only represent 15% of Sub-Saharan Africa, however, and only one tenth of the main wet areas. Unfortunately, gauge and satellite products do not provide consensus for wet area trends. A promising result for identifying regional changes is that numerous satellite products do well at interannual variations in precipitation totals and number of rain days- as well as some gauge-only products. Products perform less well for dry spell length and average intensity and worst for annual maximum 1-day totals. TRMM 3B42 and CHIRPS ranked highest for multiple indices. Several products have seemingly unrealistic trends outside of the well-gauged areas that may be due to influence of non-stationary systematic biases.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1088/1748-9326/ab2cae</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>IOP Science</dc:publisher>
  <dc:title>Identifying changing precipitation extremes in Sub-Saharan Africa with gauge and satellite products</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>