<?xml version="1.0"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" 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:title>Reliability of SM2RAIN precipitation datasets in comparison to gauge observations and hydrological modelling over arid regions</dc:title>
  <dc:creator>/Satg&#xE9;, Fr&#xE9;d&#xE9;ric</dc:creator>
  <dc:creator>Hussain, Y.</dc:creator>
  <dc:creator>Molina-Carpio, J.</dc:creator>
  <dc:creator>Pillco, R.</dc:creator>
  <dc:creator>Laugner, C.</dc:creator>
  <dc:creator>Akhter, G.</dc:creator>
  <dc:creator>/Bonnet, Marie-Paule</dc:creator>
  <dc:subject>arid region</dc:subject>
  <dc:subject>assessment</dc:subject>
  <dc:subject>gauges</dc:subject>
  <dc:subject>hydrological modelling</dc:subject>
  <dc:subject>satellite</dc:subject>
  <dc:subject>precipitation</dc:subject>
  <dc:subject>SM2RAIN</dc:subject>
  <dc:description>Numerous satellite-based precipitation datasets have been successively made available. Their precipitation estimates rely on clouds properties derived from microwave and thermal sensors in a so-named 'top-down' approach. Recently, a 'bottom-up' approach to infer precipitation from soil moisture (SM) estimates has resulted in the release of two new precipitation datasets (P-datasets). One uses satellite-based SM estimates from the European Spatial Agency (ESA) Climate Change Initiative (CCI) (SM2RAIN-CCI) while the other uses satellite-based SM from European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Advanced SCATterometer (ASCAT) (SM2RAIN-ASCAT). This study assesses SM2RAIN-ASCAT and -CCI reliability over two arid regions: Bolivian and Peruvian Altiplano and Pakistan (South Asia) using (a) direct comparisons with rain gauges and (b) testing the sensitivity of streamflow modelling to the P-datasets. Selecting two different regions and different indicators helps to assess whether the P-dataset reliability varies depending on the assessment method and location. For comparison purposes, the most reliable P-datasets from the literature are also considered (IMERG-E v.6, IMERG-L v.6, IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2). Compared to rain gauge observations and based on the modified Kling-Gupta Efficiency (KGE) values, the SM2RAIN-ASCAT and -CCI are more accurate in the Altiplano than in Pakistan. This difference is explained by a more favourable physical context for satellite-based SM estimates in the Altiplano. Over the Altiplano and despite an overall positive bias, SM2RAIN-ASCAT describes rain gauges temporal dynamics as well as IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2 and provides streamflow simulations very close to those obtained when using IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2 as forcing data.</dc:description>
  <dc:date>2021</dc:date>
  <dc:type>text</dc:type>
  <dc:identifier>https://www.documentation.ird.fr/hor/fdi:010079415</dc:identifier>
  <dc:identifier>fdi:010079415</dc:identifier>
  <dc:identifier>Satg&#xE9; Fr&#xE9;d&#xE9;ric, Hussain Y., Molina-Carpio J., Pillco R., Laugner C., Akhter G., Bonnet Marie-Paule. Reliability of SM2RAIN precipitation datasets in comparison to gauge observations and hydrological modelling over arid regions. 2021, 41 (suppl. 1), E517-E536</dc:identifier>
  <dc:language>EN</dc:language>
  <dc:coverage>ZONE ARIDE</dc:coverage>
  <dc:coverage>BOLIVIE</dc:coverage>
  <dc:coverage>PEROU</dc:coverage>
  <dc:coverage>PAKISTAN</dc:coverage>
</oai_dc:dc>
