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Evaluation of satellite-based precipitation estimation over Iran
Precipitation in semi-arid countries such as Iran is one of the most important elements for all aspects of human life. In areas with sparse ground-based precipitation observation networks, the reliable high spatial and temporal resolution of satellite-based precipitation estimation might be the best...
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Published in: | Journal of arid environments 2013-10, Vol.97, p.205-219 |
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description | Precipitation in semi-arid countries such as Iran is one of the most important elements for all aspects of human life. In areas with sparse ground-based precipitation observation networks, the reliable high spatial and temporal resolution of satellite-based precipitation estimation might be the best source for meteorological and hydrological studies. In the present study, four different satellite rainfall estimates (CMORPH, PERSIANN, adjusted PERSIANN, and TRMM-3B42 V6) are evaluated using a relatively dense Islamic Republic of Iran's Meteorological Organization (IRIMO) rain-gauge network as reference. These evaluations were done at daily and monthly time scales with a spatial resolution of 0.25° × 0.25° latitude/longitude. The topography of Iran is complicated and includes different, very diverse climates. For example, there is an extremely wet (low-elevation) Caspian Sea coastal region in the north, an arid desert in the center, and high mountainous areas in the west and north. Different rainfall regimes vary between these extremes. In order to conduct an objective intercomparison of the various satellite products, the study was designed to minimize the level of uncertainties in the evaluation process. To reduce gauge uncertainties, only the 32 pixels, which include at least five rain gauges, are considered. Evaluation results vary by different areas. The satellite products had a Probability of Detection (POD) greater than 40% in the southern part of the country and the regions of the Zagros Mountains. However, all satellite products exhibited poor performance over the Caspian Sea coastal region, where they underestimated precipitation in this relatively wet and moderate climate region. Seasonal analysis shows that spring precipitations are detected more accurately than winter precipitation, especially for the mountainous areas all over the country. Comparisons of different satellite products show that adj-PERSIANN and TRMM-3B42 V6 have better performance, and CMORPH has poor estimation, especially over the Zagros Mountains. The comparison between PERSIANN and adj-PERSIANN shows that the bias adjustment improved the POD, which is a daily scale statistic.
•This study presents the effectiveness of Satellite precipitation products in arid regions.•Real time and adjusted satellite precipitation products are compared over a diverse climate.•The validation study is performed using a unique and relatively dense gauge data over Iran. |
doi_str_mv | 10.1016/j.jaridenv.2013.05.013 |
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•This study presents the effectiveness of Satellite precipitation products in arid regions.•Real time and adjusted satellite precipitation products are compared over a diverse climate.•The validation study is performed using a unique and relatively dense gauge data over Iran.</description><subject>Animal and plant ecology</subject><subject>Animal, plant and microbial ecology</subject><subject>Biological and medical sciences</subject><subject>Caspian Sea</subject><subject>Coastal</subject><subject>Evaluation</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gages</subject><subject>General aspects. Techniques</subject><subject>Mountains</subject><subject>Networks</subject><subject>Precipitation</subject><subject>Precipitation (meteorological)</subject><subject>Remote sensing</subject><subject>Satellite precipitation</subject><subject>Satellites</subject><subject>Synecology</subject><subject>Teledetection and vegetation maps</subject><subject>Terrestrial ecosystems</subject><issn>0140-1963</issn><issn>1095-922X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqNkE1LxDAQhoMouK7-BelF8NKaTJp-3FaWVRcWvCh4C2kyhZRuW5NuwX9vlq5e9fRenpl35iHkltGEUZY9NEmjnDXYTQlQxhMqkhBnZMFoKeIS4OOcLChLaczKjF-SK-8bShkTgi_IajOp9qBG23dRX0dejdi2dsS4Uh5NNDjUdrDjDKAf7f7ETuiirVPdNbmoVevx5pRL8v60eVu_xLvX5-36cRfrlBZjjLnOKlEZCimriyIVnJcaaM5qZQqsaqM0K8s8BS4gY2Ay4GVVZAYECDQ05UtyP-8dXP95CJfIvfU6HKs67A9esiwF4HmRlv9AuaDAC54HNJtR7XrvHdZycOFF9yUZlUe7spE_duXRrqRChgiDd6cO5bVq62BCW_87DXkBIELFkqxmDoObyaKTXlvsNBob1I7S9Pavqm-5aZK3</recordid><startdate>20131001</startdate><enddate>20131001</enddate><creator>Katiraie-Boroujerdy, Pari-Sima</creator><creator>Nasrollahi, Nasrin</creator><creator>Hsu, Kuo-lin</creator><creator>Sorooshian, Soroosh</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SN</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20131001</creationdate><title>Evaluation of satellite-based precipitation estimation over Iran</title><author>Katiraie-Boroujerdy, Pari-Sima ; Nasrollahi, Nasrin ; Hsu, Kuo-lin ; Sorooshian, Soroosh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-e7c6b5bd0241f8845339c2071fad8ebfdac199742352612d6239b86d2525ed043</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Animal and plant ecology</topic><topic>Animal, plant and microbial ecology</topic><topic>Biological and medical sciences</topic><topic>Caspian Sea</topic><topic>Coastal</topic><topic>Evaluation</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gages</topic><topic>General aspects. Techniques</topic><topic>Mountains</topic><topic>Networks</topic><topic>Precipitation</topic><topic>Precipitation (meteorological)</topic><topic>Remote sensing</topic><topic>Satellite precipitation</topic><topic>Satellites</topic><topic>Synecology</topic><topic>Teledetection and vegetation maps</topic><topic>Terrestrial ecosystems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Katiraie-Boroujerdy, Pari-Sima</creatorcontrib><creatorcontrib>Nasrollahi, Nasrin</creatorcontrib><creatorcontrib>Hsu, Kuo-lin</creatorcontrib><creatorcontrib>Sorooshian, Soroosh</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Journal of arid environments</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Katiraie-Boroujerdy, Pari-Sima</au><au>Nasrollahi, Nasrin</au><au>Hsu, Kuo-lin</au><au>Sorooshian, Soroosh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of satellite-based precipitation estimation over Iran</atitle><jtitle>Journal of arid environments</jtitle><date>2013-10-01</date><risdate>2013</risdate><volume>97</volume><spage>205</spage><epage>219</epage><pages>205-219</pages><issn>0140-1963</issn><eissn>1095-922X</eissn><coden>JAENDR</coden><abstract>Precipitation in semi-arid countries such as Iran is one of the most important elements for all aspects of human life. In areas with sparse ground-based precipitation observation networks, the reliable high spatial and temporal resolution of satellite-based precipitation estimation might be the best source for meteorological and hydrological studies. In the present study, four different satellite rainfall estimates (CMORPH, PERSIANN, adjusted PERSIANN, and TRMM-3B42 V6) are evaluated using a relatively dense Islamic Republic of Iran's Meteorological Organization (IRIMO) rain-gauge network as reference. These evaluations were done at daily and monthly time scales with a spatial resolution of 0.25° × 0.25° latitude/longitude. The topography of Iran is complicated and includes different, very diverse climates. For example, there is an extremely wet (low-elevation) Caspian Sea coastal region in the north, an arid desert in the center, and high mountainous areas in the west and north. Different rainfall regimes vary between these extremes. In order to conduct an objective intercomparison of the various satellite products, the study was designed to minimize the level of uncertainties in the evaluation process. To reduce gauge uncertainties, only the 32 pixels, which include at least five rain gauges, are considered. Evaluation results vary by different areas. The satellite products had a Probability of Detection (POD) greater than 40% in the southern part of the country and the regions of the Zagros Mountains. However, all satellite products exhibited poor performance over the Caspian Sea coastal region, where they underestimated precipitation in this relatively wet and moderate climate region. Seasonal analysis shows that spring precipitations are detected more accurately than winter precipitation, especially for the mountainous areas all over the country. Comparisons of different satellite products show that adj-PERSIANN and TRMM-3B42 V6 have better performance, and CMORPH has poor estimation, especially over the Zagros Mountains. The comparison between PERSIANN and adj-PERSIANN shows that the bias adjustment improved the POD, which is a daily scale statistic.
•This study presents the effectiveness of Satellite precipitation products in arid regions.•Real time and adjusted satellite precipitation products are compared over a diverse climate.•The validation study is performed using a unique and relatively dense gauge data over Iran.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.jaridenv.2013.05.013</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animal and plant ecology Animal, plant and microbial ecology Biological and medical sciences Caspian Sea Coastal Evaluation Fundamental and applied biological sciences. Psychology Gages General aspects. Techniques Mountains Networks Precipitation Precipitation (meteorological) Remote sensing Satellite precipitation Satellites Synecology Teledetection and vegetation maps Terrestrial ecosystems |
title | Evaluation of satellite-based precipitation estimation over Iran |
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