Quantifying the reliability of four global datasets for drought monitoring over a semiarid region
Drought is one of the most relevant natural disasters, especially in arid regions such as Iran. One of the requirements to access reliable drought monitoring is long-term and continuous high-resolution precipitation data. Different climatic and global databases are being developed and made available...
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| Veröffentlicht in: | Theoretical and applied climatology 2016, Vol.123 (1-2), p.387-398 |
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| creator | Katiraie-Boroujerdy, Pari-Sima Nasrollahi, Nasrin Hsu, Kuo-lin Sorooshian, Soroosh |
| description | Drought is one of the most relevant natural disasters, especially in arid regions such as Iran. One of the requirements to access reliable drought monitoring is long-term and continuous high-resolution precipitation data. Different climatic and global databases are being developed and made available in real time or near real time by different agencies and centers; however, for this purpose, these databases must be evaluated regionally and in different local climates. In this paper, a near real-time global climate model, a data assimilation system, and two gridded gauge-based datasets over Iran are evaluated. The ground truth data include 50 gauges from the period of 1980 to 2010. Drought analysis was carried out by means of the Standard Precipitation Index (SPI) at 2-, 3-, 6-, and 12-month timescales. Although the results show spatial variations, overall the two gauge-based datasets perform better than the models. In addition, the results are more reliable for the western portion of the Zagros Range and the eastern region of the country. The analysis of the onsets of the 6-month moderate drought with at least 3 months’ persistence indicates that all datasets have a better performance over the western portion of the Zagros Range, but display poor performance over the coast of the Caspian Sea. Base on the results of this study, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset is a preferred alternative for drought analysis in the region when gauge-based datasets are not available. |
| doi_str_mv | 10.1007/s00704-014-1360-3 |
| format | Article |
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One of the requirements to access reliable drought monitoring is long-term and continuous high-resolution precipitation data. Different climatic and global databases are being developed and made available in real time or near real time by different agencies and centers; however, for this purpose, these databases must be evaluated regionally and in different local climates. In this paper, a near real-time global climate model, a data assimilation system, and two gridded gauge-based datasets over Iran are evaluated. The ground truth data include 50 gauges from the period of 1980 to 2010. Drought analysis was carried out by means of the Standard Precipitation Index (SPI) at 2-, 3-, 6-, and 12-month timescales. Although the results show spatial variations, overall the two gauge-based datasets perform better than the models. In addition, the results are more reliable for the western portion of the Zagros Range and the eastern region of the country. The analysis of the onsets of the 6-month moderate drought with at least 3 months’ persistence indicates that all datasets have a better performance over the western portion of the Zagros Range, but display poor performance over the coast of the Caspian Sea. Base on the results of this study, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset is a preferred alternative for drought analysis in the region when gauge-based datasets are not available.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-014-1360-3</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Analysis ; Aquatic Pollution ; Arid regions ; Arid zones ; atmospheric precipitation ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Climate models ; Climatology ; coasts ; Data collection ; Datasets ; disasters ; Drought ; Droughts ; Earth and Environmental Science ; Earth Sciences ; Environmental monitoring ; Forecasts and trends ; Gauges ; Global climate ; Hydrologic data ; monitoring ; Natural disasters ; Original Paper ; Precipitation (Meteorology) ; Reliability ; Semiarid lands ; semiarid zones ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Theoretical and applied climatology, 2016, Vol.123 (1-2), p.387-398</ispartof><rights>Springer-Verlag Wien 2015</rights><rights>COPYRIGHT 2016 Springer</rights><rights>Springer-Verlag Wien 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c489t-d1c4ede903b3236ec9dc8f682d911f7b9b8ec3c5c3118777cdadb054ab05443</citedby><cites>FETCH-LOGICAL-c489t-d1c4ede903b3236ec9dc8f682d911f7b9b8ec3c5c3118777cdadb054ab05443</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-014-1360-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-014-1360-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,4024,27923,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Katiraie-Boroujerdy, Pari-Sima</creatorcontrib><creatorcontrib>Nasrollahi, Nasrin</creatorcontrib><creatorcontrib>Hsu, Kuo-lin</creatorcontrib><creatorcontrib>Sorooshian, Soroosh</creatorcontrib><title>Quantifying the reliability of four global datasets for drought monitoring over a semiarid region</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>Drought is one of the most relevant natural disasters, especially in arid regions such as Iran. One of the requirements to access reliable drought monitoring is long-term and continuous high-resolution precipitation data. Different climatic and global databases are being developed and made available in real time or near real time by different agencies and centers; however, for this purpose, these databases must be evaluated regionally and in different local climates. In this paper, a near real-time global climate model, a data assimilation system, and two gridded gauge-based datasets over Iran are evaluated. The ground truth data include 50 gauges from the period of 1980 to 2010. Drought analysis was carried out by means of the Standard Precipitation Index (SPI) at 2-, 3-, 6-, and 12-month timescales. Although the results show spatial variations, overall the two gauge-based datasets perform better than the models. In addition, the results are more reliable for the western portion of the Zagros Range and the eastern region of the country. The analysis of the onsets of the 6-month moderate drought with at least 3 months’ persistence indicates that all datasets have a better performance over the western portion of the Zagros Range, but display poor performance over the coast of the Caspian Sea. Base on the results of this study, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset is a preferred alternative for drought analysis in the region when gauge-based datasets are not available.</description><subject>Analysis</subject><subject>Aquatic Pollution</subject><subject>Arid regions</subject><subject>Arid zones</subject><subject>atmospheric precipitation</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Climate models</subject><subject>Climatology</subject><subject>coasts</subject><subject>Data collection</subject><subject>Datasets</subject><subject>disasters</subject><subject>Drought</subject><subject>Droughts</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environmental monitoring</subject><subject>Forecasts and trends</subject><subject>Gauges</subject><subject>Global climate</subject><subject>Hydrologic data</subject><subject>monitoring</subject><subject>Natural disasters</subject><subject>Original Paper</subject><subject>Precipitation (Meteorology)</subject><subject>Reliability</subject><subject>Semiarid lands</subject><subject>semiarid zones</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>0177-798X</issn><issn>1434-4483</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kk9rFTEUxYNY8PnqB3BlwI0upk0meclkWUrVQkHqU3AXMvkzTZk3eSYZ8X177zAurAsJ3MDldy7n5gSh15RcUELkZYFCeEMobygTpGHP0IZyxhvOO_YcbQiVspGq-_4CvSzlkRDSCiE3yNzPZqoxnOI04PrgcfZjNH0cYz3hFHBIc8bDmHozYmeqKb4WaGbscpqHh4oPaYo15UWefvqMDS7-EE2ODkYNMU3n6CyYsfhXf-4t2n-4-Xr9qbn7_PH2-uqusbxTtXHUcu-8IqxnLRPeKme7ILrWKUqD7FXfecvszjJKOymldcb1ZMfNUjjbonfr1GNOP2Zfqj7EYv04msmnuWgqxU5JoQQB9O0_6CMsOYE3oGBWJxU42KKLlRrM6HWcQqrZWDgO1rNp8iFC_4rztgPPfAeC908EwFT_qw5mLkXf7r88ZenK2pxKyT7oY44Hk0-aEr3kqdc8NeSplzw1A027aspxeW2f_7L9H9GbVRRM0mbIsehv-5ZQQQiFD9AK9htCY6ur</recordid><startdate>2016</startdate><enddate>2016</enddate><creator>Katiraie-Boroujerdy, Pari-Sima</creator><creator>Nasrollahi, Nasrin</creator><creator>Hsu, Kuo-lin</creator><creator>Sorooshian, Soroosh</creator><general>Springer Vienna</general><general>Springer</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>3V.</scope><scope>7QH</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L6V</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>2016</creationdate><title>Quantifying the reliability of four global datasets for drought monitoring over a semiarid region</title><author>Katiraie-Boroujerdy, Pari-Sima ; 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One of the requirements to access reliable drought monitoring is long-term and continuous high-resolution precipitation data. Different climatic and global databases are being developed and made available in real time or near real time by different agencies and centers; however, for this purpose, these databases must be evaluated regionally and in different local climates. In this paper, a near real-time global climate model, a data assimilation system, and two gridded gauge-based datasets over Iran are evaluated. The ground truth data include 50 gauges from the period of 1980 to 2010. Drought analysis was carried out by means of the Standard Precipitation Index (SPI) at 2-, 3-, 6-, and 12-month timescales. Although the results show spatial variations, overall the two gauge-based datasets perform better than the models. In addition, the results are more reliable for the western portion of the Zagros Range and the eastern region of the country. The analysis of the onsets of the 6-month moderate drought with at least 3 months’ persistence indicates that all datasets have a better performance over the western portion of the Zagros Range, but display poor performance over the coast of the Caspian Sea. Base on the results of this study, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset is a preferred alternative for drought analysis in the region when gauge-based datasets are not available.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00704-014-1360-3</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Analysis Aquatic Pollution Arid regions Arid zones atmospheric precipitation Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Climate models Climatology coasts Data collection Datasets disasters Drought Droughts Earth and Environmental Science Earth Sciences Environmental monitoring Forecasts and trends Gauges Global climate Hydrologic data monitoring Natural disasters Original Paper Precipitation (Meteorology) Reliability Semiarid lands semiarid zones Waste Water Technology Water Management Water Pollution Control |
| title | Quantifying the reliability of four global datasets for drought monitoring over a semiarid region |
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