Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets
Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Prakash, Satya [verfasserIn] Gairola, R. M. [verfasserIn] Mitra, A. K. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Theoretical and applied climatology - Wien [u.a.] : Springer, 1948, 121(2014), 1-2 vom: 02. Aug., Seite 303-317 |
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| Übergeordnetes Werk: |
volume:121 ; year:2014 ; number:1-2 ; day:02 ; month:08 ; pages:303-317 |
| Links: |
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| DOI / URN: |
10.1007/s00704-014-1245-5 |
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| Katalog-ID: |
SPR007335822 |
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| 520 | |a Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. | ||
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| 650 | 4 | |a Precipitation Product |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Reanalysis Product |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Global Monsoon |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Gairola, R. M. |e verfasserin |4 aut | |
| 700 | 1 | |a Mitra, A. K. |e verfasserin |4 aut | |
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10.1007/s00704-014-1245-5 doi (DE-627)SPR007335822 (SPR)s00704-014-1245-5-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Prakash, Satya verfasserin aut Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. Monsoon Region (dpeaa)DE-He213 Global Precipitation Climatology Project (dpeaa)DE-He213 Precipitation Product (dpeaa)DE-He213 Reanalysis Product (dpeaa)DE-He213 Global Monsoon (dpeaa)DE-He213 Gairola, R. M. verfasserin aut Mitra, A. K. verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 121(2014), 1-2 vom: 02. Aug., Seite 303-317 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:121 year:2014 number:1-2 day:02 month:08 pages:303-317 https://dx.doi.org/10.1007/s00704-014-1245-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 121 2014 1-2 02 08 303-317 |
| spelling |
10.1007/s00704-014-1245-5 doi (DE-627)SPR007335822 (SPR)s00704-014-1245-5-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Prakash, Satya verfasserin aut Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. Monsoon Region (dpeaa)DE-He213 Global Precipitation Climatology Project (dpeaa)DE-He213 Precipitation Product (dpeaa)DE-He213 Reanalysis Product (dpeaa)DE-He213 Global Monsoon (dpeaa)DE-He213 Gairola, R. M. verfasserin aut Mitra, A. K. verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 121(2014), 1-2 vom: 02. Aug., Seite 303-317 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:121 year:2014 number:1-2 day:02 month:08 pages:303-317 https://dx.doi.org/10.1007/s00704-014-1245-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 121 2014 1-2 02 08 303-317 |
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10.1007/s00704-014-1245-5 doi (DE-627)SPR007335822 (SPR)s00704-014-1245-5-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Prakash, Satya verfasserin aut Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. Monsoon Region (dpeaa)DE-He213 Global Precipitation Climatology Project (dpeaa)DE-He213 Precipitation Product (dpeaa)DE-He213 Reanalysis Product (dpeaa)DE-He213 Global Monsoon (dpeaa)DE-He213 Gairola, R. M. verfasserin aut Mitra, A. K. verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 121(2014), 1-2 vom: 02. Aug., Seite 303-317 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:121 year:2014 number:1-2 day:02 month:08 pages:303-317 https://dx.doi.org/10.1007/s00704-014-1245-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 121 2014 1-2 02 08 303-317 |
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10.1007/s00704-014-1245-5 doi (DE-627)SPR007335822 (SPR)s00704-014-1245-5-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Prakash, Satya verfasserin aut Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. Monsoon Region (dpeaa)DE-He213 Global Precipitation Climatology Project (dpeaa)DE-He213 Precipitation Product (dpeaa)DE-He213 Reanalysis Product (dpeaa)DE-He213 Global Monsoon (dpeaa)DE-He213 Gairola, R. M. verfasserin aut Mitra, A. K. verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 121(2014), 1-2 vom: 02. Aug., Seite 303-317 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:121 year:2014 number:1-2 day:02 month:08 pages:303-317 https://dx.doi.org/10.1007/s00704-014-1245-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 121 2014 1-2 02 08 303-317 |
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10.1007/s00704-014-1245-5 doi (DE-627)SPR007335822 (SPR)s00704-014-1245-5-e DE-627 ger DE-627 rakwb eng 550 ASE 38.82 bkl Prakash, Satya verfasserin aut Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. Monsoon Region (dpeaa)DE-He213 Global Precipitation Climatology Project (dpeaa)DE-He213 Precipitation Product (dpeaa)DE-He213 Reanalysis Product (dpeaa)DE-He213 Global Monsoon (dpeaa)DE-He213 Gairola, R. M. verfasserin aut Mitra, A. K. verfasserin aut Enthalten in Theoretical and applied climatology Wien [u.a.] : Springer, 1948 121(2014), 1-2 vom: 02. Aug., Seite 303-317 (DE-627)25490968X (DE-600)1463177-5 1434-4483 nnns volume:121 year:2014 number:1-2 day:02 month:08 pages:303-317 https://dx.doi.org/10.1007/s00704-014-1245-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.82 ASE AR 121 2014 1-2 02 08 303-317 |
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Enthalten in Theoretical and applied climatology 121(2014), 1-2 vom: 02. Aug., Seite 303-317 volume:121 year:2014 number:1-2 day:02 month:08 pages:303-317 |
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Enthalten in Theoretical and applied climatology 121(2014), 1-2 vom: 02. Aug., Seite 303-317 volume:121 year:2014 number:1-2 day:02 month:08 pages:303-317 |
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Prakash, Satya @@aut@@ Gairola, R. M. @@aut@@ Mitra, A. K. @@aut@@ |
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In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monsoon Region</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Global Precipitation Climatology Project</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Precipitation Product</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Reanalysis Product</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Global Monsoon</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gairola, R. 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Prakash, Satya |
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Prakash, Satya ddc 550 bkl 38.82 misc Monsoon Region misc Global Precipitation Climatology Project misc Precipitation Product misc Reanalysis Product misc Global Monsoon Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets |
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550 ASE 38.82 bkl Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets Monsoon Region (dpeaa)DE-He213 Global Precipitation Climatology Project (dpeaa)DE-He213 Precipitation Product (dpeaa)DE-He213 Reanalysis Product (dpeaa)DE-He213 Global Monsoon (dpeaa)DE-He213 |
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Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets |
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Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets |
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Theoretical and applied climatology |
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Elektronische Aufsätze |
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Prakash, Satya |
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10.1007/s00704-014-1245-5 |
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comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based gpcc data sets |
| title_auth |
Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets |
| abstract |
Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. |
| abstractGer |
Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. |
| abstract_unstemmed |
Abstract Reliable information of land precipitation along with other atmospheric variables is crucial for monsoon studies, ecosystem modelling, crop modelling and numerous other applications. In this paper, three multisatellite and three reanalysis precipitation products, namely Global Precipitation Climatology Project (GPCP), Climate Prediction Center Mapping of Precipitation (CMAP1 and CMAP2), European Center for Medium Range Weather Forecasts Reanalysis-Interim (ERA-I) and National Center for Environmental Prediction (NCEP1 and NCEP2), are compared with the recent version of gauge-based gridded Global Precipitation Climatology Centre (GPCC) data sets over the global land region. The analysis is done at monthly scale and at 2.5° latitude × 2.5° longitude resolution for a 25-year (1986–2010) period. Large-scale prominent features of precipitation and its variability are qualitatively represented by all the precipitation products. However, the magnitudes considerably differ among themselves. Among the six precipitation products, GPCP performs better than the others when compared to the gridded GPCC data sets. Among the three reanalysis precipitation products, ERA-I is better than NCEP1 and NCEP2 in general. Even though NCEP2 is improved over NCEP1 over the mid-latitudes, NCEP2 has more serious problem over the orographic regions than that of NCEP1. Moreover, all the precipitation estimates exhibit similar kind of interannual variability over the global and tropical land regions. Additionally, the comparison is done for the six global monsoon regions for the regional analysis which shows that all the precipitation estimates exhibit similar kind of interannual variability in the seasonal monsoon precipitation. However, there are some regional differences among these precipitation products in the representation of monsoon variability. |
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Comparison of large-scale global land precipitation from multisatellite and reanalysis products with gauge-based GPCC data sets |
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| score |
7.401473 |