Comparison of multiple datasets with gridded precipitation observations over the Tibetan Plateau

Verfasser / Beitragende:
[Qinglong You, Jinzhong Min, Wei Zhang, Nick Pepin, Shichang Kang]
Ort, Verlag, Jahr:
2015
Enthalten in:
Climate Dynamics, 45/3-4(2015-08-01), 791-806
Format:
Artikel (online)
ID: 60547107X
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024 7 0 |a 10.1007/s00382-014-2310-6  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00382-014-2310-6 
245 0 0 |a Comparison of multiple datasets with gridded precipitation observations over the Tibetan Plateau  |h [Elektronische Daten]  |c [Qinglong You, Jinzhong Min, Wei Zhang, Nick Pepin, Shichang Kang] 
520 3 |a Precipitation is a critical component of the water balance, and hence its variability is critical for cryospheric and climate change in the Tibetan Plateau (TP). Mean annual and seasonal precipitation totals are compared between gridded observations interpolated to a high resolution (0.5°×0.5°) and multiple reanalysis type-datasets during 1979-2001. The latter include two NCEP reanalyses (NCEP1 and NCEP2), two European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses (ERA-40 and ERA-Interim), three modern reanalyses [the twentieth century reanalysis (20century), MERRA and CFSR] and three merged analysis datasets (CMAP1, CMAP2 and GPCP). Observations show an increase in mean precipitation from the northwestern to the southeastern (SE) regions of the TP which are divided by an isohyet of 400mm, and overall trends during the studied period are positive. Compared with observations, most of the datasets (NCEP1, NCEP2, CMAP1, CMAP2, ERA-Interim, ERA-40, GPCP, 20century, MERRA and CFSR) can both broadly capture the spatial distributions and identify temporal patterns and variabilities of mean precipitation. However, most multi-datasets overestimate precipitation especially in the SE where summer convection is dominant. There remain substantial disagreements and large discrepancies in precipitation trends due to differences in assimilation systems between datasets. Taylor diagrams are used to show the correlation coefficients, standard deviation, and root-mean-square difference of precipitation totals between interpolated observations and assimilated values on an annual and seasonal basis. Merged analysis data (CMAP1 and CMAP2) agree with observations more closely than reanalyses. Thus not all datasets are equally biased and choice of dataset is important. 
540 |a Springer-Verlag Berlin Heidelberg, 2014 
690 7 |a Precipitation  |2 nationallicence 
690 7 |a Multi-datasets  |2 nationallicence 
690 7 |a Observation  |2 nationallicence 
690 7 |a Tibetan Plateau  |2 nationallicence 
700 1 |a You  |D Qinglong  |u Earth System Modelling Center (ESMC), Nanjing International Academy of Meteorological Sciences (NIAMS), Key Laboratory of Meteorological Disaster, Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China  |4 aut 
700 1 |a Min  |D Jinzhong  |u Earth System Modelling Center (ESMC), Nanjing International Academy of Meteorological Sciences (NIAMS), Key Laboratory of Meteorological Disaster, Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China  |4 aut 
700 1 |a Zhang  |D Wei  |u Earth System Modelling Center (ESMC), Nanjing International Academy of Meteorological Sciences (NIAMS), Key Laboratory of Meteorological Disaster, Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China  |4 aut 
700 1 |a Pepin  |D Nick  |u Department of Geography, University of Portsmouth, Portsmouth, UK  |4 aut 
700 1 |a Kang  |D Shichang  |u State Key Laboratory of Cryospheric Science, Chinese Academy of Sciences, 730000, Lanzhou, China  |4 aut 
773 0 |t Climate Dynamics  |d Springer Berlin Heidelberg  |g 45/3-4(2015-08-01), 791-806  |x 0930-7575  |q 45:3-4<791  |1 2015  |2 45  |o 382 
856 4 0 |u https://doi.org/10.1007/s00382-014-2310-6  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00382-014-2310-6  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a You  |D Qinglong  |u Earth System Modelling Center (ESMC), Nanjing International Academy of Meteorological Sciences (NIAMS), Key Laboratory of Meteorological Disaster, Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Min  |D Jinzhong  |u Earth System Modelling Center (ESMC), Nanjing International Academy of Meteorological Sciences (NIAMS), Key Laboratory of Meteorological Disaster, Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Zhang  |D Wei  |u Earth System Modelling Center (ESMC), Nanjing International Academy of Meteorological Sciences (NIAMS), Key Laboratory of Meteorological Disaster, Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044, Nanjing, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Pepin  |D Nick  |u Department of Geography, University of Portsmouth, Portsmouth, UK  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Kang  |D Shichang  |u State Key Laboratory of Cryospheric Science, Chinese Academy of Sciences, 730000, Lanzhou, China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Climate Dynamics  |d Springer Berlin Heidelberg  |g 45/3-4(2015-08-01), 791-806  |x 0930-7575  |q 45:3-4<791  |1 2015  |2 45  |o 382