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ERA-Interim和NCEP/NCAR再分析数据气温和气压值在中天山山区适用性分析
引用本文:白磊. ERA-Interim和NCEP/NCAR再分析数据气温和气压值在中天山山区适用性分析[J]. 沙漠与绿洲气象(新疆气象), 2013, 7(3): 51-56
作者姓名:白磊
作者单位:中国科学院新疆生态与地理研究所
基金项目:国家973重点研究项目(编号:2010CB951002), 自然科学基金项目(编号:40871027) 和中国科学院知识创新重要方向项目(编号:KZCX2–YW–334).
摘    要:利用在天山山区海拔超过1 500 m的气象站的逐日气温和气压数据与同期经过水平方向和垂直方向插值后ERA-Interim和NCEP/NCAR两套再分析数据进行回归分析,研究再分析数据在天山山区不同季节的适用性,并验证再分析数据偏差与气候区的一致性。结果表明:从整体上,ERA-Interim数据气压和气温的可信度优于NCEP/NCAR数据,但在局部存在差异。两套再分析数据的偏差与气候分区、高程和季节相关。中天山山区再分析数据气温偏差呈现暖偏差,而天山南坡呈现冷偏差。两套再分析数据的气温偏差在高山带呈现暖偏差,在中山带呈现冷偏差。春秋两季气温的偏差小于夏冬两季。气压的偏差在夏季低于其他三季。而偏差可能会导致以再分析数据为驱动的气候模式结果的偏差。

关 键 词:再分析数据  ERA-Interim  NCEP/NCAR  天山山区  气温  气压  偏差
收稿时间:2011-08-18
修稿时间:2012-01-11

Reliability of NCEP/NCAR and ERA-Interim Reanalysis Data on Central Tianshan Mounts
bai lei. Reliability of NCEP/NCAR and ERA-Interim Reanalysis Data on Central Tianshan Mounts[J]. Bimonthly of Xinjiang Meteorology, 2013, 7(3): 51-56
Authors:bai lei
Affiliation:Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences
Abstract:The scarcity of weather stations in Tianshan Mountains has brought the difficulties for studying climate change and its impacts on ecological and hydrological processes. However, reanalysis data offers long-term climate data in Tianshan Mountains, which has been applied in many fields. This paper attempts to analyze reliability of NCEP/NCAR and ERA-Interim reanalysis data on Tianshan Mountains, based on the observed daily data from the stations with more than 1500m above sea level. Regression analysis is applied to analyze reanalysis data's performance in seasonal evolution. Results showed that the ERA-Interim dataset has a better performance than NCEP/NCAR dataset with a few exceptions. These errors are related to climatic zones, elevation and seasonal evolution. Temperature based on reanalysis data highlighted that warm bias occurs in the central Tianshan Mountains, but cold bias takes place in southern slope of Tianshan Mountains. In term of elevation, warm bias happens in Alpine and cold bias does in middle zone of mountains. Seasonally, temperature's bias in spring and autumn is less than that in summer and winter. And pressure's bias in summer is lowest in a year. The bias from temperature and pressure could lead into the bias in Regional Climate Model's result.
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