Trends in the Frequency of High Relative Humidity over China: 1979–2012
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In this article, the authors analyzed trends in the frequency of HRH (defined as days with relative humidity $80%) over China from the surface to the mid-troposphere ($400hPa) from 1979 to 2012 using a homogenized humidity dataset for spring (March-May), summer (June-August), autumn (September-November), and winter (December−February).Abstract:
High relative humidity (HRH) is defined as a relative humidity of at least 80%, which is often associated with the occurrence of cloud layers. Thus, the frequency of HRH and its changes in the troposphere may be related to the occurrence frequency of cloud layers and their changes. In this study, trends in the frequency of HRH (defined as days with relative humidity $80%) over China from the surface to the midtroposphere ($400hPa) from 1979 to 2012 were analyzed using a homogenized humidity dataset for spring (March‐May), summer (June‐August), autumn (September‐November), and winter (December‐February). The results for the ground level indicate decreasing trends at most stations in southeastern China in spring and in northern Chinainsummer.Inthelowertroposphere(850and700hPa),moststationsoverChinaexhibitpositivetrends in summer, autumn, and winter. For the midtroposphere (500‐400hPa), increasing trends dominate over China in spring, summer, and autumn. Finally, six reanalysis datasets, the NCEP‐NCAR, NCEP‐DOE, CFSR, ERA-Interim, MERRA, and JRA-55 datasets, were compared with the observed increasing trends in HRH frequency in the low-to-middle troposphere. Similar increasing trends in HRH frequency in the reanalysis datasets and the homogenized humidity data are observed in certain seasons and for certain regions. These results are consistent with the increasing low-to-middle cloud amounts in recent decades.read more
Citations
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References
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TL;DR: The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA's Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA's Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses as mentioned in this paper.
Journal ArticleDOI
The NCEP Climate Forecast System Reanalysis
Suranjana Saha,Shrinivas Moorthi,Hua-Lu Pan,Xingren Wu,Jiande Wang,Sudhir Nadiga,Patrick Tripp,Robert Kistler,John S. Woollen,David Behringer,Haixia Liu,Diane Stokes,Robert Grumbine,George Gayno,Jun Wang,Yu-Tai Hou,Hui-ya Chuang,Hann-Ming Henry Juang,Joe Sela,Mark Iredell,Russ Treadon,Daryl T. Kleist,Paul van Delst,Dennis Keyser,John Derber,Michael Ek,Jesse Meng,Helin Wei,Rongqian Yang,Stephen J. Lord,Huug van den Dool,Arun Kumar,Wanqiu Wang,Craig S. Long,Muthuvel Chelliah,Yan Xue,Boyin Huang,Jae-Kyung E. Schemm,Wesley Ebisuzaki,Roger Lin,Pingping Xie,Mingyue Chen,Shuntai Zhou,Wayne Higgins,Cheng-Zhi Zou,Quanhua Liu,Yong Chen,Yong Han,Lidia Cucurull,Richard W. Reynolds,Glenn Rutledge,Mitch Goldberg +51 more
TL;DR: The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010 as mentioned in this paper, which was designed and executed as a global, high-resolution coupled atmosphere-ocean-land surface-sea ice system to provide the best estimate of the state of these coupled domains over this period.
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