globalchange  > 气候变化事实与影响
DOI: 10.1175/JCLI-D-13-00382.1
Scopus记录号: 2-s2.0-84892535448
论文题名:
Biases in reanalysis snowfall found by comparing the JULES land surface model to globsnow
作者: Hancock S.; Huntley B.; Ellis R.; Baxter R.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期:2
起始页码: 624
结束页码: 632
语种: 英语
Scopus关键词: Accurate prediction ; European Space Agency ; General circulation model ; Land surface modeling ; Land surface models ; Precipitation climatology ; Snow water equivalent ; Snow-cover products ; Data processing ; Gages ; NASA ; Watches ; Snow ; accuracy assessment ; climate modeling ; data set ; error analysis ; general circulation model ; model test ; prediction ; snow accumulation ; snow cover ; weather forecasting
英文摘要: Snow exerts a strong influence on weather and climate. Accurate representation of snow processes within models is needed to ensure accurate predictions. Snow processes are known to be a weakness of land surface models (LSMs), and studies suggest that more complex snow physics is needed to avoid early melt. In this study the European Space Agency (ESA)'s Global Snow Monitoring for Climate Research (GlobSnow) snow water equivalent and NASA's "MOD10C1" snow cover products are used to assess the accuracy of snow processes within the Joint U.K. Land Environment Simulator (JULES). JULES is run "offline" from a general circulation model and so is driven by meteorological reanalysis datasets: "Princeton," Water and Global Change-Global Precipitation Climatology Centre (WATCH-GPCC), and WATCH-Climatic Research Unit (CRU). This reveals that when the model achieves the correct peak accumulation, snow does not melt early. However, generally snow does melt early because peak accumulation is too low. Examination of the meteorological reanalysis data shows that not enough snow falls to achieve observed peak accumulations. Thus, the earlier studies' conclusions may be as a result of weaknesses in the driving data, rather than in model snow processes. These reanalysis products "bias correct" precipitation using observed gauge data with an undercatch correction, overriding the benefit of any other datasets used in their creation. This paper argues that using gauge data to bias-correct reanalysis data is not appropriate for snow-affected regions during winter and can lead to confusion when evaluating model processes. © 2014 American Meteorological Society.
资助项目: NERC, Natural Environment Research Council
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51425
Appears in Collections:气候变化事实与影响

Files in This Item:

There are no files associated with this item.


作者单位: School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne, United Kingdom; NCEO, Reading, United Kingdom; School of Biological and Biomedical Sciences, University of Durham, Durham, United Kingdom; Centre for Ecology and Hydrology, Wallingford, United Kingdom

Recommended Citation:
Hancock S.,Huntley B.,Ellis R.,et al. Biases in reanalysis snowfall found by comparing the JULES land surface model to globsnow[J]. Journal of Climate,2014-01-01,27(2)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Hancock S.]'s Articles
[Huntley B.]'s Articles
[Ellis R.]'s Articles
百度学术
Similar articles in Baidu Scholar
[Hancock S.]'s Articles
[Huntley B.]'s Articles
[Ellis R.]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Hancock S.]‘s Articles
[Huntley B.]‘s Articles
[Ellis R.]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.