DOI: 10.1002/2017JD027423
Scopus记录号: 2-s2.0-85041724811
论文题名: Estimation of Systematic Errors in the GFS Using Analysis Increments
作者: Bhargava K. ; Kalnay E. ; Carton J.A. ; Yang F.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期: 3 起始页码: 1626
结束页码: 1637
语种: 英语
英文关键词: bias correction
; data assimilation
; model bias
; online correction
; systematic errors
; weather forecasting
英文摘要: We estimate the effect of model deficiencies in the Global Forecast System that lead to systematic forecast errors, as a first step toward correcting them online (i.e., within the model) as in Danforth & Kalnay (2008a, 2008b). Since the analysis increments represent the corrections that new observations make on the 6 h forecast in the analysis cycle, we estimate the model bias corrections from the time average of the analysis increments divided by 6 h, assuming that initial model errors grow linearly and first ignoring the impact of observation bias. During 2012–2016, seasonal means of the 6 h model bias are generally robust despite changes in model resolution and data assimilation systems, and their broad continental scales explain their insensitivity to model resolution. The daily bias dominates the submonthly analysis increments and consists primarily of diurnal and semidiurnal components, also requiring a low dimensional correction. Analysis increments in 2015 and 2016 are reduced over oceans, which we attribute to improvements in the specification of the sea surface temperatures. These results provide support for future efforts to make online correction of the mean, seasonal, and diurnal and semidiurnal model biases of Global Forecast System to reduce both systematic and random errors, as suggested by Danforth & Kalnay (2008a, 2008b). It also raises the possibility that analysis increments could be used to provide guidance in testing new physical parameterizations. ©2018. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/114469
Appears in Collections: 气候减缓与适应
There are no files associated with this item.
作者单位: Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, United States; NOAA/National Weather Service National Centers for Environmental Prediction, College Park, MD, United States
Recommended Citation:
Bhargava K.,Kalnay E.,Carton J.A.,et al. Estimation of Systematic Errors in the GFS Using Analysis Increments[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(3)