DOI: 10.5194/hess-22-989-2018
Scopus记录号: 2-s2.0-85041470843
论文题名: Near-real-time adjusted reanalysis forcing data for hydrology
作者: Berg P ; , Donnelly C ; , Gustafsson D
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2018
卷: 22, 期: 2 起始页码: 989
结束页码: 1000
语种: 英语
Scopus关键词: Forecasting
; Climatological observations
; Forecasting modeling
; Hydrological forecast
; Hydrological forecasting
; Hydrological prediction
; Hydrological simulations
; Meteorological condition
; Meteorological forcing
; Digital storage
; calibration
; data set
; forecasting method
; hydrological modeling
; hydrology
; meteorology
; numerical model
; precipitation (climatology)
; simulation
; temperature effect
; Arctic
; Europe
英文摘要: Extending climatological forcing data to current and real-time forcing is a necessary task for hydrological forecasting. While such data are often readily available nationally, it is harder to find fit-for-purpose global data sets that span long climatological periods through to near-real time. Hydrological simulations are generally sensitive to bias in the meteorological forcing data, especially relative to the data used for the calibration of the model. The lack of high-quality daily resolution data on a global scale has previously been solved by adjusting reanalysis data with global gridded observations. However, existing data sets of this type have been produced for a fixed past time period determined by the main global observational data sets. Long delays between updates of these data sets leaves a data gap between the present day and the end of the data set. Further, hydrological forecasts require initializations of the current state of the snow, soil and lake (and sometimes river) storage. This is normally conceived by forcing the model with observed meteorological conditions for an extended spin-up period, typically at a daily time step, to calculate the initial state. Here, we present and evaluate a method named HydroGFD (Hydrological Global Forcing Data) to combine different data sets in order to produce near-real-time updated hydrological forcing data of temperature and precipitation that are compatible with the products covering the climatological period. HydroGFD resembles the already established WFDEI (WATCH Forcing Data–ERA-Interim) method (Weedon et al., 2014) closely but uses updated climatological observations, and for the near-real time it uses interim products that apply similar methods. This allows HydroGFD to produce updated forcing data including the previous calendar month around the 10th of each month. We present the HydroGFD method and therewith produced data sets, which are evaluated against global data sets, as well as with hydrological simulations with the HYPE (Hydrological Predictions for the Environment) model over Europe and the Arctic regions. We show that HydroGFD performs similarly to WFDEI and that the updated period significantly reduces the bias of the reanalysis data. For real-time updates until the current day, extending HydroGFD with operational meteorological forecasts, a large drift is present in the hydrological simulations due to the bias of the meteorological forecasting model. © 2018 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79405
Appears in Collections: 气候变化事实与影响
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作者单位: Hydrology Research Unit, Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, Norrköping, Sweden
Recommended Citation:
Berg P,, Donnelly C,, Gustafsson D. Near-real-time adjusted reanalysis forcing data for hydrology[J]. Hydrology and Earth System Sciences,2018-01-01,22(2)