globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jhydrol.2019.02.010
WOS记录号: WOS:000462692100053
论文题名:
Exploring stochastic climate uncertainty in space and time using a gridded hourly weather generator
作者: Peleg, Nadav; Molnar, Peter; Burlando, Paolo; Fatichi, Simone
通讯作者: Peleg, Nadav
刊名: JOURNAL OF HYDROLOGY
ISSN: 0022-1694
EISSN: 1879-2707
出版年: 2019
卷: 571, 页码:627-641
语种: 英语
英文关键词: Weather generator ; Stochastic downscaling ; Climate change ; Internal climate variability ; Climate uncertainty ; High-resolution rainfall model
WOS关键词: DOWNSCALING TECHNIQUES ; INTERNAL VARIABILITY ; BASIN HYDROLOGY ; BIAS CORRECTION ; RAINFALL MODEL ; VITAL DETAILS ; PRECIPITATION ; SIMULATION ; IMPACTS ; WATER
WOS学科分类: Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向: Engineering ; Geology ; Water Resources
英文摘要:

Exploring the effects of climate change on the hydrological response at the local scale requires climate data at high spatial and temporal resolutions. This is best achieved by generating downscaled ensembles of future climate variables derived from climate models. For this purpose we present a methodology to re-parameterize the AWE-GEN-2d model (Advanced WEather GENerator for a two-dimensional grid). The model simulates key meteorological variables needed by hydrological models and is particularly suitable to explore the effects of stochastic (natural) climatic uncertainty, which is fundamental for hydrological applications, especially at sub-kilometer and hourly scales. Factors of change for different climate statistics are calculated from climate model simulations of present and future climates and subsequently applied to the statistics derived from observations to re-parameterize AWE-GEN-2d. The model abilities in generating an ensemble of future climate variables for the transient period 2020-2089 is presented with examples of precipitation and near-surface air temperature fields from hourly to multi-annual scales for a small mountainous region in the Swiss Alps. The stochastic uncertainty is examined for present and future periods and for spatial scales from the RCM scale (12-km, daily) to 2-km demonstrating the potential use of AWE-GEN-2d outputs. At the RCM scale, model results yield a small increase in annual precipitation (4%) which is within the stochastic uncertainty range for present and future periods (7%). At the fine scale of 2-km, the increase in annual precipitation can exceed the stochastic uncertainty, but for less than 10% of the domain area. On the contrary, changes in annual near-surface air temperature exceed stochastic uncertainty both at the RCM and finer scales. Stochastic climate uncertainty was concluded to be very similar when comparing present and future periods and 12-km and 2-km scales. The benefits of using AWE-GEN-2d in hydrological climate change impact assessments are finally discussed.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/133554
Appears in Collections:气候变化事实与影响

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作者单位: Swiss Fed Inst Technol, Inst Environm Engn Hydrol & Water Resources Manag, Zurich, Switzerland

Recommended Citation:
Peleg, Nadav,Molnar, Peter,Burlando, Paolo,et al. Exploring stochastic climate uncertainty in space and time using a gridded hourly weather generator[J]. JOURNAL OF HYDROLOGY,2019-01-01,571:627-641
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