DOI: 10.1002/2016MS000854
Scopus记录号: 2-s2.0-85022194381
论文题名: An advanced stochastic weather generator for simulating 2-D high-resolution climate variables
作者: Peleg N ; , Fatichi S ; , Paschalis A ; , Molnar P ; , Burlando P
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2017
卷: 9, 期: 3 起始页码: 1595
结束页码: 1627
语种: 英语
英文关键词: Atmospheric pressure
; Atmospheric temperature
; Calibration
; Climate models
; Meteorological radar
; Precipitation (meteorology)
; Radar stations
; Spatial distribution
; Stochastic models
; Stochastic systems
; Climate simulation
; Climate variables
; Meteorological variables
; Near surface air temperature
; Spatial and temporal resolutions
; Spatial and temporal scale
; Stochastic weather generator
; Weather generator
; Weather satellites
; air temperature
; alpine environment
; atmospheric pressure
; climate modeling
; cloud cover
; data set
; equipment
; instrumentation
; model validation
; numerical model
; precipitation (climatology)
; remote sensing
; satellite data
; solar radiation
; spatial resolution
; two-dimensional modeling
; vapor pressure
英文摘要: A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications. © 2017. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75762
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: Institute of Environmental Engineering, Hydrology and Water Resources Management, ETH Zurich, Zürich, Switzerland; Faculty of Engineering and the Environment, University of Southampton, Southampton, United Kingdom
Recommended Citation:
Peleg N,, Fatichi S,, Paschalis A,et al. An advanced stochastic weather generator for simulating 2-D high-resolution climate variables[J]. Journal of Advances in Modeling Earth Systems,2017-01-01,9(3)