DOI: 10.1016/j.atmosres.2018.01.016
Scopus记录号: 2-s2.0-85044259477
论文题名: Estimating the snowfall limit in alpine and pre-alpine valleys: A local evaluation of operational approaches
作者: Fehlmann M. ; Gascón E. ; Rohrer M. ; Schwarb M. ; Stoffel M.
刊名: Atmospheric Research
ISSN: 1698095
出版年: 2018
卷: 204 起始页码: 136
结束页码: 148
语种: 英语
英文关键词: Bright band
; Early warning
; Melting layer
; Micro rain radar
; Precipitation type
; Snowfall limit
Scopus关键词: Catchments
; Forecasting
; Landforms
; Precipitation (meteorology)
; Radar
; Radar measurement
; Rain
; Runoff
; Snow
; Uncertainty analysis
; Bright band
; Early warning
; European centre for medium-range weather forecasts
; Integrated forecasting systems
; Melting layers
; Numerical weather prediction models
; Rain radar
; Temporal and spatial scale
; Weather forecasting
英文摘要: The snowfall limit has important implications for different hazardous processes associated with prolonged or heavy precipitation such as flash floods, rain-on-snow events and freezing precipitation. To increase preparedness and to reduce risk in such situations, early warning systems are frequently used to monitor and predict precipitation events at different temporal and spatial scales. However, in alpine and pre-alpine valleys, the estimation of the snowfall limit remains rather challenging. In this study, we characterize uncertainties related to snowfall limit for different lead times based on local measurements of a vertically pointing micro rain radar (MRR) and a disdrometer in the Zulg valley, Switzerland. Regarding the monitoring, we show that the interpolation of surface temperatures tends to overestimate the altitude of the snowfall limit and can thus lead to highly uncertain estimates of liquid precipitation in the catchment. This bias is much smaller in the Integrated Nowcasting through Comprehensive Analysis (INCA) system, which integrates surface station and remotely sensed data as well as outputs of a numerical weather prediction model. To reduce systematic error, we perform a bias correction based on local MRR measurements and thereby demonstrate the added value of such measurements for the estimation of liquid precipitation in the catchment. Regarding the nowcasting, we show that the INCA system provides good estimates up to 6 h ahead and is thus considered promising for operational hydrological applications. Finally, we explore the medium-range forecasting of precipitation type, especially with respect to rain-on-snow events. We show for a selected case study that the probability for a certain precipitation type in an ensemble-based forecast is more persistent than the respective type in the high-resolution forecast (HRES) of the European Centre for Medium Range Weather Forecasts Integrated Forecasting System (ECMWF IFS). In this case study, the ensemble-based forecast could be used to anticipate such an event up to 7–8 days ahead, whereas the use of the HRES is limited to a lead time of 4–5 days. For the different lead times investigated, we point out possibilities of considering uncertainties in snowfall limit and precipitation type estimates so as to increase preparedness to risk situations. © 2018 The Authors Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/108935
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Climate Change Impacts and Risks in the Anthropocene (C-CIA), University of Geneva, Institute for Environmental Sciences, Boulevard Carl-Vogt 66, Geneva, 1205, Switzerland; Forecast Department, European Centre for Medium-Range Weather Forecasts (ECMWF), Shinfield Park, Reading, RG2 9AX, United Kingdom; Meteodat GmbH, Technoparkstrasse 1, Zurich, 8005, Switzerland; Department of Earth Sciences, University of Geneva, Rue des Maraîchers 13, Geneva, 1205, Switzerland; Department F.-A. Forel for Environmental and Aquatic Sciences, University of Geneva, Boulevard Carl-Vogt 66, Geneva, 1205, Switzerland
Recommended Citation:
Fehlmann M.,Gascón E.,Rohrer M.,et al. Estimating the snowfall limit in alpine and pre-alpine valleys: A local evaluation of operational approaches[J]. Atmospheric Research,2018-01-01,204