globalchange  > 气候变化事实与影响
DOI: 10.5194/hess-20-2737-2016
Scopus记录号: 2-s2.0-84978370216
论文题名:
Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach
作者: MacLeod D; , Cloke H; , Pappenberger F; , Weisheimer A
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期:7
起始页码: 2737
结束页码: 2743
语种: 英语
Scopus关键词: Moisture ; Sensitivity analysis ; Soil moisture ; Ensemble approaches ; Global sensitivity analysis ; Hydraulic parameters ; Land surface modeling ; Model uncertainties ; Seasonal forecasting models ; Uncertainty analysis ; estimation method ; forecasting method ; hydraulics ; hydrological modeling ; seasonality ; sensitivity analysis ; soil moisture ; uncertainty analysis
英文摘要: Soil moisture memory is a key component of seasonal predictability. However, uncertainty in current memory estimates is not clear and it is not obvious to what extent these are dependent on model uncertainties. To address this question, we perform a global sensitivity analysis of memory to key hydraulic parameters, using an uncoupled version of the H-TESSEL land surface model. Results show significant dependency of estimates of memory and its uncertainty on these parameters, suggesting that operational seasonal forecasting models using deterministic hydraulic parameter values are likely to display a narrower range of memory than exists in reality. Explicitly incorporating hydraulic parameter uncertainty into models may then give improvements in forecast skill and reliability, as has been shown elsewhere in the literature. Our results also show significant differences with previous estimates of memory uncertainty, warning against placing too much confidence in a single quantification of uncertainty. © 2016 Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78793
Appears in Collections:气候变化事实与影响

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作者单位: Atmospheric Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, United Kingdom; Department of Geography and Environmental Science, University of Reading, Reading, United Kingdom; Department of Meteorology, University of Reading, Reading, United Kingdom; European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom; School of Geographical Sciences, Bristol University, Bristol, United Kingdom; Department of Physics, National Centre for Atmospheric Science (NCAS), University of Oxford, Oxford, United Kingdom

Recommended Citation:
MacLeod D,, Cloke H,, Pappenberger F,et al. Evaluating uncertainty in estimates of soil moisture memory with a reverse ensemble approach[J]. Hydrology and Earth System Sciences,2016-01-01,20(7)
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