globalchange  > 影响、适应和脆弱性
DOI: 10.1002/jgrd.50450
论文题名:
A single-column model ensemble approach applied to the TWP-ICE experiment
作者: Davies L.; Jakob C.; Cheung K.; Del Genio A.; Hill A.; Hume T.; Keane R.J.; Komori T.; Larson V.E.; Lin Y.; Liu X.; Nielsen B.J.; Petch J.; Plant R.S.; Singh M.S.; Shi X.; Song X.; Wang W.; Whitall M.A.; Wolf A.; Xie S.; Zhang G.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期:12
起始页码: 6544
结束页码: 6563
语种: 英语
英文关键词: Ensemble ; Single Column Model ; TWP-ICE
Scopus关键词: Equipment testing ; Estimation ; Experiments ; Ice ; Moisture ; Precipitation (meteorology) ; Turbulent flow ; Uncertainty analysis ; Weather forecasting ; Cloud resolving model ; Ensemble ; Ensemble simulation ; Numerical weather prediction ; Parameterization schemes ; Single-column model ; Twp ices ; Vertical structures ; Computer simulation ; climate modeling ; data set ; ensemble forecasting ; evaporation ; experimental study ; numerical model ; parameterization ; prediction ; sensitivity analysis
英文摘要: Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only. Key Points An ensemble of large-scale atmospheric states is derived for TWP-ICE. Single Column Models and Cloud-Resolving Models successfully simulate ensemble. Comparison with best estimate simulations further elucidate model behavior. © 2013. American Geophysical Union. All Rights Reserved.
资助项目: AGS-0968640
Citation statistics:
被引频次[WOS]:29   [查看WOS记录]     [查看WOS中相关记录]
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63609
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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作者单位: School of Earth Sciences, University of Melbourne, Melbourne, VIC 3010, Australia; ARC Centre of Excellence for Climate System Science, Monash University, Melbourne, VIC, Australia; Bureau of Meteorology, Melbourne, VIC, Australia; NASA Goddard Institute for Space Studies, New York, NY, United States; Met Office, Exeter, United Kingdom; Centre for Australian Weather and Climate Research Bureau of Meteorology, Melbourne, VIC, Australia; Meteorologisches Institut, Ludwig-Maximilians-Universitat, Munich, Munchen, Germany; Japan Meteorological Agency, Tokyo, Japan; University of Wisconsin-Milwaukee, Milwaukee, WI, United States; University Corporation for Atmospheric Research, Boulder, CO, United States; NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States; Pacific Northwestern National Laboratory, Richland, WA, United States; Department of Meteorology, University of Reading, Reading, United Kingdom; Massachusetts Institute of Technology Massachusetts, Cambridge, United States; University of California, San Diego, CA, United States; IMSG-NOAA National Centers for Environmental Prediction, College Park, MD, United States; Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, United States; Lawrence Livermore National Laboratory, Livermore, CA, United States

Recommended Citation:
Davies L.,Jakob C.,Cheung K.,et al. A single-column model ensemble approach applied to the TWP-ICE experiment[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(12)
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