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A new statistical precipitation downscaling method with Bayesian model averaging: a case study in China
- 作者:Xianliang Zhang ; Xiaodong Yan
- 关键词:Statistical downscaling ; Bayesian model averaging ; Monthly precipitation ; Multiple linear regression method
- 刊名:Climate Dynamics
- 出版年:2015
- 出版时间:November 2015
- 年:2015
- 卷:45
- 期:9-10
- 页码:2541-2555
- 全文大小:10,029 KB
- 参考文献:Acharya N, Chattopadhyay S, Mohanty UC, Dash SK, Sahoo LN (2013) On the bias correction of general circulation model output for Indian summer monsoon. Meteorol Appl 20:349–356CrossRef
Akaike H (1974) A new look at the statistical model identification. IEEE Trans Automat Contr AC-19:716–723CrossRef Bates BC, Charles SP, Hughes JP (1998) Stochastic downscaling of numerical climate model simulations. Environ Model Softw 13:325–331CrossRef Bayes T (1763) An essay towards solving a problem in the doctrine of chances. Philos Trans R Soc 53:370–418 Bordoy R, Burlando P (2014) Stochastic downscaling of climate model precipitation outputs in orographically complex regions: 2. Downscaling methodology. Water Resour Res 50:562–579CrossRef Browne MW (2000) Cross-validation methods. J Math Psychol 44:108–132CrossRef Cannon AJ, Whitfield PH (2002) Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models. J Hydrol 259:136–151CrossRef Chen D, Chen Y (2003) Association between winter temperature in China and upper air circulation over East Asia revealed by canonical correlation analysis. Global Planet Change 37:315–325CrossRef Chen D, Achberger C, Räisänen J, Hellström C (2006) Using statistical downscaling to quantify the GCM-related uncertainty in regional climate change scenarios: a case study of Swedish precipitation. Adv Atmos Sci 23:54–60CrossRef Cheng CS, Li GL, Li Q, Auld H (2011) A synoptic weather-typing approach to project future daily rainfall and extremes at local scale in Ontario, Canada. J Clim 24:3667–3685CrossRef Chu JT, Xia J, Xu C, Singh VP (2010) Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China. Theor Appl Climatol 99:149–161CrossRef Coelho C, Stephenson DB, Doblas Reyes FJ, Balmaseda M, Guetter A, Van Oldenborgh GJ (2006) A Bayesian approach for multi-model downscaling: seasonal forecasting of regional rainfall and river flows in South America. Meteorol Appl 13:73–82CrossRef Curry CL, van der Kamp D, Monahan AH (2012) Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. I. Predicting wind speed. Clim Dyn 38:1281–1299CrossRef De Sales F, Xue YK (2013) Dynamic downscaling of 22-year CFS winter seasonal hindcasts with the UCLA-ETA regional climate model over the United States. Clim Dyn 41:255–275CrossRef Druyan LM, Fulakeza M, Lonergan P (2002) Dynamic downscaling of seasonal climate predictions over Brazil. J Clim 15:3411–3426CrossRef Duan Q, Ajami NK, Gao X, Sorooshian S (2007) Multi-model ensemble hydrologic prediction using Bayesian model averaging. Adv Water Resour 30:1371–1386CrossRef Fatichi S, Ivanov VY, Caporali E (2011) Simulation of future climate scenarios with a weather generator. Adv Water Resour 34:448–467CrossRef Fatichi S, Ivanov VY, Caporali E (2013) Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series. Clim Dyn 40:1841–1861CrossRef Fealy R, Sweeney J (2007) Statistical downscaling of precipitation for a selection of sites in Ireland employing a generalised linear modelling approach. Int J Climatol 27:2083–2094CrossRef Fowler HJ, Kilsby CG, Stunell J (2007) Modelling the impacts of projected future climate change on water resources in north-west England. Hydrol Earth Sys Sci Discuss 11:1115–1126CrossRef Goubanova K, Echevin V, Dewitte B, Codron F, Takahashi K, Terray P, Vrac M (2011) Statistical downscaling of sea-surface wind over the Peru-Chile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model. Clim Dyn 36:1365–1378CrossRef Guan H, Wilson JL, Xie H (2009) A cluster-optimizing regression-based approach for precipitation spatial downscaling in mountainous terrain. J Hydrol 375:578–588CrossRef Hay LE, McCabe GJ, Wolock DM, Ayers MA (1991) Simulation of precipitation by weather type analysis. Water Resour Res 27:493–501CrossRef Hessami M, Gachon P, Ouarda TB, St-Hilaire A (2008) Automated regression-based statistical downscaling tool. Environ Model Softw 23:813–834CrossRef Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471CrossRef Kharin VV, Zwiers FW (2002) Climate predictions with multimodel ensembles. J Clim 15:793–799CrossRef Kim JW, Chang JT, Baker NL, Wilks DS, Gates WL (1984) The statistical problem of climate inversion- Determination of the relationship between local and large-scale climate. Mon Weather Rev 112:2069–2077CrossRef Lamb HH (1972) British Isles weather types and a register of the daily sequence of circulation patterns 1861–1971. HM Stationery Office, London Liao Y, Zhang Q, Chen D (2004) Stochastic modeling of daily precipitation in China. J Geogr Sci 14:417–426CrossRef Linderson M, Achberger C, Chen D (2004) Statistical downscaling and scenario construction of precipitation in Scania, southern Sweden. Nord Hydrol 35:261–278 Maraun D, Rust HW, Osborn TJ (2010a) Synoptic airflow and UK daily precipitation extremes. Extremes 13:133–153CrossRef Maraun D, Wetterhall F, Ireson AM, Chandler RE, Kendon EJ, Widmann M, Brienen S, Rust HW, Sauter T, Themeßl M (2010b) Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48:RG3003. doi:10.1029/2009RG000314 Maraun D, Osborn TJ, Rust HW (2011) The influence of synoptic airflow on UK daily precipitation extremes. Part I: observed spatio-temporal relationships. Clim Dyn 36:261–275CrossRef Meehl G, Covey C, Delworth T, Latif M, McAvaney B, Mitchell J, Stouffer R, Taylor K (2007) The WCRP CMIP3 multi-model dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394CrossRef Murphy J (1999) An evaluation of statistical and dynamical techniques for downscaling local climate. J Clim 12:2256–2284CrossRef Orskaug E, Scheel I, Frigessi A, Guttorp P, Haugen JE, Tveito OE, Haug O (2011) Evaluation of a dynamic downscaling of precipitation over the Norwegian mainland. Tellus A 63:746–756CrossRef Osca J, Romero R, Alonso S (2013) Precipitation projections for Spain by means of a weather typing statistical method. Global Planet Change 109:46–63CrossRef Raftery AE, Zheng Y (2003) Discussion: performance of Bayesian model averaging. J Am Stat Assoc 98:931–938CrossRef Raftery AE, Gneiting T, Balabdaoui F, Polakowski M (2005) Using Bayesian model averaging to calibrate forecast ensembles. Mon Weather Rev 133:1155–1174CrossRef Rodrigues LRL, Doblas-Reyes FJ, Dos Santos Coelho CA (2013) Multi-model calibration and combination of tropical seasonal sea surface temperature forecasts. Clim Dyn. doi:10.1007/s00382-013-1779-8 Rummukainen M, Räisänen J, Bringfelt B, Ullerstig A, Omstedt A, Willén U, Hansson U, Jones C (2001) A regional climate model for northern Europe: model description and results from the downscaling of two GCM control simulations. Clim Dyn 17:339–359CrossRef Salathe EP, Mote PW, Wiley MW (2007) Review of scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United States Pacific Northwest. Int J Climatol 27:1611–1621CrossRef Schmidli J, Goodess CM, Frei C, Haylock MR, Hundecha Y, Ribalaygua J, Schmith T (2007) Statistical and dynamical downscaling of precipitation: an evaluation and comparison of scenarios for the European Alps. J Geophys Res 112:D04105. doi:10.1029/2005JD007026 Stehlik J, Bárdossy A (2003) Statistical comparison of European circulation patterns and development of a continental scale classification. Theor Appl Climatol 76:31–46CrossRef Sun CJ, Monahan AH (2013) Statistical downscaling prediction of sea surface winds over the global ocean. J Climate 26:7938–7956CrossRef Viallefont V, Raftery AE, Richardson S (2001) Variable selection and Bayesian model averaging in case–control studies. Stat Med 20:3215–3230CrossRef von Storch H, Zorita E, Cubasch U (1993) Downscaling of global climate change estimates to regional scales: an application to Iberian rainfall in wintertime. J Clim 6:1161–1171CrossRef Vrac M, Naveau P (2007) Stochastic downscaling of precipitation: from dry events to heavy rainfalls. Water Resour Res 43:W07402. doi:10.1029/2006WR005308 Wetterhall F, Halldin S, Xu C (2005) Statistical precipitation downscaling in central Sweden with the analogue method. J Hydrol 306:174–190CrossRef Wetterhall F, Bárdossy A, Chen D, Halldin S, Xu CY (2006) Daily precipitation-downscaling techniques in three Chinese regions. Water Resour Res 42:W11423 Wetterhall F, Halldin S, Xu C (2007) Seasonality properties of four statistical-downscaling methods in central Sweden. Theor Appl Climatol 87:123–137CrossRef Widmann M, Bretherton CS, Salathé EP Jr (2003) Statistical precipitation downscaling over the Northwestern United States using numerically simulated precipitation as a predictor*. J Clim 16:799–816CrossRef Wilby RL, Wigley T (1997) Downscaling general circulation model output: a review of methods and limitations. Prog Phys Geogr 21:530–548CrossRef Wilby RL, Wigley TML (2000) Precipitation predictors for downscaling: observed and general circulation model relationships. Int J Climatol 20:641–661CrossRef Wilby RL, Charles SP, Zorita E, Timbal B, Whetton P, Mearns LO (2004) Guidelines for use of climate scenarios developed from statistical downscaling methods. IPCC Task Group on Data and Scenario Support for Impact and Climate Analysis (TGICA). http://ipcc-ddc.cru.uea.ac.uk/gu-idelines/StatDown_Guide.pdf Xu C (1999) From GCMs to river flow: a review of downscaling methods and hydrologic modelling approaches. Prog Phys Geogr 23:229–249CrossRef Yee TW, Stephenson AG (2007) Vector generalized linear and additive extreme value models. Extremes 10:1–19CrossRef Yin C, Li Y, Ye W, Bornman JF, Yan X (2011) Statistical downscaling of regional daily precipitation over southeast Australia based on self-organizing maps. Theor Appl Climatol 105:11–26CrossRef
- 作者单位:Xianliang Zhang (1)
Xiaodong Yan (2)
1. College of Forestry, Shenyang Agriculture University, Shenyang, 110866, China 2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100087, China
- 刊物类别:Earth and Environmental Science
- 刊物主题:Earth sciences
Geophysics and Geodesy Meteorology and Climatology Oceanography
- 出版者:Springer Berlin / Heidelberg
- ISSN:1432-0894
文摘
A new statistical downscaling method was developed and applied to downscale monthly total precipitation from 583 stations in China. Generally, there are two steps involved in statistical downscaling: first, the predictors are selected (large-scale variables) and transformed; and second, a model between the predictors and the predictand (in this case, precipitation) is established. In the first step, a selection process of the predictor domain, called the optimum correlation method (OCM), was developed to transform the predictors. The transformed series obtained by the OCM showed much better correlation with the predictand than those obtained by the traditional transform method for the same predictor. Moreover, the method combining OCM and linear regression obtained better downscaling results than the traditional linear regression method, suggesting that the OCM could be used to improve the results of statistical downscaling. In the second step, Bayesian model averaging (BMA) was adopted as an alternative to linear regression. The method combining the OCM and BMA showed much better performance than the method combining the OCM and linear regression. Thus, BMA could be used as an alternative to linear regression in the second step of statistical downscaling. In conclusion, the downscaling method combining OCM and BMA produces more accurate results than the multiple linear regression method when used to statistically downscale large-scale variables.
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