基于空间平稳性分析，引入地理因素结合回归分析及高精度曲面建模方法（HASM）对黑河流域多年平均气温、降水给出了降尺度模拟。基于过去器测资料的验证，提出了CMIP5模式资料的合理降尺度方法。比较了降尺度结果与站点实测值的差异，同时比较了所给出的方法与经典插值方法的模拟精度。最后，基于历史时期T1（1976—2005年）的降尺度方法结合RCP2.6、RCP4.5及RCP8.5不同情景下未来时段T2（2011—2040年）、T3（2041—2070年）、T4（2071—2100年） CMIP5模式结果，对降尺度方法进行了修正，给出了未来时段气温的降尺度模拟公式，并基于此对上述3种情景下多年平均气温的CMIP5模拟结果进行了降尺度模拟。结果表明：本文所提出的降尺度方法模拟结果与站点观测值具有较好的相关性，且精度高于其他经典插值方法。对未来时段的模拟结果表明，升温最快的是RCP8.5情景，在2071—2100年，除祁连山地区外，大部分地区年平均气温大于10℃。
Based on the spatial stationarity analysis, this study proposed a new statistical downscaling method with a combination of regression method and high accuracy surface modeling method (HASM), by considering geographical and topographical factors. The downscaling results were compared with observations from meteorological stations and the results produced from classical interpolators in 1976-2005 (T1). The downscaling formula for future scenarios was given and the downscaling results for future temperature and precipitation under RCP2.6, RCP4.5 and RCP8.5 scenarios in 2011-2040 (T2), 2041-2070 (T3), and 2071-2100 (T4) were obtained. It showed that the results of the proposed downscaling method were approximate to the real values and the accuracy of the method was higher than other classical methods. Downscaling simulations of the future scenarios indicated that the temperature has the highest rising under RCP8.5 scenario. Except for Qilian mountains, temperature is more than 10 ℃ in 2071-2100.
[1] 李晓东,傅华,李凤霞,等.气候变化对西北地区生态环境影响的若干研究进展[J].草业科学,2011,28(2):286-295.
[2] Mads C F,Eric P.Using large-scale climate indices in climate change ecology studies[J].Population Ecology,2004,46(1):1-12.
[3] 张戈丽,欧阳华,张宪洲,等.基于生态地理分区的青藏高原植被覆被变化及其对气候变化的响应[J].地理研究,2010,29(11):2004-2016.
[4] 李峰平,章光新,董李勤.气候变化对水循环与水资源的影响研究综述[J].地理科学,2013,33(4):457-464.
[5] 陈亚宁,李稚,范煜婷,等.西北干旱区气候变化对水文水资源影响研究进展[J].地理学报,2014,69(9):1295-1304.
[6] 马玉平,孙琳丽,俄有浩,等.预测未来40年气候变化对我国玉米产量的影响[J].应用生态学报,2015,26(1):224-232.
[7] 李勇,杨晓光,王文峰,等.全球气候变暖对中国种植制度可能影响V.气候变暖对中国热带作物种植北界和寒害风险的影响分析[J].中国农业科学,2010,43(12):2477-2484.
[8] 程国栋,肖洪浪,傅伯杰,等.黑河流域生态-水文过程集成研究进展[J].地球科学进展,2014,29(4):431-437.
[9] 宁宝英,何元庆,和献中,等.黑河流域水资源研究进展[J].中国沙漠,2008,28(6):1180-1185.
[10] 曹玲,窦永祥,张德玉.气候变化对黑河流域生态环境的影响[J].干旱气象,2003,21(4):45-49.
[11] 胡广录,王德金,廖亚鑫,等.气象因子对黑河中游荒漠-绿洲过渡带斑块植被区封杀活动的影响[J].中国沙漠,2015,35(4):865-873.
[12] 孙佳,江灏,王可丽,等.黑河流域气候平均降水的精细化分布及总量计算[J].冰川冻土,2011,33(2):318-324.
[13] 李海燕,王可丽,江灏,等.黑河流域降水的研究进展与展望[J].冰川冻土,2009,31(2):334-341.
[14] 李占玲,徐宗学.近50年来黑河流域气温和降水量突变特征分析[J].资源科学,2011,33(10):1877-1882.
[15] 丁荣,王伏村,王静,等.近47年来黑河流域的降水时空特征分析及预报评估[J].中国沙漠,2009,29(2):335-341.
[16] Jeong D L,St-Hilaire A,Ouarda T B M J,et al.Comparison of transfer functions in statistical downscaling models for daily temperature and precipitation over Canada[J].Stochastic Environmental Research and Risk Assessment,2012,26 (5):633-653.
[17] Wilby R L,Dawson C W,Barrow E M.SDSM-a decision support tool for the assessment of regional climate change impacts[J].Environmental Modeling & Software,2002,17(2):147-159.
[18] Chen S T,Tseng H W,Lin C Y,et al.Hydrological drought in Tseng-Wen reservoir basin under climate change scenarios[J].Journal of Taiwan Agricultural Engineering,2011,57(3):44-60.
[19] Yue T X,Zhao N,Ramsey R D,et al.Climate change trend in China,with improved accuracy[J].Climatic Change,2013,120:137-151.
[20] Yue T X.Surface Modeling:High Accuracy and High Speed Methods[M].New York,USA:CRC Press,2011.
[21] Moss R,Babiker M,Brinkman S,et al.Towards New Scenarios for Analysis of Emissions,Climate Change,Impacts,and Response Strategies[R].Geneva,Switzerland:Intergovernmental Panel on Climate Change,2008.
[22] 王绍武,罗勇,赵宗慈,等.新一代温室气体排放情景[J].气候变化研究进展,2012,8(4):305-307.
[23] Kamarianakis Y,Feidas H,Kokolatos G,et al.Evaluating remotely sensed rainfall estimates using nonlinear mixed models and geographically weighted regression[J].Environment Modeling & Software,2008,23:1438-1447.
[24] 雷志栋.土壤动力学[M].北京:清华大学出版社,1988.
[25] Box G E P,Cox D R.An analysis of transformation[J].Journal of the Royal Statistical Society,1964,26:211-252.
甘公网安备 62010202000688号