盆地城市地气温差变化特征及模拟研究——以成都市为例
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摘要
地气温差对大气边界层热力交换起着极为重要的作用,对局地气候、城市边界层结构和大气污染有着重要影响,因此有必要对城市下垫面地气温差进行相应研究。本文以典型盆地城市成都为例,利用2014年成都市地表温度、气温逐时观测资料分析了该地区地气温差的变化特征,讨论了中尺度数值模式WRF(Weather Research and Forecasting Model)对盆地城市地气温差的模拟能力。结论表明:成都市平均地气温差为2. 20℃,多分布在0～2℃区间,与地表温度和气温变化不同,温差春季最大,夏、冬季次之,秋季最小;各季节温差日变化大致相似,均为中午较大,夜间在0℃左右,但极值大小不同。利用WRF对成都市典型夏季晴天地气温差进行了模拟研究,对比分析三种常用陆面过程参数化方案的模拟结果,三种方案模拟的变化趋势均与观测吻合,其中Noah方案能较好的模拟成都市地气温差的变化特征,通过参数化方案的组合方式,改进了模式对地气温差的WRF模拟能力。
The difference between land surface and air temperature(simply as Ts-Ta) plays an important role in the heat exchange of the atmospheric boundary layer. Therefore,it's necessary to study the Ts-Ta. By utilizing the observation data of temperature in Chengdu in 2014,this article analyzed the characteristics of the variation of the Ts-Ta,and the simulation ability of the numerical model WRF(Weather Research and Forecasting Model) on the Ts-Ta in the typical basin city,Chengdu,is discussed. The results showed that the Ts-Ta in Chengdu was 2. 20℃,mostly distributed between 0-2℃. The maximum Ts-Ta was in spring,followed by summer,winter,and autumn. The diurnal variations of Ts-Ta in different seasons were similar; however,the amplitude was different. The numerical model WRF was used to simulate the Ts-Ta between the typical sunny days in Chengdu. The simulation results of three common land surface process parameterization schemes were compared and analyzed. The variation trend of the three parameterized schemes was consistent with the observation,and the Noah scheme can better simulate the variation characteristics of the temperature difference in Chengdu. By combination of schemes,the simulation ability of ground temperature difference was improved.
The difference between land surface and air temperature(simply as Ts-Ta) plays an important role in the heat exchange of the atmospheric boundary layer. Therefore,it's necessary to study the Ts-Ta. By utilizing the observation data of temperature in Chengdu in 2014,this article analyzed the characteristics of the variation of the Ts-Ta,and the simulation ability of the numerical model WRF(Weather Research and Forecasting Model) on the Ts-Ta in the typical basin city,Chengdu,is discussed. The results showed that the Ts-Ta in Chengdu was 2. 20℃,mostly distributed between 0-2℃. The maximum Ts-Ta was in spring,followed by summer,winter,and autumn. The diurnal variations of Ts-Ta in different seasons were similar; however,the amplitude was different. The numerical model WRF was used to simulate the Ts-Ta between the typical sunny days in Chengdu. The simulation results of three common land surface process parameterization schemes were compared and analyzed. The variation trend of the three parameterized schemes was consistent with the observation,and the Noah scheme can better simulate the variation characteristics of the temperature difference in Chengdu. By combination of schemes,the simulation ability of ground temperature difference was improved.
引文
[1]王绍武,龚道溢.对气候变暖问题争议的分析[J].地理研究,2001,20(2):153-160
[2]Solomon S,Qin D,Manning M,et al.Climate change 2007:the Physical Science Basis.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[J].Summary for Policymakers,2007,18(2):95-123
[3]《气候变化国家评估报告》编写委员会.气候变化国家评估报告[M].北京:科学出版社,2007:469-469
[4]范丽军,韦志刚,董文杰.西北干旱区地气温差的时空特征分析[J].高原气象,2004,23(3):360-367
[5]刘武,李耀东,史小康.FY-2G地表温度反演产品改变模式初值对一次台风暴雨模拟的影响[J].气象与环境科学,2017,40(1):26-34
[6]肖晶晶,郭芬芬,李正泉,等.1951-2013年浙江热量资源变化研究[J].气象与环境科学,2017,40(3):110-118
[7]陆晓波.我国地温的变化特征及其地气温差与环流异常和夏季降水的相关分析[D].南京信息工程大学,2006:11-12
[8]符睿,韦志刚,文军,等.西北干旱区地气温差季节和年际变化特征的分析[J].高原气象,2008,27(4):844-851
[9]张文纲,李述训,吴通华,等.青藏高原地气温差变化分析[J].地理学报,2006,61(9):899-910
[10]刘颖.春季地气温差分布异常特征及其对中国东部夏季降水的影响[D].中国气象科学研究院,2008:5-6
[11]周连童,黄荣辉.中国西北干旱半干旱区春季地气温差的年代际变化特征及其对华北夏季降水年代际变化的影响[J].气候与环境研究,2006,11(1):1-13
[12]王超,韦志刚,李振朝,等.敦煌戈壁地区地气温差变化特征分析[J].干旱区资源与环境,2011,25(11):72-78
[13]王超,肖天贵,罗琴,等.盆地城市地气温差变化特征及对颗粒物浓度的影响[J].中国粉体技术,2018(3):76-80
[14]于真.四川省地表温度时空变化特征及评价模型研究[D].成都理工大学,2017:2-3
[15]胡毅,朱克云,李跃春,等.成都平原中西部近40年气候特征及其变化研究[J].成都信息工程学院学报,2004,(2):223-231
[16]张碧,胡毅,徐精文.成都平原秋季农业气候特征的分析利用[J].成都气象学院学报,1999(4):12-18
[17]Zhang,X.Y.,Y.Q.Wang,T.Niu,Corrigendum to Atmospheric aerosol compositions in China:spatial-temporal variability,chemical signature,regional haze distribution and comparisons with global aerosols Atmos.Chem.Phys.,2012(12):779-799
[18]王跃,王莉莉,赵广娜,等.北京冬季PM2.5重污染时段不同尺度环流形势及边界层结构分析[J].气候与环境研究,2014,19(2):173-184
[19]Skamarock,W.C.A description of the advanced research WRFversion 3[J].Ncar Technical,2005,113:7-25
[20]梁津,刘志红,姚琳.基于WRF/CMAQ的成都空气质量模拟与预报[J].高原山地气象研究,2016,36(3):90-96
[21]池再香,白慧,杜正静,等.贵州“2011.6”两次暴雨数值模拟研究[J].高原山地气象研究,2016,36(2):36-45
[22]吴泽,范广洲,周定文,等.基于WRF模式的雅安暴雨数值模拟研究[J].高原气象,2014,33(5):1332-1340
[23]胡向军,陶健红,郑飞,等.WRF模式物理过程参数化方案简介[J].甘肃科技,2008,24(20):73-75
[24]赖欣,文军,岑思弦,等.CLM4.0模式对中国区域土壤湿度的数值模拟及评估研究[J].大气科学,2014,38(3):499-512
[2]Solomon S,Qin D,Manning M,et al.Climate change 2007:the Physical Science Basis.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[J].Summary for Policymakers,2007,18(2):95-123
[3]《气候变化国家评估报告》编写委员会.气候变化国家评估报告[M].北京:科学出版社,2007:469-469
[4]范丽军,韦志刚,董文杰.西北干旱区地气温差的时空特征分析[J].高原气象,2004,23(3):360-367
[5]刘武,李耀东,史小康.FY-2G地表温度反演产品改变模式初值对一次台风暴雨模拟的影响[J].气象与环境科学,2017,40(1):26-34
[6]肖晶晶,郭芬芬,李正泉,等.1951-2013年浙江热量资源变化研究[J].气象与环境科学,2017,40(3):110-118
[7]陆晓波.我国地温的变化特征及其地气温差与环流异常和夏季降水的相关分析[D].南京信息工程大学,2006:11-12
[8]符睿,韦志刚,文军,等.西北干旱区地气温差季节和年际变化特征的分析[J].高原气象,2008,27(4):844-851
[9]张文纲,李述训,吴通华,等.青藏高原地气温差变化分析[J].地理学报,2006,61(9):899-910
[10]刘颖.春季地气温差分布异常特征及其对中国东部夏季降水的影响[D].中国气象科学研究院,2008:5-6
[11]周连童,黄荣辉.中国西北干旱半干旱区春季地气温差的年代际变化特征及其对华北夏季降水年代际变化的影响[J].气候与环境研究,2006,11(1):1-13
[12]王超,韦志刚,李振朝,等.敦煌戈壁地区地气温差变化特征分析[J].干旱区资源与环境,2011,25(11):72-78
[13]王超,肖天贵,罗琴,等.盆地城市地气温差变化特征及对颗粒物浓度的影响[J].中国粉体技术,2018(3):76-80
[14]于真.四川省地表温度时空变化特征及评价模型研究[D].成都理工大学,2017:2-3
[15]胡毅,朱克云,李跃春,等.成都平原中西部近40年气候特征及其变化研究[J].成都信息工程学院学报,2004,(2):223-231
[16]张碧,胡毅,徐精文.成都平原秋季农业气候特征的分析利用[J].成都气象学院学报,1999(4):12-18
[17]Zhang,X.Y.,Y.Q.Wang,T.Niu,Corrigendum to Atmospheric aerosol compositions in China:spatial-temporal variability,chemical signature,regional haze distribution and comparisons with global aerosols Atmos.Chem.Phys.,2012(12):779-799
[18]王跃,王莉莉,赵广娜,等.北京冬季PM2.5重污染时段不同尺度环流形势及边界层结构分析[J].气候与环境研究,2014,19(2):173-184
[19]Skamarock,W.C.A description of the advanced research WRFversion 3[J].Ncar Technical,2005,113:7-25
[20]梁津,刘志红,姚琳.基于WRF/CMAQ的成都空气质量模拟与预报[J].高原山地气象研究,2016,36(3):90-96
[21]池再香,白慧,杜正静,等.贵州“2011.6”两次暴雨数值模拟研究[J].高原山地气象研究,2016,36(2):36-45
[22]吴泽,范广洲,周定文,等.基于WRF模式的雅安暴雨数值模拟研究[J].高原气象,2014,33(5):1332-1340
[23]胡向军,陶健红,郑飞,等.WRF模式物理过程参数化方案简介[J].甘肃科技,2008,24(20):73-75
[24]赖欣,文军,岑思弦,等.CLM4.0模式对中国区域土壤湿度的数值模拟及评估研究[J].大气科学,2014,38(3):499-512