气候变化背景下未来中国气候生产潜力时空动态格局
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摘要
基于气温及降水数据,运用Thornthwaite Memorial模型,分析了气候变化背景下中国未来(2021-2099年)RCP4.5和RCP8.5气候情景相对于基准期(1986-2005年)气候生产潜力的时空分布及动态变化特征。结果表明:基准期、未来RCP4.5及RCP8.5情景下中国气候生产潜力(CPP)年均值分别为754.14、878.48、920.34g/(m~2·a)。未来CPP呈显著增加趋势,但并未发生突变。其中,RCP4.5情景下年均增加124.34g/(m~2·a),只21世纪前半叶显著增加;RCP8.5情景下年均增加166.20g/(m~2·a),21世纪前半、后半叶均显著增加,且后半叶增幅更大。未来RCP4.5、RCP8.5情景下中国CPP呈年代际递增趋势,20年代最低,分别为841.90、849.94g/(m~2·a),90年代最高,分别为894.43、1001.44g/(m~2·a);随着年代增加距平百分率由负到正,增幅逐渐变大。在空间上CPP总体呈现出从西北向东南逐渐递增的带状分布。未来CPP在大部分区域都增加,增幅在北部大于南部,大部分地区增幅在300g/(m~2·a)以下,只有西北部分地区增幅超过600g/(m~2·a),最高达14倍。在西、南部少数地区,未来CPP将下降,最大降幅为293g/(m~2·a)(93%)。该研究对于未来合理利用气候资源、科学应对气候变化、实施可持续发展战略具有一定的指导意义。
Climatic potential productivity(CPP) from 1986 to 2005 was taken as a baseline period and that over 2021-2099 under RCP4.5 and RCP8.5 scenarios was evaluated by Thornthwaite Memorial model by using annual temperature and precipitation data, in order to understand the temporal-spatio dynamic pattern and reveal the impact of climate change in the future in China. The results show that, the mean annual average CPP were 754.14, 878.48, and 920.34 g/(m~2·a), respectively, for baseline period and under RCP4.5 and RCP8.5 scenarios. CPP increased significantly from 2021 to 2099, but there was no mutation. Under RCP4.5 scenario, CPP increased significantly in the first half of the 21 st century, but not significantly in the latter half, with an average increase of 124.34 g/(m~2·a). Under RCP8.5 scenario, there was a significant increase both in the first half and in the latter half of the 21 st century, with an average increase of 166.20 g/(m~2·a). CPP increased age by age from the perspective of interdecadal scale. It was the lowest of 841.90, 849.94 g/(m~2·a) in 2020 s and the highest of 894.43, 1001.44 g/(m~2·a) in 2090 s under RCP4.5 and RCP8.5 scenarios. Anomalous percentage of CPP increased from negative to positive, and the growth rate increased gradually over the decades. CPP varied in different regions with a zonal distribution of gradually increasing from northwest to southeast China. It increased in most areas of China, with relatively higher rising amplitude in north than in south. The rising amplitude was lower than 300 g/(m~2·a) in most areas, and was only higher than 600 g/(m~2·a) in some areas of Northwest China, with a maximum increase of 14 times. CPP decreased in some areas in south and west China, with the highest decreasing amplitude of 293 g/(m~2·a)(a decrease of 93%). This study has some guiding significance for adapting to climate change, utilizing climate resources rationally, and implementing the sustainable development strategy.
Climatic potential productivity(CPP) from 1986 to 2005 was taken as a baseline period and that over 2021-2099 under RCP4.5 and RCP8.5 scenarios was evaluated by Thornthwaite Memorial model by using annual temperature and precipitation data, in order to understand the temporal-spatio dynamic pattern and reveal the impact of climate change in the future in China. The results show that, the mean annual average CPP were 754.14, 878.48, and 920.34 g/(m~2·a), respectively, for baseline period and under RCP4.5 and RCP8.5 scenarios. CPP increased significantly from 2021 to 2099, but there was no mutation. Under RCP4.5 scenario, CPP increased significantly in the first half of the 21 st century, but not significantly in the latter half, with an average increase of 124.34 g/(m~2·a). Under RCP8.5 scenario, there was a significant increase both in the first half and in the latter half of the 21 st century, with an average increase of 166.20 g/(m~2·a). CPP increased age by age from the perspective of interdecadal scale. It was the lowest of 841.90, 849.94 g/(m~2·a) in 2020 s and the highest of 894.43, 1001.44 g/(m~2·a) in 2090 s under RCP4.5 and RCP8.5 scenarios. Anomalous percentage of CPP increased from negative to positive, and the growth rate increased gradually over the decades. CPP varied in different regions with a zonal distribution of gradually increasing from northwest to southeast China. It increased in most areas of China, with relatively higher rising amplitude in north than in south. The rising amplitude was lower than 300 g/(m~2·a) in most areas, and was only higher than 600 g/(m~2·a) in some areas of Northwest China, with a maximum increase of 14 times. CPP decreased in some areas in south and west China, with the highest decreasing amplitude of 293 g/(m~2·a)(a decrease of 93%). This study has some guiding significance for adapting to climate change, utilizing climate resources rationally, and implementing the sustainable development strategy.
引文
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[22]廖雪萍,刘一江,李耀先,等.未来气候情景下广西冬季农业气候生产潜力的变化特征[J].西南农业学报,2017,30(2):438-443.
[23]褚荣浩,申双和,吕厚荃,等.Reg CM3下1951-2100年江苏省热量资源及一季稻气候生产潜力[J].江苏农业学报,2015,31(4):779-785.
[24]袁彬,郭建平,冶明珠,等.气候变化下东北春玉米品种熟型分布格局及其气候生产潜力[J].科学通报,2012,57(14):1252-1262.
[25]姚玉璧,李耀辉,王毅荣,等.黄土高原气候与气候生产力对全球气候变化的响应[J].干旱地区农业研究,2005,23(2):202-208.
[26]李蒙,朱勇,黄玮.气候变化对云南气候生产潜力的影响[J].中国农业气象,2010,31(3):442-446.
[27]吉莉,李家启,李强,等.气候变化对北碚区蔬菜气候生产潜力影响研究[J].中国农学通报,2013,29(20):165-169.
[28]余海龙,赖荣生,黄菊莹.气候变化对宁夏自治区中卫市环香山地区气候生产潜力的影响[J].水土保持通报,2014,34(4):291-295.
[29]侯光良,游松才.用筑后模型估算中国植物气候生产力[J].自然资源学报,1990,5(l):60-65.
[30]张宪洲.中国自然植被第一性生产力的估算与分布[J].自然资源,1993(l):15-21.
[31]李正明,王毅荣.黄土高原气候生产力演变分析[J].山西大学学报(自然科学版),2006,29(1):96-101.
[32]候西勇.1951-2000年中国气候生产潜力时空动态特征[J].干旱区地理,2008,31(5):723-730.
[33]吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比[J].地球物理学报,2013,56(4):1102-1111.
[34]初征,郭建平.未来气候变化对东北玉米品种布局的影响[J].应用气象学报,2018,29(2):165-176.
[35]徐延红.东北玉米适应气候变化措施对农业气候资源利用率的影响评估[D].北京:中国气象科学研究院,2014.
[36]刘文茹,陈国庆,曲春红,等.RCP情景下长江中下游麦稻二熟制气候生产潜力变化特征研究[J].生态学报,2018,38(1):156-166.
[37]贺山峰,葛全胜,吴绍洪,等.SRES B2情景下西南地区干旱致灾危险性时空格局预估[J].中国人口·资源与环境,2013,23(9):165-171.
[2]IPCC.Climate Change 2013:The Physical Science Basis.Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[R].Cambridge:Cambridge University Press,2013.
[3]Savin I Y,Stolbovoy V S,Savitskaya N V.Climatic potential for winter wheat yield in Russia[J].Russian Agricultural Sciences,2017,43(4):296-299.
[4]Pathaka H,Ladhab J K,Aggarwala P K,et al.Trends of climatic potential and on-farm yields of rice and wheat in the Indo-Gangetic Plains[J].Field Crops Research,2003,80(3):223-234.
[5]Ricce W D,Caramori P H,Roberto S R,et al.Climatic potential for grape production under double annual pruning system in the State of Parana,Brazil[J].Bragantia,2013,72(4):408-415.
[6]Jevti ca R,upunskia V,Lalo2evi c'M,et al.Predicting potential winter wheat yield losses caused by multiple disease systems and climatic conditions[J].Crop Protection,2017,99:17-25.
[7]Holzkmper A,Calanca P,Fuhrer J.Identifying climatic limitations to grain maize yield potentials using a suitability evaluation approach[J].Agricultural and Forest Meteorology,2013,168:149-159.
[8]Holzkaemper A,Fossati D,Hiltbrunner J,et al.Spatial and temporal trends in agro-climatic limitations to production potentials for grain maize and winter wheat in Switzerland[J].Regional Environmental Change,2015,15(1):109-122.
[9]李莉,周宏飞,包安明.中亚地区气候生产潜力时空变化特征[J].自然资源学报,2014,29(2):285-294.
[10]候西勇.1951-2000年中国气候生产潜力时空动态特征[J].干旱区地理,2008,31(5):723-730.
[11]钟章奇,王铮,夏海斌,等.全球气候变化下中国农业生产潜力的空间演变[J].自然资源学报,2015,30(12):2018-2032.
[12]潘虹,邱新法,廖留峰,等.近50年贵州省气候生产潜力时空变化特征[J].干旱区资源与环境,2014,28(11):158-163.
[13]王春娟,何可杰.气候变化背景下陕西关中西部作物气候生产潜力变化特征[J].中国农学通报,2016,32(28):170-176.
[14]刘大锋,李海花.1961-2011年阿勒泰地区的气候生产潜力变化分析[J].沙漠与绿洲气象,2013,7(2):25-28.
[15]靳英华,许嘉巍,朱孟美,等.黑钙土区50年来气候生产潜力变化分析[J].东北师大学报(自然科学版),2016,48(1):121-127.
[16]赵雪雁,王伟军,万文玉,等.近50年气候变化对青藏高原青稞气候生产潜力的影响[J].中国生态农业学报,2015,23(10):1329-1338.
[17]Dixita P N,Telleriaa R,Al Khatibb A N,et al.Decadal analysis of impact of future climate on wheat production in dry Mediterranean environment:A case of Jordan[J].Science of The Total Environment,2018,610-611:219-233.
[18]Arayaa I A,Kisekka I,Lin X,et al.Evaluating the impact of future climate change on irrigated maize production in Kansas[J].Climate Risk Management,2017,17:139-154.
[19]Gornall J,Betts R,Burke E,et al.Implications of climate change for agricultural productivity in the early twenty-first century[J].Philosophical Transactions of the Royal Society B:Biological Sciences,2010,365(1554):2973-2989.
[20]周广胜.气候变化对中国农业生产影响研究展望[J].气象与环境科学,2015,38(1):80-94.
[21]赵俊芳,郭建平,邬定荣,等.2011-2050年黄淮海冬小麦、夏玉米气候生产潜力评价[J].应用生态学报,2011,22(12):3189-3195.
[22]廖雪萍,刘一江,李耀先,等.未来气候情景下广西冬季农业气候生产潜力的变化特征[J].西南农业学报,2017,30(2):438-443.
[23]褚荣浩,申双和,吕厚荃,等.Reg CM3下1951-2100年江苏省热量资源及一季稻气候生产潜力[J].江苏农业学报,2015,31(4):779-785.
[24]袁彬,郭建平,冶明珠,等.气候变化下东北春玉米品种熟型分布格局及其气候生产潜力[J].科学通报,2012,57(14):1252-1262.
[25]姚玉璧,李耀辉,王毅荣,等.黄土高原气候与气候生产力对全球气候变化的响应[J].干旱地区农业研究,2005,23(2):202-208.
[26]李蒙,朱勇,黄玮.气候变化对云南气候生产潜力的影响[J].中国农业气象,2010,31(3):442-446.
[27]吉莉,李家启,李强,等.气候变化对北碚区蔬菜气候生产潜力影响研究[J].中国农学通报,2013,29(20):165-169.
[28]余海龙,赖荣生,黄菊莹.气候变化对宁夏自治区中卫市环香山地区气候生产潜力的影响[J].水土保持通报,2014,34(4):291-295.
[29]侯光良,游松才.用筑后模型估算中国植物气候生产力[J].自然资源学报,1990,5(l):60-65.
[30]张宪洲.中国自然植被第一性生产力的估算与分布[J].自然资源,1993(l):15-21.
[31]李正明,王毅荣.黄土高原气候生产力演变分析[J].山西大学学报(自然科学版),2006,29(1):96-101.
[32]候西勇.1951-2000年中国气候生产潜力时空动态特征[J].干旱区地理,2008,31(5):723-730.
[33]吴佳,高学杰.一套格点化的中国区域逐日观测资料及与其它资料的对比[J].地球物理学报,2013,56(4):1102-1111.
[34]初征,郭建平.未来气候变化对东北玉米品种布局的影响[J].应用气象学报,2018,29(2):165-176.
[35]徐延红.东北玉米适应气候变化措施对农业气候资源利用率的影响评估[D].北京:中国气象科学研究院,2014.
[36]刘文茹,陈国庆,曲春红,等.RCP情景下长江中下游麦稻二熟制气候生产潜力变化特征研究[J].生态学报,2018,38(1):156-166.
[37]贺山峰,葛全胜,吴绍洪,等.SRES B2情景下西南地区干旱致灾危险性时空格局预估[J].中国人口·资源与环境,2013,23(9):165-171.
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