首页> 外文期刊>气候变化研究进展(英文版) >Bias correction and projection of surface air temperature in LMDZ multiple simulation over central and eastern China
【24h】

Bias correction and projection of surface air temperature in LMDZ multiple simulation over central and eastern China

机译:中国中部和东部地区LMDZ多重模拟中的地表温度偏差校正和预测

获取原文
获取原文并翻译 | 示例
       

摘要

Based on LMDZ4 daily temperature dataset,equidistant cumulative distribution function matching method (EDCDFm) and cumulative distribution function-transform method (CDF-t) are used to evaluate the ability of models in simulating extreme temperature over central and eastern China.The future temperature change is then projected.The results show that the EDCDFm and CDF-t methods function effectively correct the spatial distribution of daily mean temperature and extreme temperature,significantly reduce the biases of the model simulation and effectively improve the capacity of models for spatial pattern of extreme temperature.However,the cold bias of the CDF-t method in winter is obviously higher than that of the EDCDFm method,and the temperature change curve of the EDCDFm method is closer to the observation than that of the CDF-t method.The projection based on the EDCDFm method shows that under the RCP4.5 emission scenario,the temperature in the study area shows a warming trend.Relative to 1986-2005,the mean temperature is projected to increase by 0.76,1.84,and 2.10 ℃ during 2017-2036,2046-2065,and 2080-2099,respectively.The spatial change for the mean,maximum,and minimum temperature in the three future periods have good consistency;warming in northern China is higher than that in the south.Uncertainties in temperature projection are large in the Tibetan Plateau and Sichuan Basin.Frost days decrease significantly,especially in the Tibetan Plateau,and the frost days in the three periods decrease by more than 15,30,and 40 d,respectively.The variation of heat wave indice is the smallest;the increase of heat wave is mainly in eastern China,and the increase in South China is more than 2 d.Besides,under the global warming of 1.5 ℃ and 2 ℃,the response characteristics of extreme temperature over central and eastern China are also analyzed.The results show that the mean temperature,maximum temperature and minimum temperature in the study area increase by more than 0.75 ℃ under 1.5 ℃ target and over 1.25 ℃ under 2 ℃ target,especially in the northwestern China and the Tibetan Plateau,relative to 1986-2005.Additionally,comparing two warming targets,the difference of three temperature indices in parts of northeastern China is over 1.5 ℃,while more than 3 d for heat wave.
机译:基于LMDZ4每日温度数据集,使用等距累积分布函数匹配方法(EDCDFm)和累积分布函数变换方法(CDF-t)评估模型模拟中部和东部极端温度的能力。未来温度变化结果表明,EDCDFm和CDF-t方法可以有效地校正日平均温度和极端温度的空间分布,大大减少了模型模拟的偏差,有效地提高了模型针对极端温度的空间格局的能力但是,冬季CDF-t方法的冷偏差明显高于EDCDFm方法,而EDCDFm方法的温度变化曲线比CDF-t方法更接近观测值。 EDCDFm方法的研究表明,在RCP4.5排放情景下,研究区域的温度呈变暖趋势。 o 1986-2005年,预计2017-2036年,2046-2065年和2080-2099年的平均温度分别上升0.76、1.84和2.10℃。平均温度的最高,最低和最低温度的空间变化。三个未来时期具有良好的一致性;华北地区的暖化程度高于南方地区。青藏高原和四川盆地的气温预测不确定性较大。霜冻天数明显减少,尤其是青藏高原,而霜冻天数则明显减少。 3个周期分别减少了15、30和40 d以上。热浪指数的变化最小;热浪的增加主要集中在华东,华南的增加超过2 d。在1.5℃和2℃的全球变暖下,还分析了华中和华东地区极端温度的响应特征。结果表明,研究区的平均温度,最高温度和最低温度增加了0.75℃以上下1.5℃目标和低于2℃目标的1.25℃以上,尤其是在中国西北部和青藏高原,相对于1986-2005年。另外,比较两个升温目标,东北部分地区的三个温度指数之差超过1.5℃ ,而热浪超过3天。

著录项

  • 来源
    《气候变化研究进展(英文版)》 |2018年第1期|81-92|共12页
  • 作者单位

    Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science &Technology, Nanjing 210044, China;

    Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science &Technology, Nanjing 210044, China;

    Jiaxiang County Meteorological Service, Jining 272400, China;

    Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science &Technology, Nanjing 210044, China;

    Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science &Technology, Nanjing 210044, China;

    Laboratory of Meteorological Dynamics, UPMC/CNRS, IPSL, Paris 75005, France;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-19 03:58:03
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号