首页 | 本学科首页   官方微博 | 高级检索  
     检索      

1991—2010年全球湖泊表面温度效应的时空格局及生物物理因子拆分
引用本文:吕恒,王伟,万梓文,李雨竹,楚淏然,赖宇婧,张珂菡,石婕.1991—2010年全球湖泊表面温度效应的时空格局及生物物理因子拆分[J].地理学报,2022,77(9):2266-2279.
作者姓名:吕恒  王伟  万梓文  李雨竹  楚淏然  赖宇婧  张珂菡  石婕
作者单位:1.南京信息工程大学气候与环境变化国际合作联合实验室大气环境中心,南京 2100442.南京信息工程大学江苏省农业气象重点实验室,南京 210044
基金项目:国家重点研发计划(2019YFA0607202);江苏省研究生科研与实践创新计划项目(KYCX21_0978)
摘    要:量化湖泊与邻近陆地的表面温度差异,拆分生物物理因子对其贡献是明确湖泊气候效应的基础。本文基于耦合CLM4.5的CESM模式模拟的1991—2010年全球气候数据,分析了全球湖泊表面温度效应(湖泊与邻近陆地的表面温度差异)的时空格局,利用IBPM因子拆分理论量化了生物物理因子对其贡献。结果表明:① 湖泊表面温度效应的季节变化明显,但年际变化不显著,北半球湖泊最强增温(4.37 K)和降温效应(-0.99 K)分别出现在9月和4月。② 除干旱区湖泊呈降温效应外,其他气候区的湖泊以增温效应为主,热带湖泊增温效应最强。③ 湖泊表面温度效应的生物物理主控因子随气候区改变,湖陆之间的蒸发差异是干旱区湖泊呈降温效应的主控因子,较低的对流散热效率是热带和温带湖泊呈增温效应的主控因子,反照率差异和冰雪融化潜热分别对寒带、极地湖泊表面温度效应的正贡献和负贡献最大。全球尺度上,湖陆之间的对流效率差异(3.77±0.13 K)和蒸发差异(-2.01±0.1 K)对湖泊表面温度效应的正、负贡献最大。

关 键 词:湖泊  表面温度  生物物理因子  时空变化  因子拆分  
收稿时间:2021-11-22
修稿时间:2022-08-11

Biophysical attribution of surface temperature difference between global lakes and their surrounding lands from 1991 to 2010
LYU Heng,WANG Wei,WAN Ziwen,LI Yuzhu,CHU Haoran,LAI Yujing,ZHANG Kehan,SHI Jie.Biophysical attribution of surface temperature difference between global lakes and their surrounding lands from 1991 to 2010[J].Acta Geographica Sinica,2022,77(9):2266-2279.
Authors:LYU Heng  WANG Wei  WAN Ziwen  LI Yuzhu  CHU Haoran  LAI Yujing  ZHANG Kehan  SHI Jie
Institution:1. Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science & Technology, Nanjing 210044, China2. Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
Abstract:Quantification of the surface temperature difference (ΔTs, lake minus land) between lakes and their surrounding lands is an important step for understanding lake climate effects. In this study, we investigated the spatial and temporal patterns of ΔTs of global lakes and elucidated biophysical mechanisms that underly these patterns. Results are based on outputs from a fully coupled simulation with the Community Earth System Model (CESM) for the period from 1991 to 2010. We found that ?Ts showed large seasonal variations, with the strongest warming (mean ΔTs = 4.37 K) in September and the strongest cooling (-0.99 K) in April in the northern hemisphere. There is no significant interannual variation in ?Ts in individual climate zones or on the global scale. Spatially, only lakes in the arid climate showed a cooling effect (annual mean ΔTs = -1.19 K). Lakes in the other four climate zones (tropical, temperate, cold, and polar) exhibited warming effects (annual mean ΔTs from 0.92 K in cold climate to 2.78 K in tropical climate). The dominant biophysical drivers of ?Ts differed across climate zones. In arid climate zone, the lake cooling effect was mainly caused by lake evaporation stronger than land evaporation. In tropical and temperate climate zones, low lake energy dissipation efficiency was the dominant contributor to lake warming. In cold and polar climate zones, the lake warming was caused by large albedo contrasts between the lake and the snow-covered land, with additional contribution from energy consumed by lake ice-melting. On the global scale, the reduced lake energy dissipation efficiency increased ?Ts by 3.77±0.13 K, while enhanced evaporation decreased ?Ts by -2.01±0.1 K.
Keywords:lake  surface temperature  biophysical attribution  spatial and temporal pattern  isolating the contributions  
点击此处可从《地理学报》浏览原始摘要信息
点击此处可从《地理学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号