Global Contributions of Incoming Radiation and Land Surface Conditions to Maximum Near-Surface Air Temperature Variability and Trend

被引:24
|
作者
Schwingshackl, Clemens [1 ]
Hirschi, Martin [1 ]
Seneviratne, Sonia I. [1 ]
机构
[1] ETH, Inst Atmospher & Climate Sci, Zurich, Switzerland
基金
欧洲研究理事会;
关键词
temperature variability; temperature trend; linear regression; radiation; soil moisture; albedo; SOIL-MOISTURE; SOLAR-RADIATION; CLIMATE; ATLANTIC; MODEL; AMPLIFICATION; VARIABLES; SELECTION; FEEDBACK; IMPACT;
D O I
10.1029/2018GL077794
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The evolution of near-surface air temperature is influenced by various dynamical, radiative, and surface-atmosphere exchange processes whose contributions are still not completely quantified. Applying stepwise multiple linear regression to Coupled Model Intercomparison Project phase 5 (CMIP5) model simulations and focusing on radiation (diagnosed by incoming shortwave and incoming longwave radiation) and land surface conditions (diagnosed by soil moisture and albedo) about 79% of the interannual variability and 99% of the multidecadal trend of monthly mean daily maximum temperature over land can be explained. The linear model captures well the temperature variability in middle-to-high latitudes and in regions close to the equator, whereas its explanatory potential is limited in deserts. While radiation is an essential explanatory variable over almost all of the analyzed domain, land surface conditions show a pronounced relation to temperature in some confined regions. These findings highlight that considering local-to-regional processes is crucial for correctly assessing interannual temperature variability and future temperature trends.
引用
收藏
页码:5034 / 5044
页数:11
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