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contributor authorDu, Jizeng;Wang, Kaicun;Cui, Baoshan;Jiang, Shaojing
date accessioned2022-01-30T17:53:51Z
date available2022-01-30T17:53:51Z
date copyright9/18/2020 12:00:00 AM
date issued2020
identifier issn0894-8755
identifier otherjclid190521.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4264147
description abstractLand surface temperature Ts and near-surface air temperature Ta are two main metrics that reflect climate change. Recently, based on in situ observations, several studies found that Ts warmed much faster than Ta in China, especially after 2000. However, we found abnormal jumps in the Ts time series during 2003–05, mainly caused by the transformation from manual to automatic measurements due to snow cover. We explore the physical mechanism of the differences between automatic and manual observations and develop a model to correct the automatic observations on snowy days in the observed records of Ts. Furthermore, the nonclimatic shifts in the observed Ts were detected and corrected using the RHtest method. After corrections, the warming rates for Ts-max, Ts-min, and Ts-mean were 0.21°, 0.34°, and 0.25°C decade−1, respectively, during the 1960–2014 period. The abnormal jump in the difference between Ts and Ta over China after 2003, which was mentioned in existing studies, was mainly caused by inhomogeneities rather than climate change. Through a combined analysis using reanalyses and CMIP5 models, we found that Ts was consistent with Ta both in terms of interannual variability and long-term trends over China during 1960–2014. The Ts minus Ta (Ts − Ta) trend is from −0.004° to 0.009°C decade−1, accounting for from −3.19% to 5.93% (from −3.09% to 6.39%) of the absolute warming trend of Ts (Ta).
publisherAmerican Meteorological Society
titleCorrection of Inhomogeneities in Observed Land Surface Temperatures over China
typeJournal Paper
journal volume33
journal issue20
journal titleJournal of Climate
identifier doi10.1175/JCLI-D-19-0521.1
journal fristpage8885
journal lastpage8902
treeJournal of Climate:;2020:;volume( 33 ):;issue: 020
contenttypeFulltext


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