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Range of monthly mean hourly land surface air temperature diurnal cycle over high northern latitudes
Author(s) -
Wang Aihui,
Zeng Xubin
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2014jd021602
Subject(s) - environmental science , diurnal cycle , latitude , surface air temperature , range (aeronautics) , atmospheric sciences , climatology , diurnal temperature variation , air temperature , meteorology , geography , geology , precipitation , geodesy , materials science , composite material
Abstract Daily maximum and minimum temperatures over global land are fundamental climate variables, and their difference represents the diurnal temperature range (DTR). While the differences between the monthly averaged DTR (MDTR) and the range of monthly averaged hourly temperature diurnal cycle (RMDT) are easy to understand qualitatively, their differences have not been quantified over global land areas. Based on our newly developed in situ data (Climatic Research Unit) reanalysis (Modern‐Era Retrospective analysis for Research and Applications) merged hourly temperature data from 1979 to 2009, RMDT in January is found to be much smaller than that in July over high northern latitudes, as it is much more affected by the diurnal radiative forcing than by the horizontal advection of temperature. In contrast, MDTR in January is comparable to that in July over high northern latitudes, but it is much larger than January RMDT, as it primarily reflects the movement of lower frequency synoptic weather systems. The area‐averaged RMDT trends north of 40°N are near zero in November, December, and January, while the trends of MDTR are negative. These results suggest the need to use both the traditional MDTR and RMDT suggested here in future observational and modeling studies. Furthermore, MDTR and its trend are more sensitive to the starting hour of a 24 h day used in the calculations than those for RMDT, and this factor also needs to be considered in model evaluations using observational data.

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