Abstract

The influences of interannual variability of vegetation LAI on surface temperature are investigated via two ensemble simulations, applying the Community Earth System Model. The interannual LAI, derived from Global Inventory Modeling and Mapping Studies NDVI for the period 1982–2011, and its associated climatological LAI, are used in the two ensemble simulations, respectively. The results show that the signals of the influences, represented as ensemble-mean differences, are generally weaker than the noises of the atmospheric variability, represented as one standard deviation of the ensemble differences. Spatially, the signals are stronger over the tropics compared with the mid–high latitudes. Such stronger signals are contributed by the significant linearity between LAI and surface temperature, which is mainly caused via the influences of LAI on evapotranspiration. The maximum amplitudes of the influences on the interannual variability of surface temperature are high and thus deserve full consideration. However, the mean magnitudes of influences are small because of the small changes in the amplitudes of LAI. This work only investigates the influences of the interannual variability of LAI and does not consider interannual changes in other vegetation characteristics, such as canopy height and fractional cover. Further work involving dynamic vegetation models may be needed to investigate the influences of vegetation variability.

Details

Title
Influences of the interannual variability of vegetation LAI on surface temperature
Author
Jia-Wen, ZHU 1 ; Xiao-Dong, ZENG 2 

 International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China 
 International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, China 
End page
297
Publication year
2016
Publication date
Jul 2016
Publisher
KeAi Publishing Communications Ltd
ISSN
16742834
e-ISSN
23766123
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2215242724
Copyright
© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.