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Titel Surface-sensible and latent heat fluxes over the Tibetan Plateau from ground measurements, reanalysis, and satellite data
VerfasserIn Q. Shi, S. Liang
Medientyp Artikel
Sprache Englisch
ISSN 1680-7316
Digitales Dokument URL
Erschienen In: Atmospheric Chemistry and Physics ; 14, no. 11 ; Nr. 14, no. 11 (2014-06-06), S.5659-5677
Datensatznummer 250118779
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/acp-14-5659-2014.pdf
 
Zusammenfassung
Estimations from meteorological stations over the Tibetan Plateau (TP) indicate that since the 1980s the surface-sensible heat flux has been decreasing continuously, and modeling studies suggest that such changes are likely linked to the weakening of the East Asian Monsoon through exciting Rossby wave trains. However, the spatial and temporal variations in the surface-sensible and latent heat fluxes over the entire TP remain unknown. This study aims to characterize the spatial and seasonal variability of the surface-sensible and latent heat fluxes at 0.5° over the TP from 1984 to 2007 by synthesizing multiple data sources including ground measurements, reanalysis products, and remote-sensing products. The root mean square errors (RMSEs) from cross validation are 14.3 Wm−2 and 10.3 Wm−2 for the monthly fused sensible and latent heat fluxes, respectively. The fused sensible and latent heat-flux anomalies are consistent with those estimated from meteorological stations, and the uncertainties of the fused data are also discussed. The associations among the fused sensible and latent heat fluxes and the related surface anomalies such as mean temperature, temperature range, snow cover, and normalized difference vegetation index (NDVI) in addition to atmospheric anomalies such as cloud cover and water vapor show seasonal dependence, suggest that the land–biosphere–atmosphere interactions over the TP could display nonuniform feedbacks to the climate changes. It would be interesting to disentangle the drivers and responses of the surface-sensible and latent heat-flux anomalies over the TP in future research from evidences of modeling results.
 
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