Characterizing the surface radiation budget over the Tibetan Plateau with ground‐measured, reanalysis, and remote sensing data sets: 2. Spatiotemporal analysis
Authors:
Open Access
- 12 August 2013
- journal article
- research article
- Published by American Geophysical Union (AGU) in Journal of Geophysical Research: Atmospheres
- Vol. 118 (16) , 8921-8934
Abstract
Recent progress in observation and modeling studies indicates that the Tibetan Plateau (TP) has been experiencing solar dimming coincident with changes of surface and atmospheric conditions since the early 1980s. However, changes and variability of the surface radiation budget over the entire Tibetan Plateau have rarely been analyzed in association with meteorological observations. Taking into consideration the limitations in ground measurements, reanalysis products, and remote sensing products, this paper applies the fused data (described in Part 1 of this two‐paper series) to analyze the seasonal and annual spatial pattern and temporal variation in the surface radiation budget (SRB) over the TP from 1984 to 2007. The climatology and interannual variability of five SRB components—downward shortwave irradiance, albedo, downward longwave flux, upward longwave flux, and net all‐wave radiation—are presented and analyzed in conjunction with atmospheric (cloud cover, water vapor) and surface (temperature, snow cover, normalized difference vegetation index) conditions over the Tibetan Plateau. Over the entire Tibetan Plateau, regardless of the increase of downward longwave radiation that counteracts the increase of upward longwave radiation, the interaction of solar dimming with changes of surface albedo has dominated the marked decrease of all‐wave net radiation since the mid‐1980s. This result indicates that the weakening and strengthening of the relationship between the components of SRB and the correlated variables of atmospheric or surface conditions exhibit a seasonal dependency over the TP. Moreover, most peaks and drops in the SRB anomalies are consistent to variations in two dominant variables.Keywords
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