Characterizing the surface radiation budget over the Tibetan Plateau with ground‐measured, reanalysis, and remote sensing data sets: 2. Spatiotemporal analysis

Abstract

[1] 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.Citation: Shi, Q., and S. Liang (2013), Characterizing the surface radiation budget over the Tibetan Plateau with ground-measured, reanalysis, and remote sensing data sets: 2. Spatiotemporal analysis,

Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau

“…Compared to the published studies, the LandFlux-EVAL LE also corresponds well with the merged net radiation and LE datasets, which were developed and validated over the TP by Shi and Liang (2013a, b) and Shi and Liang (2014). The spatial distribution of annual mean net radiation and LE can be found in study of Shi and Liang (2013a) and Shi and Liang (2014). Although the LandFlux-EVAL has not been validated against in situ measurements over the TP, the similar spatial patterns between LE and both observation-based precipitation and validated radiation to some extent demonstrate the validity of LandFlux-EVAL over the TP.…”

“…The LandFlux-EVAL benchmark product was found to agree well with observation-based precipitation, in situ measurementsvalidated radiation (Shi and Liang, 2013a), and in situ measurements-validated LE product (Shi and Liang, 2014). From this point of view, it can be served as the reference dataset.…”

A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies

“…There are multiple factors resulting in the variations at different spatial and temporal scales. He et al (2013) found from the GLASS albedo product that a large decrease in surface albedo over Greenland after 2000 ((0.0024 yr (1 ) mainly occurred at Shi and Liang (2013) found that the albedo increase over Tibetan Plateau is highly correlated with the increase in snow cover. More studies are necessary to evaluate the causes of the variations in albedo.…”

Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

“…According to Equation (6), the surface broadband albedo can be estimated from narrowband albedo [47], () n n c      (13) where is the band number of satellite sensors, is the narrow-to-broadband conversion coefficient of band .…”

“…The global land surface albedo changes with natural processes and human activities [6], such as deforestation [7,8], desertification [9], wildfire [10], and the decreasing of northern-hemisphere snow and sea-ice [11][12][13]. These changes in surface albedo also influence regional and global weather [14] in which even tiny variations of surface albedo can feedback to the climate system and affect the global and regional climate patterns.…”