Land Surface Albedo Variations in Sanjiang Plain from 1982 to 2015: Assessing with GLASS Data

As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth’s surface energy budget(SEB). Since the Sanjiang Plain has been severely affected by human activities(e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite(GLASS) broadband surface albedo product. The results showed that: 1) an increasing annual trend(+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend(+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes.

Evaluation of satellite land surface albedo products over China using ground-measurements

Land surface albedo(LSA)is an important parameter in surface energy balance and global climate change.It has been used in the fields of energy budgets,climate dynamics,and land surface processes.To apply satellite LSA products more widely,the product accuracy needs to be evaluated at different scales and under atmospheric and surface conditions.This study validates and analyzes the errors of the LSA datasets from the Global LAnd Surface Satellites(GLASS)product,the European Space Agency’s Earth Observation Envelope Programme(GlobAlbedo),the Quality Assurance for Essential Climate Variables(QA4ECV)project,the Gap-filled Snow-free Bidirectional Reflectance Distribution Function(BRDF)parameters product(MCD43GF),and the Satellite Application Facility on Climate Monitoring(CM SAF)Albedo dataset from the AVHRR data(CLARA-SAL)against the Chinese Ecosystem Research Network(CERN)measurements at different spatiotemporal scales over China from 2005 to 2015.The results show that LSA estimated by GLASS agrees well with the CERN measurements on a continental scale.The GLASS product is characterized by a correlation coefficient of 0.80,a root-mean-square error of 0.09,and a mean absolute error of 0.06.The consistency between GLASS,GlobAlbedo,and CLARA-SAL is slightly lower over the regions with high aerosol optical depth(AOD)(e.g.Sichuan Basin,northern China)and high cloud cover compared with that in regions with lower AOD and low cloud cover.The estimation errors are related to varying atmospheric and surface conditions and increase with increasing AOD and cloud cover and decreasing enhanced vegetation index.Therefore,algorithms under complex atmospheric and surface conditions(e.g.high AOD,sparse vegetation)should be optimized to improve the accuracy of LSA products.

Preliminary evaluation of the long-term GLASS albedo product

Land surface albedo is an important parameter to describe the radiant forcing in the climate system.A long-time series of global albedo products is needed to understand the mechanism of climate change.Aiming to support global change and Earth system studies,GLASS(Global LAnd Surface Satellites)provides long-term global land surface albedo product from 1981 to 2010,which are generated from multisource remote sensing data and newly developed algorithms.It is critical to assess the quality of the GLASS product when it is released to the public.This paper first introduced the algorithms and then analyzed the integrity,accuracy,and robustness of the GLASS albedo product.The results show that the GLASS albedo product is a gapless,long-term continuous,and self-consistent data-set with an accuracy similar to that of the widely acknowledged MODIS MCD43 product.The quality flag,which is provided along with the black-sky and white-sky albedo,gives a pertinent indication of the expected uncertainty in the product.