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.

Parameterization of land surface albedo

Remote measurements of Earth’s surface from ground, airborne, and spaceborne instruments show that its albedo is highly variable and is sensitive to solar zenith angle（SZA） and atmospheric opacity. Using a validated radiative transfer calculating toolbox, DISORT and a bidirectional reflectance distribution function library, AMBRALS, a land surface albedo（LSA） lookup table（LUT） is produced with respect to SZA and aerosol optical depth. With the LUT, spectral and broadband LSA can be obtained at any given illumination geometries and atmospheric conditions. It provides a fast and accurate way to simulate surface reflectance over large temporal and spatial scales for climate study.

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.

Spatial Variation in CO_(2) Concentration Improves the Simulated Surface Air Temperature Increase in the Northern Hemisphere

The increasing concentration of atmospheric CO_(2) since the Industrial Revolution has affected surface air temperature.However,the impact of the spatial distribution of atmospheric CO_(2) concentration on surface air temperature biases remains highly unclear.By incorporating the spatial distribution of satellite-derived atmospheric CO_(2) concentration in the Beijing Normal University Earth System Model,this study investigated the increase in surface air temperature since the Industrial Revolution in the Northern Hemisphere(NH) under historical conditions from 1976-2005.In comparison with the increase in surface temperature simulated using a uniform distribution of CO_(2),simulation with a nonuniform distribution of CO_(2)produced better agreement with the Climatic Research Unit(CRU) data in the NH under the historical condition relative to the baseline over the period 1901-30.Hemispheric June-July-August(JJA) surface air temperature increased by 1.28℃ ±0.29℃ in simulations with a uniform distribution of CO_(2),by 1.00℃±0.24℃ in simulations with a non-uniform distribution of CO_(2),and by 0.24℃ in the CRU data.The decrease in downward shortwave radiation in the non-uniform CO_(2) simulation was primarily attributable to reduced warming in Eurasia,combined with feedbacks resulting from increased leaf area index(LAI) and latent heat fluxes.These effects were more pronounced in the non-uniform CO_(2)simulation compared to the uniform CO_(2) simulation.Results indicate that consideration of the spatial distribution of CO_(2)concentration can reduce the overestimated increase in surface air temperature simulated by Earth system models.

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.