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

Abstract

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.

Generating a Long-Term Spatiotemporally Continuous Melt Pond Fraction Dataset for Arctic Sea Ice Using an Artificial Neural Network and a Statistical-Based Temporal Filter

“…The temporal span and spatiotemporal continuity are crucial characteristics of MPF datasets for Arctic sea ice, which influence the reliability of the long-term trends derived from satellite observations. As most of the geophysical parameters of the Earth vary with climatic and environmental factors, the trends of the geophysical parameters can be significantly influenced by the general circulation and atmospheric oscillations [69], as well as the data gaps caused by cloud obscuration [67], and thus datasets with longer temporal span and more spatiotemporal continuity are required to more accurately determine the MPF trend.…”

Reconstruction of Historical Land Surface Albedo Changes in China From 850 to 2015 Using Land Use Harmonization Data and Albedo Look‐Up Maps

“…It has also been demonstrated that the snow cover extent and fraction of diffuse skylight in China varied in the recent decades (He & Wang, 2020; Tan et al., 2019). Especially, changes in snow cover extent can cause large differences in land surface albedo; they can also amplify land surface albedo changes caused by land cover type conversions (e.g., land reclamation, deforestation, and urbanization) (Li et al., 2020). The magnitude of the radiative forcing induced by land surface albedo changes may be underestimated if changes in snow cover are not considered (Zhai et al., 2014).…”

“…A variety of land surface albedo data sets were derived using remote‐sensing data; these include the Global Land Surface Satellite (GLASS) (Liu et al., 2013; Qu et al., 2014, 2016), Cloud, Albedo, and Radiation (CLARA) (Karlsson et al., 2017; Riihelä et al., 2013), Moderate Resolution Imaging Spectroradiometer (MODIS) (Schaaf et al., 2002; Wang et al., 2018), Visible Infrared Imaging Radiometer (VIIRS) (Liu et al., 2017; Wang et al., 2013), and Landsat data (He et al., 2018; Shuai et al., 2014). Recently, land surface albedo trends on global (He et al., 2014; Li, Ma et al., 2018) and regional scales (e.g., Loess Plateau (Zhai et al., 2015), Qinghai‐Tibet Plateau (Li et al., 2014), Sanjiang Plain (Li et al., 2020), and northern China (Hu et al., 2019)) have been analyzed using these data sets. However, because land surface albedo before the satellite era cannot be directly acquired by measurements, historical land surface albedo changes must be obtained using reconstructions and model simulations (Boisier et al., 2013).…”

Spatiotemporal variation in rice evapotranspiration under the influence of rice expansion: a case study in the Sanjiang Plain, Northeast China

“…Many studies have focused on the climatic and environmental changes on the Sanjiang Plain, especially on the variations in albedo, precipitation and land cover (X. Li et al, 2020 ;Fu et al, 2016 ;Dong et al, 2015 ). Some studies have also considered the cooling effect of rice field expansion on local surface temperature (T. Liu et al, 2018 ;Huang et al, 2022 ;G.…”