Remote Sensing-Based Simulation of Snow Grain Size and Spatial–Temporal Variation Characteristics of Northeast China from 2001 to 2019

• Published in: Remote sensing (Basel, Switzerland) Vol. 15; no. 20; p. 4970
• Main Authors: Zhang, Fan, Zhang, Lijuan, Zheng, Yanjiao, Wang, Shiwen, Huang, Yutao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2023
• Subjects: Albedo; Algorithms; ART model; Climate change; Coefficient of variation; Cryosphere; Drought; Ecological effects; Electromagnetic absorption; Environmental security; Grain size; Ground-based observation; Hydrologic cycle; Hydrology; Mathematical models; Model accuracy; MODIS; northeast China; Parameters; Particle size; Radiative forcing; Radiative transfer; Remote sensing; Satellites; Simulation; Snow; snow grain size; Spatial analysis; Spatial distribution; Temporal variations; Urban areas; China
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15204970

The size of snow grains is an important parameter in cryosphere studies. It is the main parameter affecting snow albedo and can have a feedback effect on regional climate change, the water cycle and ecological security. Larger snow grains increase the likelihood of light absorption and are important for passive microwave remote sensing, snow physics and hydrological modelling. Snow models would benefit from more observations of surface grain size. This paper uses an asymptotic radiative transfer model (ART model) based on MOD09GA ground reflectance data. A simulation of snow grain size (SGS) in northeast China from 2001 to 2019 was carried out using a two-channel algorithm. We verified the accuracy of the inversion results by using ground-based observations to obtain stratified snow grain sizes at 48 collection sites in northeastern China. Furthermore, we analysed the spatial and temporal trends of snow grain size in Northeastern China. The results show that the ART model has good accuracy in inverting snow grain size, with an RMSD of 65 μm, which showed a non-significant increasing trend from 2001 to 2019 in northeast China. The annual average SGS distribution ranged from 430.83 to 452.38 μm in northeast China, 2001–2019. The mean value was 441.78 μm, with an annual increase of 0.26 μm/a, showing a non-significant increasing trend and a coefficient of variation of 0.014. The simulations show that there is also intermonth variation in SGS, with December having the largest snow grain size with a mean value of 453.92 μm, followed by January and February with 450.77 μm and 417.78 μm, respectively. The overall spatial distribution of SGS in the northeastern region shows the characteristics of being high in the north and low in the south, with values ranging from 380.248 μm to 497.141 μm. Overall, we clarified the size and distribution of snow grains over a long time series in the northeast. The results are key to an accurate evaluation of their effect on snow–ice albedo and their radiative forcing effect.