Spatial And Temporal Variation Of Snow Cover In China Based On In-situ And IMS Remote Sensing Data

As an important part of cryosphere, snow cover in winter covers 46 million km2 of the mid-and high-latitude areas on the Northern Hemisphere. The high reflectance of snow cover influencing the global & regional radiation & energy balance is an important indicator of climatic change. In the wake of the aggravation of global warming, the change of cryosphere becomes an increasingly concerned issue of researchers. In accordance with the 5th assessment report on the global climate change issued by IPCC, the continuous increasing of CO2 concentration will be followed by the continuing decrease of the global snow cover. Besides, snow cover also has an impact on other aspects of the human life and is able to cause severe snow and ice disasters. As the snow cover in China is widespread, the analysis of the spatial and temporal variation of snow cover in China is a necessary research. The analysis of meteorological observation data and remote sensing data are two main ways of studying the spatial and temporal distribution of snow cover. Having their merits and demerits, the two methods can well complement with each other.Focusing on the change of snow cover days, this paper makes use of the daily depth data of snow cover from 722 meteorological stations in China (1952-2010) and the daily IMS remote-sensing data (2007-2014) to study the parameters of snow cover in China from different perspectives. The main analysis content based on the snow cover data of meteorological stations includes:(1) The days with snow cover of meteorological stations, variable coefficient of days with snow cover, spatial distribution of the lasting days and times of snow cover, and the Mann-Kendall temporal-and-spatial variation trend of the said items beside of times of snow cover. (2) the research on annual variance of snow cover through calculating the monthly snow cover ratio of meteorological stations and the calculation of the distribution rule and variation trend of the first and final days of snow cover; (3) the years containing abnormal days with snow cover and the abnormal first and final days with snow cover; (4) the correlativity between days with snow cover of meteorological stations, and the temperature, precipitation and Arctic oscillation. The main research content based on the IMS snow and ice products include:(1) examine the accuracy of IMS snow and ice products; (2) the change of snow cover area in the whole China, and in Northeast China, North of Xinjiang and Qinghai-Tibet Plateau 2007-2014; (3) the comparison between the IMS snow and ice products with a resolution of lkm and that of 4km; (4) the distribution of days with snow cover in China 2017-2014, and the comparison between the days with snow cover shown by IMS snow and ice products and the days with snow cover monitored by meteorological stations.The research results:(1) the meteorological stations with the most days with snow cover are located in the north of Northeast China, the north of Xinjiang, and the Bayan Har Mountains region in the northeast of Qinghai-Tibet Plateau; but the annual variance of snow cover in Qinghai-Tibet Plateau is significantly different from other regions:the seasonality of annual variance is not apparent, some meteorological stations see snow cover in 12 months and the lasting days with snow cover are less and the times of snow cover are quite many. (2) Among meteorological stations having over 10 days with snow cover, those having an increasing number of days with snow cover and those having a decreasing number of days with snow cover are half and half; but the quantity of meteorological stations with a 95% significance of decreasing trend of snow cover days is more that of increasing trend; the decreasing trend of days with snow cover of those meteorological stations in Shandong Province, Changbai Mountain& Northern Heilongjiang are quite apparent, and the increasing trend prevails among the meteorological stations in Qinghai-Tibet Plateau and Northeast Plain. (3) The stability of snow cover reduces and 57% of meteorological stations show a decreasing trend of lasting days with snow cover. Snow cover periods of meteorological stations also shorten. Except the north of Hebei and Liaodong Peninsula, the first days of meteorological stations in other regions are postponed; and the final days with snow cover of the most of the meteorological stations in China are advanced significantly. (4) There are abnormal days with snow cover in 10 years among the past 6 decades. It is positive anomaly-oriented before 1980s and negative anomaly-oriented since this century. Meanwhile, there are abnormal first days with snow cover in 8 years and abnormal final days with snow cover in 12 years. The abnormal final days with snow cover year in recent 20 years are all advanced anomaly-oriented. (5) the days with snow cover of almost all meteorological stations in China are significantly positively correlated with the snow fall amount and snow fall days; except Inner Mongolian Plateau, the days with snow cover of most meteorological stations are significantly positively correlated with the days with subzero temperature, and significantly negatively correlated with the average temperature during the snow cover period. The response of the days with snow cover in different regions to the arctic oscillation is different. The positive correlation in the regions east to 100° E longitude of the increasing longitude decreases and the negative correlation increases continually. Regions west to 100° E are opposite. (6) The accuracy of IMS snow and ice products is high, the general accuracy can reach 90% or so; the independent monitoring over snow cover is allowed and it’s possible to overestimate the snow cover area. (7) The annual periodicity of snow cover area in China is apparent, but the maximum average monthly snow cover area in winter sees a sharp flotation within the range of 3-5 million km2. (8) Compared with the spatial interpolation, the remote sensing data is better to reflect the distribution of days with snow cover in China; especially in the western regions where meteorological stations are sparse and the spatial autocorrelation index of days with snow cover of those meteorological stations are lower, the IMS snow and ice products are well corresponding with the meteorological station data in terms of days with snow cover.