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Snow Phenology And Its Response To Climate In Northeastern China

Posted on:2022-02-25Degree:MasterType:Thesis
Country:ChinaCandidate:H GuoFull Text:PDF
GTID:2480306491482854Subject:Geography
Abstract/Summary:PDF Full Text Request
As one of the three stable snow cover regions in China,the seasonal snow cover participate in the water cycle,energy balance,glacier melting of the globe and has a far-reaching influence in Northeastern China.Snow cover is an important fresh water supply,on the one hand,it has the function of water storage and heat preservation,and provides favorable conditions for the production and life of local people.On the other hand,with the general trend of global warming,the increase of meltwater in spring may bring serious natural disasters such as floods,laying serious hidden dangers to the safety of people's lives and property.Therefore,it is of great significance to explore the spatio-temporal distribution characteristics and variation of snow cover,to analyze the change of snow phenology and its response relationship with precipitation,temperature and other climatic factors,so as to guide agricultural irrigation,regional water resource management,climate change and prediction in Northeastern China.In this paper,firstly,the conditional probability interpolation method based on the space-time cube is used to generate daily cloud-free snow product with 500 m resolution in Northeastern China of HY01-HY17 hydrological years,and the accuracy is verified by using the station data;secondly,Snow Cover Days(SCD),Snow Cover Onset Dates(SCOD)and Snow Cover Ending Dates(SCED)are calculated pixel by pixel,and which are analyzed regularities of spatio-temporal variation respectively.Finally,the spatio-temporal variation of annual hydrological precipitation,temperature and the dynamic response process to snow phenological parameters in Northeastern China of HY01-HY17 are systematically analyzed.The results show that:(1)Station data(2013-2017)are used to verify the daily cloudless snow products of 500 m spatial resolution in Northeastern China obtained by the conditional probability interpolation method based on the space-time cube.From the accuracy verification results,the overall accuracy(OA)is less than 0.95,and the underestimation error(UE)and overestimation error(OE)are both lower than 0.03.The results show that the cloudless product has high precision.(2)From the snow phenological parameters(SCD,SCOD and SCED)of space-time variation,in HY01-HY17 hydrological years,the SCD value of Northeastern China in plain area is obviously less than that in mountain area,which is consistent with the distribution trend of topography and geomorphology.It presents the distribution characteristics of "mountain-high SCD,plain-low SCD",and has obvious zonal differentiation of "high latitude-high SCD,low latitude-low SCD";From the different underlying surfaces,the variation trend of SCD in the forested and non-forested areas are consistent with that in the study area,which both are showed a slow increasing trend,but the mean SCD in the forested areas is significantly higher than that in the non-forested areas;From the change trend,SCD shows an increasing trend.As far as SCOD is concerned,a large area of snow began to appear in most areas from October and later,and with the increase of latitude,the earlier SCOD appeared,the greater the probability.It can be seen from the interannual variation of SCOD that the start date of snow cover varies in different hydrological years,and the start date of snow cover in the same space and different spatial positions varies,but he change trend of the SCOD in the forested and non-forested areas are consistent with that in the study area.The spatial distribution of SCED is obvious and was consistent with that of SCD.The terrain distribution shows the phenomenon of "high SCED in mountainous area,low SCED in plain",and the latitude zonal differentiation of "high SCED in high latitude,low SCED in low latitude".From the change trend of SCED,the SCED in Northeastern China shows a trend of postponement.The SCED in the forested area is obviously later than that in the non-forested area,the non-forested area basically disappeared in January of the next year,and SCED of the forested area is from the beginning of March to the end of April of the next year.(3)From the perspective of the spatio-temporal distribution of climatic factors,the spatial distribution shows a decreasing trend from east to west.The regions with more precipitation are mainly concentrated in the southeastern hilly areas of Liaodong,the Xiaoxing'an Mountains and the Changbai Mountains,while the regions with less precipitation are mainly distributed in the Horqin Sandy Land and the Inner Mongolia Plateau.In recent 17 years,the interannual precipitation shows a fluctuating upward trend.In terms of temperature,the spatial distribution of annual mean temperature in Northeastern China has obvious polarization phenomenon.The higher the latitude,the lower the temperature.The temperature in the Daxing'an Mountains and Xiaoxing'an Mountains is obviously lower than that in the Liaohe Plain and Songnen Plain.From the perspective of inter-annual variation trend,the temperature value shows a slow decreasing trend in the past 17 years.(4)From the dynamic response relationship between snow phenological parameters and climatic factors,SCD and SCED are all positively correlated with precipitation,that is to say,the more precipitation,the longer the SCD and the SCED are delayed.The SCD and SCED are negatively correlated with temperature,namely,the lower the temperature,the longer the SCD,the later the SCED.SCD,SCOD and SCED in Northeastern China are mainly affected by non-climatic factors.The influence of climatic factors accounts for 39.69%,6.03% and 18.82,respectively.Among the climatic factors,precipitation and temperature strong drive has the greatest influence on SCD,SCOD and SCED,followed by mean temperature and precipitation alone,and precipitation and temperature weak drive has little impact.
Keywords/Search Tags:Northeastern China, snow phenology, climatic factors, spatio-temporal variation, driven response
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