Evaluation of Snow Depth and Snow Cover Fraction Simulated by Two Versions of the Flexible Global Ocean–Atmosphere–Land System Model

Based on historical runs,one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project （CMIP5）,the snow depth （SD） and snow cover fraction （SCF） simulated by two versions of the Flexible Global OceanAtmosphere-Land System （FGOALS） model,Grid-point Version 2 （g2） and Spectral Version 2 （s2）,were validated against observational data.The results revealed that the spatial pattern of SD and SCF over the Northern Hemisphere （NH） are simulated well by both models,except over the Tibetan Plateau,with the average spatial correlation coefficient over all months being around 0.7 and 0.8 for SD and SCF,respectively.Although the onset of snow accumulation is captured wellby the two models in terms of the annual cycle of SD and SCF,g2 overestimates SD/SCF over most mid-and high-latitude areas of the NH.Analysis showed that g2 produces lower temperatures than s2 because it considers the indirect effects of aerosols in its atmospheric component,which is the primary driver for the SD/SCF difference between the two models.In addition,both models simulate the significant decreasing trend of SCF well over （30°-70°N） in winter during the period 1971-94.However,as g2 has a weak response to an increase in the concentration of CO2 and lower climate sensitivity,it presents weaker interannual variation compared to s2.

Classification of snow cover days in western China and comparison with satellite remote sensing data

The daily snow cover data from 232 meteorological stations to the west of 105°E in China for the period 1951-2004 were used to classify the snow cover and analyze decadal variations of snow cover types in western China, and comparison was made between the observational data and those retrieved from passive microwave remote sensing data （SMMR and SSM/I） in 1980-2004. The results show that stable snow-covered areas included northern Xinjiang, the Tianshan Mountains, and the eastern Tibetan Plateau with more than 60 snow cover days; no snow cover was found in the center of the southern Xinjiang Basin, the Sichuan Basin, and southern Yunnan. In addition to the above-mentioned, there were unstable snow-covered areas in western China. Furthermore, the snow cover types in northern Xinjiang, the Tianshan Mountains, the Hexi Corridor, and the vast areas from Chengdu to Kunming were unchanged. In the 1980s, the south-north dividing line between the major snow-covered area and snow-free area advanced to its most southern position. The snow cover days calculated from satellite remote sensing were generally longer than those from observational data in western China, mainly in the higher-altitude mountains, the Hexi Corridor, and the western Sichuan Plateau.

Comparison and analysis of snow cover data based on dif-ferent definitions of snow cover days

In order to analyze the differences between the two snow cover data, the snow cover data of 884 meteorological stations in China from 1951 to 2005 are counted. The data include days of visual snow observation, snow depth, and snow cover durations, which vary according to different definitions of snow cover days. Two series of data, as defined by ＂snow depth＂ and by ＂weather obser- vation,＂ are investigated here. Our results show that there is no apparent difference between them in east China and the Xinjiang region, but in northeast China and the Tibetan Plateau the ＂weather observation＂ data vary by more than 10 days and the ＂snow depth＂ data vary by 0.4 cm. Especially in the Tibetan Plateau, there are at least 15 more days of＂weather observation＂ snow in most areas （sometimes more than 30 days）. There is an obvious difference in the snow cover data due to bimodal snowfall data in the Tibetan Plateau, which has peak snowfalls from September to October and from .April to May. At those times the temperature is too high for snow cover fol：mation mad only a few days have trace snow cover. Also, the characteristics and changing trends of snow cover are analyzed here based on the snow cover data of nine weather stations iri the northeast region of the Tibetan Plateau, by the Mann-KendaU test. The results show significantly fewer days of snow cover and shorter snow dtwations as defined by ＂snow depth＂ compared to that as defined by ＂weather observation.＂ Mann-Kendall tests of both series of snow cover durations show an abrupt change in 1987.

Analysis on the Climatic Change Characteristics of the Snow Cover Days and Its Influence Factors in Suzhou during Recent 50 Years

[Objective] The research aimed to study climatic variation characteristics of snow cover days and its influence factors in Suzhou of Anhui Province during recent 50 years. [Method] According to annual snow cover days and correlated data in Suzhou during 1961-2010, by using linear trend method, accumulative anomaly and complete correlation coefficient method, etc., the climatic variation characteristics of snow cover days and its influence factors in Suzhou were analyzed. [Result] In recent 50 years, the snow cover period in Suzhou presented shortened trend. Except days of snow cover (≥20 cm), the annual snow cover days at each thickness all showed varying degrees of decrease trend. The annual snow cover days had wavy decline trend, and the decline amplitude was 0.84 d/10 a. From the 1960s to prior period of the 1970s, the annual snow cover days presented increase trend. From middle and later periods of the 1970s to middle period of the 1980s, the snow cover days was less and gradually increased from later period of the 1980s to the early 1990s. From middle period of the 1990s to 2003, it entered into less snow period again. From 2004 to now, it presented oscillation of snowy and less-snow alternating. The main climatic factor which affected annual snow cover days in Suzhou was average temperature. The second one was average surface temperature. [Conclusion] The research provided theoretical basis for analyzing climate variation in Suzhou under the background of global climate warming.

Spatial distributions and interannual variations of snow cover over China in the last 40 years

By using the observational snow data of more than 700 weather stations,the interannual temporal and spatial characteristics of seasonal snow cover in China were analyzed.The results show that northern Xinjiang,northeastern China–Inner Mongolia,and the southwestern and southern portions of Tibetan Plateau are three regions in China with high seasonal snow cover and also an interannual anomaly of snow cover.According to the trend of both the snow depth and snow cover days,there are three changing patterns for the seasonal snow cover:The first type is that both snow depth and snow cover days simultaneously increase or decrease;this includes northern Xinjiang,middle and eastern Inner Mongolia,and so on.The second is that snow depth increases but snow cover days decrease;this type mainly locates in the eastern parts of the northeastern plain of China and the upper reaches of the Yangtze River.The last type is that snow depth decreases but snow cover days increase at the same time such as that in middle parts of Tibetan Plateau.Snow cover in China appears to have been having a slow increasing trend during the last 40 years.On the decadal scale,snow depth and snow cover days slightly increased in the 1960s and then decreased in the 1970s;they again turn to increasing in the 1980s and persist into 1990s.

Spatiotemporal Changes of Snow Depth in Western Jilin,China from 1987 to 2018

Seasonal snow cover is a key global climate and hydrological system component drawing considerable attention due to glob-al warming conditions.However,the spatiotemporal snow cover patterns are challenging in western Jilin,China due to natural condi-tions and sparse observation.Hence,this study investigated the spatiotemporal patterns of snow cover using fine-resolution passive mi-crowave(PMW)snow depth(SD)data from 1987 to 2018,and revealed the potential influence of climate factors on SD variations.The results indicated that the interannual range of SD was between 2.90 cm and 9.60 cm during the snowy winter seasons and the annual mean SD showed a slightly increasing trend(P>0.05)at a rate of 0.009 cm/yr.In snowmelt periods,the snow cover contributed to an increase in volumetric soil water,and the change in SD was significantly affected by air temperature.The correlation between SD and air temperature was negative,while the correlation between SD and precipitation was positive during December and March.In March,the correlation coefficient exceeded 0.5 in Zhenlai,Da’an,Qianan,and Qianguo counties.However,the SD and precipitation were neg-atively correlated over western Jilin in October,and several subregions presented a negative correlation between SD and precipitation in November and April.

Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains,China

Estimating the snow cover change in alpine mountainous areas(in which meteorological stations are typically lacking)is crucial for managing local water resources and constitutes the first step in evaluating the contribution of snowmelt to runoff and the water cycle.In this paper,taking the Jingou River Basin on the northern slope of the Tianshan Mountains,China as an example,we combined a new moderate-resolution imaging spectroradiometer(MODIS)snow cover extent product over China spanning from 2000 to 2020 with digital elevation model(DEM)data to study the change in snow cover and the hydrological response of runoff to snow cover change in the Jingou River Basin under the background of climate change through trend analysis,sensitivity analysis and other methods.The results indicate that from 2000 to 2020,the annual average temperature and annual precipitation in the study area increased and snow cover fraction(SCF)showed obvious signs of periodicity.Furthermore,there were significant regional differences in the spatial distribution of snow cover days(SCDs),which were numerous in the south of the basin and sparse in the central of the basin.Factors affecting the change in snow cover mainly included temperature,precipitation,elevation,slope and aspect.Compared to precipitation,temperature had a greater impact on SCF.The annual variation in SCF was limited above the elevation of 4200 m,but it fluctuated greatly below the elevation of 4200 m.These results can be used to establish prediction models of snowmelt and runoff for alpine mountainous areas with limited hydrological data,which can provide a scientific basis for the management and protection of water resources in alpine mountainous areas.

An Empirical Formula to Compute Snow Cover Fraction in GCMs

There exists great uncertainty in parameterizing snow cover fraction in most general circulation models (GCMs) using various empirical formulae, which has great influence on the performance of GCMs. This work reviews the commonly used relationships between region-averaged snow depth (or snow water equivalent) and snow cover extent (or fraction) and suggests a new empirical formula to compute snow cover fraction, which only depends on the domain-averaged snow depth, for GCMs with different horizontal resolution. The new empirical formula is deduced based on the 10-yr (1978-1987) 0.5°× 0.5° weekly snow depth data of the scanning multichannel microwave radiometer (SMMR) driven from the Nimbus-7 Satellite. Its validation to estimate snow cover for various GCM resolutions was tested using the climatology of NOAA satellite-observed snow cover.

Temporal-spatial characteristics of observed key parameters of snow cover in China during 1957-2009

Using observed snow cover dam from Chinese meteorological stations, this study indicated that annual mean snow depth, Snow Water Equivalent （SWE）, and snow density during 1957-2009 were 0.49 cm, 0.7 ram, and 0.14 g/cm3 over China as a whole, re- spectively. On average, they were all the smallest in the Qinghai-Tibetan Plateau （QTP）, and were greater in northwestern China （NW）. Spatially, the regions with greater annual mean snow depth and SWE were located in northeastern China including eastern Inner Mongolia （NE）, northern Xinjiang municipality, and a small fraction of southwestern QTP. Annual mean snow density was below 0.14 g/cm3 in most of China, and was higher in the QTP, NE, and NW. The trend analyses revealed that both annual mean snow depth and SWE presented increasing trends in NE, NW, the QTP, and China as a whole during 1957-2009. Although the trend in China as a whole was not significant, the amplitude of variation became increasingly greater in the second half of the 20th century. Spatially, the statistically significant （95%-level） positive trends for annual mean snow depth were located in western and northem NE, northwestem Xinjiang municipality, and northeastem QTP. The distribution of positive and negative trends for annu- al mean SWE were similar to that of snow depth in position, but not in range. The range with positive trends of SWE was not as large as that of snow depth, but the range with negative trends was larger.

Changes in snow parameterization over typical vegetation in the Northern Hemisphere

季节性降雪对气候变化很敏感,常被当作气候变化的信号.由于其局地特征差异显著,不同下垫面类型的积雪过程也不尽相同.北半球中高纬度的典型下垫面(开阔灌丛,常绿针叶林和混交林)在积雪覆盖率和雪深之间有着独特的关系曲线,这种关系不仅代表了积雪过程和融雪过程的特征变化,更能用于模式进行积雪预测.研究发现,北半球中高纬度的增温改变了积雪参数化关系,进一步影响了局地能量和水循环,造成开阔灌丛的北缩和常绿针叶林及混交林的扩张.然而,目前模式中的积雪参数化并不能很好地再现全球变暖影响下融雪阶段出现的加速融化过程,并且进一步影响对春季融雪的生态影响的理解.

Spatial and Temporal Variability of Snow Depth Derived from Passive Microwave Remote Sensing Data in Kazakhstan

Snow cover plays an important role in the hydrological cycle and water management in Kazakhstan. However, traditional observations do not meet current needs. In this study, a snow depth retrieval equation was developed based on passive microwave remote sensing data. The average snow depth in winter （ASDW）, snow cover duration （SCD）, monthly maximum snow depth （MMSD）, and annual average snow depth （AASD） were derived for each year to monitor the spatial and temporal snow distributions. The SCD exhibited significant spatial variations from 30 to 250 days. The longest SCD was found in the mountainous area in eastern Kazakhstan, reaching values between 200 and 250 days in 2005. The AASD increased from the south to the north and maintained latitudinal zonality. The MMSD in most areas ranged from 20 to 30 cm. The ASDW values ranged regularity of latitudinal zonality from 15 to 20 cm in the eastern region and were characterized by spatial The ASDW in the mountainous area often exceeded 20 cm.

An estimation method of soil wind erosion in Inner Mongolia of China based on geographic information system and remote sensing

Studies of wind erosion based on Geographic Information System（GIS） and Remote Sensing（RS） have not attracted sufficient attention because they are limited by natural and scientific factors.Few studies have been conducted to estimate the intensity of large-scale wind erosion in Inner Mongolia,China.In the present study,a new model based on five factors including the number of snow cover days,soil erodibility,aridity,vegetation index and wind field intensity was developed to quantitatively estimate the amount of wind erosion.The results showed that wind erosion widely existed in Inner Mongolia.It covers an area of approximately 90×104 km2,accounting for 80% of the study region.During 1985–2011,wind erosion has aggravated over the entire region of Inner Mongolia,which was indicated by enlarged zones of erosion at severe,intensive and mild levels.In Inner Mongolia,a distinct spatial differentiation of wind erosion intensity was noted.The distribution of change intensity exhibited a downward trend that decreased from severe increase in the southwest to mild decrease in the northeast of the region.Zones occupied by barren land or sparse vegetation showed the most severe erosion,followed by land occupied by open shrubbery.Grasslands would have the most dramatic potential for changes in the future because these areas showed the largest fluctuation range of change intensity.In addition,a significantly negative relation was noted between change intensity and land slope.The relation between soil type and change intensity differed with the content of Ca CO3 and the surface composition of sandy,loamy and clayey soils with particle sizes of 0–1 cm.The results have certain significance for understanding the mechanism and change process of wind erosion that has occurred during the study period.Therefore,the present study can provide a scientific basis for the prevention and treatment of wind erosion in Inner Mongolia.

Decadal Relationship Between Atmospheric Heat Source and Winter-Spring Snow Cover over the Tibetan Plateau and Rainfall in East China

By using a reverse computation method and the NCEP/NCAR daily reanalysis data from 1960 to 2004, the atmospheric heat source （AHS） was calculated and analyzed. The results show that AHS over the Tibetan Plateau （TP） and its neighboring areas takes on a persistent downtrend in spring and summer during the foregone 50 years, especially the latest 20 years. Snow depth at 50 stations over the TP in winter and spring presents an increase, especially the spring snow depth exhibits a sharp increase in the late 1970s. A close negative correlation exists between snow cover and AHS over the TP and its neighboring areas, as revealed by an SVD analysis, namely if there is more snow over the TP in winter and spring, then the weaker AHS would appear over the TP in spring and summer. The SVD analysis between AHS over the TP in spring and summer and rainfall at 160 stations indicates that the former has a negative correlation with summer precipitation in the middle and lower reaches of the Yangtze River, and a positive correlation with that in South China and North China. The SVD analysis of both snow cover over the TP in winter and spring and rainfall at the same 160 stations indicates that the former has a marked positive correlation with precipitation in the middle and lower reaches of the Yangtze River, and a reversed correlation in South China and North China. On the decadal scale, the AHS and winter and spring snow cover over the TP have a close correlation with the decadal precipitation pattern shift （southern flood and northern drought） in East China. The mechanism on how the AHS over the TP influences rainfall in East China is discussed. The weakening of AHS over the TP in spring and summer reduces the thermodynamic difference between ocean and continent, leading to a weaker East Asian summer monsoon, which brings more water vapor to the Yangtze River Valley and less water vapor to North China. Meanwhile, the weakening of AHS over the TP renders the position of the subtropical high further westward and the rain belt lasting longer in the Yangtze River Valley, which causes more rain there and less rain in North China, thus showing the pattern of ＂southern flood and northern drought＂ in the latest 20 years. It is inferred that the increase of snow cover over the TP brings about the reduction of surface temperature and then surface heat source, leading eventually to the weakening of AHS there.

青藏高原地区积雪与雪线高度时空变化研究

积雪对气候变化具有高度敏感性,研究积雪变化对区域水循环及生态环境演变具有重要意义。基于遥感数据和河流水系分布情况,将青藏高原划分为12个子流域,分析了青藏高原及其子流域的积雪深度、积雪覆盖率、雪线高度的时空变化特征。结果表明:①1979—2020年青藏高原积雪深度呈明显降低趋势,空间上积雪深度由中心区域向四周递增,阿姆河流域多年平均积雪深度最大,印度河流域的次之。②2000-2015年青藏高原多年平均积雪覆盖率为29.66%,呈平缓的下降趋势,印度河流域的积雪覆盖率最大,高达39.83%,塔里木河的次之。③青藏高原雪线高度的变化范围为[4700,5000]m,夏季的雪线高度整体偏高,在8月达到最大值;各子流域雪线高度由大到小的排序依次为雅鲁藏布江流域、印度河流域、河西流域、恒河流域、长江流域、怒江流域、阿姆河流域、塔里木河流域、柴达木河流域、内河流域、黄河流域、澜沧江流域。研究结果对寒区水资源管理和生态环境可持续发展具有重要意义。

基于MODIS积雪覆盖度数据的青藏高原两套被动微波雪深产品降尺度对比研究

积雪深度(雪深)是流域水量平衡、融雪径流模拟等模型的重要输入参数,被动微波雪深遥感产品被广泛用于雪深监测。然而,由于山区积雪时空异质性强,这些空间分辨率较粗的雪深产品受到极大限制。本研究基于MODIS积雪覆盖度数据,根据经验融合规则以及积雪衰退曲线对“中国雪深长时间序列数据集”的两套雪深产品(由SMMR、SSMI和SSMI/S反演的称为Che_SSMI/S产品;由AMSR-2反演称为Che_AMSR2产品)进行空间降尺度,最终获得青藏高原500 m降尺度雪深数据(Che_SSMI/S_NSD和Che_AMSR2_NSD)。利用6景Landsat-8影像对两套降尺度雪深数据进行对比分析,结果发现两套降尺度数据与Landsat-8影像积雪空间分布吻合度均较高。与29个气象站点雪深数据相比,Che_AMSR2_NSD与实测雪深更为接近,相关系数(R)达到0.72,均方根误差(RMSE)为3.21 cm;而Che_SSMI/S_NSD精度较低(R=0.67,RMSE=4.44 cm),可能是由于采用不同传感器亮温数据的两套原始雪深产品精度不同所致。除此之外,实验表明被动微波雪深产品降尺度精度还受积雪深度、积雪期等因素的影响。当积雪深度小于10 cm且在积雪稳定期时,两套雪深产品降尺度精度均最高;当积雪深度大于30 cm且在积雪消融期时,两套雪深产品降尺度精度均最低。通过对比两套降尺度雪深产品,有助于全面地了解青藏高原雪深时空分布变化及其应用提供数据支持。

基于积雪数据的HBV模型改进及应用

大渡河流域内站点分布较少,历史观测数据不足,给该地区的融雪径流预报带来困难。基于欧洲中期天气预报中心提供的最新一代高分辨率陆面再分析数据集ERA5-Land,将积雪覆盖率和积雪平均深度引入度日因子雪量计算公式中,对HBV模型的积融雪模块进行改进,以提升融雪径流计算的可靠性。以大渡河上游为研究对象,选取1961—2018年的水文气象资料对模型进行率定和验证,并以2019年为例进行试预报研究。结果表明,通过引入ERA5-Land再分析数据,以及对积融雪模块进行改进,发挥了其在模拟积融雪上的优势,有效提升了融雪径流预报精度,对大渡河流域具有适用性。研究成果可为稀缺资料地区融雪径流模拟预报提供经验。

基于多源数据的西藏地区积雪变化趋势分析

利用1980—2009年气象台站的观测数据、北半球NOAA周积雪产品和2001—2010年500m分辨率的EOS/MODIS积雪产品等多源资料,从不同角度对近30a来西藏区域积雪变化趋势进行了分析.结果表明:不同资料分析均显示,近30a来西藏地区积雪不断减少,尤其以近些年较为明显.近30a积雪日数、最大积雪深度总体上呈现下降趋势,尤其是进入21世纪以来,下降趋势非常明显.从秋冬春季节的积雪变化趋势来看,冬、春两季的积雪在减少,而秋季在增多,这些变化趋势都与各季节的气温和降水密切相关.NOAA资料显示,近30a来西藏地区的积雪覆盖面积正在逐步减少;季节变化略有不同,春、秋两季略呈上升趋势,冬、夏两季在减少,且夏季减少趋势较明显.MODIS资料分析表明,近10a来西藏地区的积雪总体呈下降趋势,尤其是2007年下半年开始下降明显.秋季的积雪在增加,冬、春、夏三季的积雪趋于减少,且春季的下降趋势最明显,其次为冬季,夏季的减少幅度最小.不同海拔的积雪都有减少趋势,最明显的是海拔4 000～5 000m的积雪,其次是海拔5 000～6 000m段.按地理区域分析,近10a来西藏东、西、中3个区域的积雪都呈减少趋势,其中西部的下降趋势最明显,其次为中部,东部相对较稳定.

天山季节性积雪稳定期雪密度与积累速率的观测分析

利用Snow Fork雪特性分析仪测量的天山积雪雪崩站2009年2月21-26日及2010年1月26-31日雪特性数据,分析了季节性积雪稳定期内积雪垂直剖面密度的变化特征及其随降雪沉积时间和雪层深度的变化规律.结果表明:季节性积雪稳定期内,积雪剖面密度中部最大,表层和底层密度较低;新雪层密度随时间的推移增加速率逐渐增大,细粒雪层、中粒雪层、粗粒雪层和深霜层密度随时间推移增加速率逐渐减小;不同深度雪层密度随深度变化呈现出规律性的变化.通过建立的雪层密度随降雪沉积时间和积雪深度而变化的经验关系式,可以应用两个极易获取的积雪参数(即降雪沉积时间和积雪深度)来推算不同深度的雪层密度.

基于不同积雪日定义的积雪资料比较分析

利用天气现象定义与积雪深度定义两种方法对全国884个台站的积雪日资料进行统计处理,分别整理出每一台站各个积雪年的积雪日数、积雪深度、初终雪间隔日数3个要素的两套数据,并进行对比分析.结果表明:在全国东部大部分地区及新疆地区,两种数据差别不大,但在东北及青藏高原两套数据的差别较大.在积雪日数的比较中,两种数据在东北及青藏高原的差别基本都在10d以上,积雪深度的差别在0.4cm以上,初终雪间隔日数的差别以青藏高原最明显,大部分地区的差别在15d以上,甚至有达到30d以上的区域.对青藏高原东北边坡代表站的积雪平均值进行M-K突变检验发现,积雪深度定义的积雪日数与间隔日数减少趋势略大于天气现象定义统计的数值;而在积雪深度的比较中则相反.两种定义的积雪间隔日数均在1987年出现突变.

新疆阿勒泰地区积雪变化特征及其对冻土的影响

依据新疆阿勒泰地区气象台站观测的1961-2011年最大积雪深度、积雪日数资料与安装在库威水文站的雪特性站观测的积雪密度资料,讨论了新疆阿勒泰地区积雪的变化特征.结果表明:阿勒泰地区近50a来最大积雪深度变化均呈显著增加的趋势,且西部最大积雪深增加趋势大于东部.积雪日数变化较为复杂,在空间分布上有差异,位于最东面的富蕴和青河50a来积雪日数呈减少趋势,其余各站均为增加趋势,且东部历年平均积雪日数略高于西部,积雪日数的增加趋势比最大积雪深度增长得平缓.2011年8月-2012年9月在阿勒泰额尔齐斯河上游库威水文站架设的雪特性站观测资料表明,在额尔齐斯河源头高山区冬季积雪主要是空心化的密实化过程,升华可能是其主要的物质损失过程,引起升华的主要气象要素是气温、风速和水汽压.各站月最大冻结深度与海拔关系较为密切,随海拔的增加而增大.积雪20cm厚是积雪对下伏土壤冻结影响的一个界限,积雪厚度超过20cm就有一定的保温作用;积雪超过40cm时,气温变化对下伏土壤冻结的影响保持稳定,冻结深度也达到稳定值;但当积雪厚度超过70cm之后,冻结深度会再次发生变化,可能是由于地温从下向上的影响或地温不能与气温交换而产生的又一次变化.