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.

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.

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.

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.

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.

Investigation of Spatial and Temporal Distribution of Snow Cover by Using Satellite Imagery (Case Study: Sheshpirdam Basin)

About one third of the water needed for agriculture in the world is generated by melting snow. Snow cover, surface and ground water recharge are considered as sustainable and renewable resources. It is therefore necessary to identify and study these criteria. The aim of this study is to determine the spatial and temporal distribution of snow cover in the district of the Sheshpir basin in Fars province (in south of Iran). Ground-based observation of snow covers, especially in mountainous areas, is associated with many problems due to the insufficient accuracy of optical observation, as opposed to digital observation. Therefore, GIS and remote sensing technology can be partially effective in solving this problem. Images of Landsat 5TM and Landsat 7TM satellites were used to derive snow cover maps. The images in ENVI 4.8 software were classified by using the maximum likelihood algorithm. Other spatial analyses were performed in ARC-GIS 9.3 software. The maximum likelihood method was accuracy assessed by operation points of testing. The least and the average of overall accuracy of produced maps were found to be 91% and 98%, respectively. This demonstrates that the maximum likelihood method has high performance in the classification of images. Overall snow cover and the review of terrain through the years 2008-2009 and 2009-2010 showed that snow cover begins to accumulate in November and reaches its highest magnitude in February. Finally, no trace of snow can be observed on the surface of the basin in the month of May. By average, 34% of the basin is covered in snow from November through to May.

Comparison of Three Commonly Used Equations for Calculating Local Scour Depth around Bridge Pier under Ice Covered Flow Condition

A precise prediction of maximum scour depth around bridge foundations under ice covered condition is crucial for their safe design because underestimation may result in bridge failure and over-estimation will lead to unnecessary construction costs. Compared to pier scour depth predictions within an open channel, few studies have attempted to predict the extent of pier scour depth under ice-covered condition. The present work examines scour under ice by using a series of clear-water flume experiments employing two adjacent circular bridge piers in a uniform bed were exposed to open channel and both rough and smooth ice covered channels. The measured scour depths were compared to three commonly used bridge scour equations including Gao’s simplified equation, the HEC-18/Jones equation, and the Froehlich Design Equation. The present study has several advantages as it adds to the understanding of the physics of bridge pier scour under ice cover flow condition, it checks the validity and reliability of commonly used bridge pier equations, and it reveals whether they are valid for the case of scour under ice-covered flow conditions. In addition, it explains how accurately an equation developed for scour under open channel flow can predict scour around bridge piers under ice-covered flow condition.

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.

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.

新疆北疆最大积雪深度EOF展开场的时间变化规律

应用新疆北疆20个站1961-2006年46 a积雪资料,对最大积雪深度进行EOF展开场的时间变化规律的研究.结果表明:北疆最大积雪深度空间分布具有一致性,同时存在纬向上的反位相变化和西北-东南方向上的反位相变化.第一特征向量场主导了北疆最大积雪深度的年代际变化趋势,而代表北疆平均最大积雪深度空间上一致性的第一特征向量场年际增加趋势十分显著,1983年代之前北疆大多数年份最大积雪深度普遍偏浅,1997年之后普遍偏深.用Mann-Kendall法对其做突变检验发现,第一特征向量时间系数在1997年冬季发生了突变;而代表纬向上反位相关系的第二特征向量场虽然有增加趋势,但趋势不显著,代表西北-东南方向上的反位相关系的第三特征向量场没有明显的增减趋势.

Measuring Ice Thicknesses along the Red River in Canada Using RADARSAT-2 Satellite Imagery

The spring flood of 2009 in the Red River Valley was exacerbated with severe ice breakup and ice jamming. To assist ice jam mitigation by cutting and breaking up the river ice cover before the flood season and to support the operation of the Red River Floodway, Manitoba Water Stewardship is striving to model the occurrence of ice breakup and simulate the behaviour of ice jamming along the river. An important parameter in ice breakup forecasting is the ice thickness. RADARSAT-2 standard satellite images were collected along the course of the Red River in Manitoba during the 2009-2010 winter to help determine ice thicknesses along the river. Standard images can have transmit-receive polarizations in the horizontal-horizontal (HH) or horizontal-vertical (HV) configurations. Ice thickness measurements were taken in the field during the same time frame when the satellite passed over the Red River Valley. Good correlations were obtained between the HH-backscatter readings and the surveyed ice thicknesses. HV-backscatter readings correlate better with fresh snow depth measurements. Additionally, using same sensor incident angle and flight geometry allows ice thickening rate behavior over the course of the winter to be determined.

基于RBF网络的新疆特重雪灾区最大积雪深度预测研究

基于建立的雪灾灾损指数,确定新疆特重雪灾区域;进一步聚焦特重雪灾区的8个县(市),包括阿勒泰市、福海县、青河县、塔城市、托里县、沙湾市、尼勒克县和伊宁县,分别建立县域RBF网络模型,预测2021—2050年年最大积雪深度。结果表明:该模型可用于新疆特重雪灾区最大积雪深度预测,但预测精度仍有待提升;塔城市、尼勒克县将于2025—2029年连续出现最大积雪深度偏高事件,2039年青河县将出现最大积雪深度的极大值,因此应关注可能发生雪灾的年份与县(市),积极做好雪灾的防御工作。

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。

1961—2020年黑龙江省最大雪深时空变化及其影响因素分析

积雪作为重要的地表覆盖类型,其变化对当地的水文环境、物候变化均有重要的反馈和调节作用。基于1961—2020年黑龙江省62个气象观测站逐日积雪深度观测资料,利用Mann-Kendall检验、经验正交函数(EOF)、相关分析等方法分析了黑龙江省最大积雪深度时空变化特征及其与大气环流、气温和降雪量要素的关系。结果表明:1961—2020年黑龙江省年、冬季、春季和秋季平均最大积雪深度分别为16 cm、14 cm、10 cm和8 cm;其中年、冬季和春季最大积雪深度呈显著增加趋势,增加速率分别为1.40 cm·(10a)^(-1)(P<0.01)、1.51 cm·(10a)^(-1)(P<0.01)、0.76 cm·(10a)^(-1)(P<0.05),秋季呈不显著增加趋势。1961—2020年黑龙江省年及各季节最大积雪深度均在20世纪末至21世纪初发生突变,突变后最大积雪深度均表现出年际变幅增大。黑龙江省最大积雪深度呈现出山地(大小兴安岭地区、完达山)大于平原(松嫩平原、三江平原)的空间分布特征,而变化速率为平原大于山地,其中松嫩平原最大积雪深度增速最明显。黑龙江省最大积雪深度存在东-西反向型、东南-西北反向型两种主要变化形式。气温、降雪量、北半球极涡强度、东亚槽强度均影响黑龙江省冬季最大积雪深度,其中降雪量和北半球极涡强度的影响大于气温和东亚槽强度的影响。随着气候变暖,气温和北半球极涡强度对冬季最大积雪深度的影响更加显著。

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。

三江源地区春季流量与积雪的年际变化关系

基于三江源区站点流量资料、中国区域格点降水气温资料及遥感积雪资料,分析了长江、黄河和澜沧江源区春季流量的年际变化及其与降水、积雪、气温的关系。结果表明,1980~2020年三江源地区春季流量年际变化显著,其中5月流量的年际变率最大;三江源地区春季流量受春季雪深影响最大,其中4月、5月流量受雪深、积雪覆盖率、前期累积降水的影响显著,且流量与雪深的正相关性最强,5月流量与雪深相关系数可达0.7以上。进一步分析表明,高原积雪对流量的影响随源区不同流域、春季不同月份呈现一定的差异,其中黄河源区4月、5月流量受4月雪深影响最明显,澜沧江源区4月、5月流量与2~5月的雪深均存在较好关系,而长江源区5月流量则主要与4~5月雪深显著正相关。源区积雪对春季流量的影响也存在一定的海拔依赖性,其中低海拔区域积雪对流量的影响更多体现在春季前期,而黄河源区阿尼玛卿山、长江源区巴颜喀拉山脉及唐古拉山脉等高海拔区域的积雪对流量的影响可以持续到5月。气温作为春季融雪径流的关键因子,主要是通过影响源区前期积雪量、融雪产流过程,进而影响春季流量的异常。本研究结果在深入认识青藏高原气候变化对三江源地区春季流量的影响及过程等方面具有重要意义。

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。

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.

Snow Information Abstraction Based on Remote Sensing Data： Taking the North of Xinjiang for Example

This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis （LSMA） was used to calculate snow cover fractions （SF） within a pixel, which was used to establish a regression function with NDSI. In addition, 80 snow depths samples were collected in the study region. The correlation between image spectra reflectance and snow depth as well as the comparison between measured snow spectra and image spectra was analyzed. An algorithm was developed for snow depth inversion on the basis of the correlation between snow depth and snow spectra in the region. The results indicated that the model of SF had a high accuracy with the mean absolute error 0.06 tested by 26 true measured values and the validation for snow depth model using another dataset with 50 sampling sites showed an RMSE of 1.63. Our study showed that MODIS data provide an alternative method for snow information abstraction through development of algorithms suitable for local application.

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.