A Sensitivity Study on Parameterization Scheme of Snow Internal and Interfacial Processes in Snow Model

In order to develop a seasonal snow model of land surface process as accurately as possible for climatic study. it is necessary to fully understand the effects of important snow internal processes and interaction with air and to get an insight into influence of several relevant parameterization schemes with parameters' uncertainty to some degree. Using the snow model (SAST) developed by first author and other one and some useful field observation data, this paper has conducted a series of sensitivity studies on the parameterization schemes. They are relative to compaction process, snow thermal conduction, methodology of layering snow pack and to key parameters such as snow albedo, water holding capacity. Then, based on the results from the sensitivity studies, some useful conclusions for snow cover model improvement are obtained from the analysis of the results.

Implementing a New Snow Scheme in Simplified Simple Biosphere Model

This paper describes a modified version of SSIB through implementing a new snow model (SAST) in Simplified Simple Biosphere Model SSIB for climate study and presents the evaluation results by testing the scheme based on the field data from Russia and France. The relevant equations in the scheme are given, which describe complicated interactive processes among air-vegetation-snow-soil continuum through mass and heat exchange. An efficient numerical scheme is developed to solve the nonlinear equations successfully. By using the field data from Russia and France, the function of the new scheme is evaluated. The numerical results from the scheme show good agreement with field data. It indicates that the scheme developed here is workable and can be extended for climate study. Key words Snow cover model (SAST) - SSIB - Implementing - Evaluation This work was supported by the foundation from China: 1)NSF Grant 49835010, 2) National key program G1998040900—Part 1, 3) NSF 40075019, 4) NSF 49823002.

Test of newly developed conceptual hydrological model for simulation of rain-on-snow events in forested watershed

A conceptual hydrological model that links the Xin＇anjiang hydrological model and a physically based snow energy and mass balance model, described as the XINSNOBAL model, was developed in this study for simulating rain-on-snow events that commonly occur in the Pacific Northwest of the United States. The resultant model was applied to the Lookout Creek Watershed in the H. J. Andrews Experimental Forest in the western Cascade Mountains of Oregon, and its ability to simulate streamflow was evaluated. The simulation was conducted at 24-hour and one-hour time scales for the period of 1996 to 2005. The results indicated that runoffand peak discharge could be underestimated if snowpack accumulation and snowmelt under rain-on-snow conditions were not taken into account. The average deterministic coefficient of the hourly model in streamflow simulation in the calibration stage was 0.837, which was significantly improved over the value of 0.762 when the Xin＇anjiang model was used alone. Good simulation performance of the XINSNOBAL model in the WS 10 catchment, using the calibrated parameter of the Lookout Creek Watershed for proxy-basin testing, demonstrates that transplanting model parameters between similar watersheds can orovide a useful tool for discharge forecastin~, in un^au^ed basins.

Simulation of a Persistent Snow Storm over Southern China with a Regional Atmosphere-Ocean Coupled Model

A regional atmosphere-ocean coupled model, RegCM3-POM, was developed by coupling the regional climate model （RegCM3） with the Princeton Ocean Model （POM）. The performance of RegCM3-POM in simulating a persistent snow storm over southern China and the impact of the Madden Julian oscillation （MJO） on this persistent snow storm were investigated. Compared with the stand-alone RegCM3, the coupled model performed better at reproducing the spatial-temporal evolution and intensity of the precipitation episodes. The power spectral analysis indicated that the coupled model successfully captured the dominant period between 30 and 60 days in the precipitation field, leading to a notable improvement in simulating the magnitude of intraseasonal precipitation variation, and further in enhancing the intensity of the simulated precipitation. These improvements were mainly due to the well-simulated low-frequency oscillation center and its eastward propagation characteristics in each MJO phase by RegCM3-POM, which improved the simulations of MJO-related low-frequency vertical motions, water vapor transport, and the deep inversion layer that can directly influence the precipitation event and that further improved the simulated MJOprecipitation relationship. Analysis of the phase relationship between convection and SST indicated that RegCM3-POM exhibits a near-quadrature relation between the simulated convection and SST anomalies, which was consistent with the observations. However, such a near-quadrature relation was not as significant when the stand-alone RegCM3 was used. This difference indicated that the inherent coupled feedback process between the ocean and atmosphere in RegCM3-POM played an important part in reproducing the features of the MJO that accompanied the snow storm.

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact

Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

Observations and Modeling of Incoming Longwave Radiation to Snow Beneath Forest Canopies in the West Tianshan Mountains, China

Forest canopy reduces shortwave radiation and increases the incoming longwave radiation to snowpacks beneath forest canopies. Furthermore, the effect of forest canopy may be changed by complex topography. In this paper, we measured and simulated the incoming longwave radiation to snow beneath forest at different canopy openness in the west Tianshan Mountains, China(43°16'N, 84°24'E) during spring 2013. A sensitivity study was conducted to explore the way that terrain influenced the incoming longwave radiation to snow beneath forest canopies. In the simulation model, measurement datasets, including air temperature, incoming shortwave radiation above canopy, and longwave radiation enhanced by adjacent terrain, were applied to calculate the incoming longwave radiation to snow beneath forest canopy. The simulation results were consistent with the measurements on hourly scale and daily scale. The effect of longwave radiation enhanced by terrain was important than that of shortwave radiation above forest canopy with different openness except the 20% canopy openness. The longwave radiation enhanced due to adjacent terrain increases with the slope increase and temperature rise. When air temperature(or slope) is relatively low, thelongwave radiation enhanced by adjacent terrain is not sensitive to slope(or air temperature), but the sensitivity increases with the decrease of snow cover area on sunny slope. The effect of longwave radiation is especially sensitive when the snow cover on sunny slope melts completely. The effect of incoming shortwave radiation reflected by adjacent terrain on incoming longwave radiation to snow beneath forest canopies is more slight than that of the enhanced longwave radiation.

Application of snowmelt runoff model(SRM) in mountainous watersheds:A review

The snowmelt runoff model （SRM） has been widely used in simulation and forecast of streamflow in snow-dominated mountainous basins around the world. This paper presents an overall review of worldwide applications of SRM in mountainous watersheds, particularly jn data-sparse watersheds of northwestern China. Issues related to proper selection of input climate variables and parameters, and determination of the snow cover area （SCA）using remote sensing data in snowmelt runoff modeling are discussed through extensive review of literature. Preliminary applications of SRM in northwestern China have shown that the model accuracies are relatively acceptable although most of the watersheds lack measured hydro-meteorological data. Future research could explore the feasibility of modeling snowmelt runoff in data-sparse mountainous watersheds in northwestern China by utilizing snow and glacier cover remote sensing data, geographic information system （GIS） tools, field measurements, and innovative ways of model parameterization.

Application of Snow Melt Runoff Model in a Mountainous Basin of Iran

Simulation and modeling the stream flow provide major data while it is a challenge in mountainous basins with regard to the important role of snowmelt runoff as well as the data scarcity in these places. The main purpose of this paper is to examine the capability of an integrated application of remote sensing data and Snowmelt Runoff Model (SRM) to simulate scheme of daily stream flow in the snow-dominated catchment, located in the North-East region of Iran. The main parameters of the model are Snow Cover Area (SCA), temperature and participation. Regarding to the lack of measured data, the input variable and parameters of the model are extracted or estimated based on accessible maps, satellite data and available meteorological and hydrological stations. The changes of snow-cover, as spatial-temporal data, which are the most effective variable in performance of SRM, are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) eight-day composite snow cover images. The evaluation of the model application efficiency was tested by the coefficient of determination and the volume difference, which are 0.85% and -4.6% respectively. The result depicts the relative capability of SRM though it is evident that the more accurate the estimation of model parameters, the more efficient simulation results can be obtained.

Origin and advances in implementing blowing-snow effects in the Community Land Model

Snow cover on the Tibetan Plateau(TP)is closely related to regional and continental biological and hydrological processes.The vast snow cover,special climatic conditions,and sparse vegetative cover over the TP facilitate the occurrence of blowing snow,leading to substantial heterogeneities in the snow cover and great promotion in the moisture supply from the land surface to the overlying atmospheric boundary layer.However,blowing-snow processes are significantly misrepresented or even neglected in current models,which causes considerable uncertainties of numerical model simulations and leads to erroneous estimates of snow-related processes in mountainous terrain.We present in this paper a brief review of our work in the past 5 years to serve as a basis for further development and improvement of the land-surface model.These studies can be divided into three parts:detection of the problems,development of the land-surface model,and application of the coupled model over the TP(the logical framework is presented in Figure 1).The origin and advances in the development of a land-surface model with consideration of blowing-snow effects are described herein;and the importance of blowing-snow processes in the land-surface model,especially over the TP,is highlighted.We expect that the blowingsnow studies over the TP will play a key role in documenting and understanding the land-surface processes(LSPs)and the cryospheric changes over the TP.

Remote Sensing, Model-Derived and Ground Measurements of Snow Water Equivalent and Snow Density in Alaska

Snow water equivalent (SWE) is important for investigations of annual to decadal-scale changes in Arctic environment and energy-water cycles. Passive microwave satellite-based retrieval algorithm estimates of SWE now span more than three decades. SWE retrievals by the Advanced Microwave Scanning Radiometer for the Earth Observation System (AMSR-E) onboard the NASA-Aqua satellite ended at October 2011. A critical parameter in the AMSR-E retrieval algorithm is snow density assumed from surveys in Canada and Russia from 1940s-1990s. We compare ground SWE measurements in Alaska to those of AMSR-E, European Space Agency GlobSnow, and GIPL model. AMSR-E SWE underperforms (is less than on average) ground SWE measurements in Alaska through 2011. Snow density measurements along the Alaska permafrost transect in April 2009 and 2010 show a significant latitude-gradient in snow density increasing to the Arctic coast at Prudhoe Bay. Large differences are apparent in comparisons of our measured mean snow densities on a same snow cover class basis March-April 2009-2011 Alaska to those measured in Alaska winter 1989-1992 and Canadian March-April 1961-1990. Snow density like other properties of snow is an indicator of climate and a non-stationary variable of SWE.

面向复杂雪天场景的单幅图像去雪方法

降雪是一种复杂的天气现象,雪花多尺度、运动轨迹复杂以及远景呈现雾天效果.然而现有的单幅图像去雪方法以及数据集,并没有考虑到这些复杂的情况,从而限制了去雪方法在真实雪天图像上的表现.基于此,首先根据图像的深度信息构造了一种联合雪花和雾的雪天成像模型,合成了具有真实感的雪天图像数据集.然后设计了一种端到端的图像恢复网络,将去雾模块和去雪模块级联,并进行联合训练.其中去雪模块采用了双层U型网络用于解决雪花多尺度和轨迹复杂的问题.最后将该方法同其它最先进的方法进行实验对比,证明该方法在合成数据集和真实图像中都具有非常好的效果,且能够提升后续高级视觉任务性能.

Integration of aspect and slope in snowmelt runoff modeling in a mountain watershed

This study assessed the performances of the traditional temperature-index snowmelt runoff model(SRM) and an SRM model with a finer zonation based on aspect and slope(SRM + AS model) in a data-scarce mountain watershed in the Urumqi River Basin,in Northwest China.The proposed SRM + AS model was used to estimate the melt rate with the degree-day factor(DDF) through the division of watershed elevation zones based on aspect and slope.The simulation results of the SRM + AS model were compared with those of the traditional SRM model to identify the improvements of the SRM + AS model's performance with consideration of topographic features of the watershed.The results show that the performance of the SRM + AS model has improved slightly compared to that of the SRM model.The coefficients of determination increased from 0.73,0.69,and 0.79 with the SRM model to 0.76,0.76,and 0.81 with the SRM + AS model during the simulation and validation periods in 2005,2006,and 2007,respectively.The proposed SRM + AS model that considers aspect and slope can improve the accuracy of snowmelt runoff simulation compared to the traditional SRM model in mountain watersheds in arid regions by proper parameterization,careful input data selection,and data preparation.

CMIP6模式对欧亚大陆冬季雪水当量的模拟能力评估及未来预估

基于第六次耦合模式比较计划(CMIP6)的模式模拟数据和欧洲宇航局GlobSnow卫星遥感雪水当量(Snow Water Equivalent,SWE)资料,评估了CMIP6耦合模式对1981~2014年欧亚大陆冬季SWE的模拟能力,并应用多模式集合平均结果预估了21世纪欧亚大陆SWE的变化情况。结果表明,CMIP6耦合模式对冬季欧亚大陆中高纬度SWE空间分布具有较好的再现能力,能模拟出欧亚大陆中高纬度SWE的主要分布特征;耦合模式对SWE变化趋势及经验正交函数主要模态特征的模拟能力存在较大差异,但多模式集合能提高模式对SWE变化趋势和主要时空变化特征的模拟能力;此外,多模式集合结果对欧亚大陆冬季SWE与降水、气温的关系也有较好的再现能力。预估结果表明,21世纪欧亚大陆东北大部分地区的SWE均要高于基准期(1995~2014年),而90°E以西的欧洲大陆SWE基本上呈现减少的特征;21世纪早期,4种不同排放情景下积雪变化的差异不大,但21世纪后期积雪变化的幅度差异较大,而且排放越高积雪变化的幅度越大,模式不确定性也越大;进一步的分析表明,欧亚大陆冬季未来积雪变化特征的空间分布与全球变化背景下局地气温、降水的变化密切相关,高温高湿的条件有利于欧亚大陆东北部积雪的增多。

基于Kano模型的冰雪体育旅游服务品质分析

基于Kano模型,通过对346名参加过冰雪体育旅游消费者进行问卷调查,分析冰雪体育旅游服务品质的属性和不同消费者体验服务质量满意度的差异.结果显示,冰雪体育旅游服务品质5个构面23个要素中,2项为必备品质,3项为魅力品质,2项为无差异品质,其余16项为线性品质.不同性别的顾客在满意度的可靠性和反应性2个构面,间接反映经营者在服务过程中对女性的关照不足.不同参与次数的消费者对冰雪体育旅游服务质量的可靠性、反应性、亲和性、保证性和总体的满意度上存在差异.不同受教育程度的消费者对冰雪体育旅游服务质量的有形性、可靠性、反应性、亲和性和总体的满意度上存在差异.为更好提升消费者对冰雪体育旅游服务品质的满意度,冰雪体育旅游经营者要优先满足顾客的必备型需求和期望型需求;注重个体需求差异,创新个性化服务项目;构建统一服务质量标准,提升服务规范.

基于Crocus模型的雪深模拟研究

雪深的准确模拟对于寒区的水文过程、气候变化、生态环境具有重要意义。积雪过程模型可以定量模拟物理环境对积雪参数的影响过程,从物理意义上定量模拟区域雪深。但是,目前积雪过程模型模拟存在参数设置复杂、不确定性大等问题。因此,有必要通过参数率定找到最适应区域的参数组合,从而完成模型参数的本地化。本文应用Crocus模型,在西藏自治区的聂拉木站、普兰站和帕里站进行3 a(2019—2021年)逐日雪深模拟,利用UQ-Pyl进行模型参数的敏感性分析及率定,构建以上站点的Crocus模型,并通过相关系数(R)、标准差比(SDC)、纳什效率系数(NSE)、平均差值(BIAS)和均方根误差(RMSE)综合评估Crocus模型在聂拉木站、普兰站和帕里站的适用性。结果表明:聂拉木站、普兰站、帕里站的Crocus模型主要敏感参数分别有20、15、13个;Crocus模型在聂拉木站的雪深模拟效果最佳(R=0.989、SDC=0.990、NSE=0.978、BIAS=0.276 cm、RMSE=4.280 cm),普兰站和帕里站次之;其中,聂拉木站的积雪沉降、积累和融化过程得到了很好的模拟,普兰站在积雪较厚时模拟效果更优,帕里站在每年3—4月时模型高估了雪深,但变化趋势基本一致,3个站点的日雪深模拟结果基本反映了雪深日变化过程。本文对Crocus模型的本地化是对积雪过程模拟研究的有益补充,为理解和揭示西藏自治区的积雪过程可提供科学依据和信息,同时,也为提高区域气候预测水平、水资源有效管理、灾害预防和应对提供有力支撑。

不均匀积雪致大跨网架结构局部损伤分析

网架结构管球连接处局部损伤是此类结构的重要安全隐患。在风致雪漂移引起的不均匀积雪荷载作用下,局部损伤会加剧,最终导致结构局部破坏。因此很有必要分析不均匀积雪荷载作用下带伤服役网架结构局部损伤劣化情况。采用CFD数值模拟技术,以一正放四角锥网架结构为研究背景,分析了在90°风向角、12 m/s风速下,持续降雪24 h中网架结构屋面不均匀积雪分布的变化情况,并建立可表征网架结构管球连接处存在裂纹损伤的多尺度模型,分析了网架结构节点存在不同裂纹尺寸局部损伤时,不均匀积雪致网架结构局部损伤劣化程度。结果表明:网架结构风致积雪不均匀程度非常显著,而且当网架结构管球连接处存在局部裂纹损伤时,在降雪中后期,有管球连接损伤的节点大多都出现了不同程度的裂纹扩展,节点为最不利分布的穿透型裂纹时,裂纹扩展最大为15.64 mm。说明在持续特大降雪这种极端荷载作用下,带伤服役网架结构局部损伤将进一步加剧,危及结构使用安全。

山区高速公路不同深度路堑的积雪堆积规律

山区高速公路在风雪气象条件下极易形成较为严重的风吹雪灾害,造成雪阻和断通,其中路堑深度对路面积雪产生重要影响,但现在具有针对性的研究较少。利用大缩尺比(1∶10)的现场模型试验方法,分析了8 m深度全路堑周围的风速和积雪分布规律。使用现场模型试验结果验证数值模型,并进一步研究了不同深度全路堑、迎风半路堑和背风半路堑周围风场以及积雪沉积的形成机理。结果表明:风吹雪作用下,路堑内风速与雪深变化趋势呈负相关;全路堑以及背风半路堑的深度在小于和大于2 m时,路面积雪的主控因素分别为中央分隔带护栏和路堑边坡;迎风半路堑的深度与路面积雪堆积量之间呈正比关系,路堑边坡是影响路面积雪的主导因素,也可采用分离式路基断面形式减少路面的积雪沉积量及雪害的危害程度。研究成果可为风吹雪多发区高速公路路堑的设计和雪害防治提供有益参考。

青藏高原寒区水文过程研究进展及模型述评

全球气候变暖导致冰冻圈发生了剧烈变化,突出表现为冰川退缩、积雪消融、冻土退化等,加速了固态水资源向液态水资源的转化,打破了青藏高原寒区水资源分配的长期稳定机制。本文基于寒区冰冻圈变化水文效应角度,梳理了气候变化下青藏高原寒区水文过程研究进展,剖析了当前青藏高原寒区水文过程研究中存在的热点和难点。由于水文模型为研究水文循环过程的重要工具,模型的结构和功能决定了水文过程研究的准确度和发展方向。因此,本文总结了10个典型水文模型在模拟高原寒区冰川、融雪径流算法的优点和局限性及模型冰川、积雪、冻土模块特点,凝练总结了影响高原寒区水文过程模型模拟精度的主要问题。结果表明:青藏高原寒区气象观测站点资料的匮乏加大了数据输入、参数估计的不确定性;对冰冻圈水文内在物理过程认识不足导致了模型结构的不完备性,进而影响水文过程模拟精度。最后,本文从多元数据联合使用、机器学习应用等方面探讨了如何提高水文模型精度,为寒区水文模型的改进和完善提供参考。

基于MTSVR-ISAO的混凝土重力坝参数反演方法

混凝土坝参数识别是评价其运行状态的关键。为进一步提高参数识别的效率和精度,提出一种基于多输出孪生支持向量机(MTSVR)和改进雪消融优化器(ISAO)的混凝土坝参数反演方法。通过训练MTSVR模型模拟待反演参数与位移静水压分量之间的非线性关系以代替复杂的有限元计算。采用ISAO对目标参数进行寻优反演。工程实例分析表明,代理模型计算结果与有限元计算结果基本一致。与传统元启发优化相比,ISAO寻优收敛速度更快,准确度更高,单次参数反演用时更少。结果说明构建的反演方法可在保持计算精度前提下有效提高计算效率,方法具有有效性和实用性,为工程真实参数辨识提供参考。

结构功能主义AGIL模型视角下我国冰雪旅游目的地高质量发展瓶颈及突围之路

绿水青山就是金山银山、冰天雪地也是金山银山发展理念,为我国冰雪旅游目的地高质量发展提供了价值遵循和根本行动指南。运用文献资料等研究方法,借助结构功能主义AGIL模型,深度剖析我国冰雪旅游目的地高质量发展瓶颈及突围之路。研究认为,冰雪旅游目的地发展面临适应功能瓶颈,冰雪旅游发展不平衡不充分;达标功能瓶颈,冰雪旅游激励政策体系不健全;整合功能瓶颈,绿色低碳可持续发展行动欠缺;模式维持功能瓶颈,数字技术创新与应用薄弱。基于现实发展瓶颈,在借鉴域外国家冰雪旅游目的地发展经验基础之上,提出家庭客群、产品丰富度、冰雪旅游“三化”协同发展、产品供需适配的发展路径。