积雪覆盖对高寒草甸土壤温湿及地表能量收支的影响

利用青海玛沁微气象观测站降雪过程的观测数据,探讨了积雪覆盖对土壤温度,土壤体积含水量、土壤热通量及地表能量交换的影响。结果表明:积雪覆盖对浅层土壤温度的影响较为显著,而对深层土壤温度的影响十分微弱。地表有积雪覆盖时,浅层土壤温度日平均值升高,日变化幅度减小,日最低值升高,温度梯度绝对值减小。土壤完全冻结状态下土壤体积含水量几乎不受积雪覆盖影响,土壤融化状态下积雪覆盖会导致浅层土壤体积含水量日变化幅度减小,而对深层土壤体积含水量没有影响。积雪覆盖会减小浅层土壤热通量的日变化幅度。在总辐射相同的晴天条件下,当地表有积雪覆盖时,由于积雪的高反照率导致向上短波辐射增加,净辐射减小,同时感热通量减小而潜热通量增加,感热占比(H/Rn)下降,潜热占比(LE/Rn)升高。     

青藏高原GLASS地表反照率产品精度分析

应用2003年青藏高原3个站点的地表反照率观测结果,对比分析了GLASS(Global LAnd Surface Satellites)地表反照率1 km×1 km分辨率产品的精度,结果表明,GLASS黑空反照率、白空反照率与地表反照率地面观测结果的总体变化趋势基本一致,能够有效地反映实际地表状态的变化;局地积雪和云覆盖对GLASS地表反照率产品的精度影响较大,云覆盖导致GLASS地表反照率可能比实际地表反照率高;消除云覆盖和局地积雪的影响后,GLASS黑空反照率、白空反照率与地表反照率地面观测结果的均方根误差显著降低,分别为0.0155和0.0190。     

中国西天山季节性积雪热力特征分析

利用中国天山积雪雪崩站干、湿雪雪层内每隔5min一次的10层雪温数据,探讨了一次降雪过程后干、湿雪的雪层温度特征,对比分析了干、湿雪的雪面能量平衡方程中各分量的差异。结果表明:(1)整个冬半年积雪各层温度基本<0℃,雪温日变化振幅由雪面向下逐渐减小,积雪深层温度的波峰(谷)值稍滞后于积雪浅层温度极值1～2天。(2)湿雪冷中心的出现时间早于干雪,暖中心的出现时间晚于干雪,太阳辐射对湿雪的穿透深度大于干雪。(3)雪层温度振幅变化与能量吸收随雪深都呈指数衰减分布。积雪密度越大,吸收系数越小,穿透深度越大。(4)干雪雪面的感热通量和潜热通量几乎都为负值,积雪积累。湿雪雪面的潜热通量与感热通量方向相反,互相抵消,所以净辐射是导致湿雪消融的主要因素。     

2000~2016年青藏高原地表反照率时空分布及动态变化

应用MODIS地表反照率产品MCD43C3,结合青藏高原自然带数据、积雪覆盖率和植被指数数据,采用一元线性回归方法分析了2000~2016年青藏高原地表反照率的分布及变化特征,结果表明:1）高原地表反照率空间分布差异大,整体上东南部低、西北部高,受地形和地表覆盖影响较大。2）高原地表反照率四季的空间分布变化明显,高海拔山脉和高寒灌丛草甸是高原地表反照率年内和年际变化的敏感地区。3）高原地表反照率年变化介于0.19~0.26,一定程度上表现为“双峰单谷”型,与地表覆盖类型的季节变化密切相关。4）高原地表反照率年际变化整体呈缓慢波动减小的趋势,平均变率约为－0.4×10-3 a-1,减小的区域约占高原总面积的66%,川西 —藏东针叶林带的西南部地区减小得最快,减小速率超过1.0×10-2 a-1。5）高原地表反照率减小与冰川消融和积雪减少密切相关,高原植被覆盖改善也是一个重要因素。     

黄河源积雪期土壤温湿及冻融特征分析与模拟

利用2017~2018年黄河源地区野外观测站数据，对黄河源区两个积雪期内土壤温湿及冻融特征进行了分析，并与CLM4.5模式模拟的积雪期土壤温、湿度及辐射分量进行了对比，结果表明:CLM4.5能很好地模拟出整个积雪期土壤温度的变化趋势；对不同土壤层在不同冻结阶段土壤含水量的模拟有所差异:在完全冻结阶段，对5cm土壤层含水量模拟偏高，而80cm偏低，对10~40cm土壤层含水量的模拟偏差较小；由于降雪及土壤冻融过程主要发生在积雪期，积雪反照率使得净辐射模拟在降雪时段偏差较无降雪时段略大。      

基于加密观测的一次极端雨雪过程积雪特征分析

利用降水现象仪、地面自动站、人工加密积雪深度逐时观测资料及NCEP/NCAR 1°×1°再分析资料,对山东2020年1月5-7日罕见雨雪过程的积雪特征及温度影响机制进行了分析。结果表明:(1)降水量突破同期历史极值导致此次雨雪过程成为极端天气事件,地面影响系统为江淮气旋,冷平流较弱,积雪深度是预报难点。(2)整个过程全省各站的平均降雪含水比为0.46 cm·mm~(-1),低于过去20年间的江淮气旋暴雪过程。(3)积雪深度与高空温度、相对湿度和垂直速度的配置有关,在最大上升运动与90%以上相对湿度的叠置层次内,如果环境温度有利于树枝状冰晶增长则积雪深度和降雪含水比大,而环境温度适合空心柱状冰晶增长的则积雪深度小;云下温度高于0℃使得积雪深度减小。(4)积雪深度与近地面温度的关系表现为:气温低于0.5℃可形成有量积雪;0 cm地温对积雪的影响表现在积雪产生之前,降至0.4℃以下可形成有量积雪;雪面温度在产生积雪前后的2 h内维持在0℃左右,其他时段变化与气温类似。(5)降雪含水比基本上随着气温的升高而减小,在0.5 cm·mm~(-1)以上时一般降雪期间气温低于0.4℃。该个例揭示了积雪深度和降雪含水比的预报需要综合考虑高低空气象条件。     

雨雾、雪雾共生天气气象要素分析

利用多通道微波辐射计、边界层风廓线仪及自动/人工气象站等观测资料, 分析了2007年秋冬季北京地区雨雾和雪雾两次共生天气形成与维持过程中地面和高空气象要素伴随降雨、 降雪过程的变化。结果显示:(1) 高湿和小风是雨雾、雪雾生成并造成地面低能见度的主要气象条件。大雾形成与维持过程中, 地面水平能见度与相对湿度的反相关关系非常显著。能见度越低时, 雾的含水量也越高。 (2) 较弱的降雨和降雪可以促使雾含水量减少, 提高能见度, 但降雨或降雪蒸发增湿又利于雾的维持。 (3) 雨雾在降雨过程中高层气温经历大幅增降, 除可能受天气系统影响外, 与云层中水汽凝结释放的大量潜热和含水量大幅度增加也有关系。雪雾在降雪过程中高层温度总体随着时间趋于降低且变化幅度较小。 (4) 在降雨、降雪过程中雨雾和雪雾低层一直存在水汽饱和层, 且饱和层的顶部随降雨和降雪强度的加大而抬升, 厚度不断加大, 造成地面水平能见度进一步下降。结合催化剂人工消雾与共生雾降水 (降雨或降雪) 相似的原理, 个例分析结果初步表明较弱的降雨或降雪过程对消除暖雾、冷雾的影响有限, 对改善地面水平能见度并不显著, 这对人工消雾技术研究具有一定的启发作用。     

一次江淮气旋暴雪的积雪特征及气象影响因子分析

利用自动站、人工加密观测及常规观测资料,通过对2017年2月21—22日一次江淮气旋暴雪过程积雪特征的分析,揭示了近地面气象要素对积雪深度的复杂影响。结果表明:(1)江淮气旋系统特有的空间结构导致山东南、北地区的降雪量和积雪深度不均衡分布。(2)积雪深度具有时效性,在降雪结束时达到峰值,因温度的变化导致峰值不一定维持到次日08时。(3)积雪深度是近地面多气象要素共同作用的结果,降水相态、降雪量、降雪强度、气温、地温和风速均有影响。主要表现为:雨夹雪在转为纯雪之前可产生不超过1 cm的积雪,如果不转雪则不会产生有量积雪;各地降雪含水比差异较大,全省平均为0. 5 cm·mm~(-1),低于全国平均值;在降雪不融化的情况下,降雪量、降雪强度越大则积雪越深,降雪强度大是气温和地温都高于0℃时产生积雪的必要条件;地温和气温越低对积雪形成越有利,积雪开始产生时的地温最高阈值多在0℃左右,地温先突降后缓升是积雪产生前后的共性特征,积雪产生后1～2 h内地温略有上升并逐渐趋于稳定;积雪产生时气温一般低于0℃,气温高于0℃时大部分降雪融化;有利于产生积雪的平均风力多不超过2级,极大风则在3～4级以下。     

利用MODIS卫星资料反演中国地区晴空地表短波反照率及其特征分析

利用MODIS地表双向反照率产品(MOD43B1),结合地表海拔高度和地表覆盖类型资料,计算并分析了中国地区晴空反照率的时空分布,以及地表反照率与地形和地表覆盖的关系.首先,利用改则自动气象站的地基观测对MODIS地表反照率进行了对比验证.验证结果表明卫星观测可以较好地反映反照率随时间的变化,MODIS地表反照率与地表实测反照率符合较好.年平均地表反照率与海拔高度有很好的相关,反照率的高值出现在高海拔山区.冬春季节,我国高海拔山区因积雪覆盖成为反照率的高值区;夏秋季节,地表反照率主要受地表土壤湿度和植被盖度的影响,沙地和沙漠地带反照率最高.最后,计算了中国典型地表类型的反照率随时间的变化,结果表明大部分地表类型的反照率具有较大的时间变化,地表反照率在春秋季节较大,夏季反照率较小.     

一些陆面要素非均匀分布对模式计算结果影响的理论分析

应用平均参数化方法,从理论上分别研究了地表温度、地面粗糙度、积雪深度和密度非均匀分布对相关物理量计算的影响。结果表明:考虑地表温度的非均匀分布影响后,模式网格上平均地面的长波辐射通量增加,地面饱和水汽压也增加;在相同的地表温度分布变差系数和常温情况下,与长波辐射通量相比,地面饱和水汽压的变化对地表温度非均匀分布较为敏感;地面粗糙度非均匀分布对地面中性曳力系数和BATS型地面积雪覆盖率有一定的影响;积雪深度和密度非均匀分布也对地面积雪覆盖率有一定的影响。     

城市雪灾气象等级划分标准的研究

摘要：本文选取累积降雪量、最大日降雪量、连续降雪日数、积雪深度、日最低气温、日最大风速和日最小相对湿度7个气象因子构成城市雪灾气象指数。通过对城市雪灾气象指数的范围划分,得到从低到高的5级城市雪灾气象等级,并给出等级描述及可能影响。     

城市雪灾气象等级划分标准的研究

选取累积降雪量、最大日降雪量、连续降雪日数、积雪深度、日最低气温、日最大风速和日最小相对湿度7个气象因子构成城市雪灾气象指数。通过对城市雪灾气象指数的范围划分,得到从低到高的5级城市雪灾气象等级,并给出等级描述及可能影响。     

Albedo of coastal landfast sea ice in Prydz Bay,Antarctica: Observations and parameterization

The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica(off Zhongshan Station)during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters(e.g., snow thickness, ice thickness, surface temperature, and air temperature) were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.     

Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.     

藏北地区冬季降雪对地面反射率的影响

藏北地区是冬季青藏高原上降雪次数较多、降雪量较大、可能出现较长时间地面积雪的地区之一。每次较强的隆雪均可造成该地区地面反射率一次较长时间异常，从而改变地面热源的强度和符号。     

Effects of increasing surface reflectivity on aerosol,radiation, and cloud interactions in the urban atmosphere

The online Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is used to simulate the effects of albedo enhancement on aerosol, radiation, and cloud interactions in the Greater Montreal Area during the 2011 heat wave period. We used a 2-way nested approach to capture the full impacts of meteorological and photochemical reactions in the urban atmosphere. We conducted four sets of simulations with and without aerosol estimations and convective parameterizations to explore the aerosol interactions with radiation and cloud in the urban atmosphere. The direct, semi-direct, and indirect effects of aerosols are analyzed. The meteorological performance of the model indicates that the model slightly underpredicts air temperature, overpredicts wind speed, and underpredicts relative humidity. The chemical component of the model indicates that the model tends to underpredict fine particulate matters and overpredict ozone and nitrogen dioxide concentrations. The surface reflectivity of roofs, walls, and grounds is increased from 0.2 to 0.65, 0.60, and 0.45, respectively. Albedo enhancement led to a net decrease in radiative balance at solar noon by 25 W/m2, a decrease in daily air temperature by 0.5 °C, a reduction in water mixing ratio to 0.5 g/kg, and a decline in cloud coverage by 3% in the center part of the domain. Increasing urban albedo caused a decrease in planetary boundary layer height by 25 m. Albedo enhancement affords a decrease in temperature-sensitive photochemical reaction rates and thus reduces daily ozone concentrations by 3 ppb across the entire domain. The concentration of daily fine particulate matters decreased by 3 μg/m3 in the center part of the GMA during the 2011 heat wave period.     

A comparison of four snow models using observations from an alpine site

 Results from four snow models-two used in climate models, one being developed for hydrological forecasting and one used for avalanche forecasting-are compared with observations made during two contrasting winters at a site in the French Alps. The models are all driven with hourly measurements of air temperature, windspeed, humidity, snowfall and downward longwave and shortwave radiation, but they differ greatly in complexity. Results from the models are compared with measurements of snowdepth, snow water equivalent, surface temperature, runoff and albedo. The models all represent the duration of snow cover well, but differ in their predictions of peak accumulation and timing of runoff. Experience gained in this study is used to make recommendations for a more ambitious intercomparison between a larger number of models for a wide range of environments. Received: 31 July 1998 / Accepted: 12 February 1999     

Use of atmospheric radiation measurement program data from Barrow, Alaska, for evaluation and development of snow-albedo parameterizations

Summary Snow albedo is determined from the ratio of out-going to incoming solar radiation using three years of broadband shortwave radiometer data obtained from the Barrow, Alaska, Atmospheric Radiation Measurement (ARM) site. These data are used for the evaluation of various types of snow-albedo parameterizations applied in numerical weather prediction or climate models. These snow-albedo parameterizations are based on environmental conditions (e.g., air or snow temperature), snow related characteristics (e.g., snow depth, snow age), or combinations of both. The ARM data proved to be well suited for snow-albedo evaluation purposes for a low-precipitation tundra environment. The evaluation confirms that snow-age dependent parameterizations of snow albedo work well during snowmelt, while parameterizations considering meteorological conditions often perform better during snow accumulation. Current difficulties in parameterizing snow albedo occur for long episodes of snow-event free conditions and episodes with a high frequency of snow events or strong snowfall. In a further step, the first two years of the ARM albedo dataset is used to develop a snow-albedo parameterization, and the third year’s data serves for its evaluation. This parameterization considers snow depth, wind speed, and air temperature which are found to be significant parameters for snow-albedo modeling under various conditions. Comparison of all evaluated snow-albedo parameterizations with this new parameterization shows improved snow-albedo prediction. Correspondence: Nicole M?lders, Geophysical Institute and College of Natural Science and Mathematics, University of Alaska Fairbanks, 903 Koyukuk Drive, P.O. Box 757320, Fairbanks, AK 99775-7320, USA     

乌鲁木齐冬季清雪预报服务研究

以乌鲁木齐冬季清雪工作需求为牵引,利用乌鲁木齐2006—2016年冬季(当年11月—翌年3月)逐日降雪量、积雪深度、气温和173 d降雪日的逐时降雪量资料,分析了近11年冬季各量级降雪的分布特征、降雪持续时间和降雪的日变化特征;对积雪深度和对应降雪量做线性拟合,得出二者比值大体为0.968 cm/mm。得出清雪预报服务的重点是:小雪的有无、降雪起止时间和累积降雪量、积雪深度的预报,难点是中雪、大雪特别是暴雪和对应的积雪深度的精细化预报。