共查询到18条相似文献，搜索用时 125 毫秒
1.
乌梁素海湖冰晴天反照率日变化具有双峰特征,利用当地太阳高度角同经纬度和儒历的关系,归一化到北京时,依此表达湖冰反照率日变化规律.基于具有指数函数形式的拉普拉斯、高斯、耿贝尔和柯西4种概率密度分布函数建立线性组合模型,对日出后到日落前太阳高度角大于5°时段内的反照率日变化数据进行拟合,发现拉普拉斯密度分布函数组合是最佳统计模型.它既能拟合太阳高度角大于5°时间范围内反照率日变化曲线的双峰特征,又能反映太阳高度角大于15°时间范围内反照率日变化曲线双峰之间的U型分布.该模型不仅形式简单,而且意义明确：尺度参数约为日长的一半,双峰位置与日出时刻关系密切;同时能体现2个反照率峰值的不对称性.为发展不同地区湖冰反照率日变化参数化方案奠定基础. 相似文献
2.
基于2019—2020期间在盘锦市含章湖利用浮式观测平台开展湖冰原型观测试验,分析不同因素对湖冰变化造成的影响.结果表明:99 d冰期内湖冰的生消过程可概述为:湖泊封冻(3 d)—稳定生长(62 d)—冰厚稳定(7 d)—加速消融(24 d)—破碎分解(3d).生长期冰厚的平均增长速率为0.4 cm/d,最大冰厚为30.7 cm;不同深度(5～17 cm)冰温对气温变化的响应存在滞后性,滞后时间为70～158 min,冰温与气温的最大相关系数为0.52～0.89;降雨过程造成冰面反照率由0.22降至0.09,影响了冰内温度以及冰下40 cm以内的浅层水温,但14 mm的降雨量并未引起表面冰厚增加;降雪过程造成冰面反照率由0.25升至0.90,同时阻碍了 5 cm以内的浅层冰温对气温变化的响应,但风速长时间大于8 m/s时会导致冰面积雪被吹散,冰面重新裸露;消融期冰厚的衰减过程呈抛物线趋势,存在显著的加速过程,融化速率由0.3 cm/d逐渐增加到2.7 cm/d;湖冰生长期的冰底热通量均值为4.8 W/m~2;到消融期增加至8.1 W/m~2,为生长期的1.7倍;太阳辐射与湖冰边界侧向融化是导致湖冰加速融化的关键因素.本研究填补了国内湖冰冻融全过程实测资料的空缺,为湖冰热力学模型的改进提供了科学支撑. 相似文献
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《地球物理学进展》2020,(2)
反照率是控制地表能量收支的关键地球物理参数之一,海冰作为南北极地区重要的组成部分,海冰反照率的时空变化会对极地地区和全球范围的气候变化、物质平衡以及能量平衡等产生重要的影响.本文系统的总结了海冰反照率的影响因素、海冰反照率的参数化方法和遥感反演方法及产品的研究进展,阐明了各方法的基本原理、特点以及存在的问题等.海冰反照率的影响因素众多,主要受地表冰雪反射特性、太阳天顶角以及大气属性的影响;参数化方法提供了一种模拟海冰反照率的途径,主要通过取经验定值或建立温度、冰雪厚度以及光谱反照率等参数与海冰反照率的经验关系来进行,但是这种基于特定位置、特定时间以及特定的大气状态下的观测数据运用统计或经验方法建立的参数化方法,适用范围通常有限.遥感反演方法是高时空分辨率获取大范围及长时序海冰反照率的有力手段,主要分为传统的反演方法、直接反演方法以及基于非光学传感器的反演方法;但是遥感反演很容易受到云层的影响,仅能反演晴空下的海冰反照率,而且现有的方法基本都是针对单一传感器设计的,还没有能够联合多源传感器数据反演海冰反照率的方法.基于此,本文展望了未来海冰反照率的研究重点,即开展能够适用于云天空下的、高时空分辨率的以及能够联合多源数据反演海冰反照率的方法研究. 相似文献
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利用1993~2004年SSM/I被动微波辐射仪反演的雪深资料,1996~2004年NOAA/AVHRR可见光和红外反演的积雪覆盖面积资料,1966~2003年藏北地区6个地面台站的积雪观测资料来检验卫星资料的可用性,并研究近年来藏北积雪的时空分布和影响因素.结果表明,SSM/I, NOAA/AVHRR和实际观测的积雪资料具一致性.从积雪时间变化看：季节尺度上,藏北地区秋冬季积雪迅速增加,但春季(3~5月)融雪速度不快,呈现正反馈特征;年际尺度上,藏北地区20世纪60年代末期起积雪开始减少,80年代积雪增加,90年代起到2003年积雪总体上减少,呈现出减少—增加—减少趋势.采用小波分析发现积雪振荡周期存在着一个准2~3年,准9年和13年的周期,从20世纪70年代初到90年代中期还有一个5年的周期.积雪空间上看,藏北地区积雪主要集中在东部地区,该区每个冬春年积雪覆盖旬数超过15旬,显著高于西部少雪区,大部分积雪集中在4900~5600 m的高度左右;藏北高原积雪变动的显著区位于藏北中东部的安多和聂荣地区.利用藏北地区1966~2003年的地面温度和降水资料建立回归方程模拟年累积雪日,结果表明模拟值与实测值之间的相关系数达0.74.积雪时空分布受温度、降水等因子影响明显.1998~2003年藏北积雪的减少与全球变暖有关,但降水的减少可能是导致近年来藏北积雪减少的更主要因素. 相似文献
5.
东南极Lambert冰盆-Amery冰架区域雪面相对高程变化的精确监测 总被引：7，自引：0，他引：7
采用自动气象站对东南极冰盖Lambert冰盆-Amery冰架雪面相对高程(SSH)变化进行了连续监测, 通过Argos卫星传输的逐时数据精确分析了冰盖LGB69地点和Amery冰架G3地点SSH的年内变化过程. 2002年2月至2003年1月一个整年资料得出, LGB69全年积累量为0.68 m, 与花杆网阵所得结果接近. 10月至次年4月南极夏季为主要积累期, 占全年SSH变化量的101.6%; 5~9月南极冬季期间雪面高度几无变化, 雪层密实化作用使之略有下降, 为全年SSH变化量的−1.6%. LGB69和G3雪面上升主要由雪面突升事件导致, 而且在LGB69较G3更频发. G3点每年有2~3次雪面突升事件, 均发生在夏季, 1999~2002年共发生8次明显突升事件. 2002年LGB69点4次突升事件均伴随空气湿度增加和太阳总辐射下降, 说明因降水过程导致. 下降风对LGB69点SSH变化有正向作用, 主要积累期风速的增大伴随着积雪增加, 大于7 m/s的吹雪临界风速引起表面高程的显著增加. 因大风天气有时伴随降水过程, 目前尚难于精确计算吹雪再堆积在全年物质积累中的百分比, 但估计其贡献率在35%以上. 相似文献
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7.
本文基于Sun等1999年发展的一个简单雪盖-大气-土壤传输模式（SAST）,改进了其雪盖的分层,提出了新的模式数值求解方法.改进后的新模型使用温度和雪层内的冰质量作为预报变量,在雪层处于冻结和融化状态时,有效地求解雪层温度分布和冻融过程,减少迭代次数,节省计算时间并提高其计算精度.新模型采用7层分层方法来代替旧SAST模型3层分层方法,在厚雪情况下3层分层方法过于简单.通过与5个前苏联站点观测数据的比较,新模式的模拟结果与大部分站点的观测值符合得较好.而当雪层较厚时,7层分层的模拟情况要好于3层分层.在Khabarovsk站,雪被强风吹走造成的差异以及土壤性质的差异,可能对模拟值与观测值的差别造成重要影响.在Tulun站,模拟结果的差异主要出现在雪盖厚度上,而对雪水当量的模拟情况与观测值实际吻合得很好.在对雪盖的生命期和积雪完全融化时间的模拟上面,从春季雪盖融化的趋势来看,新模式消融期和消融结束时间的模拟和实际观测符合得较好,并且7层分层结果要好于3层分层.在运算效率方面,新的3层模型比旧SAST模型运行时间要缩短20%.而由于7层分层方案有更多层来处理,它运行的速度与旧SAST相同,但更准确.考虑强风及改进雪面反照率参数化方案将是今后改进本雪盖模式的主要方向. 相似文献
8.
本文利用新的太阳EUV辐射资料、中性大气结构模式及大气成分的吸收及电离特性,计算了100—200km大气的光电离率随高度、太阳天顶角及太阳活动的变化,求得了E-F_1谷的变化特征;利用完整的光化模式求得了电子密度随太阳天顶角的变化及对太阳活动的响应,并与IRI模式作了比较.结果表明,1.太阳活动指数与光电离率间的相关关系一般为正,但在一定的高度范围内,或在天顶角大于临界值X_(cr)=60°时,两者之间可出现负相关;2.太阳活动明显地影响E-F_1谷高与谷厚,当天顶角不变时,谷高与谷厚均与太阳活动成正相关;3.本模式与IRI间的偏差因子明显随高度及太阳天顶角而变化. 相似文献
9.
本文利用新的太阳EUV辐射资料、中性大气结构模式及大气成分的吸收及电离特性,计算了100-200km大气的光电离率随高度、太阳天顶角及太阳活动的变化,求得了E-F1谷的变化特征;利用完整的光化模式求得了电子密度随太阳天顶角的变化及对太阳活动的响应,并与IRI模式作了比较.结果表明,1.太阳活动指数与光电离率间的相关关系一般为正,但在一定的高度范围内,或在天顶角大于临界值Xcr=60°时,两者之间可出现负相关;2.太阳活动明显地影响E-F1谷高与谷厚,当天顶角不变时,谷高与谷厚均与太阳活动成正相关;3.本模式与IRI间的偏差因子明显随高度及太阳天顶角而变化. 相似文献
10.
本文应用欧洲中期预报中心（ECMWF,European Centre for Medium\|Range Weather Forecasts—ERA\|40）资料和美国国家环境预测中心和国家大气研究中心(NCEP/NCAR, National Centers for Environmental Prediction/National Center for Atmospheric Research)资料,研究了青藏高原雪深变化对南海夏季风爆发的影响和ENSO对青藏高原降雪的影响.结果表明：（1）ECMWF的雪深资料是可信的,可以用来研究青藏高原雪深变化对南海夏季风爆发的影响;（2）青藏高原的积雪异常影响到500 hPa以上的温度异常和印度洋与大陆间的气温对比,一方面使上层的南亚高压移动速度发生变化,另一方面也影响到低层大气的运动和东西向风异常,在青藏高原少雪年,东印度洋产生西风异常和一个气旋对,而在青藏高原多雪年,东印度洋产生东风异常和一个反气旋对;（3）ENSO与青藏高原春季积雪关系密切.东太平洋SST正异常时,东印度洋和南海气压偏高,从而导致该区海陆经向压强梯度增强和西风异常.另外,此时青藏高原北部气压偏高,北风偏强,副热带锋面增强,同时,印度洋的SST偏高,为青藏高原降雪提供了水汽保障,这些都有利于青藏高原的降雪. 相似文献
11.
This paper synthesizes 10‐years' worth of interannual time‐series space‐borne ERS‐1 and RADARSAT‐1 synthetic aperture radar (SAR) data collected coincident with daily measurement of snow‐covered, land‐fast first‐year sea ice (FYI) geophysical and surface radiation data collected from the Seasonal Sea Ice Monitoring and Modeling Site, Collaborative‐Interdisciplinary Cryospheric Experiment and 1998 North Water Polynya study over the period 1992 to 2002. The objectives are to investigate the seasonal co‐relationship of the SAR time‐series dataset with selected surface mass (bulk snow thickness) and climate state variables (surface temperature and albedo) measured in situ for the purpose of measuring the interannual variability of sea ice spring melt transitions and validating a time‐series SAR methodology for sea ice surface mass and climate state parameter estimation. We begin with a review of the salient processes required for our interpretation of time‐series microwave backscatter from land‐fast FYI. Our results suggest that time‐series SAR data can reliably measure the timing and duration of surface albedo transitions at daily to weekly time‐scales and at a spatial scales that are on the order of hundreds of metres. Snow thickness on FYI immediately prior to melt onset explains a statistically significant portion of the variability in timing of SAR‐detected melt onset to pond onset for SAR time‐series that are made up of more than 25 images. Our results also show that the funicular regime of snowmelt, resolved in time‐series SAR data at a temporal resolution of approximately 2·5 images per week, is not detectable for snow covers less than 25 cm in thickness. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
12.
Claude R. Duguay Greg M. Flato Martin O. Jeffries Patrick Mnard Kim Morris Wayne R. Rouse 《水文研究》2003,17(17):3465-3483
A one‐dimensional thermodynamic model for simulating lake‐ice phenology is presented and evaluated. The model can be driven with observed daily or hourly atmospheric forcing of air temperature, relative humidity, wind speed, cloud amount and snowfall. In addition to computing the energy balance components, key model output includes the temperature profile at an arbitrary number of levels within the ice/snow (or the water temperature if there is no ice) and ice thickness (clear ice and snow‐ice) on a daily basis, as well as freeze‐up and break‐up dates. The lake‐ice model is used to simulate ice‐growth processes on shallow lakes in arctic, sub‐arctic, and high‐boreal forest environments. Model output is compared with field and remote sensing observations gathered over several ice seasons. Simulated ice thickness, including snow‐ice formation, compares favourably with field measurements. Ice‐on and ice‐off dates are also well simulated when compared with field and satellite observations, with a mean absolute difference of 2 days. Model simulations and observations illustrate the key role that snow cover plays on the seasonal evolution of ice thickness and the timing of spring break‐up. It is also shown that lake morphometry, depth in particular, is a determinant of ice‐off dates for shallow lakes at high latitudes. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
13.
Lake ice supports a range of socio‐economic and cultural activities including transportation and winter recreational actives. The influence of weather patterns on ice‐cover dynamics of temperate lakes requires further understanding for determining how changes in ice composition will impact ice safety and the range of ecosystem services provided by seasonal ice cover. An investigation of lake ice formation and decay for three lakes in Central Ontario, Canada, took place over the course of two winters, 2015–2016 and 2016–2017, through the use of outdoor digital cameras, a Shallow Water Ice Profiler (upward‐looking sonar), and weekly field measurements. Temperature fluctuations across 0°C promoted substantial early season white ice growth, with lesser amounts of black ice forming later in the season. Ice thickening processes observed were mainly through meltwater, or midwinter rain, refreezing on the ice surface. Snow redistribution was limited, with frequent melt events limiting the duration of fresh snow on the ice, leading to a fairly uniform distribution of white ice across the lakes in 2015–2016 (standard deviations week to week ranging from 3 to 5 cm), but with slightly more variability in 2016–2017 when more snow accumulated over the season (5 to 11 cm). White ice dominated the end‐of‐season ice composition for both seasons representing more than 70% of the total ice thickness, which is a stark contrast to Arctic lake ice that is composed mainly of black ice. This research has provided the first detailed lake ice processes and conditions from medium‐sized north‐temperate lakes and provided important information on temperate region lake ice characteristics that will enhance the understanding of the response of temperate lake ice to climate and provide insight on potential changes to more northern ice regimes under continued climate warming. 相似文献
14.
Modelling melt and runoff from snow‐ and ice‐covered catchments is important for water resource and hazard management and for the scientific study of glacier hydrology, dynamics and hydrochemistry. In this paper, a distributed, physically based model is used to determine the effects of the up‐glacier retreat of the snowline on spatial and temporal patterns of melt and water routing across a small (0·11 km2) supraglacial catchment on Haut Glacier d'Arolla, Switzerland. The melt model uses energy‐balance theory and accounts for the effects of slope angle, slope aspect and shading on the net radiation fluxes, and the effects of atmospheric stability on the turbulent fluxes. The water routing model uses simplified snow and open‐channel hydrology theory and accounts for the delaying effects of vertical and horizontal water flow through snow and across ice. The performance of the melt model is tested against hourly measurements of ablation in the catchment. Calculated and measured ablation rates show a high correlation (r2 = 0·74) but some minor systematic discrepancies in the short term (hours). These probably result from the freezing of surface water at night, the melting of the frozen layer in the morning, and subsurface melting during the afternoon. The performance of the coupled melt/routing model is tested against hourly discharge variations measured in the supraglacial stream at the catchment outlet. Calculated and measured runoff variations show a high correlation (r2 = 0·62). Five periods of anomalously high measured discharge that were not predicted by the model were associated with moulin overflow events. The radiation and turbulent fluxes contribute c. 86% and c. 14% of the total melt energy respectively. These proportions do not change significantly as the surface turns from snow to ice, because increases in the outgoing shortwave radiation flux (owing to lower albedo) happen to be accompanied by decreases in the incoming shortwave radiation flux (owing to lower solar incidence angles) and increases in the turbulent fluxes (owing to higher air temperatures and vapour pressures). Model sensitivity experiments reveal that the net effect of snow pack removal is to increase daily mean discharges by c. 50%, increase daily maximum discharges by >300%, decrease daily minimum discharges by c. 100%, increase daily discharge amplitudes by >1000%, and decrease the lag between peak melt rates and peak discharges from c. 3 h to c. 50 min. These changes have important implications for the development of subglacial drainage systems. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
15.
湖冰厚度是湖泊在封冻期的重要物理参数,明晰其时空变化特征对于认识气候变暖背景下的湖冰响应规律具有重要的理论价值和现实意义.基于ERA5 Climate Reanalysis气温数据集、MODIS MOD09GQ数据产品和2019年湖冰钻孔测厚数据及雷达测厚数据,重建2000—2019年青海湖冰厚时间序列并分析其时空变化特征.结果表明:①2019年3月实测青海湖湖冰厚度平均增长速率为0.30 cm/d,高于2月份(0.12 cm/d).基于度日法湖冰生长模型模拟的2018年11月—2019年3月青海湖冰厚平均增长速率为0.34 cm/d,与实际观测数据相比,模拟冰厚误差为±2 cm,但在河流入湖口处和湖区南侧误差较大,且冰厚模拟数值在3月中旬前高估而之后有所低估.②青海湖多年平均冰厚介于32～37 cm,其中2008—2016年湖冰厚度年际变化剧烈,呈现先增大再稳定后减小的趋势.冻结初期湖冰厚度增长迅速,12月和1月湖冰增长速率分别为0.45和0.41 cm/d,2月后冰厚增长速率放缓,2月和3月分别为0.29和0.14 cm/d.③2000—2019年冰厚整体呈现北厚南薄、东厚西薄的空间格局,多年冰厚变化幅度湖区西部较东部稳定,湖冰平均厚度与完全封冻时长及封冻期呈正相关. 相似文献
16.
Observed reduction in recent sea ice areal extent and thickness has focused attention on the fact that the Arctic marine system appears to be responding to global‐scale climate variability and change. Passive microwave remote‐sensing data are the primary source underpinning these reports, yet problems remain in geophysical inversion of information on ice type and concentration. Uncertainty in sea‐ice concentration (SIC) retrievals is highest in the summer and fall, when water occurs in liquid phase within the snow–sea‐ice system. Of particular scientific interest is the timing and rate of new ice formation due to the control that this form of sea ice has on mass, energy and gas fluxes across the ocean–sea‐ice–atmosphere interface. In this paper we examine the critical fall freeze‐up period using in situ data from a ship‐based and aerial survey programme known as the Canadian Arctic Shelf Exchange study combined with microwave and optical Earth observations data. Results show that: (1) the overall physical conditions observed from aerial survey photography were well matched with coincident moderate‐resolution imaging spectroradiometer data and Radarsat ScanSAR imagery; (2) the shortwave albedo was linearly related to old ice concentration derived from survey photography; (3) the three SSM/I SIC algorithms (NASA Team (NT), NASA Team 2 (NT2), and Bootstrap (BT)) showed considerable discrepancies in pixel‐scale comparison with the Radarsat ScanSAR SICs well calibrated by the aerial survey data. The major causes of the discrepancies are attributed to (1) the inherent inability to detect the new thin ice in the NT and BT algorithms, (2) mismatches of the thin‐ice tie point of the NT2 algorithm, and (3) sub‐pixel ambiguity between the thin ice and the mixture of open water and sea ice. These results suggest the need for finer resolution of passive microwave sensors, such as AMSR‐E, to improve the precision of the SSM/I SIC algorithms in the marginal ice zone during early fall freeze‐up. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
17.
The magnitude and spatial distribution of snow on sea ice are both integral components of the ocean–sea‐ice–atmosphere system. Although there exists a number of algorithms to estimate the snow water equivalent (SWE) on terrestrial surfaces, to date there is no precise method to estimate SWE on sea ice. Physical snow properties and in situ microwave radiometry at 19, 37 and 85 GHz, V and H polarization were collected for a 10‐day period over 20 first‐year sea ice sites. We present and compare the in situ physical, electrical and microwave emission properties of snow over smooth Arctic first‐year sea ice for 19 of the 20 sites sampled. Physical processes creating the observed vertical patterns in the physical and electrical properties are discussed. An algorithm is then developed from the relationship between the SWE and the brightness temperature measured at 37 GHz (55°) H polarization and the air temperature. The multiple regression between these variables is able to account for over 90% of the variability in the measured SWE. This algorithm is validated with a small in situ data set collected during the 1999 field experiment. We then compare our data against the NASA snow thickness algorithm, designed as part of the NASA Earth Enterprise Program. The results indicated a lack of agreement between the NASA algorithm and the algorithm developed here. This lack of agreement is attributed to differences in scale between the Special Sensor Microwave/Imager and surface radiometers and to differences in the Antarctic versus Arctic snow physical and electrical properties. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
18.
The geophysical, thermodynamic and dielectric properties of snow are important state variables that are known to be sensitive to Arctic climate variability and change. Given recent observations of changes in the Arctic physical system (Arctic Climate Impact Assessment, 2004), it is important to focus on the processes that give rise to variability in the horizontal, vertical and temporal dimensions of the life‐history of snow on sea ice. The objectives in this study are to present these ‘state’ variables and to investigate the processes that govern variability in the vertical, horizontal and temporal dimension by using a case study over land‐fast first‐year sea ice for the period December 2003 to June 2004. Results from two sampling areas (thin and thick snowpacks) show that differences in snowpack thickness can substantially change the vertical and temporal evolution of snow properties. During the late fall and early winter (cooling period) we measured no significant changes in the physical properties, except for thin snow‐cover salinity, which decreased throughout the period. Fall‐snow desalination was only observed under thin snowpacks with a rate of ?0·12 ppt day?1. Significant changes occurred in the late winter and early spring (warming period), especially for snow grain size. Snow grain kinetic growth of 0·25–0·48 mm·day?1 was measured coincidently with increasing salinity and wetness for both thin and thick snowpacks. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献