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1.
北极海冰对全球气候起着非常重要的调制作用,海冰范围是海冰监测的基本参数。近40年,北极地区持续变暖,北极海冰显著减少,进而引发北极自然环境恶化、北半球极端天气频发、全球海平面上升等一系列环境和气候问题。准确获取北极海冰范围及其演变趋势,确定海冰变化对全球气候系统的响应,是研究和预测全球气候变化趋势的关键之一。HasISST和OISST海冰数据集在海冰监测中应用最为广泛,可为北极地区长时间序列海冰变化研究提供基础数据,但这2套数据集空间分辨率相对较低,应用于北极关键区对中国气候响应研究方面存在很大的局限,为解决这一问题和弥补国内海冰监测微波遥感数据的空白,2011年6月27日,国家卫星气象中心（National Satellite Meteorological Center, NSMC）发布了FY（Fengyun, FY）北极海冰数据集,该数据集利用搭载在FY卫星上的微波成像仪（Microwave Radiation Imager, MWRI）数据,使用Enhance NASA Team算法制作,该算法利用前向辐射传输模型模拟北极地区4种海表类型（海水、新生冰、一年冰和多年冰）在不同大气条件下MWRI辐射亮温,进而得到每种大气条件下0~100%的海冰覆盖度查找表（海冰覆盖度每次增加1%）,通过观测值与模拟值的比对得到海冰覆盖度,由该数据集计算得到的北极海冰范围在大部分区域与实际情况相符。该产品虽已进行通道间匹配误差修正和定位精度偏差订正,但由于其搭载的微波成像仪（Microwave Radiation Imager, MWRI）天线长度有限,造成传感器探测到的地物回波信号相对较弱,难以区分海冰和近岸附近的陆地,影响了该数据集的精度和应用。为解决这一问题,本文基于美国冰雪中心（National Snow and Ice Data Center, NSIDC）发布的海冰产品对FY海冰数据集进行优化,NSIDC产品利用判断矩阵对海岸线附近的像元进行识别,并对误差像元进行不同程度的修正,由NSIDC产品计算得到的北极海冰范围与实际情况更为符合。数据集优化大大提高了FY海冰数据集的精度,研究结果表明,优化后FY海冰数据集与NSIDC产品相关系数高达0.9997,且二者日、月、年平均最大海冰范围偏差仅为3.5%、1.9%、0.9%,且FY海冰数据集优化过程对其较好的空间分异特征无明显影响。该数据集可正确地反映北极海冰范围及其变化情况,且海岸线附近海冰的分布情况更准确,可为北极海冰变化研究提供可靠的基础数据。 相似文献
2.
Comparative analysis of microwave brightness temperature data in Northeast China using AMSR-E and MWRI products 总被引：1，自引：1，他引：0
With such significant advantages as all-day observation, penetrability and all-weather coverage, passive microwave remote
sensing technique has been widely applied in the research of global environmental change. As the satellite-based passive microwave
remote sensor, the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) loaded on NASA’s (National Aeronautics
and Space Administration of USA) Aqua satellite has been popularly used in the field of microwave observation. The Microwave
Radiation Imager (MWRI) loaded on the Chinese FengYun-3A (FY-3A) satellite is an AMSR-E-like conical scanning microwave sensor,
but there are few reports about MWRI data. This paper firstly proposed an optimal spatial position matching algorithm from
rough to exact for the position matching between AMSR-E and MWRI data, then taking Northeast China as an example, comparatively
analyzed the microwave brightness temperature data derived from AMSR-E and MWRI. The results show that when the antenna footprints
of the two sensors are filled with either full water, or full land, or mixed land and water with approximate proportion, the
errors of brightness temperature between AMSR-E and MWRI are usually in the range from −10 K to +10 K. In general, the residual
values of brightness temperature between the two microwave sensors with the same spatial resolution are in the range of ±3
K. Because the spatial resolution of AMSR-E is three times as high as that of MWRI, the results indicate that the quality
of MWRI data is better. The research can provide useful information for the MWRI data application and microwave unmixing method
in the future. 相似文献
3.
利用CryoSat-2卫星测高数据反演波弗特海的海冰厚度，并利用2010~2013年10月份仰视声呐(ULS)和2011年冰桥计划（IceBridge）数据对结果进行精度评估。结果表明，测高反演的海冰吃水深度与ULS吃水深度差值的最大值和标准差分别为14 cm和4 cm；测高反演的海冰厚度与冰桥计划海冰厚度差值的平均值和标准差分别为2.7 cm和65.7 cm，优于Laxon(2013)研究结果（分别优化2.1 cm和6.6 cm）。在此基础上，研究2011~2017年波弗特海夏冬两季的海冰厚度变化，发现二者具有类似的分布特征，且冬季3月海冰覆盖范围更广，厚度更大；进一步分析2011~2017年3月份冬季海冰厚度年际变化，发现其呈整体下降趋势，且2012年最小，2014年最大。 相似文献
4.
积雪对自然环境和人类活动都有极其重要的影响。积雪参数（雪面积、雪深和雪水当量）反演对水文模型和气候变化研究有着实际的意义。然而,目前森林区的雪深遥感反演精度一直有待于进一步提高。东北地区是我国最大的天然林区和重要的季节性积雪区之一,本文利用FY3B卫星微波成像仪（MWRI）L1级亮温数据和L2级雪水当量数据,以及东北典型林区野外实测雪深数据,对Chang算法、NASA 96算法和FY3B雪深业务化反演算法进行了验证与分析。结果表明：在东北典型林区的雪深反演中,Chang算法和NASA 96算法反演的雪深波动都比较大,当森林覆盖度f≤0.6时,NASA 96算法表现比较好,均方根误差值在3种算法中较小,但当f >0.6时,NASA 96算法失真严重。当考虑纯森林像元（f=1）时,Chang算法低估了雪深47%。当f≤0.3时,FY3B业务化算法始终优于Chang算法。整体上,FY3B业务化算法相对稳定,具有较高的精度。 相似文献
5.
Snow and sea ice thermodynamics in the Arctic： Model validation and sensitivity study against SHEBA data 总被引：2，自引：0，他引：2
Timo Vihma 《极地研究(英文版)》2008,19(2):108-122
Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance. 相似文献
6.
Kebiao Mao Ying Ma Lang Xia Xinyi Shen Zhiwen Sun Tianjue He Guanhua Zhou 《中国地理科学(英文版)》2014,24(5):599-606
It has been observed that low temperature, rainfall, snowfall, frost have never occurred over the past 50 years in the southern China, and weather in this area is very complex, so the monitoring equipments are few. Optical and thermal infrared remote sensing is influenced much by clouds, so the passive microwave Advanced Microwave Scanning Radiometer-Earth Observing System （AMSR-E） data are the best choice to monitor and analyze the development of disaster. In order to improve estimation accuracy, the dynamic learn- ing neural network was used to retrieve snow depth. The difference of brightness temperatures of TB18.7v and TB36.sv, TBI8.7H and TB36.sH, TB23,sv and TB89v, TBz3.8H and TB89H are made as four main input nodes and the snow depth is the only one output node of neural network. The mean and the standard deviation of retrieval errors are about 4.8 cm and 6.7 cm relative to the test data of ground measurements. The application analysis indicated that the neural network can be utilized to monitor the change of snow intensity distribution through passive microwave data in the complex weather of the southern China. 相似文献
7.
北极海冰范围时空变化及其与海温气温间的数值分析 总被引：1，自引：0，他引：1
本文利用美国国家冰雪中心提供的1989-2014年海冰范围资料,分析了北极海冰范围的年际变化和季节变化规律。分析发现,北极海冰范围呈减少趋势,每年减小
8.
I.INTKODUCTIONTheArcticOcean,withanareaofapproximately9.5X106krnZ,ispredominantlysea--icecoveredthroughouttheyearinitscentralarea,whilethesouthedgeofmarginalicezone(MIZ)variesseasonally.ThemaxinltlmofIcecoverextentoccursbetweenFebruaryandMarch,whilethemininlunlisbetweenAugustandseptember.Placingtheiceedgeto8%iceconcentration(percentarealcoveragesofseaice)isopleths,variationofextentofsea--icecoveroftheArcticOceanisI)etween9X106--16X106kmZIbytheobservationofasatellite--bornescanningm… 相似文献
9.
10.
On the basis of artificial neural network （ANN） model, this paper presents an algorithm for inversing snow depth with use of AMSR-E （Advanced Microwave Scanning Radiometer-Earth Observing System （EOS）） dataset, i.e., brightness temperature at 18.7 and 36.5GHz in Qinghai-Tibet Plateau during the snow season of 2002-2003. In order to overcome the overfitting problem in ANN modeling, this methodology adopts a Bayesian regularization approach. The experiments are performed to compare the results obtained from the ANN-based algorithm with those obtained from other existing algorithms, i.e., Chang algorithm, spectral polarization difference （SPD） algorithm, and temperature gradient （TG） algorithm. The experimental results show that the presented algorithm has the highest accuracy in estimating snow depth. In addition, the effects of the noises in datasets on model fitting can be decreased due to adopting the Bayesian regularization approach. 相似文献
11.
Sea ice is a sensitive indicator of climate change and an important component of climate system models. The Los Alamos Sea Ice Model 5.0(CICE5.0) was introduced to the Beijing Climate Center Climate System Model(BCC_CSM) as a new alternative to the Sea Ice Simulator(SIS). The principal purpose of this paper is to analyze the impacts of these two sea ice components on simulations of basic Arctic sea ice, atmosphere, and ocean states. Two sets of experiments were conducted with the same configurations except for the sea ice component used, i.e., SIS and CICE. The distributions of sea ice concentration and thickness reproduced by the CICE simulations in both March and September were closer to actual observations than those reproduced by SIS simulations, which presented a very thin sea ice cover in September. Changes in sea ice conditions also brought about corresponding modifications to the atmosphere and ocean circulation. CICE simulations showed higher agreement with the reference datasets than did SIS simulations for surface air temperature, sea level pressure, and sea surface temperature in most parts of the Arctic Ocean. More importantly, compared with simulations with SIS, BCC_CSM with CICE revealed stronger Atlantic meridional overturning circulation(AMOC), which is more consistent with actual observations. Thus, CICE shows better performance than SIS in BCC_ CSM. However, both components demonstrate a number of common weaknesses, such as overestimation of the sea ice cover in winter, especially in the Nordic Sea and the Sea of Okhotsk. Additional studies and improvements are necessary to develop these components further. 相似文献
12.
Analysis of multi-dimensional SAR for determining the thickness of thin sea ice in the Bohai Sea 总被引：1，自引：0，他引：1
Flat thin ice (<30 cm thick) is a common ice type in the Bohai Sea, China. Ice thickness detection is important to offshore exploration and marine transport in winter. Synthetic aperture radar (SAR) can be used to acquire sea ice data in all weather conditions, and it is a useful tool for monitoring sea ice conditions. In this paper, we combine a multi-layered sea ice electromagnetic (EM) scattering model with a sea ice thermodynamic model to assess the determination of the thickness of flat thin ice in the Bohai Sea using SAR at different frequencies, polarization, and incidence angles. Our modeling studies suggest that co-polarization backscattering coefficients and the co-polarized ratio can be used to retrieve the thickness of flat thin ice from C- and X-band SAR, while the co-polarized correlation coefficient can be used to retrieve flat thin ice thickness from L-, C-, and X-band SAR. Importantly, small or moderate incidence angles should be chosen to avoid the effect of speckle noise. 相似文献
13.
Abundance,biomass and composition of the ice algal and phytoplank-ton communities were investigated in the southeastern Laptev Sea in spring 1999.Diatoms dominated the algal communities and pennate diatoms dominated the dia-tom population.12 dominant algal species occurred within sea ice and underlyingwater column,including Fragilariopsis oceanica,F.cylindrus,Nitzschiafrigida,N.promare,Achnanthes taeniata,Nitzschia neofrigida,Naviculapelagica,N.vanhoef fenii,N.septentrionalis,Melosira arctica,Clindrothecaclosterium and Pyrarnimonas sp.The algal abundance of bottom 10 cm sea icevaried between 14.6 and 1562.2×10~4 ceils l~(-1)with an average of 639.0×10~4cells l~(-1),and the algal biomass ranged from 7.89 to 2093.5μg C l~(-1)with an av-erage of 886.9μg C l~(-1),which were generally one order of magnitude higherthan those of sub-bottom ice and two orders of magnitude higher than those ofunderlying surface water.The integrated algal abundance and biomass of lower-most 20 cm ice column were averagely 7.7 and 12.2 times as those of upper 20 mwater column,respectively,suggesting that the ice algae might play an importantrole in maintaining the coastal marine ecosystem before the thawing of sea ice.Icealgae influenced the phytoplankton community of the underlying water column.However,the“seeding”of ice algae for phytoplankton bloom was negligible be-cause of the iow phytoplankton biomass within the underlying water column. 相似文献
14.
The variation in Arctic sea ice has significant implications for climate change due to its huge influence on the global heat balance. In this study, we quantified the spatio-temporal variation of Arctic sea ice distribution using Advanced Microwave Scanning Radiometer(AMSR-E) sea-ice concentration data from 2003 to 2013. The results found that, over this period, the extent of sea ice reached a maximum in 2004, whereas in 2007 and 2012, the extent of summer sea ice was at a minimum. It declined continuously from 2010 to 2012, falling to its lowest level since 2003. Sea-ice extent fell continuously each summer between July and mid-September before increasing again. It decreased most rapidly in September, and the summer reduction rate was 1.35 × 10~5 km~2/yr, twice as fast as the rate between 1979 and 2006, and slightly slower than from 2002 to 2011. Area with 90% sea-ice concentration decreased by 1.32 × 10~7 km~2/yr, while locations with 50% sea-ice concentration, which were mainly covered by perennial ice, were near the North Pole, the Beaufort Sea, and the Queen Elizabeth Islands. Perennial Arctic ice decreased at a rate of 1.54 × 10~5 km~2 annually over the past 11 years. 相似文献
15.
Snow cover is characterized by the high albedo, low thermal conductivity, and notable heat transition during phase changes. Thus, snow cover significantly affects the ground thermal regime. A comparison of the snow cover in high latitudes or high-altitude snowy mountain regions indicates that the eastern Tianshan Mountains (China) show a characteristically thin snow cover (snow depth below 15 cm) with remarkable temporal variability. Based on snow depth, heat flux, and ground temperature from 2014 to 2015 in the Urumqi River source, the spatialtemporal characteristics of snow cover and snow cover influences on the thermal conditions of active layer in the permafrost area were analyzed. During the autumn (Sept. - Oct.), thin and discontinuous snow cover can noticeably accelerate the exothermic process of the ground, producing a cooling effect on the shallow soil. During the winter (Nov. - Mar.), it is inferred that the effective thermal insulation starts with snow depth exceeding 10 cm during early winter. However, the snow depth in this area is generally below 15 cm, and the resulting snow-induced thermal insulation during the winter is very limited. Due to common heavy snowfalls in the spring (Apr. to May), the monthly mean snow thickness in April reached to 15 cm and remained until mid-May. Snow cover during the spring significantly retarded the ground warming. Broadly, snow cover in the study area exerts a cooling effect on the active layer and plays a positive role in the development and preservation of permafrost. 相似文献
16.
积雪深度是表征积雪特征的重要参数,也是区域气候变化最敏感的响应因子之一。利用1979-2010年逐日中国雪深长时间序列数据集,采用GIS空间分析和地统计方法,分析了青藏高原积雪深度的时空变化规律及异常空间分布特征。结果表明：近32年来,青藏高原雪深呈显著增加趋势,增加速率为0.26 cm/10a,其中,昆仑高寒荒漠地带雪深增加最为明显,增加速率达0.73 cm/10a;20世纪80年代至90年代青藏高原雪深呈逐步增加趋势,21世纪初变化平稳;青藏高原4个季节雪深变化均呈现为上升趋势,尤以冬季增加最为明显,增加速率达0.57 cm/10a。青藏高原东南、西部和南部为雪深分布高值区;逐像元回归分析表明,高原雪深呈增加趋势的像元数占全区像元总数的67.1%,其中有91.3%为轻度和中度增加,主要分布在高原北部和西部;最大雪深变化基本维持在-0.1~0.1 cm/a（45.47%）之间,在昆仑北翼山地、柴达木山地、羌塘高寒地带南部等局部地区最大雪深有增加趋势,主要是轻度增加,面积比例为36.66%。果洛那曲高寒地带、青南高寒地带和羌塘高寒地带为青藏高原积雪深度异常变化敏感区。 相似文献
17.
In this paper, we investigated the potential of Advanced Microwave Scanning Radiometer for Earth Observation System （AMSR-E） for flood monitoring. The proposed approach was based on the polarized ratio index （PRI）, which was computed by using AMSR-E data at 37GHz, vertically and horizontally polarized brightness temperature values and the water surface fraction （WSF） got by using the PRI at 37GHz. Moderate Resolution Imaging Spectroradiometer （MODIS） data were used to validate the WSF values. The analysis of flood and waterlogging using the WSF map on July 6, 2003 indicates that the use of WSF for flood and waterlogging disaster assessment is feasible. Utilizing the correlation of WSF derived from AMSR-E and water area derived from MODIS, the water area of the Huaihe River Basin were computed by only using AMSR-E data in the summer of 2003, which overcame the influence of cloud on water estimation using MODIS data during flood. 相似文献
18.
As an important part of global climate system, the Polar sea ice is effccting on global climate changes through ocean surface radiation balance, mass balance, energy balance as well as the circulating of sea water temperature and salinity. Sea ice research has a centuries - old history. The many correlative sea ice projects were established through the extensive international cooperation during the period from the primary research of intensity and the boaring capacity of sea ice to the development of sea/ice/air coupled model. Based on these reseamhes, the sea ice variety was combined with the global climate change. All research about sea ice includes： the physical properties and processes of sea ice and its snow cover, the ecosystem of sea ice regions, sea ice and upper snow albedo, mass balance of sea ice regions, sea ice and climate coupled model. The simulation suggests that the both of the area and volume of polar sea ice would be reduced in next century. With the developing of the sea ice research, more scientific issues are mentioned. Such as the interaction between sea ice and the other factors of global climate system, the seasonal and regional distribution of polar sea ice thickness, polar sea ice boundary and area variety trends, the growth and melt as well as their influencing factors, the role of the polynya and the sea/air interactions. We should give the best solutions to all of the issues in future sea ice studying. 相似文献
19.
北极熊是北极最重要的哺乳动物之一,近年来数量却在减少。海冰作为北极熊狩猎、活动和繁殖的平台,是其栖息地的重要组成部分。因此其种群栖息地变化主要依赖于海冰变化。本文基于美国雪冰中心的海冰密集度和NOAA提供的ETOPO1基岩数据,分析了北极海冰密集度、开阔水域面积、海冰消退时间、海冰出现时间、开阔水域季节长度的年际变化,进而评价北极熊栖息地的稳定性。结果表明,海冰密集度呈现降低的趋势,开阔水域面积增大,多年冰数量减少,大多变为一年冰。海冰消退时间提前,海冰出现时间延后,开阔水域季节长度大幅增加,与1992年相比增加了72 d。19个栖息地中,巴伦支海是开阔水域面积和季节长度变化贡献最大的海域,增加速度分别为9.71×103 km2/a和71.69 d/10a。以开阔水域季节长度变化率为依据,将北极熊栖息地划分为稳定、次稳定和不稳定3个等级。总共有3个稳定栖息地,包括分布在相对其他栖息地而言纬度较低的楚科奇海、西哈得孙湾和南哈得孙湾。13个次稳定栖息地,包括拉普捷夫海、喀拉海、东格陵兰、巴芬湾、戴维斯海峡、福克斯湾、布西亚湾、麦克林托克海峡、梅尔维尔子爵海峡、挪威湾、北波弗特、南波弗特和兰开斯特海峡。3个不稳定栖息地,均位于70°N以北,包括北极盆地、巴伦支海和凯恩盆地。稳定区主要位于低纬度,不稳定区全部位于高纬度。该分级结果表明高纬度地区虽然海冰覆盖多,但是年际变化十分显著,不稳定的3个区域内北极熊对海冰变化适应时间更少,年际迁移变化大,对北极熊的生存发展更为不利。 相似文献
20.
光学与微波遥感的新疆积雪覆盖变化分析 总被引：1，自引：0，他引：1
利用2002-2013年冬季的MODIS光学遥感数据,以及AMSR-E、AMSR2与MWRI被动微波遥感数据,建立了新疆地区冬季每日积雪分布遥感反演模型。首先,将Terra与Aqua双星MODIS的积雪产品融合,初步去云并最大化积雪信息;然后,利用AMSR-E/AMSR2和MWRI被动微波数据进行每日雪盖提取;最后,利用被动微波遥感数据反演得到的每日雪盖结果对双星融合后依然有云的像元进行替换,得到每日积雪分布情况。据此模型提取了11年间冬季的积雪天数信息,结合气象台站观测数据,分析了新疆冬季积雪的年内和年际变化规律。结果表明,新疆地区积雪主要分布在北部新疆,积雪天数与地形关系密切,山区积雪天数较多,盆地及城市区积雪天数较少;积雪天数年内变化是从11月到次年1月随温度降低逐渐增加,从1月到3月积雪天数则逐渐减少。新疆地区积雪天数在这11年中存在一定的波动,积雪天数与该年的平均气温,以及月低于0℃的天数存在显著相关性,与降雪量关系不明显。新疆地区近年来积雪天数重心有向西向南移动的趋势,这可能与全球气候变暖导致多年积雪融化有关。 相似文献