基于高光谱遥感的渤海海冰厚度半经验模型

Sea ice thickness is one of the most important input parameters for the prevention and mitigation of sea ice disasters and the prediction of local sea environments and climates. Estimating the sea ice thickness is currently the most important issue in the study of sea ice remote sensing. With the Bohai Sea as the study area, a semiempirical model of the sea ice thickness(SEMSIT) that can be used to estimate the thickness of first-year ice based on existing water depth estimation models and hyperspectral remote sensing data according to an optical radiative transfer process in sea ice is proposed. In the model, the absorption and scattering properties of sea ice in different bands(spectral dimension information) are utilized. An integrated attenuation coefficient at the pixel level is estimated using the height of the reflectance peak at 1 088 nm. In addition, the surface reflectance of sea ice at the pixel level is estimated using the 1 550–1 750 nm band reflectance. The model is used to estimate the sea ice thickness with Hyperion images. The first validation results suggest that the proposed model and parameterization scheme can effectively reduce the estimation error associated with the sea ice thickness that is caused by temporal and spatial heterogeneities in the integrated attenuation coefficient and sea ice surface. A practical semi-empirical model and parameterization scheme that may be feasible for the sea ice thickness estimation using hyperspectral remote sensing data are potentially provided.     

Variation of diffuse attenuation coefficient of downwelling irradiance in the Arctic Ocean

The diffuse attenuation coefficient(Kd) for downwelling irradiance is calculated from solar irradiance data measured in the Arctic Ocean during 3rd and 4th Chinese National Arctic Research Expedition(CHINARE), including 18 stations and nine stations selected for irradiance profiles in sea water respectively. In this study, the variation of attenuation coefficient in the Arctic Ocean was studied, and the following results were obtained. First, the relationship between attenuation coefficient and chlorophyll concentration in the Arctic Ocean has the form of a power function. The best fit is at 443 nm, and its determination coefficient is more than 0.7. With increasing wavelength, the determination coefficient decreases abruptly. At 550 nm, it even reaches a value lower than 0.2. However, the exponent fitted is only half of that adapted in low-latitude ocean because of the lower chlorophyll-specific absorption in the Arctic Ocean. The upshot was that, in the case of the same chlorophyll concentration, the attenuation caused by phytoplankton chlorophyll in the Arctic Ocean is lower than in low-latitude ocean. Second, the spectral model, which exhibits the relationship of attenuation coefficients between 490 nm and other wavelength, was built and provided a new method to estimate the attenuation coefficient at other wavelength, if the attenuation coefficient at 490 nm was known. Third, the impact factors on attenuation coefficient, including sea ice and sea water mass, were discussed. The influence of sea ice on attenuation coefficient is indirect and is determined through the control of entering solar radiation. The linear relationship between averaging sea ice concentration(ASIC, from 158 Julian day to observation day) and the depth of maximum chlorophyll is fitted by a simple linear equation. In addition, the sea water mass, such as the ACW(Alaskan Coastal Water), directly affects the amount of chlorophyll through taking more nutrient, and results in the higher attenuation coefficient in the layer of 30–60 m. Consequently, the spectral model of diffuse attenuation coefficient, the relationship between attenuation coefficient and chlorophyll and the linear relationship between the ASIC and the depth of maximum chlorophyll, together provide probability for simulating the process of diffuse attenuation coefficient during summer in the Arctic Ocean.     

北极各海域海冰覆盖范围的变化特征

Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming.This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions.The results indicate that sea ice extent reduction during 1979–2013 is most significant in summer,following by that in autumn,winter and spring.In years with rich sea ice,sea ice extent anomaly with seasonal cycle removed changes with a period of 4–6 years.The year of 2003–2006 is the ice-rich period with diverse regional difference in this century.In years with poor sea ice,sea ice margin retreats further north in the Arctic.Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic.Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes,which shows an coincident change in the Arctic and sub regions.Since 2002,Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic,followed by C1 and C3.Sea ice changes in different regions show three relationships.The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high,suggesting good consistency of ice variation.In the Atlantic sector,sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea.Sea ice changes in the central Arctic are affected by surrounding seas.     

Spatio-temporal analysis of the melt onset dates over Arctic sea ice from 1979 to 2017

The melt onset dates(MOD) over Arctic sea ice plays an important role in the seasonal cycle of sea ice surface properties, which impacts Arctic surface solar radiation absorbed by the ice-ocean system. Monitoring interannual variations in MOD is valuable for understanding climate change. In this study, we investigated the spatio-temporal variability of MOD over Arctic sea ice and 14 Arctic sub-regions in the period of 1979 to 2017 from passive microwave satellite data. A set of mathematical and ...     

Numerical Simulation of Bohai Oil Spill in the Winter Sea Ice Period

The Bohai Sea is a seasonal icy sea area that has the lowest latitude of any sea experiencing icing in the northern hemisphere, and simulation studies on oil spills during its sea ice period are the key to analyzing winter oil spill accidents. This study applied the three-dimensional free surface to establish a high-resolution hydrodynamic model and simulate tidal distributions in the Bohai Sea. Then, the oil spill model of the open sea area and thermodynamic model were combined to establish a numerical model for the Bohai oil spill during the winter sea ice period. The hydrodynamic model and sea ice growth and melting model were verified, and the parameters were adjusted based on the measured values, which indicate that the numerical model established in this paper is of high accuracy,stability and ubiquity. Finally, after checking the calculations repeatedly, the diffusion coefficient for the Bohai Sea was determined to be 1.0×10~(–7 )m~2/s. It is better that the comprehensive weathering attenuation coefficient is lower than that of a non-winter oil spill, with 1.3×10~(–7 )m~2/s being the most appropriate coefficient. This study can provide the reliable technical support for the operational safety and reduction in losses caused by winter oil spill accidents for the petroleum industry.     

基于AMSR-E数据的多年冰密集度反演算法研究

In recent years, the rapid decline of Arctic sea ice area(SIA) and sea ice extent(SIE), especially for the multiyear(MY) ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square(rms) difference of MY SIA derived from the algorithm of this study are 0.65×106 km2 and0.69×106 km2 during January to March, –0.06×106 km2 and 0.14×106 km2 during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×106 km2 and 0.84×106 km2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang's, Lomax' and NASA TEAM algorithms.     

海冰对北极海冰边缘区大洋光学观测的影响评估

Diffuse attenuation coefficient(DAC) of sea water is an important parameter in ocean thermodynamics and biology, reflecting the absorption capability of sea water in different layers. In the Arctic Ocean, however, sea ice affects the radiance/irradiance measurements of upper ocean, which results in obvious errors in the DAC calculation. To better understand the impacts of sea ice on the ocean optics observations, a series of in situ experiments were carried out in the summer of 2009 in the southern Beaufort Sea. Observational results show that the profiles of spectral diffuse attenuation coefficients of seawater near ice cover within upper surface of 50 m were not contaminated by the sea ice with a solar zenith angle of 55°, relative azimuth angle of 110°≤φ≤115° and horizontal distance between the sensors and ice edge of greater than 25 m. Based on geometric optics theory, the impact of ice cover could be avoided by adjusting the relative solar azimuth angle in a particular distance between the instrument and ice. Under an overcast sky, ice cover being 25 m away from sensors did not affect the profiles of spectral DACs within the upper 50 m either. Moreover, reliable spectral DACs of seawater could be obtained with sensors completely covered by sea ice.     

Application of the HY-1 satellite to sea ice monitoring and forecasting

The HY-1A satellite is the first oceanic satellite of China. During the winter of 2002-2003, the data of the HY-1A were applied to the sea ice monitoring and forecasting for the Bohai Sea of China for the fhst time. The sea ice retrieval system of the HY-1A has been constructed. It receives 1B data from the satellite, outputs sea ice images and provides digital products of ice concentration, ice thickness and ice edge, which can be used as important information for sea ice monitoring and the initial fields of the numeric sea ice forecast and as one of the reference data for the sea ice forecasting verification. The sea ice retrieval system of the satellite is described, including its processes, methods and parameters. The retrieving results and their application to the sea ice monitoring and forecasting for the Bohai Sea are also discussed.     

Dynamics of Sea Ice and Spectrum of Ice Force

Spectrum and self-excite characters are the two significant characters of the dynamics of sea ice. The spectrum character of sea ice is mainly shown by the spectrum of ice force. The spectrum character of the sea ice is its intrinsic attributes. When the spectrum of ice force from the dynamic response of ice and structure interaction are evaluated, the effect of dynamic character of the structure must be eliminated. In this paper, the ice force spectrum at Bohai Bay and Liaodong Bay is evaluated from the displacement and strain responses of a single degree and a multi-degree freedom structure. The evaluated ice force spectrum can be used to define the spectrum character of ice in the analysis of ice induced vibration.     

北极王湾表层沉积物中的粘土矿物及其对物源与古环境变化的指示意义

Kongsfjorden is a typical fjord on the edge of the ice cap of the Arctic Svalbard-Barents Sea. Its inner bay is connected with a modern glacier front along the direction of the fjord axis with a significant gradient change in the parameters of hydrology, sedimentation, and biology. In summer, ice and snow melt-water and floating ice collapse continuously and thus transport the weathering products on the surrounding land into the sea. Thus Kongsfjorden is regards as a natural laboratory for the study of unique sedimentation in polar fjords under modern glacial-sea water conditions. In this study, fifty-two surface sediments were collected in Kongsfjorden for clay mineral analysis to study the sediment source and sediment-transport process. Our results indicate that clay minerals in the surface sediments from Kongsfjorden are mainly composed of illite, chlorite, and kaolinite, and no smectite is found. Rocks from different periods exposed extensively in the surrounding areas of Kongsfjorden provide an important material basis for clay minerals in the Kongsfjorden. Kaolinite may be mainly derived from the fluvial deposits, weathered from reddish sandstones and conglomerates during the Carboniferous Period.Illite is mainly derived from Proterozoic low-grade and medium-grade metamorphic phyllite, mica schist, and gneiss. While chlorite is mainly from Proterozoic low-grade metamorphic phyllite and mica schist. In the direction from the fluvio-glacial estuary to the sea of the glacier front of Kongsfjorden, illite increase gradually,and the content of kaolinite declines gradually. However, the change pattern of chlorite is insignificant, which may be related to the provenance. Kongsfjorden detritus is mainly transported by the fluvio-glacial streams and icebergs into the sea and deposited in the inner bay. Coarse sediments are rapidly deposited in the glacier front,estuary, and near-shore areas. Clay fraction begins to deposit significantly by 200–400 m after flowing into the sea,which due to the crystal behavior of clay minerals, hydrodynamic condition and flocculation. Kaolinite and chlorite on the south of the bay near the Blomstrandhalv?ya Island is mainly affected by ice-rafted detritus and thus can reveal the trajectory of transportation by the floating ice while entering the sea.     

Measuring solar irradiance profiles in the Arctic sea ice using fiber optic spectrometry via inclined holes

An irradiance profile measurement approach and profiling system were developed to measure the solar irradiance profile of the Arctic sea ice using fiber optic spectrometry. The approach involved using a miniature spectrometer to sense light signals collected and transmitted from a fiber probe. The fiber probe was small, and could thus move freely in inclined bore holes drilled in sea ice with its optical entrance pointing upward. The input-output relationship of the system was analyzed and built. Influence factors that determined the system output were analyzed. A correctional system output approach was proposed to correct the influence of these factors, and to obtain the solar irradiance profile based on the measurements outputted by this system. The overall performance of the system was examined in two ice floes in the Arctic during the 9 th Chinese National Arctic Research Expedition. The measured solar irradiance profiles were in good agreement with those obtained using other commercially available oceanographic radiometers. The derived apparent optical properties of sea ice were comparable to those of similar sea ice measured by other optical instruments.     

北极阿蒙森湾一年冰物理和光学性质的观测研究

利用加拿大环极冰间水道系统研究项目,作者对2007年11月24日至2008年1月26日北极群岛阿蒙森湾海域秋冬季节一年冰的物理和光学性质进行了观测研究。结果显示,观测期间的海冰厚度整体在27～108 cm范围内变化,积雪厚度仅为0～6 cm。海冰温度、盐度和密度在冰内的分布特征为:海冰表层最低温度为–22.4℃,底层最高温度为–2.2℃,冰内温度随深度单调增大;盐度变化范围为3.30～11.70,冰内盐度剖面呈现“C”形,即表层和底层盐度较大,而中间层盐度较小;海冰的平均密度略大,为（0.91±0.03）g/cm3。通过观测人造光源在海冰中的透射辐射谱分布,发现一年冰的光谱透射辐射在490 nm和589 nm处呈明显的双峰结构,但随着海冰厚度的增加,双峰结构逐渐减弱,体现了海冰对于不同谱段辐射能衰减作用的差异。在可见光范围内,裸冰和雪覆冰的吸收率最小值出现在490 nm,在443～490 nm范围内二者的吸收率随波长增大而降低,在490～683 nm范围内二者的吸收率随波长增大而升高,但雪覆冰的吸收率在可见光范围内基本保持不变,体现了雪覆冰吸收率的光谱独立性。一年冰的谱衰减系数随波长呈“U”字形分布,紫光和红光谱段的衰减系数较大,中间谱段的衰减系数较小,589 nm波长的衰减系数最小,为1.7 m–1。将谱衰减系数在可见光范围内积分,得到一年冰的积分漫射衰减系数约为2.3 m–1,略高于多年浮冰的漫射衰减系数1.5 m–1。阿蒙森湾一年冰与加拿大海盆北部多年浮冰辐射光学性质的差异,主要源于陆源物质输入引起的海冰内含物组分的改变,而不同组分对光谱的吸收和散射性质不同,进一步导致了光学性质的整体变化。     

冰–水侧向融化过程的实验室试验研究

为了探究冰层侧向融化过程,定量分析影响冰层侧向融化的主导因素,在低温实验室水槽内实施了浮冰融化实验。同步测量了冰底面和表面生消过程、浮冰侧向融化过程,同时记录了实验室气温、冰样内部不同深度处的冰温及开阔水域不同深度处的水温,利用相关分析方法研究了不同要素之间的关系及其对浮冰侧向融化速率的影响规律。结果表明,融冰前期冰样内部不同深度处的侧向融化缓慢且均匀,平均融化速率为0.05 mm/h;融冰中后期不同深度处的侧向融化速率显著增加且不再均匀,平均融化速率为0.15 mm/h。平均侧向融化速率与气温的相关系数较好（r=0.82）,优于其与平均水温（r=0.74）和水–冰温度差（r=0.48）的相关系数。建立侧向融化速率随温度（气温、水温）和深度变化的定量关系,可以准确描述浮冰侧向融化过程的非均匀性。同时验证了进行非均匀性侧向融化试验技术的可行性,为更加接近北极真实情况考虑风速和光源条件的海冰试验奠定了基础。     

基于MODIS数据的渤海海冰厚度反演算法优化

海冰厚度是监测与研究渤海海冰的重要参数。为了获取更加可靠的渤海海冰厚度数据,本研究基于MODIS数据对海冰厚度反演中的冰水分离环节和冰厚计算方法都进行了改进。对于冰水分离环节,本文在Canny边缘检测算子提取海冰基础上,加入了二值化处理、阈值判别等步骤,实现了较高精度的渤海海冰范围自动化提取。通过试验确定了海冰厚度与反照率指数关系模型中的参数,包括海冰衰减系数和海水反照率参数,使其更加符合渤海海区的物理特征。将改进后算法的海冰厚度反演结果与渤海海上石油平台实测数据进行比较,并分析了误差来源。结果表明,经过对算法的改进,海冰厚度与反照率指数关系模型的反演结果与实测数据之间的平均绝对误差由7.05 cm缩小到2.74 cm,相关系数由0.434提高到0.485。     

MODIS渤海海冰遥感资料反演

鉴于渤海海冰监测和预报对海冰卫星遥感数字化产品的迫切需求,本文利用MODIS的1B级数据进行渤海海冰参数反演,提供海冰遥感图像和海冰密集度、冰厚数值产品,作为渤海海冰监测和海冰数值预报初始场的重要信息来源,以及海冰预报质量检验的参考依据之一。反演结果表明,其各通道对海冰性质有很好的反映,资料信号比较稳定,对不同密集度和厚度的冰有较好的区分,相对NOAA/AVHRR和HY-1A资料有更好的实际应用价值;Terra/MODIS和HY-1A/COCTS海冰遥感反演结果对比也为HY-1A系列卫星海冰遥感的改进和提高提供有益的启示。     

一种融合纹理特征与NDVI的随机森林海冰精细分类方法

海冰的精准分类对于掌握海冰生长发育状况,保障航海安全等具有重要意义。由于受数据源和分类方法等影响,使得海冰分类精度提高受限。本文面向高空间分辨率的光学遥感影像,提出了一种融合纹理特征和归一化差分植被指数（NDVI）的海冰精准分类方法,运用随机森林分类器构建海冰分类方法。以青岛胶州湾为实验区,高分二号（GF-2）为实验数据,进行了海冰类型提取,并与其他分类方法进行对比。结果显示:针对GF-2高分辨率光学遥感数据,融合纹理特征和NDVI的随机森林方法,相比于传统的随机森林、支持向量机、自动决策树和融合纹理特征的最大似然分类方法,总体分类精度分别提高13.70%、11.60%、19.22%、29.37%。Kappa系数分别提高0.16、0.13、0.22、0.44。相比于融合纹理特征和归一化水指数（NDWI）的随机森林方法,总体分类精度提高了9.67%,Kappa系数提高了0.09。这表明本文构建的海冰分类方法可有效提高海冰分类精度,为海冰的精确分类提供了一种有效的技术手段。     

一种基于变分优化的逐步订正法在海冰密集度分析中的应用

卫星遥感获取的海冰密集度观测资料中包含着空间多尺度信息。然而,多数传统的数据同化方法难以在海冰密集度变化较为复杂的海冰边缘区有效提取这些多尺度信息。为解决上述问题,本文设计了一种基于变分优化的逐步订正分析方法—空间多尺度递归滤波,该方法是逐步订正分析与最小化算法的结合,它能够从长波到短波依次提取观测中的各种空间尺度信息。与传统的客观分析相比,这种基于变分的多尺度分析方法不仅能够在最小化过程中一次性的提取出观测中的多尺度信息,而且能够方便合理的进行参数配置。单观测点同化试验的分析结果表明,空间多尺度递归滤波方法具有良好的观测信息空间传播能力。随后在二维海冰密集度的分析试验中,该方法能够较好的提取SSMI海冰密集度观测资料中的空间多尺度信息,进而获得高精度的海冰密集度分析结果。