Application of an ice-ocean coupled model to Bohai Sea ice simulation

The HAMSOM(Hamburg Shelf Ocean Model),a high-resolution regional ice-ocean coupled model,was applied to investigate the seasonal evolution of Bohai Sea ice for winter 2015/2016.HAM SOM was initialized with monthly climatological temperature and salinity data from WOA13 and driven by hourly meteorological data obtained from the NCEP above the sea surface and tides at the open boundary.The ice model used here is a modified Hibler-type dynamic-thermodynamic sea ice model based upon viscous-plastic rheology.The ice extent,concentration,area,thickness,length of ice season as well as the distance between the top of Liaodong Bay(North China) and the outer ice edge line were simulated and compared with the observed data.Three types of modeling experiments were carried out to investigate the effects of wind,tide,and both wind and tide on Bohai Sea ice.The re sults show that wind,as both a dynamic and a thermodynamic factor,has a significant impact on the ice thickness,ice area,and ice-freezing and ice breakup dates as well as the ice velocity,while tides are a dynamic factor that influences only the ice velocity.During the severe ice period,the wind speed intensity increased by 25%,the average ice thickness thickened by approximately 4.0 cm in Liaodong B ay,approximately 2.1 cm in Bohai B ay and approximately2.5 cm in Laizhou B ay,and the total ice coverage area and total ice actual area increased by about 2×10~4 km~2 and 1.4×10~4 km2,respectively.While the tidal amplitude intensity increased by 25%,the average ice velocity increased by approximately 0.1 m/s.     

A coupled regional Arctic sea ice-ocean model: configuration and application

A regional sea ice-ocean coupled model for the Arctic Ocean was developed, based on the MITgcm ocean circulation model and classical Hibler79 type two categorythermodynamics-dynamics sea ice model. The sea ice dynamics and thermodynamicswere considered based on Viscous-Plastic (VP) and Winton three-layer models, respectively. A detailed configuration of coupled model has been introduced. Special attention has been paid to the model grid setup, subgrid paramerization, ice-ocean coupling and open boundary treatment. The coupled model was then applied and two test run examples were presented. The first model run was a climatology simulation with 10 years (1992?002) averaged NCAR/NCEP reanalysis data as atmospheric forcing. The second model run was a seasonal simulation for the period of 1992?007. The atmospheric forcing was daily NCAR/NCEP reanalysis. The climatology simulation captured the general pattern of the sea ice thickness distribution of the Arctic, i.e., the thickest sea ice is situated around the CanadaArchipelago and the north coast of the Greenland. For the second model run, themodeled September Sea ice extent anomaly from 1992?007 was highly correlated with the observations, with a linear correlation coefficient of 0.88. Theminimum of the Arctic sea ice area in the September of 2007 was unprecedented. The modeled sea ice area and extent for this minimum was overestimated relative to the observations. However, it captured the general pattern of the sea ice retreat.     

A coupled ice-ocean ecosystem model for 1-D and 3-D applications in the Bering and Chukchi Seas

Primary production in the Bering and Chukchi Seas is strongly influenced by the annual cycle of sea ice. Here pelagic and sea ice algal ecosystems coexist and interact with each other. Ecosystem modeling of sea ice associated phytoplankton blooms has been understudied compared to open water ecosystem model applications. This study introduces a general coupled ice-ocean ecosystem model with equations and parameters for 1-D and 3-D applications that is based on 1-D coupled ice-ocean ecosystem model development in the landfast ice in the Chukchi Sea and marginal ice zone of Bering Sea. The biological model includes both pelagic and sea ice algal habitats with 10 compartments： three phytoplankton （pelagic diatom, flagellates and ice algae： D, F, and Ai） , three zooplankton （copepods, large zooplankton, and microzooplankton ： ZS, ZL, ZP） , three nutrients （ nitrate ＋ nitrite, ammonium, silicon ： NO3 , NH4, Si） and detritus （Det）. The coupling of the biological models with physical ocean models is straightforward with just the addition of the advection and diffusion terms to the ecosystem model. The coupling with a multi-category sea ice model requires the same calculation of the sea ice ecosystem model in each ice thickness category and the redistribution between categories caused by both dynamic and thermodynamic forcing as in the physical model. Phytoplankton and ice algal self-shading effect is the sole feedback from the ecosystem model to the physical model.     

Spatial-temporal characters of Antarctic sea ice variation

1　Introduction Nowadaysglobalclimatechangehasbeenanimportantissueintheworld.Antarctic areaisjustthekeyandsensitiveregion,fromwhichscientistsaretryingtheirbesttofind theomenofglobalclimatechange.Andfortherevolvingglobalatmosphere,PolarRegions arecoldsource.TheoceanicandatmosphericconditionofPolarRegionsisimportantto globalatmosphericcirculationandclimatechange.Antarcticareaisoneofthecoldsources ofglobalearth atmospheresystem,whileequatorialareaisitsmainheatsource(seeZhou andLuetal.1996).…     

北极海冰范围时空变化及其与海温气温间的数值分析

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\begin{array}{c}5.91\times {10}^4\mathit{k}{m}^2\end{array},夏季减少趋势显著,冬季减少趋势弱。北极海冰范围显现相对稳定的季节变化规律,海冰的结冰和融化主要发生在各个边缘海,夏季期间的海冰具有融化快、冻结快的特征。结合海温、气温数据,进行北极海冰范围与海温、气温间的数值分析,结果表明北极海冰范围变化通过影响北极海温变化进而影响北极气温变化。海冰范围的季节变化滞后于海温和气温的季节变化。基于北极考察走航海温气温数据,进行楚科奇海海冰范围线与海温气温间的数值分析,发现楚科奇海海冰范围线所在区域的海温、气温与纬度高低、离陆地远近有关。     

Interannual Variability and Scenarios Projection of Sea Ice in Bohai Sea Part I: Variation Characteristics and Interannual Hindcast

The Bohai Sea is one of the southernmost areas for sea ice formation in the northern hemisphere.Sea ice disasters in this body of water severely affect marine activities and the safety of coastal residents.In this study,we analyze the variation characteristics of the sea ice in the Bohai Sea and establish an annual regression model based on predictable mode analysis method.The results show the following:1)From 1970 to 2018,the average ice grade is(2.6±0.8),with a maximum of 4.5 and a minimum of 1.0.Liaodong Bay(LDB)has the heaviest ice conditions in the Bohai Sea,followed by Bohai Bay(BHB)and Laizhou Bay(LZB).Interannual variation is obvious in all three bays,but the linear decreasing trend is significant only in BHB.2)Three modes are obtained from empirical orthogonal function analysis,namely,single polarity mode with the same sign of anomaly in all of the three bays and strong interannual variability(82.0%),the north–south dipole mode with BHB and LZB showing an opposite sign of anomalies to that in LDB and strong decadal variations(14.5%),and a linear trend mode(3.5%).Critical factors are analyzed and regression equations are established for all the principal components,and then an annual hindcast model is established by synthesizing the results of the three modes.This model provides an annual spatial prediction of the sea ice in the Bohai Sea for the first time,and meets the demand of operational sea ice forecasting.     

北极熊栖息地稳定性的遥感评估方法

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。     

The research of Polar sea ice and its role in climate change

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.     

Climatology and seasonal variability of satellite-derived chlorophyll a around the Shandong Peninsula

The chlorophyll a(Chl a) is an important indicator of marine ecosystems. The spatiotemporal variation of the Chl a greatly aff ects the mariculture and marine ranching in coastal waters of the Shandong Peninsula. In the current study, the climatology and seasonal variability of surface Chl-a concentration around the Shandong Peninsula are investigated based on 16 years(December 2002–November 2018) of satellite observations. The results indicate that the annual mean Chl-a concentration is greater in the Bohai Sea than in the Yellow Sea and decreases from coastal waters to off shore waters. The highest Chl-a concentrations are found in Laizhou Bay(4.2–8.0 mg/m 3), Haizhou Bay(4.2–5.9 mg/m 3) and the northeast coast of the Shandong Peninsula(4.4–5.0 mg/m 3), resulting from the combined eff ects of the intense riverine input and long residence time caused by the concave shape of the coastline. The seasonal Chl-a concentration shows a signifi cant spatial variation. The Chl-a concentrations in these three subregions generally exhibit an annual maximum in August/September, due to the combined eff ects of sea surface temperature, river discharge and sea surface wind. In the southeast coast region, however, the Chl-a concentration is lowest throughout the year and reaches a maximum in February with a minimum in July, forced by the seasonal evolution of the Yellow Sea Cold Water and monsoon winds. The interannual Chl-a concentration trends vary among regions and seasons. There are signifi cant increasing trends over a large area around Haizhou Bay from winter to summer, which are mainly caused by the rising sea surface temperature and eutrophication. In other coastal areas, the Chl-a concentration shows decreasing trends, which are clearest in summer and induced by the weakening land rainfall. This study highlights the diff erences in the Chl-a dynamics among regions around the Shandong Peninsula and is helpful for further studies of coupled physical-ecological-human interactions at multiple scales.     

Antarctica Sea-ice Oscillation and Its Possible Impact on Monsoon of South Sea

Antarctic sea-ice oscillation index with a seesaw pattern is defined using NCEP/NCAR reanalysis girds data of monthly Antarctica sea-ice concentration from 1979 to 2002. The relationships between the index of winter and the summer precipitations in China as well as the onset date of the summer East Asia monsoon are presented. The study result shows that the grids of correlation coefficients passed 5% confidence level between Antarctic sea-ice oscillation index and Antarctic sea-ice concentration are more than 1/3 of all grids of Antarctica sea-ice, that means the index can represent 1/3 sea-ice area. The winter index has a significant correlation with abnormal summer (June-August) precipitation in China. The area of positive correlation lies in the Yangtze River basin and its south, and that of negative correlation lies mainly in the north of Yangtze River basin. While the winter index is positive (negative), the onset date of South China Sea monsoon is earlier (later), with a probability of 79% (80%). Consequently, a conceptual model is given in term of discussing the possible process between the winter Antarctic sea ice and the monsoon precipitation in China.     

Winter climate change and sea ice-atmosphere interaction at high northern latitudes in ERA40 dataset

1 IntroductionGreen house gases, such as CO2,CH4, N2O and so on are released to the atmosphereconstantly by human activities. These gases insert positive radiative forcing to the climate.Meanwhile, aerosol, which are also released by human activities, ins…     

Spatio-temporal Variation of Arctic Sea Ice in Summer from 2003 to 2013

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.     

基于CryoSat-2数据反演2011～2017年波弗特海海冰厚度变化

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。     

极地海冰-海洋参数遥感反演模型分布式共享研究

本文以SOA开放式架构与OGC标准规范,提出了极地海冰-海洋参数遥感反演模型分布式共享服务体系。服务体系以"模型服务"为核心,探讨了模型服务接口和模型服务的互操作问题。为了简化极地海冰-海洋参数遥感反演模型的分布式共享过程,提出了极地海冰-海洋参数遥感反演模型共享服务平台的概念。共享服务平台处于模型与模型应用客户端之间,可以实现两者之间的数据转化和功能协同,以及实现模型算法与其他功能的分离,使模型开发者可以专注于模型算法的设计和实现。最后,以海冰密集度遥感反演模型和冰间湖识别模型为例,实现了极地海冰-海洋参数遥感反演模型分布式共享方法。     

Environmental capacity of petroleum hydrocarbon pollutants in Jiaozhou Bay, China: Modeling and calculation

An environmental capacity model for the petroleum hydrocarbon pollutions (PHs) in Jiaozhou Bay is constructed based on field surveys, mesocosm, and parallel laboratory experiments. Simulated results of PHs seasonal successions in 2003 match the field surveys of Jiaozhou Bay resaonably well with a highest value in July. The Monte Carlo analysis confirms that the variation of PHs concentration significantly correlates with the river input. The water body in the bay is reasonably subjected to self-purification processes, such as volatilization to the atmosphere, biodegradation by microorganism, and transport to the Yellow Sea by water exchange. The environmental capacity of PHs in Jiaozhou Bay is 1500 tons per year IF the seawater quality criterion (Grade Ⅰ/Ⅱ, 0.05 mgL-1) in the region is to be satisfied. The contribution to self-purification by volatilization, biodegradation, and transport to the Yellow Sea accounts for 48%, 28%, and 23%, respectively, which make these three processes the main ways of PHs purification in Jiaozhou Bay.     

Decadal variability shown by the arctic ocean hydrochemical data and reproduced by an ice-ocean model

The Arctic is experiencing a significant warming trend as well as a decadal oscillation. The atmospheric circulation represented by the Polar Vortex and the sea ice cover show decadal variabilities, while it has been difficult to reveal the decadal oscillation from the ocean interior. The recent distribution of Russian hydrochemical data collected from the Arctic Basin provides useful information on ocean interior variabilities. Silicate is used to provide the most valuable data for showing the boundary between the silicate-rich Pacific Water and the opposite Atlantic Water. Here, it is assumed that the silicate distribution receives minor influence from seasonal biological productivity and Siberian Rivers outflow. It shows a clear maximum around 100m depth in the Canada Basin, along with a vertical gradient below 100 m, which provides information on the vertical motion of the upper boundary of the Atlantic Water at a decadal time scale. The boundary shifts upward （downward）, as realized by the silicate reduction （increase） at a fixed depth, responding to a more intense （weaker） Polar Vortex or a positive （negative） phase of the Arctic Oscillation. A coupled ice-ocean model is employed to reconstruct this decadal oscillation.     

Practical Model of Sea Ice Thickness of Bohai Sea Based on MODIS Data

Sea ice thickness is one of the most important input parameters in the studies on sea ice disaster prevention and mitigation. It is also the most important content in remote sensing monitoring of sea ice. In this study, a practical model of sea ice thickness (PMSIT) was proposed based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In the proposed model, the MODIS data of the first band were used to estimate sea ice thickness and the difference between the second-band reflectance and the fifth-band reflectance in the MODIS data was calculated to obtain the difference attenuation index (DAI) of each pixel. The obtained DAI was used to estimate the integrated attenuation coefficient of the first band of the MODIS at the pixel level. Then the model was used to estimate sea ice thickness in the Bohai Sea with the MODIS data and then validated with the actual sea ice survey data. The validation results showed that the proposed model and corresponding parameterization scheme could largely avoid the estimation error of sea ice thickness caused by the spatial and temporal heterogeneity of sea ice extinction and allowed the error of 18.7% compared with the measured sea ice thickness.     

Analysis of multi-dimensional SAR for determining the thickness of thin sea ice in the Bohai Sea

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.     

Mechanism of sea ice formation based on comprehensive observation data in Liaodong Bay,China

Sea ice disaster is one of the principal natural hazards that affect some coastal areas of China, and the formation of ice cover in a wave field has important characteristics. However, analysis of the mechanism in which waves affect the thermodynamic process of sea ice is lacking, and the influence of waves is not taken into consideration in numerical models of sea ice, largely because of a lack of simultaneous observations of waves and sea ice. Using observational data of the sea ice cycle in the coastal waters of Liaodong Bay(China), we analyzed the characteristics of hydrology, meteorology, and sea ice thickness during the formation of sea ice, and explored the changes in the interrelationships among heat fluxes, waves, and sea ice under actual sea conditions. The results could provide a decision-making support as a reference to the establishment and improvement of China's early warning system to sea ice disasters, and the protection of ice drilling operations and production platform safety.     

Numerical Study on Seasonal Transportation of the Suspended Sediments in the Modern Yellow River Mouth Effected by the Artificial Water and Sediment Regulation

Since 2002, an artificial water and sediment regulation(AWSR) has been carried out, which largely reduced water and sediment discharged from the Yellow River into the Bohai Sea. Although the sediment transport in the Yellow River Mouth(YRM) has been observed and modeled intensively since AWSR, but preferentially for the non-storm conditions. In this study, a three-dimensional current-wave-sediment coupled model, DHI-MIKE numerical model, was used to examine the seasonal suspended-sediment transport in the YRM after the AWSR. Results show that the seasonal distribution of suspended-sediments in the YRM is dominated by wind and wave rather than river input. The major transport pathway of suspended-sediments is from the western Laizhou Bay to the Bohai Strait during the winter monsoon, especially in storm events. In addition, about 66% of the river sediments deposit within 30 km of the YRM, which is smaller than previous estimations. It suggests that the YRM has been eroded in recent decades.