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Parameter sensitivity study of the biogeochemical model in the China coastal seas

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Acta Oceanologica Sinica 2015年第12期34卷 51-60页

作者： ji xuanliang LIU Guimei GAO Shan WANG Hui National Marine Environmental Forecasting Center Key Laboratory of Research on Marine Hazards Forecasting National Marine Environmental Forecasting Center

In order to develop a coupled basin scale model of ocean circulation and biogeochemical cycling,we present a biogeochemical model including 12 components to study the ecosystem in the China coastal seas（CCS）.The formulation of phytoplankton mortality and zooplankton growth are modified according to biological characteristics of *** four sensitivity biological parameters,zooplankton assimilation efficiency rate（ZooAE_N）,zooplankton basal metabolism rate（ZooBM）,maximum specific growth rate of zooplankton（μ_（20）） and maximum chlorophyll to carbon ratio（Chl2C_m） are obtained in sensitivity experiments for the phytoplankton,and experiments about the parameter μ_（20＇）,half-saturation for phytoplankton NO_3 uptake（K_（NO_3）） and remineralization rate of small detritusN（SDeRRN） are *** results demonstrate that the biogeochemical model is quite sensitive to the zooplankton grazing parameter when it ranges from 0.1 to 1.2 d^（-1）.The K_（NO_3） and SDeRRN also play an important role in determining the nitrogen cycle within certain *** sensitive interval of KNO_3 is from 0.1 to 1.5（mmol/m^3）^（-1）,and interval of SEdRRN is from 0.01 and 0.1 d^（-1）.The observational data from September 1998 to July 2000 obtained at SEATS station are used to validate the performance of biological model after parameters *** results show that the modified model has a good capacity to reveal the biological process features,and the sensitivity analysis can save computational resources greatly during the model simulation.

关键词： China coastal seas biogeochemical model parameter sensitivity

Temporal and spatial variability of the carbon cycle in the east of China's seas:a three-dimensional physical-biogeochemical modeling study

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Acta Oceanologica Sinica 2017年第3期36卷 60-71页

作者： ji xuanliang LIU Guimei GAO Shan WANG Hui ZHANG Miaoyin National Marine Environmental Forecasting Center State Oceanic AdministrationBeijing 100081China Key Laboratory of Research on Marine Hazards Forecasting National Marine Environmental Forecasting CenterState Oceanic AdministrationBeijing 100081China

In the east of China＇s seas, there is a wide range of the continental shelf. The nutrient cycle and the carbon cycle in the east of China＇s seas exhibit a strong variability on seasonal to decadal time scales. On the basis of a regional ocean modeling system（ROMS）, a three dimensional physical-biogeochemical model including the carbon cycle with the resolution（1/12）°×（1/12）° is established to investigate the physical variations, ecosystem responses and carbon cycle consequences in the east of China＇s seas. The ROMS-Nutrient Phytoplankton Zooplankton Detritus（NPZD） model is driven by daily air-sea fluxes（wind stress, long wave radiation, short wave radiation, sensible heat and latent heat, freshwater fluxes） that derived from the National Centers for Environmental Prediction（NCEP） reanalysis2 from 1982 to 2005. The coupled model is capable of reproducing the observed seasonal variation characteristics over the same period in the East China Sea. The integrated air-sea CO_2 flux over the entire east of China＇s seas reveals a strong seasonal cycle, functioning as a source of CO_2 to the atmosphere from June to October, while serving as a sink of CO_2 to the atmosphere in the other months. The 24 a mean value of airsea CO_2 flux over the entire east of China＇s seas is about 1.06 mol/（m^2·a）, which is equivalent to a regional total of3.22 Mt/a, indicating that in the east of China＇s seas there is a sink of CO_2 to the atmosphere. The partial pressure of carbon dioxide in sea water in the east of China＇s seas has an increasing rate of 1.15 μatm/a（1μtm/a=0.101 325Pa）, but p H in sea water has an opposite tendency, which decreases with a rate of 0.001 3 a^（–1） from 1982 to *** activity is a dominant factor that controls the pCO_2 air in the east of China＇s seas, and followed by a temperature. The inverse relationship between the interannual variability of air-sea CO_2 flux averaged from the domain area and Ni？o3 SST Index indicates that the carbon cycle in the ea

关键词： the east of China's seas physical-biogeochemical model partial pressure of carbon dioxide in sea water air-sea CO2 flux

Comparison of air-sea CO2 flux and biological productivity in the South China Sea,East China Sea,and Yellow Sea:a three-dimensional physical-biogeochemical modeling study

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Acta Oceanologica Sinica 2017年第12期36卷 1-10页

作者： ji xuanliang LIU Guimei GAO Shan WANG Hui ZHANG Miaoyin National Marine Environmental Forecasting Center Beijing 100081China Key Laboratory of Research on Marine Hazards Forecasting National Marine Environmental Forecasting CenterState Oceanic AdministrationBeijing 100081China

Marginal seas play important roles in regulating the global carbon budget, but there are great uncertainties in estimating carbon sources and sinks in the continental margins. A Pacific basin-wide physical-biogeochemical model is used to estimate primary productivity and air-sea CO_2 flux in the South China Sea（SCS）, the East China Sea（ECS）, and the Yellow Sea（YS）. The model is forced with daily air-sea fluxes which are derived from the NCEP2 reanalysis from 1982 to 2005. During the period of time, the modeled monthly-mean air-sea CO_2 fluxes in these three marginal seas altered from an atmospheric carbon sink in winter to a source in summer. On annualmean basis, the SCS acts as a source of carbon to the atmosphere（16 Tg/a, calculated by carbon, released to the atmosphere）, and the ECS and the YS are sinks for atmospheric carbon（–6.73 Tg/a and –5.23 Tg/a, respectively,absorbed by the ocean）. The model results suggest that the sea surface temperature（SST） controls the spatial and temporal variations of the oceanic pCO_2 in the SCS and ECS, and biological removal of carbon plays a compensating role in modulating the variability of the oceanic pCO_2 and determining its strength in each sea,especially in the ECS and the SCS. However, the biological activity is the dominating factor for controlling the oceanic pCO_2 in the YS. The modeled depth-integrated primary production（IPP） over the euphotic zone shows seasonal variation features with annual-mean values of 293, 297, and 315 mg/（m^2·d） in the SCS, the ECS, and the YS, respectively. The model-integrated annual-mean new production（uptake of nitrate） values, as in carbon units, are 103, 109, and 139 mg/（m^2·d）, which yield the f-ratios of 0.35, 0.37, and 0.45 for the SCS, the ECS, and the YS, respectively. Compared to the productivity in the ECS and the YS, the seasonal variation of biological productivity in the SCS is rather weak. The atmospheric pCO_2 increases from 1982 to 2005, which is consistent with the anthropo

关键词： physical-biogeochemical model air to sea CO_2 flux South China Sea East China Sea Yellow Sea

Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China

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Acta Oceanologica Sinica 2015年第7期34卷 54-64页

作者： ji Qiyan ZHU Xueming WANG Hui LIU Guimei GAO Shan ji xuanliang XU Qing Key Laboratory of Ministry of Education for Coastal Disaster and Defence Hohai University Key Laboratory of Research on Marine Hazards Forecasting National Marine Environmental Forecasting CenterState Oceanic Administration

The prediction of sea surface temperature （SST） is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea （BYECS）. One is based on a surface net heat flux correction, named as Qcorrection （QC）, which nudges the flux correction to the model equation; the other is ensemble optimal interpolation （EnOI）, which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis （OSTIA） system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error （RMSE） of the four experiments is 1.74, 1.16, 1.30 and 0.91~C, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively. Although both two methods are effective in assimilating the SST, the EnOI shows more advantages than the QC, and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.

关键词： sea surface temperature data assimilation ensemble optimal interpolation quick correction Bohai Sea Yellow Sea East China Sea

Assimilating OSTIA SST into regional modeling systems for the Yellow Sea using ensemble methods

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Acta Oceanologica Sinica 2017年第3期36卷 37-51页

作者： ji xuanliang KWON Kyung Man CHOI Byoung-Ju LIU Guimei PARK Kwang-Soon WANG Hui BYUN Do-Seong LI Yun ji Qiyan ZHU Xueming National Marine Environmental Forecasting Center State Oceanic AdminstrationBeijing 100081China Key Laboratory of Research on Marine Hazards Forecasting National Marine Environmental Forecasting CenterState Oceanic AdminstrationBeijing 100081China Department of Oceanography Kunsan National UniversityGunsan 54150Republic of Korea Department of Oceanography Chonnam National UniversityGwangju 61186Republic of Korea Korea Institute of Ocean Science and Technology Ansan 15627Republic of Korea Korea Hydrographic and Oceanographic Agency Busan 49111Republic of Korea Marine Acoustics and Remote Sensing Laboratory Zhejiang Ocean UniversityZhoushan 316000China

The effects of sea surface temperature（SST） data assimilation in two regional ocean modeling systems were examined for the Yellow Sea（YS）. The SST data from the Operational Sea Surface Temperature and Sea Ice Analysis（OSTIA） were assimilated. The National Marine Environmental Forecasting Center（NMEFC） modeling system uses the ensemble optimal interpolation method for ocean data assimilation and the Kunsan National University（KNU） modeling system uses the ensemble Kalman filter. Without data assimilation, the NMEFC modeling system was better in simulating the subsurface temperature while the KNU modeling system was better in simulating SST. The disparity between both modeling systems might be related to differences in calculating the surface heat flux, horizontal grid spacing, and atmospheric forcing data. The data assimilation reduced the root mean square error（RMSE） of the SST from 1.78°C（1.46°C） to 1.30°C（1.21°C） for the NMEFC（KNU） modeling system when the simulated temperature was compared to Optimum Interpolation Sea Surface Temperature（OISST） SST dataset. A comparison with the buoy SST data indicated a 41%（31%） decrease in the SST error for the NMEFC（KNU） modeling system by the data assimilation. In both data assimilative systems, the RMSE of the temperature was less than 1.5°C in the upper 20 m and approximately 3.1°C in the lower layer in October. In contrast, it was less than 1.0°C throughout the water column in February. This study suggests that assimilations of the observed temperature profiles are necessary in order to correct the lower layer temperature during the stratified season and an ocean modeling system with small grid spacing and optimal data assimilation method is preferable to ensure accurate predictions of the coastal ocean in the YS.

关键词： ensemble optimal interpolation ensemble Kalman filter SST Yellow Sea assimilation

AMSR-E的C/X双波段垂直极化亮温反演海面盐度

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遥感技术与应用 2017年第2期32卷 356-362页

作者：王兆徽季轩梁廖菲宋清涛国家卫星海洋应用中心北京100081 国家海洋局空间海洋遥感与应用研究重点实验室北京100081 国家海洋环境预报中心北京100081 国家海洋局海洋灾害预报技术研究重点实验室北京100081 中国气象局广州热带海洋气象研究所广东广州510080 广州市气象台广东广州511430

利用星载传感器观测数据反演的大气海洋参数进行综合研究是物理海洋学等海洋学科获取信息的重要手段。特别是全球尺度精细化的海面盐度信息,只有通过卫星观测才能有效获得。星载微波辐射计能够获取低频波段的亮温数据,具有一定的海面盐... 详细信息

利用星载传感器观测数据反演的大气海洋参数进行综合研究是物理海洋学等海洋学科获取信息的重要手段。特别是全球尺度精细化的海面盐度信息,只有通过卫星观测才能有效获得。星载微波辐射计能够获取低频波段的亮温数据,具有一定的海面盐度反演能力。使用AMSR-E的C/X双波段垂直极化亮温数据和AMSR-E的L2b产品反演亚马孙河口海区和中国黄海东海海区的海面盐度,并将反演结果与WOA09气候态盐度数据进行比较。实验表明:使用星载微波辐射计的C/X双波段垂直极化亮温能够有效获得河口区域海面盐度的变化趋势,反演精度约为1.5psu,具有一定的应用价值,为将来我国盐度卫星的数据处理提供一定的帮助。

关键词：海面盐度星载微波辐射计 AMSR-E 反演算法

2001-2020年福建沿海赤潮灾害分级和时空分布特征研究

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海洋通报 2021年第5期40卷 578-590页

作者：何恩业季轩梁李晓李雪丁王丹杨静国家海洋环境预报中心自然资源部海洋灾害预报技术重点实验室北京100081 国家海洋局南海调查技术中心自然资源部海洋环境探测技术与应用重点实验室广东广州510310 山东省海洋科学研究院山东青岛266104 福建省海洋预报台福建福州350003

利用2001-2020年福建沿海赤潮事件记录资料和自然灾害风险判定方法,根据赤潮成灾面积、持续时间、危害类型、渔业直接经济损失等指标综合计算赤潮灾害指数。基于自然断点法,对赤潮灾害指数进行Ⅰ级、Ⅱ级、Ⅲ级、Ⅳ级等4个灾害级别分等... 详细信息

利用2001-2020年福建沿海赤潮事件记录资料和自然灾害风险判定方法,根据赤潮成灾面积、持续时间、危害类型、渔业直接经济损失等指标综合计算赤潮灾害指数。基于自然断点法,对赤潮灾害指数进行Ⅰ级、Ⅱ级、Ⅲ级、Ⅳ级等4个灾害级别分等定级。系统分析了福建沿海赤潮生物种类、时空分布特征和演变规律。结果表明:(1)2001-2020年福建沿海赤潮以灾害程度较轻的Ⅰ级和Ⅱ级为主,灾害程度较重的Ⅲ级和Ⅳ级仅占总次数的8.9%,但其造成的渔业直接经济损失达总损失的95.0%。(2)赤潮暴发次数和面积总体呈现下降趋势,但Ⅲ级和Ⅳ级灾害频次呈现波动特征。(3)季节尺度上表现为单波峰特征,5-6月是赤潮灾害最为严重的时段,赤潮暴发次数、面积和持续时间占总体的比例分别为73.3%、84.6%和74.9%,Ⅲ级和Ⅳ级灾害占总次数的95.2%。(4)空间尺度上,福州、宁德、厦门沿海赤潮累计次数和规模较大,但Ⅲ级和Ⅳ级赤潮灾害主要分布在泉州以北的福建沿海,泉州以南的福建海域赤潮灾害级别整体较低。(5)2001-2020年福建沿海赤潮原因种逐渐增多,硅藻占比减小、甲藻占比升高,有毒赤潮主要出现在宁德、福州、泉州海域,以米氏凯伦藻(Karenia mikimotoi)引发居多。(6)硅藻赤潮主要暴发在峡湾和海湾海域,而甲藻赤潮在峡湾、海湾和开阔的近岸海域均易暴发,近年来甲藻赤潮暴发位置呈现由福建北部向南部沿海扩张的趋势。引起这些变化的原因据推测与全球气候变化及福建近岸海域环境的变化密切相关。

关键词：赤潮有害藻华灾害分级自然断点法时空分布福建沿海

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典型东海原甲藻赤潮过程的环境影响因子分析

生态科学 2023年第6期42卷 63-73页

作者：何恩业王丹卢勇夺李晓季轩梁国家海洋环境预报中心自然资源部海洋灾害预报技术重点实验室北京100081 国家海洋局南海调查技术中心自然资源部海洋环境探测技术与应用重点实验室广州510310 山东省海洋科学研究院青岛266104 自然资源部海洋减灾中心北京100194

近二十年来,东海原甲藻(Prorocentrum donghaiense)在我国东海频繁引发赤潮,并已成为该海域的主要赤潮原因种之一。为研究该赤潮藻种对环境因子变化的响应,基于2019年5月浙江沿海赤潮发生区生态浮标和海洋台站的环境要素连续观测数据,... 详细信息

近二十年来,东海原甲藻(Prorocentrum donghaiense)在我国东海频繁引发赤潮,并已成为该海域的主要赤潮原因种之一。为研究该赤潮藻种对环境因子变化的响应,基于2019年5月浙江沿海赤潮发生区生态浮标和海洋台站的环境要素连续观测数据,结合主成分分析方法,对三次东海原甲藻赤潮生消过程及其成因进行了分析和讨论。结果表明,(1)持续的升温、降压、较高的湿度、较强的向岸风、充沛的营养盐以及海水盐度下降均是浙江沿海这几次东海原甲藻赤潮的重要诱发因素;(2)赤潮暴发期间偏弱的风速,缓慢升高的水温和气温均利于赤潮的维持;(3)溶解氧、pH与赤潮生物量呈显著正相关,亚硝氮与赤潮生物量呈显著负相关,三者的变化推测主要是赤潮生物光合作用产物和有机体分解产物的增加所引起;(4)赤潮后期偏高的pH、较强风速、盐度回升、气压升高以及水体营养盐含量的骤降均可加速赤潮的消亡。研究结果对认识东海原甲藻赤潮成因和生消机理有一定的指导意义,可为今后该种赤潮预警防控提供借鉴。

关键词：东海原甲藻赤潮主成分分析叶绿素a 环境因子

基于网络Meta分析的瘢痕药物预防及治疗评价

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中华损伤与修复杂志（电子版） 2017年第3期12卷 176-181页

作者：龚振华周峰姚建潘选良季建峰杨军项铁南通市第一人民医院烧伤整形科 226001 南通市第一人民医院检验科 226001 浙江大学医学院附属第二医院烧伤科杭州310009

目的通过网络Meta分析方法,评价现行瘢痕治疗药物在瘢痕防治中的作用。方法通过检索PubMed,Blackwell,Cochrane Central,Web of Science,Ovid及Scopus等数据库及国内中国生物医学文献数据库、万方数据库和中国期刊全文数据库等,检索瘢... 详细信息

目的通过网络Meta分析方法,评价现行瘢痕治疗药物在瘢痕防治中的作用。方法通过检索PubMed,Blackwell,Cochrane Central,Web of Science,Ovid及Scopus等数据库及国内中国生物医学文献数据库、万方数据库和中国期刊全文数据库等,检索瘢痕药物治疗及预防的相关文献,将文献提供的相关数据录入到Excel电子表格中,再将电子表格导入到R(2.15.1版)软件(http://***/)中,利用Meta软件包及Q检验等进行分析。结果通过数据库检索,本研究总计纳入35篇文献,汇总分析,药物对瘢痕治疗的总体有效率为(80.0±3.0)%,总体复发率为(28.0±3.0)%。瘢痕治疗作用的大小顺序大致为:激素类、博来霉素、5-氟尿嘧啶、丝裂霉素C、维拉帕米及胶原酶。其中胶原酶治疗效应的相对危险性值(OR)小于1,提示该药物对瘢痕的治疗不仅无效,而且可能有害;而5-氟尿嘧啶的OR区间包含1,其治疗作用也有待进一步的证实。药物辅助治疗对瘢痕复发作用的大小依次为:博来霉素、5-氟尿嘧啶、维拉帕米、激素类、咪喹莫特、秋水仙碱、他莫昔芬,其中可信区间包含50%的有咪喹莫特、他莫昔芬及维拉帕米。瘢痕药物治疗总体有效率之间的相互比较,汇总后I^2=95.6%,Q检验显示P<0.0001。而对瘢痕药物辅助治疗复发率的分析中,激素类药物及咪喹莫特对瘢痕复发的效果明显优于其他几种药物,而他莫昔芬对瘢痕复发的预防作用最低。结论用于瘢痕治疗的药物可以选择激素类、博来霉素、丝裂霉素C、维拉帕米等;而用于预防术后复发可选激素类,其他药物的作用尚有待证实。

关键词： Meta分析瘢痕药物疗法预防