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未来黄、东海营养盐浓度变化情景预测
引用本文:赵一丁,杨波,魏皓,赵亮.未来黄、东海营养盐浓度变化情景预测[J].海洋与湖沼,2015,46(5):983-994.
作者姓名:赵一丁  杨波  魏皓  赵亮
作者单位:中国海洋大学海洋环境学院 青岛 266100,中国海洋大学海洋环境学院 青岛 266100,天津科技大学海洋科学与工程学院 天津 300457,天津科技大学海洋科学与工程学院 天津 300457
基金项目:国家重点基础研究发展计划(973)项目,2010CB428904号,2011CB403606号;国家自然科学基金项目,41128006号,41276016号,41376112号。
摘    要:本文基于FGOALS(Flexible Global Ocean-Atmosphere-Land System model)对未来气候情景的预测结果,结合千年生态评估的未来两个情景下的河流营养盐载荷特征,利用黄、东海水动力模型和生态模型并采用降尺度的方法对未来黄、东海营养盐的分布特征进行情景预测。结果表明,两个情景下未来河口邻近海区营养盐浓度将显著增加,富营养化加剧;GO(Global Orchestration)情景下,河流无机氮载荷增幅较大,夏季黄海中部无机氮浓度明显升高;AM(Adapting mosaic)情景下,由于河流无机磷载荷增幅较大,海区氮磷比有所下降,夏季黄海中部表层无机氮浓度降低,而在底层升高。通过敏感性实验并结合收支分析对各海区水动力条件未来变化、河流载荷变化的相对贡献进行了评估:相对于水温和水动力环境改变,河流营养盐排放量的增长是未来营养盐浓度增加的主要原因。营养盐收支分析表明,未来对流和混合输运的变化有助于黄海营养盐浓度的增加,夏季生物量升高造成更多碎屑沉降并在底层矿化使得层化季节冷水团底部营养盐浓度增长;长江口邻近海区营养盐浓度增长主要受冲淡水羽流的影响;净初级生产增加加剧了营养盐的消耗。

关 键 词:营养盐浓度  未来情景预测  物理-生物耦合模型  降尺度  黄、东海
收稿时间:2015/1/23 0:00:00
修稿时间:2015/1/23 0:00:00

SCENARIO PREDICTION OF FUTURE NUTRIENT CONCENTRATION IN THE YELLOW SEA AND EAST CHINA SEA
ZHAO Yi-Ding,YANG Bo,WEI Hao and ZHAO Liang.SCENARIO PREDICTION OF FUTURE NUTRIENT CONCENTRATION IN THE YELLOW SEA AND EAST CHINA SEA[J].Oceanologia Et Limnologia Sinica,2015,46(5):983-994.
Authors:ZHAO Yi-Ding  YANG Bo  WEI Hao and ZHAO Liang
Institution:College of Physical and Environmental Oceanography, Ocean University of China, Qingdao 266100, China,College of Physical and Environmental Oceanography, Ocean University of China, Qingdao 266100, China,College of Marine Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China and College of Marine Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China
Abstract:Using modern data(1951-2000) of average wind filed and heat flux, we applied FGOALS(the Flexible Global Ocean-Atmosphere-Land System) model to run a downscaling three-dimensional physical-biological scheme in combination with river nutrient load, and predicted the future(2026-2075) distribution of nutrients in the Yellow Sea and East China Sea. Results show that nutrient concentration will increase significantly in adjacent estuaries, causing heavier eutrophication in both future scenarios. Two scenarios were played:GO(Global Orchestration) and AM(Adapting Mosaic). In GO scenario, DIN concentration will increase in the central Yellow Sea rises in summer due to large increase of river DIN load. In AM scenario, N/P ratio will decline, as the river DIP load increases sharply; in summer, DIN concentration in the central Yellow Sea will decline in the surface and rises in the bottom layer. Through sensitive experiment and budget analysis, we assessed relative contribution to the variation from hydrodynamics and river nutrient load. Results show that increase in nutrient export by rivers will be the major contributor. Nutrient budget analysis shows that advection and mixing will promote the nutrient concentration in the Yellow Sea. Summer biomass will increase and result in more nutrient-release in remineralization from sinking particulate organic matter in the bottom layer, then accumulate and stratify there seasonally. The offshore region of the Changjiang River estuary is mainly affected by Changjiang River plume. The net primary production will increase correspondingly to consume more nutrients.
Keywords:nutrient concentration  scenario prediction  physical-biological model  downscaling  Yellow Sea and East China Sea
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