共查询到18条相似文献，搜索用时 125 毫秒
1.
夏江江 严中伟 周文 FONG Soi Kun LEONG Ka Cheng TANG Iu Man CHANG S W LEONG W K 靳少非 《海洋学报(英文版)》2015,34(9):78-84
Projections of potential submerged area due to sea level rise are helpful for improving understanding of the influence of ongoing global warming on coastal areas. The Ensemble Empirical Mode Decomposition method is used to adaptively decompose the sea level time series in order to extract the secular trend component. Then the linear relationship between the global mean sea level(GMSL) change and the Zhujiang(Pearl) River Delta(PRD)sea level change is calculated: an increase of 1.0 m in the GMSL corresponds to a 1.3 m(uncertainty interval from1.25 to 1.46 m) increase in the PRD. Based on this relationship and the GMSL rise projected by the Coupled Model Intercomparison Project Phase 5 under three greenhouse gas emission scenarios(representative concentration pathways, or RCPs, from low to high emission scenarios RCP2.6, RCP4.5, and RCP8.5), the PRD sea level is calculated and projected for the period 2006–2100. By around the year 2050, the PRD sea level will rise 0.29(0.21 to 0.40) m under RCP2.6, 0.31(0.22 to 0.42) m under RCP4.5, and 0.34(0.25 to 0.46) m under RCP8.5, respectively.By 2100, it will rise 0.59(0.36 to 0.88) m, 0.71(0.47 to 1.02) m, and 1.0(0.68 to 1.41) m, respectively. In addition,considering the extreme value of relative sea level due to land subsidence(i.e., 0.20 m) and that obtained from intermonthly variability(i.e., 0.33 m), the PRD sea level will rise 1.94 m by the year 2100 under the RCP8.5scenario with the upper uncertainty level(i.e., 1.41 m). Accordingly, the potential submerged area is 8.57×103 km2 for the PRD, about 1.3 times its present area. 相似文献
2.
On the basis of the satellite maps of sea level anomaly(MSLA) data and in situ tidal gauge sea level data,correlation analysis and empirical mode decomposition(EMD) are employed to investigate the applicability of MSLA data,sea level correlation,long-term sea level variability(SLV) trend,sea level rise(SLR) rate and its geographic distribution in the South China Sea(SCS).The findings show that for Dongfang Station,Haikou Station,Shanwei Station and Zhapo Station,the minimum correlation coefficient between the closest MSLA grid point and tidal station is 0.61.This suggests that the satellite altimeter MSLA data are effective to observe the coastal SLV in the SCS.On the monthly scale,coastal SLV in the western and northern part of SCS are highly associated with coastal currents.On the seasonal scale,SLV of the coastal area in the western part of the SCS is still strongly influenced by the coastal current system in summer and winter.The Pacific change can affect the SCS mainly in winter rather than summer and the affected area mostly concentrated in the northeastern and eastern parts of the SCS.Overall,the average SLR in the SCS is 90.8 mm with a rising rate of(5.0±0.4) mm/a during1993–2010.The SLR rate from the southern Luzon Strait through the Huangyan Seamount area to the Xisha Islands area is higher than that of other areas of the SCS. 相似文献
3.
Based on a coupled ocean-sea ice model, this study investigates how changes in the mean state of the atmosphere in different CO_2 emission scenarios(RCP 8.5, 6.0, 4.5 and 2.6) may affect the sea ice in the Bohai Sea, China,especially in the Liaodong Bay, the largest bay in the Bohai Sea. In the RCP 8.5 scenario, an abrupt change of the atmospheric state happens around 2070. Due to the abrupt change, wintertime sea ice of the Liaodong Bay can be divided into 3 periods: a mild decreasing period(2021–2060), in which the sea ice severity weakens at a nearconstant rate; a rapid decreasing period(2061–2080), in which the sea ice severity drops dramatically; and a stabilized period(2081–2100). During 2021–2060, the dates of first ice are approximately unchanged, suggesting that the onset of sea ice is probably determined by a cold-air event and is not sensitive to the mean state of the atmosphere. The mean and maximum sea ice thickness in the Liaodong Bay is relatively stable before 2060, and then drops rapidly in the following decade. Different from the RCP 8.5 scenario, atmospheric state changes smoothly in the RCP 6.0, 4.5 and 2.6 scenarios. In the RCP 6.0 scenario, the sea ice severity in the Bohai Sea weakens with time to the end of the twenty-first century. In the RCP 4.5 scenario, the sea ice severity weakens with time until reaching a stable state around the 2070 s. In the RCP 2.6 scenario, the sea ice severity weakens until the2040 s, stabilizes from then, and starts intensifying after the 2080 s. The sea ice condition in the other bays of the Bohai Sea is also discussed under the four CO_2 emissions scenarios. Among atmospheric factors, air temperature is the leading one for the decline of the sea ice extent. Specific humidity also plays an important role in the four scenarios. The surface downward shortwave/longwave radiation and meridional wind only matter in certain scenarios, while effects from the zonal wind and precipitation are negligible. 相似文献
4.
TAI Chang-Kou 《海洋学报(英文版)》2011,30(4):102-106
An attempt is made to infer the global mean sea level(GMSL) from a global tide gauge network and frame the problem in terms of the limitations of the network. The network,owing to its limited number of gauges and poor geographical distribution complicated further by unknown vertical land movements,is ill suited for measuring the GMSL. Yet it remains the only available source for deciphering the sea level rise over the last 100 a. The poor sampling characteristics of the tide gauge network have necessitated the usage of statistical inference. A linear optimal estimator based on the Gauss-Markov theorem seems well suited for the job. This still leaves a great deal of freedom in choosing the estimator. GMSL is poorly correlated with tide gauge measurements because the small uniform rise and fall of sea level are masked by the far larger regional signals. On the other hand,a regional mean sea level(RMSL) is much better correlated with the corresponding regional tide gauge measurements. Since the GMSL is simply the sum of RMSLs,the problem is transformed to one of estimating the RMSLs from regional tide gauge measurements. Specifically for the annual heating and cooling cycle,we separate the global ocean into 10-latitude bands and compute for each 10-latitude band the estimator that predicts its RMSL from tide gauges within. In the future,the statistical correlations are to be computed using satellite altimetry. However,as a first attempt,we have used numerical model outputs instead to isolate the problem so as not to get distracted by altimetry or tide gauge errors. That is,model outputs for sea level at tide gauge locations of the GLOSS network are taken as tide gauge measurements,and the RMSLs are computed from the model outputs. The results show an estimation error of approximately 2 mm versus an error of 2.7 cm if we simply average the tide gauge measurements to estimate the GMSL,caused by the much larger regional seasonal cycle and mesoscale variation plaguing the individual tide gauges. The numerical model,Los Alamos POP model Run 11 lasting 3 1/4 a,is one of the best eddy-resolving models and does a good job simulating the annual heating and cooling cycle,but it has no global or regional trend. Thus it has basically succeeded in estimating the seasonal cycle of the GMSL. This is still going to be the case even if we use the altimetry data because the RMSLs are dominated by the seasonal cycle in relatively short periods. For estimating the GMSL trend,longer records and low-pass filtering to isolate the statistical relations that are of interest. Here we have managed to avoid the much larger regional seasonal cycle plaguing individual tide gauges to get a fairly accurate estimate of the much smaller seasonal cycle in the GMSL so as to enhance the prospect of an accurate estimate of GMSL trend in short periods. One should reasonably expect to be able to do the same for longer periods during which tide gauges are plagued by much larger regional interannual(e. g.,ENSO events) and decadal sea level variations. In the future,with the availability of the satellite altimeter data,we could use the same approach adopted here to estimate the seasonal variations of GMSL and RMSL accurately and remove these seasonal variations accordingly so as to get a more accurate statistical inference between the tide gauge data and the RMSLs(therefore the GMSL) at periods longer than 1 a,i. e.,the long-term trend. 相似文献
5.
I~IOXThe sea level rise threatens China's coastal plains and river deltas and makes them the vulnerable areas due to their loW elevation.Since the 1980s, the Chinese scientists have paid great attention to the problem of the sealevel rise caused by the global warming. They have analyZed and calculated the trend of the relative sea level change along the China's coast in the past 50 a. The result of study shows that therising rate of the sea level along China's coast is (1. 7 i 0. 3) rum/a.… 相似文献
6.
Historical simulation and twenty-first century prediction of oceanic CO2 sink and pH change 总被引：1，自引：1，他引：0
A global ocean carbon cycle model based on the ocean general circulation model POP and the improved biogeochemical model OCMIP-2 is employed to simulate carbon cycle processes under the historically observed atmospheric CO 2 concentration and different future scenarios (called Rep- resentative Concentration Pathways, or RCPs). The RCPs in this paper follow the design of Inter- governmental Panel on Climate Change (IPCC) for the Fifth Assessment Report (AR5). The model results show that the ocean absorbs CO 2 from atmosphere and the absorbability will continue in the 21st century under the four RCPs. The net air-sea CO 2 flux increased during the historical time and reached 1.87 Pg/a (calculated by carbon) in 2005; however, it would reach peak and then decrease in the 21st century. The ocean absorbs CO 2 mainly in the mid latitude, and releases CO 2 in the equator area. However, in the Antarctic Circumpolar Current (ACC) area the ocean would change from source to sink under the rising CO 2 concentration, including RCP4.5, RCP6.0, and RCP8.5. In 2100, the anthropogenic carbon would be transported to the 40 S in the Atlantic Ocean by the North Atlantic Deep Water (NADW), and also be transported to the north by the Antarctic Bottom Water (AABW) along the Antarctic continent in the Atlantic and Pacific oceans. The ocean pH value is also simulated by the model. The pH decreased by 0.1 after the industrial revolution, and would continue to decrease in the 21st century. For the highest concentration sce- nario of RCP8.5, the global averaged pH would decrease by 0.43 to reach 7.73 due to the absorption of CO 2 from atmosphere. 相似文献
7.
Altimetry-observed semi-annual cycle in the South China Sea: Real signal or alias of K1 tidal error?
There have been a number of applications of satellite altimetry to seasonal and interannual sea level variability in the South China Sea. However, these applications usually exclude shallow waters along the coast, with one of the concerns being large aliased tide-correction error. In this study the authors analyzed 14 years of merged satellite altimeter data to obtain the amplitude and phase of the semi-annual cycle and to examine the variation at the K1 alias frequency (close to the semi-annual frequency). The results indicate that the amplitude of the semi-annual cycle ranges from 3-7 cm, substantial compared with that of the annual cycle; while the amplitude at the K1 alias frequency (error of the K1 tidal correction) is essentially 1 cm only. Altimeter–derived semi-annual cycle is in good agreement with that from independent tide-gauge observations, pointing to the competent ability of satellite altimetry in observing semi-annual sea level variations in the South China Sea. 相似文献
8.
南海沿海季节性海平面异常变化特征及成因分析 总被引：1，自引：1，他引：0
Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigate the characteristics and possible causes of seasonal sea level anomalies along the South China Sea(SCS) coast. The research results show that:(1) Seasonal sea level anomalies often occur from January to February and from June to October. The frequency of sea level anomalies is the most in August, showing a growing trend in recent years. In addition, the occurring frequency of negative sea level anomaly accounts for 50% of the total abnormal number.(2) The seasonal sea level anomalies are closely related to ENSO events. The negative anomalies always occurred during the El Ni?o events, while the positive anomalies occurred during the La Ni?a(late El Ni?o) events. In addition, the seasonal sea level oscillation periods of 4–7 a associated with ENSO are the strongest in winter, with the amplitude over 2 cm.(3) Abnormal wind is an important factor to affect the seasonal sea level anomalies in the coastal region of the SCS. Wind-driven sea level height(SSH) is basically consistent with the seasonal sea level anomalies. Moreover, the influence of the tropical cyclone in the coastal region of the SCS is concentrated in summer and autumn, contributing to the seasonal sea level anomalies.(4) Seasonal variations of sea level, SST and air temperature are basically consistent along the coast of the SCS, but the seasonal sea level anomalies have no much correlation with the SST and air temperature. 相似文献
9.
基于ROMS模式利用集合最优插值同化沿轨海表面高度异常数据的研究 总被引：2，自引：1，他引：1
The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models. 相似文献
10.
Quantifying the contribution of natural variability to September Arctic sea ice decline 总被引：1，自引：0，他引：1
Arctic sea ice extent has been declining in recent decades. There is ongoing debate on the contribution of natural internal variability to recent and future Arctic sea ice changes. In this study, we contrast the trends in the forced and unforced simulations of carefully selected global climate models with the extended observed Arctic sea ice records. The results suggest that the natural variability explains no more than 42.3% of the observed September sea ice extent trend during 35 a(1979–2013) satellite observations, which is comparable to the results of the observed sea ice record extended back to 1953(61 a, less than 48.5% natural variability). This reinforces the evidence that anthropogenic forcing plays a substantial role in the observed decline of September Arctic sea ice in recent decades. The magnitude of both positive and negative trends induced by the natural variability in the unforced simulations is slightly enlarged in the context of increasing greenhouse gases in the 21st century.However, the ratio between the realizations of positive and negative trends change has remained steady, which enforces the standpoint that external forcing will remain the principal determiner of the decreasing Arctic sea ice extent trend in the future. 相似文献
11.
RCP4.5情景下预测21世纪南海海平面变化 总被引：3，自引：1，他引：2
结合卫星高度计资料和SODA温盐数据,本文利用CCSM(Community Climate System Model version4)气候系统模式在代表性浓度路径RCP4.5情景下对全球海平面变化趋势的预测模拟结果作为强迫场,用POP模式模拟预测21世纪南海海平面长期趋势变化及空间分布。模拟结果显示,在RCP4.5情景下,南海海域在21世纪末10年平均海平面相对于20世纪末10年上升了15~39cm,明显上升海域位于中南半岛东部的南海中部、南部海域和吕宋海峡东西两侧海域,上升值最大可达39cm。如果加上格陵兰和南极等陆地冰川融化的影响,21世纪南海总海平面上升值将可能达到35~75cm。南海比容海平面明显上升区域位于吕宋岛东面的深水海域,广东沿岸流和吕宋冷涡之间海域,以及中南半岛东南部海域。总比容海平面的变化主要来自热比容,盐比容贡献比较小。南海南部和西部比容海平面上升速率较低,如加里曼丹岛西北侧、泰国湾和海南岛西侧有下降趋势。 相似文献
12.
本文基于SLAMM模型分析了不同情景下海平面上升对广西沿海红树林分布面积的影响及其空间差异,通过对比实验定量分析了潮差和沉积速率的作用。结果显示,与基准年2007年相比,2100年广西红树林面积在当前海平面上升速率、典型浓度路径RCP2.6、RCP4.5和RCP8.5情景下分别减少0.57%、4.99%、7.99%和17.39%,珍珠港、茅尾海、丹兜海和英罗港受影响程度较大。当地潮差与红树林面积减少率呈负相关关系。需维持红树林生长区域的沉积速率以应对未来的海平面加速上升。 相似文献
13.
基于中国沿海10个验潮站资料,利用皮尔森Ⅲ型(P-Ⅲ)模型探讨了典型浓度路径(Representative Concentration Pathway,RCP)情景下21世纪海平面上升对中国沿海地区极值水位重现期的影响。结果表明:海平面上升将显著缩短极值水位的重现期。在RCP8.5情景下极值水位的重现期缩短最为显著。预估到2050年,在RCP8.5情景下,所研究的中国沿海地区潮位站的百年一遇极值水位将变为9~43 a一遇。到2100年,在RCP8.5情景下,百年一遇极值水位变为1~18 a一遇。当前极值水位的低概率事件将在2100年变得普遍,在RCP8.5情景下,到2100年千年一遇的几乎每两百年发生一次。由于极值水位的重现期会随着气候变化而缩短,未来沿海地区将会面临更严峻的风险与挑战。 相似文献
14.
CMIP5模式对南海SST的模拟和预估 总被引：4，自引：1，他引：3
分析了32个CMIP5模式对南海历史海表温度(SST)的模拟能力和不同排放情景下未来SST变化的预估。通过检验各气候模式对南海历史SST增温趋势和均方差的模拟,发现大部分模式都能较好地模拟出南海20世纪历史SST的基本特征和变化规律,但也有部分模式的模拟存在较大偏差。尽管这些模拟偏差较大的模式对SST多模式集合平均的影响不大,但会增加未来情景预估的不确定性。剔除15个模式后,分析了南海SST在RCP26、RCP45和RCP85三种排放情景下的变化趋势,发现在未来百年呈明显的增温趋势,多模式集合平均的增温趋势分别为0.42、1.50和3.30℃/(100a)。这些增温趋势在空间上变化不大,但随时间并不是均匀变化的。在前两种排放情景下,21世纪前期的增温趋势明显强于后期,而在RCP85情景下,21世纪后期的增温趋势强于前期。 相似文献
15.
Guillem Chust Ainhoa Caballero Marta Marcos Pedro Liria Carlos Hernández Ángel Borja 《Estuarine, Coastal and Shelf Science》2010
Global climate models have predicted a rise on mean sea level of between 0.18 m and 0.59 m by the end of the 21st Century, with high regional variability. The objectives of this study are to estimate sea level changes in the Bay of Biscay during this century, and to assess the impacts of any change on Basque coastal habitats and infrastructures. Hence, ocean temperature projections for three climate scenarios, provided by several atmosphere–ocean coupled general climate models, have been extracted for the Bay of Biscay; these are used to estimate thermosteric sea level variations. The results show that, from 2001 to 2099, sea level within the Bay of Biscay will increase by between 28.5 and 48.7 cm, as a result of regional thermal expansion and global ice-melting, under scenarios A1B and A2 of the Intergovernmental Panel on Climate Change. A high-resolution digital terrain model, extracted from LiDAR, data was used to evaluate the potential impact of the estimated sea level rise to 9 coastal and estuarine habitats: sandy beaches and muds, vegetated dunes, shingle beaches, sea cliffs and supralittoral rock, wetlands and saltmarshes, terrestrial habitats, artificial land, piers, and water surfaces. The projected sea level rise of 48.7 cm was added to the high tide level of the coast studied, to generate a flood risk map of the coastal and estuarine areas. The results indicate that 110.8 ha of the supralittoral area will be affected by the end of the 21st Century; these are concentrated within the estuaries, with terrestrial and artificial habitats being the most affected. Sandy beaches are expected to undergo mean shoreline retreats of between 25% and 40%, of their width. The risk assessment of the areas and habitats that will be affected, as a consequence of the sea level rise, is potentially useful for local management to adopt adaptation measures to global climate change. 相似文献
16.
IPCC气候情景下全球海平面长期趋势变化 总被引：5，自引：1，他引：4
利用CCSM3 (Community Climate System Model version 3)气候系统模式模拟20世纪海平面变化,在IPCC SRES A2 (IPCC,2001)情景假设下预测21世纪全球海平面长期趋势变化。模拟显示20世纪海平面上升约4.0 cm,且存在0.004 8 mm/a2的加速度,这个结果仅为热盐比容的贡献。在A2情景假设下,21世纪海平面上升存在很大的区域特征,呈纬向带状分布;总体上北冰洋上升大,南大洋高纬度海区上升小,大西洋上升值比太平洋的大;整个21世纪全球平均比容海平面上升了约30 cm,且呈加速上升的趋势。同时发现,中深层水温度和盐度变化对区域比容海平面变化具有重要贡献。北太平洋增暖主要集中在上层700 m以内,而北大西洋的增暖可达2 500 m的深度,南大洋南极绕极流海区热盐变化则是发生在整个深度。 相似文献
17.
本文利用大洋环流模式POP研究RCP4.5情景下21世纪格陵兰冰川不同的融化速率对全球及区域海平面变化的影响。结果显示:当格陵兰冰川的融化速率以每年1%增加时,全球大部分海域的动力和比容海平面变化基本不变,主要是由于格陵兰冰川在低速融化时并不会导致大西洋经向翻转流减弱。当格陵兰冰川的融化速率以每年3%和每年7%增加时,动力海平面在北大西洋副极地、大西洋热带、南大西洋副热带和北冰洋海域呈现出显著的上升趋势,这是因为格陵兰冰川快速融化导致大量的淡水输入附近海域,造成该上层海洋层化加强和深对流减弱,导致大西洋经向翻转流显著减弱;与此同时,热比容海平面在北冰洋、格陵兰岛南部海域和大西洋副热带海域显著下降,而在热带大西洋和湾流海域明显上升;此时盐比容海平面的变化与热比容海平面是反相的,这是由于大量的低温低盐水的输入,造成北大西洋副极地海域变冷变淡、大西洋经向翻转流和热盐环流显著减弱,引起了太平洋向北冰洋的热通量和淡水通量减少,导致了北冰洋海水变冷变淡,同时热带大西洋滞留了更多的高温高盐水,随着湾流被带到北大西洋,北大西洋副极地海域低温低盐的海水,被风生环流输运到副热带海域。 相似文献