Long term sea level change and water mass balance in the South China Sea

Sea level anomalies observed by altimeter during the 1993–2006 period, thermosteric sea level anomalies estimated by using subsurface temperature data produced by Ishii and SODA reanalysis data, tide gauge records and HOAPS freshwater flux data were analyzed to investigate the long term sea level change and the water mass balance in the South China Sea. The altimeter-observed sea level showed a rising rate of (3.5±0.9) mm yr-1 during the period 1993–2006, but this figure was considered to have been highly d...     

基于BDS信噪比的潮位监测精度分析与评估

基于非洲东海岸MAYG站2020年年积日268～366的信噪比（SNR）数据开展GNSS-IR（global navigation satellite system interferometric reflectometry）监测海平面高度研究,并与Dzaoudzi验潮站的实测潮位进行对比。结果显示,BDS-GEO不适用于岸基测高;BDS-MEO的监测精度优于BDS-IGSO和GPS。     

全球海水质量季节变化研究

海平面变化是海水密度和海水总质量变化的结果,是全球气候变化研究的重要内容之一。利用GRACE卫星观测得到的重力场系数变化资料及重力卫星测高得到的海平面变化扣除由模式得到的热容海平面变化,研究了海水的质量变化。研究结果显示,由这两种方法得到的海水质量变化有非常明显的季节性特征,且其周年振幅和位相非常接近。     

小波变换和改进Burg算法的GNSS-IR海面高度反演模型

针对传统的GNSS-IR海面高度监测方法信号分离不佳且精度有待提高的问题,提出结合小波变换和改进Burg算法的新型GNSS-IR海面高度反演模型。相比于传统的多项式拟合法,小波变换得到的SNR振荡项更加完整、精确。改进的Burg算法能有效抑制峰值偏移或谱分裂现象,提高谱分析精度。基于瑞典Onsala空间天文台提供的GNSS数据和验潮仪数据的实验结果表明,优化后的海平面测高模型的反演结果与验潮仪数据具有较高的一致性,相比于传统的GNSS-IR海面测高模型精度提高约20%。     

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????TOPEX/Poseidon????????????鳱??????????1994~2000??????????????????????????仯???????????????????????????仯??????к?????????????T/P??????????????????????????????7.73 mm/a???????鳱?????????12.18 mm/a????????????????4.45 mm/a?????????????鳱?????????????????????????????????鳱???????????鳱???????????????????????????????鳱?????????????????     

Global sea level change and thermal contribution

The global long-term sea level trend is obtained from the analysis of tide gauge data and TOPEX/Poseidon data. The linear trend of global mean sea level is highly non-umiform spatially, with an average rate of 2.2 mm year-1 in T/P sea-level rise from October 1992 to September 2002. Sea level change duc to temperature vanation (the thermosteric sea level) is discussed. The results are compared with TOPEX/Poseidon altimeter data in the same temporal span at different spatial scales. It is indicated that the ther-mal effect accounts for 86% and 73% of the observed seasonal variability in the northern and southern hemispheres, respectively. The TOPEX/Poseidon observed sea level lags behind the TSI, by 2 months in the zonal band of 40°-60° in both the northern and southern hemispheres. Systematic differences of about 1-2cm between TOPEX/Poseidon observations and thermosteric sea level data are obtained. The potential causes for these differences include water exchange among the atmosphere, land, and oceans, and some pos-sible deviations in thermosteric contribution estimates and geophysical corrections to the TOPEX/Poseidon data.     

Spatiotemporal features and possible mechanisms of seasonal changes in sea surface height south of Japan

Variations of sea surface height(SSH) in the Kuroshio south of Japan are addressed by analyzing 19-year(1993–2011) altimetry data from AVISO. Regionally averaged time series of observed SSH had a rising linear trend at 2.64±0.72 mm/a in this period. By analyzing the power spectra, several periods were recognized in temporal SSH variations, including those around 90 and 360 days. The seasonal cycle of SSH was minimum in winter(February) and maximum in summer(August), with peak-to-peak amplitude about 20.0 cm. The spatial distribution of linear trends was inhomogeneous, with a rising linear trend along the coastline and a tripole structure offshore. Spatial distributions of standard deviation of seasonal SSH show very dynamic activities in the southeast of Kyushu and south of Honshu. Seasonal variations of observed SSH are partially explained by surface buoyancy forcing, local wind forcing and the steric component related to subsurface water beneath the mixed layer. Results show different spatial distributions of correlation coefficient and estimation skill between seasonally observed and modeled SSH, which are calculated from surface buoyancy fl ux, local wind forcing and the steric component related to subsurface water. Of those three, the surface buoyancy fl ux has a greater contribution to variations of observed SSH on the seasonal time scale south of Japan.     

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?????????????????????????????????????????????????????Σ??о????й????????????????????????????????????????????仯??????????????????????????????????????????????????????????????仯??????????????廷???????????????????????????κ????????????????????????????????????????????????????????????????????????????     

Global distribution of thermosteric contribution to sea level rising trend

The sea level derived from TOPEX/Poseidon(T/P) altimetry data shows prominent long term trend and inter-annual variability.The global mean sea level rising rate during 1993-2003 was 2.9 mm a-1.The T/P sea level trend maps the geographical variability.In the Northern Hemisphere(15°-64°N),the sea level rise is very fast at the mid-latitude(20°-40°N) but much slower at the high-latitude,for example,only 0.5 mm a-1 in the latitude band 40°-50°N.In the Southern Hemisphere,the sea level shows high rising rate both in mid-latitude and high-latitude areas,for example,5.1 mm a-1 in the band 40°-50°S.The global thermosteric sea level(TSL) derived from Ishii temperature data was rising during 1993-2003 at a rate of 1.2 mm a-1 and accounted for more than 40% of the global T/P sea level rise.The contributions of the TSL distribution are not spatially uniform;for instance,the percentage is 67% for the Northern Hemisphere and only 29% for the Southern Hemisphere(15°-64°S) and the maximum thermosteric contribution appears in the Pacific Ocean,which contributes more than 60% of the global TSL.The sea level change trend in tropical ocean is mainly caused by the thermosteric effect,which is different from the case of seasonal variability in this area.The TSL variability dominates the T/P sea level rise in the North Atlantic,but it is small in other areas,and shows negative trend at the high-latitude area(40°-60°N,and 50°-60°S).The global TSL during 1945-2003 showed obvious rising trend with the rate of about 0.3 mm a-1 and striking inter-annual and decadal variability with period of 20 years.In the past 60 years,the Atlantic TSL was rising continuously and remarkably,contributing 38% to the global TSL rising.The TSL in the Pacific and Indian Ocean rose with significant inter-annual and decadal variability.The first EOF mode of the global TSL from Ishii temperature data was the ENSO mode in which the time series of the first mode showed steady rising trend.Among the three oceans,the first mode of the Pacific TSL presented the ENSO mode;there was relatively steady rising trend in the Atlantic Ocean,and no dominant mode in the Indian Ocean.     

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???????鳱??????5???????????NAO99b??FES2004??GOT4.7??TPXO7.2??EOT10a???о????????????????????????????????????????????????????????????????????????????2 cm??????????50 km?????й?????NAO99b?????????RSS?14.86cm??EOT10a???????Χ??????????????????????????????     

Characteristics Analysis and Risk Assessment of Extreme Water Levels Based on 60-Year Observation Data in Xiamen,China

Extreme water levels are related to astronomical tides and storm surges.Eleven typhoon systems,which have caused extreme water level rises,were selected based on 60-yr water level data from the Xiamen tide gauge station.In these 11 typhoon systems,the astronomical tide component accounts for 71%-95%of the total water level.The Gumbel distribution of extreme water level rise was estimated,and the impact of typhoon surges on water levels during the return period was analyzed.The ex-treme tide levels caused by typhoons Herb(1996)and Dujuan(2015)are much higher than those of other typhoons and correspond to the return period of 76 yr and 71 yr,respectively.The differences of sea levels in the presence and absence of these two typhoons in the 10-100 yr return period are 5.8-11.1 cm.For the 100-yr return period,the total risks within 10,25,50,and 100 yr increase by 94.3%,85.4%,72.9%,and 54.4%,respectively,if the Herb and Dujuan are not considered.Assuming that typhoon Herb(1996)occurred during the highest astronomical tide,it will produce a water level higher than that of the 1000-yr return period.Sea level rise has an important influence on the water level return period,and the contribution of nonlinear sea level rise in the next 100 yr is estimated to be 10.34%.     

Causes of land loss in Tuvalu,a small island nation in the pacific

Studies on land loss in Tuvalu reveal the following findings. Although both sea level rise and coastal erosion can cause land loss in the tropic Pacific oceanic islands, their mechanisms are different. When sea level rises, the low elevation coastal zone submerges and the erosion datum plane rises, the beach process progresses normally as always, resulting in no beach sediment coarsening. When the sea level is stable, coastal erosion removes finer sediment from reef flat, beach and land, resulting in beach sediment coarsening. The human-induced coastal erosion in the tropic Pacific oceanic islands has the following features. 1) Erosion occurs or intensifies immediately after inappropriate human activities. 2) It occurs near the places having human activities and places related to the above places in sediment supply. 3) It often occurs on original prograding or stable coasts (on lagoon coasts for atolls) because there are more coastal engineering projects and other human activities on such coasts. 4) It is chronic, covering a long period of time. The coastal geological events in Tuvalu islands do not accord with the features resulted from sea level rise but do accord with the features resulted from coastal erosion, particularly from human-induced erosion. The land loss in Tuvalu is mainly caused by inappropriate human activities including coastal engineering and aggregate mining, and partly caused by cyclones. Moreover, all recent measurements (satellite altimetry,thermosteric sea level data and tide observations) so far have not been able to verify any sea level rise around Tuvalu islands.     

MEAN SEA LEVEL AND SEA SURFACE VARIABILITY OF NQRTHWEST PACIFIC OCEAN AND EASTERN CHINA SEAS FROM GEOSAT ALTIMETRY

Collinear analysis technique is widely used for determining sea surface variability with Geosat altimeterdata from its Exact Repeat Mission(ERM).But most of the researches have been only on global scaleor in oceans deeper than 2000 m.In shallow shelf waters this method is hampered by the inaccuracy ofocean tide data supplied with Geosat Geophysical Data Records(GDRs).This work uses a modified collinearanalysis technique characterized by simultaneous separation of mean sea level and ocean tide with theleast squares method,to compute sea surface variability in the Northwest Pacific Ocean and eastern ChinaSeas.The mean sea level map obtained contains not ouly bathymetric but also dynamic features such asamphidromes,indicating considerable improvement over previous works.Our sea surface variability mapsshow clearly the main current system,the well-known Zhejiang coastal upwelling,and a northern East Chi-na Sea meso-scale eddy in good agreement with satellite sea surface temperature(SST)observation and his-to     

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Toward development of the 4Dvar data assimilation system in the Bering Sea： reconstruction of the mean dynamic ocean topography

The Bering Sea circulation is derived as a variational inverse of hydrographic profiles（ temperature and salinity） , atmospheric climatologies and historical observation of ocean curents. The important result of this study is estimate of the mean climatological sea surface height （SSH） that can be used as a reference for satellite altimetry sea level anomaly data in the Bering Sea region. Numerical experiments reveal that, when combined with satellite altimetry, the obtained reference SSH effectively constrains a realistic reconstruction of the Amukta Pass circulation.     

Trend in Observed and Projected Maximum and Minimum Temperature over N-W Himalayan Basin

Recently, study in past trends of climate variables gained significant consideration because of its contribution in adaptions and mitigation strategies for potential future changes in climate, primarily in the area of water resource management. Future interannual and inter-seasonal variations in maximum and minimum temperature may bring significant changes in hydrological systems and affect regional water resources. The present study has been performed to observe past(1970-2010) as well as future(2011-2100)spatial and temporal variability in temperature(maximum and minimum) over selected stations of Sutlej basin located in North-Western Himalayan region in India. The generation of future time series of temperature data at different stations is done using statistical downscaling technique. The nonparametric test methods, modified Mann-Kendall test and Cumulative Sum chart are used for detecting monotonic trend and sequential shift in time series of maximum and minimum temperature. Sen’s slope estimator test is used to detect the magnitude of change over a period of time on annual and seasonal basis. The cooling experienced in annual TMax and TMin at Kasol in past(1970-2010) would be replaced by warming in future as increasing trends are detected in TMax during 2020 s and 2050 s and in TMin during 2020 s, 2050 s and 2080 s under A1 B and A2 scenarios. Similar results of warming are also predicted at Sunnifor annual TMin in future under both scenarios which witnessed cooling during 1970-2010. The rise in TMin at Rampur is predicted to be continued in future as increasing trends are obtained under both the scenarios. Seasonal trend analysis reveals large variability in trends of TMax and TMin over these stations for the future periods.     

Spatiotemporal variability of precipitation during 1961–2014 across the Mongolian Plateau

Precipitation is the dominant factor that controls vegetation growth and land-use practices in the arid and semiarid Mongolian Plateau(MP), so the spatiotemporal heterogeneity of precipitation change has been an important scientific question in the region. This study investigated the spatiotemporal characteristics of annual and seasonal precipitation across the entire MP based on monthly precipitation data from 136 meteorological stations during 1961–2014 by using a modified Mann–Kendall test, Sen's slope, Morlet Wavelet Transform, and geostatistical methods. Results show the following: 1) Annual precipitation decreased slightly from 1961 to 2014.Stations with positive and negative trends were 41.9%and 58.1%, respectively. Significant positive trends were mainly in the southwestern and northeastern regions of the plateau, whereas significant negative trends were in the northern and southeastern regions.2) Precipitation decreased at rates of-5.65 and-0.41 mm/decade in summer and autumn, respectively, but increased at 1.91 and 0.51 mm/decade in spring and winter. The contribution of spring and winter precipitation to the annual amount increased significantly, but that of summer precipitation decreased significantly. 3) A large majority of stations(80.2%) showed decreasing trends in summer,whereas 89.7% and 83.1% of stations showed increasing trends in spring and winter. The spatial distribution of trend magnitude in seasonal precipitation amount was strongly heterogeneous. 4)By climatic zones, precipitation increased in humid and arid zones, but decreased in a semiarid zone. On the whole, the MP experienced a drying trend, with significant regional differentiation and seasonal variations.     

近33年来渭河流域蒸发皿蒸发量的变化特征及原因分析

为了研究渭河流域气候变化趋势及其成因,利用陕西渭河流域43个气象台站1978~2010年观测资料,采用气候趋势系数、气候倾向率和相关系数方法,分析了近33年来陕西渭河流域的蒸发皿蒸发量及其影响因子的相关性和变化趋势。结果表明:近33年来陕西渭河流域年蒸发皿蒸发量呈波动状升高,但并非显著性上升;春季和冬季的蒸发皿蒸发量表现为上升趋势,夏季和秋季则为下降趋势;四季蒸发皿蒸发量的下降主要在渭北西部;导致陕西渭河流域年蒸发皿蒸发量上升的主要原因是平均气温上升和降水量下降。     

基于Argo海洋观测资料分析2005~2015年全球比容海平面变化的时空特征

利用3家机构（JAMSTEC、SIO、IPRC）发布的Argo海洋温度和盐度数据分析2005~2015年全球SSL在不同时间和空间尺度上的变化特征。结果表明,全球平均SSL（即由海水密度变化引起的）上升速率为1.08±0.38 mm/a;年际信号对SSL变化速率的估算结果存在显著影响,近期（2011~2015年）Argo数据的估算结果（2.16±0.50 mm/a）显著大于早期（2005~2010年）的结果（0.66±0.64 mm/a）。当前Argo产品用于全球平均SSL变化趋势的分析结果较为一致,差异为3家机构所得结果平均值的10%左右;而小尺度上(20°宽纬度带)的计算结果差异很大,能达到平均值的80%。对全球SSL的空间特征的分析结果也显示,3家机构产品估算的海平面比容变化周年振幅和线性速率在更小的尺度(±5°)上存在不可忽视的差异。     

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