Prediction of china’s submerged coastal areas by sea level rise due to climate change

Based on the simulation with the Ocean-Atmosphere Coupled Model CCSM and Ocean Model POP under the greenhouse gas emission scenario of the IPCC SRES A2 (IPCC, 2001), and on the earth crust subsidence and glacier melting data, the relative sea level change is obtained along the coast of China in the 21st century. Using the SRTM elevation data the submergence of coastal low land is calculated under the extreme water level with a 100-year return period. The total flooding areas are 98.3×10³ and 104.9×10³ km² for 2050 and 2080, respectively. For the three regions most vulnerable to extreme sea level rise, i.e., the coast of Bohai Bay, the Yangtze River Delta together with neighboring Jiangsu Province and northern Zhejiang Province, and the Pearl River Delta, the flooded areas are 5.0×10³, 64.1×10³ and 15.3×10³ km² in 2050 and 5.2×10³, 67.8×10³ and 17.2×10³ km² in 2080, respectively.     

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.     

天津武清凹陷东营组地热地质条件及开发利用前景浅析

通过对武清凹陷内的地质构造特征的分析,并结合东营组地热井的勘探成果,对东营组地层特征及热储特征进行分析,计算了热储的开采潜力,评价了热流体的利用前景。分析结果表明：该区东营组热储层埋深较浅、渗透率较大、地热流体温度高达93℃、水质优良,并具有极高的理疗医用价值。如果在此以东营组地热资源为依托,建立温泉理疗项目,既响应了天津市建设“中国温泉之都”的号召,促进节能减排和生态城市建设进程,又在提高了市民的生活品质的同时,带来可观的经济效益。     

1993年10月2日若羌6.6级地震

１９９３年若羌６．６级主震－余震型地震使艾西煤矿等地边坡裂缝、山体塌陷、山石崩塌，破坏各类建筑物１６９０１６ｍ２，地震总经济损失为２７７万元．这次地震是阿尔金活动断裂带最新活动的表现。     

基于观测数据的2003?2014年北冰洋海平面时空特征

本文对比了3个不同机构提供的北冰洋月均高度计数据,发现英国极地观测与建模中心和丹麦科技大学空间中心两套数据比较一致且空间覆盖率高,适用于北冰洋海平面变化研究,而前者在数据分辨率、平滑性和与验潮站的符合程度方面均更优。对高度计和验潮站数据的分析表明,北冰洋海平面的气候态特征表现为加拿大海盆的高值和欧亚海盆的低值之间形成鲜明对比;海平面的变化以季节变化和北极涛动引起的低频变化为主,加拿大海盆的季节和年际振幅均较大,俄罗斯沿岸海平面季节变化显著。2003?2014年,北冰洋平均海平面呈上升趋势,其中加拿大海盆海平面上升最快,而俄罗斯沿岸海平面有微弱下降趋势。加拿大海盆和俄罗斯沿岸由于海冰变化显著,不同高度计产品以及高度计与验潮站数据之间差别较大,使用时需慎重。     

Co-occurrence patterns of above-ground and below-ground mite communities in farmland of Sanjiang Plain,Northeast China

One of the fundamental questions in community ecology is whether communities are random or formed by deterministic mechanisms. Although many efforts have been made to verify non-randomness in community structure, little is known with regard to co-occurrence patterns in above-ground and below-ground communities. In this paper, we used a null model to test non-randomness in the structure of the above-ground and below-ground mite communities in farmland of the Sanjiang Plain, Northeast China. Then, we used four tests for non-randomness to recognize species pairs that would be demonstrated as significantly aggregated or segregated co-occurrences of the above-ground and below-ground mite communities. The pattern of the above-ground mite commu- nity was significantly non-random in October, suggesting species segregation and hence interspecific competition. Additionally, species co-occurrence patterns did not differ from randomness in the above-ground mite community in August or in below-ground mite com- munities in August and October. Only one significant species pair was detected in the above-ground mite community in August, while no significant species pairs were recognized in the above-ground mite community in October or in the below-ground mite communities in August and October. The results indicate that non-randomness and significant species pairs may not be the general rule in the above-ground and below-ground mite communities in farmland of the Sanjiang Plain at the fine scale.     

海洋倾倒区容量评估模型的构建

倾倒区容量主要受海水动力过程(潮流输沙、风暴潮和风浪掀沙等)、倾倒区面积和水深地形等因素影响。本文基于FVCOM(Finite Volume Coast and Ocean Model)三维数值模型和随机动态统计分析模型, 利用倾倒区地形演变和倾倒量资料, 探讨海水动力过程(潮流输沙、风暴潮和风浪掀沙等)和倾废活动对海底地形变化的影响, 构建海洋倾倒区容量长期演变评估模型。利用FVCOM水动力和泥沙模型计算自然状态下潮流输沙引起的地形变化, 同时结合倾倒区多年实测水深和倾倒量资料, 分析倾倒量、潮流输沙和地形变化的统计关系, 通过实际资料拟合修订系数, 作为该倾倒区海浪和风暴潮等因素输沙所造成地形变化的参考值, 以此评估倾倒区容量长期演变。在设定实际地形变化阈值的前提下, 计算倾倒区容量。以长江口1#倾倒区为例, 1#倾倒区地形抬升0.5m/a,倾倒区容量约为670万方/a,模型结果和实际批复结果吻合。同时在甬江口2#倾倒区、罗源湾倾倒区、嵊泗上川山、东碇倾倒区和温州港倾倒区等验证, 模拟结果同实际观测结果相近。     

Assessing the global averaged sea-level budget from 2003 to 2010

A global mass balance （Greenland and Antarctica ice sheet mass loss, terrestrial water storage） and differ- ent sea-level components （observed sea-level from satellite altimetry, steric sea-level from Ishii data, and ocean mass from gravity recovery and climate experiment, GRACE） are estimated, in terms of seasonal and interannual variabilities from 2003 to 2010. The results show that a detailed analysis of the GRACE time series over the time period 2003-2010 unambiguously reveals an increase in mass loss from the Greenland ice sheet and Antarctica ice sheet. The mass loss of both ice sheets accelerated at a rate of （392.8±70.0） Gt/a during 2003-2010, which contributed （1.09±0.19） mm/a to the global mean sea-level during this time. The net terrestrial water storage （TWS） trend was negative over the 8 a time span, which gave a small positive contribution of （0.25±0.12） mm/a. The interannual variability of the global mean sea-level was at least part- ly caused by year-to-year variability of land water storage. Estimating GRACE-based ice sheet mass balance and terrestrial water storage by using published estimates for melting glaciers, the results further show that the ocean mass increase since 2003 has resulted half from an enhanced contribution of the polar ice sheets, and half from the combined ice sheet and terrestrial water storage loss. Taking also into account the melt- ing of mountain glaciers （0.41 mm/a） and the small GRACE-based contribution from continental waters （0.25 mm/a）, a total ocean mass contribution of （1.75±0.57） mm/a from 2003 to 2010 is found. Such a value represented 75% of the altimetry-based rate of sea-level rise over that period. The contributions to steric sea-level （i.e., ocean thermal expansion plus salinity effects） are estimated from： （1） the difference between altimetry-based sea-level and ocean mass change and （2） the latest Ishii data. The inferred steric sea-level rate from （1） （1.41 mm/a from 2003 to 2010） did not agree well with the Ishii-based value also estimated here （0.44 mm/a from 2003 to 2010）, but phase. The cause for such a discrepancy is not yet known but may be related to inadequate sampling of in situ ocean temperature and salinity measurements.