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1.
????????????δ?????????????????????????????????·?????????????????????????????????????????????????????????÷?Χ???ó?????:????γ??????Χ??С??8???,??x??y???????????????1 cm??????????侫???????γ??(?????γ??)??Χ????С??????????  相似文献   

2.
????GPS?????????????????????????????????????????????????????????????????GPS????????????????????Χ????λ??????к??????????????????????????????????????????????????????????????ε?????????????ó????3???????????????????????????η?Χ????????????????λ???仯???????????????????Χ????????????????飬???????????????????С???????????λ????е??????????????????????????ο????????????????????????????????????????ο??嶫????γ????????η?????????????硪??????????????γ????????????????????????ο???????????ο??嶫????????????????й????????????  相似文献   

3.
????GPS??????????????????????????4??1????15??????????????????????????????????2???????????????????????????????????????????????????????£???????11??UT10:00??13??UT6:00??14??UT6:00-14:00??15??UT14:00-16??00???γ?????Χ???????????????????????????????????????????????4????????????????й??  相似文献   

4.
??????????????????????????3?????????Ρ?ī??????????o????????????????????GLTM??2???????????LP165????????o?????????????????£??????????γ???60??Χ????κ?ī????????????????????????????????????????????????????????????15??76 km?????48.6 km???o????????????????  相似文献   

5.
??????????????????????????????Χ?????????????η????????γ???????????????????????????????????S??????????????????????????????????????????-???????????С?????????????????????????????????????????????????????????????????????Σ?L2????????????????225 m????150 m???£??????????С??175 m??  相似文献   

6.
??????????????24??????????????????????????????α?????????????????????????о????????α???????????????????????????????????????α????????????????????????????????????????????????????????????仯?????????????????′?1994??????????????????????????????????????????????2??3???о?????????????????????????γ?????????????????????????е????????????????????????????????о??????????Χ???????????????????????????????????????????????????????й??  相似文献   

7.
??TOPEX/Poseidon????????????Χ???????ν??з??????ó?????:?????????????Χ???????????ε?????;????????????????????ζ??????????,?????????????????????????????????????????????  相似文献   

8.
????TEQC????????GPS????????????????????????????????????м????????????????MP1??MP2??CSR?????????????????IGS??????????????????飬?ó???1????????????????????????з??????仯,???????????仯?????,??????????????????????????????????????Χ?????????????Χ?????????£?2?????????????????????????????????????????????????????????????и???????????????3??“????”?????30????????90%????IGS????????????????????????????Χ??????????????  相似文献   

9.
?????????????κ?InSAR????????????????????????????????????PSGRN/PSCMP???????????????????????Ms7.1???????????????????α????????????1)???????????????????????????????????????λ??仯????????????????α????????2)????????????????仯??????????????????λ?????Χ???????????????仯???Χ??3)???????????????£?????????????????????????????仯?????????????????????????????????????????????仯?????????????????????????仯?????????????????????仯??  相似文献   

10.
????????????????????????????,??????й???????????????????????Χ?????????????????????????????????????????????????????????????п????????????????????????????????????й???????????????Χ??  相似文献   

11.
利用多种测高数据反演中国南海海域重力异常   总被引:1,自引:0,他引:1  
联合Geosat/GM、ERS-1/168和Envisat 3种测高数据,基于高精度地球重力模型EGM2008,采用垂线偏差方法和逆Vening-Meinesz公式,利用移去-恢复技术确定了中国近海及邻近海域(0°N~42°N,102°E~138°E)分辨率为2′×2′的重力异常.在中国南海海域,测高重力异常与船测重力...  相似文献   

12.
Landsat satellite images were used to map and monitor the snow-covered areas of four glaciers with different aspects(Passu: 36.473°N, 74.766°E;Momhil: 36.394°N, 75.085°E; Trivor: 36.249°N,74.968°E; and Kunyang: 36.083°N, 75.288°E) in the upper Indus basin, northern Pakistan, from 1990-2014. The snow-covered areas of the selected glaciers were identified and classified using supervised and rule-based image analysis techniques in three different seasons. Accuracy assessment of the classified images indicated that the supervised classification technique performed slightly better than the rule-based technique. Snow-covered areas on the selected glaciers were generally reduced during the study period but at different rates. Glaciers reached maximum areal snow coverage in winter and premonsoon seasons and minimum areal snow coverage in monsoon seasons, with the lowest snow-covered area occurring in August and September. The snowcovered area on Passu glacier decreased by 24.50%,3.15% and 11.25% in the pre-monsoon, monsoon and post-monsoon seasons, respectively. Similarly, the other three glaciers showed notable decreases in snow-covered area during the pre-and post-monsoon seasons; however, no clear changes were observed during monsoon seasons. During pre-monsoon seasons, the eastward-facing glacier lost comparatively more snow-covered area than the westward-facing glacier. The average seasonal glacier surface temperature calculated from the Landsat thermal band showed negative correlations of-0.67,-0.89,-0.75 and-0.77 with the average seasonal snowcovered areas of the Passu, Momhil, Trivor and Kunyang glaciers, respectively, during pre-monsoon seasons. Similarly, the air temperature collected from a nearby meteorological station showed an increasing trend, indicating that the snow-covered area reduction in the region was largely due to climate warming.  相似文献   

13.
???????Envisat??????????????2004??7??12???2005??4??8?????????Ms6.7??Ms6.5?????InSAR????α??????????????ε????????????20 km??20 km??Χ???EW?????????Σ??????η???19.0 cm??30.5 cm???????????????????????????ε???????????????????????,????λ??83.71??E,30.70??N,??Mw6.1,83.72??,E30.52??N????Mw6.2??????????????? 1 m??1.4 m?????ε??????????NW?????3?????????????NS?????????-????????????λ  相似文献   

14.
??????8.0????????????????????????????????????λ??????????????η????????ν??????????????????8.0??????GPS??InSAR????α??????????????????????????????????????????1?????????????????GPS??InSAR??????????α????????????97.27%;2??????????????????????????????????????0??20 km??????????????λ???????????????????????????????????????????0??20 km???????????????????10 m????????10??15 km?????????????6.5 m??3??????????????????????????????????????????????????????????103??????????????????????121????????????????????138??????????????????????????105??4?????????????????8.7??10 20 Nm???????Mw7.9??  相似文献   

15.
һ���������������·�����   总被引:1,自引:0,他引:1  
?÷???????????????????????Щ????о???????????????????????·,????Χ0??360????????????????·?????????????????????·??????????????????????侫????2.8??????????????  相似文献   

16.
<正>柔鱼(Ommastrephes bartramii)广泛分布在北太平洋,20世纪70年代初首先由日本鱿钓船开发,我国大陆于1993年开始利用该资源,1994年进行较大规模地商业性生产。目前北太平洋鱿钓渔业已成为我国远洋渔业的支柱[1]。据估计,历史上北太平洋柔  相似文献   

17.
The three dimensional structure of the western boundary current east of the Vietnam coast was determined from measurements by Argo profiling floats which deployed near the east of the Vietnam Coast in October 2007. The trajectories of the Argo floats provided robust evidence that there does exist southward flowing current along the Vietnam coast. The southward current begins at about 15°N, 111°E, flowing along the 1 000 m isobath and extending to 5°N south. The estimated surface and parking depth velocities obtained from the floats suggest that this southward current can extend to 1 000 m depth. The mean surface velocity of the western boundary current is about 49 cm/s, with the maximum speed exceeding 100 cm/s occurring at 11.6°N, 109.5°E in the direction of 245°. The mean parking depth (1 000 m) velocity is 12–16 cm/s with the maximum speed of 36 cm/s occurring at 12.1°N, 109.7°E in the direction of 239°.  相似文献   

18.
1INTRODUCTIONForests are one of the major natural resources that per-form important environmental and recreational func-tions (COSTANZA and GROOT, 1997). It is well known that forests can absorb atmospheric carbon, maintain a certain degree of humidity in atmosphere, regulate rainfall, moderate temperature, and restrain soil erosion, etc. (AURELIA, 2003). So, the health of a forest in any given area is a very important indicator of the ecological conditions. But fire is the great…  相似文献   

19.
The global climate is intimately connected to changes in the polar oceans. The variability of sea ice coverage affects deep-water formations and large-scale thermohaline circulation patterns. The polar radiative budget is sensitive to sea-ice loss and consequent surface albedo changes. Aerosols and polar cloud microphysics are crucial players in the radiative energy balance of the Arctic Ocean. The main biogenic source of sulfate aerosols to the atmosphere above remote seas is dimethylsulfide (DMS). Recent research suggests the flux of DMS to the Arctic atmosphere may change markedly under global warming. This paper describes climate data and DMS production (based on the five years from 1998 to 2002) in the region of the Barents Sea (30–35°E and 70–80°N). A DMS model is introduced together with an updated calibration method. A genetic algorithm is used to calibrate the chlorophyll-a (CHL) measurements (based on satellite SeaWiFS data) and DMS content (determined from cruise data collected in the Arctic). Significant interannual variation of the CHL amount leads to significant interannual variability in the observed and modeled production of DMS in the study region. Strong DMS production in 1998 could have been caused by a large amount of ice algae being released in the southern region. Forcings from a general circulation model (CSIRO Mk3) were applied to the calibrated DMS model to predict the zonal mean sea-to-air flux of DMS for contemporary and enhanced greenhouse conditions at 70–80°N. It was found that significantly decreasing ice coverage, increasing sea surface temperature and decreasing mixed-layer depth could lead to annual DMS flux increases of more than 100% by the time of equivalent CO2 tripling (the year 2080). This significant perturbation in the aerosol climate could have a large impact on the regional Arctic heat budget and consequences for global warming.  相似文献   

20.
Using hydrographic data covering large areas of ocean for the period from June 21 to July 5 in 2009,we studied the circulation structure in the Luzon Strait area,examined the routes of water exchange between the South China Sea(SCS) and the Philippine Sea,and estimated the volume transport through Luzon Strait.We found that the Kuroshio axis follows a e-shaped path slightly east of 121uE in the upper layer.With an increase in depth,the Kuroshio axis became gradually farther from the island of Luzon.To study the water exchange between the Philippine Sea and the SCS,identification of inflows and outflows is necessary.We first identified which flows contributed to the water exchange through Luzon Strait,which differs from the approach taken in previous studies.We determined that the obvious water exchange is in the section of 121°E.The westward inflow from the Philippine Sea into the SCS is 6.39 Sv in volume,and mainly in the 100±500 m layer at 19.5°±20°N(accounting for 4.40 Sv),while the outflow from the SCS into the Philippine Sea is concentrated in the upper 100 m at 19°±20°N and upper 400 m at 21°±21.5°N,and below 240 m at 19°±19.5°N,accounting for 1.07,3.02 and 3.43 Sv in volume transport,respectively.  相似文献   

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