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1.
Application of nonlinear multi-channel algorithms for estimating sea surface temperature with NOAA-14 AVHRR data 总被引：1，自引：0，他引：1
李晓峰 《中国海洋湖沼学报》2000,18(3):199-207
ＩＮＴＲＯＤＵＣＴＩＯＮＳｉｎｃｅｔｈｅｅａｒｌｙ 1 970ｓ,ｔｈｅＡｄｖａｎｃｅｄＶｅｒｙＨｉｇｈＲｅｓｏｌｕｔｉｏｎＲａｄｉｏｍｅｔｅｒ(ＡＶＨＲＲ)ｏｎｂｏａｒｄｔｈｅＮａｔｉｏｎａｌＯｃｅａｎｉｃａｎｄＡｔｍｏｓｐｈｅｒｉｃＡｄｍｉｎｉｓｔｒａｔｉｏｎ (ＮＯＡＡ)ｓｅｒｉｅｓｏｆＰｏｌａｒ ｏｒｂｉｔｉｎｇＯｐｅｒａｔｉｏｎａｌＥｎ ｖｉｒｏｎｍｅｎｔａｌＳａｔｅｌｌｉｔｅｓ (ＰＯＥＳ)ｈａｓｂｅｅｎｕｓｅｄｆｏｒｓｅａｓｕｒｆａｃｅｔｅｍｐｅｒａｔｕｒｅ (ＳＳＴ)ｒｅｔｒｉｅｖａｌａｎｄｃｌｏｕ… 相似文献
2.
台风对中国东南海域叶绿素a浓度影响的遥感研究 总被引：1，自引：0，他引：1
通过对台风过境前后近一个月的MODIS卫星3A级叶绿素a浓度及海表温度数据的比较与分析,发现海表温度,海表叶绿素a浓度均受到较大的影响,其中海表温度平均下降2~3℃,最高下降近10℃;同时叶绿素a浓度在湛江、阳江海域升高约1.43倍,在东海海域平均升高2.44倍,最高可达9.75倍,并且叶绿素a浓度增长有一个约3~5 d的延迟效应。由此可见,利用卫星遥感资料监测台风对海洋叶绿素a浓度、海表表温度等环境参数的变化有应用前景。 相似文献
3.
In this study, the temporal and spatial variations of observed global oceanic precipitation during 1979–2010 are investigated. It is found that the global trend in precipitation during this period varies at a rate of 1.5%/K of surface warming while the rate is 6.6%/K during 2006–2010. The precipitation is highly correlated with Sea Surface Temperature(SST) in both the temporal and the spatial patterns since the strong 1997–98 El Nino event. Considering the distributions of precipitation and SST, seven oceanic regions are classified and presented using the observed Global Precipitation Climatology Project(GPCP) data and Extended Reconstructed Sea Surface Temperatures, version 3(ERSST.v3) data. Further examining the mechanisms of the classified oceanic precipitation regions is conducted using the Tropical Rainfall Measuring Mission(TRMM) satellite, GFDL-ESM-2G model precipitation and SST data and Hadley Center sea ice and SST version 1(Had ISST1) data. More than 85% of global oceanic precipitations are controlled by either one or both of the warmer-get-wetter mechanism and wet-get-wetter mechanism. It is estimated that a 0.5 SST signal-to-noise ratio, representing the trend of SST time series to the standard deviation, is a criterion to distinguish the mechanism of a region. When the SST ratio is larger than 0.5, the precipitation of this region is controlled by the warmer-get-wetter mechanism. SST, rather than the humidity, is the pivotal factor. On the other hand, when the SST ratio is less than 0.5, the precipitation is controlled by the wet-get-wetter mechanism. The SST variability is a significant factor contributing to the precipitation variation. 相似文献
4.
The sea surface height oscillation with a quasi-four-month period (SSHO4) along continental slope in the northern South China Sea (NSCS) is detected using satellite altimeter data and an ocean model simulation. The SSHO4 is at southwest of Dongsha Island, and is characterized by a wavelength of ~600 km and a southwestward phase speed of ~0.1 m/s. Crossing the climatological background SST front, geostrophic currents corresponding to the SSHO4 generally induce sea surface temperature (SST) "tongues" during January-March. The cold and warm SST tongues appear southwest of cyclonic and anticyclonic eddies, respectively. The distance between the warm and cold SST tongues is about half the wavelength of the SSHO4. The geostrophic currents play an important role in lateral mixing, as manifested by the SST tongue phenomena in the NSCS. 相似文献
5.
Long-term change of sea surface temperature (SST) in the China Seas from 1900 to 2006 is examined based on two different observation datasets (HadISST1 and HadSST3). Similar to the Atlantic, SST in the China Seas has been well observed dur-ing the past 107 years. A comparison between the reconstructed (HadISST1) and un-interpolated (HadSST3) datasets shows that the SST warming trends from both datasets are consistent with each other in most of the China Seas. The warming trends are stronger in winter than in summer, with a maximum rate of SST increase exceeding 2.7℃ (100 year)-1 in the East China Sea and the Taiwan Strait during winter based on HadISST1. However, the SST from both datasets experienced a sudden decrease after 1999 in the China Seas. The estimated trend from HadISST1 is stronger than that from HadSST3 in the East China Sea and the east of Taiwan Island, where the difference in the linear SST warming trends are as large as about 1℃ (100 year)-1 when using respectively HadISST1 and HadSST3 datasets. When compared to the linear winter warming trend of the land surface air temperature (1.6℃ (100 year)-1), HadSST3 shows a more reasonable trend of less than 2.1℃ (100 year)-1 than HadISST1’s trend of larger than 2.7℃ (100 year)-1 at the mouth of the Yangtze River. The results also indicate large uncertainties in the estimate of SST warming patterns. 相似文献
6.
An ENSO-like oscillation system 总被引：4，自引：0，他引：4
INTRODUCTIONElNi no SouthernOscillation (ENSO)istheinterannualinteractionofocean atmosphereinthetropical (especiallyequatorial)Pacific,andisconsideredtobethedominantmechanismoftheearth’sinterannualclimatechange.ThereareseveralparadigmsproposedforinterpretingENSO .Bjerknes’ (1 966,1 969)pio neeringworkvisualizedacloseassociationbetweenoceanandatmosphereandexplainedhowthedis turbancecoulddevelopthroughtheocean atmosphereinteraction .Heproposedapositivefeedbackmechanism .ButENSOisan… 相似文献
7.
ＩＮＴＲＯＤＵＣＴＩＯＮＴｈｅＳｏｕｔｈＣｈｉｎａＳｅａ (ＳＣＳ)ｉｓａｓｅｍｉ ｅｎｃｌｏｓｅｄｏｃｅａｎｂａｓｉｎｌｏｃａｔｅｄａｔａｓｐｅｃｉａｌｇｅｏｇｒａｐｈｉｃｐｏ ｓｉｔｉｏｎ ,ｏｎｅｏｆｔｈｅｗｏｒｌｄ’ｓｐｒｏｎｏｕｎｃｅｄｍｏｎｓｏｏｎｒｅｇｉｏｎｓ,ｗｉｔｈｎｏｒｔｈｅａｓｔｗｉｎｄｓｐｒｅｖａｉｌｉｎｇｉｎｗｉｎｔｅｒａｎｄｓｏｕｔｈｗｅｓｔｗｉｎｄｓｉｎｓｕｍｍｅｒ,ａｎｄｉｓａｃｒｕｃｉａｌｒｅｇｉｏｎｏｆｉｎｔｅｎｓｉｖｅａｉｒ ｓｅａｉｎｔｅｒａｃｔｉｏｎｏｆｇｒｅａｔ… 相似文献
8.
INTRODUCTIONPolarlowsareintensemeso scalecyclonesthatformincoldairstreamsofthepolarairmass.Theyhavehorizontalscalesoftheorderofseveralhundredkilometers;severalhourstoseveraldayslifecycles;andusuallydevelopoverhighlatitudeoceansinwinter,forexample ,theGulfofAlaska(1 3 5-1 60°W ,50 -60°N) ,theBarentsSea (2 0 -50°E ,65-75°N) ,theLabradorSea (50 -60°W ,55-65°N)andtheNorwegianSea (5°W -1 0°E ,60 -70°N) .Onsatelliteimages ,polarlowsareoftencharacterizedbytight,spiralcloudpatterns… 相似文献
9.
10.
Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of SST, over the period of January 1982 to October 2003, the corresponding TCF correlates best with the Dipole Mode Index (DMI), Niño1+2, Niño3.4, Niño3, and Niño4 indices with time lags of 10, 3, 6, 5, and 6 months, respectively. Thus, a statistical hindcasts in the prediction model are based on a canonical correlation analysis (CCA) model using the above indices as predictors spanning from 1993/1994 to 2003/2004 with a 1–12 month lead time after the canonical variants are calculated, using data from the training periods from January 1982 to December1992. The forecast model is successful and steady when the lead times are 1–12 months. The SCS warm event in 1998 was successfully predicted with lead times from 1–12 months irrespective of the strength or time extent. The prediction ability for SSTA is lower during weak ENSO years, in which other local factors should be also considered as local effects play a relatively important role in these years. We designed the two forecast models: one using both DMI and Niño indices and the other using only Niño indices without DMI, and compared the forecast accuracies of the two cases. The spatial distributions of forecast accuracies show different confidence areas. By turning off the DMI, the forecast accuracy is lower in the coastal areas off the Philippines in the SCS, suggesting some teleconnection may occur with the Indian Ocean in this area. The highest forecast accuracies occur when the forecast interval is five months long without using the DMI, while using both of Niño indices and DMI, the highest accuracies occur when the forecast interval time is eight months, suggesting that the Niño indices dominate the interannual variability of SST anomalies in the SCS. Meanwhile the forecast accuracy is evaluated over an independent test period of more than 11 years (1993/94 to October 2004) by comparing the model performance with a simple prediction strategy involving the persistence of sea surface temperature anomalies over a 1–12 month lead time (the persisted prediction). Predictions based on the CCA model show a significant improvement over the persisted prediction, especially with an increased lead time (longer than 3 months). The forecast model performs steadily and the forecast accuracy, i.e., the correlation coefficients between the observed and predicted SSTA in the SCS are about 0.5 in most middle and southern SCS areas, when the thresholds are greater than the 95% confidence level. For all 1 to 12 month lead time forecasts, the root mean square errors have a standard deviation of about 0.2. The seasonal differences in the prediction performance for the 1–12 month lead time are also examined. 相似文献
11.
NUMERICAL STUDY ON THE INTERANNUAL OSCILLATION OF SEA SURFACE TEMPERATURE IN THE SOUTH CHINA SEA 总被引：5，自引：0，他引：5
A two and a half layer oceanic model of wind-driven, thermodynamical general circulation is appliedto study the interannual oscillation of sea surface temperature (SST) in the South China Sea (SCS). Themodel consists of two active layers: the upper mixed layer (UML) and the seasonal thermocline, with themotionless abyss beneath them. The governing equations which include momentum, continuity and sea.temperature for each active layer, can describe the physics of Boussinseq approximation, reduced gravityand equatorial β-plane. The formulas for the heat flux at the surface and at the interface between twoactive layers are designed on the Haney scheme. The entrainment and detrainment at the bottom of theUML induces vertical transport of mass,momentum and heat, and couples of dynamic andthermodynamic effect.Using leap-frog integrating scheme and the Arakawa-C grid the model is forced bya time-dependent wind anomaly stress pattern obtained from category analysis of COADS. The numerical results indicate that t 相似文献
12.
Various satellite data, JRA-25 (Japan reanalysis of 25 years) reanalyzed data and WRF (Weather Research Forecast) model are used to investigate the in situ effect of the ESKF (East China Sea Kuroshio Front) on the MABL (marine atmospheric boundary layer). The intensity of the ESKF is most robust from January to April in its annual cycle. The local strong surface northerly/northeasterly winds are observed right over the ESKF in January and in April and the wind speeds decrease upward in the MABL. The thermal wind effect that is derived from the baroclinic MABL forced by the strong SST gradient contributes to the strong surface winds to a large degree. The convergence zone existing along the warm flank of the ESKF is stronger in April than in January corresponding to the steeper SST (sea surface temperature) gradient. The collocations of the cloud cover maximum and precipitation maximum are basically consistent with the convergence zone of the wind field. The clouds develop higher (lower) in the warm (cold) flank of the ESKF due to the less (more) stable stratification in the MABL. The lowest clouds are observed in April on the cold flank of the ESKF and over the Yellow Sea due to the existence of the pronounced temperature inversion. The numerical experiments with smoothed SST are consistent with the results from the ovservations. 相似文献
13.
Evaluation and fusion of SST data from MTSAT and TMI in East China Sea, Yellow Sea and Bohai Sea in 2008 总被引：1，自引：0，他引：1
Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea, Yellow Sea, and Bohai Sea throughout 2008. Most monthly-mean availabilities of MTSAT are higher than those of TMI, whereas the seasonal variation of the latter is less than that of the former. The analysis on the one-year data shows that the annual mean availability of MTSAT (61%) is greater than that of TMI (56%). This is mainly because MTSAT is a geostationary satellite, which achieves longer observation than the sun-synchronous TMI. The daily availability of TMI (28%-75%) is more constant than that of MTSAT (9%-93%). The signal of infrared sensors on MTSAT is easily disturbed on cloudy days. In contrast, the TMI microwave sensor can obtain information through clouds. Based on in-situ SSTs, the SST accuracy of TMI is superior to that of MTSAT. In 2008, the root mean square (RMS) error of TMI and MTSAT were 0.77 K and 0.84 K, respectively. The annual mean biases were 0.14 K (TMI) and -0.31 K (MTSAT). To attain a high availability of SSTs, we propose a fusion method to merge both SSTs. The annual mean availability of fusion SSTs increases 17% compared to MTSAT. In addition, the availabilities of the fusion SSTs become more constant. The annual mean RMS and bias of fusion SSTs (0.78 K and -0.06 K, respectively) are better than those of MTSAT (0.84 K and -0.31 K). 相似文献
14.
Seasonal and annual with stress fields over the Bohai Sea, the Yellow Sea and the East China Sea were computed from the wind
rose data compiled in the Climatic Atlas of Chinese Offshore Areas and North-west Pacific and published by the Ocean Press
in 1982. 684 wind roses in 2° latitude by 2° longitude boxes constructed from 278,815 wind reports are involved in the present
study. The computations are principally intended as a data source for further research. Some oceanographic consequences are
expounded on. 相似文献
15.
This paper presents a study on drag coefficients under typhoon wind forcing based on observations and numerical experiments. The friction velocity and wind speed are measured at a marine observation platform in the South China Sea. Three typhoons: SOULIK(2013), TRAMI(2013) and FITOW(2013) are observed at a buoy station in the northeast sea area of Pingtan Island. A new parameterization is formulated for the wind drag coefficient as a function of wind speed. It is found that the drag coefficient(Cd) increases linearly with the slope of 0.083′10~(-3) for wind speed less than 24 m s~(-1). To investigate the drag coefficient under higher wind conditions, three numerical experiments are implemented for these three typhoons using SWAN wave model. The wind input data are objective reanalysis datasets, which are assimilated with many sources and provided every six hours with the resolution of 0.125?×0.125?. The numerical simulation results show a good agreement with wave observation data under typhoon wind forcing. The results indicate that the drag coefficient levels off with the linear slope of 0.012′10~(-3) for higher wind speeds(less than 34 m s~(-1)) and the new parameterization improvese the simulation accuracy compared with the Wu(1982) default used in SWAN. 相似文献
16.
NEW METHOD TO OBTAIN THE POWER SPECTRA OF HIDDEN VARIABLES AND ITS APPLICATION TO OCEAN DATA 总被引：2，自引：0，他引：2
A novel method is proposed to obtain the power spectra of hidden variables in a chaotic time series. By embedding the data in phase space , and recording the conditional probability densityof points that the trajectory encounters as it evolves in the reconstructed phase space, it is possible torecover the power spectra of hidden variables in chaotic time series through a spectral analysis over theconditional probability density time series. The method is robust in the application to Lorenz system, 4-di-mension Rossler system and rigid body motion by linear feedback system (LFRBM). Applying the method the time series of sea surface temperature (SST) of the South China Sea, we obtained the power spectraof the wind speed (WS) from SST data. Furthermore, the results showged that there exists an importantnonlinear interaction between the SST and the WS. 相似文献
17.
Analysis of COADS data (1958–1987) showed that there is obviously interannual SST oscillation including QBO (Quasi-biennial
oscillation) and quasi-3.5 year oscilation, etc., of the SCS (South China Sea), which is the response of the upper mixed layer
of the sea to the impact of the East Asian Monsoon anomaly. Most SST anomalies appear in the central basin of the SCS. The
phase-locked phenomena linking the SST annual cycle and interannual oscillation is an important characteristic of the SCS
climate. There is not only SST response to atmospheric impact, but also feedback to the air. The authors put forward a scheme
of regional air-sea interaction in winter time in the SCS.
Project 49676276 supported by NSFC and also supported by FSEC. 相似文献
18.
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???????????????????????????????????????????????????????????????????????????????????????????EGM96??????????ETOPO2???????????????????????Σ?????????????????????ETOPO2?????????б????侫????????ETOPO2?????????????????? 相似文献
19.
The Upper Ocean Thermal Structure and the Genesis Locations of Tropical Cyclones in the South China Sea 总被引：2，自引：1，他引：1
WANG Lei Fung Chi-Hung Lau Kai-Hon 《中国海洋大学学报(英文版)》2007,6(2):125-131
The relationship between the upper ocean thermal structure and the genesis locations of tropical cyclones （TCs） in the South China Sea （SCS） is investigated by using the Joint Typhoon Warning Center （JTWC） best-track archives and high resolution （1/4 degree） temperature analyses of the world＇s oceans in this paper In the monthly mean genesis positions of TCs from 1945 to 2005 in the SCS, the mean sea surface temperature （SST） was 28.8℃ and the mean depth of 26℃ water was 53.1 m. From the monthly distribution maps of genesis positions of TCs, SST and the depth of 26℃ water in the SCS, we discovered that there existed regions with SST exceeding 26℃ and 26℃ water depth exceeding 50m where no tropical cyclones formed from 1945 to 2005 in the SCS, which suggests that there were other factors unfavorable for TC formation in these regions. 相似文献
20.
YANG Yuxing HUANG Fei 《中国海洋大学学报(英文版)》2005,4(4):403-410
The relationship between the variability of the Eastern India Ocean Warm Pool （EIWP） and the spring precipitation in China is studied in the paper based on an analysis of the Simple Ocean Data Assimilation （SODA） Sea Surface Temperature （SST） data, the reanalysis data of monthly grid wind field at 925 hPa with a resolution of 2.5^＊ latitude and longitude from the National Center for Environmental Prediction/National Center for Atmospheric Research （NCEP/NCAR）, and the monthly mean rainfall data from 160 observational stations in China. The results show that there is a strong correlation between the EIWP variability and the spring precipitation in China. The area, volume and intensity indices of the EIWP are negatively correlated with the spring precipitation in southwestern China, while they are positively correlated with the spring precipitation in the rest of China, especially in the northeast. For this correlation between the EIWP variability and the spring precipitation in China, it is found that the correlative relationship is mainly connected with the variations of the moisture transport by the warm air flow, which is under the influence of the EIWP variability, into the inland of China in spring. Two causative factors may influence this transport. One is the variation of the moisture transport carried by the warm air flow from the Arabian Sea influenced by the EIWP variability. The other is the variation of the equator-crossing flow （70^＊-90^＊E） influenced by the EIWP anomaly in the previous winter which exerts its effect on the moist warm air transported from the Southern Hemisphere. The position and intensity of the Western North Pacific Subtropical High （WNPSH） variability caused by EIWP variation also influence the spring precipitation in China. 相似文献