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1.
The Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) is a five-channel radiometer with wavelength from 0.6 to 12 μm. Daily 0.125° sea surface temperature (SST) data from VIRS were first produced at the National Space Development Agency (NASDA) for comparison with SST from TRMM Microwave Imager (TMI). In order to obtain accurate high spatial resolution SST for the merging of SST from infrared and microwave measurements, new SST retrieval coefficients of the Multichannel SST (MCSST) algorithm were generated using the global matchups from VIRS brightness temperature (BT) and Global Telecommunications System (GTS) SST. Cloud detection was improved and striping noise was eliminated. One-year global VIRS level-1B data were reprocessed using the MCSST algorithm and the advanced cloud/noise treatments. The bias and standard deviation between VIRS split-window SST and in situ SST are 0.10°C and 0.63°C, and for triple-window SST, are 0.06°C and 0.48°C. The results indicate that the reprocessing algorithm is capable of retrieving high quality SST from VIRS data. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   

2.
The Global Ocean Data Assimilation Experiment (GODAE) requires the availability of a global analyzed SST field with high-resolution in space (at least 10 km) and time (at least 24 hours). The new generation SST products would be based on the merging of SSTs from various satellites data and in situ measurements. The merging of satellite infrared and microwave SST data is investigated in this paper. After pre-processing of the individual satellite data, objective analysis was applied to merge the SST data from NOAA AVHRR (National Oceanic and Atmospheric Administration, Advanced Very High Resolution Radiometer), GMS S-VISSR (Geostationary Meteorological Satellite, Stretched-Visible Infrared Spin Scan Radiometer), TRMM MI (Tropical Rainfall Measuring Mission, Microwave Imager: TMI) and VIRS (Visible and Infrared Scanner). The 0.05° daily cloud-free SST products were generated in three regions, viz., the Kuroshio region, the Asia-Pacific Region and the Pacific, during one-year period of October 1999 to September 2000. Comparisons of the merged SSTs with Japan Meteorological Agency (JMA) buoy SSTs show that, with considerable error sources from individual satellite data and merging procedure, an accuracy of 0.95 K is achieved. The results demonstrate the practicality and advantages of merging SST measurements from various satellite sensors.  相似文献   

3.
In the present article, we introduce a high resolution sea surface temperature(SST) product generated daily by Korea Institute of Ocean Science and Technology(KIOST). The SST product is comprised of four sets of data including eight-hour and daily average SST data of 1 km resolution, and is based on the four infrared(IR) satellite SST data acquired by advanced very high resolution radiometer(AVHRR), Moderate Resolution Imaging Spectroradiometer(MODIS), Multifunctional Transport Satellites-2(MTSAT-2) Imager and Meteorological Imager(MI), two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2(AMSR2), and Wind SAT with in-situ temperature data. These input satellite and in-situ SST data are merged by using the optimal interpolation(OI) algorithm. The root-mean-square-errors(RMSEs) of satellite and in-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from January to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71°C and the bias value was –0.08°C. The largest RMSE and bias were 0.86 and –0.26°C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Japan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60°C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature(GHRSST) product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System(KOOS) as an input parameter for data assimilation.  相似文献   

4.
A new set of multi-channel sea surface temperature (MCSST) equations for the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-9 is derived from regression analyses between two-channel brightness temperatures andin situ SST obtained from moored buoys around Japan. Two equations are derived: one for daytime and the other for nighttime. They are linear split window type and both the equations contain a term dependent on satellite zenith angle, which has not been accounted for in the previous daytime split window equations for NOAA-9. It is shown that the new set of equation can give SSTs in much better precision than those without the zenith-angle-dependent terms. It is also found that the split window equation for NOAA-9 provided by the National Oceanographic and Atmospheric Administration/National Environmental Satellite, Data and Information Service (NOAA/NESDIS) considerably underestimates the daytime SSTs; sometimes nighttime SSTs are evenhigher than daytime SSTs. This is because the zenith angle effect to the radiation deficiet is neglected in the daytime equation by NOAA/NESDIS. By using the new MCSST equations, it is expected that the quality of satellite MCSST would be much improved, at least in regional applications around Japan, for the period of NOAA-9's operation.  相似文献   

5.
Sea surface temperature SST obtained from the initial version of the Korea Operational Oceanographic System(KOOS) SST satellite have low accuracy during summer and daytime. This is attributed to the diurnal warming effect. Error estimation of SST data must be carried out to use the real-time forecasting numerical model of the KOOS. This study suggests two quality control methods for the KOOS SST system. To minimize the diurnal warming effect, SSTs of areas where wind speed is higher than 5 m/s were used. Depending on the wind threshold value, KOOS SST data for August 2014 were reduced by 0.15°C. Errors in SST data are considered to be a combination of random, sampling, and bias errors. To estimate bias error, the standard deviation of bias between KOOS SSTs and climatology SSTs were used. KOOS SST data yielded an analysis error standard deviation value similar to OSTIA and NOAA NCDC(OISST) data. The KOOS SST shows lower random and sampling errors with increasing number of observations using six satellite datasets. In further studies, the proposed quality control methods for the KOOS SST system will be applied through more long-term case studies and comparisons with other SST systems.  相似文献   

6.
The accuracy of sea surface temperatures (SSTs) derived from the Advanced Very High Resolution Radiometer (AVHRR)/NOAA-11 is examined by comparison with sea-truth SSTs obtained from ocean data buoys durings November 1988 through December 1989. We made a 122 point data set of buoy SSTs from the oceans around Japan and the corresponding brightness temperatures of channels 4 and 5 during cloud free periods. The satellite temperatures are corrected for atmospheric effects using the NOAA Multi-Channel SST (MCSST) and Cross Product SST (CPSST) algorithms. The two algorithms give similar results for our data set and result in biases of about –0.1°C with rms errors of about 0.6°C relative to buoy SSTs. It is found that MCSSTs and CPSSTs tend to be higher than SSTs from the buoy in the Japan Sea in summer. New coefficients for the MCSST equations suitable for our data set are determined and the resultant rms error is 0.49°C. If we eliminate the cluster of anomalous summer data in the Japan Sea, the rms error becomes 0.43°C.  相似文献   

7.
For the study of the ocean south of Japan, the HIGHER spatial resolution Sea surface temperature (HIGHERS) data have been produced from the AVHRR/NOAA data. The grid size is 0.075 degree and is much smaller than that of the usual sea surface temperature (SST) analysis field, which is gridded at most in 1 degree. In order to calculate accurate SST, the split-window Multi-Channel SST method is applied to cloudless pixels, which are detected with a cloud detection algorithm. The accuracy of the HIGHERS data is checked in comparison with the in-situ observation data.  相似文献   

8.
In the previous study, merged sea surface temperature (SST) dataset called “New Generation SST” has been produced from several infrared and microwave satellite SSTs through an objective mapping. Here we examine the merged SST by comparison with moored buoy SST at 1 m depth, which is treated as true sea surface temperature. Comparison between wavelet spectra of merged and buoy SSTs shows that the former have larger amplitudes than those of the latter, which is partly explained as an aliasing effect due to TRMM Microwave Imager (TMI) aboard Tropical Rainfall Measuring Mission (TRMM) sampling on merged products. Coherency between wavelet-decomposed merged and buoy SSTs has high values in autumn and low ones in winter to spring. In winter, phase differences between them are positive, meaning that wavelet components of merged SST lag those of buoy SST. Reasons for delay and low coherency are: (1) seasonal components of merged SSTs are strongly affected by a lack of infrared SSTs due to clouds in winter, and (2) small-scale oceanic features, undetectable by coarse-resolution microwave SSTs, are blurred by the merging process. Improvements of merging methodology are discussed with regard to present study results.  相似文献   

9.
A regional algorithm to estimate SST fields in the western North Pacific, where small oceanographic disturbance are often found, has been developed using Moderate Resolution Imaging Spectroradiometers (MODIS) aboard Terra and Aqua. Its associated algorithm, which includes cloud screening and SST estimation, is based on an algorithm for the Global Imager (GLI) aboard Advanced Earth Observing Satellite-II (ADEOS-II) and is tuned for MODIS sensors. For atmospheric correction, we compare Multi-Channel SST (MCSST), Nonlinear SST (NLSST), Water Vapor SST (WVSST) and Quadratic SST (QDSST) techniques. For NLSST, four first-guess SSTs are investigated, including the values for MCSST, climatology with two different spatial resolutions, and near-real-time objective analysis. The results show that the NLSST method using high-resolution climatological SST as a first-guess has both good quality and high efficiency. The differences of root-mean-square error (RMSE) between the NLSST models using low-resolution climatology and those using high-resolution climatology are up to 0.25 K. RMSEs of the new algorithm are 0.70 K/0.65 K for daytime (Aqua/Terra) and 0.65 K/0.66 K for nighttime, respectively. Diurnal warming and the stratification of the ocean surface layer under low wind are discussed.  相似文献   

10.
We investigated the processes relating to the weakening of the SST front in the subtropical front (STF) zone using the Advanced Microwave Scanning Radiometer for the Earth Observing System SSTs for 7?years with temporal/spatial resolutions of 1?day/12.5?km. In April, the SST front is strong with a high gradient magnitude (GM) and Jensen–Shannon divergence (JSD) band; in August, SSTs become uniform (28–30?°C), together with small GMs (<0.8?°C/100?km) and JSDs (<0.75). Since the SST front features become invisible in GM/JSD snapshots and weekly–monthly averaged images, we call this phenomenon ‘SST front disappearance (SFD)’. The SFD occurs in August, but the number of high SSTs (>30?°C) in August is smaller than that in July, which indicates that the SFD results from not only the increase in lower SSTs but also the decrease in higher SSTs. In June and July, the GM distributions have quite large standard deviations compared to those in May and August. We also investigated the vertical profile of STF using in situ temperature/salinity profiles. It was revealed that the SFD influence extends to 50?m depth. The area of high integrated heat flux and shallow mixed layer depth were found to correspond to the area where the GM decreases from 0.9 to 0.6?°C/100?km during June–August. Quantitative analyses confirmed that the SFD mechanism may be attributable to the establishment of the shallow mixed layer by the high integrated heat flux from May to July. From July to August, the SST heating/cooling in the north/south of the SST front may accelerate the SFD.  相似文献   

11.
A series of molecular organic markers were determined in surface sediments from the Gulf of Genoa (Ligurian Sea) in order to evaluate their potential for palaeo-environmental reconstructions. Allochthonous input can be characterized by the distributions of n-C29 and n-C31 alkanes, n-C26 and n-C28 alkanols and branched glycerol dialkyl glycerol tetraethers (GDGTs), whose concentrations are generally highest near the river mouths. In the open basin however, terrestrial n-alkanes and n-alkanols may have an additional, eolian source. Autochthonous input is represented by crenarchaeol and isoprenoid GDGTs. Their concentrations are highest in the open basin showing the preference of Thaumarchaeota for oligotrophic waters. Indications of a significant degradation of sterols and C37 alkenones exclude these lipids as reliable productivity proxies. Using terrestrial and aquatic lipids as end-members allows estimating the percentage of terrestrial organic matter between 20% and 58% in the coastal area decreasing to 1–30% in the deep basin. The spatial distribution of sea surface temperature (SST) estimates using the alkenone-based UK′37 index is very similar to the autumnal (November) mean satellite-based SST distribution. Conversely, TEXH86-derived SST estimates are close to winter SSTs in the coastal area and summer SSTs in the open basin. This pattern reflects presumably a shift in the main production of Thaumarchaeota from the coastal area in winter to the open basin in summer. This study represents a major prerequisite for the future application of lipid biomarkers on sediment cores from the Gulf of Genoa.  相似文献   

12.
This study compares infrared and microwave measurements of sea surface temperature (SST) obtained by a single satellite. The simultaneous observation from the Global Imager (GLI: infrared) and the Advanced Microwave Scanning Radiometer (AMSR: microwave) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) provided an opportunity for the intercomparison. The GLI-and AMSR-derived SSTs from April to October 2003 are analyzed with other ancillary data including surface wind speed and water vapor retrieved by AMSR and SeaWinds on ADEOS-II. We found no measurable bias (defined as GLI minus AMSR), while the standard deviation of difference is less than 1°C. In low water vapor conditions, the GLI SST has a positive bias less than 0.2°C, and in high water vapor conditions, it has a negative (positive) bias during the daytime (nighttime). The low spatial resolution of AMSR is another factor underlying the geographical distribution of the differences. The cloud detection problem in the GLI algorithm also affects the difference. The large differences in high-latitude region during the nighttime might be due to the GLI cloud-detection algorithm. AMSR SST has a negative bias during the daytime with low wind speed (less than 7 ms−1), which might be related to the correction for surface wind effects in the AMSR SST algorithm.  相似文献   

13.
An algorithm for estimating global sea surface temperatures (SST) from data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite has been developed empirically. Four atmospheric correction models for MODIS observations are examined, and the effects of ancillary data for corrections are discussed. A nonlinear (NLSST) model using high-temporal-resolution climatological SSTs as the first guess shows high accuracy and availability. The addition of a temperature-proportional term to the NLSST model effectively improves the estimate.  相似文献   

14.
Satellite-derived sea surface temperature (SST) is validated based on in-situ data from the East China Sea (ECS) and western North Pacific where most typhoons, which make landfall on the Korean peninsula, are formed and pass. While forecasting typhoons in terms of intensity and track, coupled ocean-typhoon models are significantly influenced by initial ocean condition. Potentially, satellite-derived SST is a very useful dataset to obtain initial ocean field because of its wide spatial coverage and high temporal resolution. In this study, satellite-derived SST from various sources such as Tropical Rainfall Measuring Mission Microwave Imager (TMI), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and New Generation Sea Surface Temperature for Open Ocean (NGSST-O) datasets from merged SSTs were compared with in-situ observation data using an indirect method which is using near surface temperature for validation of satellite derived SST. In-situ observation data included shipboard measurements such as Expendable Bathythermograph (XBT), and Conductivity, Temperature, Depth (CTD), and Argo buoy data. This study shows that in-situ data can be used for microwave derived SST validation because homogeneous features of seawater prevail at water depths of 2 m to 10 m under favorable wind conditions during the summer season in the East China Sea. As a result of validation, root-mean-square errors (RMSEs) are shown to be 0.55 °C between microwave SST and XBT/CTD data mostly under weak wind conditions, and 0.7 °C between XBT/CTD measurement and NGSST-O data. Microwave SST RMSE of 0.55 °C is a potentially valuable data source for general application. Change of SST before and after typhoon passing may imply strength of ocean mixing due to upwelling and turbulent mixing driven by the typhoon. Based on SST change, ocean mixing, driven by Typhoon Nari, was examined. Satellite-derived SST reveals a significant SST drop around the track immediately following the passing of Typhoon Nari in October, 2007.  相似文献   

15.
Diurnal Sea Surface Temperature (SST) variations and the near-surface thermal structure of the tropical hot event (HE) have been investigated using advanced in-situ equatorial observations with hourly temporal resolution. The information on the HE area defined by the satellite cloud-free SSTs is used to sample the in-situ observations. The in-situ SSTs sampled for the HE conditions show that a maximum (minimum) SST has a histogram mode at 30.8°C (29.0°C), and frequently appears at 15:00 (07:00) local time. The amplitude of the diurnal SST variation (DSST) is defined by the difference between the maximum and minimum SSTs. The mean DSST during HEs is greater than 0.5°C, and has a maximum of about 0.75°C at the HE peak. The time series of mean DSST gradually increases (rapidly decreases) before (after) the peak. The satellite SST has a systematic positive bias against the corresponding daytime SST measured by the Triangle Trans-Ocean buoy Network. This bias is enhanced under conditions of large in-situ DSST. One-dimensional numerical model simulation suggests that the systematic bias is caused by the sharp vertical temperature gradient in the surface layer of HE. The near-surface thermal structure is generated by conditions of high insolation and low wind speed, which is the typical HE condition.  相似文献   

16.
HY-2 satellite is the first satellite for dynamic environmental parameters measurement of China,which was launched on 16th August 2011.A scanning microwave radiometer（RM） is carried for sea surface temperature（SST）,sea surface wind speed,columnar water vapor and columnar cloud liquid water detection.In this paper,the initial SST product of RM was validated with in-situ data of National Data of Buoy Center（NDBC） mooring and Argo buoy.The validation results indicate the accuracy of RM SST is better than 1.7 C.The comparison of RM SST and WindSat SST shows the former is warmer than the latter at high sea surface wind speed and the difference between these SSTs is depend on the sea surface wind speed.Then,the relationship between the errors of RM SST and sea surface wind speed was analyzed using NDBC mooring measurements.Based on the results of assessment and errors analysis,the suggestions of taking account of the affection of sea surface wind speed and using sea surface wind speed and direction derived from the microwave scatteromter aboard on HY-2 for SST product calibration were given for retrieval algorithm improvement.  相似文献   

17.
Producing high-quality match-ups coupling the Japanese geostationary satellite, Himawari-6 (H6), and buoy SST observations, we have developed the new SST retrieval method. Kawamura et al. (2010) developed the previous version of SST product called MTSAT SST, which left several scientific/technical questions. For solving them, 6,711 algorithm tuning match-ups with precise navigation and 240,476 validation match-ups are generated for covering all seasons and wide ocean coverage. For discriminating the previous MTSAT SST, we call the new version of SST H6 SST. It is found that the SZA dependences of MTSAT SST algorithm are different from area to area of SZA > 40–50° N/S. The regionally different SZA dependences are treated by dividing the H6 disk coverage into five areas by the latitude lines of 40° N/S first and the longitude lines of 100° K and 180° K. Using the algorithm tuning match-ups, Nonlinear SST (NLSST) equations are derived for all of the five areas. Though the sun zenith angle dependency correction term is also examined, there is no significant regional difference. Therefore, this term is used in the H6 SST algorithm again. The new H6 SST equation is formed by the areal NLSST and the sun zenith angle dependency term for each area. The statistical evaluation of H6 SST using the validation match-ups show the small negative biases and the RMS errors of about 0.74° K for each area. For the full H6 disk, the bias is −0.1° K and the RMS error 0.74° K. The histogram of H6 SST minus the in situ SST for each area has a similar Gaussian shape with small negative skewness, and the monthly validation of H6 SST for each area is consistent with those for the whole period and the histograms  相似文献   

18.
南北半球副热带高压对赤道东太平洋海温变化的响应   总被引：16，自引：0，他引：16  
本文利用1974年1月到1996年12月重分析(NOAANCEP-NCARCDAS-1)全球500hPa位势高度场资料,及同期赤道太平洋各海区SST资料,研究了南北半球副热带高压的变化特征及其对赤道东太平洋SST变化的响应。结果表明,全球副热带高压的变化及对SST的响应,在南北两个半球有很好的一致性。全球副热带高压强度的变化与超前3个月SST的正相关最为显着。对SST响应最强烈的区域主要在南北纬30°之间的低纬,低纬地区局地SST对副热带高压也有强烈的影响。从10°到30°纬度,对SST的响应分别落后于赤道2～9个月。在中、高纬大气环流的响应表现为波列特征,对暖SST及冷SST的响应波列基本相反,但对暖SST的响应更为显着。海温和副热带高压的月际持续性有明显的季节变化,副热带高压9-10月的相关障碍可能与NinoC区SST8-9月的相关障碍低点有关。  相似文献   

19.
Sea surface temperature (SST) isoline charts that were manually mapped using in situ SST data and satellite-derived SST data are valuable because they incorporate oceanographers’ knowledge and experience. This type of SST data is useful for studying sea conditions of an area, for analyzing environmental factors that could affect fishing grounds, as a parameter for atmospheric or oceanic models, or as a diagnostic tool for comparison with the SSTs produced by ocean models. However, isoline maps must be digitized and interpolated into grid data in order to be used in these applications. Herein, we propose a coupled interpolation (CI), which couples improved multi-section interpolation and single-point change surface interpolation containing orientation, for generating grid data from SST isolines. We interpolated 1049 SST isoline maps (temperature interval 1°), which cover an area of the northwestern Pacific Ocean (125°E–180°E, 26°N–50°N) and were published by the Japan Fisheries Information Service Center (JAFIC) during 1990–2000, to grid datasets with 15′ grid resolution. We assessed the quality of grid datasets by checking noise points, RMSE analysis, checking offset errors, retrieving percentage of Kuroshio axes and visually comparing inverse isotherms with original isotherms. The quality analysis and comparison with four other interpolators showed the CI interpolator to be a good technique for generating SST grid data from isotherms. We also computed the SST anomaly (SSTA) using the SST grid datasets. The amplitude values of integral SSTA in the area of 31–46°N, 170–180°E were low, whereas they were high in the SW–NE rectangular area of 35–46°N, 142–160°E.  相似文献   

20.
INTRODUCTIONDuring the 1960s, Bjerknes (1966, 1969) first noted that there had been strong relationshipbetween the tropical Pacific SST and atmospheric circulation. SST anomaly could affect tropicalatmospheric circulation by the Walker Circulation, and affect extratropical atmospheric circulationby the Hadley Circulation. When there was a "warm" event in the eastern tropical Pacific, ascending and sinking branch of the Hadley Circulation would strengthen, subtropical highs (SHs)and …  相似文献   

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