首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 281 毫秒
1.
Hourly sea surface temperature(SST) observations from the geostationary satellite are increasingly used in studies of the diurnal warming of the surface oceans. The aim of this study is to derive the spatial and temporal distribution of diurnal warming in the China seas and northwestern Pacific Ocean from Multi-functional Transport Satellite(MTSAT) SST. The MTSAT SST is validated against drifting buoy measurements firstly. It shows mean biases is about –0.2°C and standard deviation is about 0.6°C comparable to other satellite SST accuracy. The results show that the tropics, mid-latitudes controlled by subtropical high and marginal seas are frequently affected by large diurnal warming. The Kuroshio and its extension regions are smaller compared with the surrounding regions. A clear seasonal signal, peaking at spring and summer can be seen from the long time series of diurnal warming in the domain in average. It may due to large insolation and low wind speed in spring and summer, while the winter being the opposite. Surface wind speed modulates the amplitude of the diurnal cycle by influencing the surface heat flux and by determining the momentum flux. For the shallow marginal seas, such as the East China Sea, turbidity would be another important factor promoting diurnal warming. It suggests the need for the diurnal variation to be considered in SST measurement, air-sea flux estimation and multiple sensors SST blending.  相似文献   

2.
基于Himawari-8卫星的逐时次海表温度融合   总被引：1，自引：0，他引：1  
Himawari-8卫星是日本气象厅发射的新一代地球同步静止气象卫星,为获取逐时次海表温度产品提供了有力数据支持。本文以Himawari-8 AHI海表温度为基础,利用最优插值法融合GCOM-W1 AMSR2海表温度和NERA-GOOS现场观测资料,生成逐时次海表温度融合产品。为了充分利用邻近时刻的海表温度观测资料,利用Himawari-8 AHI海表温度和欧洲中期天气预报中心海面风速数据建立匹配数据集,研究建立海表温度日变化模型,实现邻近时刻海表温度的订正;为了消除多源海表温度间的系统偏差,以Himawari-8 AHI海表温度为目标数据,利用泊松方程对GCOM-W1 AMSR2海表温度进行偏差订正。实验验证结果表明,利用逐时次海表温度融合产品计算的日增温情况与海面风速具有较好的相关性,间接证实了逐时次海表温度融合产品的准确性;另外,逐时次海表温度融合产品与现场观测海表温度的偏差为0.09℃、均方根误差为0.89℃,二者具有较好的一致性,说明逐时次海表温度融合产品具有较高的精度。  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.
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   

5.
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   

6.
利用西北印度洋船测数据评估基于卫星的海表面温度   总被引：1，自引：1，他引：0  
本文描述了一次夏季在西北印度洋进行的调查船水文测量,用船测数据评估卫星海面表温度,并寻找影响海表面温度误差的主要因素。我们考虑了两种卫星数据,第一种是微波遥感产品——热带降雨测量任务微波成像仪TMI数据,另外一种是融合了微波,红外线,以及少部分观测数据的融合数据产品——可处理海表温度和海冰分析OSTIA数据。结果表明融合数据的日平均海表面温度的平均误差和均方根误差都比微波遥感小。这一结果证明了融合红外线遥感,微波遥感以及观测数据来提高海表面温度数据质量的必要性。此外,我们分析了海表面温度误差与各项水文参数之间的相关关系,包括风速,大气温度,想对湿度,大气压力,能见度。结果表明风速与TMI海表面温度误差的相关系数最大。而大气温度是影响OSTIA海表面温度误差最重要的因素;与此同时,想对湿度与海表面温度误差的相关系数也很高。  相似文献   

7.
The authors have verified a regression model for the evaluation of the daily amplitude of sea surface temperature (ΔSST) proposed by Kawai and Kawamura (2002). The authors investigated the accuracy of satellite data used for the evaluation and showed that ΔSST error caused by satellite data error is less than ±0.7 K. The evaluated ΔSSTs were compared with in situ values. Its root-mean-square error is about 0.3 K or less, except for a coastal region, and it has a bias of more than +0.1 K in the tropics. This bias can be removed by considering latent heat flux. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   

8.
An empirical method has been developed for estimation of sea surface temperature (SST) at dawn and noon in local time from microwave observations at other times of the day. By using solar radiation, microwave sea surface wind, and SSTs, root-mean-square differences were reduced to approximately 0.75 and 0.8 °C for dawn and noon, respectively. The pseudo SST variation and spatial patterns found in daily mean SST values by simple averaging of samples were damped down by use of diurnal correction. The satellite SST with the diurnal correction shows highly significant coherent variation with in-situ measurements.  相似文献   

9.
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   

10.
王进  张杰  王晶 《海洋学报》2015,37(3):46-53
Aquarius是专门用于海洋盐度监测的L波段辐射计,于2011年6月发射入轨,目前已进入业务化运行阶段。本文以太平洋为研究区域,利用Argo盐度现场数据对星载微波辐射计Aquarius的2012年2级数据产品质量进行了分析与讨论,结果表明:与Argo数据比较,Aquarius数据盐度存在0.1的负偏差,标准差约为0.7,升轨和降轨数据差异不明显;受亮温陆地污染和无线电射频干扰的影响,近岸海域反演误差较大;海面温度较高的低纬海域反演结果优于中纬度海域;受亮温敏感性及粗糙海面发射率模型的影响,Aquarius在低温水域以及高风速条件下盐度反演误差较大,标准差可达1以上。  相似文献   

11.
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   

12.
INTRODUCTIONIt has long been recognized that a diurnal thermal cycle occurs in the upper layer of the ocean(Stommel et al., 1969; Price and Weller, 1986). Interest in the subject has revived in recentyears due to the importance of resolving the diurnal cycle for correctly coupling the ocean and atmosphere (Lukas, 1991 ). While the study of the diurnal cycle is of intrinsic scientific interest, italso offers the benefit to remote sensing scientists of identifying the bias caused by the di…  相似文献   

13.
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   

14.
The importance of the diurnal variability of sea surface temperature (SST) on air-sea interaction is now being increasingly recognized. This review synthesizes knowledge of the diurnal SST variation, mainly paying attention to its impact on the atmosphere or the ocean. Diurnal SST warming becomes evident when the surface wind is weak and insolation is strong. Recent observations using satellite data and advanced instruments have revealed that a large diurnal SST rise occurs over wide areas in a specific season, and in an extreme case the diurnal amplitude of SST exceeds 5 K. The large diurnal SST rise can lead to an increase in net surface heat flux from the ocean of 50–60 Wm−2 in the daytime. The temporal mean of the increase exceeds 10 Wm−2, which will be non-negligible for the atmosphere. A few numerical experiments have indicated that the diurnal SST variation can modify atmospheric properties over the Pacific warm pool or a coastal sea, but the processes underlying the modification have not yet been investigated in detail. Furthermore, it has been shown that the diurnal change of ocean mixing process near the surface must be considered correctly in order to reproduce SST variations on an intraseasonal scale in a numerical model. The variation of mixed-layer properties on the daily scale is nonlinearly related to the intraseasonal variability. The mixed-layer deepening/shoaling process on the daily scale will also be related to biological and material circulation processes.  相似文献   

15.
We have developed an algorithm to estimate the wide-ranging Sea Surface Temperature (SST) data from the GMS-5 (Geostationary Meteorological Satellite) S-VISSR (Stretched-Visible Infrared Spin Scan Radiometer). Better SST estimates are realized by averaging the temporal variation of the VISSR calibration table and decreasing noise of the split-window terms using a spatial filter. The effects of the satellite zenith angle were examined in detail for better estimates, and VISSR-derived SSTs with root-mean-square (rms) error of 0.8 K were achieved using a new algorithm. The accuracy of SST estimates has been improved by using the temporal-spatial average of the split-window terms. Using the new techniques, we demonstrate that the hourly wide-ranging SST image data can be used to study the daily variations of SSTs in the Northern and Southern Pacific Oceans.  相似文献   

16.
本文将TMI（Tropical Rainfall Measuring Mission （TRMM）Microwave Imager）和AMSR-E（Advanced Microwave Scanning Radiometer for the Earth Observing System）卫星观测的全球海表温度与Argo浮标观测的近海表温度进行了比较。并检验了影响海温变化的因素,包括风速、水汽含量、液态云和地理位置。结果显示,TMI、AMSR-E海表温度与Argo近海表温度均明显相关。在低风速时,TMI、AMSR-E海表温度整体比Argo近海表温度高。在低风速时,TMI比AMSR-E海表温度更接近Argo近海表温度,但TMI海表温度在高纬可能没有经过良好校正。温度差异显示,在低水汽含量时,TMI和AMSR-E海表温度显示出暖的差异,代表TMI和AMSR-E海表温度在高纬均没有经过良好校正。黑潮延伸区的海表温度变化要比海潮区明显。春季在黑潮延伸区,卫星观测的海表温度与Argo近海表温度差异较小。在低风速时,TMI和AMSR-E海表温度均经过了良好校正,而TMI比AMSR-E效果更好。  相似文献   

17.
卫星遥感业务系统海表温度误差控制方法   总被引：11，自引：1，他引：11  
提高卫星遥感海表温度的反演精度是各种反演模型追求的目标,也是遥感系统业务化应用的关键.据相关文献报道,在晴空无云的条件下遥感海表温度的精度达到了0.5℃,但考虑到影响海表温度反演精度的多种因素,在遥感业务系统真正实现SST精度在1℃以内是非常困难的.在北太平洋渔场速报制作系统中,对遥感海表温度与船测温度误差统计显示均方根误差达到5.71℃,匹配点误差分布显示存在大量较大的负误差值,最大的为-17.2℃,遥感温度图也反映出存在片状温度低值区,这些区域很可能被错误地当作冷涡或冷锋区,严重干扰渔情分析,这些异常的温度误差很难通过海表温度反演模式和云检测技术来消除.采用一种标准海表温度参考图用于温度误差控制技术,可有效地检测温度反演异常值,将均方根值从5.71℃降低到1.75℃,如果采用2℃阈值控制计算均方根值,则海表温度精度达到0.785℃.该方法基本消除了遥感海表温度的低值现象,明显提高了遥感海表温度的精度,并已成功地应用于北太平洋渔区的海况速报产品制作中.  相似文献   

18.
An algorithm has been developed for retrieving sea surface temperature (SST) from hourly data transmitted from the Japanese Advanced Meteorological Imager (JAMI) aboard a Japanese geostationary satellite, Multi-functional Transport Satellite (MTSAT)-1R. Threshold tests screening cloudy pixels are empirically adjusted to cases of daytime with/without sun glitter, and nighttime. The Non-Linear SST (NLSST) equation, including several new additional terms, is used to calculate MTSAT SST. The estimated SST is compared with drifting and moored buoy measurements, with the result that the bias of the MTSAT SST is nearly 0.0°K. The root mean square (rms) error is about 0.8°K, and it is 0.7°K under the condition that the satellite zenith angle is less than 50°. It is demonstrated that the hourly MTSAT SST produced by the algorithm developed here captures diurnal SST variations in the equatorial sea in mid-November 2006.  相似文献   

19.
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   

20.
An accurate platinum resistance thermometer (PRT) has been installed on a commercial ferry that operates between Hillarys Marina, some 15 km north of Fremantle, and Rottnest Island off the Western Australian coast. The PRT is located in the engine intake system and provides continuous under-way measurements of the bulk sea surface temperature (SST) at a depth of 1 m. The “SeaFlyte” ferry makes the trip to Rottnest Island between 3 and 5 times daily and so a wealth of data is available for comparison with the SST derived using data from the GLI instrument on ADEOS-II. Analyses of the ferry and satellite data confirm the excellent quality of SST estimates from the GLI as well as four other satellite instruments—AVHRR on NOAA-16, AATSR on ENVISAT, and the MODIS instruments on TERRA and AQUA. All satellite instruments showed a comparison standard deviation of better than 0.6°C with GLI being better than 0.4°C. The number of ferry-satellite data coincidences used in this study demonstrates one of the advantages of installing measurement systems on commercial ships that operate regular passenger or freight services rather than infrequent deployments on research vessels. The analyses also demonstrate that satellite-derived SST estimates obtained under low surface wind conditions must be treated with care.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号