共查询到18条相似文献，搜索用时 93 毫秒
1.
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
2.
利用南大洋漂流浮标数据评估AMSR-E SST 总被引：4，自引：4，他引：4
利用AOML(Atlantic Oceanographical and Meteorological Laboratory)SVP漂流浮标的海表面温度数据,针对30°S以南的南大洋海域,对目前主要使用的微波遥感产品(AMSR-E,Ad-vanced Microwave Scanning Radiometer for the Earth Observing System)反演的SST进行了较为系统的评估。结果表明,AMSR-E SST比浮标数据偏冷,偏差为-0.01℃,标准差为0.70℃。夏季的偏差为0.004℃,标准差为0.64℃;冬季的偏差为-0.06℃,标准差为0.75℃,冬季的偏差和标准差较大。温差ΔT受流速影响,随着流速的增大而减小,且这种趋势在夏季更为显著。具备托伞结构的浮标与总体情况基本一致,而无托伞结构的浮标受流速的影响要大一些。同时,温差ΔT受水汽的影响,随着水汽的增加而减小,且这种影响在冬季更大一些。进一步对4个穿极和绕极浮标的追踪分析表明,温差ΔT受大洋海流系统的影响显著。在海流大的大西洋边界流和南极绕极流中,温差ΔT的不确定性要明显大于总体情况。 相似文献
3.
对上层海洋次中尺度过程研究至关重要的卫星海表温度(Sea Surface Temperature, SST)场的空间精细度一直未受到足够重视。由于卫星SST产品反演噪声的影响和实测数据的缺乏等原因,目前对卫星SST场空间精细度的研究受到较大限制。本研究开发了一套估算卫星SST场空间精细度的方法,将Suomi National Polar-orbiting Partnership卫星Visible Infrared Imager Radiometer Suite(Suomi-NPP/VIIRS)和NOAA-15卫星Advanced Very High Resolution Radiometer(NOAA-15/AVHRR)Level-2 SST场的空间能量谱与长时间在同一航线反复观测的高空间分辨率实测海温数据的空间能量谱进行了比较。研究发现VIIRS SST场夜间沿扫描方向在1.5～50 km尺度对海表温度空间能量的分布特征和变化趋势描述准确,日变化导致VIIRS白天场次中尺度空间谱能量相对夜晚有所增加。AVHRR SST场空间谱能量在次中尺度相比VIIRS有较大升高。 相似文献
4.
白天,太阳辐射将海面上层加热,会出现海表温度日变化的情况,该变化对海气热交换以及海洋生态等的研究具有重要意义,且在不同海域有着不尽相同的变化规律。文章首先介绍了海表温度日变化经验和数值模型,然后在西北太平洋海域范围内,利用美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration,NOAA)的改进型甚高分辨率辐射计(Advanced Very High Resolution Radiometer,AVHRR)海表温度数据、美国宇航局"水"卫星Aqua上先进微波扫描辐射计(Advanced Microwave Scanning Radiometer for EOS,AMSR-E)的海面风速和经计算得到的太阳辐射强度数据,通过对已有经验模型系数进行重新回归拟合,得到在该海域NOAAAVHRR海表温度数据日变化的经验模型。验证结果显示,重新回归系数后的模型在西北太平洋海域内计算所得的海表温度日变化大小与AVHRR数据本身计算所得结果相比,其平均偏差为0.01℃,标准偏差为0.22℃,可以在该海域内较好地对NOAAAVHRR海表温度数据进行日变化校正。 相似文献
5.
使用Advanced Microwave Scanning Radiometer for EOS(AMSR-E)的海洋产品数据海表温度、风速,大气水蒸气、云液态水,通过遗传算法建立其与近海面气温和比湿之间的经验关系,进行近海面气温和比湿的实时反演.反演结果与The Tropical Ocean-Atmosphere(TAO)和The National Data Buoy Center(NDBC)的浮标实测资料进行比较,实时近海面气温和比湿的均方根误差分别为1.18℃和1.36 g/kg.分析结果表明,利用遗传算法采用AMSR-E海洋产品数据可以较好地反演近海面气温和比湿. 相似文献
6.
以2015—2016年白天和夜间的VIIRS,MODIS-Terra和MODIS-Aqua三个红外SST产品为研究对象,探讨了3个红外SST的全球覆盖情况,包括统计全年有效观测天数和每日全球海洋覆盖率,将3个红外SST与Argo浮标在全球范围以及大西洋、印度洋、太平洋进行匹配统计分析,同时对匹配点平均偏差与标准偏差随纬度的变化进行研究,最后将3个红外SST进行交叉比对。结果表明:VIIRS在白天和夜间全年观测到的最大有效观测天数高于MODIS-Terra和MODIS-Aqua,该数据白天观测到的范围最大、全球海洋覆盖率也最高,夜间3个红外SST观测范围和覆盖率差别不大;VIIRS SST产品在全球以及3个大洋统计中数据质量较MODIS-Terra和MODIS-Aqua更接近Argo浮标;3个数据白天的SST平均偏差和标准差随纬度变化除了南北高纬度地区,整体浮动相差不大,VIIRS整体偏差在0℃附近,MODIS-Aqua次之,MODIS-Terra大部分都在0℃以下。夜间偏差与标准差随纬度变化平缓,在南北半球高纬度地区波动也小于白天。VIIRS白天和夜间SST值都高于其他2个红外SST。白天,VIIRS与MODIS-Aqua的温度值接近;夜间,则与MODIS-Terra的温度值接近。 相似文献
7.
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
8.
利用卫星资料分析黄海海表温度的年际与年代际变化 总被引：1，自引：0，他引：1
海表温度长期变化在一定程度上反映了海域的气候变化信号,卫星遥感资料是获取高时空分辨率水温长期变化的有效手段。基于国家海洋局1982—1999年黄海断面监测器测数据的2 954组水温数据对时空匹配的卫星(NOAA/AVHRR)反演海表温度(SST)进行校验,计算得到卫星反演SST系统偏差为(0.18±1.00)℃。卫星反演的水温空间分布以及长期变化趋势与器测趋势较为一致,可以用来研究海域SST长期变化规律。利用校验后1982-01～2011-08NOAA/AVHRR的SST数据,分析了该时段黄海冬夏季代表月2、8月海表水温的变化规律。结果显示:(1)近30a,黄海冬季水温有2次跃迁:1989—1990年由冷至暖的状态跃迁,2000-2001年出现由暖至冷的状态转变;1990年代冬季水温达最高,相比1880年代,水温升高1.07℃,新世纪水温稍有降低,水温较1990年代下降了0.53℃,温度变化较大区域位于北黄海、山东半岛沿岸,苏北浅滩毗邻海区,该区SST与局地经向风场存在显著正相关,且北极涛动通过影响冬季风间接影响黄海水温变化;(2)夏季海表水温在1994—1995年呈现由冷至暖的状态跃迁,冷、暖期水温相差0.57℃,水温变化较显著的区域为黄东海分界处,其具体变化机制需深入研究。 相似文献
9.
利用中等复杂程度全球热带大气和热带海洋模式的数值试验,模拟分析了热带太平洋和热带印度洋通过风应力桥梁的相互作用过程.利用NCEP再分析的1958～1998年SST强迫大气模式得到的风应力与NCEP再分析的同期热通量共同驱动海洋模式,作为控制试验;和控制试验平行,但强迫大气模式的SST在某一海盆取为多年气候平均值的试验作为敏感性试验.比较控制试验与敏感性试验模拟的SST变率,揭示了热带某海盆SST异常通过风应力桥梁作用对其他海盆SST的影响及其过程.数值试验结果表明:热带某海盆SST暖(冷)异常一般总是引起该海盆上空西部西(东)风异常和东部东(西)风异常;热带太平洋SST暖(冷)异常导致年际尺度上印度洋上空东(西)风异常和年代际尺度上热带印度洋风场辐散(合),该风应力导致热带印度洋年际SST暖(冷)异常以及年代际SST冷(暖)异常,但这种异常均较弱;热带印度洋SST暖(冷)异常导致热带太平洋上空东(西)风异常,该风应力异常在年际和年代际尺度上均导致热带太平洋SST冷(暖)异常,但年代际尺度上异常更明显.考虑到热带印度洋SSTA受热带太平洋SSTA影响大,并且热带太平洋SST暖(冷)异常主要通过表面热通量导致热带印度洋SST变暖(冷)的观测事实,文中揭示的热带印度洋SST暖(冷)异常通过风应力桥梁作用导致热带太平洋SST冷(暖)异常的结果表明,热带印度洋SSTA对于热带太平洋SSTA主要起着一种负反馈作用,并且这种负反馈作用在年代际尺度上更为明显. 相似文献
10.
南半球微波遥感SST与Argo浮标NST的异同分析 总被引：2，自引：0，他引：2
利用Argo剖面浮标观测得到的近表层温度数据(NST),与两种卫星微波传感器(TMI和AMSRE)反演的海表温度(SST)进行较为系统的对比分析。结果表明,在南半球海域SST与NST虽存在显著的线性关系,但两者之间的差异(△T)还是十分明显的。无论是TMI还是AMSR-E反演的SST,与Argo NST相比,△T均存在昼夜和季节变化:△T夜间较白天大,冬季达到最大,而春季则是最小。此外,△T还表现出沿纬线呈带状分布的特征。进一步研究表明,造成南半球海域SST与NST的差异主要由风速所致,且与海面流速和大气水汽含量也有一定的关系。为此,建议改进卫星遥感SST反演方法,缩小其与实测NST之间的差异,从而为南半球乃至全球海域多源SST融合提供更加可靠的统计学依据。 相似文献
11.
Eun Jin Kim Sok Kuh Kang Sung-Tae Jang Jae Hak Lee Young Ho Kim Hyoun-Woo Kang Yeong Yeon Kwon Young Ho Seung 《Ocean Science Journal》2010,45(3):159-170
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
12.
Merging satellite infrared and microwave SSTs: Methodology and evaluation of the new SST 总被引：3，自引：0，他引：3
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
13.
To investigate the feasibility and methodology of new generation sea surface temperature (SST) maps that combine various satellite
measurements, we have quantitatively evaluated SST availabilities of NOAA AVHRR (National Oceanic and Atmospheric Administration,
Advanced Very High Resolution Radiometer), GMS S-VISSR (Geostationary Meteorological Satellite, Stretched-Visible Infrared
Spin Scan Radiometer) and TRMM MI (Tropical Rainfall Measuring Mission, Microwave Imager: TMI), during the one-year period
from October 1999 to September 2000. The advantage of satellite microwave SST measurements is the ability to penetrate the
clouds that contaminate satellite infrared measurements. Daily SST availabilities were calculated in the overlapping coverage
from 20°N to 38°N and 120°E to 160°E. The annual-mean SST availabilities of AVHRR, S-VISSR and TMI are 48%, 56% and 78%, respectively.
There are large seasonal variations in the availabilities of infrared measurements. The latitude-time plots of one-degree
zonal mean SST availabilities of S-VISSR and TMI in the region from 38°S to 38°N and 80°E to 160°W show significant zonal
variations, which are influenced by the atmospheric circulation such as the Subtropical High and the Intertropical Convergence
Zone. The SST availabilities of S-VISSR and TMI in the five selected regions have large regional variations, ranging from
35% to 74% and 62% to 88% for S-VISSR and TMI, respectively. The present statistical analyses of SST availabilities in the
infrared and microwave measurements indicate that 1) a daily cloud-free high-spatial resolution may be achieved by merging
various SST measurements since their deficiencies compensate each other, and 2) nevertheless, it is necessary to take account
of the seasonal and regional variations of SST availabilities of different satellite sensors for the development of merging
technology.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
14.
Kohtaro Hosoda Hiroshi Murakami Akira Shibata Futoki Sakaida Hiroshi Kawamura 《Journal of Oceanography》2006,62(3):339-350
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
15.
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
16.
Akira Shibata 《Journal of Oceanography》2007,63(5):863-872
The effect of air-sea temperature differences on the ocean microwave brightness temperature (Tb) was investigated using the
Advanced Microwave Scanning Radiometer (AMSR) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) during a period
of seven months. AMSR Tb in the global ocean was combined with wind data supplied by the scatterometer SeaWinds aboard ADEOS-II
and air temperature given by a weather forecast model. Tb was negatively correlated with air-sea temperature difference, its
ratio lying around −0.4K/°C at the SeaWinds wind speed of 14 m/s for the 6 GHz vertical polarization. Tb of AMSR-E aboard
AQUA during 3.5 years was combined with ocean buoy data, and similar results were obtained. 相似文献
17.
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
18.
Akira Shibata 《Journal of Oceanography》2006,62(3):321-330
Ocean microwave emissions changed by the ocean wind at 6 GHz were investigated by combining data of the Advanced Microwave
Scanning Radiometer (AMSR) and SeaWinds, both aboard the Advanced Earth Observation Satellite-II (ADEOS-II). This study was
undertaken to improve the accuracy of the sea surface temperature (SST) retrieved from the AMSR 6 GHz data. Two quantities,
6V*(H*), were defined by the brightness temperature of the AMSR at 6 GHz with two polarizations (V-pol and H-pol), adjusted
for atmospheric effects and with a calm ocean surface emission removed. These quantities represent a microwave emission change
due to the ocean wind at 6 GHz. 6V* does not change in a region where 6H* is less than around 4 K (referred to as z0). Both
6V* and 6H* increase above z0. The 6V* to 6H* ratio, sp, varies with the relative wind directions. Furthermore, the sp values
vary with the SST, between the northern and southern hemisphere, and seasonally. By specifying appropriate values for z0 and
sp, the SST error between AMSR and buoy measurement became flat against 6H*, which is related to the ocean wind. Two extreme
cases were observed: the Arabian Sea in summer and the Northwestern Atlantic Ocean in winter. The air-sea temperature difference
in the former case was largely positive, while it was largely negative in the latter. The 6V* and 6H* relations differed from
global conditions in both cases, which resulted in incorrect SSTs in both areas when global coefficients were applied. 相似文献