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1.
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
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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
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中国沿海海表温度均一性检验和订正 总被引：4，自引：1，他引：3
利用惩罚最大T检验（Penalized Maximal T test，PMT）方法，选取均一的邻近气象站为参考站，基于月平均地面气温（SAT）资料，利用相关系数权重平均方法构建参考序列，同时结合元数据信息，对1960-2011年中国沿海27个海洋观测站月平均海表温度（SST）进行了均一性检验与订正，并分析了造成海表温度序列非均一的主要原因。结果表明，中国沿海海洋台站海表温度资料存在较为严重的非均一性问题，几乎所有的台站都存在断点，仪器变更（包括人工观测转自动观测）（占总断点数的52.4%）和迁站（占总断点数的33.3%）是造成序列非均一的主要原因。整套资料负订正量所占比例较高，这种负订正量与人工转自动观测后海表温度观测值偏低有密切关系。这也使得订正后中国沿海平均海表温度趋势与订正前存在明显差异，订正后中国沿海海表温度呈明显的加速上升趋势。 相似文献
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本文采用波浪订正的Ekman模型,研究分析了三种Stokes漂流近似公式(单波公式、e指数公式、Phillips谱近似公式)对海洋表层流场估算的影响。海表总流场由海表面高度(SSH)数据计算的地转流和海浪模式WAVEWATCH Ⅲ输出结果计算的非地转流组成,并采用拉格朗日浮标观测数据对计算结果进行了验证。研究表明,随着Stokes漂流近似公式精度的提高,其计算的拉格朗日流速更接近于谱积分公式的计算结果,更贴近拉格朗日浮标观测数据。与谱积分公式计算的海表拉格朗日流速相比,单波公式的平均相对偏差为0.0834,e指数公式的平均相对偏差为0.0392,Phillips谱近似公式的平均相对偏差为0.0101,说明Phillips谱近似公式在不同风速下均能对谱积分公式有良好的近似效果。在低风速条件下,由Stokes漂流近似公式精度引起的海洋表层流场估算误差可以忽略不计,但随着风速增加,由近似公式精度引起的偏差逐渐变大,此时应该选择Phillips谱近似公式计算Stokes漂流,来减小误差。 相似文献
6.
于2014年的5月(春季)和9月(秋季)在台湾海峡及其邻近南海和东海海域,采用水气平衡法进行了2个航次的海表和大气pCO_2连续走航观测,同时获取了海表温度、海表盐度、风速及气压等数据,并采用海-气CO_2分压差减法估算了海-气CO_2通量.结果显示,春、秋2个航次平均海表pCO_2分别为387±16μatm和408±18μatm.温度是影响台湾海峡及其邻近海域海表pCO_2的主控因子,水团混合和其他因素等也对海表pCO_2有一定影响.2014年春、秋季节,对研究区域的海-气CO_2释放通量的估算结果分别为0.11±1.60 mmol/(m2·d)和2.51±1.10 mmol/(m2·d).台湾海峡海表pCO_2既存在显著的季节变化,又存在较大的空间差异. 相似文献
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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
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《海洋技术学报》2017,(6)
星载海洋盐度计依据海表面盐度在微波波段的辐射特性,通过构建海面微波辐射探测器,利用海面辐射亮温、海表面粗糙度以及海面温度等信息反演得到海表面盐度,是实现全球海洋盐度观测的有效手段。构建合理的星载L波段盐度计辐射传输正演模型是准确定量反演海表盐度的基础,卫星盐度计观测亮温不仅与卫星固有参数有关,还与海洋、大气及空间因素密切相关。为了研究外界环境因素(海表盐度、温度、海面风场、海面气压、海表气温、大气水汽含量、降雨以及法拉第旋转角等)对盐度计观测亮温的影响,文中基于L波段盐度计辐射传输正演模型以及MPM93大气毫米波传播模型,通过敏感性分析,研究星载盐度计在不同环境条件下的参数敏感性,为减小外界因素对海表盐度反演精度的不利影响提供理论依据。 相似文献
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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
12.
本文基于环境场较为稳定的南太平洋目标海区,以海洋大气微波辐射传输模型(Radiative Transfer Model,RTM)模拟亮温作为参考值,对2015年1月1日—2017年12月31日的高级扫描微波辐射计(Advanced Microwave Scanning Radiometer 2,AMSR2) L1R亮温数据产品进行了质量评估。结果表明AMSR2 L1R所有通道亮温数据总偏差和标准偏差的变化范围分别为1.466～6.352 K、0.270～1.693 K,其中标准偏差在水平极化通道较大的同时随着频率的增大而增大。相比同类遥感器如全球降水测量微波成像仪(Global Precipitation Measurement Microwave Imager,GMI)等的质量分析结果,AMSR2亮温数据的标准偏差较小,这表明AMSR2亮温数据精度较高。对AMSR2 L1R亮温数据3年长时间序列的变化趋势分析表明所有通道亮温偏差均在±0.5 K范围内波动但是存在微弱的季节性变化,标准偏差随时间的变化较小,这表明AMSR2 L1R亮温数据质量较为稳定。 相似文献
13.
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
14.
新一代静止气象卫星葵花8号的晴空红外辐射率资料同化对台风“天鸽”的预报影响研究 总被引：1，自引：0，他引：1
本文以2017年第13号台风“天鸽”（Hato）为例,在WRFDA同化系统中结合日本葵花8号（Himawari-8）资料,通过同化Himawari-8晴空红外辐射率资料并进一步考察其对台风“天鸽”的结构、强度、路径分析和预报的影响。研究结果表明:同化Himawari-8晴空红外辐射率资料对台风背景场的水汽相关变量分析有显著改进,对背景场中的台风水汽信息有一定的改进作用。与控制实验,即没有同化Himawari-8晴空红外辐射率资料的实验相比,加入同化实验对台风“天鸽”的风场、500 hPa气压场的分析效果有所提高,台风气旋性环流加强,并进一步改进了对台风“天鸽”的路径、台风中心最低气压和近中心最大风速的预报。平均路径误差和降水预报相对于常规观测变量的均方根误差均有所改善。 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.
Hiroshi Kawamura Huiling Qin Futoki Sakaida Riza Yuliratno Setiawan 《Journal of Oceanography》2010,66(1):61-70
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
17.
热带印度洋SST的日变化幅度受到大气季节内振荡(Madden-Julian Oscillation,MJO)的调制,其在MJO对流最强(弱)位相达到极小(大)值,并且在MJO对流增强位相显著强于其对流减弱位相。本文利用逐时的再分析海表通量强迫一维海洋混合层模式,定量地诊断了MJO事件中SST日变化的差异成因。结果表明,SST日变化在MJO对流最强与最弱位相的显著差异主要是由短波辐射的季节内变化所致(40%),其次是风应力(38%)和潜热通量(14%),其他要素的影响较小。而SST日变化在MJO对流增强与减弱位相所呈现的不对称特征,主要是由纬向风应力的不对称性所致,这是MJO扰动结构与背景环流相互作用的结果。 相似文献
18.
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
19.
Sea surface temperature(SST) data obtained from coastal stations in Jiangsu, China during 2010–2014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles, including the correlation with the variation of the tide. Quality control of data includes the validation of extreme values and checking of hourly values based on temporally adjacent data points, with 0.15°C/h considered a suitable threshold for detecting abnormal values. The diurnal variation amplitude of the SST data is greater in spring and summer than in autumn and winter. The diurnal variation of SST has bimodal structure on most days, i.e., SST has a significant semidiurnal cycle. Moreover, the semidiurnal cycle of SST is negatively correlated with the tidal data from March to August, but positively correlated with the tidal data from October to January. Little correlation is detected in the remaining months because of the weak coastal–offshore SST gradients. The quality control and understanding of coastal SST data are particularly relevant with regard to the validation of indirect measurements such as satellitederived data. 相似文献
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Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite 总被引：4，自引：3，他引：1
ZHAO Yili ZHU Jianhu LIN Mingsen CHEN Chuntao HUANG Xiaoqi WANG He ZHANG Youguang PENG Hailong 《海洋学报(英文版)》2014,33(1):109-113
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