SUN Weifu, WANG Jin, ZHANG Jie, MA Yi, MENG Junmin, YANG Lei, MIAO Junwei. A new global gridded sea surface temperature product constructed from infrared and microwave radiometer data using the optimum interpolation method[J]. Acta Oceanologica Sinica, 2018, 37(9): 41-49. doi: 10.1007/s13131-018-1206-4
Citation: SUN Weifu, WANG Jin, ZHANG Jie, MA Yi, MENG Junmin, YANG Lei, MIAO Junwei. A new global gridded sea surface temperature product constructed from infrared and microwave radiometer data using the optimum interpolation method[J]. Acta Oceanologica Sinica, 2018, 37(9): 41-49. doi: 10.1007/s13131-018-1206-4

A new global gridded sea surface temperature product constructed from infrared and microwave radiometer data using the optimum interpolation method

doi: 10.1007/s13131-018-1206-4
  • Received Date: 2017-11-02
  • A new 0.1° gridded daily sea surface temperature (SST) data product is presented covering the years 2003-2015. It is created by fusing satellite SST data retrievals from four microwave (WindSat, AMSR-E, ASMR2 and HY-2A RM) and two infrared (MODIS and AVHRR) radiometers (RMs) based on the optimum interpolation (OI) method. The effect of including HY-2A RM SST data in the fusion product is studied, and the accuracy of the new SST product is determined by various comparisons with moored and drifting buoy measurements. An evaluation using global tropical moored buoy measurements shows that the root mean square error (RMSE) of the new gridded SST product is generally less than 0.5℃. A comparison with US National Data Buoy Center meteorological and oceanographic moored buoy observations shows that the RMSE of the new product is generally less than 0.8℃. A comparison with measurements from drifting buoys shows an RMSE of 0.52-0.69℃. Furthermore, the consistency of the new gridded SST dataset and the Remote Sensing Systems microwave-infrared SST dataset is evaluated, and the result shows that no significant inconsistency exists between these two products.
  • loading
  • Barton I, Pearce A. 2006. Validation of GLI and other satellite-derived sea surface temperatures using data from the Rottnest Island ferry, Western Australia. Journal of Oceanography, 62(3):303-310
    Bourlès B, Lumpkin R, McPhaden M J, et al. 2008. THE PIRATA program:history, accomplishments, and future directions. Bulletin of the American Meteorological Society, 89(8):1111-1126
    Chao Yi, Li Zhijin, Farrara J D, et al. 2009. Blending sea surface temperatures from multiple satellites and in situ observations for coastal oceans. Journal of Atmospheric and Oceanic Technology, 26(7):1415-1426
    Guan Lei, Kawamura H. 2004. Merging satellite infrared and microwave SSTs:Methodology and evaluation of the new SST. Journal of Oceanography, 60(5):905-912
    Hosoda K, Qin Huiling. 2011. Algorithm for estimating sea surface temperatures based on Aqua/MODIS global ocean data. 1. Development and validation of the algorithm. Journal of Oceanography, 67(1):135-145
    Høyer J L, Karagali I, Dybkjær G, et al. 2012. Multi sensor validation and error characteristics of Arctic satellite sea surface temperature observations. Remote Sensing of Environment, 121:335-346
    Hu Xiaoyue, Zhang Caiyun, Shang Shaoling. 2015. Validation and inter-comparison of multi-satellite merged sea surface temperature products in the South China Sea and its adjacent waters. Journal of Remote Sensing (in Chinese), 19(2):328-338
    Jiang Xingwei, Lin Mingsen, Liu Jianqiang, et al. 2012. The HY-2 satellite and its preliminary assessment. International Journal of Digital Earth, 5(3):266-281
    Kawai Y, Wada A. 2007. Diurnal sea surface temperature variation and its impact on the atmosphere and ocean:A review. Journal of Oceanography, 63(5):721-744
    Li Aihua, Bo Yanchen, Zhu Yuxin, et al. 2013. Blending multi-resolution satellite sea surface temperature (SST) products using Bayesian maximum entropy method. Remote Sensing of Environment, 135:52-63
    Li Ming, Liu Jiping, Zhang Zhanhai, et al. 2010. Evaluation of AMSR-E SST in the Southern Ocean using drifting buoy data. Haiyang Xuebao (in Chinese), 32(6):47-55
    Martin M, Dash P, Ignatov A, et al. 2012. Group for High Resolution Sea Surface temperature (GHRSST) analysis fields inter-comparisons. Part I:A GHRSST multi-product ensemble (GMPE). Deep Sea Research Part Ⅱ:Topical Studies in Oceanography, 77-80:21-30
    McPhaden M J, Busalacchi A J, Cheney R, et al. 1998. The tropical ocean-global atmosphere observing system:A decade of progress. Journal of Geophysical Research:Oceans, 103(C7):14169-14240
    McPhaden M J, Meyers G, Ando K, et al. 2009. RAMA:The research moored array for African-Asian-Australian monsoon analysis and prediction. Bulletin of the American Meteorological Society, 90(4):459-480
    Reynolds R W, Marsico D C. 1993. An improved real-time global sea surface temperature analysis. Journal of Climate, 6(1):114-119
    Reynolds R W, Rayner N A, Smith T M, et al. 2002. An improved in situ and satellite SST analysis for climate. Journal of Climate, 15(13):1609-1625
    Reynolds R W, Smith T M. 1994. Improved global sea surface temperature analyses using optimum interpolation. Journal of Climate, 7(6):929-948
    Reynolds R W, Smith T M, Liu Chunying, et al. 2007. Daily high-resolution-blended analyses for sea surface temperature. Journal of Climate, 20(22):5473-5496
    Shaw A G P, Vennell R. 2000. A front-following algorithm for AVHRR SST imagery. Remote Sensing of Environment, 72(3):317-327
    Song Qinglei. 2011. Processing of surface temperature data in East China Sea based on Kriging interpolation and effect analysis[dissertation]. Qingdao:The First Institute of Oceanography, State Oceanic Administration
    Wang Keguang, Zhang Jianhua, Wang Caixin. 2000. Objective analysis method of conventional SST data in the Northwest Pacific Ocean:I. Analysis of ten day average ship report data. Marine Forecasts (in Chinese), 17(4):52-59
    Wang Yanzhen, Guan Lei, Qu Liqin. 2010. Merging Sea surface temperature observed by satellite infrared and microwave radiometers using Kalman Filter. Periodical of Ocean University of China (in Chinese), 40(12):126-130
    Wu Xiangqian, Menzel W P, Wade G S. 1999. Estimation of sea surface temperatures using GOES-8/9 radiance measurements. Bulletin of the American Meteorological Society, 80(6):1127-1138
    Xi Meng. 2011. Merging infrared radiometer and microwave radiometer Sea Surface Temperature data based on the optimum interpolation[dissertation]. Beijing:National Marine Environment Forecasting Center
    Xie Jiping, Zhu Jiang, Li Yan. 2008. Assessment and inter-comparison of five high-resolution sea surface temperature products in the shelf and coastal seas around China. Continental Shelf Research, 28(10):1286-1293
    Zabolotskikh E, Mitnik L, Reul N, et al. 2014. New possibilities for geophysical parameter retrievals opened by GCOM-W1 AMSR2. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(9):4248-4261
    Zhang Hui. 2006. Merging AVHRR and AMSR-E sea surface temperature data based on wavelet transform[dissertation]. Qingdao:Ocean University of China
    Zhao Yili, Zhu Jianhua, Lin Mingsen, et al. 2014. Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite. Acta Oceanologica Sinica, 33(1):109-113
    Zhu Enze, Zhang Lei, Shi Hanqing, et al. 2016. Accuracy of WindSat sea surface temperature:Comparison of buoy data from 2004 to 2013. Journal of Remote Sensing (in Chinese), 20(2):315-327
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (1318) PDF downloads(576) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return