地球科学进展 ›› 2015, Vol. 30 ›› Issue (10): 1127 -1143. doi: 10. 11867/ j. issn. 1001-8166. 2015. 10. 1127

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中国风云卫星与海洋卫星近海SST资料融合技术及应用研究
苗春生 1( ), 程远 1, 2, 王坚红 1, 王兴 1   
  1. 1.南京信息工程大学,气象灾害预报预警与评估协同创新中心/气象灾害教育部重点实验室,江苏 南京 210044
    2. 扬州市气象局,江苏 扬州,225009
  • 收稿日期:2015-06-30 修回日期:2015-07-20 出版日期:2015-10-20
  • 基金资助:
    国家自然科学基金面上项目“海洋中尺度涡旋动力结构与维持机制研究”(编号:41276033);国家科技支撑计划项目“气象影视图形图像制作播出技术研究与应用”(编号:2012BAH05B01)资助

Data Fusion of Offshore SST from China FY and HY2 Satellites and Its Application

chunsheng Miao 1( ), yuan Cheng 1, 2, jianhong Wang 1, Xin Wang 1   

  1. 1.NUIST,Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disasterof Ministry of Education,Nanjing, 210044,China
    2 Yangzhou Meteorological Beaure,Yangzhou,Jiangsu,225009 China
  • Received:2015-06-30 Revised:2015-07-20 Online:2015-10-20 Published:2015-10-20
  • Supported by:
    Foundation item: Project supported by the National Natural Science Foundation of China “The dynamic structures and maintaining mechanisms of oceanic meso-scale eddies” (No.41276033);National Key Technology Research and Development Program of the Ministry of Science and Technology of China “Technique research and application on image and figure production and presentation of meteorological film & television” (No.2012BAH05B01)

选用美国LAPS(Local Analysis and Prediction System)数据融合系统对中国风云(FY)和海洋(HY)卫星在我国东部海域SST反演数据进行融合处理。该融合系统能够协调区域大气和下垫面海洋要素的时空特征,协调不同要素间的特征状态及匹配规律,生成适合多要素诊断计算的区域规范化数据。针对该系统没有现成的卫星SST反演数据输入接口,对船舶站SST反演数据接口进行了数值调整;依据FY卫星及HY卫星SST数据的不同特点,尤其是随卫星轨道发生的不同时空变化,在输入卫星反演数据至LAPS系统之前, 进行了多项预处理,包括对卫星反演数据异常值的判别与剔除、海陆边界要素异常梯度的鉴别与去除、不同卫星轨道坐标系网格要素的规范化处理、平滑去噪音等。经多项验证,预处理后的FY和HY卫星监测反演数据更有利于LAPS系统资料融合效果的正确性与合理性。再经LAPS系统的数据融合处理和各项验证,融合场既能保持卫星SST精细化的时空特征描述,也弥补了卫星资料非区域全覆盖的局限。将SST融合场对寒潮与冷空气过程中的东部海域海气影响进行热动力物理量时空变化诊断应用,对海面SST和感热通量的中尺度强度演变、南北空间变化差异均给出了量化描述。

Data fusion of SST from China FY and HY2 satellites was made by American LAPS(Local Analysis Prediction System). The system can ensure the spatial and temporal characteristics of different elements to fit each other in atmospheric motion,and it can provide fusion data with standard format and common corrodinate. The fusion data is suitable to join the quantitative diagnosetic analysis of variables. As the LAPS system has no a special input channel for satellite SST data, the numerical adjustment was done for data input of marine station. According to the different sensing principles of FY and HY2 satellites, and the characteristics of random spatiotemporal variation of satellite SST data, the inversion data of satellites were preprocessed by several steps, including outliers discrimination and elimination, the anomaly gradient discrimination and elimination, the numerical treatment of different satellite scanning grids, and data smoothing, etc. After the testing of different methods, it was verified that through preprocessing, the fusion effect of FY and HY2 satellites SST data was more reasonable and correct. Based on LAPS SST fusion and further statistical tests, it was confirmed that the SST fusion fields could keep the detail description of spatiotemporal features of SST distribution, and also resolved the problem of satillite SST with blank patches along the coastal zones. Furthermore, the SST fusion fields were applied to the diagnostic analysis of themodynamics spatiotemporal variance in air-sea synoptic process in cold waves and cold air invasion to Yellow sea and East China Sea. The results showed that the SST fusion could provide quantitative information and description for meso-scale strength variance, north-south varing difference of SST distribution and sensible heat flux in China offshore regions.

中图分类号: 

表1 2012年2月OISST与2月气候态海温统计结果
Table 1 Statistical result of OISST and climatology SST in February 2012
图1 2012年2月FY2E SST与气候态平均海温值的比对散点图 (a)质量控制前;(b)质量控制后; 图1 b中的虚线为σ阈值线
Fig.1 Scatter diagram of FY2E SST and climatology SST in February 2012 (a)Before quality control;(b)after quality control;dotter lines in Fig.1 b mean threshold σ
图2 HY2数据质量控制 (1)原始HY2数据;(b)HY2格点分布;(c)梯度处理后HY2数据
Fig.2 Quality control of HY-2 data (a)HY2 raw data; (b)Distribution of HY2 grids;(c)HY2 data afterelimitionofstrong gradient
图3 卫星及LAPS坐标网格对比 (a)FY2E数据稀疏化网格;(b)FY3C数据稀疏化网格;(c)HY2数据稀疏化网格;(d)LAPS 网格
Fig.3 Grids of Satellites and LAPS (a)Grid of FY2E data;(b)Grid of FY3C data;(c)Grid of HY2 data;(d)Grid of LAPS data
图4 10个时次海温场交叉验证散点图 (a)~(e)为FY3C卫星;(f)~(j)为HY2卫星
Fig.4 Scatter plots of LAPS SST and satellite sample SST (a)~(e)FY3C Satellite;(f)~(j)HY2 Satellite
图5 LAPS系统所用原始海温场资料 (a)背景场;(b)HY2海温场;(c)FY2E海温场
Fig.5 Raw SST data for LAPS System (a)background SST;(b)HY2 SST;(c)FY2E SST
图6 2012年2月27日(UTC)23:00我国东部海域LAPS融合海温结果 (a)背景场的分析;(b)HY2的分析;(c)背景场与HY2的分析;(d)背景场与FY2E的分析;(e)HY2与FY2E的分析;(f)背景场和HY2及FY2E的分析
Fig.6 LAPS fusion SST of China eastern sea area at 2300 UTC 27 February 2012 (a)Analysis of background;(b)Analysis of HY2;(c)Analysis of background and HY2;(d)Analysis of background and FY2E;(e)Analysis of HY2 and FY2E;(f)Analysis of background and HY2 and FY2E
图7 LAPS分析与浮标船舶资料的比对散点图(a至f同 图6
Fig.7 Scatter diagram of LAPS fusion SST and field SST(a-f same as fig.6)
图8 LAPS分析与OISST的比对散点图(a至f同 图6
Fig.8 Scatter diagram of LAPS fusion SST and OISST (a-f same as fig.6)
图9 寒潮过程12小时变温/℃ (a)27日08:00~20:00;(b)27日20:00至28日08:00;(c)28日08:00~20:00;(d)28日20:00至29日08:00;(e)29日08:00~20:00;(f)29日20:00至30日08:00
Fig.9 12hours of temperature variation during cold wave (a)08:00~20:00 27 December;(b)20:00 27~08:00 28 December;(c)08:00~20:00 28 December; (d)20:00 28~08:00 29 December;(e)08:00~20:00 29 December;(f)20:00 29~08:00 30 December
图10 海洋卫星HY2 的SST场 (a)12月29日07:00;(b)12月30日07:00;(c)12月31日07:00
Fig.10 The SST fields of HY2 (a)07:00 29 December;(b)07:00 30 December;(c)07:00 31 December
图11 12月31日背景场SST与融合卫星数据SST场比较 (a)背景场;(b)融合场
Fig.11 Comparison of background SST and fusion SST at 31 December (a)Background SST;(b)Fusion SST
图12 黄东海海域24小时融合SST变化/℃ (a)12月29日07:00至30日07:00;(b)12月30日 07:00至31日07:00
Fig.12 24 hours of fusion SST variation at Yellow and East Sea/℃ (a)07:00 29 December to 07:00 30 December;(b)07:00 30 December to 07:00 31 December
图13 海气温差/℃ (a)12月29日07:00;(b)12月30日07:00
Fig.13 Sea-air temperature difference/℃ (a)07:00 29 December;(b)07:00 30 December
图14 黄东海海域感热通量对比(W/m 2((a)~(b)为12月30日07:00与31日07:00 LAPS 卫星融合再分析资料;(c)~(d)为12月30日08:00与31日08:00 FNL再分析资料
Fig.14 Comparison of ocean-atmosphere sensible heat flux in yellow and east sea (a)~(b)LAPS fusion analysis data at 07:00 30 December and 07:00 31 December;(c)~(d)FNL analysis data at 08:00 30 December and 08:00 31 December
图15 FY3C与背景场融合海温 (a)10月12日10:00;(b)10月13日10:00;(c)10月14日22:00
Fig.15 Fusion SST of FY3C SST and Background SST (a)10:00 12 October;(b)10:00 13 October;(c)22:00 14 October
图16 黄东海域LAPS 风云卫星融合再分析资料海气感热通量 (a)10月12日10:00;(b)10月13日10:00;(c)10月14日22:00
Fig.16 Ocean-atmosphere sensible heat flux of LAPS analysis data in yellow and east sea (a)10:00 12 October;(b)10:00 13 October;(c)22:00 14 October
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