High and Ultra-High resolution processing of satellite Sea Surface Temperature data over Southern European Seas in the framework of MyOcean project

被引:174
|
作者
Buongiorno Nardelli, B. [1 ,2 ]
Tronconi, C. [1 ]
Pisano, A. [1 ]
Santoleri, R. [1 ]
机构
[1] CNR, Ist Sci Atmosfera & Clima, Grp Oceanog Satellite, I-80125 Naples, Italy
[2] CNR, Ist Ambiente Marino Costiero, I-80125 Naples, Italy
关键词
Sea Surface Temperature; Operational oceanography; Optimal interpolation; OBJECTIVE ANALYSIS; IN-SITU; VALIDATION; ALGORITHM;
D O I
10.1016/j.rse.2012.10.012
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the framework of the GMES (Global Monitoring for Environment and Security) My Ocean projects, funded by the European Commission, different remotely-sensed Sea Surface Temperature (SST) supercollated (L3S) and interpolated (L4) data are produced and distributed in near-real time by the Consiglio Nazionale delle Ricerche - Istituto di Scienze dell'Atmosfera e del Clima - Gruppo di Oceanografia da Satellite (CNR). These SST products are based on the night-time images collected by the infrared sensors mounted on different satellite platforms and cover the whole Southern European Seas (i.e. the Mediterranean Sea, including the eastern Atlantic Ocean, and the Black Sea). The CNR processing chains include several modules, from the data extraction and preliminary quality control, to cloudy pixel removal and satellite images collating/merging up to US. A two-step algorithm finally allows to interpolate SST data at High (HR 1/16 degrees) and Ultra-High (UHR 1/100 degrees) spatial resolution. The basic design and the main algorithms used in My Ocean processing chains are described hereafter. A validation of the HR super-collating procedure developed during MyOcean is presented. The Mediterranean HR and UHR US and L4 operational products have then been validated vs in situ SST measurements from drifting buoys, covering two years of data (2010-2011). The validation includes a comparison between the UHR CNR L4 and the G1SST 14 developed by Chao et al. (2009). (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:1 / 16
页数:16
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