Improved near real-time data management procedures for the Mediterranean ocean forecasting System-Voluntary Observing Ship program

被引:25
作者
Manzella, GMR [1 ]
Scoccimarro, E
Pinardi, N
Tonani, M
机构
[1] ENEA Progretto Speciale Clima, La Spezia, Italy
[2] Univ Bologna, Ravenna, Italy
[3] INGV, Rome, Italy
关键词
oceanography; physical; instruments and techniques; general circulation; hydrography;
D O I
10.5194/angeo-21-49-2003
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
A "ship of opportunity" program was launched as part of the Mediterranean Forecasting System Pilot Project. During the operational period (September 1999 to May 2000), six tracks covered the Mediterranean from the northern to southern boundaries approximately every 15 days, while a long eastwest track from Haifa to Gibraltar was covered approximately every month. XBT data were collected, sub-sampled at 15 inflection points and transmitted through a satellite communication system to a regional data centre. It was found that this data transmission system has limitations in terms of quality of the temperature profiles and quantity of data successfully transmitted. At the end of the MFSPP operational period, a new strategy for data transmission and management was developed. First of all, VOS-XBT data are transmitted with full resolution. Secondly, a new data management system, called Near Real Time Quality Control for XBT (NRT.QC.XBT), was defined to produce a parallel stream of high quality XBT data for further scientific analysis. The procedure includes: (1) Position control; (2) Elimination of spikes; (3) Re-sampling at a I metre vertical interval; (4) Filtering; (5) General malfunctioning check; (6) Comparison with climatology (and distance from this in terms of standard deviations); (7) Visual check; and (8) Data consistency check. The first six steps of the new procedure are completely automated; they are also performed using a new climatology developed as part of the project. The visual checks are finally done with a free-market software that allows NRT final data assessment.
引用
收藏
页码:49 / 62
页数:14
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