RUSSIAN JOURNAL OF EARTH SCIENCES VOL. 9, ES3003, doi:10.2205/2007ES000283, 2007

2. Data and Methodology

[7]  Analysis of interannual trends of SST was based on weekly mean MCSST (AVHRR, 1998; http://podaac.jpl.nasa.gov:2031/DATASET_DOCS/avhrr_wkly_mcsst.html) data with spatial and temporal resolution of 1/6o and one week. The SST data were derived from the AVHRR (Advanced Very High Resolution Radiometers) mounted on the NOAA satellites. These data are produced in the Physical Oceanography Distributed Active Archive Center of Jet Propulsion Laboratory since 1981 with the temperature resolution of about 0.3oC [McClain et al., 1985].

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Figure 1
[8]  Monthly SST fields were constructed with spatial resolution of 0.5o. Then we analyzed the SST temporal variations in each point of the grid and each meridional section (Figure 1). To take into consideration the influence of the Antarctic Circumpolar Wave (ACW) on the interannual SST trends, spectral density was calculated in each point of the grid. Period of ACW is estimated as of 3 to 6 years [White and Peterson, 1996]. For the period between 1982 and 2005 the results show that maximum value of the SST spectral density pertains to the annual signal.

[9]  Analysis of interannual trends of SLA was based on the merged sea level anomaly products (data of ERS-2, TOPEX/Poseidon, Jason-1, ENVISAT, GFO-1 missions) of the Collecte Localisation Satellites CNES as part of the Environment and Climate European Commission Projects (ENACT - EVK2-CT2001-00117, AGORA - ENV4-CT956-0113 and DUACS - ENV44-T96-0357) [Le Traon et al., 1998, 2001]; (AVISO, 2002: SSALTO/DUACS User Handbook. CLS. AVI-NT-011-312-CN).

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Figure 2
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Figure 3
[10]  This altimetry data have spatial and temporal resolution of 0.33o on Mercator projection and one week with the sea surface height resolution of about 4.2 cm [Chelton et al., 2001; Fu and Pihos, 1994]. Monthly SLA fields were constructed with spatial resolution of 0.5o. Then we analyzed the SLA temporal variations in each grid point and along each meridional section (Figure 2). We took 1993-2005 time period for the analysis. Spectral density for temporal variations was analysed in each grid point and along each meridional section. Results show that maximum value of integrated spectral density pertains to the position of the Antarctic Circumpolar Current (Figure 2).

[11]  Interannual or climatic trends of SST and SLA were calculated as linear regression for each grid point with spatial resolution of 0.5o. Results of these computations are shown in Figure 3.


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Citation: Lebedev, S. A. (2007), Interannual trends in the Southern Ocean sea surface temperature and sea level from remote sensing data, Russ. J. Earth Sci., 9, ES3003, doi:10.2205/2007ES000283.

Copyright 2007 by the Russian Journal of Earth Sciences

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