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Global Dynamics of Sea Surface Temperature Utilizing Satellite Measurements (2002-2011)

This study investigates the global dynamics of sea surface temperature (SST) between 2002 and 2011 using 108 MODIS satellite images and 300 AVHRR images. It presents a model to represent SST as a combination of a mean value, natural variability, and additional climatic variables. The analysis identifies positive and negative anomalies, indicating global long-term changes in SST. The findings reveal that significant positive anomalies occur synchronously across various oceans, while negative anomalies tend to be asynchronous. SST variability is notably higher in the Atlantic and Indian Oceans compared to the Pacific.

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Global Dynamics of Sea Surface Temperature Utilizing Satellite Measurements (2002-2011)

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  1. Dynamics of the sea surface temperature on a global scale using satellite measurementsG. Vysotskaya (1,2), A. Shevyrnogov (1,3) (1) Institute of Biophysics of SB RAS, Krasnoyarsk, Russia, (2) Institute of Computational Modelling of SB RAS, Krasnoyarsk, Russia(3) Siberian Federal University, Krasnoyarsk, Russia

  2. 108 satellite MODISimages (2160 x 4320) – 7.2002-7.2011 and 300AVHRRimages (4096 x 8192) - 1985 - 2009 were used in this investigation. Sea surface temperature may be represented as a sum: Ci,j(t) = Fi,j(  (t)) +ξi,j( (t))+Ui,j (t),where Fi,j(m) is amean for (i,j);  (t) is a number of a month for time t; ξi,j(m) is a random variable, that describe natural variability of the ocean. It depends on (i,j) and a month. Ui,j(t) is a some additional variable, that can be defined by climatic changes, human impact etc.

  3. Norm data Ei,j,m is a mean value for a point (i,j) and a month m Di,j,m is a variance for a point(i,j) and a month m. Define positive anomaly values as the upper 20% (p0.8)and negative anomaly as the lower 20% (p0.2)

  4. Square of negative and positive anomalies by AVHRR data (60°N- 60°S)

  5. Square of negative and positive anomalies by MODIS data (60°N- 60°S)

  6. Square of positive anomalies by AVHRR data (30°N- 30°S)

  7. Square of negative anomalies by AVHRR data (30°N- 30°S)

  8. Square of negative and positive anomalies by AVHRR data (30°N- 30°S)

  9. Conclusions • Long-term changes of sea surface temperature are global. • The largest positive anomalies appear almost synchronously in the different oceans. • The largest negative anomalies usually are not synchronous in the different oceans • Variability of SST in the Atlantic and Indian oceans is higher than in the Pacific ocean.

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