MAIN VARIABILITY DETECTION OF SEA SURFACE TEMPERATURE AND CHLOROPHYLL-A USING DINEOF MULTIVARIATE AND UNIVARIATE IN THE SOUTHERN MAKASSAR STRAIT.
Indonesia, as a tropical country with quite intense atmospheric convection, makes it difficult for satellites to obtain complete information and causes data gaps due to high cloud cover. This study aims to reconstruct Sea Surface Temperature (SST) and Chlorophyll-a data using the Data Interpol...
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| Format: | Final Project |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/86223 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Indonesia, as a tropical country with quite intense atmospheric convection, makes
it difficult for satellites to obtain complete information and causes data gaps due to
high cloud cover. This study aims to reconstruct Sea Surface Temperature (SST)
and Chlorophyll-a data using the Data Interpolating Empirical Orthogonal
Functions (DINEOF) method in the southern Makassar Strait. The data used are 8-
day Level 3 MODIS Aqua SST and Chlorophyll-a data from 2003 to 2022, as well
as Level 4 GHRSST SST data in 2020 for verification. From the comparison before
and after DINEOF reconstruction on Level 4 SST, an RMSE of <0.01°C and a
correlation of >0.9 were obtained, indicating good reconstruction results. The best
method for Sea Surface Temperature is univariate DINEOF missing point only with
a correlation of 0.96 and RMSE of 0.16. For chlorophyll-a, multivariate DINEOF
missing point only is the best method with a correlation of 0.73 and RMSE of 1.71.
From the mode showing the largest variance, namely the first mode, it is obtained
that the first mode has a period of one year, which is the phenomenon of monsoon
winds, and for the second mode with the same period of one year, it is the
phenomenon of upwelling. |
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