DINEOF reconstruction for creating long-term cloud-free sea surface temperature data records: A Case study in Lombok Strait, Indonesia

Abstract

Abstract A long-term reliable sea surface temperature (SST) satellite data record is requisite resources for monitoring to understand climate variability. Creating a long-term data record especially for climate variability requires a combination of multiple satellite products. Consequently, missing data issues are inevitable. Hence, DINEOF (Data Interpolating Empirical Orthogonal Functions) has been applied to attain a complete and coherent multi-sensor SST data record with EOF-based technique by reconstructing the missing data. Unfortunately, the technique can lead to large discontinuities in the data reconstruction due to images depiction within long time series data. For that reason, filtering the temporal covariance matrix had been applied to reduce the spurious variability and more realistic reconstructions are obtained. However, this approach has not yet tested in tropical region with higher evaporation which cause incomplete satellite image coverage. Therefore, the objective of this research is to reconstruct SST of Lombok strait with data gaps up to 58.16% in one year. It is successfully reconstructed until the last iteration of 42 optimal EOF modes with the convergence achieved up to 0.9806×10-3, including previous set-aside data for internal cross-validation. The results highlight that the DINEOF method can effectively reconstruct SST data in Lombok Strait.