2014Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Spatial and temporal variability of SST in the Zhejiang coastal waters during 2003-2013

Xiulin Lou, Aiqin Shi

Open publisher page 0 citations

Abstract

The spatial and temporal variability of sea surface temperature (SST) in the Zhejiang Coastal Waters of the East China Sea is investigated with long time series of cloud-gap free SST imagery. The SST dataset is reconstructed with Data INterpolating Empirical Orthogonal Function (DINEOF) method using daily MODIS Aqua SST images. An EOF analysis technique is further used to reveal the regional temporal and spatial SST variability at seasonal to inter-annual timescales. The first three EOF modes cumulatively account for more than 84% of the total SST variance. The first mode explains 71.5% of the total SST variability and it is dominated by an annual cycle. The second mode accounts for 10.3% of the SST variance and it reveals a warm/cold pattern in the coastal shelf sea. The third mode, accounting for 2.4% of the SST variance, indicates a pattern describing the synoptic-scale variability.

About this research paper

What this paper is about

The spatial and temporal variability of sea surface temperature (SST) in the Zhejiang Coastal Waters of the East China Sea is investigated with long time series of cloud-gap free SST imagery. The SST dataset is reconstructed with Data INterpolating Empirical Orthogonal Function (DINEOF) method using daily MODIS Aqua SST images. An EOF analysis technique is further used to reveal the regional temporal and spatial SST variability at seasonal to inter-annual timescales. The first three EOF modes cumulatively account for more than 84% of the total SST variance. The first mode explains 71.5% of the total SST variability and it is dominated by an annual cycle. The second mode accounts for 10.3% of the SST variance and it reveals a warm/cold pattern in the coastal shelf sea. The third mode, accounting for 2.4% of the SST variance, indicates a pattern describing the synoptic-scale variability.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The spatial and temporal variability of sea surface temperature (SST) in the Zhejiang Coastal Waters of the East China Sea is investigated with long time series of cloud-gap free SST imagery. The SST dataset is reconstructed with Data INterpolating Empirical Orthogonal Function (DINEOF) method using daily MODIS Aqua SST images. An EOF analysis technique is further used to reveal the regional temporal and spatial SST variability at seasonal to inter-annual timescales. The first three EOF modes cumulatively account for more than 84% of the total SST variance. The first mode explains 71.5% of the total SST variability and it is dominated by an annual cycle. The second mode accounts for 10.3% of the SST variance and it reveals a warm/cold pattern in the coastal shelf sea. The third mode, accounting for 2.4% of the SST variance, indicates a pattern describing the synoptic-scale variability.

Key concepts: Empirical orthogonal functions, Sea surface temperature, Climatology, Environmental science, Mode (computer interface), Temporal scales, Spatial variability, Spatial ecology

Related papers

Back to paper searchBrowse research topicsOriginal source
Spatial and temporal variability of SST in the Zhejiang coastal waters during 2003-2013 — Research Paper | ScholarLens