The ESA SST CCI project has published a new version of its climate data records covering late 1981 to the end of 2016, available on ESA’s Open Data Portal. Moreover, an extension in time (interim CDR) is routinely available from the Copernicus Climate Change Service or the Copernicus Marine Environment Monitoring Service. Read more »

Project Scientist Kevin Pearson has recently published a paper on the role of the Advanced Microwave Scanning Radiometer 2 (AMSR2) channels within an optimal estimation scheme for sea surface temperature. The article is published in volume 10, issue 1 of the journal for remote sensing, and a full version of the paper can be downloaded from www.mdpi.com/2072-4292/10/1/90.

Project Scientist Pia Nielsen-Englyst et al. have recently published a paper on the Optimal Estimation of Sea Surface Temperature from AQUA's Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). The article is in volume 10, Issue 2 of the journal for remote sensing and a full version can be downloaded from www.mdpi.com/2072-4292/10/2/229.

Project Scientist Claire Bulgin has recently published a paper on Bayesian cloud detection for 37 years of Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data. The article is published in volume 10, issue 1 of the remote sensing journal, and a pdf can be downloaded from www.mdpi.com/2072-4292/10/1/97.

Project Scientist Dave Berry has written a paper assessing the stability of the (A)ATSR sea surface temperature climate dataset from ESA's climate change initiative. The article is in volume 10, issue 1 of the journal for remote sensing, and a pdf copy can be downloaded from www.mdpi.com/2072-4292/10/1/126.

The graph shows the global average SST change over the last 24 years, since 1991 (as of December 2015). For more information, click here.

The SST CCI Science Leader, Chris Merchant, has written a blog on the Global Drifter Program, which includes information on what using the drifter array and satellite data as two independent systems can tell us about marine climate change. Click here for the full article.

The SST CCI project has produced three papers on various aspects of SST uncertainties, published in Remote Sensing of Environment:

Estimating background error covariance parameters and assessing their impact in the OSTIA system Read more »

The SST CCI Analysis product (in which daily SST is gap-filled in time and space) has been updated to version 1.1. This version uses the same SST inputs as analysis v1.0. Compared to v1.0, intermittent bugs in the externally sourced sea ice fields (with corresponding implications for high latitude SST) have been corrected. For users not directly using the sea ice fields, the update is minor; for those using the sea ice fields, it is recommended. Read more »

The ESA SST CCI project provides two software tools specifically designed to operate on the SST CCI data. These tools support the regridding of the SST data products to a coarser raster and the regional averaging of data for a selectable time interval. The algorithms implemented ensure a correct propagation of the uncertainty information and generate an additional uncertainty component taking into account the effects of incomplete sampling (e.g. due to cloud coverage).