A bias correction method for Arctic satellite sea surface temperature observations

A multi-sensor bias correction method has been developed using satellite sea surface temperature (SST) products from one microwave and five infrared sensors that cover the Arctic Ocean. The correction method has been used to construct improved single sensor and multi-sensor, merged and interpolated satellite SST products from January to December 2008. lidation of the satellite products ingested in the level 4 production shows that large biases can persist for months in this region. The SST products from the AATSR sensor on ENVISAT and the NAVOCEANO AVHRR GAC are the most stable and reliable products for the Arctic region. These products have therefore been used to construct the reference product against which the other satellite products have been corrected. The bias correction method has been developed using detailed error characteristics and thorough time-space analysis, and the bias corrected fields are validated against in situ observations from drifting buoys. All the individual satellite products show improvement in both bias and standard deviation after correction. Largest improvements are found for the Modis sensor on the Terra satellite, where biases are improved from − 0.46 K to 0.02 K with the correction method. Temporal validation statistics reveal that extended periods with significant biases are also removed by the bias correction method. ificant improvement is seen when the corrected satellite products are used for the SST analysis. When compared against drifting buoys, not included in the analysis, the corrected level 4 satellite SST product shows a bias of − 0.04 K and standard deviation of 0.54 K, compared to an original bias of − 0.28 K and standard deviation of 0.61 K. The effect of a missing reference sensor is assessed for the full period. Level 4 test runs using only one reference sensor demonstrates that improvements can be obtained with a single sensor bias correction method, and that the AATSR sensor gives the largest improvements. However, using both reference sensors in the bias calculation gives significantly better performance than using just one.