GOES-16 SST: cloud correction and gap filled for observation of upwelling in the MAB

Published: 25 October 2020| Version 1 | DOI: 10.17632/npnfntz3kp.1
Contributor:
Sarah Murphy

Description

This cloud correction method applied to GOES-16 hourly SST to cloud correct and retaining upwelling pixels in the MAB. The Quality Filter (DQF) provided by GOES consistently removed coastal upwelling pixels along the coast of New Jersey and Delaware. This Spike Filter method was applied to hourly GOES SST for the summer of 2019 and increased SST coverage in the MAB coastal region by ~15% and maintained an acceptable accuracy when validated to regional buoy SST. This includes a 1. rate of SST change 2. minimum SST threshold 3. comparison to recent SST and 4. SST bias correction. This cloud corrected SST was then gap-filled using DINEOF and compared to other available SST products.

Files

Steps to reproduce

1. Load the GOES_DATA.mat, bath_data.mat, idw_sarah.nc, and rate_of_change.m into matlab 2. Run the GOES_SST_cloudfilter.m code to apply the cloud filtering steps to GOES data 3. GOES_DINEOF_SST.nc is the cloud corrected, and DINEOF gap-filled data set that can be used for further analyses

Institutions

Rutgers University - George H. Cook Campus

Categories

Satellite Method, Remote Sensing for Sea Surface Properties, Sea Surface Temperature

Licence