brivasThis repository is a collection of python scripts to analyse and plot Sea Surface Temperature data in the southern ocean. The code reads, organises and plot daily SST data from the ESA-CCI Sea Surface Temperature Climate Data Record v2.0 and drifting buoys SST data from ICOADS.
Motivation
We want to know how well do drift buoys sample the Southern Ocean? Is there is any systematic bias introduced in the SST record from the way that buoys move over the ocean.
![Buoy animation][https://git.noc.ac.uk/brecinosrivas/orchestra-sst/-/blob/master/notebooks/2000_cci_sst_at_buoy_minus_cci_sst.mp4]
To address that question we analyse several re-gridded versions of the ESA-CCI SST data:
- ESA-CCI-SST data interpolated to each buoy lat and lon coordinates.
- ESA-CCI-SST data averaged in a 1x1 degree grid-box centred at each buoy lat and lon coordinates (a coarse resolution of the ESA-CCI SST data).
References
Freeman. et al., (2017) Freeman, E., Woodruff, S.D., Worley, S.J., Lubker, S.J., Kent, E.C., Angel, W.E., Berry, D.I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N.A., Rosenhagen, G. and Smith, S.R. (2017), ICOADS Release 3.0: a major update to the historical marine climate record. Int. J. Climatol., 37: 2211-2232. doi:10.1002/joc.4775
Good, et al. (2019) Good, S.A.; Embury, O.; Bulgin, C.E.; Mittaz, J. (2019): ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Level 4 Analysis Climate Data Record, version 2.1. Centre for Environmental Data Analysis, 22 August 2019. doi:10.5285/62c0f97b1eac4e0197a674870afe1ee6.