SST Diagnostic

Here we compute some statistics on both Sea surface temperature from Croco and from SEVRI product

The statistics have been computed over a period of 1 year between July 2012 and July 2013.

SEVIRI is described here :

https://podaac.jpl.nasa.gov/dataset/SEVIRI_SST-OSISAF-L3C-v1.0

  1. List of diagnostics

    • Monthly average comparison

    • Extrema (percentiles 5 and 95) comparison over the year

    • Root Mean Square Error computed monthly

    • Fitting of the SST on a function and compare the terms between Croco and Seviri

    (1)\[ SST(t)=a*cos(2*pi*t/Ta+phi)+b*t+c\]

    The parameters of the function allow to compare differents components of the SST and show the skills of the model.

    • a is the annual amplitude

    • Ta is annual period

    • phi is phase lagging from the begining of simulation

    • b is trending term reprensting the inter annual variability

    • c is the annual mean around which the SST is varying

    _images/sst_fitting.png _images/sst_monthly_diff_croco_seviri.png _images/sst_monthly_rmse_croco_seviri.png _images/sst_stats_croco_seviri.png _images/sst_daily_mean_basins.png

  2. What scripts ?

    • calc_save_sst_stats.ipynb is the notebook which compute the statistics and save the results as a netcdf file

    • plot_sst.ipynb is the notebook which read the intermediate files and do the plots