ESA CCI LST comparison to Historical Models¶
This diagnostic compares ESA CCI LST to multiple historical emsemble members of CMIP models. It does this over a defined region for monthly values of the land surface temperature. The result is a plot showing the mean differnce of CCI LST to model average LST, with a region of +/- one standard deviation of the model mean LST given as a measure of model variability.
The recipe and diagnostic need the all time average monthly LST from the CCI data. We use the L3C single sensor monthy data. A CMORizing script calculates the mean of the day time, and night time overpasses to give the all time average LST. This is so that the Amon output from CMIP models can be used. We created such a dataset from the Aqua MODIS data from CCI.
Available recipes and diagnostics¶
Recipes are stored in esmvaltool/recipes/
Diagnostics are stored in esmvaltool/diag_scripts/lst/
User settings in recipe¶
No required settings for script
No user defined inputs to the diagnostic
Required settings for variables
The diagnostic works with all data sources on having the same start_year and end_year, and hence that data is also available.
Required settings for preprocessor
start_longitude, end_longitude The western and eastern bounds of the region to work with.
start_latitude, end_latitude The southern and northern bounds of the region to work with.
target_grid This should be one of the model grids.
ts (atmos, monthly mean, longitude latitude time)
Observations and reformat scripts¶
This recipe and diagnostic is written to work with data created from the CMORizer esmvaltool/cmorizers/obs/cmorize_obs_esacci_lst.py. This takes the orginal ESA CCI LST files for the L3C data from Aqua MODIS DAY and NIGHT files and creates a the all time mean data this diagnostic uses. Advice from the CCI LST team is to use the monthly not daily files to create the all time average to avoid th epossibility of biasing towards night time LST values being more prevalent because of how the cloud screening algorithms work.
ESA CCI LST project https://climate.esa.int/en/projects/land-surface-temperature/