Dataset and source code for "Explanation and optimizing multi-model blending algorithm using random variables theory"

this dataset contain: de-biased model forecast data on station location, ECMWF, NCEP, JP and CMA observaton data, obs_t2m source code (in python) how to use it: 1. prepare data and python environment 1.1 if you want to run Station_FCST_MMWB.py, please download the station forecast and observation data 1.2 unzip the python-src-v2.zip 1.3 need meteva package to read/write micaps-3 format data: https://github.com/nmcdev/meteva 1.4 need cartopy to draw picture FigS01. 2. try the multi blending method <optional> 2.1 unzip the [CMA.zip, ECMWF.zip, jp.zip, NCEP.zip, obs_t2m.zip] file into ./raw_data/ 2.2 run the Station_FCST_MMWB.py in python environment 3. draw figures 3.1 run Fig01.py in python environment 3.2 run Fig02.py in python environment 3.3 run Fig03.py in python environment 3.4 run FigA01.py in python environment 3.5 run FigS01.py in python environment