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Evaluation of AI-models for convective parameters

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AI-storm

Evaluation of AI-models for convective parameters

Benchmark datasets:

- Weatherbench (ERA5 and TIGGE for 2020) -> limited levels 
https://weatherbench2.readthedocs.io/en/latest/data-guide.html 

- Observations -> soundings from University of Wyoming 

Convective parameters:

- Instability -> CAPE 

- Shear -> surface and 500 hPa 

wrf-python

Target:

Severe environments as a 0-1 binary -> fractional skill score (FSS)

Values of instability and shear -> RMSE, BIAS, SAL-score

Investigation of bias -> role of moisture

Evaluation of convective season NH&SH -> North America, Europe, Australia, Argentina

Year 2020 

Notes:

No surface humidity, but pressure levels up to 1000 hPa;

FCN-V2 outside of 0-100% RH bounds by ~20% 

FCN-V2 issues with humidity overall

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