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adding bias correction matrix for RMW forecast computation
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WPringle committed May 21, 2024
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82 changes: 82 additions & 0 deletions stormevents/nhc/const.py
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from numpy import isnan, array, argwhere
from pandas import DataFrame

# Bias correction values for the Rmax forecast
# ref: Penny et al. (2023). https://doi.org/10.1175/WAF-D-22-0209.1
bias_lat = [
0.0063,
0.0301,
0.0299,
0.0085,
-0.0199,
-0.0354,
-0.0799,
-0.1240,
-0.1572,
-0.1982,
-0.1706,
]

bias_vmax = [
-0.8047,
-0.2003,
-0.2001,
-0.4070,
-0.6271,
-0.7515,
-0.3369,
-0.3338,
-0.3930,
-0.8167,
-1.4322,
]

bias_r34 = [
-2.0503,
-5.5195,
-7.7374,
-8.4337,
-8.1458,
-10.2065,
-12.6435,
0,
0,
0,
0,
]

bias_r50 = [
-0.7659,
-3.2270,
-4.5476,
-6.2219,
-7.7406,
-8.5449,
-10.0759,
0,
0,
0,
0,
]

bias_r64 = [
-0.5082,
-2.4170,
-3.6993,
-4.7795,
0,
0,
0,
0,
0,
0,
0,
]

RMW_bias_correction = DataFrame(
index=range(12, 132, 12),
data={
"latitude": bias_lat,
"max_sustained_wind_speed": bias_vmax,
"isotach_radius": [bias_r34, bias_r50, bias_r64],
},
)

# Regression coefficients for the Rmax forecast
# ref: Penny et al. (2023). https://doi.org/10.1175/WAF-D-22-0209.1
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