pepc-global-track 0.1.0

Predict tropical cyclone track displacements using pre-trained Random Forest models

pepc-global-track

Predict tropical cyclone track displacements (longitude or latitude) using pre-trained Random Forest models.

Installation

pip install pepc-global-track

Usage

import numpy as np
from pepc_global_track import predict_track

# 1D arrays of environmental predictors at storm locations
u250 = np.array([5.0, 6.0, 7.0])   # 250 hPa zonal wind (m s^−1)
v250 = np.array([1.0, 1.5, 2.0])   # 250 hPa meridional wind (m s^−1)
u850 = np.array([3.0, 3.5, 4.0])   # 850 hPa zonal wind (m s^−1)
v850 = np.array([-1.0, -0.5, 0.0]) # 850 hPa meridional wind (m s^−1)
lat  = np.array([15.0, 16.0, 17.0]) # storm latitude (degrees)

# Predict longitude displacement
delta_lon = predict_track("WNP", "lon", u250, v250, u850, v850, lat)

# Predict latitude displacement
delta_lat = predict_track("WNP", "lat", u250, v250, u850, v850, lat)

Parameters

• basin: str — one of "AS", "BoB", "WNP", "ENP", "NA", "SI", "SP"
• type: str — "lon" (zonal displacement) or "lat" (meridional displacement)
• u250, v250, u850, v850: numpy.ndarray — 1D arrays of wind predictors
• lat: numpy.ndarray — 1D array of storm latitudes

Returns

• numpy.ndarray — 1D array of predicted displacements (no noise added)

Model Weights

Model weights are automatically downloaded from HuggingFace on first use and cached locally.