pepc-global-track 0.2.0

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

# (N, 5) array with columns [u250, v250, u850, v850, lat]
# u250, v250, u850, v850: wind predictors (m s^−1)
# lat: storm latitude (degrees)
X = np.array([
    [5.0, 1.0, 3.0, -1.0, 15.0],
    [6.0, 1.5, 3.5, -0.5, 16.0],
    [7.0, 2.0, 4.0,  0.0, 17.0],
])

# Predict longitude displacement
delta_lon = predict_track("WNP", "lon", X)

# Predict latitude displacement
delta_lat = predict_track("WNP", "lat", X)

Parameters

• basin: str — one of "AS", "BoB", "WNP", "ENP", "NA", "SI", "SP"
• type: str — "lon" (zonal displacement) or "lat" (meridional displacement)
• X: numpy.ndarray — 2D array of shape (N, 5) with columns [u250, v250, u850, v850, lat]

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.