Dan-Boat/PyESD
Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of the package is to downscale any climate variables e.g. precipitation and temperature using predictors from reanalysis datasets (eg. ERA5) to point scale. pyESD adopts many ML and AL as the transfer function.
This tool helps climate scientists and hydrologists estimate local climate conditions like precipitation and temperature from large-scale climate models or reanalysis datasets. It takes reanalysis products (e.g., ERA5) and weather station data as input, then produces high-resolution climate variable predictions for specific locations, crucial for assessing local impacts like droughts or floods.
No commits in the last 6 months. Available on PyPI.
Use this if you need to translate broad climate model outputs into precise, local climate variable estimates for a specific geographic area or weather station.
Not ideal if you require climate projections at a global or regional scale without the need for point-specific detail.
Stars
60
Forks
11
Language
Python
License
MIT
Category
Last pushed
Jan 14, 2025
Commits (30d)
0
Dependencies
13
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