Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."

Source code for ClimateLearn

Analysis ready CMIP6 data in python the easy way with pangeo tools.

GeoWombat: Utilities for geospatial data

Classification schemes for choropleth mapping.

Downscaling & bias correction of CMIP6 tasmin, tasmax, and pr for the R/CIL GDPCIR project

Mirror of Apache Open Climate Workbench

Deep Learning for empirical DownScaling. Python package with state-of-the-art and novel deep learning algorithms for empirical/statistical downscaling of gridded data

python-based predictive groundwater modeling workflow examples

python and flopy tutorials for hydrologic applications and MODFLOW modeling

A Python toolkit for running and coupling Earth surface models

An analytic element model for steady multi-layer flow

Examples of analysis of Google Cloud CMIP6 data using Pangeo tools

NOAA Phase 2 Hydrological Data Processing

Coelho, G. de A. et al. (2022) Potential Impacts of Future Extreme Precipitation Changes on Flood Engineering Design across the Contiguous United States. Published in Water Resources Research. http…

Material for AWRA2022 Geospatial R and Python Workshop

To determine baseflow from total runoff hydrograph