Recipes for reproducing Analysis-Ready & Cloud Optimized (ARCO) ERA5 datasets.
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Updated
Jul 10, 2024 - Python
Recipes for reproducing Analysis-Ready & Cloud Optimized (ARCO) ERA5 datasets.
Atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series
Functions and Python scripts to ingest ERA5 data into Google Earth Engine
Visualization and postprocessing of the WRF and ERA5 data
TopoPyScale: a Python library to perform simplistic climate downscaling at the hillslope scale
A super lightweight Lagrangian model for calculating millions of trajectories using ERA5 data
An ERA5-based hourly global pressure, temperature, and relative humidity model
A large compression model for weather and climate data, which compresses a 200+ TB ERA5 dataset into a new 0.7TB CRA5 dataset.
Global positioning by atmospheric pressure
This repository is the reproducible code of the paper Data Assimilation using ERA5, ASOS, and the U-STN model for Weather Forecasting over the UK. This paper has been accepted in the NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning.
Deep Learning for land, oceanic and atmospheric climate variable forecasts
Automatic Lidar and Ceilometer Processing Framework (ALCF)
WRF model initializer with Shiny
Student project - Soil Moisture Dynamics Forecasting Supported with Neural Networsks
Research all papers and codes related to weather forecasting based on artificial intelligence methods, including but not limited to deep learning, generative adversarial, multimodal and other strong artificial intelligence
Repository to download, process, and visualize local climate data from ERA5
This repository contains Python module to calculate backtrajectories using a Lagrangian method based on ERA5 reanalysis data.
ERA5 provides hourly estimates of a large number of atmospheric, land and oceanic climate variables. The data cover the Earth on a 30km grid and resolve the atmosphere using 137 levels from the surface up to a height of 80km. ERA5 includes information about uncertainties for all variables at reduced spatial and temporal resolutions.
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