Stars
The source code of "Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics"
基于pytorch实现的时间序列预测训练框架，各个部分模块化，方便修改模型。包含时间序列预测模型、训练、验证、测试、可视化、onnx导出、onnx推理。
Official Code of TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
Deep Learning for land, oceanic and atmospheric climate variable forecasts
This code converts the precipitation from Netcdf format to csv format to be used for SPHY preprocessor. The code is in jupyter notebook.
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
Precipitation forecast AGS U-Net
Train a LSTM with Convolutions Inputs processed by Conv-ReLU-Max-Batch architecture, on over 3000 precipitation images/maps for the US.
Computer vision time-series data exploration using deep learning approaches
ConvLSTM for short-term precipitation forecasting.
Application of Gaussian Processes to predicting local precipitation in the Upper Indus Basin, Himalayas.
Software associated with the NCAR Accelerated Scientific Discovery (Derecho) project tackling subseasonal bias correction of global predictions.
Python library for basic climate data handling @author: afahad@gmu.edu
Concept code for predicting precipitation using model fields (temperature, geopotential, wind velocity, etc.) as predictors for sub-areas across the British Isle.
Student Workbook Repository for the wrf-python Tutorial
Download figures from National Meteorological Center, China (NMC) website
mahendrawrf / Python-Practical-Application-on-Climate-Variability-Studies
Forked from liyang0711/Python-Practical-Application-on-Climate-Variability-StudiesThis tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to ex…
A Library for Advanced Deep Time Series Models.
This is an official Pytorch implementation of Conditional Local Convolution for Spatio-temporal Meteorological Forecasting, AAAI 2022
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A NWP precipitation bias correction model based on Unet
Predict tomorrow's rain. Model trained on South Florida 2015 using temperature, wind, surface pressure, and vegetation features. Tested on NY and South Florida 2022