STARCH compuets regional extreme storm physical characteristics and moisture balance based on spatiotemporal precipitation data from reanalysis or climate model data.

Related tags

Deep Learningstarch
Overview

STARCH (Storm Tracking And Regional CHaracterization)

STARCH computes regional extreme storm physical and moisture balance characteristics based on spatiotemporal precipitation data from reanlaysis or climate model data. The algorithm is proposed and implemented in (paper) to identify extreme storms and analyze their moisture balance in the Mississippi Basin based on ERA5 reanlaysis data. Detailed description and implementation of the algorithm can be found in the Jupyter Notebook "Example.ipynb".

Installation

git clone https://github.com/lorenliu13/starch.git

Dependencies

Name Version
geographiclib 1.52
matplotlib 3.4.2
mpu 0.23.1
numpy 1.20.3
pandas 1.3.3
Pillow 9.0.0
scikit_image 0.18.1
scikit_learn 1.0.2
scipy 1.6.3
skimage 0.0
tqdm 4.62.0

cdsapi and urllib3 are necesary when using the code "ERA5_single_levels_download.py" to group download ERA5 data from the ECMWF data center. Basemap Matplotlib Toolkit is necessary when using the plotting function "sequence_strom_plot_basemap()" in the Example.ipynb to visualize the storm tracking results.

Usage

Introduction and implementation of the codes can be found in "Example.ipynb".

Contributing

Feel free to open an issue for bugs and feature requests.

License

STARCH is released under the MIT License.

Authors

Acknowledgements

  • Guo Yu - Feature improvement
You might also like...
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

THUML: Machine Learning Group @ THSS 243 Dec 26, 2022
PyTorch Code of "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics"

Memory In Memory Networks It is based on the paper Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spati

Yang Li 12 May 30, 2022
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs

PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang

Pu Ren 11 Aug 23, 2022
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."

Spacetimeformer Multivariate Forecasting This repository contains the code for the paper, "Long-Range Transformers for Dynamic Spatiotemporal Forecast

QData 440 Jan 2, 2023
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination

Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l

DongYoung Kim 33 Jan 4, 2023
Diabet Feature Engineering - Predict whether people have diabetes when their characteristics are specified

Diabet Feature Engineering - Predict whether people have diabetes when their characteristics are specified

Şebnem 6 Jan 18, 2022
A new data augmentation method for extreme lighting conditions.
A new data augmentation method for extreme lighting conditions.

Random Shadows and Highlights This repo has the source code for the paper: Random Shadows and Highlights: A new data augmentation method for extreme l

Osama Mazhar 35 Nov 26, 2022
Code repo for
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Rao Muhammad Umer 6 Nov 14, 2022
Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation.
Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation.

Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation. It was introduced in Wright, Logan G. & Onodera, Tatsuhiro et al. (2021)1 to train Physical Neural Networks (PNNs) - neural networks whose building blocks are physical systems.

McMahon Lab 230 Jan 5, 2023
Comments
  • Consider combination, division, and deformation of the storm objects in tracking

    Consider combination, division, and deformation of the storm objects in tracking

    The track function may be improved following the figure in the study of Zhou et al. (2018) to deal with storm split and merge: image

    Zhou, Yang, Hyemi Kim, and Bin Guan. “Life Cycle of Atmospheric Rivers: Identification and Climatological Characteristics.” Journal of Geophysical Research: Atmospheres 123, no. 22 (2018): 12,715-12,725. https://doi.org/10.1029/2018JD029180.

    Another idea of dealing with spliting and merging of storm objects can be found in Guan et al. (2019), which gives more detailed cases: image

    Guan, Bin, and Duane E. Waliser. “Tracking Atmospheric Rivers Globally: Spatial Distributions and Temporal Evolution of Life Cycle Characteristics.” Journal of Geophysical Research: Atmospheres 124, no. 23 (2019): 12523–52. https://doi.org/10.1029/2019JD031205.

    opened by lorenliu13 0
Releases(v1.0.1)
Owner
Onosama
Onosama
GitHub Repository
SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research

SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research

59 Feb 25, 2022
SCU OlympicsRunning Baseline

Competition 1v1 running Environment check details in Jidi Competition RLChina2021智能体竞赛 做出的修改： 奖励重塑：修改了环境，重新设置了奖励的分配，使得奖励组成不只有零和博弈，还有探索环境的奖励。 算法微调：修改了官

ZiSeoi Wong 2 Nov 23, 2021
FPSAutomaticAiming——基于YOLOV5的FPS类游戏自动瞄准AI

FPSAutomaticAiming——基于YOLOV5的FPS类游戏自动瞄准AI 声明: 本项目仅限于学习交流，不可用于非法用途，包括但不限于：用于游戏外挂等，使用本项目产生的任何后果与本人无关！ 简介 本项目基于yolov5,实现了一款FPS类游戏（CF、CSGO等）的自瞄AI，本项目旨在使用现

Fabian 246 Dec 28, 2022
Select, weight and analyze complex sample data

Sample Analytics In large-scale surveys, often complex random mechanisms are used to select samples. Estimates derived from such samples must reflect

samplics 37 Dec 15, 2022
Code for "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" paper

UNICORN 🦄 Webpage | Paper | BibTex PyTorch implementation of "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" pap

118 Jan 06, 2023
MetaDrive: Composing Diverse Scenarios for Generalizable Reinforcement Learning

MetaDrive: Composing Diverse Driving Scenarios for Generalizable RL [ Documentation | Demo Video ] MetaDrive is a driving simulator with the following

DeciForce: Crossroads of Machine Perception and Autonomy 276 Jan 04, 2023
Code for Environment Inference for Invariant Learning (ICML 2020 UDL Workshop Paper)

Environment Inference for Invariant Learning This code accompanies the paper Environment Inference for Invariant Learning, which appears at ICML 2021.

Elliot Creager 40 Dec 09, 2022
We provided a matlab implementation for an evolutionary multitasking AUC optimization framework (EMTAUC).

EMTAUC We provided a matlab implementation for an evolutionary multitasking AUC optimization framework (EMTAUC). In this code, SBGA is considered a ba

7 Nov 24, 2022
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes

Sungyong Baik 44 Dec 29, 2022
Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention Network

DroneCrowd Paper Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark. Introduction This paper proposes a space-time multi-scale atte

VisDrone 98 Nov 16, 2022
Code To Tune or Not To Tune? Zero-shot Models for Legal Case Entailment.

COLIEE 2021 - task 2: Legal Case Entailment This repository contains the code to reproduce NeuralMind's submissions to COLIEE 2021 presented in the pa

NeuralMind 13 Dec 16, 2022
NeuralForecast is a Python library for time series forecasting with deep learning models

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate m

Nixtla 1.1k Jan 03, 2023
A toolkit for making real world machine learning and data analysis applications in C++

dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl

Davis E. King 11.6k Jan 01, 2023
This is the repository for The Machine Learning Workshops, published by AI DOJO

This is the repository for The Machine Learning Workshops, published by AI DOJO. It contains all the workshop's code with supporting project files necessary to work through the code.

AI Dojo 12 May 06, 2022
This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes.

Rotate-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes. Section I. Description The codes are

xinzelee 90 Dec 13, 2022
Cross View SLAM

Cross View SLAM This is the associated code and dataset repository for our paper I. D. Miller et al., "Any Way You Look at It: Semantic Crossview Loca

Ian D. Miller 99 Dec 09, 2022
Implementation of various Vision Transformers I found interesting

Implementation of various Vision Transformers I found interesting

Kim Seonghyeon 78 Dec 06, 2022
source code of “Visual Saliency Transformer” (ICCV2021)

Visual Saliency Transformer (VST) source code for our ICCV 2021 paper “Visual Saliency Transformer” by Nian Liu, Ni Zhang, Kaiyuan Wan, Junwei Han, an

89 Dec 21, 2022
a Lightweight library for sequential learning agents, including reinforcement learning

SaLinA: SaLinA - A Flexible and Simple Library for Learning Sequential Agents (including Reinforcement Learning) TL;DR salina is a lightweight library

Facebook Research 405 Dec 17, 2022
A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

FedML-AI 175 Dec 01, 2022