Mao-Lin Shen's repositories
PPP-Results
All results of applying Prognostic Potential Predictability
2D-Navier-Stokes-Solver
As the field of Computational Fluid Dynamics (CFD) progresses, the fluid flows are more and more analysed by using simulations with the help of high speed computers. In order to solve and analyse these fluid flows we require intensive simulation involving mathematical equations which governs the fluid flow, these are Navier Stokes (NS) equation. Solving these equations has become a necessity as almost every problem which is related to fluid flow analysis call for solving of Navier Stokes equation. These NS equations are partial differential equations so different numerical methods are used to solve these equations. Solving these partial differential equations so different numerical methods requires large amount of computing power and huge amount of memory is in play. Only practical feasible way to solve these equation is write a parallel program to solve them, which can then be run on powerful hardware capable of parallel processing to get the desired results High speed supercomputer will provide us very good performance in terms of reduction in execution time. In paper focus will be on finite volume as a numerical method. We will also see what GPGPU (General-Purpose computing on Graphics Processing Units) is and how we are taking its advantages to solve CFD problems.
awesome-explorables
A curated list of awesome explorable explanations.
CDEPS
Community Data Models for Earth Prediction Systems
Potential-Predictability
For calculating PPP on nostore-osl
CFDPython
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
cime
Common Infrastructure for Modeling the Earth
climlab-feedstock
A conda-smithy repository for climlab.
CMEPS
NUOPC Community Mediator for Earth Prediction Systems
datacamp-community-tutorials
Tutorials for DataCamp (www.datacamp.com)
docker-tutorial
Docker 基本教學 - 從無到有 Docker-Beginners-Guide 教你用 Docker 建立 Django + PostgreSQL 📝
eddyTracking
Code for the detection and tracking of eddies, following Chelton et al. (Prog. Ocean., 2011) given a series of sea level maps.
electron-ssr-backup
electron-ssr原作者删除了这个伟大的项目，故备份了下来，不继续开发,且用且珍惜
interactive-machine-learning-list
A collaborative list of interactive Machine Learning, Deep Learning and Statistics websites
manage_externals
cesm externals management utility
Model-Training-SUMO-
Model Training (SUMO)
MPI-ESM-Simulations
Simulations details of MPI-ESM
OpenDA
Open data assimilation toolbox
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
quark
World's first offline search engine. The Internet cannot stop us from learning. 世界上第一個離線搜索引擎。互聯網不能阻止我們學習。
scikit-learn
scikit-learn: machine learning in Python
Seasonal2Decadal-Prediction-Scripts-for-ESM
Seasonal2Decadal Prediction Scripts for NorESM
shallow-water
Python model solving the shallow water equations (linear momentum, nonlinear continuity)
subseasonal_forecasting
Using a hybrid spatial-temporal deep learning approach to forecast subseasonal weather across 514 Western USA geographical regions
tvdatafeed
A simple TradingView historical Data Downloader
US_simple_example
Using Lorenz 63 model to explain Universal Synchronizer
vnpy
基于Python的开源量化交易平台开发框架