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aes-4dvar-suite

4DVAR Suite written in Matlab. Written by Adam El-Said, University of Reading, UK, 2012-2015. The suite contains 4DVAR, wc4DVAR (dp) and wc4DVAR (dx) formulations. Applied to Lorenz95 (L95), Lorenz63 (L63) and 1D Advection (1d-adv) models.

assimilr

R implementation of the EnKPF, block-LEnKPF and naive-LEnKPF.

awesome-atmos

A curated list of awesome Python libraries, software and resources in Atmosphere, Environment and Machine Learning

dart

Data Assimilation Research Testbed

dataassimilation

elegantpaper

Elegant LaTeX Template for Working Papers

fvcom-lwenkf

gstools

GeoStatTools: Geostatistical tools like random field generation, variogram estimation and covariance models.

gsw-matlab

Clone of TEOS-10 repo

homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

latex

Custom resources for LaTeX and related.

letkf

Automatically exported from code.google.com/p/miyoshi

lstm-for-sst-prediction

code for SST prediction using LSTM

ltransv.2b

Larval TRANSport Lagrangian model is an off-line particle-tracking model that is forced with Regional Ocean Modeling System (ROMS) results.

matlab_lorenzmodel

Matlab_LorenzMode

matlab_medd

MEDD spike detection test

mcrn-da

This project involves developing reduced physical and data models and algorithms for data assimilation. The goal of the project is to address computational challenges in data assimilation of dimensionality and non-Gaussian behavior for model problems and relevant small to medium scale problems. This includes a models from many different possible areas: atmosphere, ocean, combined atmosphere/ocean, ice sheet, glacier, hurricane, ENSO, polar vortex, ecological models, etc.. The basic idea is to create computational conceptual models, both physical and data models, and combine these with standard data assimilation techniques and new techniques developed to take advantage of the structure of these conceptual models. Among the data assimilation techniques to be considered are projected particle filters. Focus is on application to problems with bimodal or multimodal behavior which ties in with work on tipping points. Another emphasis is on applying these techniques to higher dimensional problems to create lower dimensional computational conceptual models. The project involves employing, developing, and applying projected data assimilation techniques, in particular projected particle filters, using the framework developed in (Maclean, VV 2019), while focusing on the use of different state space and observation space projections for increasingly high dimensional models.

mlwrf

WRF模式前处理及后处理程序包

mml-companion

This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Faisal and Cheng Ong, written in python for Jupyter Notebook.

nctoolbox

NCTOOLBOX A Matlab toolbox for working with common data model datasets

nmc_met_diagnostic

提供气象诊断分析程序，包括动力, 热力, 水汽和天气特征分析等。

openda

Open data assimilation toolbox

pyfvcom

PyFVCOM: a collection of tools to interact with FVCOM

pyroms

Python tools for the Regional Ocean Modeling System (ROMS)

pyroms2roms

pyroms2roms is a Python version of roms2roms (see Mason etal, 2010, Ocean Modelling) and www.molemaker.org.

romstools

A variety of tools for plotting and analysing output from the Regional Ocean Model (ROMS)

thuthesis

LaTeX Thesis Template for Tsinghua University

toolsoffvcom

Matlab PostProcess of FVCOM