Giter VIP home page Giter VIP logo

tanxuezhi's Projects

miles icon miles

Mid-Latitude Evaluation System

modelling-electricity-generation-with-era5 icon modelling-electricity-generation-with-era5

This repository contains a set of R scripts and the data illustrating the possibility to model hourly electricity generation from renewable sources using the latest climate reanalysis from the Copernicus Climate Change Service (C3S).

ncl_plots icon ncl_plots

My plotting subroutines write in NCAR Command Language

ngen icon ngen

Next Generation Water Modeling Engine and Framework Prototype

omc-precip icon omc-precip

An Occurrence Markov Chain model for fitting and generating daily precipitation data

pangeo icon pangeo

A place to discuss and track issues related to the Pangeo project

pep icon pep

Matlab and ncl codes associated with the paper "Long-lead predictions of Eastern US hot days from Pacific sea surface temperatures"

pmfutures icon pmfutures

Planning for an unknown future: Incorporating meteorological uncertainty into predictions of the impact of fires and dust on US particulate matter

praga icon praga

Program for Agrometeorological Analysis

precip-dot icon precip-dot

Precipitation Extremes Analysis Project Extending the NOAA Atlas 14 using SNAP/CASC WRF products

precipitation-vod-isv icon precipitation-vod-isv

Code for Harris et al. "Satellite-Observed Vegetation Responses to Intraseasonal Precipitation Variability"

prectemp icon prectemp

analysis of temperature dependency of extreme precipitation intensity

prob_budyko icon prob_budyko

Code of Thesis to pursue an M.Sc. in Water Resources

pybkb_v3 icon pybkb_v3

Python scripts that help me be a successfull meteorologist. (Python 3)

pyprobml icon pyprobml

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

python-practical-application-on-climate-variability-studies icon python-practical-application-on-climate-variability-studies

This 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 explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

python-tidegates icon python-tidegates

🌊 ArcToolbox to analyze flooding due to storm surges and climate change

regrid2smap icon regrid2smap

A library for regridding data sets to the SMAP 36km EASE-Grid 2.0 standard

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.