Python Module to analyze temperature anomalies in Graz.
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Updated
Dec 7, 2021 - Python
Python Module to analyze temperature anomalies in Graz.
Precipitation climatology anomalies of Tanzania, shedding light on drought in the East African country. A jupyter notebook tutorial for geospatial analysis of netcdf data, and precipitation time series.
A Statistician reads published Climate Science
R Code for Statistics and Data Visualizations in Climate Science with R and Python
R.Weather CDMS, es un sistema computacional que integra colecciones de datos y su representación espacial, facilitando el registro, manejo, análisis, distribución y utilización de datos hidroclimatológicos.
Climate drivers of the springtime North America cooling pattern
Repository that containts climate relevant ML datasets from the Climate Modeling Alliance.
Code for the paper "Machine learning of cloud types in satellite observations and climate models".
Interactive deployable visualisation of volcanic datasets provided for TAR experiments of the ISA-MIP climate model intercomparison initiative.
Python workshop for EES405 course @IISERM
China Building Energy Efficiency Design Fundamental Database and Platform
Python package for comparing traditional (greenhouse gas) climate model with cloud seeding model
This repository provides a collection of codes for the analysis of GPS/RO observations.
Website for showing the all codes and methodology to analyze compound extreme events and their socio-economic impacts.
In my model I aim to investage the average growth of different species of plants. Driving question: How does the growth in different species differ within the same environment? This was an Investigative model. Commercially, logging companies would be intrested to see how to best grow plant or learn which plants are best to grow in their environment
This repository will provide support for researchers, scientists, and other members of the MITgcm climate science community to build, run, and interpret results of models in portable units of software (docker containers).
Climate Variable Prediction with Conditioned Spatio-Temporal Normalizing Flows. 🌎
SST Forecasting System: A robust forecasting platform leveraging ERA5 reanalysis data and big data tools (Airflow, Spark, Cassandra, PostgreSQL) to predict Sea Surface Temperatures. Utilizes Facebook's Prophet and Random Forest models for precise predictions, integrated with Tableau for real-time data visualization.
A project focused on climate data and tooling for Rio Grande do Sul in Brazil.
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