Because we care about education

Several numerical methods are available to understand and forecast the weather and climate systems. This course focuses on the The Weather and Resource Forecasting (WRF) model, a type of limited area model widely used in the major weather forecasting centres. 

Different aspects of numerical prediction and modelling,  uncertainty, downscaling, nesting, and best practises are part of the course syllabus. Participants will have access to one of the largest WRF training programmes to date, which has trained more than 1500 participants. 

The main contents of the course are: dynamical downscaling techniques, physical-process parameterisations, design of experiments, WPS, predictability, verification methods, and climate modelling.

This R tutorial is designed as a preparation course for the TERI-NORCE research school on 

Modelación Numérica de la Atmósfera: WRF.

This course will teach you how to run the Weather Research and Forecasting (WRF) model and how to use it in climate applications. The course is divided into 8 parts, which can be taken at the participant's own time and pace - making it a flexible option. More than 1000+ registered participants have studied WRF with us! If you would like to learn WRF, you are welcome to register at anytime! There is not start or end dates. You learn at your own pace. Certificates of participation are provided.

This course ended on March 8th, 2021, since we are producing a book (coming soon).

This is a course about numerical climate prediction aimed at those interested in learning more about the climate system, numerical methods, statistical methods, and regional climate modeling. 

It is part of the GIAN program (Global Initiative for Academic Networks) in India. The course is hosted by the Department of Civil Engineering at the National Institute of Technology Warangal (NITW).

In this course, Prof. K Venkata Reddy in India and Dr. Michel d. S. Mesquita in Norway will be teaching how to run the WRF model, how to conduct statistical analysis using R and the theory of numerical prediction.

This Tutorial is designed to take one hour and is part of the Hour of Code event. It introduces you to R, where we use input data from NOAA to visualize and analyze data. Certificates are provided.

To enroll in this course, make sure you are a registered user of this site and then send an email request to Dr. Mesquita (michel@m2lab.org) or Dr. Yarker (morgan@yarkerconsulting.com).

This course teaches participants about the Bayesian statistics theory, as well as its applications in climate science. It has a special focus on analyzing climate model output. The course is divided into 8 parts, which can be taken at the participant's own time and pace - making it a flexible option. Several skills will be developed in this course, such as: how to use the R statistics software, how to do Bayesian data analysis and how to think the "Bayesian" way. There are currently 399+ registered participants taking this course! So, if you would like to learn Bayesian statistics, you are welcome to register at anytime! Certificates of participation are provided.