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    Numerical Modelling of Weather and Climate with WRF
    Michel Mesquita

    Numerical Modelling of Weather and Climate with WRF

    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.


    Towards data science in climate research: an introduction to R
    Saurabh BhardwajMichel MesquitaMorgan Yarker

    Towards data science in climate research: an introduction to R

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

    "Towards data science in climate research: perspectives on Climate Extremes". 

    It introduces you to R, where we use input data from NOAA to visualize and analyze data. Certificates are provided.

    This course is also sponsored by Yarker Consulting and M2Lab.org.


    Modelación Numérica de la Atmósfera: WRF
    Michel MesquitaAndres Sepulveda

    Modelación Numérica de la Atmósfera: WRF

    Modelación Numérica de la Atmósfera: WRF.

    Regional Climate Modeling with WRF
    Michel Mesquita

    Regional Climate Modeling with 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).

    Numerical Climate Prediction
    Venkata Reddy KeesaraMichel Mesquita

    Numerical Climate Prediction

    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.

    Hour of code - an introduction to R
    Michel MesquitaMorgan Yarker

    Hour of code - an introduction to R

    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).

    Introduction to Applied Bayesian Statistics for Climate Research
    Michel MesquitaVidyunmala Veldore

    Introduction to Applied Bayesian Statistics for Climate Research

    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.


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