Search results | ECMWF eLearning

An introduction to Data Assimilation

Data assimilation is used in NWP to define ‘optimal' initial conditions for numerical forecasts. In this lesson you will define data assimilation and explore how it is used at ECMWF.

Level: Fundamentals

Certification course: No

What you'll learn:

What is data assimilation and how it fits into numerical weather prediction
Which sources of observations are used by ECMWF in its data assimilation process
How data assimilation methods work, including 4D- VAR
Recent improvements in data assimilation, and future challenges

Estimated duration: 40 minutes

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Numerical Weather Prediction

Climate Data Discovery – Advanced

This lesson provides details on the various data sources, and strategies to find the data needed: Processing steps, choosing projections, scenarios, ensembles, variables etc. The lesson is a follow-up of “Climate Data Discovery – Introduction”.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

Climate Data Discovery – Introduction

This lesson provides an introduction to the different sources of climate data and guides you to find the data you need.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

Climate Projections

This ‘hands-on’ lesson covers climate projections, differences between climate models, and how to choose from climate projection data.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

Data Resources - Climate Models

This lesson explains how climate models work and how the quality of climate models can be evaluated. Differences between climate projections, predictions and scenarios are explained.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

Data Resources - Introduction

This lessen provides an overview of the various types of climate data resources, and teaches what Essential Climate Variables are. It will indicate the main advantages and disadvantages of the various data sources.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

Data Resources - Observations

This lesson provides training on observations data. The different types of measurements are explained, the types of observing systems and the measurement uncertainty are explained.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

Data Resources - Reanalyses

This lesson teaches users the basics of climate reanalysis. The lesson explains how reanalyses are made, an overview of global reanalyses datasets, and their strengths and limitations.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

ecCodes – Manipulating GRIB data with tools and API

ecCodes is software developed by ECMWF to decode and encode in WMO GRIB and BUFR formats. This lesson focuses on handling GRIB data with ecCodes tools.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

Exploring meteorological data through OGC web services

Web services are used to visualise geographical data. This lesson describes web services, data standards and outlines what OGC and INSPIRE are.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

Introduction to BUFR decoding with ecCodes

ecCodes is software developed by ECMWF to decode and encode in WMO GRIB and BUFR formats. This lesson will introduce you to the BUFR format for decoding of BUFR data.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

Introduction to Metview

Metview is a powerful meteorological workstation application that enables you to access, process and visualise meteorological data. In this lesson you will learn how to use MetView.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

Introduction to the Scalable Acquisition and Pre-Processing (SAPP) system

The SAPP system is the ECMWF's operational acquisition and pre-processing system for observations and other input data. This lesson is aimed at users with little or no experience of SAPP and will provide the raw skills needed to use SAPP.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

MARS – advanced retrievals, data manipulation and computations

The Meteorological Archival and Retrieval System (MARS) enables users to access ECMWF’s data. This lesson will look at MARS requests and explore its compute capability.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

MARS ECMWF's meteorological archive

The Meteorological Archival and Retrieval System (MARS) enables users to access ECMWF’s data. This lesson will teach you how to create a customised data retrieval.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

Metview for the Single-Column Model (SCM)

This lesson will provide a quick overview of Metview's main features and enable you to use Metview to analyse and edit input data for the single-column model, run the model and visualise its output.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Software, Data and Computing

MOOC MLWC - 1. ML in Weather & Climate

The first tier of our MOOC in Machine Learning in Weather and Climate includes six modules and is an introduction to the main topics in machine learning in the context of weather and climate, from the processing of observations to data assimilation, forecasting and post-processing.

Level: Fundamentals

Certification course: No

What you'll learn:

An overview of machine learning in weather and climate
Unpack, at a conceptual level, key concepts and topics in ML
Applications and recent advances in the field

Prerequisites:

A basic knowledge of weather and climate, statistics and computing.

Full description:

In this first tier of our MOOC on Machine Learning (ML) in Weather and Climate, we give a broad overview of the key concepts ML and its applications in recent years to topics from forecasting and data assimilation to post-processing, observations and computing. This course is aimed as an introduction, which is accessible to those with an interest in ML, weather and climate, but without necessarily requiring a very technical background.

This course features a mixture of interactive modules, webinar recordings, quizzes, podcasts and code examples.

Please note that this course ran live in early 2023 and reflected the state of the art at that point in time.

Estimated duration: 14 hours

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Machine Learning

MOOC MLWC - 3. Practical ML applications in Weather & Climate

The third tier of our MOOC on Machine Learning in Weather and Climate includes six modules and gives practical examples of machine learning approaches applied to observations, forecasting, data assimilation, post-processing, ocean and climate, and operational meteorology.

Certification course: No

What you'll learn:

The application of ML methods to a range of problems in weather and climate
The details of practical code examples which can be used to apply to your own problems

Prerequisites:

Please complete MOOC MLWC - 2. Concepts of Machine Learning first, or ensure you are familiar with the topics covered there. Intermediate proficiency with Python, knowledge of statistics and experience in weather/climate is assumed.

Full description:

In this third tier of our MOOC on Machine Learning (ML) in Weather and Climate, we focus on the implementation of ML in weather and climate problems.

This six-module course gives code examples and explainers in topics including:

Satellite precipitation removal
Environmental modelling
Nowcasting
Data assimilation
Downscaling
Ocean modelling
Operational meteorology

This course is aimed at those with a technical/weather background and experience in Python. Ideally you will have already taken Tiers 1 and 2 of the MOOC on ML in Weather and Climate, or already be familiar with the concepts there.

Please note that this course ran live in early 2023 and reflected the state of the art at that point in time.

Estimated duration: 25 hours

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: MedEWSa

Overview of satellite observations and their role in Numerical Weather Prediction (NWP)

This module will teach you about data sources, the role of satellite observations, satellite data measurements, assimilation, and monitoring of satellite observations.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Research

Sectoral Application - Heat Health

In this lesson you will learn how to use the Climate Data Store (CDS) for applications in the health sector. The lesson focuses on urban heat. The lessons shows data and indicators from SIS-European Health.

Certification course: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: C3S

Search results: 29