Search results | ECMWF eLearning

An introduction to Data Assimilation

Learn about data assimilation and how it is used to define ‘optimal' initial conditions for NWP 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

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Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Numerical Weather Prediction

Climate Change and Agriculture

This lesson covers how climate change impacts the agriculture sector. Responses of different crop types to climate change is explained. Adaptation measures are introduced and how CDS data can be used for this. Examples are given from the SIS Global Agriculture.

Level: Fundamentals

Certification course: No

What you'll learn:

Understand the positive and negative impacts of climate change on agriculture
The difference between C3 and C4 crop types in their response to climate change
The different types of adaption measures
Relate the climate impacts to the SIS Global Agriculture development

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Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Climate Data Discovery – Advanced

Learn about the various data sources, and strategies to find climate data: processing, choosing projections, scenarios, ensembles and variables.

Level: Others

Certification course: No

What you'll learn:

An overview of the climate data processing chain
Scenarios used in CMIP5 and CMIP6
Strategies for selecting climate models
Downscaling techniques
The importance of skill assessment
How Sectoral Information Systems provide climate data tailored to your needs
Similarities and differences between processing climate projections, and seasonal climate predictions.

Full description:

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”.

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Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Climate Data Discovery – Introduction

An introduction to the different sources of climate data and how to find them.

Level: Fundamentals

Certification course: No

What you'll learn:

The difference between weather and climate
Different sources of climate data, including observations, renalysis, model forecasts and sectoral products
How to find the data you need

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Atmospheric composition: No

Climate: No

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Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Climate Projections

About climate projections, differences between climate models, and how to choose from climate projection data.

Level: Fundamentals

Certification course: No

What you'll learn:

What climate projections are
How to choose climate models
Where to find climate projections in the Climate Data Store
How to choose climate projection data

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Climate: No

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Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Data Resources - Climate Models

Uncover how climate models work and how they can be evaluated. Differences between climate projections, predictions and scenarios are explained.

Level: Fundamentals

Certification course: No

What you'll learn:

About the different types climate model and how they work
Differences between climate projections, predictions and scenarios
Evaluating climate models
What are climate ensembles?
The use of climate model data

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Climate: No

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Data Resources - Introduction

Learn about Essential Climate Variables, the different types of climate data resources, and their respective pros and cons.

Level: Fundamentals

Certification course: No

What you'll learn:

What Essential Climate Variables (ECVs) are
Types of climate data resources, including observations and models
Pros and cons of different data sources

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Climate: No

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Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Data Resources - Observations

Explore the different types of measurements, the types of observing systems and their measurement uncertainty.

Level: Fundamentals

Certification course: No

What you'll learn:

Which different types of measurements exist, including direct and indirect observations
The various meteorological observing systems (remote sensing, land, sea, air, etc) and their representativeness
How to account for uncertainties and propagate errors

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

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.

Level: Fundamentals

Certification course: No

What you'll learn:

What reanalysis is and how reanalyses are made
An overview of global reanalysis datasets
About ECMWF's ERA5 reanalysis data set and its strengths and weaknesses

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Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

ecCodes – Manipulating GRIB data with tools and API

This lesson is focused on how to gain flexibility and control when handling GRIB data using advanced ecCodes tools.

Level: Others

Certification course: No

What you'll learn:

How to handle and manipulate GRIB data with the advanced ecCodes GRIB tools, such as: grib_copy, grib_set, grib_-lter
Basic features of the ecCodes Application Programming Interfaces (API), which will give you the highest flexibility and level of control when handling GRIB data

Full description:

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.

Estimated duration: 40 minutes

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Climate: No

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Computing services and tools

Exploring meteorological data through OGC web services

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

Level: Others

Certification course: No

What you'll learn:

Define what web services are
Explain the typical challenges of meteorological data
Describe how the meteorological community can benefit from web services
Explain why we need data standards
Outline what OGC and INSPIRE are

Full description:

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

Estimated duration: 40 minutes

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Machine learning: No

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Category: Computing services and tools

Introduction to Metview

Metview is a meteorological workstation application that enables you to access and visualise meteorological data.

Level: Fundamentals

Certification course: No

What you'll learn:

How to use Metview to handle meteorological data files
How to inspect metadata
How to perform computations
How to visualise the results
Hands-on experience in creating sophisticated layouts comprising multiple plots on the same page
Generate and run Macro programs to obtain plots via an automated process

Full description:

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.

Estimated duration: 40 minutes

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Climate: No

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Computing services and tools

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.

Level: Fundamentals

Certification course: No

What you'll learn:

Raw skills to use the SAPP Jupyter notebook to get you started
How to modify the SAPP system for your requirements
Better understanding of the three-stage data workflow: Acquisition stage, Processing stage and Extraction stage

Full description:

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.

Estimated duration: 40 minutes

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Computing services and tools

MARS – advanced retrievals, data manipulation and computations

The Meteorological Archival and Retrieval System (MARS) enables access to ECMWF data. Explore its computing capability

Level: Others

Certification course: No

What you'll learn:

How to combine multiple requests into one call to MARS
How to write fields into multiple files
How to manipulate already retrieved data
Explain the concept of fieldsets
MARS computations

Full description:

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.

Estimated duration: 40 minutes

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Machine learning: No

Numerical weather prediction: No

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Category: Computing services and tools

MARS ECMWF's meteorological archive

The Meteorological Archival and Retrieval System (MARS) enables users to access and retrieve ECMWF’s historical data.

Level: Fundamentals

Certification course: No

What you'll learn:

What the MARS catalogue is
How the data is organised in the archive
How to create a customised data retrieval
How to improve the efficiency of your MARS requests

Full description:

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.

Estimated duration: 30 minutes

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Computing services and tools

Metview for the Single-Column Model (SCM)

This lesson provides an overview of Metview's main features to analyse and edit input data for the single-column model.

Level: Others

Certification course: No

What you'll learn:

A quick overview of Metview's main features
How to use Metview to analyse and edit input data for the single-column model
How to run the model and visualise its output

Full description:

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.

Estimated duration: 30 minutes

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Computing services and tools

MLWC MOOC 3: Applications of Machine Learning in Weather and Climate

Six modules giving ML applications in observations, forecasting, data assimilation, post-processing, ocean and more.

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

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Atmospheric composition: No

Climate: Yes

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Machine Learning

Sectoral Application - Heat Health

Learn how to use the Climate Data Store (CDS) for applications in the health sector. The lesson focuses on urban heat and data and indicators from SIS-European Health.

Level: Fundamentals

Certification course: No

What you'll learn:

How weather conditions and climate change affect health, with a focus on heat
Which data and indicators are available from the European Health Sectoral Information System (SIS) and how they are developed
Using data from the Climate Data Store and the SIS for your own applications

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Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Sectoral Application – Energy

Learn how climate change will affect the energy sector, which energy-related data and indicators are available from the CDS, and how these can be used in applications.

Level: Others

Certification course: No

What you'll learn:

Understand how climate change can affect the energy sector
What energy-related climate data and indicators are available on the Climate Data Store and how they were developed
Use the energy-related indicators to address climate change adaption challenges
Discover the C3S climate data explorer

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Forecasting: No

Machine learning: No

Numerical weather prediction: No

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Category: Climate

Sectoral Application – Tourism

An introduction to C3S applications in the tourism sector. It identifies C3S data and tools useful for tourism stakeholders in supporting climate change adaptation.

Level: Fundamentals

Certification course: No

What you'll learn:

Understand the main impacts of climate change on tourism
How to identify Climate Data Store (CDS) data and applications that are useful for tourism stakeholders in supporting climate change adaption
How to access and use data made available via the CDS and information on the tourism applications
Explore possible adaptions for the tourism sector

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Machine learning: No

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Category: Climate

Search results: 27