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Blocks

Blocks

Climate

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Machine learning

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

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.

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MLWC MOOC 2: Concepts of Machine Learning in Weather and Climate

MLWC MOOC 2: Concepts of Machine Learning in Weather and Climate

Five modules covering decision trees, deep learning, uncertainty and generative models, and physics-guided approaches.

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MLWC MOOC 1: Introduction to Machine Learning in Weather and Climate

MLWC MOOC 1: Introduction to Machine Learning in Weather and Climate

Six modules introducing the main topics in machine learning in the context of weather and climate.

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Understanding Climate Data

Understanding Climate Data

From analysis of the past to future projections

Short online course
Because you don't have to be a climate scientist to make climate data work for you!

February 2026
Online, self-paced
8 hours

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Computing services and tools

Related tags:

computing
datasets
eccodes
visualisation

MLWC MOOC 1: Introduction to Machine Learning in Weather and Climate

MLWC MOOC 1: Introduction to Machine Learning in Weather and Climate

Six modules introducing the main topics in machine learning in the context of weather and climate.

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

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.

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Using ECMWF computing facilities: the batch system

Using ECMWF computing facilities: the batch system

This lesson focuses on ECGATE - ECMWF's server allocated for users' tasks, from submitting jobs to correcting errors.

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A starter guide to ecFlow

A starter guide to ecFlow

ecFlow is a workflow package that enables users to run a large number of programmes behind a firewall.

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ecCodes – Manipulating GRIB data with tools and API

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.

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MARS ECMWF's meteorological archive

MARS ECMWF's meteorological archive

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

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Metview for the Single-Column Model (SCM)

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.

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Exploring meteorological data through OGC web services

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.

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Introduction to Metview

Introduction to Metview

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

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ecCodes: Decoding with GRIB tools

ecCodes: Decoding with GRIB tools

ecCodes is an application programming interface developed by ECMWF to decode and encode in WMO GRIB format.

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Introduction to BUFR decoding with ecCodes

Introduction to BUFR decoding with ecCodes

ecCodes is an application programming interface developed by ECMWF to decode and encode in WMO GRIB and BUFR formats.

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MARS – advanced retrievals, data manipulation and computations

MARS – advanced retrievals, data manipulation and computations

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

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Forecasting

Related tags:

ensembles
uncertainty
Numerical weather prediction
products

Understanding Uncertainty in Weather Forecasts

Understanding Uncertainty in Weather Forecasts

Learn about the main sources of uncertainty in weather forecasting and how they are addressed in early warning systems.

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The ECMWF sub-seasonal (extended range) forecasts: Introduction

The ECMWF sub-seasonal (extended range) forecasts: Introduction

Learn about sources of predictability, seasonal forecast skill and the ECMWF sub-seasonal forecasting system.

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Ensemble Forecasting: Sources of forecast uncertainty (introduction)

Ensemble Forecasting: Sources of forecast uncertainty (introduction)

Learn about sources of error in NWP, how they are quantified, and how ensembles are evaluated.

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Forecast Jumpiness: An introduction

Forecast Jumpiness: An introduction

Learn about the ways in which forecast jumpiness can appear and how it can be mitigated.

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Seasonal forecasting

Seasonal forecasting

Learn about seasonal predictability, how numerical seasonal forecast models work and their outputs.

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The Extreme Forecast Index (EFI) and the Shift Of Tail (SOT) index

The Extreme Forecast Index (EFI) and the Shift Of Tail (SOT) index

Learn how EFI, SOT and Model Climate are built and provide forecast guidance for extreme, or severe weather events.

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Machine learning

Related tags:

Climate

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

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.

Click to enter this course

MLWC MOOC 2: Concepts of Machine Learning in Weather and Climate

MLWC MOOC 2: Concepts of Machine Learning in Weather and Climate

Five modules covering decision trees, deep learning, uncertainty and generative models, and physics-guided approaches.

Click to enter this course

MLWC MOOC 1: Introduction to Machine Learning in Weather and Climate

MLWC MOOC 1: Introduction to Machine Learning in Weather and Climate

Six modules introducing the main topics in machine learning in the context of weather and climate.

Click to enter this course

Numerical weather prediction

Related tags:

ensembles
clouds
convection
IFS
Forecasting
uncertainty
parameterisation
Physical processes

Understanding Uncertainty in Weather Forecasts

Understanding Uncertainty in Weather Forecasts

Learn about the main sources of uncertainty in weather forecasting and how they are addressed in early warning systems.

Click to enter this course

Ensemble Forecasting: Sources of forecast uncertainty (introduction)

Ensemble Forecasting: Sources of forecast uncertainty (introduction)

Learn about sources of error in NWP, how they are quantified, and how ensembles are evaluated.

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Forecast Jumpiness: An introduction

Forecast Jumpiness: An introduction

Learn about the ways in which forecast jumpiness can appear and how it can be mitigated.

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Cloud and precipitation parametrization 2: ice and mixed-phase microphysics

Cloud and precipitation parametrization 2: ice and mixed-phase microphysics

This lesson covers key processes in ice and mixed-phase clouds and precipitation, and parametrization uncertainties.

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Cloud and precipitation parametrization 1: overview and warm-phase microphysics

Cloud and precipitation parametrization 1: overview and warm-phase microphysics

Explore the key microphysical and warm-phase processes of cloud and precipitation parametrisation and their use in NWP.

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Land surface: introduction to cold processes

Land surface: introduction to cold processes

Learn about the unique role of snow in forecasting, from short-range to seasonal time scales.

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Parametrisation of diabatic processes - case studies (convection)

Parametrisation of diabatic processes - case studies (convection)

Four case studies exploring the conditions that cause deep convection, considering predictability and forecast errors.

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Introduction to the parametrization of sub-grid processes

Introduction to the parametrization of sub-grid processes

Learn how sub-grid-scale processes (not explicitly simulated in NWP), are parameterised and how challenges are overcome.

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An introduction to Data Assimilation

An introduction to Data Assimilation

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

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Satellite observations and their role in NWP

Satellite observations and their role in NWP

Learn about the role of satellite observations and measurements, and how these are assimilated and monitored for NWP.

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Representing model uncertainty with stochastic physics

Representing model uncertainty with stochastic physics

Explore sources of uncertainty in NWP and how this is represented in the IFS using stochastic physics.

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An introduction to single-column modelling

An introduction to single-column modelling

How SCM is used to investigate the physical processes of a global model in isolation, its applications and limitations.

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Sources of Uncertainty

Sources of Uncertainty

Learn about uncertainties and chaotic behaviour in NWP, why ensembles are needed and how they are used at ECMWF.

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Parametrisation of diabatic processes - Convection in the context of large-scale circulation

Parametrisation of diabatic processes - Convection in the context of large-scale circulation

This lesson will take you through what convection is and the phenomena it causes.

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Parametrization of diabatic processes - The mass-flux approach and the IFS scheme

Parametrization of diabatic processes - The mass-flux approach and the IFS scheme

This lesson looks at the three classes of parametrization schemes and the main characteristics of the IFS scheme.

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Introduction to Cloud Parametrisation

Introduction to Cloud Parametrisation

An introduction to the basic concepts for the design of a cloud and precipitation microphysics parametrisation.

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