Tag - Forecasting | ECMWF eLearning

Understanding Uncertainty in Weather Forecasts

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

Level: Others

Certification course: No

What you'll learn:

In this eLearning module, we explain the basics of weather forecast uncertainty and how it can be accounted for when communicating forecasts through a forecast ‘value chain’. In this module, your learning level will be assessed through a set of quiz questions.

Hide last updated info: No

Hide number of enrollments: No

Hide full description label: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: Yes

Machine learning: No

Numerical weather prediction: Yes

Click to enter this course

Category: Forecasting

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

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

Level: Fundamentals

Certification course: No

What you'll learn:

An overview of ECMWF forecasts at medium, sub-seasonal and seasonal ranges
The basis of sub-seasonal forecasts
The ECMWF sub-seasonal ensemble forecasting system
Evaluation and performance of sub-seasonal forecasts

Full description:

Sub-seasonal (or extended range) forecasts provide outlooks up to 46 days. This lesson examines sources of predictability, seasonal forecast skill and the ECMWF sub-seasonal forecasting system.

Estimated duration: 40 minutes

Hide last updated info: No

Hide number of enrollments: No

Hide full description label: 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: Forecasting

Ensemble Forecasting: Sources of forecast uncertainty (introduction)

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

Level: Fundamentals

Certification course: No

What you'll learn:

Sources of forecast uncertainty
How ensembles quantify forecast uncertainty
How to extract information from the ensemble and evaluate performance
Communicating uncertainty

Full description:

Ensembles are run to account for uncertainties in initial conditions. This lesson explores the sources of error in NWP, how they are quantified, and how ensembles are evaluated.

Estimated duration: 40 minutes

Hide last updated info: No

Hide number of enrollments: No

Hide full description label: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: Yes

Click to enter this course

Category: Forecasting

Forecast Jumpiness: An introduction

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

Level: Fundamentals

Certification course: No

What you'll learn:

What is forecast jumpiness?
Examples of jumpiness
Jumpiness in the context of ensembles
How dynamic sensitivities relate to jumpiness

Full description:

There are times when consecutive forecasts can 'jump' significantly. This lesson will discuss the ways in which forecast jumpiness can appear and how it can be mitigated.

Estimated duration: 30 minutes

Hide last updated info: No

Hide number of enrollments: No

Hide full description label: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: No

Machine learning: No

Numerical weather prediction: Yes

Click to enter this course

Category: Forecasting

Seasonal forecasting

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

Level: Fundamentals

Certification course: No

What you'll learn:

What seasonal forecasting is, why it is useful, and some common methods
How numerical seasonal forecasts work
What seasonal forecasts look like, and how to interpret them
Challenges and prospects in seasonal forecasting and skill limits

Full description:

Seasonal forecasting is useful in planning for many sectors. This lesson will explore seasonal predictability, how numerical seasonal forecast models work and their outputs.

Estimated duration: 40 minutes

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Hide number of enrollments: No

Hide full description label: 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: Forecasting

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.

Level: Fundamentals

Certification course: No

What you'll learn:

How the Extreme Forecast Index (EFI) and the Shift Of Tail (SOT) index and Model Climate (M-climate) are built, and how they relate to one another
Limitations of these methods
Case studies

Prerequisites:

Experience in meteorology and forecasting
Basic statistics (probability distributions)

Full description:

This lesson introduces the Extreme Forecast Index (EFI), which provides specialised guidance for identifying anomalous, extreme, or severe weather events. You will learn how the EFI, the Shift of Tails (SOT), and Model Climate are constructed, and how they relate to one another.

Estimated duration: 25 minutes

Hide last updated info: No

Hide number of enrollments: No

Hide full description label: No

Atmospheric composition: No

Climate: No

Computing services and tools: No

Data applications: No

Forecasting: Yes

Machine learning: No

Numerical weather prediction: No

Click to enter this course

Category: Forecasting

Forecasting

Courses tagged with "Forecasting"