logo CNR-IBE
Close this search box.

Seasonal Forecast
Course Package

A course package to share training resources.

A joint initiative of World Meteorological Organization and CNR-IBE, with the collaboration of MeteoSwiss.


Learning and teaching about seasonal climate  forecasts: a Mediterranean educational experience toward operational climate services. | Vieri Tarchiani et al. | Special Issue: 17th EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017

What is it

T.O.P. Seasonal Forecast is a shared set of online resources to enhance knowledge in the theory of seasonal forecasting and operational use of seasonal climate forecasts.

Play Video


The training materials

T.O.P. is based on the training materials produced for face-to-face-to-face courses organized from 2014-17. Created by acknowledged researchers and scholars for RTC Italy training initiatives, they have been reorganized in a new structure, partially re-edited, and enriched with videos and other documentations. These resources can be used by other trainers to develop their own courses.


The goal of the online course is to allow seasonal climate forecast knowledge transfer to increase operational capabilities of the targeted users. It provides theoretical and practical set of knowledge on seasonal forecast and predictability models, climate and data analysis, forecast verification, and specific application of seasonal forecast for agriculture and water management.

The Training content

The Structure

The course package includes model outline with learning objectives, case studies, in-depth studies, quizzes, structured bibliography, readings.


The Modules Structure

On the basis of previous training experiences, the project team defined the course modules structure to better respond to user learning needs


Selection and Analysis

The training materials from previous courses were selected and analyzed to fit the best set of resources for each module.


Training Materials

Slide presentations, with audio or annotated comments, videos, documents.

The Course Package is organized in modules where each module contains a group of lessons focusing a specific topic.

Essential guidelines

The T.O.P. Guide
for content adaptation.

To facilitate the course adoption by a wide number of institutions and instructors and to modify content to fulfill their region and national or institutional educational standards.

/audience /learners

This course is designed for forecasters and climatologists with knowledge on general meteorology as well as physical and dynamic meteorology. 

The course package addresses National hydro-meteorological service staff members who wish to improve climate services competencies or to specialize in Seasonal Forecasting. TOP provides theoretical and practical knowledge on seasonal forecast and predictability models, climate and data analysis, forecast verification, and specific application of seasonal forecast for agriculture and water management. 

To meet heterogeneous needs of the learners, each course unit will illustrate the prerequisites and will propose external resources to fill knowledge gaps.

Some of this content will be covered briefly in the context of offering more specific expertise in climate predictions.

This approach will provide learners with a personalised learning path based on their interaction with learning components, following the idea that it is more effective to take into account different levels and needs rather than “one size fits all”.

Pre-requisite Knowledge

Competency Framework

According to the Climate Services Competency Framework approved by the WMO Executive Council of June 2016, the training course addresses the Competency 3:

Create and/or interpret climate forecasts, climate projections and model output, and more specifically the following Performance Criteria.

Explore T.O.P.

The List of Modules
The course package is structured as an eLearning Course hosted in the WMO RTC Italy Moodle Environment.
You can login/register to create a personal account and set up a personal profile to enrol.