EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Climate services for the retail sectors: the Filomena’s case

Albert Martínez Botí1, Lluís Palma1, Francesc Roura1, Andrea Manrique-Suñén1, Nube González-Reviriego1, Raül Marcos1,3, Sergio González2, Antonio López2, and Albert Soret1
Albert Martínez Botí et al.
  • 1Barcelona Supercomputing Center, Earth Sciences, Barcelona, 08034, Spain
  • 2Decathlon España, San Sebastian de los Reyes, Madrid, Spain
  • 3Universitat de Barcelona, Barcelona, 08007, Spain

The need of filling the gap between medium-range weather (up to 10-15 days) and seasonal forecasts (3–6 months) has led to several operational weather and climate centres to include the subseasonal forecasting in their predictions. Although this kind of information is starting to be explored by some stakeholders, such as renewable energy, water management, agriculture or disaster prevention, there are still much more sectors who can exploit this information. In this contribution, we will present how this type of climate information is used by the retail sector, in particular by a well known French sporting goods retailer within their operations over Spain. Having reliable climate forecasts weeks in advance would allow to manage the stock, redistribute it along with different warehouses and take different advertising campaigns and prices policies to avoid both the extra-cost that implies keeping what is not sold and running out of products. A recent proof of the influence of climate on sporting goods sales has been evidenced by the large increase in sales of mountain and snow equipment during Filomena’s episode, which violently hit the south-west, centre and north-east of the Iberian Peninsula in January 2021. Trustworthy subseasonal forecasts could be equally useful during other times of the year to make some decisions, such as extending or shortening the summer sports season. To illustrate the potential of these types of climate predictions, a case study for the Filomena event in January 2021 is presented. The sub-seasonal NCEP-CFS v2 prediction system has been used to compute the probability of each tercile category for surface temperature (above-normal, below-normal or normal - where normal is the average over a reference period). Forecasts for weekly temperature were calibrated using as reference the ERA-5 reanalysis dataset and the regions with negative skill were masked. It is interesting to point out how the predictions issued three weeks in advance already indicated that surface temperature would be below normal over Spain.

How to cite: Martínez Botí, A., Palma, L., Roura, F., Manrique-Suñén, A., González-Reviriego, N., Marcos, R., González, S., López, A., and Soret, A.: Climate services for the retail sectors: the Filomena’s case, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15813,, 2021.


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