EGU22-742
https://doi.org/10.5194/egusphere-egu22-742
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Ensemble forecast of the Madden Julian Oscillation using a stochastic weather generator based on analogs of  Z500

Meriem Krouma1,2, Pascal Yiou2, and Riccardo Silini3
Meriem Krouma et al.
  • 1ARIA Technologies, 8 Rue de la Ferme, 92100 Boulogne-Billancourt, France.
  • 2Laboratoire des Sciences du Climat et de l’Environnement, UMR 8212 CEA-CNRS-UVSQ, IPSL & U Paris-Saclay, 91191 Gif-sur-Yvette, France. (meriem.krouma@lsce.ipsl.fr)
  • 3Departament de Fisica, Universitat Politècnica de Catalunya, Edifici Gaia, Rambla Sant Nebridi 22, 08222 Terrassa, Barcelona, Spain.

Skillful forecast of the Madden Julian Oscillation (MJO) has an important scientific interest because the MJO represents one of the most important sources of  sub-seasonal predictability. Proxies of the MJO can be derived from the first principal components of wind speed and outgoing longwave radiation (OLR) in the Tropics (RMM1 and RMM2). The challenge is to forecast these two indices. This study aims at providing ensemble forecasts MJO indices  from analogs of the atmospheric circulation, mainly the geopotential at 500 hPa (Z500) by using a stochastic weather generator. We generate an ensemble of 100 members for the amplitude and the RMMs for sub-seasonal lead times (from 2 to 4 weeks). Then we evaluate the skill of the ensemble forecast and the ensemble mean using respectively probabilistic and deterministic skill scores. We found that a reasonable forecast could reach 40 days for the different seasons. We compared our SWG forecast with other forecasts of the MJO.

How to cite: Krouma, M., Yiou, P., and Silini, R.: Ensemble forecast of the Madden Julian Oscillation using a stochastic weather generator based on analogs of  Z500, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-742, https://doi.org/10.5194/egusphere-egu22-742, 2022.

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