Predictability of weather and climate

Abstract:

Despite the growing demand for long-range ENSO predictions beyond one year, quantifying the skill at these lead-times remains limited. This is partly due to inadequate long-records of seasonal reforecasts that make skill estimates of irregular ENSO events quite challenging. Here, we investigate ENSO predictability and the dependency of prediction skill on the ENSO cycle using 110-years of 24-month-long 10-member ensemble reforecasts from ECMWF’s coupled model (SEAS5-20C) initialised on 1st Nov/1st May during 1901-2010. Results show that Nino3.4 SST can be skilfully predicted up to ~18 lead months when initialised on 1st Nov, but skill drops at ~12 lead months for May starts that encounter boreal spring predictive barrier in year 2. The skill beyond the first year is highly conditioned to the phase of ENSO: Forecasts initialised at peak El Niño are more skilful in year 2 than those initialised at peak La Niña, with the transition to La Niña being more predictable than to El Niño. This asymmetry is related to the subsurface initial conditions in the western equatorial Pacific: peak El Niño states evolving into La Niña are associated with strong upper ocean heat discharge of the western Pacific, the memory of which stays beyond one year. In contrast, the western Pacific recharged state associated with La Niña is usually weaker and shorter-lived, being a weaker pre-conditioner for subsequent El Niño, the year after. High prediction skill of ENSO events beyond one year provides motivation for extending the lead-time of operational seasonal forecasts up to 2 years.