Predictability of weather and climate

Abstract:

Abstract:

Heatwaves constitute a major threat to human health and ecosystems. Projected increases in heatwave frequency and severity thus lead to the need for prediction to enhance preparedness and minimize adverse impacts. In this Review, we document current capabilities for heatwave prediction at daily to decadal timescales and outline projected changes under anthropogenic warming. Various local and remote drivers and feedbacks influence heatwave development. On daily timescales, extratropical atmospheric blocking and global land–atmosphere coupling are most pertinent, and on subseasonal to seasonal timescales, soil moisture and ocean surface anomalies contribute. Knowledge of these drivers allows heatwaves to be skilfully predicted at daily to weekly lead times. Predictions are challenging beyond timescales of a few weeks, but tendencies for above-average temperatures can be estimated. Further into the future, heatwaves are anticipated to become more frequent, persistent and intense in nearly all inhabited regions, with trends amplified by soil drying in some areas, especially the mid-latitudes. There is also an increased occurrence of humid heatwaves, especially in southern Asia. A better understanding of the relevant drivers and their model representation, including atmospheric dynamics, atmospheric and soil moisture, and surface cover should be prioritized to improve heatwave prediction and projection.

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.