eas have greater variability in weather than average, and blue areas have less variability than average. In El Niño years, many areas have more variable weather than normal, while in La Niña years, many areas have less variable weather than normal. Even though La Niña may affect weather outside the tropics less than El Niño does, the effects of La Niña may be more predictable because the impact are less variable or uncertain.
The analysis and forecast of probability distributions and extreme event risks associated with El Niños and La Niñas can be improved by advances in large ensemble predictions. Sardeshmukh, Compo, and Penland's results illustrate the need for a large number of climate model simulations to distinguish between the "noise" associated with natural variability and the ENSO signal of an increase or decrease in the likelihood of climate extremes, especially to estimate reliably changes outside of the extratropics. This work also documented that the response to ENSO conditions is not a mirror image (symmetric). The weather event responses to El Niños tend to be stronger but more variable whereas the responses to La Niñas, though more consistent, are not as large.
Enhanced climate forecasting capabilities are needed to enable regional and national managers to plan for the impact of extreme weather events in response to future climate variability, and change. Improvements in the "physics" used in the construction of climate models can and will enhance simulation of climate variability (such as ENSO) and the associated impact or signal. However, equally important, and perhaps delivering a greater bang for the buck, is the approach of running a large number of simulations with an existing state-of-the-art climate model in order to resolve changes in the risk of extreme events associated with different climate conditions.
By documenting the importance of large sample size, this study will help other climate scientists refine their own research on detecting and forecasting ENSO impacts on weather making future climate weather forecasts more reliable.
- Prashant D. Sardeshmukh, Gilbert P. Compo, and Cécile Penland, 2000: Changes of Probability Associated with El Niño. J. Climate, 13, 4268–4286. doi:10.1175/1520-0442(2000)013<4268:COPAWE>2.0.CO;2
- Gilbert P. Compo, Prashant D. Sardeshmukh, and Cécile Penland, 2001: Changes of Subseasonal Variability Associated with El Niño. J. Climate, 14, 3356–3374. doi:10.1175/1520-0442(2001)014<3356:COSVAW>2.0.CO;2