La Ni˜na – the cold phase of the El Ni˜no/Southern Oscillation (ENSO) phenomenon – is associated with drought over the US. In contrast, El Ni˜no – the warm phase of ENSO – brings increased precipitation to the southern portion of the country. Importantly, these two phases of the ENSO cycle exhibits asymmetric duration: while El Ni˜no events typically terminate after one year, La Ni˜na events, in contrast, commonly extend over two or more consecutive years.
We propose a suite of numerical simulations and observational analyses to advance the understanding of the predictability of persistent drought conditions over the US during La Ni˜na years. Our project addresses two overlooked issues of relevance to the prediction of La Ni˜na droughts over North America. First, the predictability of the duration of La Ni˜na events is unknown. Second, observations show that droughts initiated by La Ni˜na intensify and expand during the second year of the event. Thus additional mechanisms such as seasurface temperature anomalies from outside the tropical Pacific, or local land-atmosphere interactions must play an important role, exacerbating the drought’s magnitude and spatial extent. We will address these gaps by 1) diagnosing the physical processes responsible for the second year intensification of La Ni˜na droughts from a suite of observational datasets and simulations, 2) evaluating the ability of operational forecast systems to simulate 2–yr La Ni˜na events and their predictability, and 3) quantifying the potential predictability of 2–yr La Ni˜na events in a “perfect model” framework.
Skillful prediction of multi–year La Ni˜na could have a large impact in the ability to predict persistent drought conditions over a large portion of the United States. While much emphasis has been placed upon the onset of drought, the fact that historical La Ni˜na droughts have lasted more than 1 year is a reminder of how important the prediction of La Ni˜na duration/termination is. The proposed research will explore the dynamics of these processes in observations, forecast systems, and climate models with the ultimate goal of quantifying how predictable the duration of La Ni˜na droughts is. In particular we will quantify whether the return of La Ni˜na for a consecutive year can be predicted 18 and 6 months in advance.
Addressing the two gaps outlined above will directly contribute to the objectives of MAPP’s competition: “Research to Advance Understanding, Monitoring, and Prediction of Drought” because it will lead to more skillful and reliable drought forecasts at regional scales and adequate lead times needed by drought stakeholders. The core capabilities and research efforts resulting from our project will allow progress to be made toward the provision of sustained, reliable, and timely climate services related to water resources. Having the capacity to provide accurate predictions on drought termination several seasons in advance could greatly reduce the severity of social and economic damage caused by drought, a leading natural hazard for North America. Determining whether the duration of La Ni˜na droughts can be predicted directly contributes to NOAAs long-term climate goal because it improves the scientific understanding of the changing climate system and its impacts as stated by the first objective outlined by NOAA’s Next Generation Strategic Plan.