EAPSI: Investigating the Influence of the Madden-Julian Oscillation on Northern Hemisphere Winter Blocking in General Circulation Models

Henderson Stephanie A, Fort Collins CO

Investigators

Abstract

Blocking refers to a large-scale quasi-stationary high pressure that can persist for up to weeks at a time, leading to sudden long-lasting cold snaps and precipitation extremes during winter. Understanding weather extremes in a changing climate requires understanding blocking in a changing climate. This is done using General Circulation Models (GCMs), which allow scientists to alter greenhouse gases to understand the possible consequences to atmospheric phenomena. Studies have shown that blocking is poorly simulated in GCMs, resulting in blocking biases with consequences for extreme events. This award supports research to understand if blocking biases in GCMs can be reduced by improving the model Madden-Julian Oscillation (MJO). The MJO is characterized by eastward propagating convective anomalies emitting large-scale atmospheric waves that impact blocking at higher latitudes. The research will investigate how model blocking is influenced by the model MJO in collaboration with Dr. Seok-Woo Son, a specialist in extratropical dynamics, at Seoul National University in Seoul, South Korea. The research hypothesizes that in order to improve model blocking, the model MJO must be improved in addition to the model basic state, which determines the pathway of the MJO-induced Rossby waves that impact blocking. The hypothesis will be tested by analyzing and comparing between six GCMs within the Fifth phase of the Coupled Model Intercomparison Project (CMIP5), where three simulate a fairly realistic MJO and three a poor MJO as determined by diagnostics of the MJO Task Force. MJO phases will be derived by projecting model data onto the leading patterns of reanalysis-derived fields, and the Rossby wave pathway will be analyzed using wave activity flux analysis. Model blocking frequencies will be calculated per MJO phase, and results will be compared to reanalysis. Results will then be used to understand how the model MJO may contribute to blocking biases. This NSF EAPSI award is funded in collaboration with the National Research Foundation of Korea.