Assessing the Model for Prediction Across Scales (MPAS) for Studies on the Extratropical Transition of Tropical Cyclones and Climate Change

Recurving tropical cyclones (TCs), and those undergoing extratropical transition (ET) can develop into rapidly intensifying systems bringing TC-like conditions (e.g., intense rainfall, strong winds, large waves) to areas far removed from the original TC, such as Canada, Europe, the northeast U.S., or the Pacific Northwest, that are not typically accustomed to such events. Recent examples of ET events that affected the U.S. include Irene (2011) and Sandy (2012). While previous research has looked extensively at the ET process and climate change effects on tropical cyclones, relatively few studies have looked into how ET events may be affected by climate change.

The overall objective of this project is to examine how the intensity and frequency of TCs undergoing ET will be affected by climate change. This is a complicated problem as it is affected by both changes in TCs (e.g., frequency, intensity, size) as well as changes in the midlatitude environment. First, initial model verification concerning the treatment of large-scale mean fields such as jet stream location, annual precipitation patterns, and stationary pressure systems is completed. Additionally, the feasibility of representing these phenomena with MPAS, both individually and on the climatological scale, must be explored. To do this, multi-seasonal simulations are conducted using the Model for Prediction Across Scales (MPAS). The model domain uses a variable resolution mesh with 15-km grid spacing throughout the Northern Hemisphere expanding out to 60-km across the Southern Hemisphere. These simulations span a series of years representing a variety of environments (e.g., a strong El Niño, a strong La Niña, an anomalously active year in each Northern Hemispheric TC basin, an anomalously inactive year in each Northern Hemispheric TC basin, etc.). A tropical cyclone detection algorithm is applied to the model output to gather statistics on model simulated TCs and ET events. These results are verified against observations (e.g., the IBTrACS dataset) and reanalysis data (e.g., 0.75º ERA-Interim) to determine if MPAS provides an accurate representation of climatological TC activity.

These multi-seasonal simulations are then repeated using a pseudo-global climate change (PGCC) technique following the IPCC AR5 RCP 8.5 emissions scenario to allow for assessment of the model climate (e.g., jet stream strength and location, precipitation patterns, etc.) under future climate conditions, as well as climate change effects on the model TC and ET event statistics.