Examining Changes in North Atlantic Extratropical Cyclones with Climate Change
Previous work on this topic points to a consensus that a future climate will bring a reduction in the overall number of extratropical cyclones with a subsequent increase in the quantity of strongest storms. Results from Cipullo (2013), for example, show evidence of the stronger storms becoming stronger.
The focus of this study is to not only examine how the broad spectrum of these systems is evolving, but why these changes are taking place. Furthermore, we aim to contribute to the current literature by expanding on previous high-resolution analyses.
Our data set, as outlined by Cipullo (2013), consists of 10 winters simulated by the Weather Research and Forecasting (WRF) model, spanning the North Atlantic region with a horizontal grid spacing of 20 km. To assess the effects of climate change, a pseudo-global warming approach is taken to simulate the same 10 winter seasons in a warmer climate. This technique utilizes temperature changes derived from both a subset of CMIP3 models using the IPCC AR4 A2 scenario and a subset of CMIP5 models using the RCP 8.5 scenario.
The first step in investigating changes in extratropical cyclones is to impose a tracking algorithm on our data set. This project utilizes the MAP Climatology of Mid-latitude Storminess (MCMS) to identify and track cyclones over the North Atlantic. MCMS identifies cyclones as minima in the sea level pressure field and then matches them with candidate cyclones at the previous time step to form cyclone tracks.
First, we plan to inspect changes in overall cyclone and track density, as well as areas of genesis and lysis, between current and future climates. This enables us to expand on preliminary results from Cipullo (2013) showing evidence for a slight poleward shift in the storm track and a potential enhancement of cyclogenesis within the North Atlantic basin. Next, changes in cyclone deepening rates, as well as cyclone lifetime will be investigated. Once the changes between current and future climates have been quantified, a more dynamical analysis will take place to examine why these changes are occurring. This analysis will involve assessing changes in fields including, but not limited to, wind, potential vorticity, and precipitation. For example, Cipullo (2013) found general agreement in areas of increased precipitation with areas of stronger storms in a future climate, a correlation that needs to be investigated further.
We also plan to examine the sensitivity of the changes induced by climate change signals to changes due to small variations in the cyclone identification technique, as well as to using CMIP3 versus CMIP5 models to simulate the future winters for our data set.
While previous studies have examined changes in extratropical cyclones with a warming climate, the utilization of MCMS and this unique data set allows us to shed a different light on the problem and delve more into the dynamical changes taking place to one of our most influential weather phenomena.