Landfalling Tropical Cyclones: Directly Simulated vs. Statistically-Dynamically Downscaled
Open Access
- Author:
- Bolivar, Ana
- Graduate Program:
- Meteorology and Atmospheric Science
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- October 20, 2023
- Committee Members:
- Colin M. Zarzycki, Thesis Advisor/Co-Advisor
Melissa Marie Gervais, Committee Member
Paul Markowski, Program Head/Chair
Anthony Carl Didlake, Jr., Committee Member - Keywords:
- tropical cyclones
climate models
HighResMIP
statistical-dynamical downscaling
landfalls
tropical cyclone climatology - Abstract:
- We compare the representation of landfalling tropical cyclones (TCs) using two popular tools currently available for studying TC climatology: high-resolution climate models (which directly simulate TCs that can be tracked in model output) and statistical-dynamical downscaling (SDD) models (which use a model’s large-scale climatology to generate synthetic storms). To accomplish this, we analyze data from the High-Resolution Model Intercomparison Project (HighResMIP). Model TCs tracked by TempestExtremes are compared with observed landfalls using both the International Best Track Archive for Climate Stewardship and reanalysis storm tracks. We then leverage the SDD TC model described in \citet{lin2023} to create a parallel set of tracks using HighResMIP daily and monthly fields as forcings. We find that downscaling has the key advantage of being able to produce a large sample size of storms at the cost of producing unphysical behaviors that are not seen in directly simulated TCs. Downscaling results in more uniform behavior across models and there is some evidence of model biases being inherited. However, due to the limited sample size of directly simulated TCs for many HighResMIP products, there is a lack of a benchmark for comparing downscaled TC track patterns. Moreover, while either technique on its own has distinct advantages and disadvantages, comparing them gleans some information about the nature of biases inherent to HighResMIP TC climatology. Diagnostics from the SDD runs reveal that the mechanisms underlying biases in TC climatology vary across HighResMIP products. Increased cognizance of the strengths inherent to the techniques commonly used to understand future changes in TCs is crucial for increasing confidence in results of subsequent studies.