Sarah Strazzo

Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes

AbstractWhile a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results from other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences...

Observed versus GCM-Generated Local Tropical Cyclone Frequency: Comparisons Using a Spatial Lattice

Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resemblingactualTCs,butquestionsremainabouttheirfidelitytoobservedTCs.Heretheauthorsdemonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean‐Atmospheric Prediction Studies (COAPS) model over the common period 1982‐2008. Results show that the spatial distribution of TCs generated by the GFDL model compares well with observations globally, although there are areas of over- and underprediction, particularlyin parts ofthe PacificOcean. Difference maps using the spatial lattice highlightthese discrepancies. Additionally,comparisonsfocusingontheNorthAtlanticOceanbasinaremade.Resultsconfirmalargeareaof overprediction by the FSU COAPS model in the south-central portion of the basin. Relevant to projections of future U.S. hurricane activity is the fact that both models underpredict TC activity in the Gulf of Mexico.

Quantifying the sensitivity of maximum, limiting, and potential tropical cyclone intensity to SST: Observations versus the FSU/COAPS global climate model

Previous research quantified the sensitivity of limiting intensity to SST for observed tropical cyclones (TCs) and for TCs generated by two global climate models (GCMs). On average, a 1° C increase in sea surface temperature (SST) is associated with a 7.9 m s−1 increase in the statistical upper limit of observed intensity. Conversely, a 1°C increase in SST does not significantly affect the limiting intensity of GCM-generated TCs. The study presented here builds on previous research in two ways: (1) A comparison is made between the statistically defined limiting intensity and the physically defined potential intensity, and (2) a test is performed on the ability of a ∼0.94° resolution GCM to reproduce the observed statistical relationship between potential intensity and SST. Data from NASAs Modern Era Reanalysis are used to approximate the observed sensitivity of potential intensity to SST for the 1982–2008 time period. Results indicate that the sensitivity of potential intensity to SST is not statistically different from the sensitivity of observed maximum or limiting intensity to SST. This result links the statistically defined sensitivity to the physically based theory of hurricanes. Potential intensity is also estimated from the FSU/COAPS GCM. Although the FSU/COAPS model does not capture the observed sensitivity of TC maximum or limiting intensity to SST, the model reproduces the observed sensitivity of potential intensity to SST. The model generates suitable atmospheric conditions for the development of strong TCs, however strong TCs do not develop, possibly as a result of insufficient resolution.