Abstract

Abstract When Hurricane Juan tracked toward Nova Scotia, Canada, in September 2003, forecasters were faced with the challenge of predicting the intensity and timing of the hurricane’s landfall. There were two competing factors dictating the storm’s intensity: 1) the decreasing sea surface temperatures (SSTs) over which the hurricane tracked that were conducive to weakening; and 2) the increased forward motion of the storm that enhanced the surface winds on the right (storm relative) side of the storm. Since Hurricane Juan was moving very quickly (forward speed approximately 15 m s−1) it spent less time over the cooler continental shelf waters between Nova Scotia and the >26°C water of the Gulf Stream than would have been the case for a slower-moving storm. However, those waters were warmer than normal during this event, by ∼4°C. It is argued that these warmer SSTs made a significant contribution (among other factors) to this rare category-2 hurricane at landfall in Nova Scotia. To assess the role of SSTs on the decay rate of Hurricane Juan, the Mesoscale Compressible Community model of the atmosphere is used. The model consists of a fixed, nested 3-km grid driven by a coarser 12-km grid, and is initiated using a synthetic hurricane vortex constructed from observational information such as storm size and intensity, thus giving a decent representation of the real storm. The model is initiated at 0000 UTC 28 September, when the hurricane was close to maximum intensity. An ensemble of experiments are conducted for each of two SST configurations: 1) analyzed SST of 28 September 2003 and 2) climatological SST representative of late September. Results from the 3-km simulations indicate that the intensity of Hurricane Juan’s maximum surface wind just prior to landfall was ∼5 m s−1 (±∼1.5 m s−1) weaker in the normal SST case, a result that is statistically significant at the 99% level. The destructiveness of the maximum landfall winds in the normal SST case is generally about 70% of that in the observed (warmer than normal) SST case. Model performance is measured using surface weather data, as well as data collected from a research aircraft that flew into the storm just prior to landfall.

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