Abstract
A computationally efficient method of producing tropical cyclone (TC) wind analyses is developed and tested, using a hindcast methodology, for 12 Gulf of Mexico storms. The analyses are created by blending synthetic data, generated from a simple parametric model constructed using extended best-track data and climatology, with a first-guess field obtained from the NCEP–NCAR North American Regional Reanalysis (NARR). Tests are performed whereby parameters in the wind analysis and vortex model are varied in an attempt to best represent the TC wind fields. A comparison between nonlinear and climatological estimates of the TC size parameter indicates that the former yields a much improved correlation with the best-track radius of maximum wind rm. The analysis, augmented by a pseudoerror term that controls the degree of blending between the NARR and parametric winds, is tuned using buoy observations to calculate wind speed root-mean-square deviation (RMSD), scatter index (SI), and bias. The bias is minimized when the parametric winds are confined to the inner-core region. Analysis wind statistics are stratified within a storm-relative reference frame and by radial distance from storm center, storm intensity, radius of maximum wind, and storm translation speed. The analysis decreases the bias and RMSD in all quadrants for both moderate and strong storms and is most improved for storms with an rm of less than 20 n mi. The largest SI reductions occur for strong storms and storms with an rm of less than 20 n mi. The NARR impacts the analysis bias: when the bias in the former is relatively large, it remains so in the latter.
Assimilating All-Sky Himawari-8 Satellite Infrared Radiances: A Case of Typhoon Soudelor (2015)
