Uncertainty in TC Maximum Intensity with Fixed Ratio of Surface Exchange Coefficients for Enthalpy and Momentum

The classical tropical cyclone(TC)maximum intensity theory of Emanuel suggests that the maximum azimuthal wind of TC depends linearly on the ratio of surface exchange coefficients for enthalpy and momentum(C_(k)and C_(d)).In this study,a series of sensitivity experiments are conducted with the three-dimensional Cloud Model 1(CM1),by fixing the ratio of C_(k)/C_(d)but varying the specific values of C_(k)and C_(d)simultaneously.The results show significant variations in the simulated TC maximum intensity by varying C_(k)and C_(d),even if their ratio is fixed.Overall,the maximum intensity increases steadily with increasing C_(k)and C_(d)when their value is smaller than 1.00×10^(-3),and then this increasing trend slows down with further increases in the coefficients.Two previous theoretical frameworks—one based on gradient wind balance and the other incorporating the unbalanced terms-are applied to calculate the maximum potential intensity(PI).The calculated value of the former shows little variation when varying the specific values of C_(k)and C_(d),while the latter shows larger values with increases in both C_(k)and C_(d).Further examination suggests that the unbalanced effect plays a key role in contributing to the increasing intensity with increasing C_(k)and C_(d).

Multi-Factor Intensity Estimation for Tropical Cyclones in the Western North Pacific Based on the Deviation Angle Variance Technique

In this paper, the infrared cloud images from Fengyun series geostationary satellites and the best track data from the China Meteorological Administration(CMA-BST) in 2015–2017 are used to investigate the effects of two multifactor models, generalized linear model(GLM) and long short-term memory(LSTM) model, for tropical cyclone(TC) intensity estimation based on the deviation angle variance(DAV) technique. For comparison, the typical singlefactor Sigmoid function model(SFM) with the map minimum value of DAV is also used to produce TC intensity estimation. Sensitivity experiments regarding the DAV calculation radius and different training data groups are conducted, and the estimation precision and optimum calculation radius for DAV in the western North Pacific(WNP) are analyzed. The results show that the root-mean-square-error(RMSE) of the single-factor SFM is 8.79–13.91 m s^-1 by using the individual years as test sets and the remaining two years as training sets with the optimum calculation radius of 550 km. However, after selecting and using the high-correlation multiple factors from the same test and training data, the RMSEs of GLM and LSTM models decrease to 5.93–8.68 and 4.99–7.00 m s^-1 respectively, with their own optimum calculation radii of 350 and 400 km. All the sensitivity experiments indicate that the SFM results are significantly influenced by the DAV calculation radius and characteristics of the training set data, while the results of multi-factor models appear more stable. Furthermore, the multi-factor models reduce the optimum radius within the process of DAV calculation and improve the precision of TC intensity estimation in the WNP, which can be chosen as an effective approach for TC intensity estimation in marine areas.