A Logistic-growth-equation-based Intensity Prediction Scheme for Western North Pacific Tropical Cyclones

Accurate prediction of tropical cyclone(TC)intensity remains a challenge due to the complex physical processes involved in TC intensity changes.A seven-day TC intensity prediction scheme based on the logistic growth equation(LGE)for the western North Pacific(WNP)has been developed using the observed and reanalysis data.In the LGE,TC intensity change is determined by a growth term and a decay term.These two terms are comprised of four free parameters which include a time-dependent growth rate,a maximum potential intensity(MPI),and two constants.Using 33 years of training samples,optimal predictors are selected first,and then the two constants are determined based on the least square method,forcing the regressed growth rate from the optimal predictors to be as close to the observed as possible.The estimation of the growth rate is further refined based on a step-wise regression(SWR)method and a machine learning(ML)method for the period 1982−2014.Using the LGE-based scheme,a total of 80 TCs during 2015−17 are used to make independent forecasts.Results show that the root mean square errors of the LGE-based scheme are much smaller than those of the official intensity forecasts from the China Meteorological Administration(CMA),especially for TCs in the coastal regions of East Asia.Moreover,the scheme based on ML demonstrates better forecast skill than that based on SWR.The new prediction scheme offers strong potential for both improving the forecasts for rapid intensification and weakening of TCs as well as for extending the 5-day forecasts currently issued by the CMA to 7-day forecasts.

Evaluation of the Madden-Julian oscillation in HiRAM

The aim of this study was to understand the cause of Madden–Julian oscillation(MJO)bias in the High Resolution AtmosphericModel(HiRAM)driven by observed SST through process-oriented diagnosis.Wavenumber-frequency power spectrum and composite analyses indicate that HiRAM underestimates the spectral amplitude over theMJO band and mainly produces non-propagating rather than eastward-propagating intraseasonal rainfall anomalies,as observed.Column-integrated moist static energy(MSE)budget analysis is conducted to understand the MJO propagation bias in the simulation.It is found that the bias is due to the lack of a zonally asymmetric distribution of the MSE tendency anomaly in respect to the MJO convective center,which is mainly attributable to the bias in vertical MSE advection and surface turbulent flux.Further analysis suggests that it is the unrealistic simulation of MJO vertical circulation anomalies in the upper troposphere as well as overestimation of the Rossby wave response that results in the bias.