Forecasting the western Pacific subtropical high index during typhoon activity using a hybrid deep learning model

Seasonal location and intensity changes in the western Pacific subtropical high(WPSH)are important factors dominating the synoptic weather and the distribution and magnitude of precipitation in the rain belt over East Asia.Therefore,this article delves into the forecast of the western Pacific subtropical high index during typhoon activity by adopting a hybrid deep learning model.Firstly,the predictors,which are the inputs of the model,are analysed based on three characteristics:the first is the statistical discipline of the WPSH index anomalies corresponding to the three types of typhoon paths;the second is the correspondence of distributions between sea surface temperature,850 hPa zonal wind(u),meridional wind(v),and 500 hPa potential height field;and the third is the numerical sensitivity experiment,which reflects the evident impact of variations in the physical field around the typhoon to the WPSH index.Secondly,the model is repeatedly trained through the backward propagation algorithm to predict the WPSH index using 2011–2018 atmospheric variables as the input of the training set.The model predicts the WPSH index after 6 h,24 h,48 h,and 72 h.The validation set using independent data in 2019 is utilized to illustrate the performance.Finally,the model is improved by changing the CNN2D module to the DeCNN module to enhance its ability to predict images.Taking the 2019 typhoon“Lekima”as an example,it shows the promising performance of this model to predict the 500 hPa potential height field.

Westward Migration of Tropical Cyclone Activity in the Western North Pacific during 1982–2020:Features and Possible Causes

The westward migration of tropical cyclone(TC)activity has been identified in the western North Pacific(WNP),but the related features and causes remain elusive.Here,based on the best track data from China,Japan,and the US,and the NCEP–NCAR reanalysis data in 1982–2020,we investigate characteristics of the westward migration of the WNP TC activity with various metrics,and reveal possible causes for the migration of TC tracks through analyzing its seasonality and dependence on environmental conditions.The results show that the WNP TCs show significant westward migrations in a number of metrics,including location of tracks,genesis,the first track point at which TC reaches its lifetime-maximum intensity,and the last track point in the TC lifetime.It is found that TC tracks exhibit more significant westward migrations in the easterly steering flow than in the westerly steering flow.Meanwhile,the TC longitude shift shows notable seasonal variations,for which the TCs in the easterlies move further west than those in the westerlies during July–September,vice versa during October–December.The dependence of the westward migration of TC tracks on background steering flow is associated with the different environmental conditions.The westward shift in the westerly steering is mainly due to the reduced vertical wind shear(VWS),while the weakened zonal easterly steering and reduced VWS are both closely related to the westward migration in the easterly steering.These results have important implications for understanding current and future variations in TC longitude shift.

Determining Atmospheric Boundary Layer Height with the Numerical Differentiation Method Using Bending Angle Data from COSMIC

This paper presents a new method to estimate the height of the atmospheric boundary layer(ABL) by using COSMIC radio occultation bending angle(BA) data. Using the numerical differentiation method combined with the regularization technique, the first derivative of BA profiles is retrieved, and the height at which the first derivative of BA has the global minimum is defined to be the ABL height. To reflect the reliability of estimated ABL heights, the sharpness parameter is introduced, according to the relative minimum of the BA derivative. Then, it is applied to four months of COSMIC BA data(January, April, July, and October in 2008), and the ABL heights estimated are compared with two kinds of ABL heights from COSMIC products and with the heights determined by the finite difference method upon the refractivity data. For sharp ABL tops(large sharpness parameters), there is little difference between the ABL heights determined by different methods, i.e.,the uncertainties are small; whereas, for non-sharp ABL tops(small sharpness parameters), big differences exist in the ABL heights obtained by different methods, which means large uncertainties for different methods. In addition, the new method can detect thin ABLs and provide a reference ABL height in the cases eliminated by other methods. Thus, the application of the numerical differentiation method combined with the regularization technique to COSMIC BA data is an appropriate choice and has further application value.

Study and application of an improved four-dimensional variational assimilation system based on the physical-space statistical analysis for the South China Sea

The four-dimensional variational assimilation(4D-Var)has been widely used in meteorological and oceanographic data assimilation.This method is usually implemented in the model space,known as primal approach(P4D-Var).Alternatively,physical space analysis system(4D-PSAS)is proposed to reduce the computation cost,in which the 4D-Var problem is solved in physical space(i.e.,observation space).In this study,the conjugate gradient(CG)algorithm,implemented in the 4D-PSAS system is evaluated and it is found that the non-monotonic change of the gradient norm of 4D-PSAS cost function causes artificial oscillations of cost function in the iteration process.The reason of non-monotonic variation of gradient norm in 4D-PSAS is then analyzed.In order to overcome the non-monotonic variation of gradient norm,a new algorithm,Minimum Residual(MINRES)algorithm,is implemented in the process of assimilation iteration in this study.Our experimental results show that the improved 4D-PSAS with the MINRES algorithm guarantees the monotonic reduction of gradient norm of cost function,greatly improves the convergence properties of 4D-PSAS as well,and significantly restrains the numerical noises associated with the traditional 4D-PSAS system.