CHGS method for numerical forecasting of typhoon waves-Ⅰ. Spectrum of waves in growing phase

Owing to the fact that the wind speed and direction of typhoon vary rapidly with time and space in typhoon fetch; the nearer to the typhoon eye the greater the wind velocity, and the shorter the wind fetch the smaller the wind time,as a result,the more difficult for the wind wave to fully grow. Hence.in typhoon wave numerical calculation it is impossible to use the model for a fully grown wave spectrum. Lately, the author et at. presented a CHGS method for numerical forecasting of typhoon waves, where a model for the growing wave spectrum was set up (see Eq. (2) in the text). The model involves a parameter indicating the growing degree of wind wave, i. e. ,the mean wave age β. When βvalue is small, the wave energy is chiefly concentrated near the peak frequency, so that the spectral peak gets high and steep; with the increase of β the spectral shape gradually gets lower and gentler; when β=Ⅰ, the wave fully grows, the growing spectrum becomes a fully grown P-M spectrum. The model also shows a spectral “overshooting” phenomenon within the “balance zone”.

CORRECTION OF ASYMMETRIC STRENGTHENING OF QUIKSCAT WIND FIELD AND ASSIMILATION APPLICATION IN TYPHOON SIMULATION

As an approach to the technological problem that the wind data of QuikSCAT scatterometer cannot accurately describe the zone of typhoon-level strong wind speed, some objective factors such as the typhoon moving speed, direction and friction are introduced in this study to construct the asymmetric strengthening of the QuikSCAT wind field. Then by adopting a technology of four-dimensional data assimilation, an experiment that includes both the assimilation and forecasting phases is designed to simulate Typhoon Rananim numerically. The results show that with model constraints and adjustment, this technology can incorporate the QuikSCAT wind data to the entire column of the model atmosphere, improve greatly the simulating effects of the whole-column wind, pressure field and the track as well as the simulated typhoon intensity covered by the forecast phase, and work positively for the forecasting of landfall locations.

Impacts of Multigrid NLS-4DVar-based Doppler Radar Observation Assimilation on Numerical Simulations of Landfalling Typhoon Haikui (2012)

We applied the multigrid nonlinear least-squares four-dimensional variational assimilation(MG-NLS4DVar)method in data assimilation and prediction experiments for Typhoon Haikui(2012)using the Weather Research and Forecasting(WRF)model.Observation data included radial velocity(Vr)and reflectivity(Z)data from a single Doppler radar,quality controlled prior to assimilation.Typhoon prediction results were evaluated and compared between the NLS-4DVar and MG-NLS4DVar methods.Compared with a forecast that began with NCEP analysis data,our radar data assimilation results were clearly improved in terms of structure,intensity,track,and precipitation prediction for Typhoon Haikui(2012).The results showed that the assimilation accuracy of the NLS-4DVar method was similar to that of the MG-NLS4DVar method,but that the latter was more efficient.The assimilation of Vr alone and Z alone each improved predictions of typhoon intensity,track,and precipitation;however,the impacts of Vr data were significantly greater that those of Z data.Assimilation window-length sensitivity experiments showed that a 6-h assimilation window with 30-min assimilation intervals produced slightly better results than either a 3-h assimilation window with 15-min assimilation intervals or a 1-h assimilation window with 6-min assimilation intervals.

The Sensitive Regions Identified by CNOPs of Three Typhoon Events

In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.

A numerical simulation of latent heating within Typhoon Molave

The weather research and forecasting（WRF） model is a new generation mesoscale numerical model with a fine grid resolution（2 km）, making it ideal to simulate the macro-and micro-physical processes and latent heating within Typhoon Molave（2009）. Simulations based on a single-moment, six-class microphysical scheme are shown to be reasonable, following verification of results for the typhoon track, wind intensity, precipitation pattern, as well as inner-core thermodynamic and dynamic structures. After calculating latent heating rate, it is concluded that the total latent heat is mainly derived from condensation below the zero degree isotherm, and from deposition above this isotherm. It is revealed that cloud microphysical processes related to graupel are the most important contributors to the total latent heat. Other important latent heat contributors in the simulated Typhoon Molave are condensation of cloud water, deposition of cloud ice, deposition of snow, initiation of cloud ice crystals, deposition of graupel, accretion of cloud water by graupel, evaporation of cloud water and rainwater,sublimation of snow, sublimation of graupel, melting of graupel, and sublimation of cloud ice. In essence, the simulated latent heat profile is similar to ones recorded by the Tropical Rainfall Measuring Mission, although specific values differ slightly.

A baroclinic typhoon model with a moving multi-nested grid andvariational adjustment initializationII. Forecast experiments

A 3-dimensional baroclinic typhoon model with a moving multi-nested grid and its initialization are described first. Prediction results are improved by using a simple but effective data assimilation method in which the initial field is adjusted by the sixth hour's typhoon report and the weak-constraint variational principle. Finally someforecast examples made by this typhoon model are given.

Prediction of Typhoon Tracks Using Dynamic Linear Models

This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis of typhoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive model for the prediction of typhoon tracks.

SEA SURFACE TEMPERATURE RESPONSE TO TYPHOON MORAKOT(2009) AND ITS INFLUENCE

While previous studies indicate that typhoons can decrease sea surface temperature(SST) along their tracks, a few studies suggest that the cooling patterns in coastal areas are different from those in the open sea. However, little is known about how the induced cooling coupled with the complex ocean circulation in the coastal areas can affect tropical cyclone track and intensity. The sea surface responses to the land falling process of Typhoon Morakot(2009) are examined observationally and its influences on the activity of the typhoon are numerically simulated with the WRF model. The present study shows that the maximum SST cooling associated with Morakot occurred on the left-hand side of the typhoon track during its landfall. Numerical simulations show that, together with the SST gradients associated with the coastal upwelling and mesoscale oceanic vortices, the resulting SST cooling can cause significant difference in the typhoon track, comparable to the current 24-hour track forecasting error. It is strongly suggested that it is essential to include the non-uniform SST distribution in the coastal areas for further improvement in typhoon track forecast.

EXPERIMENTS OF ENSEMBLE FORECAST OF TYPHOON TRACK USING BDA PERTURBING METHOD

A new method, BDA perturbing, is used in ensemble forecasting of typhoon track. This method is based on the Bogus Data Assimilation scheme. It perturbs the initial position and intensity of typhoons and gets; a series of bogus vortex. Then each bogus vortex is used in data assimilation to obtain initial conditions. Ensemble forecast members are constructed by conducting simulation with these initial conditions. Some cases of typhoon are chosen to test the validity of this new method and the results show that： using the BDA perturbing method to perturb initial position and intensity of typhoon for track tbrecast can improve accuracy, compared with the direct use of the BDA assimilation scheme. And it is concluded that a perturbing amplitude of intensity of 5 hPa is probably more appropriate than 10 hPa if the BDA perturbing method is used in combination with initial position perturbation.

THE ENSEMBLE FORECASTING OF TROPICAL CYCLONE MOTION I:USING A PRIMITIVE EQUATION BAROTROPIC MODEL

Ensemble forecasting of tropical cyclone (TC) motion was studied using a primitive equation barotropic model by perturbing initial position and structure for 1979 1993 TC. The results show that TC initial position perturbation affects its track, but the ensemble mean is close to control forecast. Experiments was also performed by perturbing TC initial parameters which were used to generate TC initial field, and more improvement can be obtained by taking ensemble mean of selective member than selecting members randomly. The skill of 60 % 70 % of all cases is improved in selective ensemble mean. When the ambient steering current is weak, more improvement can be obtained over the control forecast.

Combinatorial Optimization of Physics Parameterization Schemes for Typhoon Simulation Based on a Simple Genetic Algorithm(SGA)

Each physical process in a numerical weather prediction(NWP)system may have many different parameterization schemes.Early studies have shown that the performance of different physical parameterization schemes varies with the weather situation to be simulated.Thus,it is necessary to select a suitable combination of physical parameterization schemes according to the variation of weather systems.However,it is rather difficult to identify an optimal combination among millions of possible parameterization scheme combinations.This study applied a simple genetic algorithm(SGA)to optimizing the combination of parameterization schemes in NWP models for typhoon forecasting.The feasibility of SGA was verified with the simulation of Typhoon Mujigae(2015)by using the Weather Research and Forecasting(WRF)model and Typhoon Higos(2020)by using the Coupled Ocean–Atmosphere–Wave–Sediment Transport(COAWST)modeling system.The results show that SGA can efficiently obtain the optimal combination of schemes.For Typhoon Mujigae(2015),the optimal combination can be found from the 1,304,576 possible combinations by running only 488 trials.Similar results can be obtained for Typhoon Higos(2020).Compared to the default combination proposed by the COAWST model system,the optimal combination scheme significantly improves the simulation of typhoon track and intensity.This study provides a feasible way to search for the optimal combinations of physical parameterization schemes in WRF and COAWST for more accurate typhoon simulation.This can help provide references for future development of NWP models,and for analyzing the coordination and adaptability of different physical process parameterization schemes under specific weather backgrounds.

Western North Pacific Tropical Cyclone Intensity Guidance Evaluations Using an Alternative Verification Technique

In this study,six intensity forecast guidance techniques from the East China Regional Meteorological Center are verified for the 2008 and 2009 typhoon seasons through an alternative forecast verification technique.This technique is used to verify intensity forecasts if those forecasts call for a typhoon to dissipate or if the real typhoon dissipates.Using a contingency table,skill scores,chance,and probabilities are computed.It is shown that the skill of the six tropical cyclone intensity guidance techniques was highest for the 12-h forecasts,while the lowest skill of all the six models did not occur in 72-h forecasting.For both the 2008 and 2009 seasons,the average probabilities of the forecast intensity having a small error(6 m s-1) tended to decrease steadily.Some of the intensity forecasts had small skill scores,but the associated probabilities of the forecast intensity errors > 15 m s-1 were not the highest.

ANALYSIS OF RAINSTORMS ASSOCIATED WITH SIMILAR TRACK TROPICAL CYCLONES HAITANG (0505) AND BILIS (0604)

It is generally thought that the influence of comparable track typhoons is approximately similar, but in fact their wind and especially their rainstorm distribution are often very different. Therefore, a contrastive analysis of rainstorms by tropical cyclones (TCs) Haitang (0505) and Bilis (0604), which are of a similar track, is designed to help understand the mechanism of the TC rainstorm and to improve forecasting skills. The daily rainfall of TC Haitang (0505) and Bilis (0604) is diagnosed and compared. The result indicates that these two TCs have similar precipitation distribution before landfall but different precipitation characteristics after landfall. Using NCEP/GFS analysis data, the synoptic situation is analyzed; water vapor transportation is discussed regarding the calculated water vapor flux and divergence. The results show that the heavy rainfall in the Zhejiang and Fujian Provinces associated with Haitang (0505) and Bilis (0604) before landfall results from a peripheral easterly wind, a combination of the tropical cyclone and the terrain. After landfall and moving far inland of the storm, the precipitation of Haitang is caused by water vapor convergence carried by its own circulation; it is much weaker than that in the coastal area. One of the important contributing factors to heavy rainstorms in southeast Zhejiang is a southeast jet stream, which is maintained over the southeast coast. In contrast, the South China Sea monsoon circulation transports large amounts of water vapor into Bilis – when a water-vapor transport belt south of the tropical cyclone significantly strengthens – which strengthens the transport. Then, it causes water vapor flux to converge on the south side of Bilis and diverge on the north side. Precipitation is much stronger on the south side than that on the north side. After Bilis travels far inland, the cold air guided by a north trough travels into the TC and remarkably enhances precipitation. In summary, combining vertical wind shear with water vapor transportation is a good way to predict rainstorms associated with landing tropical cyclones.

Impact of GNSS radio occultation bending angle data assimilation in YH4DVAR system

Global Navigation Satellite System （GNSS） radio occultation measurements have been assimilated into the four- dimensional variational data assimilation system （YH4DVAR） using a one-dimensional bending angle operator （GBAO） as a new type of observation. For the sake of verifying the impact of GNSS radio occultation （RO） measurements to the data assimilation system, three experiments have been conducted. The statistical results of the analysis error experiment and forecast skill experiment show that the GNSS RO measurements have an impact on the analysis system. The typhoon forecast experiment shows the impact on the important weather process. They all have a positive impact on the weather forecast. Lastly, we look forward to future work on the observation system simulation experiment （OSSE） to investigate the impact of GNSS RO measurements as a function of observation number, which is an effective method to estimate the saturation of the observation number.

Impact of FY-3D MWRI Radiance Assimilation in GRAPES 4DVar on Forecasts of Typhoon Shanshan

In this study, Fengyun-3 D(FY-3 D) Micro Wave Radiation Imager(MWRI) radiance data were directly assimilated into the Global/Regional Assimilation and Pr Ediction System(GRAPES) four-dimensional variational(4 DVar) system. Quality control procedures were developed for MWRI applications by using algorithms from similar microwave instruments. Compared with the FY-3 C MWRI, the bias of FY-3 D MWRI observations did not show a clear node-dependent difference from the numerical weather prediction background simulation. A conventional bias correction approach can therefore be used to remove systematic biases before the assimilation of data. After assimilating the MWRI radiance data into GRAPES, the geopotential height and humidity analysis fields were improved relative to the control experiment. There was a positive impact on the location of the subtropical high, which led to improvements in forecasts of the track of Typhoon Shanshan.

Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast

The Atmospheric Infrared Sounder （AIRS） can provide the profile information on atmospheric temperature and humidity in high vertical resolution. The assimilation of its radiances has been proven to improve the Numerical Weather Prediction （NWP） in global models. In this study, regional assimilation of AIRS radiances was carried out in a community assimilation system, using Gridpoint Statistical Interpolation （GSI） coupled with the Weather Research and Forecasting （WRY） model. The AIRS channel selection, quality control, and radiances bias correction were examined and illustrated for optimized assimilation. The bias correction scheme in the regional model showed that corrections on most of the channels produce satisfactory results except for several land surface channels. The assimilation and forecast experiments were carried out for three typhoon cases （Saola, Damrey, and Haikui in 2012） with and without including AIRS radiances. Results show that the assimilation of AIRS radiances into the WRF/GSI model improves both the typhoon track and intensity in a 72-hour forecast.

A high-resolution Asia-Pacific regional coupled prediction system with dynamically downscaling coupled data assimilation

A regional coupled prediction system for the Asia-Pacific(AP-RCP)(38°E-180°,20°S-60°N) area has been established.The AP-RCP system consists of WRF-ROMS(Weather Research and Forecast,and Regional Ocean Model System) coupled models combined with local observational information through dynamically downscaling coupled data assimilation(CDA).The system generates 18-day forecasts for the atmosphere and ocean environment on a daily quasi-operational schedule at Pilot National Laboratory for Marine Science and Technology(Qingdao)(QNLM),consisting of 2 different-resolution coupled models:27 km WRF coupled with 9 km ROMS,9 km WRF coupled with 3 km ROMS,while a version of 3 km WRF coupled with 3 km ROMS is in a test mode.This study is a first step to evaluate the impact of high-resolution coupled model with dynamically downscaling CDA on the extended-range predictions,focusing on forecasts of typhoon onset,improved precipitation and typhoon intensity forecasts as well as simulation of the Kuroshio current variability associated with mesoscale oceanic activities.The results show that for realizing the extended-range predictability of atmospheric and oceanic environment characterized by statistics of mesoscale activities,a fine resolution coupled model resolving local mesoscale phenomena with balanced and coherent coupled initialization is a necessary first step.The next challenges include improving the planetary boundary physics and the representation of air-sea and air-land interactions to enable the model to resolve kilometer or sub-kilometer processes.

Analysis of characteristics and evaluation of forecast accuracy for Super Typhoon Doksuri(2023)

Super Typhoon Doksuri is a significant meteorological challenge for China this year due to its strong intensity and wide influence range,as well as significant and prolonged hazards.In this work,we studied Doksuri's main characteristics and assessed its forecast accuracy meticulously based on official forecasts,global models and regional models with lead times varying from 1 to 5 days.The results indicate that Typhoon Doksuri underwent rapid intensification and made landfall at 09:55 BJT on July 28 with a powerful intensity of 50 m s−1 confirmed by the real-time operational warnings issued by China Meteorological Administration(CMA).The typhoon also caused significant wind and rainfall impacts,with precipitation at several stations reaching historical extremes,ranking eighth in terms of total rainfall impact during the event.The evaluation of forecast accuracy for Doksuri suggests that Shanghai Multi-model Ensemble Method(SSTC)and Fengwu Model are the most effective for short-term track forecasts.Meanwhile,the forecasts from the European Centre for Medium-Range Weather Forecasts(ECMWF)and United Kingdom Meteorological Office(UKMO)are optimal for long-term predictions.It is worth noting that objective forecasts systematically underestimate the typhoon maximum intensity.The objective forecast is terribly poor when there is a sudden change in intensity.CMA-National Digital Forecast System(CMA-NDFS)provides a better reference value for typhoon accumulated rainfall forecasts,and regional models perform well in forecasting extreme rainfall.The analyses above assist forecasters in pinpointing challenges within typhoon predictions and gaining a comprehensive insight into the performance of each model.This improves the effective application of model products.