Regional Specialized Meteorological Center Research Articles

Performance of International Global Models and Official Tropical Cyclone Forecasts Over the Bien Dong Sea for the Period 2012–2019

This research validates tropical cyclone (TC) forecasts from the National Centre for Hydro‐Meteorological Forecasting of Vietnam, the Regional Specialized Meteorological Center (RSMC) Tokyo, and global models (the Japanese Meteorological Agency [JMA], global spectral model [GSM], the National Centers for Environmental Prediction [NCEP], Global Forecast System [GFS], and the European Centre for Medium‐Range Weather Forecasts [ECMWF] Integrated Forecasting System [IFS]) for 72 activated TCs over the Bien Dong Sea. The best quality track forecasts come from the IFS and then GFS and GSM, while the GFS provides a good intensity forecast compared to IFS and GSM. The official guidance and model track forecast tend to be slower and leftward compared to observations (negative biases of along and cross‐track errors). Regarding the ECMWF’s ensemble track forecast, the strike probability forecast is quite overforecast/overconfident, especially for a lead time of 72 h and at high probabilities.

Multi-step forecasting of the Philippine storm frequencies using Poisson neural network

The paper aims to forecast the Philippine storm frequencies using nonlinear Poisson autoregressive model with exogenous variables. The nonlinearity is defined by its kernel which is an artificial neural network (ANN) with one hidden layer and two output neurons, and is trained to simultaneously forecast two semesters ahead for a given input. Furthermore, the covariates studied were the Average Sea Surface Temperatures in the NINO3.4 region (5∘− 5∘S,170∘− 120∘W) and the Average Sea Surface Temperatures in the eastern pole (0∘− 10∘S,90∘− 110∘E) of the Dipole Mode Index. The data, taken from the Japan Meteorological Agency’s Regional Specialized Meteorological Center with time points running from 1950 to October 2021, is modeled at a semester-level granularity. The estimation is done using maximum likelihood estimation by minimizing the negative log-likelihood function. Furthermore, Bayesian hyper-parameter optimization was used to tune the model across different activation functions, number of hidden neurons, training optimizers, and train and validation splits. Lastly, the best model from the hyper-parameter optimization was then compared to univariate Poisson autoregressive model (and its Bayesian counterpart) and Negative Binomial Autoregressive model. The proposed model captures well the characteristics of the data both in terms of the point forecast and the associated uncertainties.

Interagency discrepancies in tropical cyclone intensity estimates over the western North Pacific in recent years

AbstractThis study investigates interagency discrepancies among best‐track estimates of tropical cyclone (TC) intensity in the western North Pacific, provided by the Joint Typhoon Warning Center (JTWC), the China Meteorological Administration (CMA), and the Regional Specialized Meteorological Center (RSMC) Tokyo during 2013 to 2019. The results reveal evident differences in maximum wind speed (MSW) estimates, where linear systematic differences are significant. However, the Dvorak parameter (CI) numbers derived from the MSWs reported by the three agencies are internally consistent. Further analysis suggests that the remained CI discrepancies are related to differences in the estimation of intensity trends, initial intensities, and TC positions among these datasets. In addition, the CI estimates provided by the JTWC for TCs over the open ocean are generally higher than those reported by the CMA and RSMC. However, the estimates from CMA and RSMC tend to give higher TC intensities for the TCs in the mainland and coastal areas of China and Japan, respectively, than those over the open ocean with the same intensity in JTWC dataset. This pattern potentially reflects the extensive use of surface observations by these two agencies for landfalling and offshore TCs. These results may help the research community to get more accurate details about the TCs in WNP from the best track datasets of different agencies.

Comparison of Tropical Cyclone Wind Radius Estimates between the KMA, RSMC Tokyo, and JTWC

This study compared estimates of gale-force wind radii (R30 or R34) and storm-force wind radii (R50) of tropical cyclones (TC) by three agencies—the Korea Meteorological Administration (KMA), the Regional Specialized Meteorological Center (RSMC) Tokyo, and the Joint Typhoon Warning Center (JTWC)—in the western North Pacific during 2015–2018 and investigated the characteristics of these estimates. The results showed that the KMA’s R30 and R50 estimates were smaller (38% and 29%, respectively) than those of the RSMC Tokyo, and larger (11%) for R30 and smaller (12%) for R50 than those of the JTWC. The differences between these agencies seem to be largely determined by whether the agency estimates wind radii based only on a TC’s own winds or on TC winds combined with other mid-latitude synoptic systems to make TC warnings more comprehensive. The former is mainly the practice of the KMA and JTWC, whereas the latter is mainly the practice of the RSMC Tokyo. The factors considered for estimating wind radii also differ between the agencies: the KMA heavily relies on TC intensity—the higher the intensity, the larger the radius—while the RSMC Tokyo and JTWC rely less on TC intensity than the KMA but additionally consider the latitude and storm translation speed in their estimations. In particular, the TC translation speed considered by the RSMC Tokyo and JTWC explains why their estimated wind radii exhibit, on average, greater asymmetries (i.e., greater differences between the longest and shortest radii) than those estimated by the KMA. The findings of agency-dependent characteristics of TC wind radius data help to better determining and understanding the TC impact areas for TC risk reduction and management.

A 50‐Year Tropical Cyclone Exposure Climatology in Southeast Asia

AbstractIn this study, the landfalling tropical cyclone (TC) exposure in Southeast Asia for a 50‐year period from 1970 to 2019 is investigated relative to the total western North Pacific (WNP) climatology taking disparities in historical records into account. Long‐term trends in landfalling TCs are analyzed and intercompared among the Regional Specialized Meteorological Center of Tokyo (TOKYO), China Meteorological Administration (CMA), Hong Kong Observatory (HKO), and Joint Typhoon Warning Center (JTWC) best track datasets. Interannual and intra‐seasonal variations are further examined by sub‐region and nation using JTWC records. Approximately half of the WNP TCs make landfall in Southeast Asia representing over 75% of the total WNP landfalls in all datasets. Over the study period, there is a slight upward trend in landfalling TC frequency in both the WNP and Southeast Asia in the JTWC dataset, while the number of landfall events has decreased in the CMA and TOKYO datasets. A consistent northward shift in landfalling locations over the 50‐year period is found in all datasets such that landfalls have decreased in the Philippines, Vietnam, but increased in some South China areas. The TOKYO dataset alone suggests that landfalling TCs in South China have slowed down over the study period, which would increase rainfall and wind risks in their path if substantiated. Less TC landfalls occur in El Niño years with landfalling locations shifting northwestward over the Asian mainland, while landfalls are higher and more distributed in La Niña, and highest in Neutral years.

Are We Reaching the Limit of Tropical Cyclone Track Predictability in the Western North Pacific?

Abstract The annual-mean position errors (PE) of tropical cyclone (TC) track forecasts from three forecast agencies [WMO Regional Specialized Meteorological Center in Tokyo (RSMC-Tokyo), China Meteorological Administration (CMA), and Joint Typhoon Warning Center of the United States (JTWC)] are analyzed to document the past improvements and project future tendency in track forecast accuracy for TCs in the western North Pacific. An improvement of 48 h (2 days) in lead time has been achieved in the past 30 years, but with noticeable stepwise periods of improvements with superposed short-term fluctuations. The stepwise improvement features differ among the three forecast agencies, but are highly related to the development of objective forecast guidance and the application strategy. As demonstrated by an exponential model for the growth of PEs with lead time for TCs of tropical storm category and above, the improvements in the past 10 years have mainly been due to the reduction in analysis errors rather than the reduction in the error growth rate. If the current trend continues, a further 2-day improvement in TC track forecast lead times may be projected for the coming 15 years up to 2035, and we certainly have not reached yet the limit of TC track predictability in the western North Pacific.

Prediction of Track of Super Cyclone Amphan using WRF-ARW Model

An attempt has been made to study the prediction of the track of Super Cyclone (SuC) Amphan that formed on 13 May over Southeast Bay of Bengal (BoB) and made landfall to West Bengal-Bangladesh Coast on 20 May 2020 using Advanced Research WRF (ARW) dynamics of Weather Research and Forecasting (WRF) model. Model integration has been carried out using two-way interactive nesting domains with resolutions of 27 km for domain 1 and 9 km for domain 2 respectively covering the Bay of Bengal. Simulations are performed at an interval of 6 hours with ICs using the National Centre for Environmental Prediction (NCEP) global forecast system (GFS) 0.25° analysis and forecasts. To understand the applicability of the model in predicting the track along with landfall position and landfall time, nine real-time numerical forecasts have been carried out with model simulation starting at 00 UTC of 13 May, 14 May, 15 May, 16 May, 17 May, 18 May, 19 May, 20 May and 21 May 2020. The experiments with initial time on 16 May, 17 May, 18 May, 19 May, and 20 May 2020 have produced the best performance for the track and intensity prediction which are comparable to those provided by Bangladesh Meteorological Department (BMD) and Regional Specialized Meteorological Centre (RSMC). The tracks are produced based on the distribution of sea level pressure and vorticity. The model shows that the track prediction accuracy increases as the lead time decreases with the updated ICs. The results obtained from the model are in good agreement with the reported data. The experiment of SuCAmphan produced better track and intensity predictions with lead-time of 144, 120, 96, 48, and 24 hours. The results demonstrate that the model is capable to produce the track of SuCAmphan with reasonable accuracy. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 10(2), 2021, P 35-42

Climatological Features of Squall Line at the Borneo Coastline during Southwest Monsoon

Borneo Squall Line (BSL) is a disaster risk associated with intense rain and wind gust that affect the activities and residence near the northern coast of Borneo. Using 3-hourly rainfall from Tropical Rainfall Measuring Mission (TRMM) 3B42V7 during southwest monsoon season (May–September) from 1998–2018, a total of 629 squall days were identified. Their monthly and annual average was 6 and 30 days, respectively, with July representing the month with the highest number of squall line days. BSL is frequently initiated during midnight/predawn and terminated in the morning. Composite analyses of BSL days using the daily winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim revealed that lower tropospheric wind convergence is a crucial controlling factor for BSL formation. The position of the monsoon trough closer to the equatorial South China Sea (SCS), and strong westerly and south-westerly winds played an important role in creating this wind convergence region. Analyses of tropical cyclone (TC) data from the Regional Specialized Meteorological Centre (RSMC), Tokyo showed that nearly 72% of BSL occurred with the presence of TC. Spectral analysis exhibited prominent frequencies mainly in the 3–4- and 6-year time scale, which likely reflected the influence of interannual modulation of El-Niño Southern Oscillation (ENSO). Correlation coefficient between squall days and Sea Surface Temperature (SST) anomalies indicated that BSL increased after La-Niña events. This study is expected to have implications for real-time squall line forecasting in Malaysia and contributes toward a better understanding of BSL.

Prediction of Typhoon Track and Intensity Using a Generative Adversarial Network With Observational and Meteorological Data

To save lives and reduce damage from the destructive impacts of a typhoon, an accurate and fast forecast method is highly demanded. Particularly, predictions for short lead times, known as nowcasting, rely on fast forecasts allowing immediate emergency plannings in the affected areas. In this paper, we propose a generative adversarial network that operates on a single graphics processing unit, to predict both the track and intensity of typhoons for short lead times within fractions of a second. To investigate the effects of meteorological variables on typhoon forecasts, we conducted a parameter study for 6-h track predictions. The results of the study indicate that learning velocity, temperature, pressure, and humidity along with satellite images have positive effects on prediction accuracy. To address the limited access to observational data and facilitate predictions for 12-h intervals, we replaced satellite images with reanalysis data of the total cloud cover and vorticity fields. This replacement led to an increase in data from 76 to 757 typhoons, and it reduced the error of the 6-h track forecasts by 23.5%. The best combination of the parameter study yields track predictions in intervals of 6 and 12 h with the corresponding averaged absolute errors of 44.5 and 68.7 km. Typhoon intensities are predicted by extracting information from generated velocity fields with averaged hit rates of 87.3% and 83.2% for 6- and 12-h interval forecasts, respectively. For typhoons after 1994, tracks and intensities for 12-h intervals are compared to forecasts from the Joint Typhoon Warning Center and Regional Specialized Meteorological Center Tokyo.

Long short-term memory (LSTM)-based wind speed prediction during a typhoon for bridge traffic control

A short-term wind speed prediction framework is proposed for bridge traffic control under strong winds. The framework mainly focuses on improving the prediction accuracy for the timeframe of traffic control during a typhoon. Two concepts are newly proposed to achieve the goal: 1) hybrid modeling of wind speed at the bridge; and, 2) the adoption of a time-shifted data correction (TSDC) method. First, the hybrid modeling considers two available data types, one from a structural health monitoring system of the bridge and the other from the regional specialized meteorological center (RSMC). The training features of a long short-term memory (LSTM) approach are chosen based on the maximum sustained winds of a typhoon. Second, the TSDC method accounts for a time-delay phenomenon between the maximum wind speed at the bridge deck and the maxima or minima of the selected features. The Mean Absolute Error (MAE)-based grid search method determines the preferable combinations of two parameters: input data length and the time-shifted length of the training data. As a numerical example, typhoons from 2020 are used as test data to demonstrate the improvement in prediction performance via the use of hybrid modeling and the TSDC method.

Seasonal to Interannual Variability of Vertical Wind Shear and Its Relationship with Tropical Cyclogenesis in the Mozambique Channel

This article explores the relationship between vertical wind shear (VWS) and tropical cyclone (TC) genesis in the Mozambique Channel (MC) for the period 1979–2019. Additionally, SST, low-level relative vorticity, 700 hPa relative humidity and upper-level divergence were also analyzed for the peak cyclogenesis months to explore their relative contributions. The analyses were done using NCEP/NCAR Reanalysis-1 for the atmospheric fields, monthly Optimum Interpolation SST V2, and for the cyclogenesis the TC best track data from the La Reunion–Regional Specialized Meteorological and Joint Typhoon Warning Centre. A total of 43 TCs generated in the MC were observed for the analysed period. The maximum frequency of cyclogenesis in the MC was observed during January and February and the spatial location of maximum TC genesis was coincident with the minimum values of the VWS. The VWS showed significant correlations with TC intensity, particularly when considering the upper atmosphere (200–500 hPa) or the bulk (200–850 hPa) VWS. The mean composites of the cyclogenesis months over the MC of SST, relative humidity at 700 hPa, divergence at upper atmosphere, showed significant values. However, linear correlations between these factors vs. TC genesis frequency and intensity were not significant. Analyses of interannual correlations between VWS and Niño-3.4 (subtropical southwest Indian Ocean dipole-SIOD) showed statistically significant positive (negative) correlations at different lags, suggesting that La Niña and the positive phase of SIOD conditions are favorable to weaker VWS and thus to intensification of TCs in the Mozambique Channel. Thirteen landfall cases were observed with seven over the Madagascar west coast and six over the Mozambique coast. The landfall over the Madagascar (Mozambique) coast was associated with strengthened (weakened) VWS.

A HWRF-POM-TC coupled model forecast performance over North Indian Ocean: VSCS TITLI & VSCS LUBAN

Abstract The HWRF-POM-TC coupled model is run operationally at India Meteorological Department (IMD). This study is first attempt to assess the IMD's operational HWRF-POM-TC (Atmosphere-Ocean) coupled model forecast performance over North Indian Ocean (NIO). The two cyclonic storms one each in Arabian Sea and Bay of Bengal were examined. Among them, VSCS LUBAN formed over Arabian Sea (AS) and was followed by the formation of VSCS TITLI over Bay of Bengal (BoB). It constituted a rare case whereby two VSCS have formed in the north Indian Ocean (NIO) simultaneously. The HWRF-POM-TC modeling system, which was developed at National Centers for Environmental Prediction (NCEP) based on Non-hydrostatic Mesoscale Model (NMM) dynamic core, was customized for NIO conditions. For the two storms, VSCS LUBAN & VSCS TITLI, 28 and 15 consecutive 6-hourly HWRF model runs were performed. The HWRF-POM-TC coupled model showed great skill in forecasting of Track and Intensity for examined cyclones. The result shows that the model predicted the intensification and landfall of VSCS Luban & Titli in agreement with the best track data as made available by Cyclone Warning Division (CWD), India Meteorological Department which is also recognized as Regional Specialized Meteorological Center (RSMC) by WMO for NIO.

Tropical cyclone track prediction using a large-area WRF model at the Hong Kong Observatory

Tropical cyclone (TC) track predictions of the 10-km resolution WRF (provisionally named "AAMC-WRF") of the Hong Kong Observatory (HKO), spanning (20⁰S - 60⁰N, 45⁰E − 160⁰E) is studied for a 1-year period from April 2018 to Mar 2019. Real-time predictions, up to 4 times a day and T+48 h ahead, are verified against operational analysis positions of HKO for storms over the South China Sea (SCS) and Western North Pacific (WNP); and of the New Delhi Regional Specialised Meteorological Centre (RSMC) for storms over the North Indian Ocean basin (NIO; including the Bay of Bengal). Out of 21 named TCs over SCS and WNP, mean positional errors of the AAMC-WRF are 33 km (T+0), 63 km (T+24), and 107 km (T+48) based on 209, 178 and 142 forecasts. The AAMC-WRF outperformed Meso-NHM, also run in real-time at HKO, with mean error reduction up to 34 km or 24%. Mean positional errors for 13 NIO storms are 38 km (T+0), 69 km (T+24) and 107 km (T+48) based on 183, 131 and 85 forecasts. This is the first study in which TC predictions of a regional model are simultaneously examined over the SCS, WNP and NIO basins through real-time experiments.

Reexamination of the Tropical Cyclone Wind–Pressure Relationship Based on Pre-1987 Aircraft Data in the Western North Pacific

Abstract The wind–pressure relationship (WPR) for tropical cyclones (TCs) in the western North Pacific is reexamined based on aircraft data, TC best track data, and daily reanalysis data during 1957–87. Minimum sea level pressure (MSLP) was estimated from aircraft reconnaissance, and maximum surface wind speeds (MSWs) were adjusted from the maximum wind speed at flight level. The mean MSLP was found to be higher during 1957–64 than during 1965–87, presumably due to the change in reconnaissance instrumentation and technology, which results in a systematic MSW bias (too high) before 1965 in the China Meteorological Administration (CMA) dataset. Further analyses found that the WPR used in the CMA dataset is more accurate for strong TCs, while the WPR in the Tokyo Regional Specialized Meteorological Center (RSMC) dataset is better for weak TCs after the MSW-RSMC converted by the Dvorak conversion table (1984) and when using the aircraft datasets as a baseline. Several prevailing operational WPRs used in the western North Pacific are reexamined. Results show that the WPR of Knaff and Zehr explains 71% of the variance with a MAE of 9.22 hPa, which represents a significant improvement over other WPRs. Utilizing data after 1965 (a total of 1874 samples), the effects of TC center latitude, size, translation speed, intensification trend, and environmental pressure on the WPRs were examined. Results show that faster-traveling TCs, smaller in size, and located in a higher environmental pressure at lower latitudes, exhibited a higher MSLP for a given MSW. Meanwhile, the latitude, translational speed, and the environmental pressure produces additional improvement, but the TC size and intensity change added only a little skill to the WPR equation.

Convective Cloud RGB Product and Its Application to Tropical Cyclone Analysis Using Geostationary Satellite Observation

Red-Green-Blue (RGB) imagery techniques are useful for both forecasters and public users because they are intuitively understood, have advantageous visualization, and do not lose observational information. This study presents a novel RGB convective cloud product and its application to tropical cyclone analysis using Communication, Oceanography, and Meteorology (COMS) satellite observations. The RGB convective cloud product was developed using the brightness temperature differences between WV (6.75 μm) and IR1 (10.8 μm), and IR2 (12.0 μm) and IR1 (10.8 μm) as well as the brightness temperature in the IR1 bands of the COMS, with the threshold values estimated from the Korea Meteorological Administration (KMA) radar observations and the EUMETSAT RGB recipe. To verify the accuracy of the convective cloud RGB product, the product was applied to the center positions analysis of two typhoons in 2013. Thus, the convective cloud RGB product threshold values were estimated for WV-IR1 (-20 K to 15 K), IR1 (210 K to 300 K), and IR1-IR2 (-4 K to 2 K). The product application in typhoon analysis shows relatively low bias and root mean square errors (RMSE)s of 23 and 28 km for DANAS in 2013, and 17 and 22 km for FRANCISCO in 2013, as compared to the best tracks data from the Regional Specialized Meteorological Center (RSMC) in Tokyo. Consequently, our proposed RGB convective cloud product has the advantages of high accuracy and excellent visualization for a variety of meteorological applications.

On the Rapid Weakening of Very Intense Tropical Cyclone Hellen (2014)

Abstract In late March 2014, very intense Tropical Cyclone Hellen threatened the Comoros Archipelago and the Madagascan northwest coastline as it became one of the strongest tropical cyclones (TCs) ever observed over the Mozambique Channel. Its steep intensity changes were not well anticipated by operational forecasting models or by La Reunion regional specialized meteorological center forecasters. In particular, the record-setting rapid weakening over the open ocean was not supported by usual large-scale predictors. AROME, a new nonhydrostatic finescale model, is able to closely reproduce these wide intensity changes. When benchmarked against available observations, the model is also consistent in terms of inner-core structure, environmental features, track, and intensity. In the simulation, a northwesterly 400-hPa environmental wind is associated with unsaturated air, while the classic 200–850-hPa wind shear remains weak, and does not suggest a specifically unfavorable environment. The 400-hPa constraint affects the simulated storm through two pathways. Air with low equivalent potential temperature (θe) is flushed downward into the inflow layer in the upshear semicircle, triggering the decay of the storm. Then, direct erosion of the upper half of the warm core efficiently increases the surface pressure and also plays an instrumental role in the rapid weakening. When the storm gets closer to the Madagascan coastline, low-θe air can be directly advected within the inflow layer. Results illustrate on a real TC case the recently proposed paradigm for TC intensity modification under vertical wind shear and highlight the need for innovative tools to assess the impact of wind shear at all vertical levels.

Investigate the relationship between Storm Formation and Tropical Cyclone Genesis Potential Index in the Vietnam East Sea

Abstract: In this paper, the relationship between Tropical Cyclone (TC) Genesis Potential Index (GPI) and the number of TC (NTC) associated with ENSO over the Vietnam East Sea (VES) was investigated. Observed TC data of the Regional Specialized Meteorological Center (RSMC) Tokyo Typhoon Center and ERA Interim reanalysis data for the period 1985-2015 were used. The results show a good agreement between GPI and NTC over the VES with the correlation coefficient is 0.84. There were more TCs formed over the VES during La Nina years and less TCs during El Nino years. There were positive anomalies of GPI, environmental factors (relative humidity, sea surface temperature, absolute vorticity, potential intensity)over the region where the highest densityof TCs genesis locatedduring La Nina years while there were negative anomalies found during El Nino years. Relative humidity has the largest contribution to the positive difference GPI between La Nina years and El Nino years, the less contribution comes from the potential intensity, absolute vorticity, and wind shear.
 Keywords: GPI, Tropical Cyclone Genesis, ENSO, Vietnam East Sea.

The orographic effect of Reunion Island on tropical cyclone track and intensity

Like Taiwan, the orography of Reunion Island may impact tropical cyclone (TC) track and intensity. A Mann–Whitney test is applied on best‐track data from the Regional Specialized Meteorological Center (RSMC) La Reunion to demonstrate that this effect is detectable at less than 250 km from the island. A set of idealized experiments is carried out to investigate this effect with the French non‐hydrostatic mesoscale numerical model Meso‐NH at 12 and 4‐km horizontal grid spacing. Results show that the island influences TC track and intensity within two radii of maximum winds, defining a distance of influence. The impact is similar to an aspiration of the vortex by the island, accompanied by vortex weakening. An asymmetry is found between TCs passing north or south of the island and can be explained by the presence of the island in the flow.

An Analysis of Tropical Cyclone Activity over the Western North Pacific in 2011

ABSTRACT This paper uses China Meteorological Administration tropical cyclone (TC) best track data to analyze the characteristics of TC activity over the western North Pacific in 2011. Results derived from two other datasets, issued by the Regional Specialized Meteorological Center Tokyo and the Joint Typhoon Warning Center, were also compared. We show that the annual TC activity in 2011 was weaker than the climatology, and exhibited remarkable intraseasonal signals. The main TC genesis region migrated seasonally between the southwest (7° – 17°N, 120° – 140°E) and northeast (17°–25°N, 135°–165°E) quadrants. Moreover, three prevailing tracks were identified: westward tracks, recurving tracks between 125°–135°E, and northward tracks near 155°E. Special attention was paid to the intra-annual features of TC activity during 2011 and the potential modulators of this activity, including the tropical Indo-Pacific oceans, East Asian Monsoon (EAM), and Intraseasonal Oscillation (ISO). The seasonal migration of the main TC genesis region can be attributed to modulation by the EAM trough and ISO rather than the El Nino-Southern Oscillation. Both the EAM trough and ISO provided favorable conditions, including cyclonic vorticity in the low troposphere, limited vertical shear, and moisture convergence, in both of the main TC genesis quadrants, but unfavorable conditions outside the particular genesis quadrant. Moreover, both EAM and ISO generated a favorable circulation that steered TCs to move along the three prevailing tracks. These findings indicate that TC activity in 2011 was more significantly affected by both the EAM and ISO than by the ENSO.

Analysis of More Tropical Cyclone Genesis over the Western North Pacific in 2016

Tropical cyclone (TC) is the most catastrophic weather system characterized by strong winds and heavy rains, and is therefore the main research object of tropical meteorology. Based on National Oceanic and Atmospheric Administration (NOAA) Sea Surface Temperature (SST), Outgoing Long wave Radiation (OLR) and National Centers for Environmental Prediction (NCEP) monthly reanalysis data and Regional Specialized Meteorological Center (RSMC) Tokyo best track data and China Meteorological Administration (CMA) tropical cyclone during 1979-2016, we analyze the feathers of tropical cyclones and causes of more tropical cyclones (TCs) over the western north Pacific(including the South China Sea) (WNP) in 2016. The results show that compared the number of tropical cyclone genesis was higher, the originated time was later and concentrated in autumn, the region of more cyclones formed in north and east, and the number of landing TCs was higher. Negative sea surface temperature anomaly in the equatorial eastern Pacific and a westward deviation of the ascending branch of Walker circulation can strengthen the intensity of convection activity based on an existing lead-lag correlation during the period of TC activity (from August to September).The West Pacific subtropical high (WPSH) was exceptionally stronger than in other years and its west ridge point appreciably stretched westward and northward from August to September in 2016, which is favorable to TC genesis. At the same time, ω positive anomaly located in northward which was favorable for more TC genesis in WNP. In addition, the anomalous distribution of environmental factors such as low vorticity, OLR and vertical wind shear may also be the cause of the formation of tropical cyclones in the West North Pacific in 2016.