Study of the Boundary Layer Structure of a Landfalling Typhoon Based on the Observation from Multiple Ground-Based Doppler Wind Lidars

The boundary layer structure is crucial to the formation and intensification of typhoons, but there is still a lack of high-precision turbulence observations in the typhoon boundary layer due to limitations of the observing instruments under typhoon conditions. Using joint observations from multiple ground-based Doppler wind lidars (DWL) collected by the Shanghai Typhoon Institute of China Meteorological Administration (CMA) during the transit of Typhoon Lekima (8–11 August 2019), the characteristics of the wind field and physical quantities (including turbulent kinetic energy (TKE) and typhoon boundary layer height (TBLH)) of the boundary layer of typhoon Lekima were analyzed. The magnitude of TKE was shown to be related not only to the horizontal wind speed but also to the presence of a strong downdraft, which leads to a rapid increase of TKE. The magnitudes of TKE in different quadrants of Typhoon Lekima were also found to differ. The TKE in the front right quadrant of the typhoon was 2.5–6.0 times that in the rear left quadrant and ~1.7 times that in the rear right quadrant. The TKE over the island was larger than that over the urban area. Before Typhoon Lekima made landfall, the TKE increased with decreasing distance to the typhoon center. After typhoon landfall, the TKE changes were different on the left and right sides of the typhoon center, with the TKE on the left decreasing rapidly, while that on the right changed little. The typhoon boundary layer height calculated by five methods was compared and was found to decrease gradually before typhoon landfall and increased gradually afterward. The trends of the TBLH calculated using helicity and TKE were consistent, and both determine the TBLH well, while the maximum tangential wind speed height (humax) was larger than the height calculated by other methods. This study confirms that DWL has a strong detecting capability for the finescale structure of the typhoon boundary layer and provides a powerful tool for the validation of numerical simulations of typhoon structure.

Spatio-Temporal Variations of Precipitable Water Vapor and Horizontal Tropospheric Gradients from GPS during Typhoon Lekima

GPS data during Typhoon Lekima at 700 stations in China were processed by the Precise Point Positioning (PPP) method. A refined regional Tm model was used to derive the precipitable water vapor (PWV) at these GPS stations. Spatio-temporal variations of PWV with the typhoon process were analyzed. As the typhoon approached, PWV at stations near the typhoon center increased sharply from about 50 mm to nearly 80 mm and then dropped back to about 40–50 mm as the typhoon left. Comparisons of GPS, radiosonde, the Global Data Assimilation System (GDAS) Global Forecast System (GFS) analysis products and ERA5 reanalysis products at four matched GPS-RS stations show overall overestimations of PWV from radiosonde, GFS and ERA5 compared with GPS in a statistical perspective. An empirical orthogonal functions (EOF) analysis of the PWV during the typhoon event revealed some different patterns of variability, with both the first EOF (~36.1% of variance) and second EOF (~30.3% of variance) showing distinctively large anomalies over the typhoon landing locations. The typhoon caused a large horizontal tropospheric gradient (HTG) with the magnitude reaching 5 mm and the direction pointing to the typhoon center when it made a landfall on mainland China. The magnitude and the consistency of the HTG direction decreased overall as the typhoon weakened.

Decision-Tree-Based Classification of Lifetime Maximum Intensity of Tropical Cyclones in the Tropical Western North Pacific

The National Typhoon Center of the Korea Meteorological Administration developed a statistical–dynamical typhoon intensity prediction model for the western North Pacific, the CSTIPS-DAT, using a track-pattern clustering technique. The model led to significant improvements in the prediction of the intensity of tropical cyclones (TCs). However, relatively large errors have been found in a cluster located in the tropical western North Pacific (TWNP), mainly because of the large predictand variance. In this study, a decision-tree algorithm was employed to reduce the predictand variance for TCs in the TWNP. The tree predicts the likelihood of a TC reaching a maximum lifetime intensity greater than 70 knots at its genesis. The developed four rules suggest that the pre-existing ocean thermal structures along the track and the latitude of a TC’s position play significant roles in the determination of its intensity. The developed decision-tree classification exhibited 90.0% and 80.5% accuracy in the training and test periods, respectively. These results suggest that intensity prediction with the CSTIPS-DAT can be further improved by developing independent statistical models for TC groups classified by the present algorithm.

An Impact Study of GNSS RO Data on the Prediction of Typhoon Nepartak (2016) Using a Multi-resolution Global Model with 3D-Hybrid Data Assimilation

Conventional soundings are rather limited over the western North Pacific and can be largely compensated by GNSS radio occultation (RO) data. We utilize the GSI hybrid assimilation system to assimilate RO data and the multi-resolution global model (MPAS) to investigate the RO data impact on prediction of Typhoon Nepartak that passed over southern Taiwan in 2016. In this study, the performances of assimilation with local RO refractivity and bending angle operators are compared for the assimilation analysis and typhoon forecast.Assimilations with both RO data have shown similar and comparable temperature and moisture increments after cycling assimilation and largely reduce the RMSEs of the forecast without RO data assimilation at later times. The forecast results at 60-15-km resolution show that RO data assimilation largely improves the typhoon track prediction compared to that without RO data assimilation, and assimilation with bending angle has better performances than assimilation with refractivity, in particular for wind forecast. The improvement in the forecasted track is mainly due to the improved simulation for the translation of the typhoon. Diagnostics of wavenumber-one potential vorticity (PV) tendency budget indicates that the northwestward typhoon translation dominated by PV horizontal advection is slowed down by the southward tendency induced by the stronger differential diabatic heating south of the typhoon center for bending-angle assimilation. Simulations with the enhanced resolution of 3 km in the region of the storm track show further improvements in both typhoon track and intensity prediction with RO data assimilation. Positive RO impacts on track prediction are also illustrated for other two typhoons using the MPAS-GSI system.

Coordinated observation system for extreme weathers consisting of AWS network with lightning sensor and micro-satellites

<p>In order to predict the intensity and location of extreme weathers, such as torrential rainfall by individual thunderstorm or typhoon, we are developing the new methodology of weather monitoring using a ground AWS network with lightning sensors and micro-satellites weighting about 50kg, which will realize quasi-real-time thunderstorm monitoring with broad coverage. Based on the AWS network data, we plan to operate micro-satellites in nearly real-time, manipulating the attitude of satellite for capturing the most dangerous or important cloud images for 3D reconstruction. We have developed and launched several micro-satellites and been improving the target pointing operation for this decade. We succeeded in obtaining the images of the typhoon center at a resolution of 60-100 m for Typhoon Trami in 2018 and Typhoon Maysak in 2020. Using 4 or a few 10s images captured from different angles by one micro-satellite when it passed over the typhoon area, 3D models of typhoon eye were reconstructed, which have a ground resolution of ~100 m. Due to the unusual temperature profile around typhoon eye, it’s very difficult to estimate the heigh distribution of cloud top only with a thermal infrared image at a resolution of 2 km taken by geostationary meteorological satellite. This is one of the biggest limitations in estimating the precise intensity of typhoons, namely, the center pressure or the maximum wind velocity. The on-demand flexible operation of micro-satellite will achieve the high accuracy estimation of typhoon intensity as well as the speed estimation of individual thunderstorm development, which can be applied to disaster management. This research was conducted by a mixed team of Japan and the Philippines, supported by Science and Technology Research Partnership for Sustainable Development (SATREPS), which is funded by Japan Science and Technology Agency (JST) / Japan International Cooperation Agency (JICA).</p>

ANALYSIS OF IONOSPHERIC TEC ANOMALIES DURING SUPER TYPHOONS MEGI AND MERANTI

In this paper, we detected and analyzed ionospheric anomalies during the 2016 super typhoons Megi and Meranti using the sliding interquartile range method applied to the ionospheric total electron content (TEC) grid data from the Global Ionospheric Model (GIM) provided by the Center for Orbit Determination in Europe (CODE). We found that ionospheric TEC anomalies occurred 2 days before the origination of super typhoon Megi. The anomalies occurred from 02:00 to 12:00 local time over a period of 10 h, with a maximum outlier of 12 TEC units over the typhoon center. Anomalies occurred in the ionosphere over both the area near the typhoon center and the corresponding equatorial magnetic conjugate region. The anomalies in both areas showed approximately the same trends. It is very likely that the disturbances from the ionospheric anomalies over the typhoon center were one of the precursors for the typhoon event. Similar ionospheric anomalies also occurred in the ionosphere 2 days before the formation and development of super typhoon Meranti...

Effects of Typhoon Paths on Storm Surge and Coastal Inundation in the Pearl River Estuary, China

A coastal inundation simulation system was developed for the coast of the Pearl River estuary (PRE), which consists of an assimilation typhoon model and the coupled ADCIRC (Advanced Circulation) + SWAN (Simulating Waves Nearshore) model. The assimilation typhoon model consists of the Holland model and the analysis products of satellite images. This is the first time an assimilation typhoon model has been implemented and tested for coastal inundation via case studies. The simulation results of the system agree well with the real measurements. Three observed typhoon paths (Hope, Nida, and Hato) were chosen to be the studied paths based on their positions relative to the PRE, China. By comparing the results of experiments with different forcing fields, we determined that the storm surge and the coastal inundation were mainly induced by wind forcing. By simulating coastal inundation for different typhoon center speeds, the Hato3 path most easily causes coastal inundation in the PRE. Moreover, the moving speed of the typhoon’s center significantly affects the coastal inundation in the PRE. The inundation becomes very serious as the movement of the typhoon center was slow down. This study provides a new reference for future predictions of coastal inundations.

Assessment of heavy rainfall risk of typhoon Hagibis (2019) associated with typhoon track

<p>Typhoon Hagibis (2019) caused heavy rainfall and big flood damage in many river basins in Japan. In this research, we suggested the risk assessment method for heavy rainfall due to typhoon from the view point of a typhoon track by using records of rain gauges and typhoon track data from 1951. The relationships between typhoon position and rainfall intensity were obtained from the rain gauges and the typhoon track data for each rain gauge points. The relationships make it clear that typhoon track passes through the areas in which heavy rainfall occurred. The relationship can be used for risk assessment of heavy rainfall<span>  </span>in terms of typhoon track. The track of Typhoon Hagibis is the heaviest rainfall track for some points located in north of the typhoon track. However, some points close to the typhoon center or in south of the typhoon track are not the heaviest rainfall track. It means that if typhoon Hagibis shifted the track, the typhoon would cause heavier rainfall in some points. The result can be used not only for estimation of potential rainfall but also for selection of dangerous typhoons from large ensemble dataset. We assessed heavy rainfall risk of typhoons similar to typhoon Hagibis under historical and future climate by using the large ensemble climate dataset (d4PDF).</p>