Hong Kong Observatory Research Articles

An overview of nowcasting development, applications, and services in the Hong Kong Observatory

The Hong Kong Observatory (HKO) has been developing a suite of nowcasting systems to support operations of the forecasting center and to provide a variety of nowcasting services for the general public and specialized users. The core system is named the Short-range Warnings of Intense Rainstorm of Localized Systems (SWIRLS), which is a radar-based nowcasting system mainly for the automatic tracking of the movement of radar echoes and the short-range Quantitative Precipitation Forecast (QPF). The differential, integral (or variational), and object-oriented tracking algorithms were developed and integrated into the nowcasting suite. In order to predict severe weather associated with intense thunderstorms, such as high gust, hail, and lightning, SWIRLS was enhanced to SWIRLS-II by introduction of a number of physical models, especially the icing physics as well as the thermodynamics of the atmosphere. SWIRLS-II was further enhanced with non-hydrostatic, high resolution numerical models for extending the forecast range up to 6 h ahead. Meanwhile, SWIRLS was also modifled for providing nowcasting services for aviation community and specialized users. To take into account the rapid development of lightning events, ensemble nowcasting techniques such as time-lagged and weighted average ensemble approaches were also adopted in the nowcasting system. Apart from operational uses in Hong Kong, SWIRLS/SWIRLS-II was also exported to other places to participate in several international events such as the WMO/WWRP Forecast Demonstration Project (FDP) during the Beijing 2008 Olympics Games and the Shanghai Expo 2010. Meanwhile, SWIRLS has also been transferred to various regional meteorological organizations for establishing their nowcasting infrastructure. This paper summarizes the history and the technologies of SWIRLS/SWIRLS-II and its variants and the associated nowcasting applications and services provided by the HKO since the mid 1990s.

Impacts of reconnaissance flight data on numerical simulation of tropical cyclones over South China Sea

AbstractIn 2011, the Hong Kong Observatory (HKO) and the Government Flying Service (GFS) of the Hong Kong Government conducted reconnaissance data collection flights for two tropical cyclones over the South China Sea. It was the first time in the region that flight measurements of this kind had been carried out specifically for tropical cyclones. Horizontal wind velocity components, temperature and relative humidity at selected flight levels were recorded at the temporal resolution of 20 times per second to delineate the wind flow and other meteorological conditions. They were found to be consistent with other synoptic station data sparsely located over the sea areas, as well as in good agreement with the ocean surface wind data from the satellite microwave scatterometer. In this study, aircraft measurements for the two tropical cyclones in 2011 and one in July 2009 were assimilated into the HKO mesoscale Non‐Hydrostatic Model (NHM) using its three‐dimensional variational data assimilation (3DVAR) to investigate the impact of the data on the model analysis and forecast. Model sensitivity experiments with and without the flight measurements were conducted. The flight observations were found to improve model analysis and forecasts of wind circulation, temperature and humidity in the vicinity of the tropical cyclones. Improvement in track forecast was obtained although an insignificant effect was seen in predicting the central pressure of the storms. The inclusion of flight measurements also improved the forecast of the surface wind distribution and precipitation associated with the tropical cyclones.

Performance of LIDAR- and radar-based turbulence intensity measurement in comparison with anemometer-based turbulence intensity estimation based on aircraft data for a typical case of terrain-induced turbulence in association with a typhoon

The Hong Kong Observatory (HKO) provides low-level turbulence alerting service for the Hong Kong International Airport (HKIA) through the windshear and turbulence warning system (WTWS). In the WTWS, turbulence intensities along the flight paths of the airport are estimated based upon correlation equations established between the surface anemometer data and the turbulence data from research aircraft before the opening of the airport. The research aircraft data are not available on day-to-day basis. The remote sensing meteorological instruments, such as the Doppler light detection and ranging (LIDAR) and radar, may be used to provide direct measurements of turbulence intensities over the runway corridors. The performances of LIDAR- and radar-based turbulence intensity data are studied in this paper based on actual turbulence intensity measurements made on 423 commercial jets for a typical case of terrain-induced turbulence in association with a typhoon. It turns out that, with the tuning of the relative operating characteristic (ROC) curve between hit rate and false alarm rate, the LIDAR-based turbulence intensity measurement performs better than the anemometer-based estimation of WTWS for turbulence intensity at moderate level or above. On the other hand, the radar-based measurement does not perform as well when compared with WTWS. By combining LIDAR- and radar-based measurements, the performance is slightly better than WTWS, mainly as a result of contribution from LIDAR-based measurement. As a result, the LIDAR-based turbulence intensity measurement could be used to replace anemometer-based estimate for non-rainy weather conditions. Further enhancements of radar-based turbulence intensity meas- urement in rain would be necessary.

Aviation Model: A Fine-Scale Numerical Weather Prediction System for Aviation Applications at the Hong Kong International Airport

The Hong Kong Observatory (HKO) is planning to implement a fine-resolution Numerical Weather Prediction (NWP) model for supporting the aviation weather applications at the Hong Kong International Airport (HKIA). This new NWP model system, called Aviation Model (AVM), is configured at a horizontal grid spacing of 600 m and 200 m. It is based on the WRF-ARW (Advance Research WRF) model that can have sufficient computation efficiency in order to produce hourly updated forecasts up to 9 hours ahead on a future high performance computer system with theoretical peak performance of around 10 TFLOPS. AVM will be nested inside the operational mesoscale NWP model of HKO with horizontal resolution of 2 km. In this paper, initial numerical experiment results in forecast of windshear events due to seabreeze and terrain effect are discussed. The simulation of sea-breeze-related windshear is quite successful, and the headwind change observed from flight data could be reproduced in the model forecast. Some impacts of physical processes on generating the fine-scale wind circulation and development of significant convection are illustrated. The paper also discusses the limitations in the current model setup and proposes methods for the future development of AVM.

Improving the wind and temperature measurements of an airborne meteorological measuring system

The Aircraft Integrated Meteorological Measuring System 20 Hz (AIMMS-20) has been used by the Hong Kong Observatory (HKO), China in data collection for tropical cyclone situations over the South China Sea and windshear and turbulence measurement at the Hong Kong International Airport (HKIA). This paper discusses possible methods for further enhancing the quality of the wind and temperature measurements from the system. For wind measurement, the enhancement methods include: error modelling of the accelerometer (e.g., bias offset and cross-axis rate sensitivity), global positioning system (GPS) phase lag consideration, better representation of the inertial measurement unit (IMU) velocity based on the GPS velocities and considering their location differences, consideration of the slower update of GPS velocity, and wing flexure. For temperature measurement, the methods include the consideration of the temperature sensor response and the sensor housing response. The results of typical flights using AIMMS-20 show that the accuracy of the wind and temperature data could be improved by 20%–30%. Though the discussion in the present paper is related mainly to a specific meteorological measuring system on a particular aircraft, the techniques so employed should be a useful reference for similar systems installed on other aircraft.

A northerly winter monsoon surge over the South China Sea studied by remote sensing and a numerical model

A northerly winter monsoon surge, which occurred on 15 December 2009 over the South China Sea (SCS), is studied by using satellite-based and ground-based remote-sensing data and an atmospheric numerical model. The remote-sensing data are from the advanced synthetic aperture radar (ASAR) onboard the Environmental Satellite (Envisat), the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite, the imager onboard the geostationary satellite MTSAT-1R (Multi-Functional Transport Satellite-1R) and the weather radar of the Hong Kong Observatory (HKO). A northerly winter monsoon surge is a cold air outbreak associated with a northerly wind, the passage of a cold front from north to south and a strong drop in air temperature. The analyses of the weather radar and the MTSAR-1R images of 15 December show that the surge of 15 December was associated with a rain band and a cloud front travelling over the SCS in a southeastward direction. Due to the interaction of the cold air (13°C) with the warm water (19°C), they dissolved when they had reached an offshore distance of approximately 160 km. The high-resolution (150 m) ASAR image reveals fine-scale features of the wind field, in particular details of the wind front, such as embedded rain cells and atmospheric gravity waves. Quantitative information on the near-surface wind field is retrieved from the ASAR, and it is shown that the wind field associated with the surge is quite variable and that speeds up to 15 m s–1 are encountered in coastal wind jets. Finally, the remote-sensing data are compared with the simulation results of the pre-operational version of the Atmospheric Integrated Rapid-cycle (AIR) forecast model of the HKO. It is shown that, in general, the AIR model reproduces quite well the observational data.

A case study of missed approach of aircraft due to tailwind associated with thunderstorms

ABSTRACTTwo aircraft had to conduct missed approaches in the overnight period of 8–9 September 2010 due to intense thunderstorm activity at the Hong Kong International Airport (HKIA). The missed approach event is studied in detail in this paper using the available flight data and other meteorological measurements. It appeared that the missed approaches were attributable to strong tailwind associated with the downdraft of the thunderstorm. Timely wind shear/microburst alerts had been provided to the pilots in this case based on the measurements from a Terminal Doppler Weather Radar (TDWR) and ground‐based anemometer measurements at HKIA. The nowcasting and forecasting aspects for such an event are also discussed. The Aviation Thunderstorm Nowcasting System (ATNS) developed by the Hong Kong Observatory (HKO) is found to provide adequate nowcasting of thunderstorm activity for this particular case and the aviation weather forecasters could be alerted of such intense convective weather at the airport more than half an hour ahead. On the forecasting side, the mesoscale meteorological model used by HKO may provide an indication of the strong tailwind associated with the thunderstorm at 6–7 h ahead, though the exact timing of the tailwind at the airport may be delayed by a couple of hours compared with the actual situation. Using the model the downdraft of the thunderstorm in this event is examined in detail.

Use of SWIRLS nowcasting system for quantitative precipitation forecast using Indian DWR data

Local severe storms are extreme weather events that last only for a few hours and evolve rapidly. Very often the mesoscale features associated these local severe storms are not well-captured synoptically. Forecasters have to predict the changing weather situation in the next 0-6 hrs based on latest observations. The operational process to predict the weather in the next 0-6 hrs is known as “nowcast”. Observational data that are typically suited for nowcasting includes Doppler Weather Radar (DWR), wind profiler, microwave sounder and satellite radiance. To assist forecasters, in predicting the weather information and making warning decisions, various nowcasting systems have been developed by various countries in recent years. Notable examples are Auto-Nowcaster (U.S.), BJ-ANC (China-U.S.), CARDS (Canada), GRAPES-SWIFT (China), MAPLE (Canada), NIMROD (U.K.), NIWOT (U.S.), STEPS (Australia), SWIRLS (Hong Kong, China), TIFS (Australia), TITAN (U.S.) (Dixon and Wiener, 1993) and WDSS (U.S.). Some of these systems were used in the two forecast demonstration projects organized by WMO for the Sydney 2000 and Beijing 2008 Olympic. A common feature of these systems is that they all use rapidly updated radar data, typically once every 6 minutes.The nowcasting system SWIRLS (“Short-range Warning of Intense Rainstorms in Localized Systems”) has been developed by the Hong Kong Observatory (HKO) and was put into operation in Hong Kong in 1999. Since then system has undergone several upgrades, the latest known as “SWIRLS-2” to support the Beijing 2008 Olympic Games. SWIRLS-2 is being adapted by India Meteorological Department (IMD) for use and test for the Commonwealth Games 2010 at New Delhi with assistance from HKO. SWIRLS-2 ingests a range of observation data including SIGMET/IRIS DWR radar product, raingauge data, radiosonde data, lightning data to analyze and predict reflectivity, radar-echo motion, QPE, QPF, as well as track of thunderstorm and its associated severe weather, including cloud-to-ground lightning, severe squalls and hail, and probability of precipitation. SWIRLS-2 uses a number of algorithms to derive the storm motion vectors. These include TREC (“Tracking of Radar Echoes by Correlation”), GTrack (Group tracking of radar echoes, an object-oriented technique for tracking the movement of a storm as a whole entity) and lately MOVA (“Multi-scale Optical flow by Variational Analysis”). This latest algorithm uses optical flow, a technique commonly used in motion detection in image processing, and variational analysis to derive the motion vector field. By cascading through a range of scales, MOVA can better depict the actual storm motion vector field as compared with TREC and GTrack which does well in tracking small scales features and storm entity respectively. In this paper the application of TREC and MOVA to derive the storm motion vector, reflectivity and QPF using Indian DWR data has been demonstrated for the thunderstorm events over Kolkata and New Delhi. The system has been successfully operationalized for Delhi and neighborhood area for commonwealth games 2010. Real time products are available on IMD website

Regional temperature forecast for the next day in Hong Kong

For a century or so, the Hong Kong Observatory (HKO) has been providing temperature forecast for the whole of Hong Kong with the HKO Headquarters as the reference location. In recent decades, due to spreading of population from the main urban center to satellite towns, there is an increasing demand for regional temperature forecasts. To support such provision, the HKO has developed a regression model to provide objective guidance to forecasters in formulating forecasts of maximum and minimum temperatures for the next day at various locations in Hong Kong. In this paper, the regression model is presented, together with the assessment of its performance. Based on the verification of one year of forecasts, it is found that the root mean square errors (RMSEs) of maximum (minimum) temperature forecasts are from about 1.3 to 2.1 (1.1 to 1.4) degrees, respectively. The regression model is shown to have generally out-performed the operational regional spectral model then operated by HKO. Regional temperature forecast methods of other meteorological or research centers are also surveyed. Equipped with the regression model, the HKO has launched an online regional temperature forecast service for the next day in Hong Kong since March 2008.

LIDAR-based turbulence intensity calculation using glide-path scans of the Doppler LIght Detection And Ranging (LIDAR) systems at the Hong Kong International Airport and comparison with flight data and a turbulence alerting system

Glide-path scans of the LIght Detection And Ranging (LIDAR) systems have been devised by the Hong Kong Observatory (HKO) for windshear alerting over the Hong Kong International Airport (HKIA). This paper studies the use of glide-path scans in the alerting of low-level turbulence which may be encountered by the aircraft. Turbulence intensity, namely, eddy dissipation rate (EDR), is calculated by structure function approach based on the radial velocity data obtained in the glide-path scans. Two methods have been employed in the calculation, namely, the azimuthal structure function and the longitudinal structure function. They are found to give generally consistent EDR values. The LIDAR-based EDR estimates are then compared with the EDR values derived from flight data. Results show that the two sets of EDR data are comparable with each other. Application of LIDAR-based EDR in turbulence alerting is demonstrated in two typical examples of low-level turbulence at HKIA. Such EDR values are found to be consistent with pilots' subjective perception of the turbulence. Finally, EDR values provided by the operational Windshear and Turbulence Warning System (WTWS) of HKO are compared with those obtained by the LIDAR, demonstrating the operational benefits of including the LIDAR-based EDR in the alerting of mechanical turbulence.

Quick Access Recorder Data Analysis Software for Windshear and Turbulence Studies

For analysis of low-level windshear and turbulence events at the Hong Kong International Airport (HKIA), besides pilot reports routinely received from Air Traffic Control, Quick Access Recorder (QAR) data are obtained from the local airlines by the Hong Kong Observatory (HKO). Instead of using directly the wind data recorded on the aircraft by the flight management system (FMS), there has been a collaborative study between HKO and the National Aerospace Laboratory (NLR) in The Netherlands to develop a QAR data analysis software to calculate the meteorological quantities, such as the three components of the wind, windshear hazard factor and turbulence intensity parameters, taking into account the aircraft’s aerodynamic factors (e.g. sideslip angle, angle-of-attack). This paper describes the main features of the calculation software, named WINDSTURB, and illustrates its application to windshear and turbulence studies through selected cases at HKIA.

Aviation Applications of the Pulsed Doppler LIDAR – Experience in Hong Kong

The Hong Kong Observatory (HKO) introduced a Doppler LIDAR to the Hong Kong International Airport (HKIA) in 2002, the first LIDAR for aviation alerting services in the world. Since then, HKO has developed a number of weather products based on the LIDAR’s velocity and backscatter power data. LIDAR is found to provide crucial information in a wide variety of aviation applications. This paper gives a review of the experience in Hong Kong in the development of aviation-related weather products using the LIDAR data. Applications include: automatic windshear alerting from the HKO-developed glide-path scans, detection of low-level turbulence, 2D wind retrieval for intense convective events from LIDAR-radar dual Doppler analysis, 3D wind retrieval from a single LIDAR for terrain-disrupted airflow, visibility map based on backscatter power distribution in conical scans, and mixing-height monitoring in vertical scans.

Depiction of complex airflow near Hong Kong International Airport using a Doppler LIDAR with a two-dimensional wind retrieval technique

The Hong Kong Observatory (HKO) operates a Doppler Light Detection And Ranging (LIDAR) system at the Hong Kong International Airport (HKIA) to monitor the airflow around the airport area. The LIDAR measures the radial component of the wind field. To better visualize the airflow, a variational method which has been successfully applied to Doppler Radar data is adopted in this study to retrieve the two-dimensional wind field based on the LIDAR measurements. The wind field so obtained is found to reveal many salient features of terrain-induced airflow disturbances at HKIA, such as mountain waves and vortices. Its application to the detection of low-level windshear is demonstrated through selected cases. With a simple extension of the variational method, dual-Doppler analysis is also carried out using the radial velocity data from both the LIDAR and a Terminal Doppler Weather Radar (TDWR) to retrieve the wind field at the airport area in a gust front event.

Study of Rain Events over the South China Sea by Synergistic Use of Multi-sensor Satellite and Ground-based Meteorological Data

Rain cells and rain bands over the South China Sea off the coast of Hong Kong are studied by using multi-sensor satellite and ground-based meteorological data. These include synthetic aperture radar (SAR) images acquired by the Advanced Synthetic Aperture Radar (ASAR) onboard the European ENVISAT satellite, weather radar images from the Hong Kong Observatory (HKO), rain rate data acquired by the Special Sensor Microwave Imager (SSM/I) sensor onboard the F15 satellite of the American Defense Meteorological Satellite Program (DMSP) and the rain sensors onboard the Tropical Rainfall Measurement Mission (TRMM) satellite, cloud image of GOES-9 satellite, sea surface wind maps acquired by the scatterometer onboard the QUIKSCAT satellite, and meteorological data from weather stations in Hong Kong. Three rain events, typical of Hong Kong, are studied. The first event consists of a cluster of rain cells associated with the summer monsoon, the second one of rain cells aligned in a rain band generated by an upper-air trough, and the third one consists of small rain cells embedded in a cold front. It is shown that ASAR images, which have a resolution of 30 m in the Image Mode (IM) and 150 m resolution in the Wide Swath Mode (WSM), yield much more detailed information on the spatial structure of rain events over the ocean than data obtained from SSSM/I and the rain sensors onboard the TRMM satellite. The precipitation radar (PR) onboard TRMM, which is the rain measuring instrument flown in space with the next best resolution, has a resolution of only 4 km. However, the disadvantage of SAR is that it is sometimes difficult to identify SAR signatures visible on SAR images of the sea surface unambiguously as caused by rain events. By comparing SAR images with simultaneously acquired weather radar images of the Hong Kong Observatory, a better knowledge of radar signatures on SAR images resulting from rain events over the ocean is obtained. This knowledge then helps greatly in detecting rain events on SAR images which are acquired over ocean areas, which are not in the reach of weather radar stations. SAR images containing radar signature of rain events allow a much more detailed study of fine-scale structures of rain events over the World's ocean, in particular of clusters of rain cells, than any other sensor presently flown in space.

Predicting daylight availability dynamically based on forecasts of a weather observatory

By using measured data of the research class IDMP station, a subset of three sky types and their probability of occurrence has previously been established to represent sky conditions of Hong Kong. This was dubbed the Hong Kong Representative Sky (HKRS). The HKRS allows a better prediction of daylight on the vertical surfaces of buildings than the CIE Overcast Sky. The HKRS was still a static representation. This paper investigates the possibility of using the weather predictions of the observatory to establish dynamically the HKRS. A methodology is proposed, and the results indicate that the approach is feasible. It is established that the weather prediction information issued by the Hong Kong Observatory (HKO) provides a reliable means for estimating probabilities of the sky types at a particular moment. By using this information, a better prediction of vertical sky component (VSC) on building surfaces, with a reduction of 20–30% mean absolute error, can be achieved. Engineers and architects may use this more accurate information to design more dynamically.

Numerical simulation of a South China Sea typhoon Leo (1999)

¶A South China Sea typhoon, Leo (1999), was simulated using the Penn State/NCAR mesoscale model MM5 with the Betts-Miller convective parameterization scheme (BMEX). The simulation had two nested domains with resolutions at 54 and 18 km, and the forecast duration was 36 hours. The model was quite successful in predicting the track, the rapid deepening, the central pressure, and the maximum wind speed of typhoon Leo as verified with reports from the Hong Kong Observatory (HKO). The structure of the eye, the eye wall, and the spiral convective cloud band simulated in the model are found to be comparable to corresponding features identified in satellite images for the storm, and also with those reported by other authors. A trajectory analysis was performed. Three kinds of trajectory were found: (1) spirally rising trajectories near the eye wall; (2) spirally rising/descending trajectories in the convective/cloud free belt; (3) straight and fast rising trajectories in a heavy convection zone along one of the cloud bands on the periphery of the tropical cyclone. Both the HKO and the U.S. Joint Typhoon Warning Center (JTWC) reported the rapid deepening of Leo started around 00 UTC 29 April. In the model, the eye was first formed in the lower troposphere, and it extended to the upper troposphere within a few hours. We speculate that the spin-up of cyclonic rotation in the low-level eye enhanced the positive vorticity along the low-level eye wall. The positive vorticity was then transported to the upper troposphere by convection, leading to an extension and growth of the eye into the upper troposphere. To examine the impact of convective parameterization scheme (CPS) on the simulation, the Grell scheme (GLEX) was also tested. The GLEX predicted a weaker typhoon with a wilder eye that extended not as high up in the upper troposphere as BMEX. The different structures of the eye between the BMEX and GLEX suggest that the mesoscale features of the eye are dependent on the convection. In other words, the vertical and horizontal distribution of convective heating is essential to the development and structure of the eye.