Annex I Hong Kong Observatory Summer Placement Programme 2015 Training Programme : An Observatory mentor with relevant expertise will supervise the students. Training Period : 8 weeks, starting from 8 June 2015. General Requirements : Applicants should (1) be citizen of Hong Kong; (2) be undergraduate students; (3) have academic background and specific knowledge/skills as specified in Annex II; and (4) be fluent in both Chinese and English. Scholarship : A scholarship for 8 weeks (with a current rate at HK$ 8,800 per month) will be granted by the Observatory to each of the students successfully enrolled in the Programme. The Observatory reserves the right to choose to withdraw the scholarship, on a pro-rata basis, should the offer be terminated for any reasons. Student Status : Students will receive training at the Observatory as student trainees and there is no employer-employee relationship. Their status as registered students of their respective university will be maintained. Project Specifications : Please refer to Annex II Application Procedures : Applicants should submit the application form together with copies of official transcript of studies (or other means of proof of studies containing academic results) and other information as required in Annex II, (i) by post to Training and Exercises Division, 2304-2309 Miramar Tower, 132 Nathan Road, Tsim Sha Tsui, Kowloon. Or (ii) by email to train2@hko.gov.hk The deadline for application is 24 April 2015. Note : Personal data provided by job applications will be used strictly in accordance with the HKSAR Government s personal data policies, a copy of which will be provided upon request. Offer of Appointment : Successful candidates will be notified by 26 May 2015. Those who have not been informed of the results of selection by this date shall assume that their applications are unsuccessful. Enquiries : For further information, please contact Mr. Terence Kung at 2926 8319 or Ms PY Yeung at 2926 8318.
Proposals of Summer Placement Programme 2015 Division Project Title Job description Subject and year of study required A2 Impact of dual-polarization Doppler radar data on Mathematics or short-term related quantitative precipitation forecast A2 Spatial structure of wind disturbances affecting aircraft landing/departure Hong Kong Observatory acquired its first dual-polarization Doppler radar in year 2012. The aim of the project is to study the impact of assimilating the additional information obtained from a dual-polarization Doppler radar in a short-term rainfall forecast from a numerical weather prediction (NWP) model. The placement student will be required to develop computer programs to convert radar data in its raw format into a format that can be input into NWP model and evaluate the performance of a NWP model. The Hong Kong Observatory operates the world s first LIDAR (LIght Detection And Ranging) system for alerting of windshear for departing and arriving aircraft at the Hong Kong International Airport. This project studies the spatial characteristics of wind disturbances leading to pilot reports of windshear/ turbulence using spectral methods (e.g. Fourier or wavelet analysis). The intern will develop algorithms for identifying key wind features from high-resolution wind measurements from the LIDAR; and conduct re-analysis of past windshear/ turbulence episodes to improve understanding of their spatial-temporal evolution. Physics, Mathematics or related Annex II Specific knowledge / skills required / remarks Genuine interest in meteorology. Strong academic background. Experience with computer simulation preferred. Strong academic background with knowledge in fluid dynamics. Experience in Fortran/C++ programming.
A2 High-resolution simulation of urban wind flow Wind measurements are influenced by their surrounding environment. When considering the issuance of Tropical Cyclone (TC) Warning Signals, the Hong Kong Observatory makes reference to a number of reference stations to assess the sustained wind conditions generally over Hong Kong. This project studies the effect of urban development on wind measurements at one of the TC reference stations. Physics, Engineering or related Strong academic background. Interest in urban meteorology e.g. local wind effects in Hong Kong. Experience in computer simulations beneficial. The intern will develop algorithms for processing high-resolution urban data over the Kai Tak area; and conduct Computer Fluid Dynamics (CFD) simulations on the wind distribution under TC conditions. Results will be validated against observations from Automatic Weather Stations.
D1&D3 A study on the effects of climatic factors on reservoir yields in Hong Kong Identify possible meteorological factors which may influence reservoir yields in Hong Kong. Explore correlations between the reservoir yields and different meteorological elements or indices using the meteorological observations of the Observatory and the water yield data of the Water Supplies Department (WSD). Further assess the possible contribution of climatic effects on the observed changes in reservoir yields in Hong Kong. Science, Atmospheric Science, Statistics, or related Strong interest in meteorology and hydrology. Proficiency in data processing, statistics analysis and the use of statistical analysis tools (e.g. R programming software). The project may also need to collaborate with experts of WSD, in particular on the interpretation of reservoir yield data. D1 A search of trochoidal motion for tropical cyclones near landfall This project aims to explore oscillations in the track of a tropical cyclone (TC) when it is close to land. The work will involve examining observations near TC center to identify possible oscillations/vacillations in the track. Once these TCs are identified, detailed radar images will be examined to ascertain whether these oscillations/vacillations did exist. Characteristics of these TCs such as intensity, translation speed, etc. will also be investigated. Science, Atmospheric Science, Statistics, or related Strong interest in meteorology, in particular on tropical cyclones. Skillful in data processing and analysis. Proficiency in literature search and review.
D3 F3 Forecasting yield collected in reservoirs in Hong Kong using ECMWF seasonal forecast products Development of model post-processing method for generating location-specific weather forecast over Hong Kong ECMWF seasonal forecast data will be downscaled to generate yield forecasts for Hong Kong which is not a standard output parameter of climate models. The performance of a consensus forecast derived from a number of predictors identified from ECMWF model data will be investigated. Comparison between the new and existing method will be made. Develop automatic algorithms for generating location-specific weather forecast using numerical weather prediction model outputs, for example temperature and wind forecast, including the effects due to orography and land-surface characteristics. Physics, Statistics, Geography, Earth Genuine interests in meteorology and climate statistics. Proficiency in literature search, data management and the use of statistical analysis tools (e.g. R package) Interest and knowledge in meteorology. Good knowledge in scientific computing and statistical data analysis. Familiar with Linux/UNIX environment. F3 A study on using high-resolution raingauge data to enhance rainfall nowcasting To study the impact of raingauge measurements at 1-minute interval on the rainfall nowcasting system to better support the operation of the rainstorm warning. Interest and knowledge in meteorology. Good knowledge in data analysis, computer programming, and using statistical analysis software. Familiar with Linux/UNIX environment.
F4 Development of digital weather forecast for Pearl River Delta region Study the use of forecast data from Numerical Weather Prediction (NWP) models to develop rainfall and cloud cover forecasts for gridded locations within the Pearl River Delta region. Physics, Science, Earth System Science or related Interest and knowledge in meteorology and weather forecasting. Familiar with Linux/UNIX environment. Good knowledge in scientific programming and statistical data analysis. R2 R3 Development of an online system for management of education and training resources Experimental studies of soil moisture measurements in Hong Kong Develop an in-house online application to manage the Hong Kong Observatory s internal and external education and training resources. The system will consist of an user friendly interface to manage and facilitate search for relevant resources. Tailor-made functions to enhance user experience like recording individual training records and CPD hours will be included. Evaluate the performance of soil moisture sensors and study the characteristics of soil moisture data collected by the sensors. Computer Science, IT Engineering, or related Completion of 1 st or 2 nd Knowledge in web development. Experience in script and database programming using PHP and MySQL. Genuine interest in meteorology. Knowledge in data management and skills in the use of statistical analysis tools (e.g. Microsoft Excel) preferred.
R3 R4 Evaluation of meteorological sensors for use in portable automatic weather station development Comparison of the various dispersion schemes in the Observatory s Accident Consequence Assessment System (ACAS) Assess the performance of a variety of meteorological sensors for development of microprocessor based portable weather stations. The evaluation process would involve design and development of prototype circuit boards involving SMD and low level programming. To carry out simulation case studies using various dispersion schemes available in the Hong Kong Observatory s ACAS, with an aim to gain better understanding of their characteristics and applicability under different situations. Physics, Electronics, Computer Science or related Completion of 1 st or 2 nd Nuclear Engineering or related Completion of 2nd Interest in meteorology and meteorological instrumentation. Knowledge of electronic prototyping, java/c programming, and use of statistical analysis tools (e.g. MS Excel) would be advantageous. Experience in data analysis and graph plotting. Some knowledge in computer programming is preferred.