Application of statistical weather generators
WeaGETS is a MATLAB-based versatile random day-to-day weather generator. It can produce everyday rainfall amount, the maximum and minimum temperature for one station for any length of time. Because WeaGETS generates data over a long time, it is ideal for assessing agricultural and hydrological...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/154394 |
| _version_ | 1811695397097177088 |
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| author | Wang, Qin Yu |
| author2 | Qin Xiaosheng |
| author_facet | Qin Xiaosheng Wang, Qin Yu |
| author_sort | Wang, Qin Yu |
| collection | NTU |
| description | WeaGETS is a MATLAB-based versatile random day-to-day weather generator. It can produce
everyday rainfall amount, the maximum and minimum temperature for one station for any length
of time. Because WeaGETS generates data over a long time, it is ideal for assessing agricultural
and hydrological risk. It also allows for weather simulation in unknown regions. Furthermore, it
can be used as a low-cost method to investigate the impact of climate change on a specific place.
In this report, we use the first-order Markov model to generate the frequency of rainfall. Gamma
distribution to produce everyday rainfall amount. Precipitation generating parameters have been
smoothed using second-order Fourier Harmonics. Tmax and Tmin are generated under a conditional
scheme. WeaGETS is being used to simulate twenty-three years of data from the Year 1894 to the
Year 2006. We show all the details of data analysis for the first Year 1984 with the help of Excel
and graph. For the other twenty-two years, data can be found in the appendix. We use MATLAB
to run the WeaGETS. The coding we used had already been developed. Our primary target is to
find the accuracy of the simulation data generated by WeaGETS then find the application of the
WeaGETS.
After comparing both data analyze based on yearly and monthly, we find WeaGETS
underestimates the daily rainfall amount, frequency of rainfall, and minimum temperature.
However, it overestimates the maximum temperature, so we hope the WeaGETS can be improved
in the future. Moreover, we hope WeaGETS can develop to simulate not only for a single station.
Finally, we also hope WeaGETS can add more climate parameters for the simulation. |
| first_indexed | 2024-10-01T07:22:49Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/154394 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:22:49Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1543942021-12-23T12:04:51Z Application of statistical weather generators Wang, Qin Yu Qin Xiaosheng School of Civil and Environmental Engineering XSQIN@ntu.edu.sg Engineering::Civil engineering WeaGETS is a MATLAB-based versatile random day-to-day weather generator. It can produce everyday rainfall amount, the maximum and minimum temperature for one station for any length of time. Because WeaGETS generates data over a long time, it is ideal for assessing agricultural and hydrological risk. It also allows for weather simulation in unknown regions. Furthermore, it can be used as a low-cost method to investigate the impact of climate change on a specific place. In this report, we use the first-order Markov model to generate the frequency of rainfall. Gamma distribution to produce everyday rainfall amount. Precipitation generating parameters have been smoothed using second-order Fourier Harmonics. Tmax and Tmin are generated under a conditional scheme. WeaGETS is being used to simulate twenty-three years of data from the Year 1894 to the Year 2006. We show all the details of data analysis for the first Year 1984 with the help of Excel and graph. For the other twenty-two years, data can be found in the appendix. We use MATLAB to run the WeaGETS. The coding we used had already been developed. Our primary target is to find the accuracy of the simulation data generated by WeaGETS then find the application of the WeaGETS. After comparing both data analyze based on yearly and monthly, we find WeaGETS underestimates the daily rainfall amount, frequency of rainfall, and minimum temperature. However, it overestimates the maximum temperature, so we hope the WeaGETS can be improved in the future. Moreover, we hope WeaGETS can develop to simulate not only for a single station. Finally, we also hope WeaGETS can add more climate parameters for the simulation. Bachelor of Engineering (Civil) 2021-12-23T12:04:51Z 2021-12-23T12:04:51Z 2021 Final Year Project (FYP) Wang, Q. Y. (2021). Application of statistical weather generators. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154394 https://hdl.handle.net/10356/154394 en WR-30 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Civil engineering Wang, Qin Yu Application of statistical weather generators |
| title | Application of statistical weather generators |
| title_full | Application of statistical weather generators |
| title_fullStr | Application of statistical weather generators |
| title_full_unstemmed | Application of statistical weather generators |
| title_short | Application of statistical weather generators |
| title_sort | application of statistical weather generators |
| topic | Engineering::Civil engineering |
| url | https://hdl.handle.net/10356/154394 |
| work_keys_str_mv | AT wangqinyu applicationofstatisticalweathergenerators |