Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula
Several sources of bias are involved at each stage of a quantitative precipitation estimation process because weather radars measure precipitation amounts indirectly. Conventional methods compare the relative uncertainties between different stages of the process but seldom present the total uncertai...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/21/7928 |
| _version_ | 1797548487932379136 |
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| author | Jae-Kyoung Lee Chang Geun Song |
| author_facet | Jae-Kyoung Lee Chang Geun Song |
| author_sort | Jae-Kyoung Lee |
| collection | DOAJ |
| description | Several sources of bias are involved at each stage of a quantitative precipitation estimation process because weather radars measure precipitation amounts indirectly. Conventional methods compare the relative uncertainties between different stages of the process but seldom present the total uncertainty. Therefore, the objectives of this study were as follows: (1) to quantify the uncertainty at each stage of the process and in total; (2) to elucidate the ratio of the uncertainty at each stage in terms of the total uncertainty; and (3) to explain the uncertainty propagation process at each stage. This study proposed novel application of three methods (maximum entropy method, uncertainty Delta method, and modified-fractional uncertainty method) to determine the total uncertainty, level of uncertainty increase, and percentage of uncertainty at each stage. Based on data from 18 precipitation events that occurred over the Korean Peninsula, the applicability of the three methods was tested using a radar precipitation estimation process that comprised two quality control algorithms, two precipitation estimation methods, and two post-processing precipitation bias correction methods. Results indicated that the final uncertainty of each method was reduced in comparison with the initial uncertainty, and that the uncertainty was different at each stage depending on the method applied. |
| first_indexed | 2024-03-10T15:00:05Z |
| format | Article |
| id | doaj.art-b1a83befa1e84474844c5bd0399a169d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T15:00:05Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b1a83befa1e84474844c5bd0399a169d2023-11-20T20:14:39ZengMDPI AGApplied Sciences2076-34172020-11-011021792810.3390/app10217928Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean PeninsulaJae-Kyoung Lee0Chang Geun Song1Innovation Center for Engineering Education, Daejin University, Pocheon-si, Gyeonggi-do 11159, KoreaDepartment of Safety Engineering, Incheon National University, Incheon 22012, KoreaSeveral sources of bias are involved at each stage of a quantitative precipitation estimation process because weather radars measure precipitation amounts indirectly. Conventional methods compare the relative uncertainties between different stages of the process but seldom present the total uncertainty. Therefore, the objectives of this study were as follows: (1) to quantify the uncertainty at each stage of the process and in total; (2) to elucidate the ratio of the uncertainty at each stage in terms of the total uncertainty; and (3) to explain the uncertainty propagation process at each stage. This study proposed novel application of three methods (maximum entropy method, uncertainty Delta method, and modified-fractional uncertainty method) to determine the total uncertainty, level of uncertainty increase, and percentage of uncertainty at each stage. Based on data from 18 precipitation events that occurred over the Korean Peninsula, the applicability of the three methods was tested using a radar precipitation estimation process that comprised two quality control algorithms, two precipitation estimation methods, and two post-processing precipitation bias correction methods. Results indicated that the final uncertainty of each method was reduced in comparison with the initial uncertainty, and that the uncertainty was different at each stage depending on the method applied.https://www.mdpi.com/2076-3417/10/21/7928radar-based precipitationuncertainty quantificationuncertainty propagationmaximum entropydelta methodfractional uncertainty method |
| spellingShingle | Jae-Kyoung Lee Chang Geun Song Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula Applied Sciences radar-based precipitation uncertainty quantification uncertainty propagation maximum entropy delta method fractional uncertainty method |
| title | Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula |
| title_full | Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula |
| title_fullStr | Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula |
| title_full_unstemmed | Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula |
| title_short | Novel Application of Uncertainty Analysis Methods for Quantitative Precipitation Estimation Based on Weather Radars in the Korean Peninsula |
| title_sort | novel application of uncertainty analysis methods for quantitative precipitation estimation based on weather radars in the korean peninsula |
| topic | radar-based precipitation uncertainty quantification uncertainty propagation maximum entropy delta method fractional uncertainty method |
| url | https://www.mdpi.com/2076-3417/10/21/7928 |
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