An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models
Climate change scenarios are used for predicting future precipitation. More detailed regional climate change scenarios are being used through dynamic downscale based on global circulation model results. There is a global tendency to utilize simulated precipitation data from downscaled regional clima...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/7363471 |
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| author | Dongwoo Jang |
| author_facet | Dongwoo Jang |
| author_sort | Dongwoo Jang |
| collection | DOAJ |
| description | Climate change scenarios are used for predicting future precipitation. More detailed regional climate change scenarios are being used through dynamic downscale based on global circulation model results. There is a global tendency to utilize simulated precipitation data from downscaled regional climate models (RCMs) suitable for each country. In Korea, there are studies for improving the accuracy of climate change scenario precipitation forecasts compared with observed precipitation. In this study, the precipitation of five regional climate models and actual observed precipitation provided in Korea are applied to ANN (artificial neural network), which suggests ways to improve prediction accuracy for precipitation. The ANN ensemble of RCMs simulates the actual observed precipitation more accurately than the individual RCM. In particular, it is more effective inland than in coastal areas, where precipitation patterns are complex. Pearson correlation coefficient of ANN is high as 0.04 compared with MRA. It is expected that more detailed analysis will be possible if it is applied not only to four cities but also to other regions in Korea. If observed precipitation data are collected in sufficient quantity, the applicability of the ANN model will widen. |
| format | Article |
| id | doaj-art-7ec962fc09b441bab1cef3046cef49ec |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-7ec962fc09b441bab1cef3046cef49ec2025-02-03T05:49:49ZengWileyAdvances in Civil Engineering1687-80861687-80942021-01-01202110.1155/2021/73634717363471An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate ModelsDongwoo Jang0Department of Civil & Environmental Engineering, Incheon National University, Incheon 22012, Republic of KoreaClimate change scenarios are used for predicting future precipitation. More detailed regional climate change scenarios are being used through dynamic downscale based on global circulation model results. There is a global tendency to utilize simulated precipitation data from downscaled regional climate models (RCMs) suitable for each country. In Korea, there are studies for improving the accuracy of climate change scenario precipitation forecasts compared with observed precipitation. In this study, the precipitation of five regional climate models and actual observed precipitation provided in Korea are applied to ANN (artificial neural network), which suggests ways to improve prediction accuracy for precipitation. The ANN ensemble of RCMs simulates the actual observed precipitation more accurately than the individual RCM. In particular, it is more effective inland than in coastal areas, where precipitation patterns are complex. Pearson correlation coefficient of ANN is high as 0.04 compared with MRA. It is expected that more detailed analysis will be possible if it is applied not only to four cities but also to other regions in Korea. If observed precipitation data are collected in sufficient quantity, the applicability of the ANN model will widen.http://dx.doi.org/10.1155/2021/7363471 |
| spellingShingle | Dongwoo Jang An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models Advances in Civil Engineering |
| title | An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models |
| title_full | An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models |
| title_fullStr | An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models |
| title_full_unstemmed | An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models |
| title_short | An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models |
| title_sort | application of ann ensemble for estimating of precipitation using regional climate models |
| url | http://dx.doi.org/10.1155/2021/7363471 |
| work_keys_str_mv | AT dongwoojang anapplicationofannensembleforestimatingofprecipitationusingregionalclimatemodels AT dongwoojang applicationofannensembleforestimatingofprecipitationusingregionalclimatemodels |