Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models
The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essen...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Climate |
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| Online Access: | https://www.mdpi.com/2225-1154/11/12/245 |
| _version_ | 1797381523362545664 |
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| author | Seyhakreaksmey Duong Layheang Song Rattana Chhin |
| author_facet | Seyhakreaksmey Duong Layheang Song Rattana Chhin |
| author_sort | Seyhakreaksmey Duong |
| collection | DOAJ |
| description | The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change. |
| first_indexed | 2024-03-08T20:53:46Z |
| format | Article |
| id | doaj.art-7ff72967f3b94ee2a62f3314ced90c03 |
| institution | Directory Open Access Journal |
| issn | 2225-1154 |
| language | English |
| last_indexed | 2024-03-08T20:53:46Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Climate |
| spelling | doaj.art-7ff72967f3b94ee2a62f3314ced90c032023-12-22T14:00:56ZengMDPI AGClimate2225-11542023-12-01111224510.3390/cli11120245Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 ModelsSeyhakreaksmey Duong0Layheang Song1Rattana Chhin2Faculty of Hydrology and Water Resources Engineering, Institute of Technology of Cambodia, Russian Federation Blvd., Phnom Penh P.O. Box 86, CambodiaFaculty of Hydrology and Water Resources Engineering, Institute of Technology of Cambodia, Russian Federation Blvd., Phnom Penh P.O. Box 86, CambodiaFaculty of Hydrology and Water Resources Engineering, Institute of Technology of Cambodia, Russian Federation Blvd., Phnom Penh P.O. Box 86, CambodiaThe consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change.https://www.mdpi.com/2225-1154/11/12/245Coupled Model Intercomparison Project Phase 6Bias-Corrected Spatial Disaggregationconsecutive dry daysconsecutive wet daysmaximum 1-day precipitation |
| spellingShingle | Seyhakreaksmey Duong Layheang Song Rattana Chhin Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models Climate Coupled Model Intercomparison Project Phase 6 Bias-Corrected Spatial Disaggregation consecutive dry days consecutive wet days maximum 1-day precipitation |
| title | Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models |
| title_full | Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models |
| title_fullStr | Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models |
| title_full_unstemmed | Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models |
| title_short | Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models |
| title_sort | precipitation projection in cambodia using statistically downscaled cmip6 models |
| topic | Coupled Model Intercomparison Project Phase 6 Bias-Corrected Spatial Disaggregation consecutive dry days consecutive wet days maximum 1-day precipitation |
| url | https://www.mdpi.com/2225-1154/11/12/245 |
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