High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island Catchment
In the vicinity of orographic barriers, interactions between mountains and prevailing winds can enhance rainfall and generate strong spatial gradients of precipitation. Orographic rainfall is still poorly quantified despite being an important driver of headwater catchment hydrology, in particular wh...
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| Format: | Article |
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Frontiers Media S.A.
2021-01-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2020.546246/full |
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| author | L. Benoit L. Benoit M. Lucas H. Tseng Y.-F. Huang Y.-P. Tsang A. D. Nugent T. W. Giambelluca T. W. Giambelluca G. Mariethoz |
| author_facet | L. Benoit L. Benoit M. Lucas H. Tseng Y.-F. Huang Y.-P. Tsang A. D. Nugent T. W. Giambelluca T. W. Giambelluca G. Mariethoz |
| author_sort | L. Benoit |
| collection | DOAJ |
| description | In the vicinity of orographic barriers, interactions between mountains and prevailing winds can enhance rainfall and generate strong spatial gradients of precipitation. Orographic rainfall is still poorly quantified despite being an important driver of headwater catchment hydrology, in particular when considered at high space-time resolution. In this paper, we propose a complete framework for the observation and quantification of orographic rainfall gradients at the local scale. This framework, based on the stochastic interpolation of drop-counting rain gauge observations, provides reconstructions of local rain fields at high space-time resolution. It allows us to capture the life-cycle of individual rain cells, which typically occurs at a spatial scale of approximately 1–5 km and a temporal scale of approximately 5–15 min over our study area. In addition, the resulting rain estimates can be used to investigate how rainfall gradients develop during rain storms, and to provide better input data to drive hydrological models. The proposed framework is presented in the form of a proof-of-concept case study aimed at exploring orographic rain gradients in Mānoa Valley, on the leeward side of the Island of Oʻahu, Hawaiʻi, USA. Results show that our network of eight rain gauges captured rainfall variations over the 6 × 5 km2 study area, and that stochastic interpolation successfully leverages these in-situ data to produce rainfall maps at 200 m × 1 min resolution. Benchmarking against Kriging shows better performance of stochastic interpolation in reproducing key statistics of high-resolution rain fields, in particular rain intermittency and low intensities. This leads to an overall enhancement of rain prediction at ungauged locations. |
| first_indexed | 2024-12-14T04:26:47Z |
| format | Article |
| id | doaj.art-a1da122fcc284d8d9c425b128a871cf0 |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-12-14T04:26:47Z |
| publishDate | 2021-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-a1da122fcc284d8d9c425b128a871cf02022-12-21T23:17:11ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632021-01-01810.3389/feart.2020.546246546246High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island CatchmentL. Benoit0L. Benoit1M. Lucas2H. Tseng3Y.-F. Huang4Y.-P. Tsang5A. D. Nugent6T. W. Giambelluca7T. W. Giambelluca8G. Mariethoz9Institute of Earth Surface Dynamics (IDYST), University of Lausanne, Lausanne, SwitzerlandWater Resources Research Center, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesDepartment of Geography, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesDepartment of Geography, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesDepartment of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesDepartment of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesDepartment of Atmospheric Sciences, School of Ocean and Earth Science and Technology, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesDepartment of Geography, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesWater Resources Research Center, University of Hawai‘i at Mānoa, Honolulu, HI, United StatesInstitute of Earth Surface Dynamics (IDYST), University of Lausanne, Lausanne, SwitzerlandIn the vicinity of orographic barriers, interactions between mountains and prevailing winds can enhance rainfall and generate strong spatial gradients of precipitation. Orographic rainfall is still poorly quantified despite being an important driver of headwater catchment hydrology, in particular when considered at high space-time resolution. In this paper, we propose a complete framework for the observation and quantification of orographic rainfall gradients at the local scale. This framework, based on the stochastic interpolation of drop-counting rain gauge observations, provides reconstructions of local rain fields at high space-time resolution. It allows us to capture the life-cycle of individual rain cells, which typically occurs at a spatial scale of approximately 1–5 km and a temporal scale of approximately 5–15 min over our study area. In addition, the resulting rain estimates can be used to investigate how rainfall gradients develop during rain storms, and to provide better input data to drive hydrological models. The proposed framework is presented in the form of a proof-of-concept case study aimed at exploring orographic rain gradients in Mānoa Valley, on the leeward side of the Island of Oʻahu, Hawaiʻi, USA. Results show that our network of eight rain gauges captured rainfall variations over the 6 × 5 km2 study area, and that stochastic interpolation successfully leverages these in-situ data to produce rainfall maps at 200 m × 1 min resolution. Benchmarking against Kriging shows better performance of stochastic interpolation in reproducing key statistics of high-resolution rain fields, in particular rain intermittency and low intensities. This leads to an overall enhancement of rain prediction at ungauged locations.https://www.frontiersin.org/articles/10.3389/feart.2020.546246/fullrainfall mappingorographic rainfall gradientstochastic interpolationdrop counting rain gaugeshydrometeorology |
| spellingShingle | L. Benoit L. Benoit M. Lucas H. Tseng Y.-F. Huang Y.-P. Tsang A. D. Nugent T. W. Giambelluca T. W. Giambelluca G. Mariethoz High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island Catchment Frontiers in Earth Science rainfall mapping orographic rainfall gradient stochastic interpolation drop counting rain gauges hydrometeorology |
| title | High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island Catchment |
| title_full | High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island Catchment |
| title_fullStr | High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island Catchment |
| title_full_unstemmed | High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island Catchment |
| title_short | High Space-Time Resolution Observation of Extreme Orographic Rain Gradients in a Pacific Island Catchment |
| title_sort | high space time resolution observation of extreme orographic rain gradients in a pacific island catchment |
| topic | rainfall mapping orographic rainfall gradient stochastic interpolation drop counting rain gauges hydrometeorology |
| url | https://www.frontiersin.org/articles/10.3389/feart.2020.546246/full |
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