Evaluation of historical precipitation interannual variability in CMIP6 over the United States
Interannual precipitation variability profoundly influences society via its effects on agriculture, water resources, infrastructure, and disaster risks. In this study, we use daily in situ precipitation observations from the global historical climatology network-daily (GHCN-D) to assess the ability...
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IOP Publishing
2025-01-01
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| Series: | Environmental Research: Climate |
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| Online Access: | https://doi.org/10.1088/2752-5295/ada17c |
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| author | Ryan D Harp Thierry N Taguela Akintomide A Akinsanola Daniel E Horton |
| author_facet | Ryan D Harp Thierry N Taguela Akintomide A Akinsanola Daniel E Horton |
| author_sort | Ryan D Harp |
| collection | DOAJ |
| description | Interannual precipitation variability profoundly influences society via its effects on agriculture, water resources, infrastructure, and disaster risks. In this study, we use daily in situ precipitation observations from the global historical climatology network-daily (GHCN-D) to assess the ability of 21 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, including the 50-member fifth-generation Canadian Earth System Model single model initial-condition large ensemble (CanESM5_SMILE), to realistically simulate historical interannual precipitation variability trends within 17 regions of the contiguous United States (CONUS). We assess how accurately the CMIP6 simulations align with observational data across annual, summer, and winter periods, focusing on four key hydrometeorological metrics, including interannual precipitation variability, relative interannual precipitation variability (coefficient of variation), annual mean precipitation, and annual wet day frequency. Our findings reveal that CMIP6 ensemble members generally reproduce the spatial patterns of observed trends in annual mean precipitation. In most regions, models agree well with the signs of observed changes in annual mean precipitation, though discrepancies in trend magnitude are evident. Further, observed trends in winter mean precipitation broadly exhibit a spatial pattern similar to that of the observed annual mean. However, analysis of the CanESM5_SMILE shows that trends in precipitation variability may primarily be the result of model-simulated internal variability, suggesting caution in interpreting multi-model single-realization ensemble results. Challenges in accurately simulating interannual precipitation variability underscore the need for ongoing model refinement and validation to enhance climate projections, especially in regions vulnerable to extreme precipitation events. |
| format | Article |
| id | doaj-art-4f9776b821e64189b6c523a77a372e51 |
| institution | Kabale University |
| issn | 2752-5295 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
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| series | Environmental Research: Climate |
| spelling | doaj-art-4f9776b821e64189b6c523a77a372e512025-01-02T16:20:35ZengIOP PublishingEnvironmental Research: Climate2752-52952025-01-013404503210.1088/2752-5295/ada17cEvaluation of historical precipitation interannual variability in CMIP6 over the United StatesRyan D Harp0https://orcid.org/0000-0002-2872-8541Thierry N Taguela1https://orcid.org/0000-0001-8140-125XAkintomide A Akinsanola2https://orcid.org/0000-0002-0192-0082Daniel E Horton3https://orcid.org/0000-0002-2065-4517Department of Earth, Environmental, and Planetary Sciences, Northwestern University , Evanston, IL, United States of AmericaDepartment of Earth and Environmental Sciences, University of Illinois Chicago , Chicago, IL, United States of AmericaDepartment of Earth and Environmental Sciences, University of Illinois Chicago , Chicago, IL, United States of America; Environmental Science Division, Argonne National Laboratory , Lemont, IL, United States of AmericaDepartment of Earth, Environmental, and Planetary Sciences, Northwestern University , Evanston, IL, United States of AmericaInterannual precipitation variability profoundly influences society via its effects on agriculture, water resources, infrastructure, and disaster risks. In this study, we use daily in situ precipitation observations from the global historical climatology network-daily (GHCN-D) to assess the ability of 21 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, including the 50-member fifth-generation Canadian Earth System Model single model initial-condition large ensemble (CanESM5_SMILE), to realistically simulate historical interannual precipitation variability trends within 17 regions of the contiguous United States (CONUS). We assess how accurately the CMIP6 simulations align with observational data across annual, summer, and winter periods, focusing on four key hydrometeorological metrics, including interannual precipitation variability, relative interannual precipitation variability (coefficient of variation), annual mean precipitation, and annual wet day frequency. Our findings reveal that CMIP6 ensemble members generally reproduce the spatial patterns of observed trends in annual mean precipitation. In most regions, models agree well with the signs of observed changes in annual mean precipitation, though discrepancies in trend magnitude are evident. Further, observed trends in winter mean precipitation broadly exhibit a spatial pattern similar to that of the observed annual mean. However, analysis of the CanESM5_SMILE shows that trends in precipitation variability may primarily be the result of model-simulated internal variability, suggesting caution in interpreting multi-model single-realization ensemble results. Challenges in accurately simulating interannual precipitation variability underscore the need for ongoing model refinement and validation to enhance climate projections, especially in regions vulnerable to extreme precipitation events.https://doi.org/10.1088/2752-5295/ada17cUnited Statesprecipitationinterannual variabilityCMIP6 modelsinternal variability |
| spellingShingle | Ryan D Harp Thierry N Taguela Akintomide A Akinsanola Daniel E Horton Evaluation of historical precipitation interannual variability in CMIP6 over the United States Environmental Research: Climate United States precipitation interannual variability CMIP6 models internal variability |
| title | Evaluation of historical precipitation interannual variability in CMIP6 over the United States |
| title_full | Evaluation of historical precipitation interannual variability in CMIP6 over the United States |
| title_fullStr | Evaluation of historical precipitation interannual variability in CMIP6 over the United States |
| title_full_unstemmed | Evaluation of historical precipitation interannual variability in CMIP6 over the United States |
| title_short | Evaluation of historical precipitation interannual variability in CMIP6 over the United States |
| title_sort | evaluation of historical precipitation interannual variability in cmip6 over the united states |
| topic | United States precipitation interannual variability CMIP6 models internal variability |
| url | https://doi.org/10.1088/2752-5295/ada17c |
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