Elise M. B. Olson, Jasmin G. John, John P. Dunne, Charles Stock, Elizabeth J. Drenkard, Adrienne J. Sutton
{"title":"基于高频地表观测数据和地球系统模型的特定地点多重压力评估","authors":"Elise M. B. Olson, Jasmin G. John, John P. Dunne, Charles Stock, Elizabeth J. Drenkard, Adrienne J. Sutton","doi":"10.1029/2023EA003357","DOIUrl":null,"url":null,"abstract":"<p>Global Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well-resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation-based assessments of the fraction of days experiencing surface T-pH and T-Ω<sub><i>arag</i></sub> multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EA003357","citationCount":"0","resultStr":"{\"title\":\"Site-Specific Multiple Stressor Assessments Based on High Frequency Surface Observations and an Earth System Model\",\"authors\":\"Elise M. B. Olson, Jasmin G. John, John P. Dunne, Charles Stock, Elizabeth J. Drenkard, Adrienne J. Sutton\",\"doi\":\"10.1029/2023EA003357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Global Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well-resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation-based assessments of the fraction of days experiencing surface T-pH and T-Ω<sub><i>arag</i></sub> multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases.</p>\",\"PeriodicalId\":54286,\"journal\":{\"name\":\"Earth and Space Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EA003357\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Earth and Space Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1029/2023EA003357\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ASTRONOMY & ASTROPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth and Space Science","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2023EA003357","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
Site-Specific Multiple Stressor Assessments Based on High Frequency Surface Observations and an Earth System Model
Global Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well-resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation-based assessments of the fraction of days experiencing surface T-pH and T-Ωarag multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases.
期刊介绍:
Marking AGU’s second new open access journal in the last 12 months, Earth and Space Science is the only journal that reflects the expansive range of science represented by AGU’s 62,000 members, including all of the Earth, planetary, and space sciences, and related fields in environmental science, geoengineering, space engineering, and biogeochemistry.