{"title":"补充ERA5和E-OBS的高分辨率欧洲河流流量","authors":"Stefan Hagemann , Tobias Stacke","doi":"10.1016/j.oceano.2022.07.003","DOIUrl":null,"url":null,"abstract":"<div><p>The 0.5° resolution of many global observational or quasi-observational datasets is not sufficient for the evaluation of current state-of-the-art regional climate models or the forcing of ocean model simulations over Europe. While higher resolved products are available for meteorological data, e.g. ERA5 reanalysis and the E-OBS vs 22 (EOBS22) datasets, they lack crucial information at the land-ocean boundary. ERA5 is frequently used to force regional climate models (RCMs) or ocean models and both datasets are commonly used as reference datasets for the evaluation of RCMs. Therefore, we extended both datasets with high-resolution river discharge for the period 1979–2018. On the one hand, our discharge data close the water cycle at the land-ocean interface so that the discharges can be used as lateral freshwater input for ocean models applied in the European region. On the other hand, the data can be used to identify trends in discharge that are induced by recent climate change as ERA5 and EOBS22 are rather independent datasets. The experimental setup to generate the discharges was chosen in a way that it could be easily adapted in a climate or Earth system modelling framework. Consequently, the recently developed 5 Min. horizontal resolution version of the hydrological discharge (HD) model was used to simulate discharge. It has already been applied in multiple climate modelling studies and is coupled within several global and regional Earth system models. As the HD model currently does not regard direct human impacts of the river runoff, it is well suited to investigate climate change-related discharge trends. In order to calculate the necessary gridded input fields for the HD model from ERA5 and EOBS22 data, we used the HydroPy global hydrological model. For both experiments, we found that the general behavior of discharge is captured well for many European rivers, which is consistent to earlier results. For the EOBS22 based discharges, a widespread low bias in simulated discharge occurs, which is likely caused by the missing undercatch correction in the underlying precipitation data. The analysis of trends over Southeastern Europe was hampered by missing data in EOBS22 after 2004. Using both experiments, we identified consistent trend patterns in various discharge statistics, with increases in low flow characteristics over Northern Europe and general drying trends over Central and Southern Europe. In summary, we introduced an experimental setup that is useful to generate high-resolution river runoff data consistent with the meteorological forcing for historical periods and future scenarios from any climate model data instead of having to rely on observed time series.</p></div>","PeriodicalId":54694,"journal":{"name":"Oceanologia","volume":"65 1","pages":"Pages 230-248"},"PeriodicalIF":2.6000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Complementing ERA5 and E-OBS with high-resolution river discharge over Europe\",\"authors\":\"Stefan Hagemann , Tobias Stacke\",\"doi\":\"10.1016/j.oceano.2022.07.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The 0.5° resolution of many global observational or quasi-observational datasets is not sufficient for the evaluation of current state-of-the-art regional climate models or the forcing of ocean model simulations over Europe. While higher resolved products are available for meteorological data, e.g. ERA5 reanalysis and the E-OBS vs 22 (EOBS22) datasets, they lack crucial information at the land-ocean boundary. ERA5 is frequently used to force regional climate models (RCMs) or ocean models and both datasets are commonly used as reference datasets for the evaluation of RCMs. Therefore, we extended both datasets with high-resolution river discharge for the period 1979–2018. On the one hand, our discharge data close the water cycle at the land-ocean interface so that the discharges can be used as lateral freshwater input for ocean models applied in the European region. On the other hand, the data can be used to identify trends in discharge that are induced by recent climate change as ERA5 and EOBS22 are rather independent datasets. The experimental setup to generate the discharges was chosen in a way that it could be easily adapted in a climate or Earth system modelling framework. Consequently, the recently developed 5 Min. horizontal resolution version of the hydrological discharge (HD) model was used to simulate discharge. It has already been applied in multiple climate modelling studies and is coupled within several global and regional Earth system models. As the HD model currently does not regard direct human impacts of the river runoff, it is well suited to investigate climate change-related discharge trends. In order to calculate the necessary gridded input fields for the HD model from ERA5 and EOBS22 data, we used the HydroPy global hydrological model. For both experiments, we found that the general behavior of discharge is captured well for many European rivers, which is consistent to earlier results. For the EOBS22 based discharges, a widespread low bias in simulated discharge occurs, which is likely caused by the missing undercatch correction in the underlying precipitation data. The analysis of trends over Southeastern Europe was hampered by missing data in EOBS22 after 2004. Using both experiments, we identified consistent trend patterns in various discharge statistics, with increases in low flow characteristics over Northern Europe and general drying trends over Central and Southern Europe. In summary, we introduced an experimental setup that is useful to generate high-resolution river runoff data consistent with the meteorological forcing for historical periods and future scenarios from any climate model data instead of having to rely on observed time series.</p></div>\",\"PeriodicalId\":54694,\"journal\":{\"name\":\"Oceanologia\",\"volume\":\"65 1\",\"pages\":\"Pages 230-248\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Oceanologia\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0078323422000793\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OCEANOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oceanologia","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0078323422000793","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
引用次数: 2
摘要
许多全球观测或准观测数据集的0.5°分辨率不足以评估目前最先进的区域气候模式或海洋模式模拟对欧洲的强迫作用。虽然有更高分辨率的产品可用于气象数据,例如ERA5再分析和E-OBS vs 22 (EOBS22)数据集,但它们缺乏陆地-海洋边界的关键信息。ERA5经常用于强迫区域气候模式(RCMs)或海洋模式,这两个数据集通常用作评估RCMs的参考数据集。因此,我们用1979-2018年期间的高分辨率河流流量扩展了这两个数据集。一方面,我们的排放数据接近陆地-海洋界面的水循环,因此排放可以用作欧洲地区应用的海洋模式的侧向淡水输入。另一方面,由于ERA5和EOBS22是相当独立的数据集,这些数据可用于识别近期气候变化引起的排放趋势。产生排放的实验装置的选择方式可以很容易地适应气候或地球系统建模框架。因此,采用最近开发的5分钟水平分辨率水文流量(HD)模型来模拟流量。它已应用于多个气候模式研究,并与若干全球和区域地球系统模式相结合。由于HD模型目前没有考虑人类对河流径流的直接影响,因此它非常适合研究与气候变化有关的排放趋势。为了从ERA5和EOBS22数据中计算HD模型所需的网格化输入场,我们使用了HydroPy全球水文模型。在这两个实验中,我们发现许多欧洲河流的一般排放行为被很好地捕获,这与早期的结果是一致的。对于基于EOBS22的流量,模拟流量出现了广泛的低偏差,这可能是由于下垫降水数据中缺少捕获下校正造成的。2004年之后EOBS22的数据缺失阻碍了对东南欧趋势的分析。通过这两个实验,我们在各种流量统计数据中发现了一致的趋势模式,北欧的低流量特征增加,中欧和南欧的总体干燥趋势增加。总之,我们介绍了一个实验装置,它可以从任何气候模式数据中生成与历史时期和未来情景的气象强迫相一致的高分辨率河流径流数据,而不必依赖于观测到的时间序列。
Complementing ERA5 and E-OBS with high-resolution river discharge over Europe
The 0.5° resolution of many global observational or quasi-observational datasets is not sufficient for the evaluation of current state-of-the-art regional climate models or the forcing of ocean model simulations over Europe. While higher resolved products are available for meteorological data, e.g. ERA5 reanalysis and the E-OBS vs 22 (EOBS22) datasets, they lack crucial information at the land-ocean boundary. ERA5 is frequently used to force regional climate models (RCMs) or ocean models and both datasets are commonly used as reference datasets for the evaluation of RCMs. Therefore, we extended both datasets with high-resolution river discharge for the period 1979–2018. On the one hand, our discharge data close the water cycle at the land-ocean interface so that the discharges can be used as lateral freshwater input for ocean models applied in the European region. On the other hand, the data can be used to identify trends in discharge that are induced by recent climate change as ERA5 and EOBS22 are rather independent datasets. The experimental setup to generate the discharges was chosen in a way that it could be easily adapted in a climate or Earth system modelling framework. Consequently, the recently developed 5 Min. horizontal resolution version of the hydrological discharge (HD) model was used to simulate discharge. It has already been applied in multiple climate modelling studies and is coupled within several global and regional Earth system models. As the HD model currently does not regard direct human impacts of the river runoff, it is well suited to investigate climate change-related discharge trends. In order to calculate the necessary gridded input fields for the HD model from ERA5 and EOBS22 data, we used the HydroPy global hydrological model. For both experiments, we found that the general behavior of discharge is captured well for many European rivers, which is consistent to earlier results. For the EOBS22 based discharges, a widespread low bias in simulated discharge occurs, which is likely caused by the missing undercatch correction in the underlying precipitation data. The analysis of trends over Southeastern Europe was hampered by missing data in EOBS22 after 2004. Using both experiments, we identified consistent trend patterns in various discharge statistics, with increases in low flow characteristics over Northern Europe and general drying trends over Central and Southern Europe. In summary, we introduced an experimental setup that is useful to generate high-resolution river runoff data consistent with the meteorological forcing for historical periods and future scenarios from any climate model data instead of having to rely on observed time series.
期刊介绍:
Oceanologia is an international journal that publishes results of original research in the field of marine sciences with emphasis on the European seas.