Evaluation of the ERA5‐Land Reanalysis Data Set for Process‐Based River Temperature Modeling Over Data Sparse and Topographically Complex Regions

Mihalevich, Bryce A.; Neilson, Bethany T.; Buahin, Caleb A.

doi:10.1029/2021wr031294

Cited by 7 publications

(3 citation statements)

References 71 publications

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“…On the other hand, the ERA5-Land dataset, which was released in July 2019, is an upgraded version of ERA5 that focused on land applications by incorporating the terrestrial component of ERA5 reanalysis from 1950 to the present [25]. Notably, the ERA5-Land dataset has a higher spatial resolution compared to the ERA-Interim and ERA5 datasets, representing an improvement over these datasets [18,26,27]. The ERA5 and ERA5-Land temperature and precipitation data, which offer long-term time series and spatial coverage over the entire Altay region, can compensate for the limitations of sparse meteorological station distribution and limited temporal data in arid and semi-arid areas.…”

Section: Era5 and Era5-land Temperature And Precipitation Datamentioning

confidence: 99%

Evaluating and Correcting Temperature and Precipitation Grid Products in the Arid Region of Altay, China

Zhang,

Jiapaer,

et al. 2024

Remote Sensing

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Temperature and precipitation are crucial indicators for investigating climate changes, necessitating precise measurements for rigorous scientific inquiry. While the Fifth Generation of European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis (ERA5), ERA5 of the Land Surface (ERA5-Land), and China Meteorological Forcing Dataset (CMFD) temperature and precipitation products are widely used worldwide, their suitability for the Altay region of arid and semi-arid areas has received limited attention. Here, we used the Altay region as the study area, utilizing meteorological station data and implementing the residual revision method for temperature and the coefficient revision method for precipitation to rectify inaccuracies in monthly temperature and precipitation records from ERA5-Land, ERA5, and CMFD. We evaluate the accuracy of these datasets before and after correction using bias, Taylor diagrams, and root-mean-square error (RMSE) metrics. Additionally, we employ Tropical Rainfall Measuring Mission satellite precipitation data (TRMM) as a benchmark to assess the performance of ERA5-Land, ERA5, and CMFD monthly precipitation before and after correction. The results revealed significant differences in the temperature and precipitation capture capabilities of ERA5-Land, ERA5, and CMFD in the Altay region. Overall, these data exhibit substantial errors and are not directly suitable for scientific research. However, we applied residual and coefficient revision methods. After this revision, ERA5-Land, ERA5, and CMFD showed significantly improved temperature and precipitation capture capabilities, especially for ERA5-Land. In terms of temperature, post-revision-CMFD (CMFDPR) demonstrated better temperature capture capabilities. All three datasets showed weaker performance in mountainous regions compared to plains. Notably, post-revision-ERA5 (ERA5PR) seemed unsuitable for capturing temperature in the Altay region. Concerning rain, CMFDPR, post-revision-ERA5-Land (ERA5-LandPR) and ERA5PR outperformed TRMM in capturing precipitation. CMFDPR and ERA5-LandPR both outperform ERA5PR. In summary, the revision datasets effectively compensated for the sparse distribution of meteorological stations in the Altay region, providing reliable data support for studying climate change in arid and semi-arid areas.

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Section: Era5 and Era5-land Temperature And Precipitation Datamentioning

confidence: 99%

Evaluating and Correcting Temperature and Precipitation Grid Products in the Arid Region of Altay, China

Zhang,

Jiapaer,

et al. 2024

Remote Sensing

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“…While process‐based models have the capacity to evaluate not only a range of forest‐cover scenarios but also the effects of climate change and water management, they require substantial effort by highly qualified analysts, as well as extensive input data, such as solar radiation, that may not be available in an operational context. However, the increasing availability and ongoing development of atmospheric re‐analysis products such as the European Centre for Medium‐Range Weather Forecasts ERA5 product may help to mitigate challenges related to availability of input data (Mihalevich et al, 2022). Further research should focus on evaluating the utility of these products as input to stream temperature models.…”

Section: Process‐based Modellingmentioning

confidence: 99%

“…For smaller streams, hyporheic exchange can have a substantial influence on stream thermal dynamics (e.g., Johnson, 2004 Weather Forecasts ERA5 product may help to mitigate challenges related to availability of input data (Mihalevich et al, 2022). Further research should focus on evaluating the utility of these products as input to stream temperature models.…”

Section: Temporal Scale and Extentmentioning

confidence: 99%

JAMES BUTTLE REVIEW: Quantifying the influence of forestry and forest disturbance on stream temperature: Methodologies and challenges

Moore,

MacDonald

2024

Hydrological Processes

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Stream temperature governs many aquatic ecosystem processes and plays a key role in determining the distribution of cold‐water amphibians and cool‐ and cold‐water fish, including salmonids. Decades of research have focused on the effects of forestry and forest disturbance on stream temperature, and new projects are underway or being planned in jurisdictions including the Provinces of Alberta and British Columbia, Canada, and Washington State, USA. The objective of this paper is to provide a critical review of methodologies employed in previous studies. The review initially focuses on the range of metrics used to quantify stream thermal regimes and the factors that control stream temperature variability in time and space, then focuses on sampling and analytical methodologies used to quantify stream temperature response to forestry activity and forest disturbance. Empirical methods include sampling in time, space, or both, and may or may not include pre‐ and post‐harvest data. Process‐based mechanistic and hybrid empirical‐mechanistic models have also been applied. The advantages and disadvantages of these approaches are discussed, and recommendations provided to support the design and execution of future studies.

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Water Budget Input Linked to Atmospheric Rivers in British Columbia's Nechako River Basin

Sobral,

Déry

2024

Hydrological Processes

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This study explores the contribution of atmospheric rivers (ARs) to the water budget input of the Nechako River Basin (NRB) in British Columbia (BC), western Canada. The study quantifies the fraction of precipitation, rainfall, snowfall, and snow water equivalent (SWE) associated with ARs at multiple scales and tests for trends using the Mann–Kendall (MK) test. AR‐related totals for 1950–2021 were created by linking AR events to water budget input variables of the ERA5‐Land reanalysis product on a daily scale. Associations with different phases of the El Niño‐Southern Oscillation (ENSO) climate pattern and AR‐related contributions to the NRB are also investigated. Results indicate an increasing fractional contribution of rain in ARs landfalling in the NRB in the last two decades (2000–2019). Moreover, 21% of the total annual precipitation in the NRB is associated with ARs, with decreasing contributions from west to east. October has higher AR‐related total precipitation than other months, while March, May and June are the least affected. ARs contribute disproportionately more to mid‐ and high‐intensity daily precipitation totals, and provide up to 45% and 24% of the seasonal rainfall and snowfall, respectively. AR‐related SWE is relatively higher in autumn due to the increased frequency and intensity of ARs, resulting in a greater fractional contribution of ARs to the snowpack compared to winter. ARs influence snowpack accumulation during fall (18%) and winter (13%) but also increase the risk of natural hazards. The MK test for AR‐related water budget variables on the annual scale identified no significant trends. However, AR‐related snowfall shows decreasing trends in the NRB, more specifically in the Upper Nechako, Lower Nechako and Stellako sub‐basins during the summer. Over the study period, ARs consistently contribute up to one‐fifth of the annual input to the NRB's water budget. This study provides the first quantitative assessment and trend analyses of AR contributions to the water budget input of a reservoir‐regulated watershed in north‐central BC, yielding valuable information for hydropower production, ecological flows, irrigation, domestic and industrial water use.

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Evaluation of the ERA5‐Land Reanalysis Data Set for Process‐Based River Temperature Modeling Over Data Sparse and Topographically Complex Regions

Cited by 7 publications

References 71 publications

Evaluating and Correcting Temperature and Precipitation Grid Products in the Arid Region of Altay, China

Evaluating and Correcting Temperature and Precipitation Grid Products in the Arid Region of Altay, China

JAMES BUTTLE REVIEW: Quantifying the influence of forestry and forest disturbance on stream temperature: Methodologies and challenges

Water Budget Input Linked to Atmospheric Rivers in British Columbia's Nechako River Basin

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