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This page includes a list of scientific work that fully or partly include diagnostics and verification and/or description of the Copernicus Arctic Regional Reanalysis (CARRA) data set. The list includes links, abstract of peer-reviewed work and some details to provide initial insight on what part of the CARRA data is evaluated. The list is not necessarily complete in terms of including all published work on and with the CARRA data set, but provides a starting point to seek information on the quality of different aspects of the data set in the literature.
Peer-reviewed studies
Schyberg et al. in preparation: The Copernicus Arctic regional reanalyis | ||||
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Type of study: System description | Parameters: 2m air temperature and humidity, 10m wind speed, precipitation, Mean sea Level Pressure | Comparison against: synop observations, ERA5 | Region and time period: 1991-2020, both CARRA domains (sub-regions: Svalbard, coast, inland etc…) | Features: Summary statistics, trends, case-studies |
Summary/abstract (paper): This paper is in preparation and will provide a full scientific description and evaluation of the Copernicus Arctic Regional Reanalysis. Abstract and link to published paper will be provided when published. |
Køltzow M., Schyberg H., Støylen E., & Yang X. (2022). Value of the Copernicus Arctic Regional Reanalysis (CARRA) in representing near-surface temperature and wind speed in the north-east European Arctic. Polar Research, 41. https://doi.org/10.33265/polar.v41.8002 | ||||
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Type of study: Evaluation/verification | Parameters: 2m air temperature, 10m wind speed | Comparison against: synop observations, ERA5 | Region and time period: 1998-2018, CARRA-East (sub-regions: Svalbard, coast, inland etc…) | Features: Summary statistics, spatial and temporal variability, extremes/ high-impact |
Summary/abstract (paper): The representation of 2-m air temperature and 10-m wind speed in the high-resolution (with a 2.5-km grid spacing) Copernicus Arctic Regional Reanalysis (CARRA) and the coarser resolution (ca. 31-km grid spacing) global European Center for Medium-range Weather Forecasts fifth-generation reanalysis (ERA5) for Svalbard, northern Norway, Sweden and Finland is evaluated against observations. The largest differences between the two reanalyses are found in regions with complex terrain and coastlines, and over the sea ice for temperature in winter. In most aspects, CARRA outperforms ERA5 in its agreement with the observations, but the value added by CARRA varies with region and season. Furthermore, the added value by CARRA is seen for both parameters but is more pronounced for temperature than wind speed. CARRA is in better agreement with observations in terms of general evaluation metrics like bias and standard deviation of the errors, is more similar to the observed spatial and temporal variability and better captures local extremes. A better representation of high-impact weather like polar lows, vessel icing and warm spells during winter is also demonstrated. Finally, it is shown that a substantial part of the difference between reanalyses and observations is due to representativeness issues, that is, sub-grid variability, which cannot be represented in gridded data. This representativeness error is larger in ERA5 than in CARRA, but the fraction of the total error is estimated to be similar in the two analyses for temperature but larger in ERA5 for wind speed. https://polarresearch.net/index.php/polar/article/view/8002/14479 |
Hansche, I., Shahi, S., Abermann, J., & Schöner, W. (2023). The vertical atmospheric structure of the partially glacierised Mittivakkat valley, southeast Greenland. Journal of Glaciology, 1-12. doi:10.1017/jog.2022.120 | ||||
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Type of study: Investigation of atmospheric temperature inversions | Parameters: air temperature | Comparison against: UAV-observations compared with CARRA, ERA5, ERA-interim and radiosondes | Region and time period: Mittivakkat valley (southeast Greenland), field campaign summer 2019 | Features; Inversion characteristics, comparisons by correlation and RMSE |
Summary/abstract(paper): |
Isaksen, K., Nordli, Ø., Ivanov, B. et al. Exceptional warming over the Barents area. Sci Rep 12, 9371 (2022). https://doi.org/10.1038/s41598-022-13568-5 | ||||
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Type of study: Investigation of temperature trends | Parameters: 2m air temperature | Comparison against: ERA5, dependent and in-dependent in-situ/synop | Region and time period: 1991-2020, Svalbard and Barents Sea area | Features; Trends, summary statistics (bias, standard deviation of error, RMSE), sea-ice dependency |
Summary/abstract(paper): |
Moore, G. W. K., & Imrit, A. A. (2022). Impact of resolution on the representation of the mean and extreme winds along Nares Strait. Journal of Geophysical Research: Atmospheres, 127, e2022JD037443. https://doi.org/10.1029/2022JD037443 | ||||
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Type of study: Investigation of wind speed in complex terrain | Parameters: 10 m wind speed | Comparison against: ERA5, ECMWF Operational analysis and in-situ/synop | Region and time period: 2016-2019, Nares strait | Features; General statistics and extremes |
Summary/abstract (paper): |
Lundesgaard, Ø., Sundfjord, A., Lind, S., Nilsen, F., and Renner, A. H. H.: Import of Atlantic Water and sea ice controls the ocean environment in the northern Barents Sea, Ocean Sci., 18, 1389–1418, https://doi.org/10.5194/os-18-1389-2022, 2022 | ||||
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Type of study: Ocean properties | Parameters: 10m wind speed & MSLP | Comparison against: in-situ/synop, ocean currents | Region and time period: 2018-2020, Northern Barents Sea | Features; Relationship between atmosphere forcing and ocean currents |
Summary/abstract (paper): |
Steffensen Schmidt, L., Schuler, T. V., Thomas, E. E., and Westermann, S.: Meltwater runoff and glacier mass balance in the high Arctic: 1991–2022 simulations for Svalbard, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-1409, 2023. | ||||
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Type of study: glacier mass balance, runoff and snow conditions | Parameters: 2m air temperature, 2m relative humidity, 10m wind speed, incoming short- and longwave radiation | Comparison against: Dependent and independent in-situ observations- | Region and time period: 1991-2021, Svalbard | Features; Evaluation of CARRA used as forcing data for relevant parameters. Bias and RMSE are calculated. |
preprint open for discussion Summary/abstract (paper): The Arctic is undergoing increased warming compared to the global mean, which has major implications for fresh-water runoff into the oceans from seasonal snow and glaciers. Here, we present high-resolution (2.5 km) simulations of glacier mass balance, runoff and snow conditions in Svalbard from 1991–2022, one of the fastest warming regions in the Arctic. The simulations are created using the CryoGrid community model forced by both CARRA reanalysis (1991–2021) and AROME-ARCTIC forecasts (2016–2022). Updates to the water percolation and runoff scheme are implemented in the CryoGrid model for the simulations. In-situ observations available for Svalbard are used to carefully evaluate the quality of the simulations and model forcing. The overlap period of 2016–2021, when both CARRA and AROME-ARCTIC data are available, is used to evaluate the consistency between the two forcing datasets. We find a slightly negative climatic mass balance (cmb) over the simulation period of −0.08 m w.e. yr−1, but with no statistically significant trend. The average runoff was found to be 41 Gt yr−1, with an significant increasing trend of 6.3 Gt decade−1. In addition, we find the simulated climatic mass balance and runoff using CARRA and AROME-ARCTIC forcing are similar, and differ by only 0.1 m w.e. in climatic mass balance and by 0.2 m w.e. in glacier runoff when averaged over all of Svalbard. There is, however, a clear difference over Nordenskiöldland, where AROME-ARCTIC simulates significantly higher mass balance and significantly lower runoff. This indicates that AROME-ARCTIC may provide high-quality predictions of the total mass balance of Svalbard, but regional uncertainties should be taken into consideration. The data produced from both the CARRA and AROME-ARCTIC forced CryoGrid simulations are made publicly available, and these high resolution simulation may be re-used in a wide range of applications including studies on glacial runoff, ocean currents, and ecosystems https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1409/ |
A selection of relevant presentations
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Known issues for the Copernicus Arctic Regional reanalysis. Copernicus Knowledge Base (CKB) article. Copernicus Arctic Regional Reanalysis (CARRA): known issues and uncertainty information#Knownissues
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This document has been produced in the context of the Copernicus Climate Change Service (C3S). The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation agreementAgreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view. |
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