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Table of Contents

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
Type of study: System description

Parameters2m 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.

Batrak, Y., Cheng, B., and Kallio-Myers, V.: Sea ice cover in the Copernicus Arctic Regional Reanalysis, The Cryosphere Discuss. [preprint],, in review, 2023.
Type of study: Evaluation/verification

Parameters:  Sea ice properties

Comparison against: satellite products, buoysERA5

Region and time period: mainly 2000-2020, CARRA-East and CARRA-West

Features: Summary statistics, climatology

Summary/abstract (paper):

The Copernicus Arctic Regional Reanalysis (CARRA) is a novel regional high-resolution atmospheric reanalysis product that covers a considerable part of the European Arctic including substantial amounts of ice-covered areas. Sea ice in CARRA is modelled by means of a one-dimensional thermodynamic sea ice parameterisation scheme, which also explicitly resolves the evolution of the snow layer over sea ice. In the present study we assess the representation of sea ice cover in the CARRA product and validate it against a wide set of satellite products and observations from ice mass balance buoys. We show that sea ice cover in CARRA adequately represents general interannual trends towards thinner and warmer ice in the Arctic. Compared to ERA5, sea ice in CARRA shows a reduced warm bias in the ice surface temperature. The strongest improvement was observed for winter months over the Central Arctic, and the Greenland and Barents seas where a 4.91 °C median ice surface temperature error of ERA5 is reduced to 1.88 °C in CARRA on average. Over the Baffin Bay, intercomparisons suggest the presence of a cold winter-time ice surface temperature bias in CARRA. No improvement over ERA5 was found in the ice surface albedo with spring-time errors in CARRA being up to 8 % higher on average than those in ERA5 when computed against the CLARA-A2 satellite retrieval product. Summer-time ice surface albedos are comparable in CARRA and ERA5. Sea ice thickness and snow depth in CARRA adequately resolve the annual cycle of sea ice cover in the Arctic and bring added value compared to ERA5. However, limitations of CARRA indicate potential benefits of utilising more advanced approaches for representing sea ice cover in next generation reanalyses.

Box, J. E., Nielsen, K. P., Yang, X., Niwano, M., Wehrlé, A., van As, D., Fettweis, X., Køltzow, Morten A. Ø., Palmason, B., Fausto, R. S., van den Broeke, M. R., Huai, B., Ahlstrøm, A. P., Langley, K., Dachauer, A., & Noël, B. (2023). Greenland ice sheet rainfall climatology, extremes and atmospheric river rapids. Meteorological Applications, 30(4), e2134.
Type of study: Evaluation and precipitation analysis

Parameters:  Rainfall

Comparison against: in-situERA5

Region and time period: CARRA-West

Features: Summary statistics, climatology, trends, case studies

Summary/abstract (paper):

Greenland rainfall has come into focus as a climate change indicator and from a variety of emerging cryospheric impacts. This study first evaluates rainfall in five state-of-the-art numerical prediction systems (NPSs) (CARRA, ERA5, NHM-SMAP, RACMO, MAR) using in situ rainfall data from two regions spanning from land onto the ice sheet. The new EU Copernicus Climate Change Service (C3S) Arctic Regional ReAnalysis (CARRA), with a relatively fine (2.5 km) horizontal grid spacing and extensive within-model-domain observational initialization, has the lowest average bias and highest explained variance relative to the field data. ERA5 inland wet bias versus CARRA is consistent with the field data and other research and is presumably due to more ERA5 topographic smoothing. A CARRA climatology 1991–2021 has rainfall increasing by more than one-third for the ice sheet and its peripheral ice masses. CARRA and in situ data illuminate extreme (above 300 mm per day) local rainfall episodes. A detailed examination CARRA data reveals the interplay of mass conservation that splits flow around southern Greenland and condensational buoyancy generation that maintains along-flow updraft ‘rapids’ 2 km above sea level, which produce rain bands within an atmospheric river interacting with Greenland. CARRA resolves gravity wave oscillations that initiate as a result of buoyancy offshore, which then amplify from terrain-forced uplift. In a detailed case study, CARRA resolves orographic intensification of rainfall by up to a factor of four, which is consistent with the field data.

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

Type of study:

Investigation of atmospheric temperature inversions


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


Inversion characteristics, comparisons by correlation and RMSE 


Air temperature inversions, a situation in which atmospheric temperature increases with height, are key components of the Arctic planetary boundary layer. The present study investigates the spatial and temporal variations of temperature inversions over different surface types (rock, gravel, snow, ice) along the Mittivakkat valley (southeast Greenland). For this purpose, 113 vertical profiles with high spatio-temporal resolution of air temperature and relative humidity were collected with unoccupied aerial vehicles (UAVs) during a 13-day field campaign in summer 2019. Air temperature inversions were present in 83% of the profiles, of which 24% were surface-based inversions and 76% were elevated inversions. The proglacial area covered with bare rock and gravel induces surface heating and convection during the day and, through interaction with local circulation patterns, leads to the frequent formation of elevated inversions. In contrast, the glacier surface itself acts as a persistent cooling surface and leads to the formation of surface-based inversions. A low-level fog layer that forms under the inversion layer may be causing non-linear vertical ablation gradients on Mittivakkat Gletsjer. Furthermore, we demonstrate that atmospheric measurements using UAVs can better capture small-scale processes than other products like radiosonde or modeled reanalysis data.

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.
Type of study: Evaluation/verification

Parameters2m 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.

Isaksen, K., Nordli, Ø., Ivanov, B. et al. Exceptional warming over the Barents area. Sci Rep 12, 9371 (2022).

Type of study:

Investigation of temperature trends


2m air temperature

Comparison against:

ERA5, dependent and in-dependent in-situ/synop 

Region and time period:

1991-2020, Svalbard and Barents Sea area


Trends, summary statistics (bias, standard deviation of error, RMSE), sea-ice dependency


In recent decades, surface air temperature (SAT) data from Global reanalyses points to maximum warming over the northern Barents area. However, a scarcity of observations hampers the confidence of reanalyses in this Arctic hotspot region. Here, we study the warming over the past 20–40 years based on new available SAT observations and a quality controlled comprehensive SAT dataset from the northern archipelagos in the Barents Sea. We identify a statistically significant record-high annual warming of up to 2.7 °C per decade, with a maximum in autumn of up to 4.0 °C per decade. Our results are compared with the most recent global and Arctic regional reanalysis data sets, as well as remote sensing data records of sea ice concentration (SIC), sea surface temperature (SST) and high-resolution ice charts. The warming pattern is primarily consistent with reductions in sea ice cover and confirms the general spatial and temporal patterns represented by reanalyses. However, our findings suggest even a stronger rate of warming and SIC-SAT relation than was known in this region until now.

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.

Type of study:

Investigation of wind speed in complex terrain


10 m wind speed

Comparison against:

ERA5, ECMWF Operational analysis and in-situ/synop 

Region and time period:

2016-2019, Nares strait


General statistics and extremes

Summary/abstract (paper):

Nares Strait is the long and narrow strait bounded by steep topography that connects the Arctic Ocean's Lincoln Sea to the North Atlantic's Baffin Bay. The winds that blow along the strait play an important role in modulating ice and water exports from the Arctic Ocean as well as in helping to establish the Arctic's largest and most productive polynya that forms at its southern terminus. However, its remote location has limited our knowledge of the winds along the strait. Here we use weather station data from the region as well as two reanalyses and an operational analysis with nominal horizontal resolutions that vary from ∼30 to ∼2.5 km to characterize the wind field in the vicinity of the strait. The strait has a width that varies from ∼40 to ∼100 km and as such the wind field is typically ageostrophic and controlled by the pressure gradient in the along-strait direction. We show that model resolution plays a role in the representation of both the mean and extreme winds along the strait through the ability to represent this ageostrophic flow. Higher windspeeds occur in the vicinity of Smith Sound and are associated with a left-hand corner jet. Kane Basin, the widest section of the strait, is characterized by a gradient in windspeed with higher speeds in the center of the basin and lower winds in the eastern basin that is the result of sheltering by the steep topography of the upstream Washington Land peninsula.

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,, 2022

Type of study:

Ocean properties


10m wind speed & MSLP

Comparison against:

in-situ/synop, ocean currents

Region and time period:

2018-2020, Northern Barents Sea


Relationship between atmosphere forcing and ocean currents

Summary/abstract (paper):
The northern Barents Sea is a cold, seasonally ice-covered Arctic shelf sea region that has experienced major warming and sea ice loss in recent decades. Here, a 2-year observational record from two ocean moorings provides new knowledge about the seasonal hydrographic variability in the region and about the ocean exchange across its northern margin. The combined records of temperature, salinity, and currents show the advection of warmer and saltier waters of Atlantic origin into the Barents Sea from the north. The source of these warmer water masses is the Atlantic Water boundary current that flows along the continental slope north of Svalbard. Time-varying southward inflow through cross-shelf troughs was the main driver of the seasonal cycle in ocean temperature at the moorings. Inflows were intensified in autumn and early winter, in some cases occurring below the sea ice cover and halocline water. On shorter timescales, subtidal current variability was correlated with the large-scale meridional atmospheric pressure gradient, suggesting wind-driven modulation of the inflow. The mooring records also show that import of sea ice into the Barents Sea has a lasting impact on the upper ocean, where salinity and stratification are strongly affected by the amount of sea ice that has melted in the area. A fresh layer separated the ocean surface from the warm mid-depth waters following large sea ice imports in 2019, whereas diluted Atlantic Water was found close to the surface during episodes in autumn 2018 following a long ice-free period. Thus, the advective imports of ocean water and sea ice from surrounding areas are both key drivers of ocean variability in the region.

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],, 2023.

Type of study:

glacier mass balance, runoff and snow conditions


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


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

A selection of relevant presentations

Box, J., 2022: C3S General Assembly, September 2022: What can the Copernicus Arctic Regional Reanalysis (CARRA) add to the existing reanalysis information in Greenland? (Presentation) Recorded presentations available at:

Box, J., 2022: Copernicus Polar Workshop, September 2022, Extreme Greenland ice sheet climate events in high-detail via the Copernicus Arctic Regional Reanalysis (CARRA). 

Køltzow, M. et al., 2022, C3S General Assembly, September 2022: The strengths and weaknesses of the new Arctic (CARRA) and European (CERRA) regional reanalyses (Presentation) Recorded presentations available at:

Multiple authors, 2020: User workshop on Copernicus regional reanalysis for Europe and the European Arctic, September 2020. Multiple (recorded) presentations.

A selection of relevant conference abstracts and not peer-reviewed literature

Dahlgren, P. and T. Valkonen, 2021: Use of wind retrievals in regional reanalysis, 15th International Winds Workshop, online, abstract available in abstract brochure here:

Kallio-Myers, V., Batrak, Y., and Cheng, B.: Comparison of Arctic sea-ice albedo between CARRA and ERA5 reanalyses and satellite based CLARA-A2, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1510,, 2023.

Landgren, O., Lutz, J., Dobler, A., and Isaksen, K.: Multi-decadal convection-permitting climate simulation over Svalbard and its benefit for assessing the future of cultural heritage sites, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-556,, 2022

Maniktala, D., 2022, Analysing seasonal snow cover trends and patterns on Svalbard, student thesis, Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.

Nielsen, K. P., Schyberg, H., Yang, X., Støylen, E., Dahlgren, P., Amstrup, B., Peralta, C., Køltzow, M., and Bojarova, J.: 24 years of C3S Arctic regional reanalysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15178,, 2021.

Schyberg, H. The Copernicus Arctic Regional Reanalysis, WCRP-WWRP Symposium on Data Assimilation and Reanalysis / 2021 ECMWF Annual Seminar on Observations, 13-18 September 202,

Schyberg, H., Yang, X., Støylen, E., Dahlgren, P., S. Madsen, M., Køltzow, M., and Olesen, M.: Evolution of the Copernicus Arctic Regional Reanalysis, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-535,, 2022.

Slättberg, N., Maturilli, M., and Dahlke, S.: Fram Strait Marine Cold Air Outbreaks and associated surface heat fluxes in the ERA5 & CARRA reanalyses, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14048,, 2023.

Torres-Alavez, A., Landgren, O., Boberg, F., Christensen, O. B., Mottram, R., Olesen, M., Van Ulft, B., Verro, K., and Batrak, Y.: Assessing Performance of a new High Resolution polar regional climate model with remote sensing and in-situ observations: HCLIM in the Arctic and Antarctica, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14090,, 2023.

Zhaohui, Cheng:  Polar mesoscale cyclones in ERA5 and CARRA, 2023, Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.

Relevant CARRA documents

Nielsen, K. P. et al.: Copernicus Arctic Regional Reanalysis (CARRA): Data User Guide. Available at Copernicus Arctic Regional Reanalysis (CARRA): Data User Guide

Yang, X., et al., 2020: C3S Arctic regional reanalysis - Full System documentation. Available at

Yang, X., et al., 2020: Complete test and verification report on fully configured reanalysis and monitoring system. Available at

Bojarova J., 2020: Uncertainty estimation method. Available at

Copernicus Arctic Regional Reanalysis: Added value to the ERA5 global reanalysis. Copernicus Knowledge Base (CKB) article. Copernicus Arctic Regional Reanalysis (CARRA): Added value to the ERA5 global reanalysis

Uncertainty information for the Copernicus Arctic Regional reanalysis. Copernicus Knowledge Base (CKB) article. Copernicus Arctic Regional Reanalysis (CARRA): known issues and uncertainty information#Uncertaintyinformation

Known issues for the Copernicus Arctic Regional reanalysis. Copernicus Knowledge Base (CKB) article. Copernicus Arctic Regional Reanalysis (CARRA): known issues and uncertainty information#Knownissues

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 agreement signed on 11/11/2014). 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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