References
- Atlaskin, E. and Vihma, T. 2012. Evaluation of NWP results for wintertime nocturnal boundary‐layer temperatures over Europe and Finland. Q. J. R. Meteorol. Soc. 138, 1440–1451. doi:https://doi.org/10.1002/qj.1885
- Bauer, P., Magnusson, L., Thépaut, J.-N. and Hamill, T. M. 2016. Aspects of ECMWF model performance in polar areas. Q. J. R. Meteorol. Soc. 142, 583–596. doi:https://doi.org/10.1002/qj.2449
- Bauer, P., Thorpe, A. and Brunet, G. 2015. The quiet revolution of numerical weather prediction. Nature 525, 47–55. doi:https://doi.org/10.1038/nature14956
- Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J. and co-authors. 2017. The HARMONIE–AROME model configuration in the ALADIN–HIRLAM NWP system. Mon. Weather Rev. 145, 1919–1935. doi:https://doi.org/10.1175/MWR-D-16-0417.1
- Bouallégue, B., Z., S. E., Theis, C. and Gebhardt, 2013. Enhancing COSMO-DE ensemble forecasts by inexpensive techniques. Meteorol. Z. 22, 49–59. doi:https://doi.org/10.1127/0941-2948/2013/0374
- Di Luca, A., de Elía, R. and Laprise, R. 2012. Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations. Clim. Dyn. 38, 1229–1247. doi:https://doi.org/10.1007/s00382-011-1068-3
- Ebisuzaki, W. and Kalnay, E. 1991. Ensemble experiments with a new lagged average forecasting scheme. WMO Research Activities in Atmospheric and Oceanic Modelling. Report 15, 6.31–6.32. Geneva, Switzerland: WMO.
- Esau, I. and Repina, I. 2012. Wind climate in Kongsfjorden, Svalbard, and attribution of leading wind driving mechanisms through turbulence-resolving simulations. Adv. Meteorol. 2012, 1–16.
- Feser, F., Rockel, B., von Storch, H., Winterfeldt, J. and Zahn, M. 2011. Regional climate models add value to global model data: A review and selected examples. Bull. Amer. Meteor. Soc. 92, 1181–1192. doi:https://doi.org/10.1175/2011BAMS3061.1
- Frogner, I., Andrae, U., Bojarova, J., Callado, A. Escribà, P. and co-authors. 2019a. HarmonEPS - the HARMONIE Ensemble Prediction System. Wea. Forecast. 34(6), 1909–1937.
- Frogner, I.‐L., Singleton, A. T., Køltzow, M. Ø. and Andrae, U. 2019b. Convection‐permitting ensembles: Challenges related to their design and use. Q. J. R. Meteorol. Soc. 145, 90–106. doi:https://doi.org/10.1002/qj.3525
- Gascard, J.-C., Riemann-Campe, K., Gerdes, R., Schyberg, H., Randriamampianina, R. and co-authors. 2017. Future sea ice conditions and weather forecasts in the Arctic: Implications for Arctic shipping. Ambio 46, 355–367. doi:https://doi.org/10.1007/s13280-017-0951-5
- Giard, D. and Bazile, E. 2000. Implementation of a new assimilation scheme for soil and surface variables in a global NWP model. Mon. Wea. Rev. 128, 997–1015. doi:https://doi.org/10.1175/1520-0493(2000)128<0997:IOANAS>2.0.CO;2
- Giorgi, F. 2019. Thirty years of regional climate modeling: Where are we and where are we going next? J. Geophys. Res. Atmos. 124, 5696–5723.
- Hagelin, S., Son, J., Swinbank, R., McCabe, A., Roberts, N. M. and co-authors. 2017. The Met Office convective‐scale ensemble, MOGREPS‐UK. Q. J. R. Meteorol. Soc. 143, 2846–2861. doi:https://doi.org/10.1002/qj.3135
- Hou, D., Kalnay, E. and Droegemeier, K. K. 2001. Objective verification of the SAMEX'98 ensemble forecasts. Mon. Wea. Rev. 129, 73–91. doi:https://doi.org/10.1175/1520-0493(2001)129<0073:OVOTSE>2.0.CO;2
- Jung, T. and Leutbecher, M. 2007. Performance of the ECMWF forecasting system in the Arctic during winter. Q. J. R. Meteorol. Soc. 133, 1327–1340. doi:https://doi.org/10.1002/qj.99
- Jung, T. and Leutbecher, M. 2008. Scale-dependent verification of ensemble forecasts. Q. J. R. Meteorol. Soc. 134, 973–984. doi:https://doi.org/10.1002/qj.255
- Jung, T., Gordon, N. D., Bauer, P., Bromwich, D. H., Chevallier, M. and co-authors. 2016. Advancing polar prediction capabilities on daily to seasonal time scales. Bull. Amer. Meteor. Soc. 97, 1631–1647. doi:https://doi.org/10.1175/BAMS-D-14-00246.1
- Kielland, G. 2005. KVALOBS - The quality assurance system of Norwegian Meteorological Institute observations. Instruments and Observing Methods. Rep. 82, WMO/TD-1265 3. https://library.wmo.int/pmb_ged/wmo-td_1265.pdf
- Kim, D.-H., Kim, H. M. and Hong, J. 2019. Evaluation of wind forecasts over Svalbard using the high-resolution Polar WRF with 3DVAR. Arct. Antarct. Alp. Res. 51, 471–489. doi:https://doi.org/10.1080/15230430.2019.1676939
- Kochendorfer, J., Rasmussen, R., Wolff, M., Baker, B., Hall, M. E. and co-authors. 2017. The quantification and correction of wind-induced precipitation measurement errors. Hydrol. Earth Syst. Sci. 21, 1973–1989. doi:https://doi.org/10.5194/hess-21-1973-2017
- Kolstad, E. W., Bracegirdle, T. J. and Seierstad, I. A. 2009. Marine cold-air outbreaks in the North Atlantic: Temporal distribution and associations with large-scale atmospheric circulation. Clim. Dyn. 33, 187–197. doi:https://doi.org/10.1007/s00382-008-0431-5
- Køltzow, M., Casati, B., Bazile, E., Haiden, T. and Valkonen, T. 2019. An NWP model intercomparison of surface weather parameters in the European Arctic during the year of polar prediction special observing period Northern Hemisphere 1. Wea. Forecast. 34, 959–983. doi:https://doi.org/10.1175/WAF-D-19-0003.1
- Køltzow, M., Casati, B., Haiden, T. and Valkonen, T. 2020. Verification of solid precipitation forecasts from Numerical Weather Prediction models in Norway. Wea. Forecast. 35(6), 2279–2292.
- Kristiansen, J., Sørland, S. L., Iversen, T., Bjørge, D. and Køltzow, M. Ø. 2011. High‐resolution ensemble prediction of a polar low development. Tellus A 63, 585–604. doi:https://doi.org/10.1111/j.1600-0870.2010.00498.x
- Müller, M., Batrak, Y., Kristiansen, J., Køltzow, M. A., Noer, G. and co-authors. 2017. Characteristics of a convective-scale weather forecasting system for the European Arctic. Mon. Wea. Rev. 145, 4771–4787. doi:https://doi.org/10.1175/MWR-D-17-0194.1
- Nordeng, T. E., Brunet, G. and Caughey, J. 2007. Improvements of weather forecasts in polar regions. WMO Bull. 56, 250–257.
- Osinski, R. and Bouttier, F. 2018. Short-range probabilistic forecasting of convective risks for aviation based on a lagged-average-forecast ensemble approach. Met. Apps. 25, 105–118. doi:https://doi.org/10.1002/met.1674
- Owens, R. G. and Hewson, T. D. 2018. ECMWF Forecast User Guide. Reading: ECMWF.
- Randriamampianina, R., Bormann, N., Køltzow, M., Lawrence, H., Sandu, I. and co-authors. 2021. Relative impact of observations on a regional Arctic numerical weather prediction system. Q. J. R. Meteorol. Soc. 147: 2212–2232. doi:https://doi.org/10.1002/qj.4018
- Randriamampianina, R., Schyberg, H. and Mile, M. 2019. Observing system experiments with an Arctic mesoscale numerical weather prediction model. Remote Sens. 11, 981. doi:https://doi.org/10.3390/rs11080981
- Raynaud, L. and Bouttier, F. 2017. The impact of horizontal resolution and ensemble size for convective‐scale probabilistic forecasts. Q. J. R. Meteorol. Soc. 143, 3037–3047. doi:https://doi.org/10.1002/qj.3159
- Rojo, M., Noer, G. Claud, C. 2019. Polar low tracks in the Norwegian sea and the Barents Sea from 1999 until 2019. PANGAEA. doi:https://doi.org/10.1594/PANGAEA.903058
- Rummukainen, M. 2016. Added value in regional climate modeling. WIREs Clim. Change 7, 145–159. doi:https://doi.org/10.1002/wcc.378
- Scheufele, K., Kober, K., Craig, G. C. and Keil, C. 2014. Combining probabilistic precipitation forecasts from a nowcasting technique with a time-lagged ensemble. Met. Apps. 21, 230–240. doi:https://doi.org/10.1002/met.1381
- Singleton, A. and Grote, R. 2020. Verification of EPS forecasts using AROME-Arctic (Alertness project deliverable). Met Norway report 02-2020. Online at: https://www.met.no/publikasjoner/met-report/met-report-2020
- Valkonen, T., Stoll, P., Batrak, Y., Køltzow, M., Schneider, T. M. and co-authors. 2020. Evaluation of a sub-kilometre NWP system in an Arctic fjord-valley system in winter. Tellus A: Dynamic Meteorology and Oceanography 72, 1–21. doi:https://doi.org/10.1080/16000870.2020.1838181
- Wang, X., Steinle, P., Seed, A. and Xiao, Y. 2016. The sensitivity of heavy precipitation to horizontal resolution, domain size, and rain rate assimilation: Case studies with a convection-permitting model. Adv. Meteorol. 2016, 7943845.
- WMO. 2017. Navigating weather, water, ice and climate information for safe polar mobilities. WWRP/PPP 5, 74p. Online at: https://epic.awi.de/id/eprint/46211/1/012_WWRP_PPP_No_5_2017_11_OCT.pdf
- Woollings, T., Franzke, C., Hodson, D. L. R., Dong, B., Barnes, E. A. and co-authors. 2015. Contrasting interannual and multidecadal NAO variability. Clim. Dyn. 45, 539–556. doi:https://doi.org/10.1007/s00382-014-2237-y
- Yang, X., B. Palmason, K. Sattler, S. Thorsteinsson, B. Amstrup and coauthors, 2018. IGB, the upgrade to the joint operational HARMONIE by DMI and IMO in 2018. ALADIN-HIRLAM Newsletter, No 11, ALADIN Consortium, Brussels, Belgium, 93–96. Online at: http://www.umr-cnrm.fr/aladin/IMG/pdf/nl11.pdf