A Comparison of Sea Surface Temperature Perturbation Methods for a Convection Permitting Ensemble Prediction System Over the European Arctic
By: Rafael Grote and Andrew Thomas Singleton
References
- Batrak, Y, Kourzeneva, E and Homleid, M. 2018. Implementation of a simple thermodynamic sea ice scheme, SICE version 1.0-38h1, within the ALADIN–HIRLAM numerical weather prediction system version 38h1. Geosci. Model Dev., 11: 3347–3368. DOI: 10.5194/gmd-11-3347-2018
- Bengtsson, L, Andrae, U, Aspelien, T, Batrak, Y, Calvo, J, de Rooy, W, Gleeson, E, Hansen-Sass, B, Homleid, M, Hortal, M, Ivarsson, K-I, Lenderink, G, Niemelä, S, Nielsen, KP, Onvlee, J, Rontu, L, Samuelsson, P, Muñoz, DS, Subias, A, Tijm, S, Toll, V, Yang, X and Køltzow, MØ. 2017. The HARMONIE–AROME Model Configuration in the ALADIN–HIRLAM NWP System. Mon. Weather Rev., 145: 1919–1935. DOI: 10.1175/MWR-D-16-0417.1
- Bouttier, F, Raynaud, L, Nuissier, O and Ménétrier, B. 2016. Sensitivity of the AROME ensemble to initial and surface perturbations during HyMeX: Sensitivity of AROME Ensemble. Q. J. R. Meteorol. Soc., 142: 390–403. DOI: 10.1002/qj.2622
- Brousseau, P, Berre, L, Bouttier, F and Desroziers, G. 2011. Background-error covariances for a convective-scale data-assimilation system: AROME–France 3D-Var. Q. J. R. Meteorol. Soc., 137: 409–422. DOI: 10.1002/qj.750
- Buizza, R and Palmer, TN. 1995. The singular-vector structure of the atmospheric global circulation. J. Atmospheric Sci., 52: 1434–1456. DOI: 10.1175/1520-0469(1995)052<;1434:TSVSOT>2.0.CO;2
- Donlon, CJ, Martin, M, Stark, J, Roberts-Jones, J, Fiedler, E and Wimmer, W. 2012. The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system. Remote Sens. Environ., Advanced Along Track Scanning Radiometer(AATSR) Special Issue, 116: 140–158. DOI: 10.1016/j.rse.2010.10.017
- Ebisuzaki, W and Kalnay, E. 1991. Ensemble experiments with a new lagged average forecasting scheme. WMO Res. Act. Atmospheric Ocean. Model. Rep., 15: 308.
- Eguíluz, VM, Fernández-Gracia, J, Irigoien, X and Duarte, CM. 2016. A quantitative assessment of Arctic shipping in 2010–2014. Sci. Rep., 6: 30682. DOI: 10.1038/srep30682
- Frogner, I-L, Andrae, U, Bojarova, J, Callado, A, Escribà, P, Feddersen, H, Hally, A, Kauhanen, J, Randriamampianina, R, Singleton, A, Smet, G, van der Veen, S and Vignes, O. 2019. HarmonEPS—The HARMONIE Ensemble Prediction System. Weather Forecast, 34: 1909–1937. DOI: 10.1175/WAF-D-19-0030.1
- Giard, D and Bazile, E. 2000. Implementation of a New Assimilation Scheme for Soil and Surface Variables in a Global NWP Model. Mon. Weather Rev., 128: 997–1015. DOI: 10.1175/1520-0493(2000)128<;0997:IOANAS>2.0.CO;2
- Gunnarsson, B and Moe, A. 2021. Ten Years of International Shipping on the Northern Sea Route: Trends and Challenges. Arct. Rev., 12: 4–30. DOI: 10.23865/arctic.v12.2614
- Hagelin, S, Son, J, Swinbank, R, McCabe, A, Roberts, N and Tennant, W. 2017. The Met Office convective-scale ensemble, MOGREPS-UK. Q. J. R. Meteorol. Soc., 143: 2846–2861. DOI: 10.1002/qj.3135
- Hovelsrud, GK, Veland, S, Kaltenborn, B, Olsen, J and Dannevig, H. 2021. Sustainable Tourism in Svalbard: Balancing economic growth, sustainability, and environmental governance. Polar Rec, 57. DOI: 10.1017/S0032247421000668
- Isaksen, L, Bonavita, M, Buizza, R, Fisher, M, Haseler, J, Leutbecher, M and Raynaud, L. 2010. Ensemble of data assimilations at ECMWF.
- Jung, T, Gordon, ND, Bauer, P, Bromwich, DH, Chevallier, M, Day, JJ, Dawson, J, Doblas-Reyes, F, Fairall, C, Goessling, HF, Holland, M, Inoue, J, Iversen, T, Klebe, S, Lemke, P, Losch, M, Makshtas, A, Mills, B, Nurmi, P, Perovich, D, Reid, P, Renfrew, IA, Smith, G, Svensson, G, Tolstykh, M and Yang, Q. 2016. Advancing Polar Prediction Capabilities on Daily to Seasonal Time Scales. Bull. Am. Meteorol. Soc., 97: 1631–1647. DOI: 10.1175/BAMS-D-14-00246.1
- Kalnay, E. 2019. Historical perspective: earlier ensembles and forecasting forecast skill. Q. J. R. Meteorol. Soc., 145: 25–34. DOI: 10.1002/qj.3595
- Keller, JD, Kornblueh, L, Hense, A and Rhodin, A. 2008. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique. Meteorol. Z., 707–718. DOI: 10.1127/0941-2948/2008/0333
- 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. Weather Forecast., 34: 959–983. DOI: 10.1175/WAF-D-19-0003.1
- Larson, LG. 2018. Investigating Statistical vs. Practical Significance of the Kolmogorov-Smirnov Two-Sample Test Using Power Simulations and Resampling Procedures.
- Lavaysse, C, Carrera, M, Bélair, S, Gagnon, N, Frenette, R, Charron, M and Yau, MK. 2013. Impact of Surface Parameter Uncertainties within the Canadian Regional Ensemble Prediction System. Mon. Weather Rev., 141: 1506–1526. DOI: 10.1175/MWR-D-11-00354.1
- Lewis, JM. 2005. Roots of Ensemble Forecasting. Mon. Weather Rev., 133: 1865–1885. DOI: 10.1175/MWR2949.1
- Masson, V, Le Moigne, P, Martin, E, Faroux, S, Alias, A, Alkama, R, Belamari, S, Barbu, A, Boone, A, Bouyssel, F, Brousseau, P, Brun, E, Calvet, J-C, Carrer, D, Decharme, B, Delire, C, Donier, S, Essaouini, K, Gibelin, A and Voldoire, A. 2013. The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of Earth surface variables and fluxes. Geosci. Model Dev., 6: 929–960. DOI: 10.5194/gmd-6-929-2013
- Müller, M, Batrak, Y, Kristiansen, J, Køltzow, MAØ, Noer, G and Korosov, A. 2017a. Characteristics of a Convective-Scale Weather Forecasting System for the European Arctic. Mon. Weather Rev., 145: 4771–4787. DOI: 10.1175/MWR-D-17-0194.1
- Müller, M, Homleid, M, Ivarsson, K-I, Køltzow, MAØ, Lindskog, M, Midtbø, KH, Andrae, U, Aspelien, T, Berggren, L, Bjørge, D, Dahlgren, P, Kristiansen, J, Randriamampianina, R, Ridal, M and Vignes, O. 2017b. AROME-MetCoOp: A Nordic Convective-Scale Operational Weather Prediction Model. Weather Forecast., 32: 609–627. DOI: 10.1175/WAF-D-16-0099.1
- Ollinaho, P, Lock, S-J, Leutbecher, M, Bechtold, P, Beljaars, A, Bozzo, A, Forbes, RM, Haiden, T, Hogan, RJ and Sandu, I. 2017. Towards process-level representation of model uncertainties: stochastically perturbed parametrizations in the ECMWF ensemble: Process-level Representation of Model Uncertainties. Q. J. R. Meteorol. Soc., 143: 408–422. DOI: 10.1002/qj.2931
- Palmer, TN, Buizza, R, Doblas-Reyes, F, Jung, T, Leutbecher, M, Shutts, GJ, Steinheimer, M and Weisheimer, A. 2009. Stochastic parametrization and model uncertainty. ECMWF Tech. Memo., 598: 1–42.
- Pulkkinen, S, Nerini, D, Pérez Hortal, AA, Velasco-Forero, C, Seed, A, Germann, U and Foresti, L. 2019. Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0). Geosci. Model Dev., 12: 4185–4219. DOI: 10.5194/gmd-12-4185-2019
- Seed, AW, Pierce, CE and Norman, K. 2013. Formulation and evaluation of a scale decomposition-based stochastic precipitation nowcast scheme. Water Resour. Res., 49: 6624–6641. DOI: 10.1002/wrcr.20536
- Tennant, W and Beare, S. 2014. New schemes to perturb sea-surface temperature and soil moisture content in MOGREPS. Q. J. R. Meteorol. Soc., 140: 1150–1160. DOI: 10.1002/qj.2202
- Toth, Z and Kalnay, E. 1993. Ensemble forecasting at NMC: The generation of perturbations. Bull. Am. Meteorol. Soc., 74: 2317–2330. DOI: 10.1175/1520-0477(1993)074<;2317:EFANTG>2.0.CO;2
- Wang, Y, Bellus, M, Wittmann, C, Steinheimer, M, Weidle, F, Kann, A, Ivatek-Šahdan, S, Tian, W, Ma, X, Tascu, S and Bazile, E. 2011. The Central European limited-area ensemble forecasting system: ALADIN-LAEF. Q. J. R. Meteorol. Soc., 137: 483–502. DOI: 10.1002/qj.751
DOI: https://doi.org/10.16993/tellusa.27 | Journal eISSN: 3035-9554
Language: English
Page range: 271 - 289
Submitted on: Dec 20, 2021
Accepted on: Jul 9, 2023
Published on: Aug 14, 2023
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
© 2023 Rafael Grote, Andrew Thomas Singleton, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.