[en] The ability of state‐of‐the‐art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic‐CORDEX initiative. Some models employ large‐scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA‐Interim, National Centers for Environmental Prediction‐Climate Forecast System Reanalysis, National Aeronautics and Space Administration‐Modern‐Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency‐Japanese 55‐year reanalysis) in winter and summer for 1981–2010 period. In addition, we compare cyclone statistics between ERA‐Interim and the Arctic System Reanalysis reanalyses for 2000–2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large‐scale spectral nudging show a better agreement with ERA‐Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Akperov, M.
Rinke, A.
Mokhov, I.
Matthes, H.
Semenov, V.
Adakudlu, M.
Cassano, J.
Christensen, J.
Dembitskaya, M.
Dethloff, K.
Fettweis, Xavier ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie
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Bibliography
Akperov, M., Mokhov, I., Rinke, A., Dethloff, K., & Matthes, H. (2015). Cyclones and their possible changes in the Arctic by the end of the twenty first century from regional climate model simulations. Theoretical and Applied Climatology, 122(1-2), 85–96. https://doi.org/10.1007/s00704-014-1272-2
Akperov, M. G., Bardin, M. Y., Volodin, E. M., Golitsyn, G. S., & Mokhov, I. I. (2007). Probability distributions for cyclones and anticyclones from the NCEP/NCAR reanalysis data and the INM RAS climate model. Izvestiya Atmospheric and Oceanic Physics, 43(6), 705–712. https://doi.org/10.1134/S0001433807060047
Akperov, M. G., & Mokhov, I. I. (2010). A comparative analysis of the method of extratropical cyclone identification. Atmospheric and Oceanic Physics, 46(5), 574–590. https://doi.org/10.1134/S0001433810050038
Akperov, M. G., & Mokhov, I. I. (2013). Estimates of the sensitivity of cyclonic activity in the troposphere of extratropical latitudes to changes in the temperature regime. Izvestiya Atmospheric and Oceanic Physics, 49(2), 113–120. https://doi.org/10.1134/S0001433813020035
Bardin, M. Y., & Polonsky, A. B. (2005). North Atlantic oscillation and synoptic variability in the European-Atlantic region in winter. Izvestiya Atmospheric and Oceanic Physics, 41(3), 127–136.
Berg, P., Döscher, R., & Koenigk, T. (2013). Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic. Geoscientific Model Development, 6(3), 849–859. https://doi.org/10.5194/gmd-6-849-2013
Brayshaw, D. J., Hoskins, B. J., & Blackburn, M. (2009). The basic ingredients of the North Atlantic storm track. Part I: Land–sea contrast and orography. Journal of the Atmospheric Sciences, 66(9), 2539–2558. https://doi.org/10.1175/2009JAS3078.1
Bromwich, D. H., Wilson, A. B., Bai, L., Liu, Z., Barlage, M., Shih, C.-F., et al. (2017). The Arctic System Reanalysis Version 2. Bulletin of the American Meteorological Society. https://doi.org/10.1175/BAMS-D-16-0215.1
Brümmer, B., Thiemann, S., & Kirchgáßner, A. (2000). A cyclone statistics for the Arctic based on European Centrere-analysis data. Meteorology and Atmospheric Physics, 75(3-4), 233–250. https://doi.org/10.1007/s007030070006
Chernokulsky, A. V., Esau, I., Bulygina, O. N., Davy, R., Mokhov, I. I., Outten, S., & Semenov, V. A. (2017). Climatology and interannual variability of cloudiness in the Atlantic Arctic from surface observations since the late 19th century. Journal of Climate, 30(6), 2103–2120. https://doi.org/10.1175/JCLI-D-16-0329.1
Christensen, J. H., Krishna Kumar, K., Aldrian, E., An, S.-I., Cavalcanti, I. F. A., de Castro, M., et al. (2013). Climate phenomena and their relevance for future regional climate change. In T. F. Stocker, et al. (Eds.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1217–1308). Cambridge, United Kingdom and New York: Cambridge University Press. https://doi.org/10.1017/CBO9781107415324.028
Christensen, O. B., Drews, M., Christensen, J. H., Dethloff, K., Ketelsen, K., Hebestadt, I., & Rinke, A. (2007). DMI technical report, 06–17, The HIRHAM Regional Climate Model Version 5 (β).
Côté, H., Grise, K. M., Son, S. W., de Elía, R., & Frigon, A. (2015). Challenges of tracking extratropical cyclones in regional climate models. Climate Dynamics, 44(11-12), 3101–3109. https://doi.org/10.1007/s00382-014-2327-x
Crawford, A. D., & Serreze, M. C. (2016). Does the summer arctic frontal zone influence arctic ocean cyclone activity? Journal of Climate, 29(13), 4977–4993. https://doi.org/10.1175/JCLI-D-15-0755.1
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., et al. (2011). The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553–597. https://doi.org/10.1002/qj.828
Ebita, A., Kobayashi, S., Ota, Y., Moriya, M., Kumabe, R., Onogi, K., et al. (2011). The Japanese 55-year Reanalysis “JRA-55”: An interim report. SOLA, 7, 149–152. https://doi.org/10.2151/sola.2011-038
European Organisation for the Exploitation of Meteorological Satellites (2015). Global sea ice concentration reprocessing dataset 1978-2015 (v1.2, 2015). Norwegian and Danish Meteorological Institutes. Retrieved from http://osisaf.met.no
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., et al. (2017). Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model. The Cryosphere, 11, 1015–1033. https://doi.org/10.5194/tc-11-1015-2017
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., et al. (2017). The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Journal of Climate, 30(14), 5419–5454. https://doi.org/10.1175/JCLI-D-16-0758.1
Golitsyn, G. S., Mokhov, I. I., Akperov, M. G., & Bardin, M. Y. (2007). Distribution functions of probabilities of cyclones and anticyclones from 1952 to 2000: An instrument for the determination of global climate variations. Doklady Earth Sciences, 413(1), 324–326. https://doi.org/10.1134/S1028334X07020432
Gutjahr, O., Heinemann, G., Preußer, A., Willmes, S., & Drüe, C. (2016). Quantification of ice production in Laptev Sea polynyas and its sensitivity to thin-ice parameterizations in a regional climate model. The Cryosphere, 10, 2999–3019. https://doi.org/10.5194/tc-2999-2016
Heinemann, G., & Claud, C. (1997). Report of a workshop on “Theoretical and observational studies of POLAR lows” of the EUROPEAN GEOPHYSICAL SOCIETY POLAR LOWS WORKING GROUP. Bulletin of the American Meteorological Society, 78, 2643–2658.
Inoue, J., Curry, J. A., & Maslanik, J. A. (2008). Application of aerosondes to melt-pond observations over Arctic Sea ice. Journal of Atmospheric and Oceanic Technology, 25(2), 327–334. https://doi.org/10.1175/2007JTECHA955.1
Inoue, J., Hori, M. E., & Takaya, K. (2012). The role of Barents Sea ice in the wintertime cyclone track and emergence of a warm-Arctic cold-Siberian anomaly. Journal of Climate, 25(7), 2561–2568. https://doi.org/10.1175/JCLI-D-11-00449.1
Jaiser, R., Dethloff, K., Handorf, D., Rinke, A., & Cohen, J. (2012). Impact of sea ice cover changes on the northern hemisphere atmospheric winter circulation. Tellus Series A: Dynamic Meteorology and Oceanography, 64(1), 1–11. https://doi.org/10.3402/tellusa.v64i0.11595
Klaus, D., Dethloff, K., Dorn, W., Rinke, A., & Wu, D. L. (2016). New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data. Geophysical Research Letters, 43, 5450–5459. https://doi.org/10.1002/2015GL067530
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., et al. (2015). The JRA-55 Reanalysis: General specifications and basic characteristics. Journal of the Meteorological Society of Japan, 93(1), 5–48. https://doi.org/10.2151/jmsj.2015-001
Koenigk, T., Berg, P., & Döscher, R. (2015). Arctic climate change in an ensemble of regional CORDEX simulations. Polar Research, 34(1), 24603. https://doi.org/10.3402/polar.v34.24603
Kolstad, E. W., & Bracegirdle, T. J. (2016). Sensitivity of an apparently hurricane-like polar low to sea surface temperature. Quarterly Journal of the Royal Meteorological Society, 143(703), 966–973. https://doi.org/10.1002/qj.2980
Koyama, T., Stroeve, J., Cassano, J., & Crawford, A. (2017). Sea ice loss and Arctic cyclone activity from 1979 to 2014. Journal of Climate. https://doi.org/10.1175/JCLI-D-16-0542.1
Kriegsmann, A., & Brümmer, B. (2014). Cyclone impact on sea ice in the central Arctic Ocean: A statistical study. The Cryosphere, 8(1), 303–317. https://doi.org/10.5194/tc-8-303-2014
Kristjansson, J. E., & McInnes, H. (1999). The impact of Greenland on cyclone evolution in the North Atlantic. Quarterly Journal of the Royal Meteorological Society, 125(560), 2819–2834. https://doi.org/10.1002/qj.49712556003
Laffineur, T., Claud, C., Chaboureau, J.-P., & Noer, G. (2014). Polar lows over the Nordic Seas: Improved representation in ERA-Interim compared to ERA-40 and the impact on downscaled simulations. Monthly Weather Review, 142(6), 2271–2289. https://doi.org/10.1175/MWR-D-13-00171.1
Lang, A., Yang, S., & Kaas, E. (2017). Sea ice thickness and recent Arctic warming. Geophysical Research Letters, 44, 409–418. https://doi.org/10.1002/2016GL071274
Lucas-Picher, P., Boberg, F., Christensen, J. H., & Berg, P. (2013). Dynamical downscaling with reinitializations: A method to generate fine-scale climate data sets suitable for impact studies. Journal of Hydrometeorology, 14(4), 1159–1174. https://doi.org/10.1175/JHM-D-12-063.1
Lucas-Picher, P., Wulff-Nielsen, M., Christensen, J. H., Aðalgeirsdóttir, G., Mottram, R., & Simonsen, S. B. (2012). Very high resolution regional climate model simulations over Greenland: Identifying added value. Journal of Geophysical Research, 117, D02108. https://doi.org/10.1029/2011JD016267
Martynov, A., Laprise, R., Sushama, L., Winger, K., Šeparović, L., & Dugas, B. (2013). Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: Model performance evaluation. Climate Dynamics, 41(11-12), 2973–3005. https://doi.org/10.1007/s00382-013-1778-9
McCabe, G. J., Clark, M. P., & Serreze, M. C. (2001). Trends in Northern Hemisphere surface cyclone frequency and intensity. Journal of Climate, 14(12), 2763–2768. https://doi.org/10.1175/1520-0442(2001)014%3C2763:TINHSC%3E2.0.CO;2
Mizuta, R. (2012). Intensification of extratropical cyclones associated with the polar jet change in the CMIP5 global warming projections. Geophysical Research Letters, 39, L19707. https://doi.org/10.1029/2012GL053032
Mokhov, I. I., Akperov, M. G., Lagun, V. E., & Lutsenko, E. I. (2007). Intense Arctic mesocyclones. Izvestiya Atmospheric and Oceanic Physics, 43(3), 259–265. https://doi.org/10.1134/S0001433807030012
Mokhov, I. I., Chernokul'skii, A. V., Akperov, M. G., Dufresne, J.-L., & Le Treut, H. (2009). Variations in the characteristics of cyclonic activity and cloudiness in the atmosphere of extratropical latitudes of the Northern Hemisphere based from model calculations compared with the data of the reanalysis and satellite data. Doklady Earth Sciences, 424(1), 147–150. https://doi.org/10.1134/S1028334X09010310
Neu, U., Akperov, M. G., Bellenbaum, N., Benestad, R., Blender, R., Caballero, R., et al. (2013). Imilast: A community effort to intercompare extratropical cyclone detection and tracking algorithms. Bulletin of the American Meteorological Society, 94(4), 529–547. https://doi.org/10.1175/BAMS-D-11-00154.1
Nishii, K., Nakamura, H., & Orsolini, Y. J. (2015). Arctic summer storm track in CMIP3/5 climate models. Climate Dynamics, 44(5-6), 1311–1327. https://doi.org/10.1007/s00382-014-2229-y
Orsolini, Y. J., & Sorteberg, A. (2009). Projected changes in Eurasian and Arctic summer cyclones under global warming in the Bergen climate model. Atmospheric and Oceanic Science Letters, 2(1), 62–67. https://doi.org/10.1080/16742834.2009.11446776
Parkinson, C. L., & Comiso, J. C. (2013). On the 2012 record low Arctic sea ice cover: Combined impact of preconditioning and an August storm. Geophysical Research Letters, 40, 1356–1361. https://doi.org/10.1002/grl.50349
Pinto, J. G., Ulbrich, U., Leckebusch, G. C., Spangehl, T., Reyers, M., & Zacharias, S. (2007). Changes in storm track and cyclone activity in three SRES ensemble experiments with the ECHAM5 / MPI-OM1 GCM. Changes, 29(2-3), 195–210. https://doi.org/10.1007/s00382-007-0230-4
Rasmussen, E. A., & Turner, J. (2003). Polar lows: Mesoscale weather systems in the polar regions (p. 612). Cambridge University Press. https://doi.org/10.1017/CBO9780511524974
Rinke, A., Dethloff, K., Dorn, W., Handorf, D., & Moore, J. C. (2013). Simulated Arctic atmospheric feedbacks associated with late summer sea ice anomalies. Journal of Geophysical Research: Atmospheres, 118, 7698–7714. https://doi.org/10.1002/jgrd.50584
Saha, S., Moorthi, S., Pan, H.-L., Wu, X., Wang, J., Nadiga, S., et al. (2010). The NCEP Climate Forecast System Reanalysis. Bulletin of the American Meteorological Society, 91(8), 1015–1058. https://doi.org/10.1175/2010BAMS3001.1
Scinocca, J., Kharin, V., Jiao, Y., Qian, M., Lazare, M., Solheim, L., et al. (2016). Coordinated global and regional climate modeling. Journal of Climate, 29(1), 17–35. https://doi.org/10.1175/JCLI-D-15-0161.1
Seiler, C., & Zwiers, F. W. (2016). How well do CMIP5 climate models reproduce explosive cyclones in the extratropics of the Northern Hemisphere? Climate Dynamics, 46(3-4), 1241–1256. https://doi.org/10.1007/s00382-015-2642-x
Sein, D. V., Koldunov, N. V., Pinto, J. G., & Cabos, W. (2014). Sensitivity of simulated regional Arctic climate to the choice of coupled model domain. Tellus Series A: Dynamic Meteorology and Oceanography, 66(1), 1–18. https://doi.org/10.3402/tellusa.v66.23966
Sein, D. V., Mikolajewicz, U., Gröger, M., Fast, I., Cabos, W., Pinto, J. G., et al. (2015). Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation. Journal of Advances in Modeling Earth Systems, 7(1), 268–304.
Semenov, V. A., & Latif, M. (2015). Nonlinear winter atmospheric circulation response to Arctic sea ice concentration anomalies for different periods during 1966–2012. Environmental Research Letters, 10(5), 054020. https://doi.org/10.1088/1748-9326/10/5/054020
Šeparović, L., Alexandru, A., Laprise, R., Martynov, A., Sushama, L., Winger, K., et al. (2013). Present climate and climate change over North America as simulated by the fifth-generation Canadian regional climate model. Climate Dynamics, 41(11-12), 3167–3201. https://doi.org/10.1007/s00382-013-1737-5
Sepp, M., & Jaagus, J. (2011). Changes in the activity and tracks of Arctic cyclones. Climatic Change, 105(3-4), 577–595. https://doi.org/10.1007/s10584-010-9893-7
Serreze, M. C., & Barrett, A. P. (2008). The summer cyclone maximum over the central Arctic Ocean. Journal of Climate, 21(5), 1048–1065. https://doi.org/10.1175/2007JCLI1810.1
Serreze, M. C., Box, J. E., Barry, R. G., & Walsh, J. E. (1993). Meteorology, and atmospheric physics characteristics of Arctic synoptic activity, 1952–1989. Hemisphere, 164, 147–164.
Serreze, M. C., Carse, F., Barry, R. G., & Rogers, J. C. (1997). Icelandic low cyclone activity: Climatological features, linkages with the NAO, and relationships with recent changes in the Northern Hemisphere circulation. Journal of Climate, 10(3), 453–464. https://doi.org/10.1175/1520-0442(1997)010%3C0453:ILCACF%3E2.0.CO;2
Shkolnik, I. M., & Efimov, S. V. (2013). Cyclonic activity in high latitudes as simulated by a regional atmospheric climate model: Added value and uncertainties. Environmental Research Letters, 8(4), 45007. https://doi.org/10.1088/1748-9326/8/4/045007
Simmonds, I., Burke, C., & Keay, K. (2008). Arctic climate change as manifest in cyclone behavior. Journal of Climate, 21(22), 5777–5796. https://doi.org/10.1175/2008JCLI2366.1
Simmonds, I., & Keay, K. (2009). Extraordinary September Arctic sea ice reductions and their relationships with storm behavior over 1979-2008. Geophysical Research Letters, 36, L19715. https://doi.org/10.1029/2009GL039810
Simmonds, I., & Rudeva, I. (2012). The great arctic cyclone of August 2012. Geophysical Research Letters, 39, L23709. https://doi.org/10.1029/2012GL054259
Simmonds, I., & Rudeva, I. (2014). A comparison of tracking methods for extreme cyclones in the Arctic basin. Tellus A, 66(1), 1–13. https://doi.org/10.3402/tellusa.v66.25252
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Wang, W., & Powers, J. G. (2008). A description of the Advanced Research WRF Version 3. NCAR technical note, NCAR/TN-475+STR.
Smirnova, J., & Golubkin, P. (2017). Comparing polar lows in atmospheric reanalyses: Arctic system reanalysis versus ERA-Interim. Monthly Weather Review, 145(6), 2375–2383. https://doi.org/10.1175/MWR-D-16-0333.1
Smith, B., Samuelsson, P., Wramneby, A., & Rummukainen, M. (2011). A model of the coupled dynamics of climate, vegetation and terrestrial ecosystem biogeochemistry for regional applications. Tellus Series A: Dynamic Meteorology and Oceanography, 63(1), 87–106. https://doi.org/10.1111/j.1600-0870.2010.00477.x
Sommerfeld, A., Nikiema, O., Rinke, A., Dethloff, K., & Laprise, R. (2015). Arctic budget study of intermember variability using HIRHAM5 ensemble simulations. Journal of Geophysical Research: Atmospheres, 120, 9390–9407. https://doi.org/10.1002/2015JD023153
Spengler, T., Claud, C., Heinemann, G., Spengler, T., Claud, C., & Heinemann, G. (2017). Polar low workshop summary. Bulletin of the American Meteorological Society, 98(6), ES139–ES142. https://doi.org/10.1175/BAMS-D-16-0207.1
Takhsha, M., Nikiéma, O., Lucas-Picher, P., Laprise, R., Hernández-Díaz, L., & Winger, K. (2017). Dynamical downscaling with the fifth-generation Canadian regional climate model (CRCM5) over the CORDEX Arctic domain: Effect of large-scale spectral nudging and of empirical correction of sea-surface temperature. Climate Dynamics, 1–26. https://doi.org/10.1007/s00382-017-3912-6
Thompson, D. W. J., & Wallace, J. M. (1998). The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophysical Research Letters, 25(9), 1297–1300. https://doi.org/10.1029/98GL00950
Tilinina, N., Gulev, S. K., & Bromwich, D. H. (2014). New view of Arctic cyclone activity from the Arctic System Reanalysis. Geophysical Research Letters, 41, 1766–1772. https://doi.org/10.1002/2013GL058924
Tsukernik, M., Kindig, D. N., & Serreze, M. C. (2007). Characteristics of winter cyclone activity in the northern North Atlantic: Insights from observations and regional modeling. Journal of Geophysical Research, 112, D03101. https://doi.org/10.1029/2006JD007184
Ulbrich, U., Leckebusch, G. C., Grieger, J., Schuster, M., Akperov, M., Bardin, M. Y., et al. (2013). Are greenhouse gas signals of northern hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm? Meteorologische Zeitschrift, 22(1), 61–68. https://doi.org/10.1127/0941-2948/2013/0420
Vavrus, S. J. (2013). Extreme Arctic cyclones in CMIP5 historical simulations. Geophysical Research Letters, 40, 6208–6212. https://doi.org/10.1002/2013GL058161
von Storch, H., Langenberg, H., & Feser, F. (2000). A spectral nudging technique for dynamical downscaling purposes. Monthly Weather Review, 128(10), 3664–3673. https://doi.org/10.1175/1520-0493(2000)128%3C3664:ASNTFD%3E2.0.CO;2
Wang, X. L., Feng, Y., Chan, R., & Isaac, V. (2016). Inter-comparison of extra-tropical cyclone activity in nine reanalysis datasets. Atmospheric Research, 181, 133–153. https://doi.org/10.1016/j.atmosres.2016.06.010
Wernli, H., & Schwierz, C. (2006). Surface cyclones in the ERA-40 da- taset (1958–2001). Part I: Novel identification method and global clima- tology. Journal of the Atmospheric Sciences, 63(10), 2486–2507. https://doi.org/10.1175/JAS3766.1
Woollings, T., Hannachi, A., & Hoskins, B. (2010). Variability of the North Atlantic eddy-driven jet stream. Quarterly Journal of the Royal Meteorological Society, 136(649), 856–868. https://doi.org/10.1002/qj.625
Zahn, M., & Von Storch, H. (2008). A long-term climatology of North Atlantic polar lows. Geophysical Research Letters, 35, L22702. https://doi.org/10.1029/2008GL035769
Zahn, M., & von Storch, H. (2010). Decreased frequency of North Atlantic polar lows associated with future climate warming. Nature, 467(7313), 309–312. https://doi.org/10.1038/nature09388
Zappa, G., Shaffrey, L. C., & Hodges, K. I. (2013). The ability of CMIP5 models to simulate North Atlantic extratropical cyclones. Journal of Climate, 26(15), 5379–5396. https://doi.org/10.1175/JCLI-D-12-00501.1
Zhang, J., Lindsay, R., Schweiger, A., & Steele, M. (2013). The impact of an intense summer cyclone on 2012 Arctic sea ice retreat. Geophysical Research Letters, 40, 720–726. https://doi.org/10.1002/grl.50190
Zhang, J., & Rothrock, D. A. (2003). Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates. Monthly Weather Review, 131(5), 845–861. https://doi.org/10.1175/1520-0493(2003)131h0845:MGSIWAi2.0.CO;2
Zhang, W., Jansson, C., Miller, P. A., Smith, B., & Samuelsson, P. (2014). Biogeophysical feedbacks enhance the Arctic terrestrial carbon sink in regional Earth system dynamics. Biogeosciences, 11(19), 5503–5519. https://doi.org/10.5194/bg-11-5503-2014
Zhang, X., Walsh, J. E., Zhang, J., Bhatt, U. S., & Ikeda, M. (2004). Climatology and interannual variability of Arctic cyclone activity: 1948-2002. Journal of Climate, 17(12), 2300–2317. https://doi.org/10.1175/1520-0442(2004)017%3C2300:CAIVOA%3E2.0.CO;2
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