On the contribution of internal climate variability to European future climate trends
By: T. Koenigk, L. Bärring, D. Matei, G. Nikulin, G. Strandberg, E. Tyrlis, S. Wang and R. Wilcke
References
- Arora, V. K. 2003. Simulating energy and carbon fluxes over winter wheat using coupled land surface and terrestrial ecosystem models. Agric. For. Meteorol. 118, 21–47. doi:10.1016/S0168-1923(03)00073-X
- Arora, V. K., Scinocca, J. F., Boer, G. J., Christian, J. R., Denman, K. L. and co-authors. 2011. Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases. Geophys. Res. Lett. 38, 1–6. doi:10.1029/2010GL046270
- Bengtsson, L. and Hodges, K. I. 2019. Can an ensemble climate simulation be used to separate climate change signals from internal unforced variability? Clim. Dyn. 52, 3553–3573. doi:10.1007/s00382-018-4343-8
- Bittner, M., Schmidt, H., Timmreck, C. and Sienz, F. 2016. Using a large ensemble of simulations to assess the Northern Hemisphere stratospheric dynamical response to tropical volcanic eruptions and its uncertainty. Geophys. Res. Lett. 43, 9324–9332. doi:10.1002/2016GL070587
- Christian, J. R., Arora, V. K., Boer, G. J., Curry, C. L., Zahariev, K. and co-authors. 2010. The global carbon cycle in the CCCma earth system model CanESM1: preindustrial control simulation. J. Geophy. Res. 115, 1–20. doi:10.1029/2008JG000920
- Dai, A. and Bloecker, C. E. 2019. Impacts of internal variability on temperature and precipitation trends in large ensemble simulations by two climate models. Clim. Dyn. 52, 289–306. doi:10.1007/s00382-018-4132-4
- Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P. and co-authors. 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597. doi:10.1002/qj.828
- Deser, C., Knutti, R., Solomon, S. and Phillips, A. S. 2012. Communication of the role of natural variability in future North American climate. Nat. Clim. Change 2, 775–779. doi:10.1038/nclimate1562
- Deser, C., Phillips, A., Bourdette, V. and Teng, H. 2012. Uncertainty in climate change projections: the role of internal variability. Clim. Dyn. 38, 527–546. doi:10.1007/s00382-010-0977-x
- Deser, C., Phillips, A. S., Alexander, M. A. and Smoliak, B. V. 2014. Projecting North American climate over the next 50 years: uncertainty due to internal variability. J. Clim. 27, 2271–2296. doi:10.1175/JCLI-D-13-00451.1
- Fischer, E. M., Sedlacek, J., Hawkins, E. and Knutti, R. 2014. Models agree on forced response pattern of precipitation and temperature extremes. Geophys. Res. Lett. 41, 8554–8562. doi:10.1002/2014GL062018
- Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J. and co-authors. 2013. Climate and carbon cycle changes from 1850 to 2100 in MPI‐ESM simulations for the Coupled Model Intercomparison Project phase 5. J. Adv. Model. Earth Syst. 5, 572–597. doi:10.1002/jame.20038
- Hawkins, E. 2011. Our evolving climate: communicating the effects of climate variability. Weather 66, 175–179. doi:10.1002/wea.761
- Hawkins, E. and Sutton, R. 2009. The potential to narrow uncertainties in regional climate predictions. Bull. Am. Meteor. Soc. 90, 1095–1107. doi:10.1175/2009BAMS2607.1
- Hawkins, E. and Sutton, R. 2012. Time of emergence of climate signals. Geophys. Res. Lett. 39, 1–6. doi:10.1029/2011GL050087
- Hedemann, C., Mauritsen, T., Jungclaus, J. and Marotzke, J. 2017. The subtle origins of surface-warming hiatuses. Nat. Clim. Change 7, 336–339. doi:10.1038/nclimate3274
- Horton, D. E., Johnson, N. C., Singh, D., Swain, D. L., Rajaratnam, B. and co-authors. 2015. Contribution of changes in atmospheric circulation patterns to extreme temperature trends. Nature 522, 465–469. doi:10.1038/nature14550
- Jahn, A., Kay, J. E., Holland, M. M. and Hall, D. M. 2016. How predictable is the timing of a summer ice-free Arctic? Geophys. Res. Lett. 43, 9113–9120. doi:10.1002/2016GL070067
- Jönsson, P. and Bärring, L. 1994. Zonal index variations, 1899–1992: links to air temperature in southern Scandinavia. Geogr. Ann. Ser. A Phys. Geogr. 76, 207–219.
- Jungclaus, J. H., Fischer, N., Haak, H., Lohmann, K., Marotzke, J. and co-authors. 2013. Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model. J. Adv. Model. Earth Syst. 5, 422–446. doi:10.1002/jame.20023
- Kirchmeier-Young, M. C., Zwiers, F. W. and Gillett, N. P. 2017. Attribution of extreme events in Arctic sea ice extent. J. Clim. 30, 553–571. doi:10.1175/JCLI-D-16-0412.1
- Koenigk, T., Gao, Y., Gastineau, G., Keenlyside, N., Nakamura, T. and co-authors. 2019. Impact of Arctic sea ice variations on winter temperature anomalies in northern hemispheric land areas. Clim. Dyn. 52, 3111–3137. doi:10.1007/s00382-018-4305-1
- Knutti, R. and Sedlacek, J. 2013. Robustness and uncertainties in the new CMIP5 climate model projections. Nat. Clim. Change 3, 369–373. doi:10.1038/nclimate1716
- Maher, N., Milinski, S., Suarez‐Gutierrez, L., Botzet, M., Dobrynin, M. and co-authors. 2019. The Max Planck Institute Grand Ensemble: enabling the exploration of climate system variability. J. Adv. Model. Earth Syst. 11, 2050–2021. doi:10.1029/2019MS001639
- Marotzke, J. 2019. Quantifying the irreducible uncertainty in near-term climate projections. Wiley Interdiscip. Rev. Clim. Change 10, e563. doi:10.1002/wcc.563
- Moberg, A. and Bergström, H. 1997. Homogenization of Swedish temperature data. Part III: the long temperature records from Uppsala and Stockholm. Int. J. Climatol. 17, 667–699. doi:10.1002/(;SICI)1097-0088(19970615)17:7<667::AID-JOC115>3.0.CO;2-J
- Moberg, A., Jones, P. D., Barriendos, M., Bergström, H., Camuffo, D. and co-authors. 2000. Day‐to‐day temperature variability trends in 160‐ to 275‐year‐long European instrumental records. J. Geophys. Res. 105, 22849–22868. doi:10.1029/2000JD900300
- Mori, M., Watanabe, M., Shiogama, H., Inoue, J. and Kimoto, M. 2014. Robust Arctic sea-ice influence on the frequent Eurasian cold winters in past decades. Nat. Geosci. 7, 869–873. doi:10.1038/ngeo2277
- Niederdrenk, A. L. and Notz, D. 2018. Arctic sea ice in a 1.5 °C warmer world. Geophys. Res. Lett. 45, 1963–1971. doi:10.1002/2017GL076159
- Notz, D., Haumann, F. A., Haak, H., Jungclaus, J. H. and Marotzke, J. 2013. Arctic sea-ice evolution as modeled by Max Planck Institute for Meteorology’s Earth system model. J. Adv. Modell. Earth Syst. 5, 1–22.
- Ogawa, F., Keenlyside, N., Gao, Y., Koenigk, T., Yang, S. and co-authors. 2018. Evaluating impacts of recent Arctic sea ice loss on the northern hemisphere winter climate change. Geophys. Res. Lett. 45, 3255–3263. doi:10.1002/2017GL076502
- Rondeau-Genesse, G. and Braun, M. 2019. Impact of internal variability on climate change for the upcoming decades: analysis of the CanESM2-LE and CESM-LE large ensembles. Clim. Change 156, 299–314. doi:10.1007/s10584-019-02550-2
- Sigmond, M. and Fyfe, J. 2016. Tropical Pacific impacts on cooling North American winters. Nat. Clim. Change 6, 970–974. doi:10.1038/nclimate3069
- Suárez-Gutiérrez, L., Chao, L., Müller, W. A. and Marotzke, J. 2018. Internal variability in European summer temperatures at 1.5 °C and 2 °C of global warming. Environ. Res. Lett. 13, 064026. doi:10.1088/1748-9326/aaba58
- Suárez-Gutiérrez, L., Li, C., Thorne, P. W. and Marotzke, J. 2017. Internal variability in simulated and observed tropical tropospheric temperature trends. Geophys. Res. Lett. 44, 5709–5719. doi:10.1002/2017GL073798
- Taylor, K. E., Stouffer, R. J. and Meehl, G. A. 2012. An overview of CMIP5 and the experiment design. Bull. Am. Meteor. Soc. 93, 485–498. doi:10.1175/BAMS-D-11-00094.1
- Vihma, T. 2014. Effects of Arctic sea ice decline on weather and climate: a review. Surv. Geophys. 35, 1175–1214. doi:10.1007/s10712-014-9284-0
- von Storch, H. and Zwiers, F. 1999. Statistical Analysis in Climate Research. Cambridge University Press, Cambridge.
- von Trentini, F., Leduc, M. and Ludwig, R. 2019. Assessing natural variability in RCM signals: comparison of a multi model EURO-CORDEX ensemble with a 50-member single model large ensemble. Clim. Dyn. 53, 1963–1979. doi:10.1007/s00382-019-04755-8
DOI: https://doi.org/10.1080/16000870.2020.1788901 | Journal eISSN: 3035-9554
Language: English
Page range: 1788901 - 1788901
Published on: Jan 1, 2020
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
© 2020 T. Koenigk, L. Bärring, D. Matei, G. Nikulin, G. Strandberg, E. Tyrlis, S. Wang, R. Wilcke, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.