The Lorenz energy cycle: trends and the impact of modes of climate variability

References

• Ambaum, M. H. 2010. Thermal Physics of the Atmosphere. Chichester, UK: John Wiley & Sons Ltd.
   Google Scholar
• Barpanda, P. and Shaw, T. 2017. Using the moist static energy budget to understand storm-track shifts across a range of time scales. J. Atmos. Sci. 74, 2427–2446. doi:https://doi.org/10.1175/JAS-D-17-0022.1
   Web of Science ®Google Scholar
• Boer, G. J. and Lambert, S. 2008. The energy cycle in atmospheric models. Clim. Dyn. 30, 371–390. doi:https://doi.org/10.1007/s00382-007-0303-4
   Web of Science ®Google Scholar
• Cassou, C. 2008. Intraseasonal interaction between the Madden-Julian Oscillation and the North Atlantic oscillation. Nature 455, 523–527. doi:https://doi.org/10.1038/nature07286
   PubMed Web of Science ®Google Scholar
• Castanheira, J. M. and Marques, C. A. 2019. The energy cascade associated with daily variability of the north atlantic oscillation. Q. J. R. Meteorol. Soc. 145, 197–210. doi:https://doi.org/10.1002/qj.3422
   Web of Science ®Google Scholar
• Chemke, R. and Ming, Y. 2020. 2020: Large atmospheric waves will get stronger while small waves will get weaker by the end of the 21st century. Geophys. Res. Lett. 47, e2020GL090441.
   Web of Science ®Google Scholar
• Clément, M., Nikiéma, O. and Laprise, R. 2017. Limited-area atmospheric energetics: illustration on a simulation of the crcm5 over eastern north America for december 2004. Clim. Dyn. 48, 2797–2818. doi:https://doi.org/10.1007/s00382-016-3198-0
   Web of Science ®Google Scholar
• Dai, A. and Song, M. 2020. Little influence of arctic amplification on mid-latitude climate. Nat. Clim. Chang. 10, 231–237. doi:https://doi.org/10.1038/s41558-020-0694-3
   Web of Science ®Google Scholar
• Davis, N. and Davis, S. M. 2018. Reconciling hadley cell expansion trend estimates in reanalyses. Geophys. Res. Lett. 45, 11–439.
   Web of Science ®Google Scholar
• Feldstein, S. B. and Franzke, C. L. E. 2017. Atmospheric teleconnection patterns. In: Nonlinear and Stochastic Climate Dynamics (eds. L. E. Franzke, and T. O’Kane). Cambridge, UK: Cambridge University Press, pp. 54–104.
   Google Scholar
• Frajka-Williams, E., Beaulieu, C. and Duchez, A. 2017. Emerging negative atlantic multidecadal oscillation index in spite of warm subtropics. Sci. Rep. 7, 1–8.
   Web of Science ®Google Scholar
• Franzke, C. L. E., Feldstein, S. B. and Lee, S. 2011. Synoptic analysis of the Pacific–North American teleconnection pattern. Q. J. R. Meteorol. Soc. 137, 329–346. doi:https://doi.org/10.1002/qj.768
   Web of Science ®Google Scholar
• Franzke, C. L. E., Jelic, D., Lee, S. and Feldstein, S. B. 2019. Systematic decomposition of the MJO and its Northern Hemispheric extratropical response into Rossby and inertio-gravity components. Q. J. R. Meteorol. Soc. 145, 1147–1164. doi:https://doi.org/10.1002/qj.3484
   Web of Science ®Google Scholar
• Franzke, C. L. E. and Torelló I Sentelles, H. 2020. Mortality risks and modes of climate variability. Clim. Change 162, 141–157.
   Google Scholar
• Gocic, M. and Trajkovic, S. 2013. Analysis of changes in meteorological variables using mann-kendall and sen’s slope estimator statistical tests in serbia. Global Planet. Change 100, 172–182. doi:https://doi.org/10.1016/j.gloplacha.2012.10.014
   Web of Science ®Google Scholar
• Hannachi, A., Straus, D. M., Franzke, C. L. E., Corti, S. and Woollings, T. 2017. Low-frequency nonlinearity and regime behavior in the Northern Hemisphere extratropical atmosphere. Rev. Geophys. 55, 199–234. URL, 2015RG000509. doi:https://doi.org/10.1002/2015RG000509
   Web of Science ®Google Scholar
• Hernández-Deckers, D. and von Storch, J.-S. 2010. Energetics responses to increases in greenhouse gas concentration. J. Clim. 23, 3874–3887. doi:https://doi.org/10.1175/2010JCLI3176.1
   Web of Science ®Google Scholar
• Holton, J. R. and Hakim, G. J. 2012. An Introduction to Dynamic Meteorology, Vol. 88. Burlington, MA: Academic Press.
   Google Scholar
• Hu, Q., Tawaye, Y. and Feng, S. 2004. Variations of the northern hemisphere atmospheric energetics: 1948–2000. J. Climate 17, 1975–1986. doi:https://doi.org/10.1175/1520-0442(2004)017<1975:VOTNHA>2.0.CO;2
   Web of Science ®Google Scholar
• Huang, J. and McElroy, M. B. 2014. Contributions of the hadley and ferrel circulations to the energetics of the atmosphere over the past 32 years. J. Clim. 27, 2656–2666. doi:https://doi.org/10.1175/JCLI-D-13-00538.1
   Web of Science ®Google Scholar
• Kang, S. M. and Lu, J. 2012. Expansion of the hadley cell under global warming: Winter versus summer. J. Clim. 25, 8387–8393. doi:https://doi.org/10.1175/JCLI-D-12-00323.1
   Web of Science ®Google Scholar
• Kim, Y.-H. and Kim, M.-K. 2013. Examination of the global Lorenz energy cycle using merra and ncep-reanalysis 2. Clim. Dyn. 40, 1499–1513. doi:https://doi.org/10.1007/s00382-012-1358-4
   Web of Science ®Google Scholar
• Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., and co-authors. 2015. The jra-55 reanalysis: General specifications and basic characteristics. J. Meteorol. Soc. Japan 93, 5–48. doi:https://doi.org/10.2151/jmsj.2015-001
   Web of Science ®Google Scholar
• Lembo, V., Lunkeit, F. and Lucarini, V. 2019a. Thediato (v1. 0)–a new diagnostic tool for water, energy and entropy budgets in climate models. Geosci. Model Dev. 12, 3805–3834. doi:https://doi.org/10.5194/gmd-12-3805-2019
   Web of Science ®Google Scholar
• Lembo, V., Messori, G., Graversen, R. and Lucarini, V. 2019b. Spectral decomposition and extremes of atmospheric meridional energy transport in the northern hemisphere midlatitudes. Geophys. Res. Lett. 46, 7602–7613. doi:https://doi.org/10.1029/2019GL082105
   Web of Science ®Google Scholar
• Li, L., Ingersoll, A. P., Jiang, X., Feldman, D. and Yung, Y. L. 2007. Lorenz energy cycle of the global atmosphere based on reanalysis datasets. Geophys. Res. Lett. 34, L16813.
   Web of Science ®Google Scholar
• Li, L., Jiang, X., Chahine, M. T., Wang, J. and Yung, Y. L. 2011. The mechanical energies of the global atmosphere in el niño and la niña years. J. Atmos. Sci. 68, 3072–3078. doi:https://doi.org/10.1175/JAS-D-11-072.1
   Web of Science ®Google Scholar
• Lorenz, E. N. 1955. Available potential energy and the maintenance of the general circulation. Tellus 7, 157–167.
   Google Scholar
• Lucarini, V., Fraedrich, K. and Ragone, F. 2011. New results on the thermodynamic properties of the climate system. J. Atmos. Sci. 68, 2438–2458. URL https://journals.ametsoc.org/jas/article/68/10/2438/27096/New-Results-on-the-Thermodynamic-Properties-of-the. doi:https://doi.org/10.1175/2011JAS3713.1
   Web of Science ®Google Scholar
• Makarieva, A., Gorshkov, V., Nefiodov, A., Sheil, D., Nobre, A. and co-authors. 2017. Kinetic energy generation in heat engines and heat pumps: the relationship between surface pressure, temperature and circulation cell size. Tellus A: Dyn. Meteorol. Oceanograph. 69, 1272752. doi:https://doi.org/10.1080/16000870.2016.1272752
   Web of Science ®Google Scholar
• Mann, H. B. 1945. Nonparametric tests against trend. Econometrica 13, 245–259. doi:https://doi.org/10.2307/1907187
   Web of Science ®Google Scholar
• Marques, C., Rocha, A. and Corte-Real, J. 2010. Comparative energetics of era-40, jra-25 and ncep-r2 reanalysis, in the wave number domain. Dyn. Atmos. Oceans 50, 375–399. doi:https://doi.org/10.1016/j.dynatmoce.2010.03.003
   Web of Science ®Google Scholar
• Marques, C. A., Rocha, A., Corte-Real, J., Castanheira, J. M., Ferreira, J. and co-authors. 2009. Global atmospheric energetics from ncep–reanalysis 2 and ecmwf–era40 reanalysis. Int. J. Climatol. 29, 159–174. doi:https://doi.org/10.1002/joc.1704
   Web of Science ®Google Scholar
• Martineau, P., Nakamura, H., Kosaka, Y. and Yamamoto, A. 2020. Importance of a vertically tilting structure for energizing the north atlantic oscillation. Sci. Rep. 10, 1–10.
   Web of Science ®Google Scholar
• Nachar, N. 2008. The Mann-Whitney U: a test for assessing whether two independent samples come from the same distribution. Tutor Quant. Methods Psychol. 4, 13–20. doi:https://doi.org/10.20982/tqmp.04.1.p013
   Google Scholar
• Neelin, J. D. and Held, I. M. 1987. Modeling tropical convergence based on the moist static energy budget. Mon. Wea. Rev. 115, 3–12. doi:https://doi.org/10.1175/1520-0493(1987)115<0003:MTCBOT>2.0.CO;2
   Web of Science ®Google Scholar
• Pan, Y., Li, L., Jiang, X., Li, G., Zhang, W. and co-authors. 2017. Earth’s changing global atmospheric energy cycle in response to climate change. Nat. Commun. 8, 14367–14368. doi:https://doi.org/10.1038/ncomms14367
   Web of Science ®Google Scholar
• Peixóto, J. P. and Oort, A. H. 1974. The annual distribution of atmospheric energy on a planetary scale. J. Geophys. Res. 79, 2149–2159. doi:https://doi.org/10.1029/JC079i015p02149
   Web of Science ®Google Scholar
• Prigogine, I. 1962. Non-Equilibrium Statistical Mechanics. Wiley, New York, p. 336.
   Google Scholar
• Ruggieri, P., Alvarez-Castro, M. C., Athanasiadis, P., Bellucci, A., Materia, S., and co-authors. 2020. North atlantic circulation regimes and heat transport by synoptic eddies. J. Clim. 33, 4769–4785. doi:https://doi.org/10.1175/JCLI-D-19-0498.1
   Web of Science ®Google Scholar
• Salmi, T. 2002. Detecting Trends of Annual Values of Atmospheric Pollutants by the Mann-Kendall Test and Sen’s Slope Estimates-the Excel Template Application MAKESENS. Finnish Meteorological Institute Helsinki: Ilmatieteen laitos.
   Google Scholar
• Sardeshmukh, P. D. and Hoskins, B. J. 1988. The generation of global rotational flow by steady idealized tropical divergence. J. Atmos. Sci. 45, 1228–1251. doi:https://doi.org/10.1175/1520-0469(1988)045<1228:TGOGRF>2.0.CO;2
   Web of Science ®Google Scholar
• Seidel, D. J., Fu, Q., Randel, W. J. and Reichler, T. J. 2008. Widening of the tropical belt in a changing climate. Nature Geosci. 1, 21–24. doi:https://doi.org/10.1038/ngeo.2007.38
   Web of Science ®Google Scholar
• Sen, P. K. 1968. Estimates of the regression coefficient based on Kendall’s tau. J. Amer. Stat. Assoc. 63, 1379–1389. doi:https://doi.org/10.1080/01621459.1968.10480934
   Web of Science ®Google Scholar
• Shaw, T. A., Barpanda, P. and Donohoe, A. 2018. A moist static energy framework for zonal-mean storm-track intensity. J. Atmos. Sci. 75, 1979–1994. doi:https://doi.org/10.1175/JAS-D-17-0183.1
   Web of Science ®Google Scholar
• Simmonds, I., Keay, K. and Lim, E.-P. 2003. Synoptic activity in the seas around antarctica. Mon. Wea. Rev. 131, 272–288. doi:https://doi.org/10.1175/1520-0493(2003)131<0272:SAITSA>2.0.CO;2
   Web of Science ®Google Scholar
• Sohn, B., Yeh, S.-W., Schmetz, J. and Song, H.-J. 2013. Observational evidences of walker circulation change over the last 30 years contrasting with gcm results. Clim. Dyn. 40, 1721–1732. doi:https://doi.org/10.1007/s00382-012-1484-z
   Web of Science ®Google Scholar
• Trenberth, K. E. and Fasullo, J. T. 2013. An apparent hiatus in global warming? Earth’s Future 1, 19–32. doi: https://doi.org/https://doi.org/10.1002/2013EF000165, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2013EF000165, https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2013EF000165. doi:https://doi.org/10.1002/2013EF000165
   Web of Science ®Google Scholar
• Ulbrich, U. and Speth, P. 1991. The global energy cycle of stationary and transient atmospheric waves: Results from ecmwf analyses. Meteorl. Atmos. Phys. 45, 125–138. doi:https://doi.org/10.1007/BF01029650
   Web of Science ®Google Scholar
• Veiga, J. A. P., Pezza, A. B., Ambrizzi, T., Rao, V. B., Franchito, S. H. and co-authors. 2013. The energy cycle associated to the pacific walker circulation and its relationship to enso. Atmos. Climate. Sci. 3, 627–642.
   Google Scholar
• Ye, Q. and Ahammed, F. 2020. Quantification of relationship between annual daily maximum temperature and annual daily maximum rainfall in south Australia. Atmos. Oceanic Sci. Lett. 13, 286–288.
   Web of Science ®Google Scholar