• Betts, A. K., , Ball J. H. , , Beljaars A. C. M. , , Miller M. J. , , and Viterbo P. A. , 1996: The land surface–atmosphere interaction: A review based on observational and global modelling perspectives. J. Geophys. Res., 101, 72097225, doi:10.1029/95JD02135.

    • Search Google Scholar
    • Export Citation
  • Bi, D., and et al. , 2013: The ACCESS coupled model: Description, control climate and evaluation. Aust. Meteor. Oceanogr. J., 63, 932.

    • Search Google Scholar
    • Export Citation
  • Boberg, F., , and Christensen J. H. , 2012: Overestimation of Mediterranean summer temperature projections due to model deficiencies. Nat. Climate Change, 2, 433436, doi:10.1038/nclimate1454.

    • Search Google Scholar
    • Export Citation
  • CPC, 2013a: Monthly OISST.v2 (1981–2010 base period) data. NOAA/NWS/CPC, accessed 12 May 2013. [Available online at http://www.cpc.ncep.noaa.gov/data/indices/sstoi.indices.]

  • CPC, 2013b: Monthly OISST.v1 (1971–2000 base period) data. NOAA/NWS/CPC, accessed 12 May 2013. [Available online at http://www.cpc.ncep.noaa.gov/data/indices/old_indices/sstoi.indices_old.]

  • Davies, T., , Cullen M. J. P. , , Malcolm A. J. , , Mawson M. H. , , Staniforth A. , , White A. A. , , and Wood N. , 2005: A new dynamical core for the Met Office’s global and regional modelling of the atmosphere. Quart. J. Roy. Meteor. Soc., 131, 17591782, doi:10.1256/qj.04.101.

    • Search Google Scholar
    • Export Citation
  • Delworth, T. L., , and Manabe S. , 1988: The influence of potential evaporation on the variabilities of simulated soil wetness and climate. J. Climate, 1, 523547, doi:10.1175/1520-0442(1988)001<0523:TIOPEO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Diffenbaugh, N. S., , and Ashfaq M. , 2010: Intensification of hot extremes in the United States. Geophys. Res. Lett., 37, L15701, doi:10.1029/2010GL043888.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., 2011: The terrestrial segment of soil moisture–climate coupling. Geophys. Res. Lett., 38, L16702, doi:10.1029/2011GL048268.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., , Jin Y. , , Singh B. , , and Yan X. , 2013a: Evolving land–atmosphere interactions over North America from CMIP5 simulations. J. Climate, 26, 73137327, doi:10.1175/JCLI-D-12-00454.1.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., , Jin Y. , , Singh B. , , and Yan X. , 2013b: Trends in land–atmosphere interactions from CMIP5 simulations. J. Hydrometeor., 14, 829849, doi:10.1175/JHM-D-12-0107.1.

    • Search Google Scholar
    • Export Citation
  • Dirmeyer, P. A., , Wang Z. , , Mbuh M. J. , , and Norton H. E. , 2014: Intensified land surface control on boundary layer growth in a changing climate. Geophys. Res. Lett., 41, 12901294, doi:10.1002/2013GL058826.

    • Search Google Scholar
    • Export Citation
  • Dix, M., and et al. , 2013: The ACCESS coupled model: Documentation of core CMIP5 simulations and initial results. Aust. Meteor. Oceanogr. J., 63, 8399.

    • Search Google Scholar
    • Export Citation
  • Edwards, J., , and Slingo A. , 1996: Studies with a flexible new radiation code. I: Choosing a configuration for a large-scale model. Quart. J. Roy. Meteor. Soc., 122, 689719, doi:10.1002/qj.49712253107.

    • Search Google Scholar
    • Export Citation
  • Findell, K. L., , and Eltahir E. A. B. , 2003: Atmospheric controls on soil moisture boundary layer interactions. Part II: Feedbacks within the continental United States. J. Hydrometeor., 4, 570583, doi:10.1175/1525-7541(2003)004<0570:ACOSML>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fischer, E. M., , Seneviratne S. I. , , Lüthi D. , , and Schär C. , 2007: Contribution of land–atmosphere coupling to recent European summer heat waves. Geophys. Res. Lett., 34, L06707, doi:10.1029/2006GL029068.

    • Search Google Scholar
    • Export Citation
  • Flato, G., and et al. , 2013: Evaluation of climate models. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 741–866.

  • Ford, T. W., , and Quiring S. M. , 2014: In situ soil moisture coupled with extreme temperatures: A study based on the Oklahoma Mesonet. Geophys. Res. Lett., 41, 47274734, doi:10.1002/2014GL060949.

    • Search Google Scholar
    • Export Citation
  • Gates, W. L., 1992: AMIP: The Atmospheric Model Intercomparison Project. Bull. Amer. Meteor. Soc., 73, 1962–1970, doi:10.1175/1520-0477(1992)073<1962:ATAMIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gregory, D., , and Rowntree P. , 1990: A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev., 118, 14831506, doi:10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Guo, Z., , and Dirmeyer P. A. , 2013: Interannual variability of land–atmosphere coupling strength. J. Hydrometeor., 14, 16361646, doi:10.1175/JHM-D-12-0171.1.

    • Search Google Scholar
    • Export Citation
  • Hewitt, H. T., , Copsey D. , , Culverwell I. D. , , Harris C. M. , , Hill R. S. R. , , Keen A. B. , , McLaren A. J. , , and Hunke E. C. , 2011: Design and implementation of the infrastructure of HadGEM3: The next-generation Met Office climate modelling system. Geosci. Model Dev., 4 (2), 223253, doi:10.5194/gmd-4-223-2011.

    • Search Google Scholar
    • Export Citation
  • Hirsch, A. L., , Kala J. , , Pitman A. J. , , Carouge C. , , Evans J. P. , , Haverd V. , , and Mocko D. , 2014a: Impact of land surface initialization approach on subseasonal forecast skill: A regional analysis in the Southern Hemisphere. J. Hydrometeor., 15, 300319, doi:10.1175/JHM-D-13-05.1.

    • Search Google Scholar
    • Export Citation
  • Hirsch, A. L., , Pitman A. J. , , Seneviratne S. I. , , Evans J. P. , , and Haverd V. , 2014b: Summertime maximum and minimum temperature coupling asymmetry over Australia determined using WRF. Geophys. Res. Lett., 41, 15461552, doi:10.1002/2013GL059055.

    • Search Google Scholar
    • Export Citation
  • Hirschi, M., and et al. , 2011: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe. Nat. Geosci., 4, 1721, doi:10.1038/ngeo1032.

    • Search Google Scholar
    • Export Citation
  • Jaeger, E. B., , and Seneviratne S. I. , 2011: Impact of soil moisture–atmosphere coupling on European climate extremes and trends in a regional climate model. Climate Dyn., 36, 19191939, doi:10.1007/s00382-010-0780-8.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , Dirmeyer P. A. , , Hahmann A. N. , , Ijpelaar R. , , Tyahla L. , , Cox P. M. , , and Suarez M. J. , 2002: Comparing the degree of land–atmosphere interaction in four atmospheric general circulation models. J. Hydrometeor., 3, 363–375, doi:10.1175/1525-7541(2002)003<0363:CTDOLA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and et al. , 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 11381140, doi:10.1126/science.1100217.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and et al. , 2006: GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview. J. Hydrometeor., 7, 590610, doi:10.1175/JHM510.1.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , Schubert S. D. , , and Suarez M. J. , 2009a: Analyzing the concurrence of meteorological droughts and warm periods, with implications for the determination of evaporative regime. J. Climate, 22, 33313341, doi:10.1175/2008JCLI2718.1.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , Wang H. , , Schubert S. D. , , Suarez M. J. , , and Mahanama S. , 2009b: Drought-induced warming in the continental United States under different SST regimes. J. Climate, 22, 53855400, doi:10.1175/2009JCLI3075.1.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and et al. , 2011: The second phase of the Global Land–Atmosphere Coupling Experiment: Soil moisture contributions to subseasonal forecast skill. J. Hydrometeor., 12, 805822, doi:10.1175/2011JHM1365.1.

    • Search Google Scholar
    • Export Citation
  • Kowalczyk, E. A., and et al. , 2013: The land surface model component of ACCESS: Description and impact on the simulated surface climatology. Aust. Meteor. Oceanogr. J., 63, 6582.

    • Search Google Scholar
    • Export Citation
  • Lewis, S. C., , and Karoly D. J. , 2013: Evaluation of historical diurnal temperature range trends in CMIP5 models. J. Climate, 26, 90779089, doi:10.1175/JCLI-D-13-00032.1.

    • Search Google Scholar
    • Export Citation
  • Lorenz, R., , Davin E. L. , , and Seneviratne S. I. , 2012: Modeling land–climate coupling in Europe: Impact of land surface representation on climate variability and extremes. J. Geophys. Res., 117, D20109, doi:10.1029/2012JD017755.

    • Search Google Scholar
    • Export Citation
  • Lorenz, R., , Pitman A. J. , , Donat M. G. , , Hirsch A. L. , , Kala J. , , Kowalczyk E. A. , , Law R. M. , , and Srbinovsky J. , 2014: Representation of climate extreme indices in the ACCESS1.3b coupled atmosphere–land surface model. Geosci. Model Dev., 7, 545567, doi:10.5194/gmd-7-545-2014.

    • Search Google Scholar
    • Export Citation
  • Martin, G. M., , Ringer M. A. , , Pope V. D. , , Jones A. , , Dearden C. , , and Hinton T. J. , 2006: The physical properties of the atmosphere in the New Hadley Centre Global Environmental Model (HadGEM1). Part I: Model description and global climatology. J. Climate, 19, 12741301, doi:10.1175/JCLI3636.1.

    • Search Google Scholar
    • Export Citation
  • Miralles, D. G., , van den Berg M. J. , , Teuling A. J. , , and de Jeu R. A. M. , 2012: Soil moisture–temperature coupling: A multiscale observational analysis. Geophys. Res. Lett., 39, L21707, doi:10.1029/2012GL053703.

    • Search Google Scholar
    • Export Citation
  • Miralles, D. G., , Teuling A. J. , , van Heerwaarden C. C. , , and Vilà-Guerau de Arellano J. , 2014: Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci., 7, 345349, doi:10.1038/ngeo2141.

    • Search Google Scholar
    • Export Citation
  • Mueller, B., , and Seneviratne S. I. , 2012: Hot days induced by precipitation deficits at the global scale. Proc. Natl. Acad. Sci. USA, 109, 12 39812 403, doi:10.1073/pnas.1204330109.

    • Search Google Scholar
    • Export Citation
  • Mueller, B., , and Seneviratne S. I. , 2014: Systematic land climate and evapotranspiration biases in CMIP5 simulations. Geophys. Res. Lett., 41, 128134, doi:10.1002/2013GL058055.

    • Search Google Scholar
    • Export Citation
  • Orlowsky, B., , and Seneviratne S. I. , 2010: Statistical analyses of land–atmosphere feedbacks and their possible pitfalls. J. Climate, 23, 39183932, doi:10.1175/2010JCLI3366.1.

    • Search Google Scholar
    • Export Citation
  • PCMDI, 2013: AMIP boundary condition data at 1 by 1 degree resolution. Lawrence Livermore National Laboratory, accessed 17 July 2013. [Available online at http://www-pcmdi.llnl.gov/projects/amip/AMIP2EXPDSN/BCS/amipbc_dwnld.php.]

  • Pitman, A. J., , Arneth A. , , and Ganzeveld L. , 2012: Regionalizing global climate models. Int. J. Climatol., 32, 321337, doi:10.1002/joc.2279.

    • Search Google Scholar
    • Export Citation
  • Priestley, C. H. B., , and Taylor R. J. , 1972: On the assessment of surface heat flux and evaporation using large-scale parameters. Mon. Wea. Rev., 100, 8192, doi:10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Puri, K., and et al. , 2013: Implementation of the initial ACCESS numerical weather prediction system. Aust. Meteor. Oceanogr. J., 63, 265284.

    • Search Google Scholar
    • Export Citation
  • Quesada, B., , Vautard R. , , Yiou P. , , Hirschi M. , , and Seneviratne S. I. , 2012: Asymmetric European summer heat predictability from wet and dry southern winters and springs. Nat. Climate Change, 2, 736–741, doi:10.1038/nclimate1536.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., , Lüthi D. , , Litschi M. , , and Schär C. , 2006: Land–atmosphere coupling and climate change in Europe. Nature, 443, 205209, doi:10.1038/nature05095.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., , Corti T. , , Davin E. L. , , Hirschi M. , , Jaeger E. B. , , Lehner I. , , Orlowsky B. , , and Teuling A. J. , 2010: Investigating soil moisture–climate interactions in a changing climate: A review. Earth-Sci. Rev., 99, 125–161, doi:10.1016/j.earscirev.2010.02.004.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., and et al. , 2013: Impact of soil moisture–climate feedbacks on CMIP5 projections: First results from the GLACE-CMIP5 experiment. Geophys. Res. Lett., 40, 52125217, doi:10.1002/grl.50956.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., , Williamson D. , , and Zwiers F. , 2000: The Sea Surface Temperature and Sea-Ice Concentration Boundary Conditions For AMIP II Simulations. PCMDI Rep. 60, 24 pp. [Available online at http://www-pcmdi.llnl.gov/publications/pdf/60.pdf.]

  • van den Hurk, B., , Doblas-Reyes F. , , Balsamo G. , , Koster R. D. , , Seneviratne S. I. , , and Camargo H. Jr., 2012: Soil moisture effects on seasonal temperature and precipitation forecast scores in Europe. Climate Dyn., 38, 349362, doi:10.1007/s00382-010-0956-2.

    • Search Google Scholar
    • Export Citation
  • Wang, G., , Kim Y. , , and Wang D. , 2007: Quantifying the strength of soil moisture–precipitation coupling and its sensitivity to changes in surface water budget. J. Hydrometeor., 8, 551570, doi:10.1175/JHM573.1.

    • Search Google Scholar
    • Export Citation
  • Wang, Y. P., , and Leuning R. , 1998: A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy I: Model description and comparison with a multi-layered model. Agric. For. Meteor., 91, 89111, doi:10.1016/S0168-1923(98)00061-6.

    • Search Google Scholar
    • Export Citation
  • Wang, Y. P., , Kowalczyk E. , , Leuning R. , , Abramowitz G. , , Raupach M. R. , , Pak B. , , van Gorsel E. , , and Luhar A. , 2011: Diagnosing errors in a land surface model (CABLE) in the time and frequency domains. J. Geophys. Res., 116, G01034, doi:10.1029/2010JG001385.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., , Alexander L. , , Hegerl G. C. , , Jones P. , , Tank A. K. , , Peterson T. C. , , Trewin B. , , and Zwiers F. W. , 2011: Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdiscip. Rev.: Climate Change, 2, 851870, doi:10.1002/wcc.147.

    • Search Google Scholar
    • Export Citation
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Intraseasonal versus Interannual Measures of Land–Atmosphere Coupling Strength in a Global Climate Model: GLACE-1 versus GLACE-CMIP5 Experiments in ACCESS1.3b

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  • 1 ARC Centre of Excellence for Climate System Science, and Climate Change Research Centre, University of New South Wales, Sydney, New South Wales, Australia
  • | 2 CSIRO Oceans and Atmosphere Flagship, Aspendale, Victoria, Australia
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Abstract

Land–atmosphere coupling can strongly affect climate and climate extremes. Estimates of land–atmosphere coupling vary considerably between climate models, between different measures used to define coupling, and between the present and the future. The Australian Community Climate and Earth-System Simulator, version 1.3b (ACCESS1.3b), is used to derive and examine previously used measures of coupling strength. These include the GLACE-1 coupling measure derived on seasonal time scales; a similar measure defined using multiyear simulations; and four other measures of different complexity and data requirements, including measures that can be derived from standard model runs and observations. The ACCESS1.3b land–atmosphere coupling strength is comparable to other climate models. The coupling strength in the Southern Hemisphere summer is larger compared to the Northern Hemisphere summer and is dominated by a strong signal in the tropics and subtropics. The land–atmosphere coupling measures agree on the location of very strong land–atmosphere coupling but show differences in the spatial extent of these regions. However, the investigated measures show disagreement in weaker coupled regions, and some regions are only identified by a single measure as strongly coupled. In future projections the soil moisture trend is crucial in generating regions of strong land–atmosphere coupling, and the results suggest an expansion of coupling “hot spots.” It is concluded that great care needs to be taken in using different measures of coupling strength and shown that several measures that can be easily derived lead to inconsistent conclusions with more computationally expensive measures designed to measure coupling strength.

Corresponding author address: Ruth Lorenz, ARC Centre of Excellence for Climate System Science, University of New South Wales, Level 4, Mathews Building, Sydney NSW 2052, Australia. E-mail: r.lorenz@unsw.edu.au

Abstract

Land–atmosphere coupling can strongly affect climate and climate extremes. Estimates of land–atmosphere coupling vary considerably between climate models, between different measures used to define coupling, and between the present and the future. The Australian Community Climate and Earth-System Simulator, version 1.3b (ACCESS1.3b), is used to derive and examine previously used measures of coupling strength. These include the GLACE-1 coupling measure derived on seasonal time scales; a similar measure defined using multiyear simulations; and four other measures of different complexity and data requirements, including measures that can be derived from standard model runs and observations. The ACCESS1.3b land–atmosphere coupling strength is comparable to other climate models. The coupling strength in the Southern Hemisphere summer is larger compared to the Northern Hemisphere summer and is dominated by a strong signal in the tropics and subtropics. The land–atmosphere coupling measures agree on the location of very strong land–atmosphere coupling but show differences in the spatial extent of these regions. However, the investigated measures show disagreement in weaker coupled regions, and some regions are only identified by a single measure as strongly coupled. In future projections the soil moisture trend is crucial in generating regions of strong land–atmosphere coupling, and the results suggest an expansion of coupling “hot spots.” It is concluded that great care needs to be taken in using different measures of coupling strength and shown that several measures that can be easily derived lead to inconsistent conclusions with more computationally expensive measures designed to measure coupling strength.

Corresponding author address: Ruth Lorenz, ARC Centre of Excellence for Climate System Science, University of New South Wales, Level 4, Mathews Building, Sydney NSW 2052, Australia. E-mail: r.lorenz@unsw.edu.au
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