Response and sensitivity of the nocturnal boundary layer over land to added longwave radiative forcing

R.T. McNider, G.J. Steeneveld, A.A.M. Holtslag, R.A. Pielke sr., S. Mackaro, A. Pour Biazar, J. Walters, U. Nair, J. Christy

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61 Citations (Scopus)


One of the most significant signals in the thermometer-observed temperature record since 1900 is the decrease in the diurnal temperature range over land, largely due to rising of the minimum temperatures. Generally, climate models have not well replicated this change in diurnal temperature range. Thus, the cause for night-time warming in the observed temperatures has been attributed to a variety of external causes. We take an alternative approach to examine the role that the internal dynamics of the stable nocturnal boundary layer (SNBL) may play in affecting the response and sensitivity of minimum temperatures to added downward longwave forcing. As indicated by previous nonlinear analyses of a truncated two-layer equation system, the SNBL can be very sensitive to changes in greenhouse gas forcing, surface roughness, heat capacity, and wind speed. A new single-column model growing out of these nonlinear studies is used to examine the SNBL. Specifically, budget analyses of the model are provided that evaluate the response of the boundary layer to forcing and sensitivity to mixing formulations. Based on these model analyses, it is likely that part of the observed long-term increase in minimum temperature is reflecting a redistribution of heat by changes in turbulence and not by an accumulation of heat in the boundary layer. Because of the sensitivity of the shelter level temperature to parameters and forcing, especially to uncertain turbulence parameterization in the SNBL, there should be caution about the use of minimum temperatures as a diagnostic global warming metric in either observations or models.
Original languageEnglish
Article numberD14106
JournalJournal of Geophysical Research: Atmospheres
Publication statusPublished - 2012


  • diurnal temperature-range
  • global climate model
  • surface-temperature
  • minimum temperature
  • atmospheric models
  • heat-flux
  • intermittent turbulence
  • vertical resolution
  • contrasting nights
  • soil-moisture

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