The similarity of the temporal variations of land and atmospheric states during the onset (September) through to the peak (February) of the wet season over northern Australia is statistically diagnosed using ensembles of offline land surface model simulations that produce a range of different background soil moisture states. We derive the temporal correspondence between variations in the soil moisture and the planetary boundary layer via a statistical measure of rank correlation. The simulated evaporative fraction and the boundary layer are shown to be strongly correlated during both SON (September–October–November) and DJF (December–January–February) despite the differing background soil moisture states between the two seasons and among the ensemble members. The sign and magnitude of the boundary layer–surface layer soil moisture association during the onset of the wet season (SON) differs from the correlation between the evaporative fraction and boundary layer from the same season, and from the correlation between the surface soil moisture and boundary layer association during DJF. The patterns and magnitude of the surface flux–boundary layer correspondence are not captured when the relationship is diagnosed using the surface layer soil moisture alone. The conflicting results arise because the surface layer soil moisture lacks strong correlation with the atmosphere during the monsoon onset because the evapotranspiration is dominated by transpiration. Our results indicate that accurately diagnosing the correspondence and therefore coupling strength in seasonally dry regions, such as northern Australia, requires root zone soil moisture to be included.
Figure 10. The standard deviation of the Kτ correlation metric among the ensemble members between the afternoon computed LCL and
either the morning root zone soil moisture (SMrz ) over (a) DJF and (b) SON or the morning first layer soil moisture (SM1) over (c) DJF and
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Last updated 29 November 2013