There is a concern that the low level cool and moist biases (Bao and Zhang 2013) of EraInt data may affect the identification of surface stable layers, especially where surface and upper equivalent potential temperatures are close in value. Colman(1990a) and Horgan et. al. 2007 found U.S. ES occurred above shallow strong surface inversions. If Australian ES similarly occurred over strong surface inversions, and if EraInt vertical resolution is sufficient to capture strong surface inversions, the EraInt surface to upper θe values would be well separated, thus surface stable layer identification using EraInt and its dry bias may not be affected. Any temperature or moisture biases may also affect thermodynamic quantity values used in ES discriminators such as θe or MUCAPE. Figure 2 shows observed temperature and dewpoint temperature profiles compared to EraInt temperature and dewpoint temperature for one year (2013) at both Melbourne Airport (00 and 12UTC soundings, number of soundings n= 720 ) and Giles Airport (only 00UTC soundings available, n=360 ). The EraInt dewpoint temperature was calculated from the temperature and relative humidity values that were linearly interpolated to the observed sounding location using Equation 8 in Lawrence (2005). The equation gives small approximation errors for temperatures between -40oC < T < 50oC and 1% < RH < 100%, where T is the temperature in oC. Comparisons to observed soundings at 00 UTC for Giles Airport confirms the EraInt low-level dry bias found in Bao and Zhang (2013). EraInt θe or MUCAPE values may therefore be underestimated. Moist biases at Melbourne Airport for both 00UTC (and 12UTC – not shown) could be due to the southern grid points of used in the horizontal interpolation being located over the ocean. Large standard deviations seen in all plots could simply be due to EraInt moist, dry, warm and or cool layers not in EraInt soundings not matching exactly in the vertical when compared to observed soundings.