Errors in Epply PSP measurements

We've seen the well-known problem of negative Epply PSP values at night in the EBEX-2000 data. Just for fun, we've compared these at one site (8) to the dome and case temperatures of an adjacent PIR. The correlation is shown in Figure 1. In this plot, and Figures 3-5, the left panel shows Rsw vs. Tdome^4-Tcase^4 and the right panel shows Rsw vs. just Tdome-Tcase. The red line in the left panel is the fit found by a radiometer used by Bush et al. (see below). The red line in the right panel is an eyeball fit to the EBEX data. A regression of Rsw = 12 (Tdome-Tcase) + 3 fits rather well. I've seen different offsets for different sensors, e.g. 13 (Tdome-Tcase) - 2 for Rsw.out.s8.

To see what this error would be during the day, Figure 2shows this regression function in blue, along with the nighttime Rsw data that it is fitting (black). The daytime error is about 2%, which is rather large, though small compared to the energy balance residual.

Note that this error is not exactly correctable, since we don't have a Tdome and Tcase for the PSPs. There are some studies which have installed temperature sensors on the PSPs (Bush et al., 2000 and Haeffelin, 2000). Bush et al. find that the error is linear in Td^4-Tc^4, and thus directly explained by radiative heat transfer. However, they find that the coefficients must be determined for each radiometer. If a fit to Td-Tc were better than Td^4-Tc^4, Tony suggests that this would indicate heat transfer by convection, conduction and/or diffusion, rather than by radiation.

I've also looked at data from OASIS98 (Figure 3), and 80 days of SHEBA (all nighttime!) (Figure 4). A slope of 13 fits all of these data quite well! For CASES97, the Tdome.down was bad so it can't be used. Rsw.up from CASES97 (Figure 5) doesn't fit the slope of 13 very well -- perhaps different ventillation was used.