On the Measurement of Dewfall and Fog-Droplet Deposition

Abstract

An observational study has been conducted concerning atmospheric dewfall and fog-droplet deposition with application to the formation and maintenance of fog layers. The relationship between dew and fog is discussed together with the challenges and requirements to measure representative values of their deposition to the surface. A practical instrument developed at the UK Met Office Research Unit, Cardington, is described. The instrument is a small portable device that uses a load cell to measure the weight of a pan upon which various types of natural and artificial canopies can be placed, and can measure dewfall and fog-droplet deposition to an accuracy of 0.0005 mm. Dewfall results from this device are shown for a selection of nights under varying conditions. On a given night the overriding factor determining the amount of dew deposition appears to be location. Several dewmeter devices were placed at different locations around the 18 ha Cardington field site for various clear nights and it was found that dew amounts varied significantly, depending on location: canopies with a more open aspect experienced more deposition by up to a factor of two. The results also suggest that the hygroscopic effect of a canopy, whereby water is absorbed into the canopy and topsoil layer before dew formation begins, is also important for the removal of atmospheric water vapour. Results indicate this effect can be of a similar magnitude to dew deposition. Measurements of fog-droplet deposition showed total water deposition rates did not change when thin radiation fog formed. When optically thick adiabatic fog formed, deposition rates were seen to decrease with time or be generally lower than for thinner radiation fog. Further observations are required to establish if the behaviours found are typical for all fogs.

Appendix 1

This section discusses the calculation of canopy longwave emissivity. This is measured using an aluminium cone with a polished inner face (and thus very low emissivity of $\approx$0.03). The narrow end of the cone has a small aperture and mounting for a Heitronics KT19.85 II infra-red thermometer (IRT, 9.6–11.5 $\upmu$m wavelength sensitivity). The wide aperture is open and is placed over the canopy of interest and the IRT measures the radiance emitted. The IRT assumes an emissivity of 1 and returns calculated temperature. Placing this cone over a surface with high emissivity (0.95 or more) gives the surface an effective emissivity of close to 1 (J Taylor, Met Office, personal communication, 2010). The black-body emissivity is then calculated using Planck’s law,

$$\begin{aligned} B_\lambda =\frac{2hc^{2}\lambda ^{-5}}{\exp \left( {\dfrac{hc}{\lambda kT}} \right) -1}, \end{aligned}$$

(5)

where $B_{\lambda }$ is the emitted radiance at temperature $T$, and $h,c,k,\lambda$ are the Planck function, speed of light, Boltzmann constant and wavelength of light under consideration respectively. For an object emitting and reflecting radiation at a wavelength, $\lambda$, we have,

$$\begin{aligned} R_\mathrm{m} =\varepsilon B_{\lambda T_\mathrm{o}} +\left( {1-\varepsilon }\right) B_{\lambda T_\mathrm{r}}. \end{aligned}$$

(6)

The first term on the right-hand side is the emitted radiation from the canopy and the second term is the reflected component; $\varepsilon$ is the emissivity. In practice, $T_\mathrm{o}$ and $T_\mathrm{r}$ are the canopy skin and sky temperatures respectively. Therefore the IRT may be used with the aluminium cone to measure $T_\mathrm{o}$ and the radiance in the first term of Eq. 6 estimated using Eq. 5. $R_\mathrm{m}$ is measured by removing the IRT from the cone and measuring the canopy temperature from a height of approximately 500–600 mm, then using Eq. 5. Finally, the sky radiance is estimated by pointing the IRT at the sky, measuring $T_\mathrm{r}$, and using Eq. 5 to estimate the radiance for the second term in Eq. 6; Eq. 6 can then be solved for the emissivity. Whilst making these measurements, it became apparent that atmospheric conditions were critical to the success of the calculation. Strong sunlight, any wind, or variable cloud cover usually resulted in poor calculations (standard deviations calculated for $\varepsilon$ were very large with values of $\varepsilon > 1$). However, measurements made at dawn under low light, no wind and clear sky were found to produce acceptable results.

The emissivity calculated from an infra-red device may be corrected in the following way. Firstly, the measured radiance $R_\mathrm{m}$ is determined using Eq. 5, then $B_{\lambda T_\mathrm{o}}$ is calculated using Eq. 6 with known emissivity. In this instance, the sky radiance is not known, but may be estimated based on a sky temperature of $-$60 $^{\circ }$C. (This was a typical measured value during some of the clear-night trials.)

Given the second term in Eq. 6 is small, and $\varepsilon$ near 1 in most instances, this only introduces a small error. For the RSDD canopy, and using the data shown in Fig. 9, altering sky temperature by $\pm$20 $^{\circ }$C from the value used above yields an average change in calculated temperature of 0.16 $^{\circ }$C. In practice, the radiometer accuracy of $\approx$1 $^{\circ }$C is the greater error. Finally, the correct temperature may be calculated by re-arranging Eq. 5,

$$\begin{aligned} T=\frac{hc}{\lambda k}\left[ {\ln \left( {\frac{2hc^{2}\lambda ^{-5}}{B_{\lambda T_{o}} }+1} \right) } \right] ^{-1}. \end{aligned}$$

(7)