Estimating fog-top height through near-surface micrometeorological measurements

Abstract

Fog-top height (fog thickness) is very useful information for aircraft manoeuvres, data assimilation/validation of Numerical Weather Prediction models or nowcasting of fog dissipation. This variable is usually difficult to determine, since the fog-layer top cannot be observed from the surface. In some cases, satellite data, ground remote-sensing instruments or atmospheric soundings are used to provide approximations of fog-top height. These instruments are expensive and their data not always available. In this work, two different methods for the estimation of fog-top height from field measurements are evaluated from the statistical analysis of several radiation-fog events at two research facilities. Firstly, surface friction velocity and buoyancy flux are here presented as potential indicators of fog thickness, since a linear correlation between fog thickness and surface turbulence is found at both sites. An operational application of this method can provide a continuous estimation of fog-top height with the deployment of a unique sonic anemometer at surface. Secondly, the fog-top height estimation based on the turbulent homogenisation within well-mixed fog (an adiabatic temperature profile) is evaluated. The latter method provides a high percentage of correctly-estimated fog-top heights for well-mixed radiation fog, considering the temperature difference between different levels of the fog. However, it is not valid for shallow fog (∼ less than 50 m depth), since in this case, the weaker turbulence within the fog is not able to erode the surface-based temperature inversion and to homogenise the fog layer. 1 tem (ILS). Most airports have regulatory meteorological 2 instrumentation composed by surface visibilimeters, a 3 ceilometer (measuring cloud base and cloud cover) and 4 standard meteorological instrumentation, but all these 5 data are not enough to provide information about fog-6 top height. 7 Despite the numerous potential applications of this 8 variable, its numerical value is not always clear. Many 9 studies cannot provide information about observed fog-10 top height due to the lack of measurements in the ver-11 tical. In many cases, temperature and humidity data 12 from atmospheric soundings are used to estimate fog 13 thickness (e.g., Koračin et al., 2001; Liu et al., 2011; 14 Boers et al., 2013; Bari et al., 2015). However, these 15 soundings are not always available, or their temporal 16 frequency is not sufficient to cover the whole fog cy-17 cle. In other cases, remote sensing instruments are used 18 to estimate the fog top. Dabas et al. (2012) studied the 19 ability of using reflectivity measurements from sodar to 20 estimate fog-top height, while Boers et al. (2013) de-21 rived visibility from radar reflectivity for a case study of 22 radiation fog. Ceilometers detect cloud-base height of 23 low clouds (e.g., Dupont et al., 2012), but they are not 24 useful to provide information about fog-top height. All 25 these instruments are usually expensive and sometimes 26 their vertical resolution is not a...

Radiation and cloud-base lowering fog events: Observational analysis and evaluation of WRF and HARMONIE

“…The mean temperature difference between 10 and 2 m was low (0.20 • C), associated with relatively high values of turbulence (mean T KE of 0.11 m 2 s -2 ), leading to the observed thick fog. This weak stratification fulfils the expected features of deep fog (Román-Cascón et al, 2016b).…”

“…Many observational and/or modelling studies have focused on this type of fog (e.g., Terradellas et al, 2008;Van der Velde et al, 2010;Bergot, 2013;Price et al, 2018, among many others), but models still have problems simulating it, especially when its formation is not imposed by the local topography (Müller et al, 2010). The characteristics of radiation fogs are variable, from short-lived, not-mixed and shallow fog events of a few meters to persistent, well-mixed and deep events of several hundreds of meters (Duynkerke, 1999;Román-Cascón et al, 2016b). Radiation fog can start its dissipation from the lower layers close to the surface or from the upper ones following different mechanisms, which are normally associated with increases in temperature, wind or turbulence.…”

Radiosonde‐Derived Temperature Inversions and Their Association With Fog Over 37 Melt Seasons in East Greenland

“…In the TCM, fog top is estimated from the height of the capping inversion or from the first layer where the thermal profile is near neutral or unstable. The TCM cannot be applied to shallow fog or fog with a surface‐based inversion and, in addition, requires either high vertical‐resolution or high temporal‐resolution profiles (Román‐Cascón et al, ). Several other techniques have been proposed to retrieve cloud base, top, and thickness from low‐ and high‐resolution radiosonde profiles (e.g., Chernykh & Eskridge, ; Minnis et al, ; Poore et al, ; Wang & Rossow, ; Zhang et al, , ).…”

Understanding and Reducing False Alarms in Observational Fog Prediction

“… 2015 ; Román-Cascón et al. 2016a , b ). In many cases, this is the result of deficiencies in subgrid-scale parametrizations (Steeneveld et al.…”