Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog

Bergot, Thierry; Terradellas, Enric; Cuxart, Joan; Mira, Antoni; Liechti, Olivier; Müller, Mathias; Nielsen, Niels

doi:10.1175/jam2475.1

Cited by 97 publications

(78 citation statements)

References 20 publications

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“…The boundary-layer 1D model COBEL has been coupled with another land-surface scheme: NOAH (Chen et al, 1997;Müller et al, 2005). A 1D model intercomparison for the forecasting of fog events (Bergot et al, 2006) showed that COBEL-ISBA and COBEL-NOAH behaved differently. This confirms the impact of the land-surface scheme on the forecast of low-visibility conditions.…”

Section: Simulations With No Mast: Nomastmentioning

confidence: 99%

Assessing the impact of observations on a local numerical fog prediction system

Rémy¹,

Bergot²

2009

Quart J Royal Meteoro Soc

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ABSTRACT:As poor visibility conditions have great influence on air traffic, a need exists for accurate, updated fog and low-cloud forecasts. COBEL-ISBA, a boundary-layer one-dimensional numerical model, has been developed for the very short-term forecasting of fog and low clouds. This forecasting system assimilates the information from a local observation system designed to provide details on the state of the surface boundary layer, as well as that of the fog and low-cloud layers. This article aims to assess the influence of each component of the observation system on the initial conditions and lowvisibility forecasts. The objective is to obtain a quantitative assessment of the impact on numerical fog forecasts of using a reduced (for smaller-sized airports) or enhanced (using a sodar) set of observations. We first used simulated observations, and focused on modelling the atmosphere before fog formation and then on simulating the life-cycle of fog and low clouds. Within this framework, we also estimated the impact of using a sodar to estimate the thickness of the cloud layer. We showed that the radiative flux observations were the most important of all in cloudy conditions, and that the measurement mast did not have to be higher than 10 m. Using either a sodar or radiative flux to estimate the optical thickness of a cloud layer gave the same scores. Using both of them together did not significantly improve the forecast. Simulations with real observations over a winter of simulations confirmed these findings.

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Section: Simulations With No Mast: Nomastmentioning

confidence: 99%

Assessing the impact of observations on a local numerical fog prediction system

Rémy¹,

Bergot²

2009

Quart J Royal Meteoro Soc

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“…Many important features of fog have also been characterized using one-dimensional (1-D) modelling (Bergot et al, 2007;Tardif, 2007;Stolaki et al, 2015). However, to study some aspects of the characteristics of a fog layer, it has become necessary to explicitly simulate turbulent motion in 3-D as shown by Nakanishi (2000), who was the first to use a large eddy simulation (LES) for fog.…”

Section: Introductionmentioning

confidence: 99%

Large eddy simulation of radiation fog: impact of dynamics on the fog life cycle

et al. 2017

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Abstract. Large eddy simulations (LESs) of a radiation fog event occurring during the ParisFog experiment are studied with a view to analyse the impact of the dynamics of the boundary layer on the fog life cycle. The LES, performed with the Meso-NH model at 5 m resolution horizontally and 1 m vertically, and with a 2-moment microphysical scheme, includes the drag effect of a tree barrier and the deposition of droplets on vegetation. The model shows good agreement with measurements of near-surface dynamic and thermodynamic parameters and liquid water path. The blocking effect of the trees induces elevated fog formation, as actually observed, and horizontal heterogeneities during the formation. It also limits cooling and cloud water production. Deposition is found to exert the most significant impact on fog prediction as it not only erodes the fog near the surface but also modifies the fog life cycle and induces vertical heterogeneities. A comparison with the 2 m horizontal resolution simulation reveals small differences, meaning that grid convergence is achieved. Conversely, increasing numerical diffusion through a wind advection operator of lower order leads to an increase in the liquid water path and has a very similar effect to removing the tree barrier. This study allows us to establish the major dynamical ingredients needed to accurately represent the fog life cycle at very high-resolution.

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“…G. Waersted et al: Radiation in fog (Bergot et al, 2007;Steeneveld et al, 2015). Fog is difficult to model with numerical weather forecast models because of its local nature and the subtle balance between the physical processes that govern its life cycle, which must be parameterised in the models (Steeneveld et al, 2015).…”

mentioning

confidence: 99%

Radiation in fog: quantification of the impact on fog liquid water based on ground-based remote sensing

Wærsted¹,

Haeffelin

Dupont

et al. 2017

Atmos. Chem. Phys.

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Abstract. Radiative cooling and heating impact the liquid water balance of fog and therefore play an important role in determining their persistence or dissipation. We demonstrate that a quantitative analysis of the radiation-driven condensation and evaporation is possible in real time using groundbased remote sensing observations (cloud radar, ceilometer, microwave radiometer). Seven continental fog events in midlatitude winter are studied, and the radiative processes are further explored through sensitivity studies. The longwave (LW) radiative cooling of the fog is able to produce 40-70 g m −2 h −1 of liquid water by condensation when the fog liquid water path exceeds 30 g m −2 and there are no clouds above the fog, which corresponds to renewing the fog water in 0.5-2 h. The variability is related to fog temperature and atmospheric humidity, with warmer fog below a drier atmosphere producing more liquid water. The appearance of a cloud layer above the fog strongly reduces the LW cooling relative to a situation with no cloud above; the effect is strongest for a low cloud, when the reduction can reach 100 %. Consequently, the appearance of clouds above will perturb the liquid water balance in the fog and may therefore induce fog dissipation. Shortwave (SW) radiative heating by absorption by fog droplets is smaller than the LW cooling, but it can contribute significantly, inducing 10-15 g m −2 h −1 of evaporation in thick fog at (winter) midday. The absorption of SW radiation by unactivated aerosols inside the fog is likely less than 30 % of the SW absorption by the water droplets, in most cases. However, the aerosols may contribute more significantly if the air mass contains a high concentration of absorbing aerosols. The absorbed radiation at the surface can reach 40-120 W m −2 during the daytime depending on the fog thickness. As in situ measurements indicate that 20-40 % of this energy is transferred to the fog as sensible heat, this surface absorption can contribute significantly to heating and evaporation of the fog, up to 30 g m −2 h −1 for thin fog, even without correcting for the typical underestimation of turbulent heat fluxes by the eddy covariance method. Since the radiative processes depend mainly on the profiles of temperature, humidity and clouds, the results of this paper are not site specific and can be generalised to fog under different dynamic conditions and formation mechanisms, and the methodology should be applicable to warmer and moister climates as well. The retrieval of approximate emissivity of clouds above fog from cloud radar should be further developed.

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Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog

Cited by 97 publications

References 20 publications

Assessing the impact of observations on a local numerical fog prediction system

Assessing the impact of observations on a local numerical fog prediction system

Large eddy simulation of radiation fog: impact of dynamics on the fog life cycle

Radiation in fog: quantification of the impact on fog liquid water based on ground-based remote sensing

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