How important are aerosol–fog interactions for the successful modelling of nocturnal radiation fog?

Poku, Craig; Ross, Andrew; Blyth, Alan; Hill, Adrian A.; Price, J. D.

doi:10.1002/wea.3503

Cited by 24 publications

(38 citation statements)

References 40 publications

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“…Recent studies of IOP 1 have shown that humidity and wind speed in the residual layer control the optical thickening of the fog (Smith et al, 2018), in addition to the hygroscopic growth and the fraction of CCN activated into droplets (Boutle et al, 2018). Over the same case, Poku et al (2019) recently showed, with a two-moment microphysical scheme using a single mode of CCN, that the CCN number concentration has a greater impact on fog water content than the CCN soluble fraction. The LES intercomparison will be helpful to investigate the added value of the two-moment bulk microphysical scheme LIMA using a prognostic and multimodal representation of an aerosol population.…”

Section: Discussionmentioning

confidence: 99%

Fog in heterogeneous environments: the relative importance of local and non‐local processes on radiative‐advective fog formation

Ducongé

Lac

Vié

et al. 2020

Quart J Royal Meteoro Soc

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A 100 m resolution simulation of radiation fog observed during the Local And Non‐local Fog EXperiment (LANFEX) was performed over the Shropshire hills (UK) in order to understand the impact of local circulation on valley fog formation. The model correctly resolves all valleys and their different geometries, their associated dynamical features, and the different fog conditions between the measurement sites. Passage of stratocumulus during the night led to fog dissipation and gave the opportunity to study two fog formation stages. In the narrow valleys, fog formed at the valley floor and non‐local drainage‐flow processes acted to dissipate it. This equilibrium determined the fog optical thickness, which varied within and between valleys. Wider basins were more subject to dense fog conditions (due to local formation) than narrower valleys, where advecting fog events are locally observed through basins overflowing. The largest and most open valley of Jay Barns was impacted by numerous circulations from narrower tributary valleys, and their complex interactions affected fog formation differently between events. The impact of cloud microphysics on the simulated fog is studied by comparing simulations with one‐moment and two‐moment schemes. The use of a two‐moment scheme brings improvements when the prognostic number concentration is used to compute cloud optical properties, meaning that the radiative impact of droplet concentration is greater than its gravitational settling effect.

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Section: Discussionmentioning

confidence: 99%

Fog in heterogeneous environments: the relative importance of local and non‐local processes on radiative‐advective fog formation

Ducongé

Lac

Vié

et al. 2020

Quart J Royal Meteoro Soc

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“…Current operational versions of MetUM use a fixed droplet number of 50 cm −1 from the surface up to 50 m and then taper to an aerosol‐dependent value at 150 m altitude. Other LANFEX studies have focused on fog microphysics (Boutle et al ., 2018; Poku et al ., 2019; Ducongé et al ., 2020). The microphysics scheme used here was evaluated for fog against the LANFEX observations and large‐eddy simulations (Boutle et al ., 2018).…”

Section: Model Observational and Case Study Detailsmentioning

confidence: 99%

“…Deep adiabatic radiation fogs are typically longer‐lived, with a greater potential to persist during the day and thus a greater impact (Price, 2011). The stability transition is sensitive to various conditions, including aerosol concentrations (Boutle et al ., 2018; Poku et al ., 2019), wind speed, and humidity (Smith et al ., 2018).…”

Section: Introductionmentioning

confidence: 99%

Sub‐km scale numerical weather prediction model simulations of radiation fog

Smith

Renfrew

Dorling

et al. 2020

Quart J Royal Meteoro Soc

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The numerical weather prediction (NWP) of fog remains a challenge, with accurate forecasts relying on the representation of many interacting physical processes. The recent Local And Non‐local Fog EXperiment (LANFEX) has generated a detailed observational dataset, creating a unique opportunity to assess the NWP of fog events. We evaluate the performance of operational and research configurations of the Met Office Unified Model (MetUM) with three horizontal grid lengths, 1.5 km and 333 and 100 m, in simulating four LANFEX case studies. In general, the subkilometre (sub‐km) scale versions of MetUM are in better agreement with the observations; however, there are a number of systematic model deficiencies. MetUM produces valleys that are too warm and hills that are too cold, leading to valleys that do not have enough fog and hills that have too much. A large sensitivity to soil temperature was identified from a set of parametrisation sensitivity experiments. In all the case studies, the model erroneously transfers heat too readily through the soil to the surface, preventing fog formation. Sensitivity tests show that the specification of the soil thermal conductivity parametrisation can lead to up to a 5‐hr change in fog onset time. Overall, the sub‐km models demonstrate promise, but they have a high sensitivity to surface properties.

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“…In recent years, several studies have focused on microphysical processes in fog [3,[5][6][7][8][9][10][11][12][13][14]. Since the supersaturation in fog is low and the mean radius of fog droplets is rather small, collision and coalescence is a second order process, but the diffusional growth of the droplet population plays an important role.…”

Section: Introductionmentioning

confidence: 99%

“…Third, bulk schemes, regardless of which parameterization they use, can only represent activation with a non-physical discrete transition between aerosol and cloud droplets. Recent research [9,13,14,[20][21][22] studied the influence of aerosols and microphysics on fog by using more or less advanced Eulerian cloud physic approaches. Moreover, Boutle et al [5], Maalick et al [10], Tonttila et al [23] used sectional models which allows to represent aerosol-fog interactions in a detailed and interactive way.…”

Section: Introductionmentioning

confidence: 99%

Towards a Better Representation of Fog Microphysics in Large-Eddy Simulations Based on an Embedded Lagrangian Cloud Model

Schwenkel

Maronga

2020

Atmosphere

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The development of radiation fog is influenced by multiple physical processes such as radiative cooling and heating, turbulent mixing, and microphysics, which interact on different spatial and temporal scales with one another. Once a fog layer has formed, the number of fog droplets and their size distribution have a particularly large impact on the development of the fog layer due to their feedback on gravitational settling and radiative cooling at the fog top, which are key processes for fog. However, most models do not represent microphysical processes explicitly, or parameterize them rather crudely. In this study we simulate a deep radiation fog case with a coupled large-eddy simulation (LES)–Lagrangian cloud model (LCM) approach for the first time. By simulating several hundred million fog droplets as Lagrangian particles explicitly (using the so-called superdroplet approach), we include a size-resolved diffusional growth including Köhler theory and gravitational sedimentation representation. The results are compared against simulations using a state of the art bulk microphysics model (BCM). We simulate two different aerosol backgrounds (pristine and polluted) with each microphysics scheme. The simulations show that both schemes generally capture the key features of the deep fog event, but also that there are significant differences: the drop size distribution produced by the LCM is broader during the formation and dissipation phase than in the BCM. The LCM simulations suggest that its spectral shape, which is fixed in BCMs, exhibits distinct changes during the fog life cycle, which cannot be taken into account in BCMs. The picture of the overall fog droplet number concentration is twofold: For both aerosol environments, the LCM shows lower concentrations of larger fog droplets, while we observe a higher number of small droplets and swollen aerosols reducing the visibility earlier than in the BCM. As a result of the different model formulation we observe higher sedimentation rates and lower liquid water paths for the LCM. The present work demonstrates that it is possible to simulate fog with the computational demanding approach of LCMs to assess the advantages of high-resolution cloud models and further to estimate errors of traditional parameterizations.

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How important are aerosol–fog interactions for the successful modelling of nocturnal radiation fog?

Cited by 24 publications

References 40 publications

Fog in heterogeneous environments: the relative importance of local and non‐local processes on radiative‐advective fog formation

Fog in heterogeneous environments: the relative importance of local and non‐local processes on radiative‐advective fog formation

Sub‐km scale numerical weather prediction model simulations of radiation fog

Towards a Better Representation of Fog Microphysics in Large-Eddy Simulations Based on an Embedded Lagrangian Cloud Model

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