Large‐eddy simulation of a warm‐air advection episode in the summer Arctic

Sotiropoulou, Georgia; Tjernström, Michael; Savre, Julien; Ekman, Annica M. L.; Hartung, Kerstin; Sedlar, Joseph

doi:10.1002/qj.3316

Cited by 16 publications

(27 citation statements)

References 43 publications

(83 reference statements)

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“…e.g., Pithan et al 2018). Numerical modeling on different scales constitute one way forward, for example single-column or largeeddy modeling at different locations using advection tendencies from reanalysis (e.g., Sotiropoulou et al 2018;Hartung et al 2018), or Lagrangian modeling where a hypothetical atmospheric column is advected along a trajectory over the observed surface conditions (Sotiropoulou 2016;Pithan et al 2014). Modeling needs to be informed by observations, and observation design may also need to consider a Lagrangian framework, as was pioneered in ASTEX (Albrecht et al 1995) but rarely repeated.…”

Section: Discussionmentioning

confidence: 99%

Arctic Summer Airmass Transformation, Surface Inversions, and the Surface Energy Budget

et al. 2019

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2019)Arctic summer airmass transformation, surface inversions, and the surface energy budget. Journal of Climate, 32 (3). pp. 769-789. ABSTRACTDuring the Arctic Clouds in Summer Experiment (ACSE) in summer 2014 a weeklong period of warm-air advection over melting sea ice, with the formation of a strong surface temperature inversion and dense fog, was observed. Based on an analysis of the surface energy budget, we formulated the hypothesis that, because of the airmass transformation, additional surface heating occurs during warm-air intrusions in a zone near the ice edge. To test this hypothesis, we explore all cases with surface inversions occurring during ACSE and then characterize the inversions in detail. We find that they always occur with advection from the south and are associated with subsidence. Analyzing only inversion cases over sea ice, we find two categories: one with increasing moisture in the inversion and one with constant or decreasing moisture with height. During surface inversions with increasing moisture with height, an extra 10-25 W m 22 of surface heating was observed, compared to cases without surface inversions; the surface turbulent heat flux was the largest single term. Cases with less moisture in the inversion were often cloud free and the extra solar radiation plus the turbulent surface heat flux caused by the inversion was roughly balanced by the loss of net longwave radiation.

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Section: Discussionmentioning

confidence: 99%

Arctic Summer Airmass Transformation, Surface Inversions, and the Surface Energy Budget

et al. 2019

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“…Spaceborne measurements over this area indicated a rapid decrease in sea ice concentration, from >90% to ~50%, during the examined event (Figures a and b), while the analysis of the surface energy budget revealed a surplus of 30–40 W/m 2 at maximum (Tjernström et al, ). Later, Sotiropoulou et al () showed that this additional energy flux can be attributed entirely to the clouds, maintained by the advected moisture. The key role of moisture and clouds during warm‐air advection episodes has been documented in previous studies as well (e.g., Kapsch et al, ; Park et al, ), albeit these focused on different seasons.…”

Section: Introductionmentioning

confidence: 99%

Modeling Extreme Warm‐Air Advection in the Arctic: The Role of Microphysical Treatment of Cloud Droplet Concentration

2019

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As the Arctic climate is changing fast, with increasing areas of open water in summer, there is a growing interest in the processes related to the marginal ice zones. Recent studies have indicated that such a critical process may be the advection of warm and moist air from the south. In this study, the performance of the Weather Research and Forecasting (WRF) model is evaluated during an extreme warm advection episode over melting sea ice that occurred near the Arctic ice edge in summer 2014. The model gives a reasonably good representation of the atmospheric conditions and the Arctic boundary layer, characterized by very strong surface inversions and the frequent presence of low‐level jets. However, the representation of the highly variable cloud conditions, from optically thick to optically thin, dissipating clouds, is sensitive to the choice of cloud droplet treatment in WRF. Simulations with relatively high cloud droplet number concentrations (Ndrop ≥ 100 cm−3) are more successful in representing the optically thick cloud state, whereas to reproduce optically thin and tenuous clouds Ndrop should be <50 cm−3. The WRF‐Chem model, with a realistic treatment of the cloud‐aerosol interactions, allows for large variations in Ndrop and hence can reproduce the cloud water properties reasonably well for most of the simulation time. This contributes to an improved representation of the cloud longwave radiative effect, compared to the simulations where a less adaptive treatment of Ndrop is applied.

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“…As illustrated in Figure b, the subsidence profile is linearized between the thermal inversion z i and the surface. This corresponds to assuming a constant large‐scale divergence within that height range, a configuration often applied in LES of low cloud transitions (e.g., Loewe et al, ; Neggers et al, ; Sandu & Stevens, ; Sotiropoulou et al, ). One of the main reasons for adopting it here is that the linearization effectively removes any fingerprints of the parameterized boundary layer in the ECMWF model, which should be resolved by the LES itself.…”

Section: Methodsmentioning

confidence: 99%

“…Typically, LES experiments are based on measurements at fixed sites or during field campaigns, with the simulations being critically interpreted and evaluated (Fridlind et al, ; Klein et al, ; Morrison et al, ; Ovchinnikov et al, ). In recent years LES of mixed‐phase clouds in warm air intrusions is increasingly being pursued and is yielding valuable new insights (Loewe et al, ; Savre & Ekman, ; Savre et al, ; Sotiropoulou et al, ).…”

Section: Introductionmentioning

confidence: 99%

Local and Remote Controls on Arctic Mixed‐Layer Evolution

Neggers

Chylik

Egerer

et al. 2019

J Adv Model Earth Syst

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In this study Lagrangian large-eddy simulation of cloudy mixed layers in evolving warm air masses in the Arctic is constrained by in situ observations from the recent PASCAL field campaign. A key novelty is that time dependence is maintained in the large-scale forcings. An iterative procedure featuring large-eddy simulation on microgrids is explored to calibrate the case setup, inspired by and making use of the typically long memory of Arctic air masses for upstream conditions. The simulated mixed-phase clouds are part of a turbulent mixed layer that is weakly coupled to the surface and is occasionally capped by a shallow humidity layer. All eight simulated mixed layers exhibit a strong time evolution across a range of time scales, including diurnal but also synoptic fingerprints. A few cases experience rapid cloud collapse, coinciding with a rapid decrease in mixed-layer depth. To gain insight, composite budget analyses are performed. In the mixed-layer interior the heat and moisture budgets are dominated by turbulent transport, radiative cooling, and precipitation. However, near the thermal inversion the large-scale vertical advection also contributes significantly, showing a distinct difference between subsidence and upsidence conditions. A bulk mass budget analysis reveals that entrainment deepening behaves almost time-constantly, as long as clouds are present. In contrast, large-scale subsidence fluctuates much more strongly and can both counteract and boost boundary-layer deepening resulting from entrainment. Strong and sudden subsidence events following prolonged deepening periods are found to cause the cloud collapses, associated with a substantial reduction in the surface downward longwave radiative flux.

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Large‐eddy simulation of a warm‐air advection episode in the summer Arctic

Cited by 16 publications

References 43 publications

Arctic Summer Airmass Transformation, Surface Inversions, and the Surface Energy Budget

Arctic Summer Airmass Transformation, Surface Inversions, and the Surface Energy Budget

Modeling Extreme Warm‐Air Advection in the Arctic: The Role of Microphysical Treatment of Cloud Droplet Concentration

Local and Remote Controls on Arctic Mixed‐Layer Evolution

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