Evidence of Strong Flux Underestimation by Bulk Parametrizations During Drifting and Blowing Snow

Sigmund, Armin; Dujardin, Jérôme; Comola, Francesco; Sharma, Varun; Huwald, Hendrik; Melo, Daniela Brito; Hirasawa, Naohiko; Nishimura, Koichi; Lehning, Michael

doi:10.1007/s10546-021-00653-x

Cited by 27 publications

(32 citation statements)

References 51 publications

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“…Based on the fact that saltation snow particles are broken and become spherical balls by continuous collisions with the surface (Sato et al, 2008;Okaze et al, 2018), we considered snowflakes as spherical balls and use equivalent diameter to describe different shapes of snowflakes in the simulation. And this is consistent with the major works in 1) numerical simulation of drifting snow physical process using Eulerian-Lagrangian (Schmidt, 1980;Nemoto and Nishimura, 2004;Groot Zwaaftink et al, 2014;Li et al, 2017;Wang and Huang, 2017;Melo et al, 2022;Sigmund et al, 2022) and 2) site observation in estimating the mass flux and particle size distribution (Guala et al, 2008;Crivelli et al, 2016). Drag force-when particle velocity differs from the fluid velocity, fluid has a drag effect on the particles:…”

Section: Particle Movement Modelsupporting

confidence: 88%

“…Future work, will therefore address these limitations and attempt to include electrostatic forces in a saltation model such as the CRYOS LES (Sharma et al, 2018). A main aspect of this future work should be on dynamically modelling charging of particles and on analysing the influence on total mass flux and sublimation (Sigmund et al, 2022). Overall, this will allow for a better understanding of the momentum/energy transfer near the surface under the effect of the strong electric field in drifting snow, and this can support a theoretical basis for the solving interfere of radiation communication in blizzards.…”

Section: Discussionmentioning

confidence: 99%

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Idealized Study of a Static Electrical Field on Charged Saltating Snow Particles

Huang

et al. 2022

Front. Earth Sci.

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Strong electric fields, with values of tens kV/m near the surface, are observed during drifting and blowing snow events. Charge separation can significantly affect particle motion. Although several investigations attempted to shed light on the mechanisms of charge separation and the resulting electric field structure, few studies paid attention to the effect of electrification on the particle trajectory, which may influence the transport mechanism. In this work, we studied trajectories of individual, charged particles in an idealized static electrical field by solving the equations of motion in a neutral atmospheric boundary layer. The results show that negatively charged particles have a lower saltation height while positively charged particles jump higher as long as friction velocities are small. This effect reverses for higher friction velocities as rebound velocities start to dominate over vertical acceleration. We find regimes, in which charge separation leads to suspension of particles close to the ground. The threshold condition for this saltation-suspension transition is related to the rebound velocity and charge-to-mass ratio of the charged particle. Our study is a first step towards a better understanding on the influence of charge separation on drifting snow and should lead to include this effect in state of the art saltation models.

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Section: Particle Movement Modelsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Idealized Study of a Static Electrical Field on Charged Saltating Snow Particles

Huang

et al. 2022

Front. Earth Sci.

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“…The high snow transport rates are also a result of the relatively low aerodynamic roughness length of sea ice, where z 0 is typically lower for first-year ice (FYI) than for second-or multi-year ice (SYI or MYI) (Weiss et al, 2011). In addition, large parts of the snow mass can be expected to get blown into leads or undergo sublimation (Déry and Yau, 2002;Déry and Tremblay, 2004;Leonard and Maksym, 2011;Liston et al, 2020), which has recently been shown to be underestimated by current models (Sigmund et al, 2022). Besides thermodynamic ice growth at its bottom, snow can directly contribute to ice formation on top of the sea ice as snow ice.…”

Section: Introductionmentioning

confidence: 99%

Snowfall and snow accumulation during the MOSAiC winter and spring seasons

et al. 2022

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Abstract. Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth and density retrievals from a SnowMicroPen and approximately weekly measured snow depths along fixed transect paths. We used the derived SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were also compared with ERA5 reanalysis snowfall rates for the drift track. We found an accumulated snow mass of 38 mm SWE between the end of October 2019 and end of April 2020. The initial SWE over first-year ice relative to second-year ice increased from 50 % to 90 % by end of the investigation period. Further, we found that the Vaisala Present Weather Detector 22, an optical precipitation sensor, and installed on a railing on the top deck of research vessel Polarstern, was least affected by blowing snow and showed good agreements with SWE retrievals along the transect. On the contrary, the OTT Pluvio2 pluviometer and the OTT Parsivel2 laser disdrometer were largely affected by wind and blowing snow, leading to too high measured precipitation rates. These are largely reduced when eliminating drifting snow periods in the comparison. ERA5 reveals good timing of the snowfall events and good agreement with ground measurements with an overestimation tendency. Retrieved snowfall from the ship-based Ka-band ARM zenith radar shows good agreements with SWE of the snow cover and differences comparable to those of ERA5. Based on the results, we suggest the Ka-band radar-derived snowfall as an upper limit and the present weather detector on RV Polarstern as a lower limit of a cumulative snowfall range. Based on these findings, we suggest a cumulative snowfall of 72 to 107 mm and a precipitation mass loss of the snow cover due to erosion and sublimation as between 47 % and 68 %, for the time period between 31 October 2019 and 26 April 2020. Extending this period beyond available snow cover measurements, we suggest a cumulative snowfall of 98–114 mm.

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“…Indeed, Town and Walden (2009) found for measurements at the South Pole station that the bulk approach underestimates the LHF by 40-60 % compared to observations obtained using the direct EC method. Sigmund et al (2022) observed a three times smaller flux using a bulk approach compared to the EC method during a storm period at the Syowa S17 station in East Antarctica. They find a flux underestimation using a bulk approach of 16-20 % with blowing snow turned off in their simulations and even 70-87 % when blowing snow is enabled.…”

Section: Introductionmentioning

confidence: 88%

On the importance of the humidity flux for the surface mass balance in the accumulation zone of the Greenland Ice Sheet

Dietrich

Steen‐Larsen

Wahl

et al. 2023

Preprint

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Abstract. It is highly uncertain how the humidity flux between the snow surface and the atmosphere contributes to the surface mass balance (SMB) of the interior Greenland Ice Sheet (GrIS). Due to sparse observations, evaluations of the simulated humidity flux are limited. Model-based estimates of the humidity flux contribution to the SMB are, therefore, unconstrained and even disagree in magnitude and sign. In this study, we evaluate the regional climate model MAR at the EGRIP (East Greenland Ice-Core Project) site in the accumulation zone of the GrIS. We use a combined dataset of continuous one-level bulk estimates of the humidity flux covering the period 05/2016–08/2019 and direct eddy-covariance humidity flux measurements from all four summer seasons. In summer, we document a bias of too little sublimation (-1.3 W m−2) caused by a cold bias in both air and surface temperature leading to a reduced humidity gradient. In winter, MAR overestimates deposition by about one order of magnitude. This is a consequence of an overestimated temperature gradient in too stable atmospheric conditions compared to observations. Both systematic errors cause a large discrepancy in the annual net humidity flux between the model and observations of -9 mm w. eq. yr−1. Remarkably, the simulated net annual humidity flux contributes positively to the SMB, contrary to observations documenting a net sublimation flux. We correct the systematic errors by applying a simple but effective correction function to the simulated latent heat flux. Using this correction, we find that 5.1 % of the annual mass gain at the EGRIP site sublimates again, and 4.3 % of the total mass gain is deposited vapor from the near-surface air. The estimated net humidity flux contribution to the annual SMB is about -1 % (net sublimation) compared to +5.6 % for the uncorrected simulation. In summer, the corrected MAR simulation shows that deposition accounts for 9.6 % of the total mass gain and that 31 % of the total mass gain at the EGRIP site sublimates again. The net fluxes contribute to -32 % of the summer SMB. These results demonstrate that the humidity flux is a major driver of the summer SMB in the accumulation zone of the GrIS and highlight that even small changes could increase its importance for the annual SMB in a warming climate.

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Evidence of Strong Flux Underestimation by Bulk Parametrizations During Drifting and Blowing Snow

Cited by 27 publications

References 51 publications

Idealized Study of a Static Electrical Field on Charged Saltating Snow Particles

Idealized Study of a Static Electrical Field on Charged Saltating Snow Particles

Snowfall and snow accumulation during the MOSAiC winter and spring seasons

On the importance of the humidity flux for the surface mass balance in the accumulation zone of the Greenland Ice Sheet

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