Experiments on wind-driven heat exchange processes over melting snow

Snowmelt runoff predictions in alpine catchments are challenging because of the high spatial variability of the snow cover driven by various snow accumulation and ablation processes. In spring, the coexistence of bare and snow-covered ground engages a number of processes such as the enhanced lateral advection of heat over partial snow cover, the development of internal boundary layers, and atmospheric decoupling effects due to increasing stability at the snow cover. The interdependency of atmospheric conditions, topographic settings and snow coverage remains a challenge to accurately account for these processes in snow melt models. In this experimental study, we used an Infrared Camera (VarioCam) pointing at thin synthetic projection screens with negligible heat capacity. Using the surface temperature of the screen as a proxy for the air temperature, we obtained a two-dimensional instantaneous measurement. Screens were installed across the transition between snow-free and snow-covered areas. With IR-measurements taken at 10Hz, we capture the dynamics of turbulent temperature fluctuations over the patchy snow cover at high spatial and temporal resolution. From this data we were able to obtain high-frequency, two-dimensional windfield estimations adjacent to the surface.Preliminary results show the formation of a stable internal boundary layer (SIBL), which was temporally highly variable. Our data suggest that the SIBL height is very shallow and strongly sensitive to the mean near-surface wind speed. Only strong gusts were capable of penetrating through this SIBL leading to an enhanced energy input to the snow surface.With these type of results from our experiments and further measurements this spring we aim to better understand small scale energy transfer processes over patch snow cover and it&#8217;s dependency on the atmospheric conditions, enabling to improve parameterizations of these processes in coarser-resolution snow melt models.

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Global carbon and water exchange during drought reflects adaptation of rooting depth to climate and topography

10.5194/egusphere-egu21-6376 ◽

2021 ◽

Author(s):

Benjamin Stocker ◽

Shersingh Tumber-Davila ◽

Alexandra Konings ◽

Rob Jackson

Keyword(s):

Remote Sensing ◽

Snow Accumulation ◽

Rooting Depth ◽

Small Scale ◽

Observation Data ◽

Systematic Bias ◽

Thermal Infrared Remote Sensing ◽

Near Surface ◽

Rooting Zone ◽

Zone Water

The rooting zone water storage capacity (S) defines the total amount of water available to plants for transpiration during rain-free periods. Thereby, S determines the sensitivity of carbon and water exchanges between the land surface and the atmosphere, controls the sensitivity of ecosystem functioning to progressive drought conditions, and mediates feedbacks between soil moisture and near-surface air temperatures. While being a central quantity for water-carbon-climate coupling, S is inherently difficult to observe. Notwithstanding scarcity of observations, terrestrial biosphere and Earth system models rely on the specification of S either directly or indirectly through assuming plant rooting depth.Here, we model S based on the assumption that plants size their rooting depth to maintain function under the expected maximum cumulative water deficit (CWD), occurring with a return period of 40 years (CWDX40), following Gao et al. (2014). CWDX40 is &#8220;translated&#8221; into a rooting depth by accounting for the soil texture. CWD is defined as the cumulative evapotranspiration (ET) minus precipitation, where ET is estimated based on thermal infrared remote sensing (ALEXI-ET), and precipitation is from WATCH-WFDEI, modified by accounting for snow accumulation and melt. In contrast to other satellite remote sensing-based ET products, ALEXI-ET makes no a priori assumption about S and, as our evaluation shows, exhibits no systematic bias with increasing CWD. It thus provides a robust observation of surface water loss and enables estimation of S with global coverage at 0.05&#176; (~5 km) resolution.Modelled S and its variations across biomes is largely consistent with observed rooting depth, provided as ecosystem-level maximum estimates by Schenk et al. (2002), and a recently compiled comprehensive plant-level dataset. In spite of the general agreement of modelled and observed rooting depth across large climatic gradients, comparisons between local observations and global model predictions are mired by a scale mismatch that is particularly relevant for plant rooting depth, for which the small-scale topographical setting and hydrological conditions, in particular the water table depth, pose strong controls.To resolve this limitation, we investigate the sensitivity of photosynthesis (estimated by sun-induced fluorescence, SIF), and of the evaporative fraction (EF, defined as ET over net radiation) to CWD. By employing first principles for the constraint of rooting zone water availability on ET and photosynthesis, it can be derived how their sensitivity to the increasing CWD relates to S. We make use of this relationship to provide an alternative and independent estimate of S (SdSIF and SdEF), informed by Earth observation data, to which S, modelled using CWDX40, can be compared. Our comparison reveals a strong correlation (R2=0.54) and tight consistency in magnitude between the two approaches for estimating S.&#160;Our analysis suggests adaptation of plant structure to prevailing climatic conditions and drought regimes across the globe and at catchment scale and demonstrates its implications for land-atmosphere exchange. Our global high-resolution mapping of S reveals contrasts between plant growth forms (grasslands vs. forests) and a discrepant importance across the landscape of plants&#8217; access to water stored at depth, and enables an observation-informed specification of S in global models.

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Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

Journal of Hydrology and Hydromechanics ◽

10.1515/johh-2016-0038 ◽

2016 ◽

Vol 64 (4) ◽

pp. 316-328 ◽

Cited By ~ 5

Author(s):

Pavel Krajčí ◽

Michal Danko ◽

Jozef Hlavčo ◽

Zdeněk Kostka ◽

Ladislav Holko

Keyword(s):

Spatial Variability ◽

Snow Cover ◽

Air Temperature ◽

Snow Water Equivalent ◽

Flood Forecasting ◽

Snow Accumulation ◽

Small Scale ◽

Climatic Data ◽

Tatra Mountains ◽

Snow Water

AbstractSnow accumulation and melt are highly variable. Therefore, correct modeling of spatial variability of the snowmelt, timing and magnitude of catchment runoff still represents a challenge in mountain catchments for flood forecasting. The article presents the setup and results of detailed field measurements of snow related characteristics in a mountain microcatchment (area 59 000 m2, mean altitude 1509 m a. s. l.) in the Western Tatra Mountains, Slovakia obtained in winter 2015. Snow water equivalent (SWE) measurements at 27 points documented a very large spatial variability through the entire winter. For instance, range of the SWE values exceeded 500 mm at the end of the accumulation period (March 2015). Simple snow lysimeters indicated that variability of snowmelt and discharge measured at the catchment outlet corresponded well with the rise of air temperature above 0°C. Temperature measurements at soil surface were used to identify the snow cover duration at particular points. Snow melt duration was related to spatial distribution of snow cover and spatial patterns of snow radiation. Obtained data together with standard climatic data (precipitation and air temperature) were used to calibrate and validate the spatially distributed hydrological model MIKE-SHE. The spatial redistribution of input precipitation seems to be important for modeling even on such a small scale. Acceptable simulation of snow water equivalents and snow duration does not guarantee correct simulation of peakflow at short-time (hourly) scale required for example in flood forecasting. Temporal variability of the stream discharge during the snowmelt period was simulated correctly, but the simulated discharge was overestimated.

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Geostatistical FDEM inversion: a three-dimensional real case application

10.5194/egusphere-egu21-16130 ◽

2021 ◽

Author(s):

Leonardo Azevedo ◽

João Narciso ◽

Ellen Van De Vijver

Keyword(s):

Spatial Distribution ◽

Physical Properties ◽

Three Dimensional ◽

Real Case ◽

Small Scale ◽

Inversion Method ◽

Two Dimensional ◽

Data Set ◽

Near Surface ◽

Direct Observations

The near surface is a complex and often highly heterogeneous system as its current status results from interacting processes of both natural and anthropogenic origin. Effective sustainable management and land use planning, especially in urban environments, demands high-resolution subsurface property models enabling to capture small-scale processes of interest. The modelling methods based only on discrete direct observations from conventional invasive sampling techniques have limitations with respect to capturing the spatial variability of these systems. Near-surface geophysical surveys are emerging as powerful techniques to provide indirect measurements of subsurface properties. Their integration with direct observations has the potential for better predicting the spatial distribution of the subsurface physical properties of interest and capture the heterogeneities of the near-surface systems.Within the most common geophysical techniques, frequency-domain electromagnetic (FDEM) induction methods have demonstrated their potential and efficiency to characterize heterogeneous deposits due to their simultaneous sensitivity to electrical conductivity (EC) and magnetic susceptibility (MS). The inverse modelling of FDEM data based on geostatistical techniques allows to go beyond conventional analyses of FDEM data. This geostatistical FDEM inversion method uses stochastic sequential simulation and co-simulation to perturbate the model parameter space and the corresponding FDEM forward model solutions, including both the synthetic FDEM responses and their sensitivity to changes on the physical properties of interest. A stochastic optimization driven by the misfit between true and synthetic FDEM data is applied to iterative towards a final subsurface model. This method not only improve the confidence of the obtained EC and MS inverted models but also allows to quantify the uncertainty related to them. Furthermore, taking into account spatial correlations enables more accurate prediction of the spatial distribution of subsurface properties and a more realistic reconstruction of small-scale spatial variations, even when considering highly heterogeneous near surface systems. Moreover, a main advantage of this iterative geostatistical FDEM inversion method is its ability to flexibly integrate data with different resolution in the same framework.In this work, we apply this iterative geostatistical FDEM inversion technique, which has already been successfully demonstrated for one- and two-dimensional applications, to invert a real case FDEM data set in three dimensions. The FDEM survey data set was collected on a site located near Knowlton (Dorset, UK), which is geologically characterized by Cretaceous chalk overlain by Quaternary siliciclastic sand deposits. The subsurface at the site is known to contain several archaeological features, which produces strong local in-phase anomalies in the FDEM survey data. We discuss the particular challenges involved in the three-dimensional application of the inversion method to a real case data set and compare our results against previously obtained ones for one- and two-dimensional approximations.

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The Importance of Near-Surface Winter Precipitation Processes in Complex Alpine Terrain

Journal of Hydrometeorology ◽

10.1175/jhm-d-18-0055.1 ◽

2019 ◽

Vol 20 (2) ◽

pp. 177-196 ◽

Cited By ~ 7

Author(s):

Franziska Gerber ◽

Rebecca Mott ◽

Michael Lehning

Keyword(s):

Winter Precipitation ◽

Snow Accumulation ◽

Windward Side ◽

Leeward Side ◽

Small Scale ◽

Orographic Precipitation ◽

Near Surface ◽

Simulated Precipitation ◽

Snow Precipitation ◽

Precipitation Enhancement

Abstract In this study, near-surface snow and graupel dynamics from formation to deposition are analyzed using WRF in a large-eddy configuration. The results reveal that a horizontal grid spacing of ≤50 m is required to resolve local orographic precipitation enhancement, leeside flow separation, and thereby preferential deposition. At this resolution, precipitation patterns across mountain ridges show a high temporal and spatial variability. Simulated and observed event-mean snow precipitation across three mountain ridges in the upper Dischma valley (Davos, Switzerland) for two precipitation events show distinct patterns, which are in agreement with theoretical concepts, such as small-scale orographic precipitation enhancement or preferential deposition. We found for our case study that overall terrain–flow–precipitation interactions increase snow accumulation on the leeward side of mountain ridges by approximately 26%–28% with respect to snow accumulation on the windward side of the ridge. Cloud dynamics and mean advection may locally increase precipitation on the leeward side of the ridge by up to about 20% with respect to event-mean precipitation across a mountain ridge. Analogously, near-surface particle–flow interactions, that is, preferential deposition, may locally enhance leeward snow precipitation on the order of 10%. We further found that overall effect and relative importance of terrain–flow–precipitation interactions are strongly dependent on atmospheric humidity and stability. Weak dynamic stability is important for graupel production, which is an essential component of solid winter precipitation. A comparison to smoothed measurements of snow depth change reveals a certain agreement with simulated precipitation across mountain ridges.

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Adaptation of the near-surface wind to the development of sand transport

Journal of Fluid Mechanics ◽

10.1017/s0022112093003684 ◽

1993 ◽

Vol 252 ◽

pp. 99-115 ◽

Cited By ~ 89

Author(s):

Ian K. Mcewan ◽

Brian B. Willetts

Keyword(s):

Boundary Layer ◽

Turbulent Boundary Layer ◽

Surface Wind ◽

Internal Boundary Layer ◽

Internal Boundary ◽

Sand Transport ◽

Temporal Response ◽

Near Surface ◽

Spatial Response ◽

Aerodynamic Roughness

A model of wind-blown sand transport is described with particular emphasis on the feedback between the grain cloud and the near-surface wind. The results from this model are used to develop Owen's (1964) hypothesis that ‘the grain layer behaves, so far as the flow outside it is concerned, as increased aerodynamic roughness whose height is proportional to the thickness of the layer’. The hypothesis is developed to show the influence this dynamic roughness has on the turbulent boundary layer above the saltation layer. Two processes are identified which influence the path of the system towards equilibrium. The first is the feedback between the near-surface wind and the grain cloud in which the quantity of sand transported is limited by the carrying capacity of the wind. The second is due to the temporal development of an internal boundary layer in response to the additional roughness imposed on the flow above the grain layer by the grain cloud. A similarity is noted between the temporal response of a turbulent boundary layer to sand transport and the spatial response of a turbulent boundary layer downstream of a step increase in surface roughness. Finally it is noted that the work may have important implications for transport rate prediction in unsteady winds.

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Salinity variability in satellite subpixels: impact on satellite in-situ comparisons.

10.5194/egusphere-egu21-1205 ◽

2021 ◽

Author(s):

Clovis Thouvenin-Masson ◽

Jacqueline Boutin ◽

Jean-Luc Vergely ◽

Dimitry Khvorostyanov ◽

Xavier Perrot ◽

...

Keyword(s):

Sampling Error ◽

In Situ Measurements ◽

Global Ocean ◽

Small Scale ◽

Two Dimensional ◽

Surface Salinity ◽

Near Surface ◽

One Dimensional ◽

Ship Tracks

Sea Surface Salinity (SSS) are retrieved from SMOS and SMAP L-band radiometers at a spatial resolution of about 50km.&#160;Traditionally, satellite SSS products validation is based on comparisons with in-situ near surface salinity measurements.&#160;In-situ measurements are performed on moorings, argo floats and along ship tracks[JB1]&#160;, which provide punctual or one-dimensional (along ship tracks) estimations of the SSS.&#160;The sampling difference between one-dimensional or punctual in-situ measurements and two-dimensional satellite products results in a sampling error that must be separated from measurement errors for the validation of satellite products.&#160;We use a small-scale resolution field (1/12&#176; Mercator Global Ocean Physics Analysis and Forecast) to estimate the expected sampling error of each kind of in-situ measurements, by comparing punctual, [JB2]&#160;one-dimensional and two-dimensional SSS variability.&#160;The better understanding of sampling errors allows a more accurate validation of satellite SSS and of the errors estimated by satellite retrieval algorithms. The improvement is quantified by considering the standard deviation of satellite minus in-situ salinities differences normalized by the sampling and retrieval errors. This quantity should be equal to one if all the error contributions are correctly considered. This methodology will be applied to SMOS SSS and to merged SMOS and SMAP SSS products.

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Detailed simulations of snow properties and accumulation across the Antarctic Ice Sheet

10.5194/egusphere-egu2020-10368 ◽

2020 ◽

Author(s):

Jan Lenaerts ◽

Eric Keenan ◽

Nander Wever ◽

Marissa Dattler ◽

Carleen Reijmer ◽

...

Keyword(s):

Mass Balance ◽

Ice Sheet ◽

Snow Accumulation ◽

Small Scale ◽

Blowing Snow ◽

Antarctic Ice Sheet ◽

Near Surface ◽

Surface Mass ◽

Order Of Magnitude ◽

Snow Model

Surface mass balance (SMB) represents a large uncertainty in characterizing Antarctic Ice Sheet (AIS) mass balance. Atmospheric reanalysis products, which are commonly used for AIS SMB studies, do not include small-scale snow redistribution processes even though these can be of the same order of magnitude as snow accumulation in many parts of the AIS. Therefore, a proper representation of these processes is critical to interpret local SMB and firn observations, such as from ICESat-2 repeat altimetry. In this study, we use a detailed, multi-layer snow model (SNOWPACK) forced by a global atmospheric reanalysis (MERRA-2). Firstly, we show that a new accumulation scheme, designed to better represent wind-driven snow compaction in SNOWPACK, substantially reduces simulated biases in near-surface snow density at 131 locations across the AIS. Next, we employ a distributed version of SNOWPACK to two regions on the AIS, and compare the simulation output to airborne radar and in-situ observations of SMB. Our results demonstrate that SNOWPACK can capture the timing of blowing snow events, snow erosion events, as well as observed kilometer-scale spatial SMB variability. This study illustrates the importance of using high-resolution SMB models when converting surface height (volume) observations to mass changes.

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Horizontal Vortex Tubes near a Simulated Tornado: Three-Dimensional Structure and Kinematics

Atmosphere ◽

10.3390/atmos10110716 ◽

2019 ◽

Vol 10 (11) ◽

pp. 716 ◽

Cited By ~ 1

Author(s):

Oliveira ◽

Xue ◽

Roberts ◽

Wicker ◽

Yussouf

Keyword(s):

Wide Spectrum ◽

Surface Wind ◽

3D Structure ◽

Three Dimensional ◽

Surface Friction ◽

Radar Data ◽

Dimensional Structure ◽

Small Scale ◽

Near Surface ◽

Vortex Tubes

Supercell thunderstorms can produce a wide spectrum of vortical structures, ranging from midlevel mesocyclones to small-scale suction vortices within tornadoes. A less documented class of vortices are horizontally-oriented vortex tubes near and/or wrapping about tornadoes, that are observed either visually or in high-resolution Doppler radar data. In this study, an idealized numerical simulation of a tornadic supercell at 100 m grid spacing is used to analyze the three-dimensional (3D) structure and kinematics of horizontal vortices (HVs) that interact with a simulated tornado. Visualizations based on direct volume rendering aided by visual observations of HVs in a real tornado reveal the existence of a complex distribution of 3D vortex tubes surrounding the tornadic flow throughout the simulation. A distinct class of HVs originates in two key regions at the surface: around the base of the tornado and in the rear-flank downdraft (RFD) outflow and are believed to have been generated via surface friction in regions of strong horizontal near-surface wind. HVs around the tornado are produced in the tornado outer circulation and rise abruptly in its periphery, assuming a variety of complex shapes, while HVs to the south-southeast of the tornado, within the RFD outflow, ascend gradually in the updraft.

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Properties of the frequency spectra of the temperature anomalies of ocean surface and near-surface air in a simple stochastic climate model with fluctuating parameters

Известия Российской академии наук Физика атмосферы и океана ◽

10.31857/s0002-351555427-36 ◽

2019 ◽

Vol 55 (4) ◽

pp. 27-36

Author(s):

D. A. Petrov

Keyword(s):

Surface Wind ◽

Sensible Heat Flux ◽

Ocean Surface ◽

Small Scale ◽

Model Parameters ◽

Radiation Balance ◽

Frequency Spectra ◽

Near Surface ◽

Temperature Anomalies ◽

First Case

The frequency properties of the ocean surface temperature anomalies (SST) and near-surface air (SAT) spectra are analyzed on the basis of a simple energy balance model of the climate, taking into account the fluctuations of the radiation balance, the latent and sensible heat flux and the velocity of the near-surface wind in two particular cases when the statistical properties of the model parameters are the white noise (small-scale-mesoscale subintervals) and the combined case when the properties of the synoptic subinterval of this parameters are taken into account in the SAT block. It was found that in the first case, the spectra have no features, and in the second they contain selected frequencies in the synoptic and low- frequency intervals. The dependent of their frequencies on model parameters are analyzed. The properties of standard deviations of SST and SAT are investigated.

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The influence of convective momentum transport and vertical wind shear on the evolution of a cold air outbreak

10.5194/egusphere-egu2020-7076 ◽

2020 ◽

Author(s):

Beatrice Saggiorato ◽

Louise Nuijens ◽

A. Pier Siebesma ◽

Stephan de Roode ◽

Irina Sandu ◽

...

Keyword(s):

Boundary Layer ◽

Wind Shear ◽

Surface Wind ◽

Cloud Layer ◽

Momentum Transport ◽

Small Scale ◽

Near Surface ◽

Cold Air ◽

Cold Air Outbreak ◽

Convective Momentum Transport

To study the influence of convective momentum transport (CMT) on wind, boundary layer and cloud evolution in a marine cold air outbreak (CAO) we use Large-Eddy Simulations subjected to different baroclinicity (wind shear) but similar surface forcing. The simulated domain is large enough ( &#8776;100 &#215; 100 km2) to develop typical mesoscale cellular convective structures. &#160;We find that a maximum friction induced by momentum transport (MT) locates in the cloud layer for an increase of geostrophic wind with height (forward shear, FW) and near the surface for a decrease of wind with height (backward shear, BW). Although the total MT always acts as a friction, the interaction of friction-induced cross-isobaric flow with the Coriolis force can develop super-geostrophic winds near the surface (FW) or in the cloud layer (BW). The contribution of convection to MT is evaluated by decomposing the momentum flux by column water vapor and eddy size, revealing that CMT acts to accelerate sub-cloud layer winds under FW shear and that mesoscale circulations contribute significantly to MT for this horizontal resolution (250 m), even if small scale eddies are non-negligible and likely more important as resolution increases. Under FW shear, a deeper boundary layer and faster cloud transition are simulated, because MT acts to increase surface fluxes and wind shear enhances turbulent mixing across cloud tops. Our results show that the coupling between winds and convection is crucial for a range of problems, from CAO lifetime and cloud transitions to ocean heat loss and near-surface wind variability.

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