scholarly journals Snow albedo sensitivity to macroscopic surface roughness using a new ray tracing model

2019 ◽  
Author(s):  
Fanny Larue ◽  
Ghislain Picard ◽  
Laurent Arnaud ◽  
Inès Ollivier ◽  
Clément Delcourt ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Smooth Surface ◽  
Incident Angle ◽  
The Sun ◽  
Multiple Reflections ◽  
Snow Albedo ◽  
Snow Properties ◽  
Angle Effect ◽  
Effective Angle ◽  
The Impact

Abstract. Most models simulating snow albedo assume a flat and smooth surface, neglecting surface roughness. However, the presence of macroscopic roughness leads to a systematic decrease in albedo due to two effects: 1) photons are trapped in concavities (multiple reflection effect) and, 2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incident angle relative to a smooth surface, promoting higher absorption, whilst the other sides has weak contributions because of the increased incident angle or because they are shadowed (called the effective angle effect here). This paper aims to quantify the impact of surface roughness on albedo and to assess the respective role of these two effects, with 1) observations over varying amounts of surface roughness, and 2) simulations using the new Rough Surface Ray Tracer (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400–1050 nm) over manually-created roughness surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of surface roughness features (7 % of the surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle (Өs) is larger than 50°. For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03–0.04 at 700 nm and of 0.06–0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for surface roughness improves the model observation agreement by a factor two at 700 nm and 1000 nm (errors of 0.03 and 0.04, respectively), compared to simulations considering a flat smooth surface. The model is used to explore the albedo sensitivity to surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective angle effect have more impact with low SSA (

scholarly journals Snow albedo sensitivity to macroscopic surface roughness using a new ray-tracing model

2020 ◽  
Vol 14 (5) ◽  
pp. 1651-1672 ◽  
Author(s):  
Fanny Larue ◽  
Ghislain Picard ◽  
Laurent Arnaud ◽  
Inès Ollivier ◽  
Clément Delcourt ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Ray Tracing ◽  
Smooth Surface ◽  
Incidence Angle ◽  
Surface Energy Budget ◽  
The Sun ◽  
Snow Albedo ◽  
Angle Effect ◽  
Effective Angle ◽  
The Impact

Abstract. Most models simulating snow albedo assume a flat and smooth surface, neglecting surface roughness. However, the presence of macroscopic roughness leads to a systematic decrease in albedo due to two effects: (1) photons are trapped in concavities (multiple reflection effect) and (2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incidence angle relative to a smooth surface, promoting higher absorption, whilst the other sides have weak contributions because of the increased incidence angle or because they are shadowed (called the effective-angle effect here). This paper aims to quantify the impact of surface roughness on albedo and to assess the respective role of these two effects, with (1) observations over varying amounts of surface roughness and (2) simulations using the new rough surface ray-tracing (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400–1050 nm) over manually created roughness surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of surface roughness features (7 % of the surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle (θs) is larger than 50∘. For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03–0.04 at 700 nm and of 0.06–0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for surface roughness improves the model observation agreement by a factor of 2 at 700 and 1000 nm (errors of 0.03 and 0.04, respectively) compared to simulations considering a flat smooth surface. The model is used to explore the albedo sensitivity to surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective-angle effect have a greater impact with low specific surface area (SSA; <10 m2 kg−1). The effective-angle effect also increases rapidly with θs at large θs. This latter effect is larger when the overall slope of the surface is facing away from the sun and has a roughness orientation perpendicular to the sun. For a snowpack where artificial surface roughness features were created, we showed that a broadband albedo decrease of 0.05 may cause an increase in the net shortwave radiation of 80 % (from 15 to 27 W m−2). This paper highlights the necessity of considering surface roughness in the estimation of the surface energy budget and opens the way for considering natural rough surfaces in snow modelling.

scholarly journals The retrieval of snow properties from SLSTR/Sentinel-3 – part 1: method description and sensitivity study

2020 ◽  
Author(s):  
Linlu Mei ◽  
Vladimir Rozanov ◽  
Christine Pohl ◽  
Marco Vountas ◽  
John P. Burrows
Keyword(s):  
Surface Roughness ◽  
Optical Properties ◽  
Particle Shape ◽  
Crystal Surface ◽  
Atmospheric Correction ◽  
Sensitivity Study ◽  
Ice Crystal ◽  
Aerosol Cloud ◽  
Snow Properties ◽  
The Impact

Abstract. The eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm has been applied on the Top-Of-Atmosphere reflectance measured by the Sea and Land Surface Temperature Radiometer (SLSTR) instrument onboard Sentinel-3 to derive snow properties: Snow Grain Size (SGS), Snow Particle Shape (SPS) and Specific Surface Area (SSA) under cloud-free conditions. This is the first part of the paper, to describe the retrieval method and the sensitivity study. Nine pre-defined ice crystal particle shapes (aggregate of 8 columns, Drontal, hollow bullet rosettes, hollow column, plate, aggregate of 5 plates, aggregate of 10 plates, solid bullet rosettes, column) are used to describe the snow optical properties. The optimal SGS and SPS are estimated iteratively utilizing a Look-Up-Table (LUT) approach. The SSA is then calculated using another pre-calculated LUT for the retrieved SGS and SPS. The optical properties (e.g., phase function) of the ice crystals can reproduce the wavelength-dependent/angular-dependent snow reflectance features, compared to laboratory measurements. A comprehensive study to understand the impact of aerosol, ice crystal shape, ice crystal surface roughness, and cloud contamination on the retrieval accuracy of snow properties has been performed based on SCIATRAN radiative transfer simulations. The main findings are (1) Snow angular and spectral reflectance feature can be described by the predefined ice crystal properties only when both SGS and SPS can be optimally and iteratively obtained; (2) The impact of ice crystal surface roughness plays minor effects on the retrieval results; (3) SGS and SSA show an inverse linear relationship; (4) The retrieval of SSA assuming non-convex particle shape, compared to convex particle (e.g. sphere) shows larger results; (5) Aerosol/cloud contamination due to unperfected atmospheric correction and cloud screening introduces underestimation of SGS, inaccurate SPS and overestimation of SSA.

scholarly journals The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study

2021 ◽  
Vol 15 (6) ◽  
pp. 2757-2780
Author(s):  
Linlu Mei ◽  
Vladimir Rozanov ◽  
Christine Pohl ◽  
Marco Vountas ◽  
John P. Burrows
Keyword(s):  
Surface Roughness ◽  
Particle Size ◽  
Optical Properties ◽  
Particle Shape ◽  
Crystal Surface ◽  
Spectral Response ◽  
Sensitivity Study ◽  
Ice Crystal ◽  
Snow Properties ◽  
The Impact

Abstract. The eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm has been designed for the top-of-atmosphere reflectance measured by the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board Sentinel-3 to derive snow properties: snow grain size (SGS), snow particle shape (SPS) and specific surface area (SSA) under cloud-free conditions. This is the first part of the paper, to describe the retrieval method and the sensitivity study. Nine pre-defined SPSs (aggregate of 8 columns, droxtal, hollow bullet rosette, hollow column, plate, aggregate of 5 plates, aggregate of 10 plates, solid bullet rosette, column) are used to describe the snow optical properties. The optimal SGS and SPS are estimated iteratively utilizing a look-up-table (LUT) approach. The SSA is then calculated using another pre-calculated LUT for the retrieved SGS and SPS. The optical properties (e.g., phase function) of the ice crystals can reproduce the wavelength-dependent and angular-dependent snow reflectance features, compared to laboratory measurements. A comprehensive study to understand the impact of aerosols, SPS, ice crystal surface roughness, cloud contamination, instrument spectral response function, the snow habit mixture model and snow vertical inhomogeneity in the retrieval accuracy of snow properties has been performed based on SCIATRAN radiative transfer simulations. The main findings are (1) snow angular and spectral reflectance features can be described by the predefined ice crystal properties only when both SGS and SPS can be optimally and iteratively obtained; (2) the impact of ice crystal surface roughness on the retrieval results is minor; (3) SGS and SSA show an inverse linear relationship; (4) the retrieval of SSA assuming a non-convex particle shape, compared to a convex particle shape (e.g., sphere), shows larger retrieval results; (5) aerosol/cloud contamination due to unperfected atmospheric correction and cloud screening introduces underestimation of SGS, “inaccurate” SPS and overestimation of SSA; (6) the impact of the instrument spectral response function introduces an overestimation into retrieved SGS, introduces an underestimation into retrieved SSA and has no impact on retrieved SPS; and (7) the investigation, by taking an ice crystal particle size distribution and habit mixture into account, reveals that XBAER-retrieved SGS agrees better with the mean size, rather than with the mode size, for a given particle size distribution.

scholarly journals Snow spectral albedo at Summit, Greenland: comparison between in situ measurements and numerical simulations using measured physical and chemical properties of the snowpack

2012 ◽  
Vol 6 (6) ◽  
pp. 5119-5167 ◽  
Author(s):  
C. M. Carmagnola ◽  
F. Domine ◽  
M. Dumont ◽  
P. Wright ◽  
B. Strellis ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Physical Properties ◽  
Chemical Properties ◽  
Physical And Chemical Properties ◽  
Near Surface ◽  
Snow Albedo ◽  
Snow Properties ◽  
Physical And Chemical ◽  
The Impact ◽  
And Chemical Properties

Abstract. The albedo of surface snow is determined both by the near-surface profile of the physical and chemical properties of the snowpack and by the spectral and angular characteristics of the incident solar radiation. Simultaneous measurements of the physical and chemical properties of snow were carried out at Summit Camp, Greenland (72°36´ N, 38°25´ W, 3210 m a.s.l.) in May and June 2011, along with spectral albedo measurements. One of the main objectives of the field campaign was to test our ability to predict snow albedo comparing measured snow spectral albedo to the albedo calculated with a radiative transfer model. To achieve this goal, we made daily measurements of the snow spectral albedo in the range 350–2200 nm and recorded snow stratigraphic information down to roughly 80 cm. The snow specific surface area (SSA) was measured using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement, Gallet et al., 2009). Samples were also collected for chemical analyses including black carbon (BC) and trace elements, to evaluate the impact of light absorbing particulate matter in snow. This is one of the most comprehensive albedo-related data sets combining chemical analysis, snow physical properties and spectral albedo measurements obtained in a polar environment. The surface albedo was calculated from density, SSA, BC and dust profiles using the DISORT model (DIScrete Ordinate Radiative Transfer, Stamnes et al., 1988) and compared to the measured values. Results indicate that the energy absorbed by the snowpack through the whole spectrum considered can be inferred within 1.35%. This accuracy is only slightly better than that which can be obtained considering pure snow, meaning that the impact of impurities on the snow albedo is small at Summit. In the visible region, the discrepancies between measured and simulated albedo are mostly due to the lack of correction of the cosine collector deviation from a true cosine response. In the near-infrared, minor deviations up to 0.014 can be due the accuracy of SSA measurements and to the surface roughness, whereas deviations up to 0.05 can be explained by the vertical resolution of measurements of surface layer physical properties. At 1430 and around 1800 nm the discrepancies are larger and independent of the snow properties; they may be due to the uncertainties in the ice refractive index at these wavelengths. This work contributes to the development of physically-based albedo schemes in detailed snowpack models, and to the improvement of retrieval algorithms for estimating snow properties from remote sensing data.

scholarly journals Impact of light-absorbing particles on snow albedo darkening and associated radiative forcing over High Mountain Asia: High resolution WRF-Chem modeling and new satellite observations

2018 ◽  
Author(s):  
Chandan Sarangi ◽  
Yun Qian ◽  
Karl Rittger ◽  
Kat J. Bormann ◽  
Ying Liu ◽  
...  
Keyword(s):  
Grain Size ◽  
Snow Cover ◽  
Spatial Resolution ◽  
Radiative Forcing ◽  
High Mountain ◽  
Western Himalayas ◽  
Snow Albedo ◽  
Snow Properties ◽  
Realistic Representation ◽  
The Impact

Abstract. Light-absorbing particles (LAPs), mainly dust and black carbon, can significantly impact snowmelt and regional water availability over High Mountain Asia (HMA). In this study, for the first time, online aerosol-snow interactions enabled and a fully coupled chemistry Weather Research and Forecasting (WRF-Chem) regional model is used to simulate LAP-induced radiative forcing on snow surfaces in HMA at relatively high spatial resolution (12 km, WRF-HR) than previous studies. Simulated macro- and micro-physical properties of the snowpack and LAP-induced snow darkening are evaluated against new spatially and temporally complete datasets of snow covered area, grain size, and impurities-induced albedo reduction over HMA. A WRF-Chem quasi-global simulation with the same configuration as WRF-HR but a coarser spatial resolution (1 degree, WRF-CR) is also used to illustrate the impact of spatial resolution on simulations of snow properties and aerosol distribution over HMA. Due to a more realistic representation of terrain slopes over HMA, the higher resolution model (WRF-HR) shows significantly better performance in simulating snow area cover, duration of snow cover, snow albedo and snow grain size over HMA, as well as an evidently better atmospheric aerosol loading and mean LAPs concentration in snow. However, the differences in albedo reduction from model and satellite retrievals is large during winter due to associated overestimation in simulated snow fraction. It is noteworthy that Himalayan snow cover have high magnitudes of LAP-induced snow albedo reduction (4–8 %) in summer (both from WRF-HR and satellite estimates), which, induces a snow-mediated radiative forcing of ∼ 30–50 W/m2. As a result, Himalayas (specifically western Himalayas) hold the most vulnerable glaciers and mountain snowpack to the LAP-induced snow darkening effect within HMA. In summary, coarse spatial resolution and absence of snow-aerosol interactions over Himalaya cryosphere will result in significant underestimation of aerosol effect on snow melting and regional hydroclimate.

scholarly journals Impact of light-absorbing particles on snow albedo darkening and associated radiative forcing over high-mountain Asia: high-resolution WRF-Chem modeling and new satellite observations

2019 ◽  
Vol 19 (10) ◽  
pp. 7105-7128 ◽  
Author(s):  
Chandan Sarangi ◽  
Yun Qian ◽  
Karl Rittger ◽  
Kathryn J. Bormann ◽  
Ying Liu ◽  
...  
Keyword(s):  
Grain Size ◽  
Snow Cover ◽  
Spatial Resolution ◽  
Radiative Forcing ◽  
High Mountain ◽  
Western Himalayas ◽  
Snow Albedo ◽  
Microphysical Properties ◽  
Snow Properties ◽  
The Impact

Abstract. Light-absorbing particles (LAPs), mainly dust and black carbon, can significantly impact snowmelt and regional water availability over high-mountain Asia (HMA). In this study, for the first time, online aerosol–snow interactions are enabled and a fully coupled chemistry Weather Research and Forecasting (WRF-Chem) regional model is used to simulate LAP-induced radiative forcing on snow surfaces in HMA at relatively high spatial resolution (12 km, WRF-HR) compared with previous studies. Simulated macro- and microphysical properties of the snowpack and LAP-induced snow darkening are evaluated against new spatially and temporally complete datasets of snow-covered area, grain size, and impurity-induced albedo reduction over HMA. A WRF-Chem quasi-global simulation with the same configuration as WRF-HR but a coarser spatial resolution (1∘, WRF-CR) is also used to illustrate the impact of spatial resolution on simulations of snow properties and aerosol distribution over HMA. Due to a more realistic representation of terrain slopes over HMA, the higher-resolution model (WRF-HR) shows significantly better performance in simulating snow area cover, duration of snow cover, snow albedo and snow grain size over HMA, as well as an evidently better atmospheric aerosol loading and mean LAP concentration in snow. However, the differences in albedo reduction from model and satellite retrievals is large during winter due to associated overestimation in simulated snow fraction. It is noteworthy that Himalayan snow cover has high magnitudes of LAP-induced snow albedo reduction (4 %–8 %) in pre-monsoon seasons (both from WRF-HR and satellite estimates), which induces a snow-mediated radiative forcing of ∼30–50 W m−2. As a result, the Himalayas (specifically the western Himalayas) hold the most vulnerable glaciers and mountain snowpack to the LAP-induced snow darkening effect within HMA. In summary, coarse spatial resolution and absence of snow–aerosol interactions over the Himalayan cryosphere will result in significant underestimation of aerosol effects on snow melting and regional hydroclimate.

The Impact of Light Polarisation on Light Field of Scenes with Multiple Reflections

2020 ◽  
pp. 108-115 ◽  
Author(s):  
Vladimir P. Budak ◽  
Anton V. Grimaylo
Keyword(s):  
Mathematical Model ◽  
Light Field ◽  
Global Illumination ◽  
Multiple Reflections ◽  
Software Environment ◽  
The Monte Carlo Method ◽  
Mueller Matrices ◽  
Volume Integration ◽  
The Impact

The article describes the role of polarisation in calculation of multiple reflections. A mathematical model of multiple reflections based on the Stokes vector for beam description and Mueller matrices for description of surface properties is presented. On the basis of this model, the global illumination equation is generalised for the polarisation case and is resolved into volume integration. This allows us to obtain an expression for the Monte Carlo method local estimates and to use them for evaluation of light distribution in the scene with consideration of polarisation. The obtained mathematical model was implemented in the software environment using the example of a scene with its surfaces having both diffuse and regular components of reflection. The results presented in the article show that the calculation difference may reach 30 % when polarisation is taken into consideration as compared to standard modelling.

The Homeland, Imprisoned and Illegal: The Impact of Marginalisation on Views of the Homeland in Kanafānī's and Khalīfa's Work

2019 ◽  
Vol 13 (1) ◽  
pp. 1-18
Author(s):  
Jedidiah Anderson
Keyword(s):  
Affect Theory ◽  
The Sun ◽  
Minor Literature ◽  
War Machine ◽  
Ghassan Kanafani ◽  
The Impact

This paper deals with the concept of Al-Waṭan, or ‘the homeland’, in Arabic in The Shell (Al-Qawqʿa) by Muṣṭafā Khalifa and Men in the Sun (Rijāl fīsh-Shams) by Ghassān Kanafānī. Analysis of how alienation from this concept has affected both Khalifa's and Kanafānī's characters is carried out through the lenses of Deleuze and Guattari's theories of rhizomatic associations and minor literature, as well as through the lens of affect theory. The paper also examines parallels between definitions of Al-Waṭan/the homeland in Ibn Manẓūr's classical dictionary Lisān al-ʿArab and Deleuze and Guattari's concepts of the war machine and the apparatus of capture.

scholarly journals Smoothing additive manufactured parts using ns-pulsed laser radiation

2021 ◽  
Author(s):  
Florian Kuisat ◽  
Fernando Lasagni ◽  
Andrés Fabián Lasagni
Keyword(s):  
Surface Roughness ◽  
Mechanical Performance ◽  
State Of The Art ◽  
Pulsed Laser ◽  
Industrial Applications ◽  
Laser Source ◽  
Pulsed Laser Radiation ◽  
Current State ◽  
The Impact

AbstractIt is well known that the surface topography of a part can affect its mechanical performance, which is typical in additive manufacturing. In this context, we report about the surface modification of additive manufactured components made of Titanium 64 (Ti64) and Scalmalloy®, using a pulsed laser, with the aim of reducing their surface roughness. In our experiments, a nanosecond-pulsed infrared laser source with variable pulse durations between 8 and 200 ns was applied. The impact of varying a large number of parameters on the surface quality of the smoothed areas was investigated. The results demonstrated a reduction of surface roughness Sa by more than 80% for Titanium 64 and by 65% for Scalmalloy® samples. This allows to extend the applicability of additive manufactured components beyond the current state of the art and break new ground for the application in various industrial applications such as in aerospace.

Nature instigated Grey wolf algorithm for parametric optimization during machining (Milling) of polymer nanocomposites

2021 ◽  
pp. 089270572199320
Author(s):  
Prakhar Kumar Kharwar ◽  
Rajesh Kumar Verma
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Polymer Nanocomposites ◽  
Feed Rate ◽  
Fitness Function ◽  
Depth Of Cut ◽  
Multiwall Carbon Nanotube ◽  
Grey Wolf ◽  
Milling Characteristics ◽  
The Impact

The new era of engineering society focuses on the utilization of the potential advantage of carbon nanomaterials. The machinability facets of nanocarbon materials are passing through an initial stage. This article emphasizes the machinability evaluation and optimization of Milling performances, namely Surface roughness (Ra), Cutting force (Fc), and Material removal rate (MRR) using a recently developed Grey wolf optimization algorithm (GWOA). The Taguchi theory-based L27 orthogonal array (OA) was employed for the Machining (Milling) of polymer nanocomposites reinforced by Multiwall carbon nanotube (MWCNT). The second-order polynomial equation was intended for the analysis of the model. These mathematical models were used as a fitness function in the GWOA to predict machining performances. The ANOVA outcomes efficiently explore the impact of machine parameters on Milling characteristics. The optimal combination for lower surface roughness value is 1.5 MWCNT wt.%, 1500 rpm of spindle speed, 50 mm/min of feed rate, and 3 mm depth of cut. For lower cutting force, 1.0 wt.%, 1500 rpm, 90 mm/min feed rate and 1 mm depth of cut and the maximize MRR was acquired at 0.5 wt.%, 500 rpm, 150 mm/min feed rate and 3 mm depth of cut. The deviation of the predicted value from the experimental value of Ra, Fc, and MRR are found as 2.5, 6.5 and 5.9%, respectively. The convergence plot of all Milling characteristics suggests the application potential of the GWO algorithm for quality improvement in a manufacturing environment.

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