scholarly journals Spectral snow-reflectance models for grain-size and liquid-water fraction in melting snow for the solar-reflected spectrum

2002 ◽  
Vol 34 ◽  
pp. 71-73 ◽  
Author(s):  
Robert O. Green ◽  
Jeff Dozier ◽  
Dar Roberts ◽  
Tom Painter
Keyword(s):  
Grain Size ◽  
Optical Properties ◽  
Liquid Water ◽  
Spectral Reflectance ◽  
Hydrological Modeling ◽  
Sphere Model ◽  
Snow Layer ◽  
Melting Snow ◽  
Water Fraction ◽  
Spectral Models

AbstractTwo spectral snow-reflectance models that account for the effects of grain-size and liquid-water fraction are described and initial validation results presented. The models are based upon the spectral complex refractive index of liquid water and ice in the region from 400 to 2500 nm. Mie scattering calculations are used to specify the essential optical properties of snow in the models. Two approaches are explored to model the effect of liquid water in the snow. The first accounts for the liquid water as separate spheres interspersed with ice spheres in the snow layer. The second accounts for the liquid water as coatings on ice grains in the snow layer. A discrete-ordinate radiative transfer code is used to model the spectral reflectance of the snow for the Mie-calculated optical properties. Both the interspersed- and coated-sphere models show that the snow-absorption feature at 1030 nm shifts to shorter wavelength as the liquid-water content increased. The expression of these shifts is different for the two models. A comparison of the models with a spectral measurement of frozen and melting snow shows better agreement with the coated-sphere model. A spectral fitting algorithm was developed and tested with the coated-sphere model to derive the grain-size and liquid-water fraction from snow spectral reflectance measurements. Consistent values of grain-size and liquid water were retrieved from the measured snow spectra. This research demonstrates the use of spectral models and spectral measurements to derive surface snow grain-size and liquid-water fraction. The results of this research may be extended to regional and greater scales using data acquired by airborne and spaceborne imaging spectrometers for contributions to energy balance and hydrological modeling.

scholarly journals A bulk parametrization of melting snowflakes with explicit liquid water fraction for the COSMO model

2013 ◽  
Vol 6 (6) ◽  
pp. 1925-1939 ◽  
Author(s):  
C. Frick ◽  
A. Seifert ◽  
H. Wernli
Keyword(s):  
Liquid Water ◽  
Melting Process ◽  
Cloud Microphysics ◽  
Gradual Transition ◽  
Small Scale ◽  
Snow Melting ◽  
Melting Snow ◽  
Water Fraction ◽  
Cosmo Model ◽  
Fall Speed

Abstract. A new snow melting parametrization is presented for the non-hydrostatic limited-area COSMO ("consortium for small-scale modelling") model. In contrast to the standard cloud microphysics of the COSMO model, which instantaneously transfers the meltwater from the snow to the rain category, the new scheme explicitly considers the liquid water fraction of the melting snowflakes. These semi-melted hydrometeors have characteristics (e.g., shape and fall speed) that differ from those of dry snow and rain droplets. Where possible, theoretical considerations and results from vertical wind tunnel laboratory experiments of melting snowflakes are used as the basis for characterising the melting snow as a function of its liquid water fraction. These characteristics include the capacitance, the ventilation coefficient, and the terminal fall speed. For the bulk parametrization, a critical diameter is introduced. It is assumed that particles smaller than this diameter, which increases during the melting process, have completely melted, i.e., they are converted to the rain category. The values of the bulk integrals are calculated with a finite difference method and approximately represented by polynomial functions, which allows an efficient implementation of the parametrization. Two case studies of (wet) snowfall in Germany are presented to illustrate the potential of the new snow melting parametrization. It is shown that the new scheme (i) produces wet snow instead of rain in some regions with surface temperatures slightly above the freezing point, (ii) simulates realistic atmospheric melting layers with a gradual transition from dry snow to melting snow to rain, and (iii) leads to a slower snow melting process. In the future, it will be important to thoroughly validate the scheme, also with radar data and to further explore its potential for improved surface precipitation forecasts for various meteorological conditions.

scholarly journals A bulk parameterization of melting snowflakes with explicit liquid water fraction for the COSMO model version 4.14

2013 ◽  
Vol 6 (2) ◽  
pp. 2927-2966
Author(s):  
C. Frick ◽  
A. Seifert ◽  
H. Wernli
Keyword(s):  
Liquid Water ◽  
Melting Process ◽  
Cloud Microphysics ◽  
Snow Melting ◽  
Melting Snow ◽  
Water Fraction ◽  
Model Version ◽  
Cosmo Model ◽  
Fall Speed ◽  
Bulk Parameterization

Abstract. A new snow melting parameterization is presented for the non-hydrostatic limited-area COSMO ("consortium for small-scale modelling") model version 4.14. In contrast to the standard cloud microphysics of the COSMO model, which instantaneously transfers the meltwater from the snow to the rain category, the new scheme explicitly considers the liquid water fraction of the melting snowflakes. These semi-melted hydrometeors have characteristics (e.g., shape and fall speed) that differ from those of dry snow and rain droplets. Where possible, theoretical considerations and results from vertical wind tunnel laboratory experiments of melting snowflakes are used as the basis for characterizing the melting snow as a function of its liquid water fraction. These characteristics include the capacitance, the ventilation coefficient, and the terminal fall speed. For the bulk parameterization, a critical diameter is introduced. It is assumed that particles smaller than this diameter, which increases during the melting process, have completely melted, i.e., they are converted to the rain category. The values of the bulk integrals are calculated with a finite difference method and approximatively represented by polynomial functions, which allows an efficient implementation of the parameterization. Two case studies of (wet) snowfall in Germany are presented to illustrate the potential of the new snow melting parameterization. It is shown that the new scheme (i) produces wet snow instead of rain in some regions with surface temperatures slightly above the freezing point, (ii) simulates realistic atmospheric melting layers with a gradual transition from dry snow to melting snow to rain, and (iii) leads to a slower snow melting process. In the future, it will be important to thoroughly validate the scheme, also with radar data and to further explore its potential for improved surface precipitation forecasts for various meteorological conditions.

scholarly journals Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest

2021 ◽  
Author(s):  
Hibiki M. Noda ◽  
Hiroyuki Muraoka ◽  
Kenlo Nishida Nasahara
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Spectral Reflectance ◽  
Canopy Structure ◽  
Terrestrial Ecosystems ◽  
Optical Remote Sensing ◽  
Canopy Reflectance ◽  
Broadleaf Forest ◽  
Leaf Optical Properties ◽  
Deciduous Broadleaf Forest

AbstractThe need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.

scholarly journals Snow dielectric properties: from DC to microwave X-band

1994 ◽  
Vol 19 ◽  
pp. 92-96 ◽  
Author(s):  
TH. Achammer ◽  
A. Denoth
Keyword(s):  
Grain Size ◽  
Dielectric Properties ◽  
Water Content ◽  
Liquid Water ◽  
Liquid Water Content ◽  
Frequency Range ◽  
Snow Density ◽  
Cold Room ◽  
X Band ◽  
Grain Size And Shape

Broadband measurements of dielectric properties of natural snow samples near or at 0°C are reported. Measurement quantities are: dielectric permittivity, loss factor and complex propagation factor for electromagnetic waves. X-band measurements were made in a cold room in the laboratory; measurements at low and intermediate frequencies were carried out both in the field (Stubai Alps, 3300 m; Hafelekar near Innsbruck, 2100 m) and in the cold room. Results show that in the different frequency ranges the relative effect on snow dielectric properties of the parameters: density, grain-size and shape, liquid water content, shape and distribution of liquid inclusions and content of impurities, varies significantly. In the low-frequency range the influence of grain-size and shape and snow density dominates; in the medium-frequency range liquid water content and density are the dominant parameters. In the microwave X-band the influence of the amount, shape and distribution of liquid inclusions and snow density is more important than that of the remaining parameters.

scholarly journals Using a two-layered sphere model to investigate the impact of gas vacuoles on the inherent optical properties of <i>Microcystis aeruginosa</i>

2013 ◽  
Vol 10 (12) ◽  
pp. 8139-8157 ◽  
Author(s):  
M. W. Matthews ◽  
S. Bernard
Keyword(s):  
Optical Properties ◽  
Microcystis Aeruginosa ◽  
Cyanobacterial Blooms ◽  
Shell Layer ◽  
Sphere Model ◽  
Homogeneous Population ◽  
Chl A ◽  
Inherent Optical Properties ◽  
Gas Vacuoles ◽  
The Impact

Abstract. A two-layered sphere model is used to investigate the impact of gas vacuoles on the inherent optical properties (IOPs) of the cyanophyte Microcystis aeruginosa. Enclosing a vacuole-like particle within a chromatoplasm shell layer significantly altered spectral scattering and increased backscattering. The two-layered sphere model reproduced features in the spectral attenuation and volume scattering function (VSF) that have previously been attributed to gas vacuoles. This suggests the model is good at least as a first approximation for investigating how gas vacuoles alter the IOPs. Measured Rrs was used to provide a range of values for the central value of the real refractive index, 1 + ε, for the shell layer using measured IOPs and a radiative transfer model. Sufficient optical closure was obtained for 1 + ε between 1.1 and 1.14, which had corresponding Chl a-specific phytoplankton backscattering, bbφ*, between 3.9 and 7.2 × 10−3 m2 mg−1 at 510 nm. The bbφ* values are in close agreement with the literature and in situ particulate backscattering measurements. Rrs simulated for a population of vacuolate cells was greatly enlarged relative to a homogeneous population. A sensitivity analysis of empirical algorithms for estimating Chl a in eutrophic/hypertrophic waters suggests these are robust under variable constituent concentrations and likely to be species-sensitive. The study confirms that gas vacuoles cause significant increase in backscattering and are responsible for the high Rrs values observed in buoyant cyanobacterial blooms. Gas vacuoles are therefore one of the most important bio-optical substructures influencing the IOPs in phytoplankton.

Modeling Surface Temperatures for Snow-Covered Roads: A Case Study for a Heated Pavement in Bærum, Norway

2018 ◽  
Vol 2672 (12) ◽  
pp. 220-231
Author(s):  
Anne D. W. Nuijten ◽  
Inge Hoff ◽  
Knut V. Høyland
Keyword(s):  
Thermal Conductivity ◽  
Water Content ◽  
Liquid Water ◽  
Surface Condition ◽  
Winter Season ◽  
High Water ◽  
Liquid Water Content ◽  
High Water Content ◽  
Snow Layer ◽  
Snow Samples

Heated pavements are used as an alternative to removing snow and ice mechanically and chemically. Usually a heated pavement system is automatically switched on when snowfall starts or when there is a risk of ice formation. Ideally, these systems run based on accurate predictions of surface conditions a couple of hours ahead of time, for which both weather forecasts and reliable surface temperature predictions are needed. The effective thermal conductivity of the snow layer is often described as a function of its density. However the thermal conductivity of a snow layer can vary considerably, not only for snow samples with a different density, but also for snow samples with the same density, but with a variation in the liquid water content. In this paper a physical temperature and surface condition model is described for snow-covered roads. The model is validated for an entire winter season on a heated pavement in Norway. Two different models to describe the thermal conductivity through the snow layer were compared. Results show that the thermal conductivity of the snow layer can be best described as a function of the density for snow with a low liquid water content. For snow with a high water content, the thermal conductivity can be best described as a function of the volume fractions and thermal conductivity of ice, water, and air, in which air and ice are modeled as a series system and water and air/ice in parallel.

The Effect of Ethanol Solvent on Characterization of MAPbI3 Perovskite

2021 ◽  
Vol 1039 ◽  
pp. 307-312
Author(s):  
Mohammad Malik Abood ◽  
Osama Abdul Azeez Dakhil ◽  
Aref Saleh Baron
Keyword(s):  
Grain Size ◽  
Optical Properties ◽  
Morphological Characteristics ◽  
X Ray Diffraction ◽  
Lead Iodide ◽  
X Ray ◽  
Diffraction Patterns ◽  
Photovoltaic Technologies ◽  
Perovskite Photovoltaic

Methyl ammonium lead iodide CH3NH3PbI3 Perovskite was synthesized by a new method mixing between one and two steps, in addition, the ethanol solvent was used to dissolve CH3NH3I and compared with isopropanol solvent. The characterizations of synthesized perovskite samples included the structural properties, morphological characteristics and optical properties. The intensity and orientation in X-ray diffraction patterns appear clearly in ethanol solvent while disappearing at a peak at 12o due to the speed reaction of perovskite in this solvent. Additionally, the ethanol solvent increasing the grain size of perovskite which homogeneity of the surface morphology. the ethanol solvent cause a decrease in the wavelength of absorbance edge in addition to an increase in the energy bandgap value. Keywords: Ethanol Solvent, Perovskite, Photovoltaic Technologies, X-ray diffraction.

scholarly journals Method of Measuring Liquid Water Mass Fraction of Snow by Alcohol Solution

1986 ◽  
Vol 32 (112) ◽  
pp. 538-539 ◽  
Author(s):  
D. Fisk
Keyword(s):  
Liquid Water ◽  
Water Mass ◽  
Field Measurements ◽  
Absolute Error ◽  
Liquid Water Content ◽  
Snow Sample ◽  
Maximum Absolute Error ◽  
Water Fraction ◽  
Single Operator ◽  
Temperature Depression

Abstracta method of making field measurements of the liquid water fraction of snow has been developed in which a snow sample is dissolved in methanol to produce a temperature depression. The depression is linearly related to the liquid water content of the snow sample. a single operator can perform four to five measurements per hour with a maximum absolute error of 1.0%.

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