scholarly journals Retrieval of snow properties from the Sentinel-3 Ocean and Land Colour Instrument

Author(s):  
Alexander Kokhanovsky ◽  
Maxim Lamare ◽  
Olaf Danne ◽  
Marie Dumont ◽  
Carsten Brockmann ◽  
...  

The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing (http://step.esa.int/main/toolboxes/snap/). In this work we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400-1020nm, we derive important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on the spatial grid of 300m. The algorithm also incorporates cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long – term snow property records essential for climate monitoring and data assimilation studies - especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.

2019 ◽  
Vol 11 (19) ◽  
pp. 2280 ◽  
Author(s):  
Alexander Kokhanovsky ◽  
Maxim Lamare ◽  
Olaf Danne ◽  
Carsten Brockmann ◽  
Marie Dumont ◽  
...  

The Sentinel Application Platform (SNAP) architecture facilitates Earth Observation data processing. In this work, we present results from a new Snow Processor for SNAP. We also describe physical principles behind the developed snow property retrieval technique based on the analysis of Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A/B measurements over clean and polluted snow fields. Using OLCI spectral reflectance measurements in the range 400–1020 nm, we derived important snow properties such as spectral and broadband albedo, snow specific surface area, snow extent and grain size on a spatial grid of 300 m. The algorithm also incorporated cloud screening and atmospheric correction procedures over snow surfaces. We present validation results using ground measurements from Antarctica, the Greenland ice sheet and the French Alps. We find the spectral albedo retrieved with accuracy of better than 3% on average, making our retrievals sufficient for a variety of applications. Broadband albedo is retrieved with the average accuracy of about 5% over snow. Therefore, the uncertainties of satellite retrievals are close to experimental errors of ground measurements. The retrieved surface grain size shows good agreement with ground observations. Snow specific surface area observations are also consistent with our OLCI retrievals. We present snow albedo and grain size mapping over the inland ice sheet of Greenland for areas including dry snow, melted/melting snow and impurity rich bare ice. The algorithm can be applied to OLCI Sentinel-3 measurements providing an opportunity for creation of long-term snow property records essential for climate monitoring and data assimilation studies—especially in the Arctic region, where we face rapid environmental changes including reduction of snow/ice extent and, therefore, planetary albedo.


2016 ◽  
Author(s):  
K. Urumović ◽  
K. Urumović Sr.

Abstract. In this paper, the results of permeability and specific surface area analyses as functions of granulometric composition of various sediments (from silty clays to very well-graded gravels) are presented. The effective porosity and the referential grain size are presented as fundamental granulometric parameters expressing an effect of the forces operating on fluid movement through the saturated porous media. This paper suggests procedures for calculating referential grain size and determining effective (flow) porosity, which result in parameters that reliably determine the specific surface area and permeability. These procedures ensure the successful application of the Kozeny–Carman model up to the limits of validity of Darcy’s law. The value of effective porosity in the referential mean grain size function was calibrated within the range of 1.5 μm to 6.0 mm. The reliability of the parameters applied in the KC model was confirmed by a very high correlation between the predicted and tested hydraulic conductivity values (R2=0.99 for sandy and gravelly materials; R2=0.70 for clayey-silty materials). The group representation of hydraulic conductivity (ranging from 10–12 m/s up to 10–2 m/s) presents a coefficient of correlation of R2=0.97 for a total of 175 samples of various deposits. These results present new developments in the research of the effective porosity, the permeability and the specific surface area distributions of porous materials. This is important because these three parameters are critical conditions for successful groundwater flow modeling and contaminant transport. Additionally, from a practical viewpoint, it is very important to identify these parameters swiftly and very accurately.


2007 ◽  
Vol 336-338 ◽  
pp. 2017-2020 ◽  
Author(s):  
Fan Yong Ran ◽  
Wen Bin Cao ◽  
Yan Hong Li ◽  
Xiao Ning Zhang

Nanosize anatase TiO2 powders have been synthesized by hydrothermal synthesis by using technical grade TiOSO4 as precursor and urea as precipitating agent. The initial pressure of the reaction system was set at 6 MPa. Stirring speed was fixed at 300r/min. The reaction system reacted at the temperature ranged from 110 to 150°C for holding 2hrs to 8hrs and the concentration of the precursor was ranged from 0.25M to1.5M. XRD patterns show that the synthesized powders are in the form of anatase phase. Calculated grain size is ranged from 6.7 to 8.9nm by Scherrer method from the line broadening of the (101) diffraction peak of anatase. The specific surface area of the powders synthesized under different conditions is ranged from 124 to 240m2/g. The grain size of the powders increases with the increase of the reaction temperature, holding time and precursor concentration, respectively. The specific surface area decreases with the increase of reaction temperature and holding time, and does not obviously change with the change of precursor concentration when the concentration of the precursor is less than 1M. However, when the concentration is higher than 1M, the specific surface area will decrease quickly with the increase of the precursor concentration. XRD and DSC-TG analysis shows that the synthesized anatase TiO2 will begin to transform to rutile TiO2 at about 840°C. When heated to 1000°C for holding 1h, the anatase powders will transform to rutile completely.


2014 ◽  
Vol 1015 ◽  
pp. 501-504 ◽  
Author(s):  
Yong Guang Bi ◽  
Xu Si Xu

Papers with Ca (NO3)2• 4H2O and (NH4)2HPO4as raw material, prepared by ionic liquids assisted nanoHAP, resulting hexagonal nanoHAP are crystal grain size are 10-20nm level, are smaller nanometer range ; specific surface area, the findings show that ionic liquids have the technology to promote the significance of the preparation method can provide a reference for large-scale preparation of biomedical nanomaterials.


2021 ◽  
Author(s):  
Yong Li

<p>Debris flow is composed of solid grains of different sizes. the characteristics of grain size distribution reflect the movement mode and dynamic conditions of the fluid, and have different effects on the movement of debris flow. Due to the high variability of debris flow materials, the granular interaction is bound to affect the fluid properties. The grain size distribution (GSD) of debris flow satisfies the formula: P(D)=CD<sup>-μ</sup>exp(-D/D<sub>c</sub>), where, GSD parameters μ and D<sub>c</sub> can comprehensively reflect the change of grain composition. with μ reflecting the structure and variation characteristics of fine grains, and D<sub>c</sub> reflecting the range of grain size. Field surveys in various regions indicate that the GSD parameters are distinct in materials of flow, source, and deposition. The GSD parameters of source soil and deposition soil are random and discrete, while the GSD parameters of fluid samples show obvious negative power function form: D<sub>c</sub>= aμ<sup>b</sup> (Figure 1). This shows that the grain composition of debris flow contains some dynamic information. In this paper, we use natural soil materials in a typical debris flow valley to conduct a series dynamically mixing and rotating experiments to simulate the flow evolution, and explore the change of grains under the action of dynamics and the effect of grain adjustment on the mobility of debris flow. The results show that the GSD shows a significant regularity after dynamic rotation. The specific performance is that μ and D<sub>c</sub> change from the initial random discrete state to negative power correlation (Figure 2), and the appearance of this correlation corresponds to the best mobility of debris flow. At the same time, the Malvern laser grain size analyzer was used to analyze the specific surface area of fine grains (<0.20 mm) in the dynamic rotation experiment. The results show that with the increase of dynamic time, the specific surface area increases according to power law, and when the time reaches about 100 minutes, the growth slows down, and the specific surface area changes little. The experimental results are helpful for a deep understanding of the dynamics of debris flow.</p>


2011 ◽  
Vol 295-297 ◽  
pp. 668-671 ◽  
Author(s):  
Jun De Xing ◽  
Xiao Fei Jia

A series of Cu-based catalysts for the synthesis of indole by the reaction of aniline and ethylene glycol were prepared and characterized by ICP-AES and XRD. The results indicated that the activity and stability of Cu/SiO2 catalyst was increased after adding Zn, Mn, Cr and Fe promoters. Mn promoter was favorable for the dispersion of Cu, Zn, Cr, Fe and enlarged the specific surface area of catalysts. It could be seen that the catalysts prepared by impregnation method had better stability and higher activity than the catalysts prepared by co-precipitation method. The catalysts with small grain size of Cu had higher activity than those with big grain size. Some catalysts showed excellent performances in this reaction.


2021 ◽  
Author(s):  
Florent Domine ◽  
Georg Lackner ◽  
Denis Sarrazin ◽  
Mathilde Poirier ◽  
Maria Belke-Brea

Abstract. Seasonal snow covers Arctic lands 6 to 10 months of the year and is therefore an essential element of the Arctic geosphere and biosphere. Yet, even the most sophisticated snow physics models are not able to simulate fundamental physical properties of Arctic snowpacks such as density, thermal conductivity and specific surface area. The development of improved snow models is in progress but testing requires detailed driving and validation data for high Arctic herb tundra sites, which are presently not available. We present 6 years of such data for an ice-wedge polygonal site in the Canadian high Arctic, in Qarlikturvik valley on Bylot Island at 73.15 °N. The site is on herb tundra with no erect vegetation and thick permafrost. Detailed soil properties are provided. Driving data are comprised of air temperature, air relative and specific humidity, wind speed, short wave and long wave downwelling radiation, atmospheric pressure and precipitation. Validation data include time series of snow depth, shortwave upwelling radiation, surface temperature, snow temperature profiles, soil temperature and water content profiles at five depths, snow thermal conductivity at three heights and soil thermal conductivity at 10 cm depth. Field campaigns in mid-May for 5 of the 6 years of interest provided spatially-averaged snow depths and vertical profiles of snow density and specific surface area in the polygon of interest and at other spots in the valley. Data are available at https://doi.org/10.5885/45693CE-02685A5200DD4C38 (Domine et al., 2021). Data files will be updated as more years of data become available.


2015 ◽  
Vol 6 ◽  
pp. 27-35 ◽  
Author(s):  
Agnieszka Opalinska ◽  
Iwona Malka ◽  
Wojciech Dzwolak ◽  
Tadeusz Chudoba ◽  
Adam Presz ◽  
...  

The correlation between density and specific surface area of ZrO2 nanoparticles (NPs) was studied. The NPs were produced using a hydrothermal process involving microwave heating. The material was annealed at 1100 °C which resulted in an increase in the average grain size of the ZrO2 NPs from 11 to 78 nm and a decrease in the specific surface area from 97 to 15 m2/g. At the same time, the density increased from 5.22 g/m3 to 5.87 g/m3. This effect was interpreted to be the result of the presence of a hydroxide monolayer on the NP surface. A smaller ZrO2 grain size was correlated with a larger contribution of the low density surface layer to the average density. To prove the existence of such a layer, the material was synthesized using 50% heavy water. Fourier transform infrared spectroscopy (FTIR) permitted the identification of the –OD groups created during synthesis. It was found that the –OD groups persisted on the ZrO2 surface even after annealing at 1100 °C. This hydroxide layer is responsible for the decrease in the average density of the NPs as their size decreases. This study of the correlation between particle size and density may be used to assess the quality of the NPs. In most cases, the technological aim is to avoid an amorphous layer and to obtain fully crystalline nanoparticles with the highest density possible. However, due to the effect of the surface layers, there is a maximum density which can be achieved for a given average NP diameter. The effect of the surface layer on the NP density becomes particularly evident for NPs smaller than 50 nm, and thus, the density of nanoparticles is size dependent.


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