scholarly journals Viscous compression model for estimating the depth of new snow

1998 ◽  
Vol 26 ◽  
pp. 77-82 ◽  
Author(s):  
Yuji Kominami ◽  
Yasoichi Endo ◽  
Shoji Niwano ◽  
Syuichi Ushioda
Keyword(s):  
Standard Deviation ◽  
Snow Depth ◽  
Empirical Relation ◽  
Snow Surface ◽  
Maximum Difference ◽  
Snow Layer ◽  
Time Step ◽  
Hourly Data ◽  
Previous Time Step ◽  
Good Agreement

This paper describes a method for estimating the depth of new snow, using hourly data of total snow depth and precipitation. As the snow cover is compacted continuously due to its own weight, the depth of new snow deposited since the previous time-step to the present time is given by a difference between the height of the present snow surface and the present is impacted height of the previous snow surface. Thus, based on viscous compression theory and an empirical relation between compressive viscosity and the density of snow, an equation has been derived to compute the time variation of the thickness of a snow layer due to viscous compression. Using this equation, the present height of the previous snow surface, which cannot be measured by simple means, was computed and the depth of daily new snow was estimated as its difference from the present measured total snow depth. The approximated results were found to be in good agreement with data measured in Tohkamachi during the three winters from 1992–93 to 1994–95. The standard deviation was 1.71 cm and the maximum difference between estimated values and observed values was ± 8 cm.

scholarly journals Viscous compression model for estimating the depth of new snow

1998 ◽  
Vol 26 ◽  
pp. 77-82
Author(s):  
Yuji Kominami ◽  
Yasoichi Endo ◽  
Shoji Niwano ◽  
Syuichi Ushioda
Keyword(s):  
Standard Deviation ◽  
Snow Depth ◽  
Empirical Relation ◽  
Snow Surface ◽  
Maximum Difference ◽  
Snow Layer ◽  
Time Step ◽  
Hourly Data ◽  
Previous Time Step ◽  
Good Agreement

This paper describes a method for estimating the depth of new snow, using hourly data of total snow depth and precipitation. As the snow cover is compacted continuously due to its own weight, the depth of new snow deposited since the previous time-step to the present time is given by a difference between the height of the present snow surface and the present is impacted height of the previous snow surface. Thus, based on viscous compression theory and an empirical relation between compressive viscosity and the density of snow, an equation has been derived to compute the time variation of the thickness of a snow layer due to viscous compression. Using this equation, the present height of the previous snow surface, which cannot be measured by simple means, was computed and the depth of daily new snow was estimated as its difference from the present measured total snow depth. The approximated results were found to be in good agreement with data measured in Tohkamachi during the three winters from 1992–93 to 1994–95. The standard deviation was 1.71 cm and the maximum difference between estimated values and observed values was ± 8 cm.

scholarly journals Retrieval of snow freeboard of Antarctic sea ice using waveform fitting of CryoSat-2 returns

2019 ◽  
Vol 13 (3) ◽  
pp. 861-878 ◽  
Author(s):  
Steven W. Fons ◽  
Nathan T. Kurtz
Keyword(s):  
Sea Ice ◽  
Physical Model ◽  
Snow Depth ◽  
Trust Region ◽  
Surface Elevation ◽  
Snow Surface ◽  
Snow Layer ◽  
Antarctic Sea Ice ◽  
The Difference ◽  
Waveform Fitting

Abstract. In this paper we develop a CryoSat-2 algorithm to retrieve the surface elevation of the air–snow interface over Antarctic sea ice. This algorithm utilizes a two-layer physical model that accounts for scattering from a snow layer atop sea ice as well as scattering from below the snow surface. The model produces waveforms that are fit to CryoSat-2 level 1B data through a bounded trust region least-squares fitting process. These fit waveforms are then used to track the air–snow interface and retrieve the surface elevation at each point along the CryoSat-2 ground track, from which the snow freeboard is computed. To validate this algorithm, we compare retrieved surface elevation measurements and snow surface radar return power levels with those from Operation IceBridge, which flew along a contemporaneous CryoSat-2 orbit in October 2011 and November 2012. Average elevation differences (standard deviations) along the flight lines (IceBridge Airborne Topographic Mapper, ATM – CryoSat-2) are found to be 0.016 cm (29.24 cm) in 2011 and 2.58 cm (26.65 cm) in 2012. The spatial distribution of monthly average pan-Antarctic snow freeboard found using this method is similar to what was observed from NASA's Ice, Cloud, and land Elevation Satellite (ICESat), where the difference (standard deviation) between October 2011–2017 CryoSat-2 mean snow freeboard and spring 2003–2007 mean freeboard from ICESat is 1.92 cm (9.23 cm). While our results suggest that this physical model and waveform fitting method can be used to retrieve snow freeboard from CryoSat-2, allowing for the potential to join laser and radar altimetry data records in the Antarctic, larger (∼30 cm) regional differences from ICESat and along-track differences from ATM do exist, suggesting the need for future improvements to the method. Snow–ice interface elevation retrieval is also explored as a potential to obtain snow depth measurements. However, it is found that this retrieval method often tracks a strong scattering layer within the snow layer instead of the actual snow–ice interface, leading to an overestimation of ice freeboard and an underestimation of snow depth in much of the Southern Ocean but with promising results in areas such as the East Antarctic sector.

scholarly journals Retrieval of snow freeboard of Antarctic sea ice using waveform fitting of CryoSat-2 returns

2018 ◽  
Author(s):  
Steven W. Fons ◽  
Nathan T. Kurtz
Keyword(s):  
Sea Ice ◽  
Physical Model ◽  
Snow Depth ◽  
Trust Region ◽  
Surface Elevation ◽  
Snow Surface ◽  
Snow Layer ◽  
Antarctic Sea Ice ◽  
Antarctic Snow ◽  
Waveform Fitting

Abstract. In this paper we develop a CryoSat-2 algorithm to retrieve the surface elevation of the air-snow interface over Antarctic sea ice. This algorithm utilizes a two-layer physical model that accounts for scattering from a snow layer atop sea ice as well as scattering from below the snow surface. The model produces waveforms that are fit to CryoSat-2 level 1B data through a bounded trust region least squares fitting process. These fit waveforms are then used to track the air-snow interface and retrieve the surface elevation at each point along the CryoSat-2 ground track, from which the snow freeboard is computed. To validate this algorithm, we compare retrieved surface elevation measurements and snow surface radar return power levels with those from Operation IceBridge, which flew along a contemporaneous CryoSat-2 orbit in October 2011 and November 2012. Average elevation differences along the flight lines (IceBridge Airborne Topographic Mapper (ATM) – CryoSat-2) are found to be 0.016 cm in 2011 and 2.58 cm in 2012. The spatial distribution of monthly average pan-Antarctic snow freeboard found using this method is similar to what was observed from NASA's Ice, Cloud, and land Elevation Satellite (ICESat), where the difference between October 2011–2017 CryoSat-2 mean snow freeboard and spring 2003–2007 mean freeboard from ICESat is 1.92 cm. Our results suggest that this physical model and waveform fitting method can be used to retrieve snow freeboard from CryoSat-2, allowing for the potential to join laser and radar altimetry data records in the Antarctic. Snow-ice interface elevation retrieval is also explored as a potential to obtain snow depth measurements. However, it is found that this retrieval method often tracks a strong scattering layer within the snow layer instead of the actual snow-ice interface, leading to an overestimation of ice freeboard and an underestimation of snow depth in much of the Southern Ocean but with promising results in areas such as the East Antarctic sector.

scholarly journals Simulation of Daily Mean Soil Temperatures for Agricultural Land Use Considering Limited Input Data

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 441
Author(s):  
Philipp Grabenweger ◽  
Branislava Lalic ◽  
Miroslav Trnka ◽  
Jan Balek ◽  
Erwin Murer ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Input Data ◽  
Agricultural Land ◽  
Soil Column ◽  
Soil Conditions ◽  
Snow Layer ◽  
Time Step ◽  
Soil Temperatures ◽  
Dimensional Simulation ◽  
Limited Input Data

A one-dimensional simulation model that simulates daily mean soil temperature on a daily time-step basis, named AGRISOTES (AGRIcultural SOil TEmperature Simulation), is described. It considers ground coverage by biomass or a snow layer and accounts for the freeze/thaw effect of soil water. The model is designed for use on agricultural land with limited (and mostly easily available) input data, for estimating soil temperature spatial patterns, for single sites (as a stand-alone version), or in context with agrometeorological and agronomic models. The calibration and validation of the model are carried out on measured soil temperatures in experimental fields and other measurement sites with various climates, agricultural land uses and soil conditions in Europe. The model validation shows good results, but they are determined strongly by the quality and representativeness of the measured or estimated input parameters to which the model is most sensitive, particularly soil cover dynamics (biomass and snow cover), soil pore volume, soil texture and water content over the soil column.

scholarly journals A high-fidelity realization of the Euclid code comparison N-body simulation with Abacus

2019 ◽  
Vol 485 (3) ◽  
pp. 3370-3377 ◽  
Author(s):  
Lehman H Garrison ◽  
Daniel J Eisenstein ◽  
Philip A Pinto
Keyword(s):  
Power Spectrum ◽  
High Performance ◽  
High Fidelity ◽  
Step Size ◽  
Time Step ◽  
Code Comparison ◽  
Force Accuracy ◽  
Integration Errors ◽  
Better Than ◽  
Good Agreement

Abstract We present a high-fidelity realization of the cosmological N-body simulation from the Schneider et al. code comparison project. The simulation was performed with our AbacusN-body code, which offers high-force accuracy, high performance, and minimal particle integration errors. The simulation consists of 20483 particles in a $500\ h^{-1}\, \mathrm{Mpc}$ box for a particle mass of $1.2\times 10^9\ h^{-1}\, \mathrm{M}_\odot$ with $10\ h^{-1}\, \mathrm{kpc}$ spline softening. Abacus executed 1052 global time-steps to z = 0 in 107 h on one dual-Xeon, dual-GPU node, for a mean rate of 23 million particles per second per step. We find Abacus is in good agreement with Ramses and Pkdgrav3 and less so with Gadget3. We validate our choice of time-step by halving the step size and find sub-percent differences in the power spectrum and 2PCF at nearly all measured scales, with ${\lt }0.3{{\ \rm per\ cent}}$ errors at $k\lt 10\ \mathrm{Mpc}^{-1}\, h$. On large scales, Abacus reproduces linear theory better than 0.01 per cent. Simulation snapshots are available at http://nbody.rc.fas.harvard.edu/public/S2016.

scholarly journals MAX-DOAS observations of aerosols, formaldehyde and nitrogen dioxide in the Beijing area: comparison of two profile retrieval approaches

2015 ◽  
Vol 8 (2) ◽  
pp. 941-963 ◽  
Author(s):  
T. Vlemmix ◽  
F. Hendrick ◽  
G. Pinardi ◽  
I. De Smedt ◽  
C. Fayt ◽  
...  
Keyword(s):  
Standard Deviation ◽  
A Priori ◽  
Systematic Bias ◽  
Aerosol Extinction ◽  
Data Set ◽  
Near Surface ◽  
Beijing Area ◽  
Least Squares Fit ◽  
Relative Differences ◽  
Good Agreement

Abstract. A 4-year data set of MAX-DOAS observations in the Beijing area (2008–2012) is analysed with a focus on NO2, HCHO and aerosols. Two very different retrieval methods are applied. Method A describes the tropospheric profile with 13 layers and makes use of the optimal estimation method. Method B uses 2–4 parameters to describe the tropospheric profile and an inversion based on a least-squares fit. For each constituent (NO2, HCHO and aerosols) the retrieval outcomes are compared in terms of tropospheric column densities, surface concentrations and "characteristic profile heights" (i.e. the height below which 75% of the vertically integrated tropospheric column density resides). We find best agreement between the two methods for tropospheric NO2 column densities, with a standard deviation of relative differences below 10%, a correlation of 0.99 and a linear regression with a slope of 1.03. For tropospheric HCHO column densities we find a similar slope, but also a systematic bias of almost 10% which is likely related to differences in profile height. Aerosol optical depths (AODs) retrieved with method B are 20% high compared to method A. They are more in agreement with AERONET measurements, which are on average only 5% lower, however with considerable relative differences (standard deviation ~ 25%). With respect to near-surface volume mixing ratios and aerosol extinction we find considerably larger relative differences: 10 ± 30, −23 ± 28 and −8 ± 33% for aerosols, HCHO and NO2 respectively. The frequency distributions of these near-surface concentrations show however a quite good agreement, and this indicates that near-surface concentrations derived from MAX-DOAS are certainly useful in a climatological sense. A major difference between the two methods is the dynamic range of retrieved characteristic profile heights which is larger for method B than for method A. This effect is most pronounced for HCHO, where retrieved profile shapes with method A are very close to the a priori, and moderate for NO2 and aerosol extinction which on average show quite good agreement for characteristic profile heights below 1.5 km. One of the main advantages of method A is the stability, even under suboptimal conditions (e.g. in the presence of clouds). Method B is generally more unstable and this explains probably a substantial part of the quite large relative differences between the two methods. However, despite a relatively low precision for individual profile retrievals it appears as if seasonally averaged profile heights retrieved with method B are less biased towards a priori assumptions than those retrieved with method A. This gives confidence in the result obtained with method B, namely that aerosol extinction profiles tend on average to be higher than NO2 profiles in spring and summer, whereas they seem on average to be of the same height in winter, a result which is especially relevant in relation to the validation of satellite retrievals.

scholarly journals On the Shape–Slope Relation of Drop Size Distributions in Convective Rain

2005 ◽  
Vol 44 (7) ◽  
pp. 1146-1151 ◽  
Author(s):  
Axel Seifert
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Drop Size ◽  
Empirical Relation ◽  
Size Distributions ◽  
Shape Parameters ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Drop Size Distributions ◽  
Good Agreement

Abstract The relation between the slope and shape parameters of the raindrop size distribution parameterized by a gamma distribution is examined. The comparison of results of a simple rain shaft model with an empirical relation based on disdrometer measurements at the surface shows very good agreement, but a more detailed discussion reveals some difficulties—for example, deviations from the gamma shape and the overestimation of collisional breakup.

Low-Reynolds-number flow around an oscillating circular cylinder at low Keulegan–Carpenter numbers

1998 ◽  
Vol 360 ◽  
pp. 249-271 ◽  
Author(s):  
H. DÜTSCH ◽  
F. DURST ◽  
S. BECKER ◽  
H. LIENHART
Keyword(s):  
Reynolds Number ◽  
Circular Cylinder ◽  
Time Step ◽  
Time Resolved ◽  
Reynolds Number Flow ◽  
Line Force ◽  
Number Flow ◽  
Weakly Stable ◽  
Fluid Behaviour ◽  
Good Agreement

Time-averaged LDA measurements and time-resolved numerical flow predictions were performed to investigate the laminar flow induced by the harmonic in-line oscillation of a circular cylinder in water at rest. The key parameters, Reynolds number Re and Keulegan–Carpenter number KC, were varied to study three parameter combinations in detail. Good agreement was observed for Re=100 and KC=5 between measurements and predictions comparing phase-averaged velocity vectors. For Re=200 and KC=10 weakly stable and non-periodic flow patterns occurred, which made repeatable time-averaged measurements impossible. Nevertheless, the experimentally visualized vortex dynamics was reproduced by the two-dimensional computations. For the third combination, Re=210 and KC=6, which refers to a totally different flow regime, the computations again resulted in the correct fluid behaviour. Applying the widely used model of Morison et al. (1950) to the computed in-line force history, the drag and the added-mass coefficients were calculated and compared for different grid levels and time steps. Using these to reproduce the force functions revealed deviations from those originally computed as already noted in previous studies. They were found to be much higher than the deviations for the coarsest computational grid or the largest time step. The comparison of several in-line force coefficients with results obtained experimentally by Kühtz (1996) for β=35 confirmed that force predictions could also be reliably obtained by the computations.

Automated Method for the Analysis of Riboflavin in Milk, with Application to Other Selected Foods

1974 ◽  
Vol 57 (5) ◽  
pp. 1085-1088
Author(s):  
James R Kirk
Keyword(s):  
Standard Deviation ◽  
Continuous Flow ◽  
Quantitative Method ◽  
Green Fluorescence ◽  
Internal Standards ◽  
Automated Method ◽  
Sodium Hydrosulfite ◽  
Automated Technique ◽  
Good Agreement

Abstract A continuous flow automated technique was developed for the determination of riboflavin in milk. The determination is based on the measurement of the natural yellow-green fluorescence of riboflavin at an excitation of 436 nm and emission of 510 nm. Blank values are determined for each sample after sodium hydrosulfite reduction of the riboflavin. Mean recovery and standard deviation for riboflavin in milk determined by the continuous flow procedure using internal standards were 9 7% and ± 2.42%, respectively. The recovery value was in good agreement with that determined using a manual procedure, while the standard deviation was 33% less than that found when using the manual procedure. The results from this study indicate that the continuous flow automated procedure for the determination of riboflavin in milk is a simple, quantitative method which eliminates many of the time-consuming analytical steps.

scholarly journals In-Situ LED-Based Observation of Snow Surface and Depth Transects

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2292
Author(s):  
Celeste Barnes ◽  
Chris Hopkinson ◽  
Thomas Porter ◽  
Zhouxin Xi
Keyword(s):  
Snow Depth ◽  
Surface Albedo ◽  
Surface Condition ◽  
Field Of View ◽  
Snow Surface ◽  
Depth Measurement ◽  
Individual Distance ◽  
Strong Linear Relationship ◽  
Better Than

As part of a new snowpack monitoring framework, this study evaluated the feasibility of using an LED LIDAR (Leddar) time of flight sensor for snowpack depth measurement. The Leddar sensor has two additional features over simple sonic ranging sensors: (i) the return signal is divided into 16 segments across a 48° field of view, each recording individual distance-to-target (DTT) measurements; (ii) an index of reflectance or intensity signal is recorded for each segment. These two features provide information describing snowpack morphology and surface condition. The accuracy of Leddar sensor DTT measurements for snow depth monitoring was found to be < 20 mm, which was better than the 50 mm quoted by the manufacturer, and the precision was < 5 mm. Leddar and independent sonic ranger snow depth measurement showed strong linear agreement (r2 = 0.98). There was also a strong linear relationship (r2 = 0.98) between Leddar and manual field snow depth measurements. The intensity signal response was found to correlate with snow surface albedo and inversely with air temperature (r = 0.77 and −0.77, respectively).

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