Effect of spatial variability of wet snow on modeled and observed microwave emissions

Abstract Effective snow grain radius (re) is mapped at high resolution using near-infrared hyperspectral imaging (NIR-HSI). The NIR-HSI method can be used to quantify re spatial variability, change in re due to metamorphism, and visualize water percolation in the snowpack. Results are presented for three different laboratory-prepared snow samples (homogeneous, ice lens, fine grains over coarse grains), the sidewalls of which were imaged before and after melt induced by a solar lamp. The spectral reflectance in each ~3 mm pixel was inverted for re using the scaled band area of the ice absorption feature centered at 1030 nm, producing re maps consisting of 54 740 pixels. All snow samples exhibited grain coarsening post-melt as the result of wet snow metamorphism, which is quantified by the change in re distributions from pre- and post-melt images. The NIR-HSI method was compared to re retrievals from a field spectrometer and X-ray computed microtomography (micro-CT), resulting in the spectrometer having the same mean re and micro-CT having 23.9% higher mean re than the hyperspectral imager. As compact hyperspectral imagers become more widely available, this method may be a valuable tool for assessing re spatial variability and snow metamorphism in field and laboratory settings.

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Measurements of mid-winter spatial distribution of meltwater saturation

Annals of Glaciology ◽

10.3189/172756410791386418 ◽

2010 ◽

Vol 51 (54) ◽

pp. 146-152

Author(s):

J.C. Kapil ◽

Anupam Kumar ◽

P.S. Negi

Keyword(s):

Spatial Distribution ◽

Spatial Variability ◽

Snow Cover ◽

Measurement Techniques ◽

Three Dimensional ◽

Dielectric Measurement ◽

Snow Stratigraphy ◽

Wet Snow ◽

Water Contents ◽

Saturation Profiles

AbstractUnder melt–freeze conditions crusts may evolve within a snowpack, which may favour avalanche initiation by forming a hard bed surface for weakly bonded faceted grains. We used a parallel-probe saturation profiler (PPSP) to record the distribution of water contents within the snowpack. Diurnal effects of melt–freeze action on the growth of crusts were monitored with the help of the PPSP device. Saturation profiles were collected from a partially wet snow cover. Snow stratigraphy was conducted manually in the morning, after overnight freezing, to identify the location and the granular compositions of the crusts that had evolved. A one-to-one correspondence between the saturation spikes collected using the PPSP and the actual positions of the crusts was established. The PPSP was also used to monitor three-dimensional variations in the maximum percolation depths within a south-facing snowpack. The operation of the PPSP is faster than existing dielectric measurement techniques, so it was applied to study the spatial variability of maximum percolation depths on the slopes of different aspects.

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Sampling and mapping of heterogeneous surfaces: multi-resolution tiling adjusted to spatial variability

International Journal of Geographical Information Systems ◽

10.1080/026937996137756 ◽

1996 ◽

Vol 10 (7) ◽

pp. 851-876

Author(s):

Ferenc Csillag ◽

Miklos Kertesz ◽

Agnes Kummert

Keyword(s):

Spatial Variability ◽

Heterogeneous Surfaces

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Spatial variability induces generalization in contextual cueing.

Journal of Experimental Psychology Learning Memory and Cognition ◽

10.1037/xlm0000796 ◽

2020 ◽

Vol 46 (12) ◽

pp. 2295-2313

Author(s):

Yoko Higuchi ◽

Yoshiyuki Ueda ◽

Kazuhisa Shibata ◽

Jun Saiki

Keyword(s):

Spatial Variability ◽

Contextual Cueing

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Spatial variability in responses to environmental conditions in Southern Hemisphere long-finned pilot whales

Marine Ecology Progress Series ◽

10.3354/meps13109 ◽

2019 ◽

Vol 629 ◽

pp. 207-218 ◽

Cited By ~ 1

Author(s):

V Hamilton ◽

K Evans ◽

B Raymond ◽

E Betty ◽

MA Hindell

Keyword(s):

Spatial Variability ◽

Southern Hemisphere ◽

Environmental Conditions ◽

Pilot Whales

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DISTRIBUIÇÃO DA EVAPORAÇÃO EM ESTUFA PLÁSTICA NA PRIMAVERA

Irriga ◽

10.15809/irriga.2001v6n3p120-127 ◽

2001 ◽

Vol 6 (3) ◽

pp. 120-127

Author(s):

Reginaldo Ferreira Santos ◽

Antonio Evaldo Klar

Keyword(s):

Spatial Variability ◽

Pan Evaporation ◽

Spring Season ◽

Class A ◽

Agricultural Sciences ◽

E Mail ◽

Center Area ◽

Class A Pan

DISTRIBUIÇÃO DA EVAPORAÇÃO EM ESTUFA PLÁSTICA NA PRIMAVERA Reginaldo Ferreira SantosCentro de Ciências Exatas e Tecnológica da UNIOESTE- CP 711CEP 858114-110, Cascavel, PR - Fone: 0XX45 2203155. E-mail: [email protected] Evaldo KlarDepartamento de Engenharia Rural - Faculdade de Ciências Agronômica- UNESP - CEP 18603-970 - Botucatu, SP. CP: 237. E-mail: [email protected] 1 RESUMO O presente trabalho teve como objetivo avaliar a distribuição da evaporação no interior de uma estufa plástica, com uma cultura de pimentão, através da variabilidade espacial e comparar a evaporação dos microevaporímetros com os valores do Tanque classe "A". O experimento foi conduzido no Campus da Universidade Estadual Paulista - FCA/UNESP, no período de primavera, em estufa plástica de polietileno de baixa densidade (PEBD). Na distribuição da evaporação em estufa com orientação norte/sul, verificou-se que as maiores evaporações ocorreram nas extremidades sul e norte tendente ao lado oeste. Já as menores evaporações localizaram-se no centro. No período de primavera, a evaporação média nos microevaporímetros superestimou em 55% a evaporação determinada no Tanque classe "A". UNITERMOS: evaporação, geoestatística, estufa. SANTOS, R.F, KLAR, A.E. EVAPORATION DISTRIBUTION INSIDE A PLASTIC TUNNEL IN THE SPRING SEASON 2 ABSTRACT The main aim of this study was to verify the evaporation distribution inside a plastic tunnel, with pepper crop, oriented to north/south, through spatial variability and to compare Class A Pan evaporation to punctual evaporations of 40 equidistant microevaporimeters placed from 50cm the soil. The study was carried out at the College of Agricultural Sciences/UNESP, Botucatu – SP in the spring season. The highest evaporation occurred next to north and to south sides of the tunnel, with tendency to west. Consequently, the lowest evaporations occurred at the center area. The microevaporimeter evaporations were 55% higher than those obtained from Class A Pan. KEYWORDS: evaporation distribution, microevaporimeter.

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