scholarly journals Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys

2020 ◽  
Vol 14 (10) ◽  
pp. 3287-3308
Author(s):  
Michael Studinger ◽  
Brooke C. Medley ◽  
Kelly M. Brunt ◽  
Kimberly A. Casey ◽  
Nathan T. Kurtz ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Wind Direction ◽  
Accumulation Rate ◽  
Snow Accumulation ◽  
Small Scale ◽  
Temporal And Spatial Variability ◽  
Geophysical Surveys ◽  
Slope Wind ◽  
Temporal And Spatial ◽  
Ku Band

Abstract. We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery acquired in 2014, 2016, and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88∘ S, an elevation bias validation site for ICESat-2 and potential validation site for CryoSat-2. We find significant small-scale variability (<10 km) in snow accumulation based on the snow radar subsurface stratigraphy, indicating areas of strong wind redistribution are prevalent at 88∘ S. In general, highs in snow accumulation rate correspond with topographic lows, resulting in a negative correlation coefficient of r2=-0.32 between accumulation rate and MSWD (mean slope in the mean wind direction). This relationship is strongest in areas where the dominant wind direction is parallel to the survey profile, which is expected as the geophysical surveys only capture a two-dimensional cross section of snow redistribution. Variability in snow accumulation appears to correlate with variability in MSWD. The correlation coefficient between the standard deviations of accumulation rate and MSWD is r2=0.48, indicating a stronger link between the standard deviations than the actual parameters. Our analysis shows that there is no simple relationship between surface slope, wind direction, and snow accumulation rates for the overall survey area. We find high variability in surface roughness derived from laser altimetry measurements on length scales smaller than 10 km, sometimes with very distinct and sharp transitions. Some areas also show significant temporal variability over the course of the 3 survey years. Ultimately, there is no statistically significant slope-independent relationship between surface roughness and accumulation rates within our survey area. The observed correspondence between the small-scale temporal and spatial variability in surface roughness and backscatter, as evidenced by Ku-band radar signal strength retrievals, will make it difficult to develop elevation bias corrections for radar altimeter retrieval algorithms.

scholarly journals Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys

2020 ◽  
Author(s):  
Michael Studinger ◽  
Brooke C. Medley ◽  
Kelly M. Brunt ◽  
Kimberly A. Casey ◽  
Nathan T. Kurtz ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Accumulation Rate ◽  
Snow Accumulation ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Temporal And Spatial Variability ◽  
Geophysical Surveys ◽  
Slope Wind ◽  
Temporal And Spatial ◽  
Airborne Geophysical Data

Abstract. We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow and Ku-band radar and optical imagery acquired in 2014, 2016 and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88° S as this is a bias validation site for ICESat-2 and may be a potential validation site for CryoSat-2. We find significant small–scale variability (

Small-scale temporal and spatial variability in the erosion threshold and properties of cohesive intertidal sediments

2006 ◽  
Vol 26 (3) ◽  
pp. 351-362 ◽  
Author(s):  
T.J. Tolhurst ◽  
E.C. Defew ◽  
J.F.C. de Brouwer ◽  
K. Wolfstein ◽  
L.J. Stal ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Small Scale ◽  
Intertidal Sediments ◽  
Erosion Threshold ◽  
Temporal And Spatial Variability ◽  
Temporal And Spatial

Small-scale temporal and spatial variability in the abundance of plastic pellets on sandy beaches: Methodological considerations for estimating the input of microplastics

2016 ◽  
Vol 102 (1) ◽  
pp. 114-121 ◽  
Author(s):  
Fabiana Tavares Moreira ◽  
Alessandro Lívio Prantoni ◽  
Bruno Martini ◽  
Michelle Alves de Abreu ◽  
Sérgio Biato Stoiev ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Sandy Beaches ◽  
Small Scale ◽  
Temporal And Spatial Variability ◽  
Temporal And Spatial ◽  
Methodological Considerations ◽  
Plastic Pellets

scholarly journals Temporal and spatial variability of snow accumulation in central Greenland

1997 ◽  
Vol 102 (D25) ◽  
pp. 30059-30068 ◽  
Author(s):  
H. Kuhns ◽  
C. Davidson ◽  
J. Dibb ◽  
C. Stearns ◽  
M. Bergin ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Snow Accumulation ◽  
Temporal And Spatial Variability ◽  
Temporal And Spatial

scholarly journals “WEBSNOW”: ESTIMATION OF SNOW COVER FROM FREELY ACCESSIBLE WEBCAM IMAGES IN THE ALPS

2020 ◽  
Vol V-2-2020 ◽  
pp. 695-701
Author(s):  
S. Flöry ◽  
C. Ressl ◽  
M. Hollaus ◽  
G. Pürcher ◽  
L. Piermattei ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Temporal Resolution ◽  
Small Scale ◽  
Mountain Areas ◽  
Processing Times ◽  
Temporal And Spatial Variability ◽  
The Alps ◽  
Temporal And Spatial ◽  
Aerial Platforms

Abstract. The alpine snow cover exhibits a high spatial variability in the horizontal and vertical directions even on a very small scale, mainly caused by the high variability of alpine terrain. To quantify the annual and inter-annual snow dynamics continuously reliable measurements of the temporal and spatial variability are required. While remote sensing from satellite and aerial platforms have been successfully used to estimate snow cover at larger scales, especially in mountain areas spatial and temporal resolution are too low to capture local changes. In the alpine region, webcam images are freely available for touristic purposes capturing images at high frequency intervals. Within the WebSnow project the feasibility of using such images for the detection of snow was investigated. With the developed workflow, processing times could be reduced and satisfactory results obtained. Our results show, that webcam networks have the potential for monitoring snow at high spatial and temporal resolution.

scholarly journals Global distributions of overlapping gravity waves in HIRDLS data

2015 ◽  
Vol 15 (14) ◽  
pp. 8459-8477 ◽  
Author(s):  
C. J. Wright ◽  
S. M. Osprey ◽  
J. C. Gille
Keyword(s):  
Gravity Wave ◽  
Gravity Waves ◽  
Spectral Characteristics ◽  
Small Scale ◽  
Spectral Form ◽  
Broadband Emission ◽  
Temporal And Spatial Variability ◽  
Abstract Data ◽  
Temporal And Spatial ◽  
Wave Phenomena

Abstract. Data from the High Resolution Dynamics Limb Sounder (HIRDLS) instrument on NASA's Aura satellite are used to investigate the relative numerical variability of observed gravity wave packets as a function of both horizontal and vertical wavenumber, with support from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on TIMED. We see that these distributions are dominated by large vertical and small horizontal wavenumbers, and have a similar spectral form at all heights and latitudes, albeit with important differences. By dividing our observed wavenumber distribution into particular subspecies of waves, we demonstrate that these distributions exhibit significant temporal and spatial variability, and that small-scale variability associated with particular geophysical phenomena such as the monsoon arises due to variations in specific parts of the observed spectrum. We further show that the well-known Andes/Antarctic Peninsula gravity wave hotspot during southern winter, home to some of the largest wave fluxes on the planet, is made up of relatively few waves, but with a significantly increased flux per wave due to their spectral characteristics. These results have implications for the modelling of gravity wave phenomena.

scholarly journals Global distributions of overlapping gravity waves in HIRDLS data

2015 ◽  
Vol 15 (4) ◽  
pp. 4333-4382 ◽  
Author(s):  
C. J. Wright ◽  
S. M. Osprey ◽  
J. C. Gille
Keyword(s):  
Spatial Variability ◽  
Gravity Wave ◽  
Gravity Waves ◽  
Spectral Characteristics ◽  
Small Scale ◽  
Spectral Form ◽  
Temporal And Spatial Variability ◽  
Abstract Data ◽  
Temporal And Spatial ◽  
Wave Phenomena

Abstract. Data from the HIRDLS instrument on NASA's Aura satellite are used to investigate the relative numerical variability of observed gravity wave packets as a function of both horizontal and vertical wavenumber, with support from the SABER instrument on TIMED. We see that these distributions are dominated by small vertical and large horizontal wavenumbers, and have a similar spectral form at all heights and latitudes, albeit with important differences. By dividing our observed wavenumber distribution into particular subspecies of wave, we demonstrate that these distributions exhibit significant temporal and spatial variability, and that small-scale variability associated with particular geophysical phenomena such as the monsoon arises due to variations in specific parts of the observed spectrum. We further show that the well-known Andes/Antarctic Pensinsula gravity wave hotspot during southern winter, home to some of the largest wave fluxes on the planet, is made up of relatively few waves, but with a significantly increased flux per wave due to their spectral characteristics. These results have implications for the modelling of gravity wave phenomena.

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