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936 KiB

Open AccessArticle

Estimation of Mass Balance of the Grosser Aletschgletscher, Swiss Alps, from ICESat Laser Altimetry Data and Digital Elevation Models

by Jan Kropáček, Niklas Neckel and Andreas Bauder

Remote Sens. 2014, 6(6), 5614-5632; https://doi.org/10.3390/rs6065614 - 17 Jun 2014

Cited by 25 | Viewed by 7603

Abstract

Traditional glaciological mass balance measurements of mountain glaciers are a demanding and cost intensive task. In this study, we combine data from the Ice Cloud and Elevation Satellite (ICESat) acquired between 2003 and 2009 with air and space borne Digital Elevation Models (DEMs) [...] Read more.

Traditional glaciological mass balance measurements of mountain glaciers are a demanding and cost intensive task. In this study, we combine data from the Ice Cloud and Elevation Satellite (ICESat) acquired between 2003 and 2009 with air and space borne Digital Elevation Models (DEMs) in order to derive surface elevation changes of the Grosser Aletschgletscher in the Swiss Alps. Three different areas of the glacier are covered by one nominal ICESat track, allowing us to investigate the performance of the approach under different conditions in terms of ICESat data coverage, and surface characteristics. In order to test the sensitivity of the derived trend in surface lowering, several variables were tested. Employing correction for perennial snow accumulation, footprint selection and adequate reference DEM, we estimated a mean mass balance of −0.92 ± 0.18 m w.e. a⁻¹. for the whole glacier in the studied time period. The resulting mass balance was validated by a comparison with another geodetic approach based on the subtraction of two DEMs for the years 1999 and 2009. It appears that the processing parameters need to be selected depending on the amount of available ICESat measurements, quality of the elevation reference and character of the glacier surface. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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29314 KiB

Open AccessArticle

Investigating High-Resolution AMSR2 Sea Ice Concentrations during the February 2013 Fracture Event in the Beaufort Sea

by Alexander Beitsch, Lars Kaleschke and Stefan Kern

Remote Sens. 2014, 6(5), 3841-3856; https://doi.org/10.3390/rs6053841 - 29 Apr 2014

Cited by 84 | Viewed by 14017

Abstract

Leads with a length on the order of 1000 km occurred in the Beaufort Sea in February 2013. These leads can be observed in Moderate Resolution Imaging Spectroradiometer (MODIS) images under predominantly clear sky conditions. Sea ice concentrations (SIC) derived from the Advanced [...] Read more.

Leads with a length on the order of 1000 km occurred in the Beaufort Sea in February 2013. These leads can be observed in Moderate Resolution Imaging Spectroradiometer (MODIS) images under predominantly clear sky conditions. Sea ice concentrations (SIC) derived from the Advanced Microwave Scanning Radiometer 2 (AMSR2) using the Bootstrap (BST) algorithm fail to show the lead occurrences, as is visible in the MODIS images. In contrast, SIC derived from AMSR2 using the Arctic Radiation and Turbulence Interaction Study (ARTIST) sea ice algorithm (ASI) reveal the lead structure, due to the higher spatial resolution possible when using 89-GHz channel data. The ASI SIC are calculated from brightness temperatures interpolated on three different grids with resolutions of 3.125 km (ASI-3k), 6.25 km (ASI-6k) and 12.5 km (ASI-12k) to investigate the effect of the spatial resolution. Single-swath data is used to study the effect of temporal sampling in comparison to daily averages. For a region of interest in the Beaufort Sea, BST and ASI-3k show area-averaged SIC of 97%±0.7% and 93%±7.0%, respectively. For ASI-6k, the area-averaged SIC are similar to ASI-3k, while ASI-12k data show more agreement with BST. Visual comparison with MODIS True Color imagery exhibits good agreement with ASI-3k. In particular, ASI-3k are able to reproduce lead structure and size in the sea ice cover, which are not or are less visible in the other SIC data. The results will be valuable for selecting a SIC data product for studies of the interaction between ocean, ice, and atmosphere in the polar regions. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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1882 KiB

Open AccessArticle

Identification of Soil Freezing and Thawing States Using SAR Polarimetry at C-Band

by Thomas Jagdhuber, Julia Stockamp, Irena Hajnsek and Ralf Ludwig

Remote Sens. 2014, 6(3), 2008-2023; https://doi.org/10.3390/rs6032008 - 05 Mar 2014

Cited by 36 | Viewed by 8970

Abstract

The monitoring of soil freezing and thawing states over large areas is very challenging on ground. In order to investigate the potential and the limitations of space-borne SAR polarimetry at C-band for soil state survey, analyses were conducted on an entire winter time [...] Read more.

The monitoring of soil freezing and thawing states over large areas is very challenging on ground. In order to investigate the potential and the limitations of space-borne SAR polarimetry at C-band for soil state survey, analyses were conducted on an entire winter time series of fully polarimetric RADARSAT-2 data from 2011/2012 to identify freezing as well as thawing states within the soil. The polarimetric data were acquired over the Sodankylä test site in Finland together with in situ measurements of the soil and the snow cover. The analyses indicate clearly that the dynamics of the polarimetric entropy and mean scattering alpha angle are directly correlated to soil freezing and thawing states, even under distinct dry snow cover. First modeling attempts using the Extended Bragg soil scattering model justify the observed trends, which indicate surface-like scattering during frozen soil conditions and multiple/volume scattering for thawed soils. Hence, these first investigations at C-band foster motivation to work towards a robust polarimetric detection of soil freezing and thawing states as well as their transition phase. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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5226 KiB

Open AccessArticle

A Nine-Year Climatology of Arctic Sea Ice Lead Orientation and Frequency from AMSR-E

by David Bröhan and Lars Kaleschke

Remote Sens. 2014, 6(2), 1451-1475; https://doi.org/10.3390/rs6021451 - 18 Feb 2014

Cited by 32 | Viewed by 9022

Abstract

We infer the fractional coverage of sea ice leads (as concentration) in the Arctic from Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E) brightness temperatures. The lead concentration resolves leads of at least 3 km in width. We introduce a new [...] Read more.

We infer the fractional coverage of sea ice leads (as concentration) in the Arctic from Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E) brightness temperatures. The lead concentration resolves leads of at least 3 km in width. We introduce a new algorithm based on the progressive probabilistic Hough transform to automatically infer lead positions and orientations from daily AMSR-E satellite observations. Because the progressive probabilistic Hough transform often detects an identical lead several times the algorithm clusters neighboring leads that belong to one lead position. A first comparison of automatically detected lead positions and orientations with manually detected lead positions and orientations reveals that 57% of the reference leads are correctly determined. Around 11% of automatically detected leads are located where no reference lead occurs. The automatically detected lead orientations are distributed slightly differently from the reference lead orientations. A second comparison of automatically detected leads in the Fram Strait to leads in a wide swath mode Advanced Synthetic Aperture Radar scene shows a good agreement. We provide an Arctic-wide time series of lead orientations for winters from 2002 to 2011. For example, while a lead orientation of 110° with respect to the Greenwich meridian prevails in the Fram Strait, lead orientations in the Beaufort Sea are more isotropically distributed. We find significant preferred lead orientations almost everywhere in the Arctic Ocean when averaged over the entire AMSR-E time series. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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517 KiB

Open AccessArticle

Estimating Temperature Fields from MODIS Land Surface Temperature and Air Temperature Observations in a Sub-Arctic Alpine Environment

by Scott N. Williamson, David S. Hik, John A. Gamon, Jeffrey L. Kavanaugh and Gwenn E. Flowers

Remote Sens. 2014, 6(2), 946-963; https://doi.org/10.3390/rs6020946 - 24 Jan 2014

Cited by 67 | Viewed by 10361

Abstract

Spatially continuous satellite infrared temperature measurements are essential for understanding the consequences and drivers of change, at local and regional scales, especially in northern and alpine environments dominated by a complex cryosphere where in situ observations are scarce. We describe two methods for [...] Read more.

Spatially continuous satellite infrared temperature measurements are essential for understanding the consequences and drivers of change, at local and regional scales, especially in northern and alpine environments dominated by a complex cryosphere where in situ observations are scarce. We describe two methods for producing daily temperature fields using MODIS “clear-sky” day-time Land Surface Temperatures (LST). The Interpolated Curve Mean Daily Surface Temperature (ICM) method, interpolates single daytime Terra LST values to daily means using the coincident diurnal air temperature curves. The second method calculates daily mean LST from daily maximum and minimum LST (MMM) values from MODIS Aqua and Terra. These ICM and MMM models were compared to daily mean air temperatures recorded between April and October at seven locations in southwest Yukon, Canada, covering characteristic alpine land cover types (tundra, barren, glacier) at elevations between 1,408 m and 2,319 m. Both methods for producing mean daily surface temperatures have advantages and disadvantages. ICM signals are strongly correlated with air temperature (R² = 0.72 to 0.86), but have relatively large variability (RMSE = 4.09 to 4.90 K), while MMM values had a stronger correlation to air temperature (R² = 0.90) and smaller variability (RMSE = 2.67 K). Finally, when comparing 8-day LST averages, aggregated from the MMM method, to air temperature, we found a high correlation (R² = 0.84) with less variability (RMSE = 1.54 K). Where the trend was less steep and the y-intercept increased by 1.6 °C compared to the daily correlations. This effect is likely a consequence of LST temperature averages being differentially affected by cloud cover over warm and cold surfaces. We conclude that satellite infrared skin temperature (e.g., MODIS LST), which is often aggregated into multi-day composites to mitigate data reductions caused by cloud cover, changes in its relationship to air temperature depending on the period of aggregation. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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3021 KiB

Open AccessArticle

Melt Patterns and Dynamics in Alaska and Patagonia Derived from Passive Microwave Brightness Temperatures

by Kathryn Semmens and Joan Ramage

Remote Sens. 2014, 6(1), 603-620; https://doi.org/10.3390/rs6010603 - 06 Jan 2014

Cited by 3 | Viewed by 6737

Abstract

Glaciers and icefields are critical components of Earth’s cryosphere to study and monitor for understanding the effects of a changing climate. To provide a regional perspective of glacier melt dynamics for the past several decades, brightness temperatures (T_b) from the passive [...] Read more.

Glaciers and icefields are critical components of Earth’s cryosphere to study and monitor for understanding the effects of a changing climate. To provide a regional perspective of glacier melt dynamics for the past several decades, brightness temperatures (T_b) from the passive microwave sensor Special Sensor Microwave Imager (SSM/I) were used to characterize melt regime patterns over large glacierized areas in Alaska and Patagonia. The distinctness of the melt signal at 37V-GHz and the ability to acquire daily data regardless of clouds or darkness make the dataset ideal for studying melt dynamics in both hemispheres. A 24-year (1988–2011) time series of annual T_b histograms was constructed to (1) characterize and assess temporal and spatial trends in melt patterns, (2) determine years of anomalous T_b distribution, and (3) investigate potential contributing factors. Distance from coast and temperature were key factors influencing melt. Years of high percentage of positive T_b anomalies were associated with relatively higher stream discharge (e.g., Copper and Mendenhall Rivers, Alaska, USA and Rio Baker, Chile). The characterization of melt over broad spatial domains and a multi-decadal time period offers a more comprehensive picture of the changing cryosphere and provides a baseline from which to assess future change. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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7121 KiB

Open AccessArticle

Calving Fronts of Antarctica: Mapping and Classification

by Christine Wesche, Daniela Jansen and Wolfgang Dierking

Remote Sens. 2013, 5(12), 6305-6322; https://doi.org/10.3390/rs5126305 - 25 Nov 2013

Cited by 28 | Viewed by 11674

Abstract

Antarctica is surrounded by a variety of large, medium and small sized ice shelves, glacier tongues and coastal areas without offshore floating ice masses. We used the mosaic of the Radarsat-1 Antarctica Mapping Project (RAMP) Antarctic Mapping Mission 1 (AMM) to classify the [...] Read more.

Antarctica is surrounded by a variety of large, medium and small sized ice shelves, glacier tongues and coastal areas without offshore floating ice masses. We used the mosaic of the Radarsat-1 Antarctica Mapping Project (RAMP) Antarctic Mapping Mission 1 (AMM) to classify the coastline of Antarctica in terms of surface structure patterns close to the calving front. With the aid of an automated edge detection method, complemented by manual control, the surface structures of all ice shelves and glacier tongues around Antarctica were mapped. We found dense and less dense patterns of surface structures unevenly distributed over the ice shelves and ice tongues. Dense surface patterns are frequent on fast flowing ice masses (ice streams), whereas most ice shelves show a dense surface pattern only close to the grounding line. Flow line analyses on ten ice shelves reveal that the time of residence of the ice along a flow path and—associated with it—the healing of surface crevasses can explain the different surface structure distribution close to the grounding line and the calving front on many ice shelves. Based on the surface structures relative to the calving front within a 15 km-wide seaward strip, the ice shelf fronts can be separated into three classes. The resulting map of the classified calving fronts around Antarctica and their description provide a detailed picture of crevasse formation and the observed dominant iceberg shapes. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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Review

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1233 KiB

Open AccessReview

Open Access Data in Polar and Cryospheric Remote Sensing

by Allen Pope, W. Gareth Rees, Adrian J. Fox and Andrew Fleming

Remote Sens. 2014, 6(7), 6183-6220; https://doi.org/10.3390/rs6076183 - 01 Jul 2014

Cited by 30 | Viewed by 15103

Abstract

This paper aims to introduce the main types and sources of remotely sensed data that are freely available and have cryospheric applications. We describe aerial and satellite photography, satellite-borne visible, near-infrared and thermal infrared sensors, synthetic aperture radar, passive microwave imagers and active [...] Read more.

This paper aims to introduce the main types and sources of remotely sensed data that are freely available and have cryospheric applications. We describe aerial and satellite photography, satellite-borne visible, near-infrared and thermal infrared sensors, synthetic aperture radar, passive microwave imagers and active microwave scatterometers. We consider the availability and practical utility of archival data, dating back in some cases to the 1920s for aerial photography and the 1960s for satellite imagery, the data that are being collected today and the prospects for future data collection; in all cases, with a focus on data that are openly accessible. Derived data products are increasingly available, and we give examples of such products of particular value in polar and cryospheric research. We also discuss the availability and applicability of free and, where possible, open-source software tools for reading and processing remotely sensed data. The paper concludes with a discussion of open data access within polar and cryospheric sciences, considering trends in data discoverability, access, sharing and use. Full article

(This article belongs to the Special Issue Cryospheric Remote Sensing)

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