scholarly journals Comparison of historical and recent accumulation rates on Abramov Glacier, Pamir Alay

2020 ◽  
pp. 1-16
Author(s):  
Marlene Kronenberg ◽  
Horst Machguth ◽  
Anja Eichler ◽  
Margit Schwikowski ◽  
Martin Hoelzle
Keyword(s):  
Ground Truth ◽  
Mass Gain ◽  
High Mountain ◽  
Accumulation Rates ◽  
Northern Margin ◽  
In Situ Data ◽  
Limited Mass ◽  
Radar Measurements ◽  
Ground Penetrating

Abstract Glaciers located in western High Mountain Asia (HMA) have shown mass gain or limited mass losses compared to other mountain regions since ~2000. Increases in accumulation may be responsible. Although no contemporary measurements exist to explore this hypothesis, extensive historic measurements including firn density, stratigraphy and accumulation rates at ~4400 m a.s.l. on Abramov Glacier, Pamir Alay, provide valuable indications of accumulation changes. Abramov Glacier is located at the northern margin of western HMA. In this study, we assess unique historical firn data of Abramov Glacier from the 1970s to evaluate past firn conditions in this data sparse region. The current firn state is investigated based on a series of in situ measurements including firn cores and ground-penetrating radar measurements performed in 2018. We compare the legacy data with contemporary firn characteristics. Our results indicate a high year-to-year variability, but generally increasing net accumulation during the last 60 years on Abramov Glacier, with 0.84 ± 0.22 m w.e. for 2011–18 compared to 0.68 ± 0.32 m w.e. for 1965–72 and 0.59 ± 0.22 m w.e. for 1970–97. These results from in situ data provide ground truth for the data-sparse western HMA.

scholarly journals Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness

2020 ◽  
Vol 12 (4) ◽  
pp. 650
Author(s):  
Pablo Sánchez-Gámez ◽  
Carolina Gabarro ◽  
Antonio Turiel ◽  
Marcos Portabella
Keyword(s):  
Soil Moisture ◽  
Sea Ice ◽  
Brightness Temperature ◽  
European Space Agency ◽  
Ground Truth ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
In Situ Data ◽  
L Band

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) missions are providing brightness temperature measurements at 1.4 GHz (L-band) for about 10 and 4 years respectively. One of the new areas of geophysical exploitation of L-band radiometry is on thin (i.e., less than 1 m) Sea Ice Thickness (SIT), for which theoretical and empirical retrieval methods have been proposed. However, a comprehensive validation of SIT products has been hindered by the lack of suitable ground truth. The in-situ SIT datasets most commonly used for validation are affected by one important limitation: They are available mainly during late winter and spring months, when sea ice is fully developed and the thickness probability density function is wider than for autumn ice and less representative at the satellite spatial resolution. Using Upward Looking Sonar (ULS) data from the Woods Hole Oceanographic Institution (WHOI), acquired all year round, permits overcoming the mentioned limitation, thus improving the characterization of the L-band brightness temperature response to changes in thin SIT. State-of-the-art satellite SIT products and the Cumulative Freezing Degree Days (CFDD) model are verified against the ULS ground truth. The results show that the L-band SIT can be meaningfully retrieved up to 0.6 m, although the signal starts to saturate at 0.3 m. In contrast, despite the simplicity of the CFDD model, its predicted SIT values correlate very well with the ULS in-situ data during the sea ice growth season. The comparison between the CFDD SIT and the current L-band SIT products shows that both the sea ice concentration and the season are fundamental factors influencing the quality of the thickness retrieval from L-band satellites.

scholarly journals Triple-frequency radar retrieval of microphysical properties of snow

2021 ◽  
Vol 14 (11) ◽  
pp. 7243-7254
Author(s):  
Kamil Mroz ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew Heymsfield ◽  
Alain Protat ◽  
...  
Keyword(s):  
Water Content ◽  
Radar Data ◽  
Characteristic Size ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
Radar Measurements ◽  
Highly Correlated ◽  
Mean Square Errors

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterised by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment For Future Precipitation Mission. During this campaign, in situ microphysical probes were mounted on the same aeroplane as the radars. This nearly perfectly co-located dataset of the remote and in situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content (IWC) and mean mass-weighted diameters obtaining root-mean-square errors of 0.13 and 0.15, respectively, for log 10IWC and log 10Dm. The retrieval of the degree of riming is more challenging, and only the algorithm that uses Doppler information obtains results that are highly correlated with the in situ data.

scholarly journals Combining MODIS, AVHRR and in situ data for evapotranspiration estimation over heterogeneous landscape of the Tibetan Plateau

2014 ◽  
Vol 14 (3) ◽  
pp. 1507-1515 ◽  
Author(s):  
Y. Ma ◽  
Z. Zhu ◽  
L. Zhong ◽  
B. Wang ◽  
C. Han ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Ground Truth ◽  
The Tibetan Plateau ◽  
Evaporative Fraction ◽  
Modis Data ◽  
In Situ Data ◽  
Heterogeneous Landscape ◽  
Wide Range ◽  
Avhrr Data

Abstract. In this study, a parameterization method based on MODIS (Moderate Resolution Imaging Spectroradiometer) data, AVHRR (Advanced Very High-Resolution Radiometer) data and in situ data is introduced and tested for estimating the regional evaporative fraction Λ over a heterogeneous landscape. As a case study, the algorithm was applied to the Tibetan Plateau (TP) area. Eight MODIS data images (17 January, 14 April, 23 July and 16 October in 2003; 30 January, 15 April, 1 August and 25 October in 2007) and four AVHRR data images (17 January, 14 April, 23 July and 16 October in 2003) were used in this study to compare winter, spring, summer and autumn values and for annual variation analysis. The results were validated using the "ground truth" measured at Tibetan Observation and Research Platform (TORP) and the CAMP/Tibet (CEOP (Coordinated Enhanced Observing Period) Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau) meteorological stations. The results show that the estimated evaporative fraction Λ in the four different seasons over the TP is in clear accordance with the land surface status. The Λ fractions show a wide range due to the strongly contrasting surface features found on the TP. Also, the estimated Λ values are in good agreement with "ground truth" measurements, and their absolute percentage difference (APD) is less than 10.0% at the validation sites. The AVHRR data were also in agreement with the MODIS data, with the latter usually displaying a higher level of accuracy. It was therefore concluded that the proposed algorithm was successful in retrieving the evaporative fraction Λ using MODIS, AVHRR and in situ data over the TP. MODIS data are the most accurate and should be used widely in evapotranspiration (ET) research in this region.

scholarly journals Sea Surface Salinity Seasonal Variability in the Tropics from Satellites, Gridded In Situ Products and Mooring Observations

2020 ◽  
Vol 13 (1) ◽  
pp. 110
Author(s):  
Frederick M. Bingham ◽  
Susannah Brodnitz ◽  
Lisan Yu
Keyword(s):  
Seasonal Variability ◽  
Ground Truth ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Zero Bias ◽  
In Situ Data ◽  
The Tropics ◽  
Good Agreement

Satellite observations of sea surface salinity (SSS) have been validated in a number of instances using different forms of in situ data, including Argo floats, moorings and gridded in situ products. Since one of the most energetic time scales of variability of SSS is seasonal, it is important to know if satellites and gridded in situ products are observing the seasonal variability correctly. In this study we validate the seasonal SSS from satellite and gridded in situ products using observations from moorings in the global tropical moored buoy array. We utilize six different satellite products, and two different gridded in situ products. For each product we have computed seasonal harmonics, including amplitude, phase and fraction of variance (R2). These quantities are mapped for each product and for the moorings. We also do comparisons of amplitude, phase and R2 between moorings and all the satellite and gridded in situ products. Taking the mooring observations as ground truth, we find general good agreement between them and the satellite and gridded in situ products, with near zero bias in phase and amplitude and small root mean square differences. Tables are presented with these quantities for each product quantifying the degree of agreement.

scholarly journals Triple frequency radar retrieval of microphysical properties of snow

2021 ◽  
Author(s):  
Kamil Mroz ◽  
Alessandro Battaglia ◽  
Cuong Nguyen ◽  
Andrew Heymsfield ◽  
Alain Protat ◽  
...  
Keyword(s):  
Water Content ◽  
Radar Data ◽  
Characteristic Size ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Triple Frequency ◽  
Radar Measurements ◽  
Highly Correlated ◽  
Ice Water

Abstract. An algorithm based on triple-frequency (X, Ka, W) radar measurements that retrieves the size, water content and degree of riming of ice clouds is presented. This study exploits the potential of multi-frequency radar measurements to provide information on bulk snow density that should underpin better estimates of the snow characteristic size and content within the radar volume. The algorithm is based on Bayes' rule with riming parameterized by the “fill-in” model. The radar reflectivities are simulated with a range of scattering models corresponding to realistic snowflake shapes. The algorithm is tested on multi-frequency radar data collected during the ESA-funded Radar Snow Experiment. During this campaign in-situ microphysical probes were mounted on the same airplane as the radars. This nearly perfectly collocated dataset of the remote and in-situ measurements gives an opportunity to derive a combined multi-instrument estimate of snow microphysical properties that is used for a rigorous validation of the radar retrieval. Results suggest that the triple-frequency retrieval performs well in estimating ice water content and mean-mass-weighted diameters obtaining root-mean-square-error of 0.13 and 0.15, respectively for log10 IWC and log10 Dm. The retrieval of the degree of riming is more challenging and only the algorithm that uses Doppler information obtains results that are highly correlated with the in-situ data.

scholarly journals Uncertainty Assessment of Ice Discharge Using GPR-Derived Ice Thickness from Gourdon Glacier, Antarctic Peninsula

Geosciences ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 12 ◽  
Author(s):  
Stefan Lippl ◽  
Norbert Blindow ◽  
Johannes J. Fürst ◽  
Sebastián Marinsek ◽  
Thorsten C. Seehaus ◽  
...  
Keyword(s):  
Uncertainty Assessment ◽  
In Situ Measurements ◽  
Ice Thickness ◽  
Outlet Glacier ◽  
In Situ Data ◽  
Continuity Equations ◽  
Reconstruction Methods ◽  
A Minor ◽  
Ground Penetrating

Ice cliffs within a glacier represent a challenge for the continuity equations used in many glacier models by interrupting the validity of input parameters. In the case of Gourdon Glacier on James Ross Island, Antarctica, a ∼300–500 m high, almost vertical cliff, separates the outlet glacier from its main accumulation area on the plateau of the island. In 2017 and 2018 we conducted ice thickness measurements during two airborne ground penetrating radar campaigns in order to evaluate differences to older measurements from the 1990s. The observed differences are mostly smaller than the estimated error bars. In comparison to the in situ data, the published “consensus ice thickness estimate” strongly overestimates the ice thickness at the outlet. We analyse three different interpolation and ice thickness reconstruction methods. One approach additionally includes the mass input from the plateau. Differences between the interpolation methods have a minor impact on the ice discharge estimation if the used flux gates are in areas with a good coverage of in situ measurements. A much stronger influence was observed by uncertainties in the glacier velocities derived from remote sensing, especially in the direction of the velocity vector in proximity to the ice cliff. We conclude that the amount of in situ measurements should be increased for specific glacier types in order to detect biases in modeled ice thickness and ice discharge estimations.

Ice thickness measurements of the debris covered Ngozumpa glacier, Nepal

2020 ◽  
Author(s):  
Lindsey Nicholson ◽  
Fabien Maussion ◽  
Christoph Mayer ◽  
Hamish Pritchard ◽  
Astrid Lambrecht ◽  
...  
Keyword(s):  
Field Measurements ◽  
Rate Of Change ◽  
Ice Thickness ◽  
High Mountain ◽  
Global Consensus ◽  
Glacier Ice ◽  
Radar Measurements ◽  
Global Sea Level ◽  
Ground Penetrating ◽  
Thickness Measurements

<p>The presence of extensive debris cover on glaciers in parts of High Mountain Asia increases the certainty about the present day amount of ice, its ongoing rate of change and resultant impact on global sea level rise, regional water and local hazards<br><br>Here we use ground penetrating radar measurements of ice thickness for the Ngozumpa glacier, a large debris-covered glacier in Nepal, to explore the challenges of using such data to calculate glacier volume, and to compare how these field measurements compare to the modelled glacier thickness for this glacier generated by the four models used in the global consensus glacier ice thickness dataset, which suggested the region holds 27% less ice than previous estimates (Farinotti and others, 2019). We also compare the ice thickness measured at Ngozumpa glacier to existing data from the smaller neighboring Khumbu glacier and evaluate the maximum volume of a possible moraine dammed lake at this site.</p>

scholarly journals Consistency of Radiometric Satellite Data over Lakes and Coastal Waters with Local Field Measurements

2020 ◽  
Vol 12 (4) ◽  
pp. 616 ◽  
Author(s):  
Krista Alikas ◽  
Ilmar Ansko ◽  
Viktor Vabson ◽  
Ave Ansper ◽  
Kersti Kangro ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Field Measurements ◽  
Ground Truth ◽  
Local Data ◽  
Ground Truth Data ◽  
In Situ Data ◽  
Global Coverage

The Sentinel-3 mission launched its first satellite Sentinel-3A in 2016 to be followed by Sentinel-3B and Sentinel-3C to provide long-term operational measurements over Earth. Sentinel-3A and 3B are in full operational status, allowing global coverage in less than two days, usable to monitor optical water quality and provide data for environmental studies. However, due to limited ground truth data, the product quality has not yet been analyzed in detail with the fiducial reference measurement (FRM) dataset. Here, we use the fully characterized ground truth FRM dataset for validating Sentinel-3A Ocean and Land Colour Instrument (OLCI) radiometric products over optically complex Estonian inland waters and Baltic Sea coastal areas. As consistency between satellite and local data depends on uncertainty in field measurements, filtering of the in situ data has been made based on the uncertainty for the final comparison. We have compared various atmospheric correction methods and found POLYMER (POLYnomial-based algorithm applied to MERIS) to be most suitable for optically complex waters under study in terms of product accuracy, amount of usable data and also being least influenced by the adjacency effect.

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