Sea ice drift was measured by Surface Velocity Profiler 2019P88, an autonomous platform, installe... more Sea ice drift was measured by Surface Velocity Profiler 2019P88, an autonomous platform, installed on drifting sea ice in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The time series describes the position and additional parameters of the buoy between 07 Oct 2019 and 06 March 2020 in sample intervals of 10 minutes. The data set has been processed, including the flagging of obvious inconsistencies in position. The position is flagged if the drift velocity exceeds a threshold (Quality flag, position = 1), if the position exceeds extreme values, such as longitutde > 360 deg (Quality flag, position = 2), and if the position is exactly 0.0 (Quality flag, position = 4). These quality flag values can be sums of each other.
[1] Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates ... more [1] Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004–2008); airborne electromagnetic measurements (2001–2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992–2008) and from submarines (1975–2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982–1986) and coastal stations (1998–2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than $2 m and underestimate the thickness of ice measured thicker than about $2 m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25–30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models. Citation: Johnson, M., et al. (2012), Evaluation of Arctic sea ice thickness simulated by Arctic Ocean Model Intercomparison Project models,
... signal snow thick-ness measurements and brightness temperatures at 11, 21 and 35 GHz with dif... more ... signal snow thick-ness measurements and brightness temperatures at 11, 21 and 35 GHz with different incidence angles and polarizations were performed over sea ice in the Kara and Laptev ... [2] R. Fuhrhop, G.Heygster, K.-P.Johnsen, P.Schliisse1, M.Schrader, and C.Simmer. ...
With five years of successful helicopter electromagnetic (HEM) sea ice thickness measurements the... more With five years of successful helicopter electromagnetic (HEM) sea ice thickness measurements the Alfred Wegener Institute (AWI) decided to construct an EM platform on a fixed wing aircraft in an attempt to overcome the helicopter flight range restrictions. The system operates in the frequency domain with 1990 Hz and a vertical coplanar coil configuration. The primary field voltage is electrically attenuated on the receiver coil which allows for increased amplification and resolution of the much smaller amplitude secondary field voltage. Before data are converted to ice thickness a correction for electronic drift and orientation effects is applied. First test flights show that the ice thickness accuracy of the fixed-wing system lies only between 1 m and 2.5 m in comparison to 0.1 m for the HEM systems. The lower accuracy is probably caused by electrical noise of the airplane engines and coil motion.
Regular observation of Arctic and Antarctic sea ice thickness is of high importance for a better ... more Regular observation of Arctic and Antarctic sea ice thickness is of high importance for a better understanding of processes of climate change in polar regions. For regular and accurate observations of polar sea ice thickness a long range airborne device is necessary. Airborne electromagnetic induction (AEM) sounding was found to be an ideal method for accurate and wide area sea ice thickness measurements. As a consequence of five years of successful helicopter electromagnetic (HEM) sea ice thickness measurements and to overcome helicopter range restrictions, the Alfred Wegener Institute (AWI) constructed a new airplane based fixed wing EM system. The first test flights were carried out in 2006 over the North Sea and in April 2007 in Svalbard, where the system's performance was proven under arctic conditions. The system operates in frequency domain with 1990 Hz and a vertical coplanar coil configuration. Thus the system produces a horizontal dipole. The coils are mounted beneath ...
Using in situ data from 2011 and 2013, we evaluate the ability of CryoSat-2 (CS-2) to retrieve se... more Using in situ data from 2011 and 2013, we evaluate the ability of CryoSat-2 (CS-2) to retrieve sea-ice freeboard over fast ice in McMurdo Sound. This provides the first systematic validation of CS-2 in the coastal Antarctic and offers insight into the assumptions currently used to process CS-2 data. European Space Agency Level 2 (ESAL2) data are compared with results of a Waveform Fitting (WfF) procedure and a Threshold-First-Maximum-Retracker-Algorithm employed at 40% (TFMRA40). A supervised freeboard retrieval procedure is used to reduce errors associated with sea surface height identification and radar velocity in snow. We find ESAL2 freeboards located between the ice and snow freeboard rather than the frequently assumed snow/ice interface. WfF is within 0.04 m of the ice freeboard but is influenced by variable snow conditions causing increased radar backscatter from the air/snow interface. Given such snow conditions and additional uncertainties in sea surface height identificati...
ABSTRACT We present sea-ice surface roughness estimates, i.e. the standard deviation of relative ... more ABSTRACT We present sea-ice surface roughness estimates, i.e. the standard deviation of relative surface elevation, in the Arctic regions of Fram Strait and the Nansen Basin north of Svalbard acquired by an airborne laser scanner and a single-beam laser altimeter in 2010. We compare the scanner to the altimeter and compare the differences between the two survey regions. We estimate and correct sensor roll from the scanner data using the hyperbolic response of the scanner over a flat surface. Measurement surveys had to be longer than 5 km north of Svalbard and longer than 15 km in Fram Strait before the statistical distribution in surface roughness from the scanner and altimeter became similar. The shape of the surface roughness probability distributions agrees with those of airborne electromagnetic induction measurements of ice thickness. The ice in Fram Strait had a greater mean surface roughness, 0.16 m vs 0.09 m, and a wider distribution in roughness values than the ice in the Nansen Basin. An increase in surface roughness with increasing ice thickness was observed over fast ice found in Fram Strait near the coast of Greenland but not for the drift ice.
Based on the surface morphology of sea ice in the Weddell Sea measured by a helicopter-borne lase... more Based on the surface morphology of sea ice in the Weddell Sea measured by a helicopter-borne laser altimeter during the Winter Weddell Outflow Study 2006, form drag on ice ridges and its contribution to total drag, and air-ice drag coefficient C dn (10) corresponding to 10m altitude under a neutral stability condition are studied using the drag partition theory. The results revealed that, for compacted ice field, form drag on ridges and its contribution to total drag both increase with ridging intensity (the ratio of mean sail height to mean spacing), while decrease with increasing roughness length. And this ratio to the total drag was 35% corresponding to the typical ridging intensity and roughness length in the winter Weddell Sea, indicating an important impact of form drag on ridges to the momentum exchange at the air-ice interface. Besides, there is an increasing trend of the drag coefficient C dn (10) with increasing ridging intensity. Meanwhile, C dn (10) increases for the sma...
Sea ice drift was measured by Surface Velocity Profiler 2019P88, an autonomous platform, installe... more Sea ice drift was measured by Surface Velocity Profiler 2019P88, an autonomous platform, installed on drifting sea ice in the Arctic Ocean during MOSAiC (Leg 1) 2019/20. The time series describes the position and additional parameters of the buoy between 07 Oct 2019 and 06 March 2020 in sample intervals of 10 minutes. The data set has been processed, including the flagging of obvious inconsistencies in position. The position is flagged if the drift velocity exceeds a threshold (Quality flag, position = 1), if the position exceeds extreme values, such as longitutde > 360 deg (Quality flag, position = 2), and if the position is exactly 0.0 (Quality flag, position = 4). These quality flag values can be sums of each other.
[1] Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates ... more [1] Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004–2008); airborne electromagnetic measurements (2001–2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992–2008) and from submarines (1975–2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982–1986) and coastal stations (1998–2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than $2 m and underestimate the thickness of ice measured thicker than about $2 m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25–30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models. Citation: Johnson, M., et al. (2012), Evaluation of Arctic sea ice thickness simulated by Arctic Ocean Model Intercomparison Project models,
... signal snow thick-ness measurements and brightness temperatures at 11, 21 and 35 GHz with dif... more ... signal snow thick-ness measurements and brightness temperatures at 11, 21 and 35 GHz with different incidence angles and polarizations were performed over sea ice in the Kara and Laptev ... [2] R. Fuhrhop, G.Heygster, K.-P.Johnsen, P.Schliisse1, M.Schrader, and C.Simmer. ...
With five years of successful helicopter electromagnetic (HEM) sea ice thickness measurements the... more With five years of successful helicopter electromagnetic (HEM) sea ice thickness measurements the Alfred Wegener Institute (AWI) decided to construct an EM platform on a fixed wing aircraft in an attempt to overcome the helicopter flight range restrictions. The system operates in the frequency domain with 1990 Hz and a vertical coplanar coil configuration. The primary field voltage is electrically attenuated on the receiver coil which allows for increased amplification and resolution of the much smaller amplitude secondary field voltage. Before data are converted to ice thickness a correction for electronic drift and orientation effects is applied. First test flights show that the ice thickness accuracy of the fixed-wing system lies only between 1 m and 2.5 m in comparison to 0.1 m for the HEM systems. The lower accuracy is probably caused by electrical noise of the airplane engines and coil motion.
Regular observation of Arctic and Antarctic sea ice thickness is of high importance for a better ... more Regular observation of Arctic and Antarctic sea ice thickness is of high importance for a better understanding of processes of climate change in polar regions. For regular and accurate observations of polar sea ice thickness a long range airborne device is necessary. Airborne electromagnetic induction (AEM) sounding was found to be an ideal method for accurate and wide area sea ice thickness measurements. As a consequence of five years of successful helicopter electromagnetic (HEM) sea ice thickness measurements and to overcome helicopter range restrictions, the Alfred Wegener Institute (AWI) constructed a new airplane based fixed wing EM system. The first test flights were carried out in 2006 over the North Sea and in April 2007 in Svalbard, where the system's performance was proven under arctic conditions. The system operates in frequency domain with 1990 Hz and a vertical coplanar coil configuration. Thus the system produces a horizontal dipole. The coils are mounted beneath ...
Using in situ data from 2011 and 2013, we evaluate the ability of CryoSat-2 (CS-2) to retrieve se... more Using in situ data from 2011 and 2013, we evaluate the ability of CryoSat-2 (CS-2) to retrieve sea-ice freeboard over fast ice in McMurdo Sound. This provides the first systematic validation of CS-2 in the coastal Antarctic and offers insight into the assumptions currently used to process CS-2 data. European Space Agency Level 2 (ESAL2) data are compared with results of a Waveform Fitting (WfF) procedure and a Threshold-First-Maximum-Retracker-Algorithm employed at 40% (TFMRA40). A supervised freeboard retrieval procedure is used to reduce errors associated with sea surface height identification and radar velocity in snow. We find ESAL2 freeboards located between the ice and snow freeboard rather than the frequently assumed snow/ice interface. WfF is within 0.04 m of the ice freeboard but is influenced by variable snow conditions causing increased radar backscatter from the air/snow interface. Given such snow conditions and additional uncertainties in sea surface height identificati...
ABSTRACT We present sea-ice surface roughness estimates, i.e. the standard deviation of relative ... more ABSTRACT We present sea-ice surface roughness estimates, i.e. the standard deviation of relative surface elevation, in the Arctic regions of Fram Strait and the Nansen Basin north of Svalbard acquired by an airborne laser scanner and a single-beam laser altimeter in 2010. We compare the scanner to the altimeter and compare the differences between the two survey regions. We estimate and correct sensor roll from the scanner data using the hyperbolic response of the scanner over a flat surface. Measurement surveys had to be longer than 5 km north of Svalbard and longer than 15 km in Fram Strait before the statistical distribution in surface roughness from the scanner and altimeter became similar. The shape of the surface roughness probability distributions agrees with those of airborne electromagnetic induction measurements of ice thickness. The ice in Fram Strait had a greater mean surface roughness, 0.16 m vs 0.09 m, and a wider distribution in roughness values than the ice in the Nansen Basin. An increase in surface roughness with increasing ice thickness was observed over fast ice found in Fram Strait near the coast of Greenland but not for the drift ice.
Based on the surface morphology of sea ice in the Weddell Sea measured by a helicopter-borne lase... more Based on the surface morphology of sea ice in the Weddell Sea measured by a helicopter-borne laser altimeter during the Winter Weddell Outflow Study 2006, form drag on ice ridges and its contribution to total drag, and air-ice drag coefficient C dn (10) corresponding to 10m altitude under a neutral stability condition are studied using the drag partition theory. The results revealed that, for compacted ice field, form drag on ridges and its contribution to total drag both increase with ridging intensity (the ratio of mean sail height to mean spacing), while decrease with increasing roughness length. And this ratio to the total drag was 35% corresponding to the typical ridging intensity and roughness length in the winter Weddell Sea, indicating an important impact of form drag on ridges to the momentum exchange at the air-ice interface. Besides, there is an increasing trend of the drag coefficient C dn (10) with increasing ridging intensity. Meanwhile, C dn (10) increases for the sma...
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