You do not present any uncertainties in the presented numbers, while the results clearly show a l... more You do not present any uncertainties in the presented numbers, while the results clearly show a large variability. P1 L14-19: Present this differently: first describe the process, then the result. Thus first that there exists a very persisten surface based temperature inversion driven by radiative cooling. P1 L21-22: Formulate more direct, this is not a new insight but already found for Antarctica. P1 L24-28: Formulate more direct: this is basically the new result of your research. Start with the why this is so interesting, then the result. Leave out the last sentence. This should already be clear.
Traditionally, the availability of in situ observations of ice surface temperature is very limite... more Traditionally, the availability of in situ observations of ice surface temperature is very limited and therefore satellite observations are very important for obtaining a spatially broad and continuous measurement of the ice surface temperature. However, today there is no fiducial reference measurement ice surface temperature (FRM IST) dataset that can be used for routine validation of satellite IST products. To establish the uncertainty budget for instruments in the Arctic, an inter-comparison of ice surface temperature drifting buoys and a field inter-comparison experiment were conducted. The uncertainty budget includes contributions from the uncertainty on the in situ measurements, uncertainty on the satellite IST products and spatial, temporal and vertical variability. The uncertainty budget was based on observations from ice drifting buoys in Qaanaaq, Greenland and radiometric IST skin observations from an automatic weather station. It was showed that the cumulated effects of t...
A field inter-comparison experiment over sea ice was conducted in March-April, 2016 on the sea ic... more A field inter-comparison experiment over sea ice was conducted in March-April, 2016 on the sea ice off Qaanaaq, in Northwest Greenland. Six different thermal infrared radiometers participated in the inter-comparison, the first of its kind over sea ice, including two Fiducial Reference Measurements Thermal Infrared Radiometers. The weather conditions were typical for a high Arctic environment, with surface temperatures between -30C and -10C and low wind speeds. Pairwise comparisons of the 10 minute averaged brightness temperatures from the radiometers showed mean differences between 0.13 and 1.0 K and standard deviation from 0.05 to 1.20 K. Inter-comparison of the sky brightness temperatures showed that a lower limit of ~173 K was reached with both FRM-TIR instruments during cold sky conditions. Several other experiments have been conducted during the field campaign, such as spatial variability study, a freeze-up experiment and an angular dependence experiment. All these experiments ...
Surface temperature is among the most important variables in the surface energy balance equation ... more Surface temperature is among the most important variables in the surface energy balance equation and it significantly affects the atmospheric boundary layer structure, the turbulent heat exchange and, over ice, the ice growth rate. Here we measure the surface temperature using thermal infrared sensors from 10-12 μm wavelength, a method whose primary limitation over sea ice is the detection of clouds. However, in the Arctic and around Antarctica there are very few conventional observations of surface temperature from buoys, and it is sometimes difficult to determine if the temperature is measured at the surface or within the snowpack, the latter of which often results in a warm bias. To reduce this bias, much interest is being paid to alternative remote sensing methods for monitoring high latitude surface temperature. We used Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data to produce a high latitude sea surface temperature (SST), ice surface temperatu...
We establish a methodology for assimilating satellite observations of ice surface temperature (IS... more We establish a methodology for assimilating satellite observations of ice surface temperature (IST) into a coupled ocean and sea-ice model. The method corrects the 2 m air temperature based on the difference between the modeled and the observed IST. Thus the correction includes biases in the surface forcing and the ability of the model to convert incoming parameters at the surface to a net heat flux. A multisensor, daily, gap-free surface temperature analysis has been constructed over the Arctic region. This study revealed challenges estimating the ground truth based on buoys measuring IST, as the quality of the measurement varied from buoy to buoy. With these precautions we find a cold temperature bias in the remotely sensed data, and a warm bias in the modeled data relative to ice mounted buoy temperatures, prior to assimilation. As a consequence, this study weighted the modeled IST and the observed IST equally in the correction. The impact of IST was determined for experiments with and without the assimilation of IST and sea-ice concentration. We find that assimilation of remotely sensed data results in a cooling of IST, which improves the timing of the snow melt onset. The improved snow cover in spring is only based on observations from one buoy, thus additional good quality observations could strengthen the conclusions. The ice cover and the sea-ice thickness are increased, primarily in the experiment without sea-ice concentration assimilation.
An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocea... more An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of American microwave radiometer data from Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from 1978 to 2014 and updates and further developments are planned for the next phase of the project. The methodology is using: 1) numerical weather prediction (NWP) input to a radiative transfer model (RTM) for correction of the brightness temperatures for reduction of atmospheric noise, 2) dynamical algorithm tie-points to mitigate trends in residual atmospheric, sea ice and water emission characteristics and inter-sensor differences/biases, 3) and a hybrid sea ice concentration algorithm using the Bristol algorithm ov...
The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seaso... more The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seasonal sea ice forecasts. Typical tools for such forecasts are numerical models of the coupled ocean sea ice system such as the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM). The model uses as input the initial state of the system and the atmospheric boundary condition over the forecasting period. This study investigates the potential of remotely sensed ice thickness observations in constraining the initial model state. For this purpose it employs a variational assimilation system around NAOSIM and the Alfred Wegener Institute's CryoSat-2 ice thickness product in conjunction with the University of Bremen's snow depth product and the OSI SAF ice concentration and sea surface temperature products. We investigate the skill of predictions of the summer ice conditions starting in March for three different years. Straightforward assimilation of the above combination of data streams r...
Sea ice concentration has been retrieved in polar regions with satellite microwave radiometers fo... more Sea ice concentration has been retrieved in polar regions with satellite microwave radiometers for over 30 years. However, the question remains as to what is an optimal sea ice concentration retrieval method for climate monitoring. This paper presents some of the key results of an extensive algorithm inter-comparison and evaluation experiment. The skills of 30 sea ice algorithms were evaluated systematically over low and high sea ice concentrations. Evaluation criteria included standard deviation relative to independent validation data, performance in the presence of thin ice and melt ponds, and sensitivity to error sources with seasonal to inter-annual variations and potential climatic trends, such as atmospheric water vapour and water-surface roughening by wind. A selection of 13 algorithms is shown in the article to demonstrate the results. Based on the findings, a hybrid approach is suggested to retrieve sea ice concentration globally for climate monitoring purposes. This approa...
You do not present any uncertainties in the presented numbers, while the results clearly show a l... more You do not present any uncertainties in the presented numbers, while the results clearly show a large variability. P1 L14-19: Present this differently: first describe the process, then the result. Thus first that there exists a very persisten surface based temperature inversion driven by radiative cooling. P1 L21-22: Formulate more direct, this is not a new insight but already found for Antarctica. P1 L24-28: Formulate more direct: this is basically the new result of your research. Start with the why this is so interesting, then the result. Leave out the last sentence. This should already be clear.
Traditionally, the availability of in situ observations of ice surface temperature is very limite... more Traditionally, the availability of in situ observations of ice surface temperature is very limited and therefore satellite observations are very important for obtaining a spatially broad and continuous measurement of the ice surface temperature. However, today there is no fiducial reference measurement ice surface temperature (FRM IST) dataset that can be used for routine validation of satellite IST products. To establish the uncertainty budget for instruments in the Arctic, an inter-comparison of ice surface temperature drifting buoys and a field inter-comparison experiment were conducted. The uncertainty budget includes contributions from the uncertainty on the in situ measurements, uncertainty on the satellite IST products and spatial, temporal and vertical variability. The uncertainty budget was based on observations from ice drifting buoys in Qaanaaq, Greenland and radiometric IST skin observations from an automatic weather station. It was showed that the cumulated effects of t...
A field inter-comparison experiment over sea ice was conducted in March-April, 2016 on the sea ic... more A field inter-comparison experiment over sea ice was conducted in March-April, 2016 on the sea ice off Qaanaaq, in Northwest Greenland. Six different thermal infrared radiometers participated in the inter-comparison, the first of its kind over sea ice, including two Fiducial Reference Measurements Thermal Infrared Radiometers. The weather conditions were typical for a high Arctic environment, with surface temperatures between -30C and -10C and low wind speeds. Pairwise comparisons of the 10 minute averaged brightness temperatures from the radiometers showed mean differences between 0.13 and 1.0 K and standard deviation from 0.05 to 1.20 K. Inter-comparison of the sky brightness temperatures showed that a lower limit of ~173 K was reached with both FRM-TIR instruments during cold sky conditions. Several other experiments have been conducted during the field campaign, such as spatial variability study, a freeze-up experiment and an angular dependence experiment. All these experiments ...
Surface temperature is among the most important variables in the surface energy balance equation ... more Surface temperature is among the most important variables in the surface energy balance equation and it significantly affects the atmospheric boundary layer structure, the turbulent heat exchange and, over ice, the ice growth rate. Here we measure the surface temperature using thermal infrared sensors from 10-12 μm wavelength, a method whose primary limitation over sea ice is the detection of clouds. However, in the Arctic and around Antarctica there are very few conventional observations of surface temperature from buoys, and it is sometimes difficult to determine if the temperature is measured at the surface or within the snowpack, the latter of which often results in a warm bias. To reduce this bias, much interest is being paid to alternative remote sensing methods for monitoring high latitude surface temperature. We used Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data to produce a high latitude sea surface temperature (SST), ice surface temperatu...
We establish a methodology for assimilating satellite observations of ice surface temperature (IS... more We establish a methodology for assimilating satellite observations of ice surface temperature (IST) into a coupled ocean and sea-ice model. The method corrects the 2 m air temperature based on the difference between the modeled and the observed IST. Thus the correction includes biases in the surface forcing and the ability of the model to convert incoming parameters at the surface to a net heat flux. A multisensor, daily, gap-free surface temperature analysis has been constructed over the Arctic region. This study revealed challenges estimating the ground truth based on buoys measuring IST, as the quality of the measurement varied from buoy to buoy. With these precautions we find a cold temperature bias in the remotely sensed data, and a warm bias in the modeled data relative to ice mounted buoy temperatures, prior to assimilation. As a consequence, this study weighted the modeled IST and the observed IST equally in the correction. The impact of IST was determined for experiments with and without the assimilation of IST and sea-ice concentration. We find that assimilation of remotely sensed data results in a cooling of IST, which improves the timing of the snow melt onset. The improved snow cover in spring is only based on observations from one buoy, thus additional good quality observations could strengthen the conclusions. The ice cover and the sea-ice thickness are increased, primarily in the experiment without sea-ice concentration assimilation.
An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocea... more An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of American microwave radiometer data from Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from 1978 to 2014 and updates and further developments are planned for the next phase of the project. The methodology is using: 1) numerical weather prediction (NWP) input to a radiative transfer model (RTM) for correction of the brightness temperatures for reduction of atmospheric noise, 2) dynamical algorithm tie-points to mitigate trends in residual atmospheric, sea ice and water emission characteristics and inter-sensor differences/biases, 3) and a hybrid sea ice concentration algorithm using the Bristol algorithm ov...
The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seaso... more The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seasonal sea ice forecasts. Typical tools for such forecasts are numerical models of the coupled ocean sea ice system such as the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM). The model uses as input the initial state of the system and the atmospheric boundary condition over the forecasting period. This study investigates the potential of remotely sensed ice thickness observations in constraining the initial model state. For this purpose it employs a variational assimilation system around NAOSIM and the Alfred Wegener Institute's CryoSat-2 ice thickness product in conjunction with the University of Bremen's snow depth product and the OSI SAF ice concentration and sea surface temperature products. We investigate the skill of predictions of the summer ice conditions starting in March for three different years. Straightforward assimilation of the above combination of data streams r...
Sea ice concentration has been retrieved in polar regions with satellite microwave radiometers fo... more Sea ice concentration has been retrieved in polar regions with satellite microwave radiometers for over 30 years. However, the question remains as to what is an optimal sea ice concentration retrieval method for climate monitoring. This paper presents some of the key results of an extensive algorithm inter-comparison and evaluation experiment. The skills of 30 sea ice algorithms were evaluated systematically over low and high sea ice concentrations. Evaluation criteria included standard deviation relative to independent validation data, performance in the presence of thin ice and melt ponds, and sensitivity to error sources with seasonal to inter-annual variations and potential climatic trends, such as atmospheric water vapour and water-surface roughening by wind. A selection of 13 algorithms is shown in the article to demonstrate the results. Based on the findings, a hybrid approach is suggested to retrieve sea ice concentration globally for climate monitoring purposes. This approa...
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