Reduction of weather effects in the calculation of sea-ice concentration with the DMSP SSM/I

Abstract A problem in mapping the polar sea-ice covers in both hemispheres has been the sporadic false indication of sea ice over the open ocean and at the ice edge. These spurious sea-ice concentrations result from variations in sea-surface roughening by surface winds, atmospheric water vapor and both precipitating and non-precipitating liquid water. This problem was addressed for sea-ice concentrations derived from the Nimbus-7 scanning multi-channel microwave radiometer (SMMR) data through the development of a weather filter based on spectral information from the 18.0 and 37.0 GHz vertical polarization SMMR channels. Application of a similar filter for use with sea-ice concentration maps derived with the special-sensor microwave imager (SSM/I) sensor is less successful. This results from the position of the 19.35 GHz SSM/I channels, which are closer to the center of the 22.2 GHz atmospheric water-vapor line than are the SMMR 18.0 GHz channels. Thus, the SSM/I 19.35 GHz channels are more sensitive to changes in atmospheric water vapor, which results in greater contamination problems. An additional filter has been developed, based on a combination of the 19.35 and 22.2GHz. SSM/I channels. Examples of the effectiveness of the new filter are presented and limitations are discussed.

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Reduction of weather effects in the calculation of sea-ice concentration with the DMSP SSM/I

Journal of Glaciology ◽

10.3189/s0022143000034791 ◽

1995 ◽

Vol 41 (139) ◽

pp. 455-464 ◽

Cited By ~ 4

Author(s):

Donald J. Cavalieri ◽

Karen M. St. Germain ◽

Calvin T. Swift

Keyword(s):

Water Vapor ◽

Sea Ice ◽

Microwave Radiometer ◽

Atmospheric Water Vapor ◽

Surface Roughening ◽

Atmospheric Water ◽

Sea Ice Concentration ◽

Ice Concentration ◽

Vapor Line ◽

Microwave Imager

AbstractA problem in mapping the polar sea-ice covers in both hemispheres has been the sporadic false indication of sea ice over the open ocean and at the ice edge. These spurious sea-ice concentrations result from variations in sea-surface roughening by surface winds, atmospheric water vapor and both precipitating and non-precipitating liquid water. This problem was addressed for sea-ice concentrations derived from the Nimbus-7 scanning multi-channel microwave radiometer (SMMR) data through the development of a weather filter based on spectral information from the 18.0 and 37.0 GHz vertical polarization SMMR channels. Application of a similar filter for use with sea-ice concentration maps derived with the special-sensor microwave imager (SSM/I) sensor is less successful. This results from the position of the 19.35 GHz SSM/I channels, which are closer to the center of the 22.2 GHz atmospheric water-vapor line than are the SMMR 18.0 GHz channels. Thus, the SSM/I 19.35 GHz channels are more sensitive to changes in atmospheric water vapor, which results in greater contamination problems. An additional filter has been developed, based on a combination of the 19.35 and 22.2GHz. SSM/I channels. Examples of the effectiveness of the new filter are presented and limitations are discussed.

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The EUMETSAT sea ice climate record

10.5194/tc-2016-34 ◽

2016 ◽

Cited By ~ 1

Author(s):

R. T. Tonboe ◽

S. Eastwood ◽

T. Lavergne ◽

A. M. Sørensen ◽

N. Rathmann ◽

...

Keyword(s):

Sea Ice ◽

Weather Prediction ◽

Microwave Radiometer ◽

Open Water ◽

The Arctic ◽

Radiative Transfer Model ◽

Transfer Model ◽

Sea Ice Concentration ◽

Ice Concentration ◽

Microwave Imager

Abstract. 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 over ice and the Bootstrap algorithm in frequency mode over open water. A new algorithm has been developed to estimate the spatially and temporally varying sea ice concentration uncertainties. A comparison to sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate ice concentrations. The sea ice climate dataset is available for download at (www.osisaf.org) including documentation.

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The EUMETSAT sea ice concentration climate data record

The Cryosphere ◽

10.5194/tc-10-2275-2016 ◽

2016 ◽

Vol 10 (5) ◽

pp. 2275-2290 ◽

Cited By ~ 32

Author(s):

Rasmus T. Tonboe ◽

Steinar Eastwood ◽

Thomas Lavergne ◽

Atle M. Sørensen ◽

Nicholas Rathmann ◽

...

Keyword(s):

Sea Ice ◽

Microwave Radiometer ◽

Open Water ◽

The Arctic ◽

Climate Data ◽

Sea Ice Concentration ◽

Ice Concentration ◽

Data Record ◽

Microwave Imager ◽

Climate Data Record

Abstract. 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 microwave radiometer data from NASA's 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 October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation.

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Review of methods to retrieve sea ice parameters from satellite microwave radiometer data

Известия Российской академии наук Физика атмосферы и океана ◽

10.31857/s0002-3515551128-151 ◽

2019 ◽

Vol 55 (1) ◽

pp. 128-151

Author(s):

E. V. Zabolotskikh

Keyword(s):

Sea Ice ◽

Microwave Radiometer ◽

Open Water ◽

Sea Ice Concentration ◽

Internet Resources ◽

Ice Concentration ◽

Satellite Microwave ◽

Microwave Imager ◽

Microwave Radiometers

Sea ice monitoring using long-term data of satellite passive microwave instruments enables climate change estimates. These numerical estimates depend on the methods used for sea ice parameter retrievals. This work presents a review of methods to retrieve sea ice parameters from the data of satellite microwave radiometers. Physical modeling of the sea ice–ocean–atmosphere microwave radiation provides the means to identify the general sources of the retrieval errors and to classify the methods by used approach. The basics of the algorithms are formulated along with assumptions and approximations as well as the data used for the algorithm verification. Weather filters are considered to identify the areas of open water. A comparative analysis of method advantages and limitations is given related to sea ice concentration retrievals from such satellite instruments as the series of Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer (AMSR). A review of the basic satellite sea ice products based on SSM/I, AMSR-E and AMSR2 data is complemented by the list of the essential internet resources for operational and historical sea ice data.

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Sea Ice Concentration and Sea Ice Extent Mapping with L-Band Microwave Radiometry and GNSS-R Data from the FFSCat Mission Using Neural Networks

Remote Sensing ◽

10.3390/rs13061139 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1139

Author(s):

David Llaveria ◽

Juan Francesc Munoz-Martin ◽

Christoph Herbert ◽

Miriam Pablos ◽

Hyuk Park ◽

...

Keyword(s):

Sea Ice ◽

Microwave Radiometer ◽

Cost Effective ◽

The Arctic ◽

Sea Ice Concentration ◽

Sea Ice Extent ◽

Neural Network Approach ◽

Ice Concentration ◽

L Band ◽

Moderate Cost

CubeSat-based Earth Observation missions have emerged in recent times, achieving scientifically valuable data at a moderate cost. FSSCat is a two 6U CubeSats mission, winner of the ESA S3 challenge and overall winner of the 2017 Copernicus Masters Competition, that was launched in September 2020. The first satellite, 3Cat-5/A, carries the FMPL-2 instrument, an L-band microwave radiometer and a GNSS-Reflectometer. This work presents a neural network approach for retrieving sea ice concentration and sea ice extent maps on the Arctic and the Antarctic oceans using FMPL-2 data. The results from the first months of operations are presented and analyzed, and the quality of the retrieved maps is assessed by comparing them with other existing sea ice concentration maps. As compared to OSI SAF products, the overall accuracy for the sea ice extent maps is greater than 97% using MWR data, and up to 99% when using combined GNSS-R and MWR data. In the case of Sea ice concentration, the absolute errors are lower than 5%, with MWR and lower than 3% combining it with the GNSS-R. The total extent area computed using this methodology is close, with 2.5% difference, to those computed by other well consolidated algorithms, such as OSI SAF or NSIDC. The approach presented for estimating sea ice extent and concentration maps is a cost-effective alternative, and using a constellation of CubeSats, it can be further improved.

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New Gridded Product for the Total Columnar Atmospheric Water Vapor over Ocean Surface Constructed from Microwave Radiometer Satellite Data

Remote Sensing ◽

10.3390/rs13122402 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2402

Author(s):

Weifu Sun ◽

Jin Wang ◽

Yuheng Li ◽

Junmin Meng ◽

Yujia Zhao ◽

...

Keyword(s):

Water Vapor ◽

Microwave Radiometer ◽

Atmospheric Water Vapor ◽

Global Ocean ◽

Optimal Interpolation ◽

Fusion Product ◽

Mean Deviation ◽

Atmospheric Water ◽

Absolute Deviation ◽

Better Than

Based on the optimal interpolation (OI) algorithm, a daily fusion product of high-resolution global ocean columnar atmospheric water vapor with a resolution of 0.25° was generated in this study from multisource remote sensing observations. The product covers the period from 2003 to 2018, and the data represent a fusion of microwave radiometer observations, including those from the Special Sensor Microwave Imager Sounder (SSMIS), WindSat, Advanced Microwave Scanning Radiometer for Earth Observing System sensor (AMSR-E), Advanced Microwave Scanning Radiometer 2 (AMSR2), and HY-2A microwave radiometer (MR). The accuracy of this water vapor fusion product was validated using radiosonde water vapor observations. The comparative results show that the overall mean deviation (Bias) is smaller than 0.6 mm; the root mean square error (RMSE) and standard deviation (SD) are better than 3 mm, and the mean absolute deviation (MAD) and correlation coefficient (R) are better than 2 mm and 0.98, respectively.

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Ice Concentration Retrieval from the Analysis of Microwaves: A New Methodology Designed for the Copernicus Imaging Microwave Radiometer

Remote Sensing ◽

10.3390/rs12071060 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1060 ◽

Cited By ~ 1

Author(s):

Lise Kilic ◽

Catherine Prigent ◽

Filipe Aires ◽

Georg Heygster ◽

Victor Pellet ◽

...

Keyword(s):

Sea Ice ◽

Spatial Resolution ◽

Microwave Radiometer ◽

Optimal Estimation ◽

Arctic Sea Ice ◽

The Arctic ◽

Special Focus ◽

Polar Regions ◽

Sea Ice Concentration ◽

Ice Concentration

Over the last 25 years, the Arctic sea ice has seen its extent decline dramatically. Passive microwave observations, with their ability to penetrate clouds and their independency to sunlight, have been used to provide sea ice concentration (SIC) measurements since the 1970s. The Copernicus Imaging Microwave Radiometer (CIMR) is a high priority candidate mission within the European Copernicus Expansion program, with a special focus on the observation of the polar regions. It will observe at 6.9 and 10.65 GHz with 15 km spatial resolution, and at 18.7 and 36.5 GHz with 5 km spatial resolution. SIC algorithms are based on empirical methods, using the difference in radiometric signatures between the ocean and sea ice. Up to now, the existing algorithms have been limited in the number of channels they use. In this study, we proposed a new SIC algorithm called Ice Concentration REtrieval from the Analysis of Microwaves (IceCREAM). It can accommodate a large range of channels, and it is based on the optimal estimation. Linear relationships between the satellite measurements and the SIC are derived from the Round Robin Data Package of the sea ice Climate Change Initiative. The 6 and 10 GHz channels are very sensitive to the sea ice presence, whereas the 18 and 36 GHz channels have a better spatial resolution. A data fusion method is proposed to combine these two estimations. Therefore, IceCREAM will provide SIC estimates with the good accuracy of the 6+10GHz combination, and the high spatial resolution of the 18+36GHz combination.

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