The Electrically Scanning Microwave Radiometer (ESMR) on board the NIMBUS 5 satellite was a one channel 19.35 GHz horizontally polarized microwave radiometer operating from 11. Dec. 1972 to 16. May. 1977 (1617 days) with some interruptions. After a major data gap from 3. Jun. 1975 until 25. Aug. 1975 the instrument was only operated approximately every other day. The data have recently been made available online by NASA in the format which was used for the tape archive (TAP-files).
The experimental NIMBUS satellite programme was very successful and there is heritage from it in modern satellite programs and even though ESMR was a predecessor of modern multi-frequency radiometers there are still parts of modern processing methodologies which can be applied to the data to derive the sea ice extent globally. In fact both the dynamical tie-points and the atmospheric noise reduction of the brightness temperatures (Tb’s) can reduce the noise over both ice and open water consistently. These are also the reasons for reprocessing the data. The ESMR sea ice dataset extends the sea ice climate data record with an important period in the 1970s.

The Electrically Scanning Microwave Radiometer (ESMR) on board the NIMBUS 5 satellite was a one channel 19.35 GHz horizontally polarized microwave radiometer operating from 11. Dec. 1972 to 16. May. 1977 (1617 days) with some interruptions. After a major data gap from 3. Jun. 1975 until 25. Aug. 1975 the instrument was only operated approximately every other day. The data have recently been made available online by NASA in the format which was used for the tape archive (TAP-files).
The experimental NIMBUS satellite programme was very successful and there is heritage from it in modern satellite programs and even though ESMR was a predecessor of modern multi-frequency radiometers there are still parts of modern processing methodologies which can be applied to the data to derive the sea ice extent globally. In fact both the dynamical tie-points and the atmospheric noise reduction of the brightness temperatures (Tb’s) can reduce the noise over both ice and open water consistently. These are also the reasons for reprocessing the data. The ESMR sea ice dataset extends the sea ice climate data record with an important period in the 1970s.

The AI4Arctic / ASIP Sea Ice Dataset - version 2 (ASID-v2) contain 461 Sentinel-1 Synthetic Aperture Radar (SAR) scenes matched with sea ice charts produced by the Danish Meteorological Institute in 2018-2019. Ice charts contain sea ice concentration, stage of development and form of ice, provided in manual drawn polygons. The ice charts have been projected into the the S1 geometry for easy use as labels in deep learning or other machine learning algorithm training processes. The dataset also includes AMSR2 microwave radiometer sensor measurements to compliment the learning of the of sea ice concentrations although in a much lower resolution than the Sentinel-1 data. Details are described in the manual that is published together with the dataset.The manual has been revised, the latest is the 30-09-2020 version.

The AI4Arctic / ASIP Sea Ice Dataset - version 2 (ASID-v2) contain 461 Sentinel-1 Synthetic Aperture Radar (SAR) scenes matched with sea ice charts produced by the Danish Meteorological Institute in 2018-2019. Ice charts contain sea ice concentration, stage of development and form of ice, provided in manual drawn polygons. The ice charts have been projected into the the S1 geometry for easy use as labels in deep learning or other machine learning algorithm training processes. The dataset also includes AMSR2 microwave radiometer sensor measurements to compliment the learning of the of sea ice concentrations although in a much lower resolution than the Sentinel-1 data. Details are described in the manual that is published together with the dataset.The manual has been revised, the latest is the 30-09-2020 version.

The AI4Arctic / ASIP Sea Ice Dataset - version 2 (ASID-v2) contain 461 Sentinel-1 Synthetic Aperture Radar (SAR) scenes matched with sea ice charts produced by the Danish Meteorological Institute in 2018-2019. Ice charts contain sea ice concentration, stage of development and form of ice, provided in manual drawn polygons. The ice charts have been projected into the the S1 geometry for easy use as labels in deep learning or other machine learning algorithm training processes. The dataset also includes AMSR2 microwave radiometer sensor measurements to compliment the learning of the of sea ice concentrations although in a much lower resolution than the Sentinel-1 data. Details are described in the manual that is published together with the dataset.The manual has been revised, the latest is the 30-09-2020 version.

The AI4Arctic / ASIP Sea Ice Dataset - version 2 (ASID-v2) contain 461 Sentinel-1 Synthetic Aperture Radar (SAR) scenes matched with sea ice charts produced by the Danish Meteorological Institute in 2018-2019. Ice charts contain sea ice concentration, stage of development and form of ice, provided in manual drawn polygons. The ice charts have been projected into the the S1 geometry for easy use as labels in deep learning or other machine learning algorithm training processes. The dataset also includes AMSR2 microwave radiometer sensor measurements to compliment the learning of the of sea ice concentrations although in a much lower resolution than the Sentinel-1 data. Details are described in the manual that is published together with the dataset.