Description: Research on improving the prediction skill of climate models requires refining the quality of observational data used for initializing and tuning the models. This is especially true in the Polar Regions where uncertainties about the interactions between sea ice, ocean and atmosphere are driving ongoing monitoring efforts. The Copernicus Imaging Microwave Radiometer (CIMR) is an European Space Agency (ESA) candidate mission which promises to offer high resolution, low uncertainty observation capabilities at the 1.4, 6.9,10.65,18.7 and 36.5 GHz frequencies. To assess the potential impact of CIMR for sea ice parameter retrieval, a comparison is made between retrievals based on present AMSR2 observations and a retrieval using future CIMR equivalent observations over a data set of validated sea ice concentration (SIC) values. An optimal estimation retrieval method (OEM) is used which can use input from different channel combinations to retrieve seven geophysical parameters (sea ice concentration, multi year ice fraction, ice surface temperature, columnar water vapor, liquid water path, over ocean wind speed and sea surface temperature). An advantage of CIMR over existing adiometers is that it would provide higher spatial resolution observations at the lower frequency channels (6.9, 10.65, 18.7 GHz) which are less sensitive to atmospheric influence. This enables the passive microwave based retrieval of SIC and other surface parameters with higher resolution and lower uncertainty than is currently possible. An information content analysis expands the comparison between AMSR2 and CIMR to all retrievable surface and atmospheric parameters. This analysis quantifies the contributions to the observed signal and highlights the differences between different input channel combinations. The higher resolution of the low frequency CIMR channels allow for unprecedented detail to be achieved in Arctic passive microwave sea ice retrievals. The presence of 1.4 GHz channels on board CIMR opens up the possibility for thin sea ice thickness (SIT) retrieval. A combination of collocated AMSR2 and SMOS observations is used to simulate a full CIMR suite of measurements and the OEM is modified to include SIT as a retrieval parameter. The output from different retrieval configurations is compared both with an operational SIT product and with a ship observation data set. The CIMR instrument can provide increased accuracy for SIC retrieval at very high resolutions with a combination of the 18.7 and 36.5 GHz channels while also maintaining sensitivity for atmospheric water vapor retrieval. In combination with the 1.4 GHz channels, SIT can be added as an eighth retrieval parameter with performance on par with existing operational products. -------------------------------------------- This dataset contains the output from a multi-parameter retrieval method based on satellite passive microwave measurements. The eight retrieval parameters are wind speed over ocean, total atmospheric water vapor, atmospheric liquid water path, sea surface temperature, ice surface temperature, sea ice concentration (SIC), multi-year ice fraction and sea ice thickness (SIT). The method uses as input a combination of AMSR2 (Advanced Microwave Scanning Radiometer) and SMOS (Soil Moisture Ocean Salinity) instrument measurements in order to simulate the channel combination of the upcoming CIMR (Copernicus Imaging Microwave Radiometer) mission. -- Sea ice concentration is one of the two primary mission parameters of the CIMR instrument and SIC output from 13 different CIMR equivalent channel combinations is included in this dataset. -- The full set of eight retrieval parameters are given for four different CIMR equivalent configurations which all include the L-band channels necessary for SIT retrieval. -- The SIC dataset contains three files each for 100% and 0% SIC scenes: - The filename prefix always starts with RRDP_0 for for 0% SIC and RRDP_1 for 100% SIC scenes; - the suffix 6-89_SIC includes 11 channel combinations using all frequencies between 6.9 and 89 GHz; - full_CIMR_SIC represents a retrieval using the full CIMR suite of channels (1.4, 6.9, 10.8, 18.7 and 36.5 GHz); - only_1.4_SIC contains the SIC retrieval results when only using the 1.4 GHz channels. -- While all AMSR based channels (between 6.9 and 89 GHz) are grouped into one file, the collocation between the AMSR and SMOS determines a smaller common coverage dataset which required the 1.4 (only SMOS) and 1.4 + 6.9-〉36.5 GHz (SMOS + AMSR) to be split into different files. -- The columns of the files are in order Longitude (lon), Latitude (lat), SIC value in % retrieved by using the channel frequencies shown in the header, day, month and year. Each row represents one pixel and all pixels are arranged in chronological order. -- The SIT dataset includes four files matching four comparable retrieval schemes. Unlike the SIC dataset, here all eight retrieval parameters are included. The four files are: - "RRDP_Thin_SIT_all_channel_dep.asc" - all CIMR channels are taken into account when retrieving SIT; - "RRDP_Thin_SIT_only_L-band_dep.asc" - only the 1.4 GHz (L band) channels influence the retrieval of SIT; - "RRDP_Thin_SIT_high_weight_L-band.asc" - all channels influence SIT retrieval but the L band channels have a higher weight on the final result due to their high sensitivity to this parameter; - "RRDP_Thin_SIT_high_certainty_SIC_a-priori.asc" - all channels influence SIT retrieval and additionally the SIC is fixed to 100% in order to ensure that lower SIC is not mistakenly retrieved as low SIT. This additional step is analogous with how current passive microwave SIT retrieval algorithms work, where all retrieval pixels are considered to be completely covered by sea ice. -- The columns are in order longitude, latitude, wind speed (m/s), water vapor (mm), liquid water path (mm), sea surface temperature (K), ice surface temperature (K), sea ice concentration (0 =0% SIC to 1 =100% SIC), multi-year ice fraction (0-1 = fraction of 100% SIC), sea ice thickness (cm), convergence quality flag (0 - good, -1 - bad), number if iterations needed to reach convergence, day, month, year -- Notes on availability of primary input data: 1. The input for the processed SIC dataset comes from the Reference dataset for Sea Ice Concentration (https://figshare.com/articles/Reference_dataset_for_sea_ice_concentration/6626549/6) also called the Round Robin Data Package (RRDP). This base dataset contains scenes with validated 100% sea ice cover (RRDP SIC1) and scenes with no sea ice presence (RRDP SIC0). The data set covers the years 2013, 2014 and 2015. 2. The SIT dataset is based on a different RRDP version than the SIC one. This thin sea ice RRDP set includes validated SMOS SIT data and covers the years 2010 and 2011. This second dataset was created for and discussed in: Heygster et al. (2014) 3. A related article relevant to the optimal estimation retrieval method used to generate this dataset is: Scarlat et al. (2017)

Description: The Optical IP Camera was mostly observing the snow surface and aligned instruments at the remote sensing site during the MOSAiC expedition in the central Arctic, saving 4K images in JPEG format in 5 minute intervals. Between October to March it was mostly working continuously, while the data from April to September is more sparse. Occasional transects (remote sensing transects) and experiments were recorded in higher acquisition rates. The camera is equipped with high brightness NIR LED spotlights, turning on automatically in low light situations. Over the course of the expedition, the camera had several remote sensing instruments and the snow and ice surface in the field of view and can be used as a supportive dataset for events at the remote sensing site. It was operated always in conjunction with an infrared camera (doi:10.1594/PANGAEA.940717), pointing at the same targets but with a wider opening angle. The same camera model was also attached to the remote sensing hut (doi:10.1594/PANGAEA.939443) during parts of the campaign.

Description: The Optical IP Camera was attached to the remote sensing hut during the MOSAiC expedition, saving 4K images in JPEG format in 5 minute intervals. It was installed during MOSAiC leg 2 and leg 3, 10 February to 17 April 2020. The camera is equipped with high brightness NIR LED spotlights, turning on automatically in low light situations. During its operation time, the camera had several remote sensing instruments in the field of view and can be used as a supportive dataset for events at the remote sensing site.

Description: The Hyperspectral camera Specim IQ measures relative reflectances for 512x512 pixels in 204 bands in a wavelength range from 400 nm to 1000 nm. Within the field of view, there was a white reference placed so that the reflectances can be compared to other datasets. During the MOSAiC expedition, the camera was installed at the remote sensing site on the ice. It was looking at the snow and ice, taking an image every 30 minutes for periods in April 2020 and July 2020. Each data record is a folder (compressed as one file) readable by the Specim IQ software, which is downloadable free of charge from the manufacturer (Specim) after registration. This dataset is from an experimental setup to explore the use of spatially resolved hyperspectral imaging of Arctic sea ice.

Description: This dataset contains ground-based radiometer observations from the University of Manitoba Surface Based Radiometer (UoM SBR) at 19, 37 and 89 GHz taken during Leg 1 to Leg 5 of the MOSAiC campaign (October 2019 - September 2020). Included are I) calibrated brightness temperatures, II) quality controlled calibrated brightness temperatures, resampled to 1 minute temporal resolution. Details about the data format, usage and the instrument can be found in the file Data_manual.pdf.

Description: Surface temperature maps, gridded in 1 m resolution, are provided for 35 flights between 02.10.2019 and 23.04.2020 during the MOSAiC expedition. There is one file for every flight. The flights can be identified by the event-related Device Operation label or Flight ID. The surface temperature maps are an advanced data product based on the surface temperature images from each flight. The images are gridded to an equidistant grid. The 5 m resolution data are included to provide data with a smaller file size so they are easier accessible and available for comparison of the effect of a different spatial resolution. These gridded surface temperatures are available for a quick look in png format as another data type of this data set. The surface temperature is derived from the measured brightness temperature with a constant emissivity of 0.996. Additionally, the time-fixed surface temperature is included, which is corrected by the temporal temperature drift during each flight. All data are ice drift corrected and georeferenced, and provided with longitude and latitude coordinates as well as relative coordinates referenced to the position of RV Polarstern.

Description: The surface temperature maps are provided for 35 flights between 02.10.2019 and 23.04.2020 during the MOSAiC expedition. There is one file for every flight. The flights can be identified by the event-related Device Operation label or Flight ID. Surface temperature maps are an advanced data product based on the surface temperature images from each flight. The maps are gridded to an equidistant grid. These displayed maps give a quick overview of the processed data, which are available in NetCDF format as another data type of this data set. The surface temperature is derived from the measured brightness temperature with a constant emissivity of 0.996. Additionally, the time-fixed surface temperature is shown, which is corrected by the temporal temperature drift during each flight. The data are displayed in relative coordinates referenced to the position of RV Polarstern.