Climate change resulting in ocean warming, sea level rise, and sea ice melting has consequences for the global economy, navigation, and security. The Copernicus Imaging Microwave Radiometer (CIMR) mission is a high priority candidate mission within the European Copernicus Expansion program. CIMR is designed to observe the ocean and sea ice and more particularly the Arctic environment. Sea surface temperature (SST), ocean wind speed, sea surface salinity (SSS), and sea ice concentration (SIC) are fundamental variables for understanding, monitoring, and predicting the state of the ocean and sea ice. CIMR is a conically scanning microwave radiometer imager that includes channels at 1.4, 6.9, 10.65, 18.7, and 36.5 GHz, in a Sun‐synchronous polar orbit, to provide SST, ocean wind speed, SSS, and SIC with an increased accuracy and/or spatial resolution. Here we analyze the performances of the CIMR mission in terms of theoretical retrieval precision and spatial resolution on the SST, SSS, and SIC products. A careful information content analysis is conducted. The CIMR performances are compared with the Advanced Microwave Scanning Radiometer 2 and the Soil Moisture Active Passive current missions. Maps of the retrieval precision based on realistic conditions are computed. CIMR will provide SST, SSS, and SIC with a spatial resolution of 15, 55, and 5 km and a precision of 0.2 K, 0.3 psu, and 5%, respectively. The SST and SIC will be retrieved at better than 30 km from the coast. CIMR is currently in preparatory phase, and if selected, it is for a launch in the 2025+ time frame.

Mapping sea ice concentration (SIC) and understanding sea ice properties and variability is important, especially today with the recent Arctic sea ice decline. Moreover, accurate estimation of the sea ice effective temperature (T_eff) at 50 GHz is needed for atmospheric sounding applications over sea ice and for noise reduction in SIC estimates. At low microwave frequencies, the sensitivity to the atmosphere is low, and it is possible to derive sea ice parameters due to the penetration of microwaves in the snow and ice layers. In this study, we propose simple algorithms to derive the snow depth, the snow–ice interface temperature (T_Snow−Ice) and the T_eff of Arctic sea ice from microwave brightness temperatures (TBs). This is achieved using the Round Robin Data Package of the ESA sea ice CCI project, which contains TBs from the Advanced Microwave Scanning Radiometer 2 (AMSR2) collocated with measurements from ice mass balance buoys (IMBs) and the NASA Operation Ice Bridge (OIB) airborne campaigns over the Arctic sea ice. The snow depth over sea ice is estimated with an error of 5.1 cm, using a multilinear regression with the TBs at 6, 18, and 36 V. The T_Snow−Ice is retrieved using a linear regression as a function of the snow depth and the TBs at 10 or 6 V. The root mean square errors (RMSEs) obtained are 2.87 and 2.90 K respectively, with 10 and 6 V TBs. The T_eff at microwave frequencies between 6 and 89 GHz is expressed as a function of T_Snow−Ice using data from a thermodynamical model combined with the Microwave Emission Model of Layered Snowpacks. T_eff is estimated from the T_Snow−Ice with a RMSE of less than 1 K.

A Passive and Active Reference Microwave to Infrared Ocean (PARMIO) physical radiative transfer model has been selected by an international team of experts to be used as a community ocean surface emissivity model. A fast version of this physical community model is developed within the framework of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Numerical Weather Prediction Satellite Application Facilities visiting scientist programme: the SURface Fast Emissivity Model for Ocean (SURFEM‐Ocean), for implementation in the Radiative Transfer code for TOVS (RTTOV) as an alternative/replacement of the well‐known FAST microwave Emissivity Model (FASTEM). First, the configuration of the PARMIO model is adapted to microwave frequencies from 500 MHz to 700 GHz, and issues observed in the preliminary studies with cold sea surface temperatures (SST) and high ocean wind speeds (OWS) are corrected. Second, an artificial neural network method is used to reproduce the results of the PARMIO model much faster. The computation of the analytical Jacobians is also implemented. Finally, SURFEM‐Ocean results are compared with satellite observations and other ocean emissivity models. SURFEM‐Ocean extends the capability of FASTEM. It computes emissivities from 500 MHz to 700 GHz, for all incidence angles, for the fourth Stokes polarizations, for OWS from 0 to 50 m/s, SST from −2 to 30°C, sea surface salinity from 0 to 40 psu, and for all wind directions.

The Copernicus Imaging Microwave Radiometer (CIMR) is currently being implemented by the European Space Agency (ESA) as a Copernicus Expansion Mission primarily designed to observe the Polar Regions in support of the Integrated European Policy for the Arctic. It is a conically scanning microwave radiometer with polarized channels centered at 1.414, 6.925, 10.65, 18.7, and 36.5 GHz and channel NEΔT between 0.2 and 0.7 K. A large rotating deployable mesh reflector will provide real‐aperture resolutions ranging from 60 (1.4 GHz) to 5 km (36.5 GHz). To evaluate CIMR retrieval performance, a simplified end‐to‐end simulation of the mission has been carried out. The simulation includes important processes and input parameters, such as test geophysical datasets, forward models, an instrument simulator, and retrieval algorithms to derive the key mission geophysical products. The forward modeling is tested by producing Brightness Temperatures (TBs) from 4 global scenes. A comparison with current observations of the open ocean and sea ice at similar frequencies confirmed the realism of the simulations. The produced top‐of‐atmosphere TBs are converted to Antenna brightness Temperatures (TAs), taking into account the instrument design, and are then inverted to retrieve Sea Ice Concentration (SIC), Sea Surface Temperature (SST), and Sea Surface Salinity (SSS). Evaluating the retrieval performance showed that the simulated CIMR instrument can provide SST, SSS, and SIC measurements with precisions and spatial resolutions conforming with the mission requirements. The evaluation also highlighted the challenges of observing the Arctic environment and put in perspective CIMR capabilities compared with current instruments.

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.

The Copernicus Imaging Microwave Radiometer (CIMR) is one of the high-priority missions for the expansion of the Copernicus program within the European Space Agency (ESA). It is designed to respond to the European Union Arctic policy. Its channels, incidence angle, precision, and spatial resolutions have been selected to observe the Arctic Ocean with the recommendations expressed by the user communities. In this note, we present the sensitivity analysis that has led to the choice of the CIMR channels. The famous figure from Wilheit (1979), describing the frequency sensitivity of passive microwave satellite observations to ocean parameters, has been extensively used for channel selection of microwave radiometer frequencies on board oceanic satellite missions. Here, we propose to update this sensitivity analysis, using state-of-the-art radiative transfer simulations for different geophysical conditions (Arctic, mid-latitude, tropics). We used the Radiative Transfer Model (RTM) from Meissner and Wentz (2012) for the ocean surface, the Round Robin Data Package of the ESA Climate Change Initiative (Pedersen et al., 2019) for the sea ice, and the RTM from Rosenkranz (2017) for the atmosphere. The sensitivities of the brightness temperatures (TBs) observed by CIMR as a function of sea surface temperature (SST), sea surface salinity (SSS), sea ice concentration (SIC), ocean wind speed (OWS), total column water vapor (TCWV), and total column liquid water (TCLW) are presented as a function of frequency between 1 and 40 GHz. The analysis underlines the difficulty to reach the user requirements with single-channel retrieval, especially under cold ocean conditions. With simultaneous measurements between 1.4 and 36 GHz onboard CIMR, applying multi-channel algorithms will be facilitated, to provide the user community with the required ocean and ice information under arctic environments.