Simulated geophysical noise in the Copernicus Imaging Microwave Radiometer (CIMR) ice concentration estimates over snow covered sea ice

Abstract

As a direct response to the Polar Expert Group recommendations for sea ice concentration and high latitude SST’s, EU and ESA have initiated phase A studies for a low frequency high spatial and temporal resolution polar orbiting satellite microwave radiometer in preparation for the Expansion phase of the Copernicus Space Component from 2025: the Copernicus Imaging Microwave Radiometer (CIMR).

Compared to the existing and planned Passive Microwave Radiometers (SSMIS, MWRI, AMSR2,...) CIMR will have significantly higher spatial resolution and for one of the two primary geophysical variables: sea ice concentration (SIC) it will have high resolution and very low noise at the same time. These two things are trade-offs with current radiometers. The second primary parameter sea surface temperature (SST) will significantly increase coverage at high latitudes because of the microwave cloud penetrating capabilities.

Using simulated brightness temperature (Tb) datasets over snow covered sea ice (SIC=100%) the sensitivity of SIC algorithms each using CIMR channels have been investigated. The simulated Tb dataset has been generated using a combination of a column thermodynamical model and an emission model. We then know the truth, which is 100% SIC, and noise is defined as variability near this reference point. In general, the sources of geophysical noise are: 1) surface emissivity and effective temperature variations, and 2) atmospheric influence on the measured radiances and how these propagate in different SIC algorithms. The goal is to identify SIC algorithms where the combination of CIMR channels is minimizing the geophysical noise or alternatively find algorithms with low sensitivity to noise sources that we cannot correct for.

Spatial resolution is a strong requirement in SIC applications and spatial resolution varies with electromagnetic frequency. Therefore we compare the geophysical SIC noise for each algorithm with the representativeness uncertainty using a microwave radiometer imaging simulator.

Sea ice emissivity variations are caused by variations of the microphysical parameters of sea ice and snow such as temperature, salinity, snow thickness, density, roughness and wetness. Each of the systematic geophysical noise sources has or may have climatological trends so even if the noise source is small yet systematic it may introduce artificial trends in the sea ice climate data record (CDR). When constructing a sea ice CDR there are several criteria for selecting algorithms such as consistency in the methodology, availability of long time-series of consistent satellite data, quantification of uncertainties, and stability.

This study is part of the European Space Agency (ESA) CIMR mission advisory group phase A studies. These studies are assessing and developing the CIMR mission concept for its applications, here SIC