Abstract
Abstract. The spaceborne passive microwave sensors Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) provide brightness temperature data in the L band (1.4 GHz). At this low frequency the atmosphere is close to transparent and in polar regions the thickness of thin sea ice can be derived. SMOS measurements cover a large incidence angle range, whereas SMAP observes at a fixed 40∘ incidence angle. By using brightness temperatures at a fixed incidence angle obtained directly (SMAP), or through interpolation (SMOS), thin sea ice thickness retrieval is more consistent as the incidence angle effects do not have to be taken into account. Here we transfer a retrieval algorithm for the thickness of thin sea ice (up to 50 cm) from SMOS data at 40 to 50∘ incidence angle to the fixed incidence angle of SMAP. The SMOS brightness temperatures (TBs) at a given incidence angle are estimated using empirical fit functions. SMAP TBs are calibrated to SMOS to provide a merged SMOS–SMAP sea ice thickness product. The new merged SMOS–SMAP thin ice thickness product was improved upon in several ways compared to previous thin ice thickness retrievals. (i) The combined product provides a better temporal and spatial coverage of the polar regions due to the usage of two sensors. (ii) The radio frequency interference (RFI) filtering method was improved, which results in higher data availability over both ocean and sea ice areas. (iii) For the intercalibration between SMOS and SMAP brightness temperatures the root mean square difference (RMSD) was reduced by 30 % relative to a prior attempt. (iv) The algorithm presented here allows also for separate retrieval from any of the two sensors, which makes the ice thickness dataset more resistant against failure of one of the sensors. A new way to estimate the uncertainty of ice thickness retrieval was implemented, which is based on the brightness temperature sensitivities.
Highlights
Sea ice is an important climate parameter (Moritz et al, 2002; Stroeve et al, 2007; Holland et al, 2010) and accurate knowledge of sea ice properties is needed for weather and climate modeling and prediction and for ship routing
Three Soil Moisture Ocean Salinity (SMOS) grid cells in the Kara and Barents seas located at 78.71◦ N, 57.41◦ E, 77.37◦ N, 81.71◦ E and 75.81◦ N, 79.57◦ E were used for training over a period of 3 months (1 October–26 December 2010), with sea ice thickness (SIT) obtained using the relation with the cumulated freezing degree days (CFDD) based on NCEP temperature data as presented in Huntemann et al (2014)
With more than 75 % of the ship observations being of thin ice below 50 cm ice thickness, the dataset is well suited for comparison to the SMOS– Soil Moisture Active Passive (SMAP) product presented in this paper
Summary
Sea ice is an important climate parameter (Moritz et al, 2002; Stroeve et al, 2007; Holland et al, 2010) and accurate knowledge of sea ice properties is needed for weather and climate modeling and prediction and for ship routing. The Soil Moisture Ocean Salinity (SMOS) satellite was launched by ESA in November 2009 It is a synthetic aperture passive microwave radiometer working in the L band (1.4 GHz). In 2015 the Soil Moisture Active Passive (SMAP) satellite was launched by NASA (Entekhabi et al, 2010, 2014) It carries two sensors on board, an L-band radiometer and a radar which share a rotating 6 m real aperture antenna reflector. A previous approach to convert SMOS to SMAP TBs for usage in soil moisture retrieval and assimilation systems is presented in Lannoy et al (2015) and involves a quadratic fitting of the SMOS TBs at the SMAP incidence angle and employment of auxiliary data and an empirical atmospheric model to correct for the atmospheric and extraterrestrial contributions, respectively. The fit is a step required for the SMOS and SMAP merged product to combine the observations of the two sensors at a common incidence angle
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