Arctic sea ice type distribution from various microwave remote sensing products

<p>Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study analyzed eight daily SITY products from five retrieval approaches covering the winters of 1999&#8211;2019, including purely radiometer-based (C3S-SITY), scatterometer-based (KNMI-SITY and IFREMER-SITY) and combined ones (OSISAF-SITY and Zhang-SITY). These SITY products were inter-compared against a weekly sea ice age product (i.e. NSIDC-SIA) and evaluated with five Synthetic Aperture Radar images. The average Arctic multiyear ice (MYI) extent difference between the SITY products and NSIDC-SIA varies from -1.32&#215;10⁶ km² to 0.49&#215;10⁶ km² . Among all, KNMI-SITY and Zhang-SITY in the QSCAT period (2002-2009) agree best with NSIDC-SIA and perform the best, with smallest bias of -0.001&#215;10⁶ km² in FYI extent and -0.02&#215;10⁶ km² in MYI extent, respectively. In the ASCAT period (2007-2019), KNMI-SITY tends to overestimate MYI (especially in early winter), whereas Zhang-SITY and IFREMER-SITY tend to underestimate MYI. C3S-SITY performs well in some early winter cases however exhibits large temporal variabilities as OSISAF-SITY. Factors that could impact performances of the SITY products are analyzed and summarized: (1) Ku-band scatterometer generally performs better than C-band scatterometer on SITY discrimination, while the latter sometimes identifies first-year ice (FYI) more accurately, especially when surface scattering dominants the backscatter signature. (2) Simple combination of scatterometer and radiometer data is not always beneficial without further rules of priority. (3) The representativeness of training data and efficiency of classification are crucial for SITY classification. Spatial and temporal variation of characteristic training dataset should be well accounted in the SITY method. (4) Post-processing corrections play important roles and should be considered with caution.</p>