## 4 Conclusions  
We have processed the CS2 data archive from 2011 to 2019 to retrieve SWHs in the ice free polar ocean with a focus on the Arctic. These data are are available as 1 Hz satellite records and combined into 100 km spatial and 1 day temporal resolution gridded product. We focussed on obtaining wave height information close to the sea ice edge in order to aid the development of wave models in the seasonally ice covered Arctic ocean. The new semi-analytical retracker of [23] has accurately matched both pulse limited (LRM) and synthetic aperture (SAR) waveforms, processed with computational efficiency. The retracker is consistent with previous retracking attempts [21; 31] and has given notable improvements in both coverage and data quality. Compared to the RADS data set, there are marked differences in the two different modes of operation. Whilst the LRM mode uses the same base data, in SAR mode RADS uses a pre-processed pLRM. This difference along with our discovered LRM to SAR mode bias, give spatial inconsistencies for both data. There is a clear improvement with the  
Figure 12: Antarctic climatological maps of retrieved SWH (m) for (**a**) Jan. Feb. Mar., (**b**) Apr. May. Jun., (**c**) Jul. Aug. Sep., (**d**) Oct. Nov. Dec. for the years 2011–2019. Plot (**a**) indicates the regions used in Figure S1 (Supplemental Material). Overlaid on each plots are the contours of 15% 50% and 85% sea NSIDC ice concentration for that quarter. Note that the Weddell, Indian, West Pacific, Ross and Bellingshausen & Admunsen sectors extend only to \(-60^{\circ}\), whilst the Southern Ocean region is over all longitudes..  
marginal seas, where the RADS processing chain does not adequately filter out sea ice contaminated open ocean radar echo waveforms and thus the accuracy of any retrieved SWH. The developed processing chain allows for the accurate checking of our waveform fit to gather the cleanest and widest data coverage. Whilst our retrieved SWH show the closest correlation to the SAMOSA physical retracker obtainable through the ESA GPOD system, our dedicated SWH focussed processing chain allows for the processing of the entire CS2 time series, a task not possible using the GPOD system that only works for CS2 SAR mode. Note that the consistency of our 1 Hz downsampled waveform processing has the same data quality to the 20 Hz processed SAMOSA data. Far from the influence of sea ice, in the North Atlantic, the comparison with buoy K7, Figure 6, shows consistency for all the retracking methods, with a slight improvement for our SAR specific new method and the SAMOSA data. In marginal seas our new data maintains its consistency to in situ observations where other products can become degraded or lose coverage. This data set was produced as part of the NERC Marginal Ice Zone project to address the lack of observational wave height data in marginal seas. As we have focussed upon the accurate analysis of CryoSat2 data in these locations and made sure to make our data are consistent with those produced for further ocean data, this data set makes a significant contribution to the validation of ocean wave models in polar regions. The data are available at [[http://www.cpom.ucl.ac.uk/ocean_wave_height/](http://www.cpom.ucl.ac.uk/ocean_wave_height/)]([http://www.cpom.ucl.ac.uk/ocean_wave_height/](http://www.cpom.ucl.ac.uk/ocean_wave_height/)), (accessed on 20 August 2021) with a summary of the processing code at [[https://github.com/CPOMUCL/SWH](https://github.com/CPOMUCL/SWH)]([https://github.com/CPOMUCL/SWH](https://github.com/CPOMUCL/SWH)), (accessed on 20 August 2021). The following are available online at www.mdpi.com/xxx/s1, supplemental Figures S1 and S2 are additional information of Section 3.8. Conceptualization, T.A., M.T. and H.H. ; methodology, T.A. and H.H. ; software, T.A. and H.H. ; validation, H.H. ; formal analysis, H.H., M.T. and J.L. ; data curation, H.H. and A.R. ; writing, H.H. ; supervision, project administration and funding acquisition, M.T.