We quantified the regional variations and trends of pan-Arctic snow depth and density, associated with snow-ice formation. We coupled SnowModel-LG, a snow modeling system adapted for snow depth and density reconstruction over sea ice, with HIGHTSI, a 1-D sea ice thermodynamic model, to simulate snow-ice growth. Pan-Arctic model simulations were performed over the period 1 August 1980 through 31 July 2020. The model outputs were gridded to the 25x25 km Equal-Area Scalable Earth Grid (EASE-Grid), provided by the National Snow and Ice Data Center (NSIDC) (361 x 361 pixels). We compared snow depth and density from the coupled product (SnowModel-LG_HS) to outputs from the SnowModel-LG. The data set includes Pan-Arctic information of snow depth and snow density from both SnowModel-LG and SnowModel-LG_HS together with snow-ice thickness on the day of maximum snow-on-sea-ice volume. It also includes the trends of snow depth, snow density and snow-ice based on SnowModel-LG_HS. Specifically, it includes the following (8) csv files: 1. snod_sm.csv: Annual pan-Arctic snow depth on the day of maximum snow-on-sea-ice volume based on SnowModel-LG 2. snod.csv: Annual pan-Arctic snow depth on the day of maximum snow-on-sea-ice volume based on SnowModel-LG_HS 3. sden_sm.csv: Annual pan-Arctic snow density on the day of maximum snow-on-sea-ice volume based on SnowModel-LG 4. sden.csv: Annual pan-Arctic snow density on the day of maximum snow-on-sea-ice volume based on SnowModel-LG_HS 5. sice.csv: Annual pan-Arctic snow-ice thickness on the day of maximum snow-on-sea-ice volume based on SnowModel-LG_HS 6. s_snod.csv: Long-term trends of snow depth from 1980 through 2020 7. s_sden.csv: Long-term trends of snow density from 1980 through 2020 8. s_sice.csv: Long-term trends of snow-ice from 1980 through 2020 The dimensions of the csv files 1-5 are (361 pixels x 361 pixels x 40 years). The dimensions of the csv files 6-8 are (361 pixels x 361 pixels).

2022