SMOS and SMAP combined SSS L3 maps over the Chukchi and the Beaufort seas during summer 2019

SSS weekly fields are derived from SMOS and SMAP measurements from June to September 2019. SMOS SSS is from a modified version of the CEC-LOCEAN L3 Arctic, distributed by the “Centre Aval de Traitement des Données SMOS” (CATDS; Supply et al., 2020). In this new version, the SMOS level 2 SSS are from the ESA Climate Change Initiative (CCI) v3.2 reprocessing described in Perrot et al. (2021). In comparison with level 2 SSS used in Supply et al. (2020): - SSS is computed with an updated dielectric constant parametrization (Boutin et al., 2020). - SMOS vicarious calibration, the so-called Ocean Target Transformation, is derived using Argo optimal interpolated SSS (Gaillard et al., 2016) instead of a climatology. - SST and wind speed used as priors in the SSS retrieval are taken from European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 instead of ECMWF forecasted fields. - Updated sea ice filtering derived from the difference between SMOS retrieved pseudo dielectric constant (Acard parameter) and the one expected from retrieved SSS and SST: instead of being applied only at level 3, sea ice filtering is applied both at level 2 (swath product) and at level 3 (weekly averaged product). SSS is derived with a correction of SST-induced bias using Remote Sensing Systems (RSS) SST. SMOS SSS are averaged over 9 days on a 25km Equal-Area Scalable Earth (EASE) 2.0 grid adapted to polar areas. These fields have an effective spatial resolution close to 50 km, corresponding to the original resolution of SMOS SSS (no spatial interpolation is applied from level 2 to level 3). Given the difficulty to find a reference to adjust absolute SSS values in the Arctic Ocean, this product does not contain any Land Sea Contamination (LSC) correction; nevertheless, in the averaging process, SMOS SSS is weighted by the Chi2 of the retrieval, and we expect it to be degraded on SMOS dwell lines largely contaminated by LSC. SMAP SSS is from the Jet Propulsion Laboratory (JPL; Fore et al., 2020) version 4.3 8-day averaged SSS provided on a 0.25° regular grid, with a spatial interpolation from level 2 to level 3. In this product that uses a LSC correction, the effective spatial resolution of SSS is close to 60 km. The use of JPL SMAP SSS instead of SMAP SSS distributed by RSS is motivated by a less restrictive ice mask in the polar regions. Between 19 June 19th and July 23rd 2019, SMAP was in safe mode and did not provide SSS estimates. SMOS, SMAP and combined SSS are provided with an uncertainty estimated by the SSS retrieval algorithm. Additional sea ice filtering applied to SMOS and SMAP SSS: only SSS estimates with an uncertainty lower than 0.6 pss are considered in the following. SSS estimates from both satellites (SMAP interpolated in the 25 km EASE 2.0 grid) are intercalibrated using summer 2019 saildrones measurements (Saildrone (2020), Vazquez-Cuervo et al., 2021) and finally combined. Video: illustration of SSS evolution (SMOS, SMAP and combined SSS) during summer sea ice retreat between June and September 2019 (Ocean and Sea Ice Satellite Application Facility (OSI-SAF) Sea Ice Concentration (SIC) derived from AMSR-2 measurements, provided by the Danish and the Norwegian Meteorological Institute).

本数据集的周级海表盐度（Sea Surface Salinity, SSS）产品源自2019年6月至9月的土壤湿度与海洋盐度卫星（Soil Moisture and Ocean Salinity, SMOS）和土壤湿度主动被动卫星（Soil Moisture Active Passive, SMAP）观测数据。其中SMOS海表盐度数据取自由"Centre Aval de Traitement des Données SMOS" (CATDS；Supply等，2020)分发的改进版CEC-LOCEAN北极L3级产品。在该新版产品中，SMOS L2级海表盐度数据来自Perrot等（2021）所述的欧洲空间局气候变化倡议（ESA Climate Change Initiative, CCI）v3.2再处理数据集。相较于Supply等（2020）所采用的L2级海表盐度数据，本次更新包含以下改进：- 海表盐度计算采用了更新后的介电常数参数化方案（Boutin等，2020）；- SMOS替代定标（即所谓“洋面目标校正变换”）采用Argo最优插值海表盐度（Gaillard等，2016）计算，而非气候态数据；- 海表盐度反演中作为先验信息的海表温度（Sea Surface Temperature, SST）与风速数据取自欧洲中期天气预报中心（European Centre for Medium-Range Weather Forecasts, ECMWF）ERA5再分析数据集，而非ECMWF预报场数据；- 基于SMOS反演伪介电常数（Acard参数）与由反演海表盐度和海表温度推算的伪介电常数之差，更新了海冰滤波方案：该滤波不再仅应用于L3级产品，而是同时作用于L2级（条带产品）与L3级（周平均产品）。本数据集通过遥感系统公司（Remote Sensing Systems, RSS）提供的海表温度数据，对海表温度引起的盐度偏差进行了校正。SMOS海表盐度数据在适配极地区域的25km等面积可缩放地球（EASE）2.0网格上进行9天平均，其有效空间分辨率约为50km，与SMOS海表盐度的原始分辨率一致（L2级至L3级未进行空间插值）。由于北极海域难以找到用于校正绝对海表盐度值的参考数据，本产品未包含海陆污染（Land Sea Contamination, LSC）校正步骤；但在平均过程中，SMOS海表盐度数据以反演的卡方（χ²）值作为权重，因此在受海陆污染严重影响的SMOS观测驻留带，该数据质量会有所下降。SMAP海表盐度数据取自喷气推进实验室（Jet Propulsion Laboratory, JPL；Fore等，2020）发布的v4.3版本8天平均海表盐度产品，该产品采用0.25°规则网格，且从L2级至L3级进行了空间插值。该产品包含海陆污染校正步骤，其海表盐度有效空间分辨率约为60km。之所以选用JPL发布的SMAP海表盐度数据而非RSS分发的版本，是因为前者在极地区域采用了限制更宽松的海冰掩膜。2019年6月19日至7月23日期间，SMAP卫星处于安全模式，未提供海表盐度反演结果。SMOS、SMAP及融合后的海表盐度产品均附带由海表盐度反演算法估算的不确定性误差。此外，本数据集对SMOS与SMAP海表盐度数据增设了海冰滤波步骤：仅保留不确定性低于0.6 pss的海表盐度反演结果。两颗卫星的海表盐度反演结果（其中SMAP数据已插值至25km EASE 2.0网格）通过2019年夏季帆式海洋无人机观测数据（Saildrone，2020；Vazquez-Cuervo等，2021）完成交叉定标，最终进行融合。配套视频：展示2019年6月至9月夏季海冰消融期间海表盐度的变化过程（SMOS、SMAP及融合海表盐度数据），海冰密集度（Sea Ice Concentration, SIC）数据取自丹麦与挪威气象研究所提供的第二代先进微波扫描辐射计（Advanced Microwave Scanning Radiometer 2, AMSR-2）观测反演结果，由海洋与海冰卫星应用设施（Ocean and Sea Ice Satellite Application Facility, OSI-SAF）发布。