Satellite-based surface temperatures of the Arctic ocean and sea ice, 1982–2021.

The Arctic is warming faster than any other region. Despite much attention there has actually been limited consensus on the magnitude of Arctic amplification over time. Within the framework of the Copernicus Marine Monitoring Service Sea Ice Thematic Assembly Center, the first gap-free (L4) of combined sea surface temperature (SST) and sea ice surface temperature (IST) climate data record of the Arctic (>58°N) has been developed for the period 1982-2021. The data set has been generated using optimal interpolation to combine multiple infrared satellite observations to daily, gap-free fields with a spatial resolution of 0.05 degrees. The combination of SST and IST provides a consistent climate indicator which can be used to monitor day-to-day variations as well as climate trends in the Arctic Ocean. Validation against in situ measurements from drifting buoys, moored buoys and Argo floats shows mean differences of 0.01 °C, 0.04 °C and 0.04 °C and standard deviations of 0.54 °C, 0.56 °C and 0.51 °C, respectively for the open ocean. Over sea ice, validation shows a mean difference of 1.52 °C and standard deviation of 3.12 °C, for skin surface temperatures. For air temperatures from the North Pole (NP) ice drifting stations as well as ECMWF distributed buoys and CRREL buoys, validation shows mean differences of −2.35 °C, −3.21 °C and –2.87 °C and standard deviations of 3.12 °C, 3.34 °C and 3.36 °C, respectively. Analysis of the CDR show sea and sea-ice surface temperature of the Arctic has risen with about 4.5 °C over the period 1982–2021, with a peak warming of around 10 °C in the northeastern Barents Sea. The L4 ISTs have been converted to near surface air temperatures (T2m) and initial results indicate that it is possible to derive reliable T2m over sea ice based on the satellite-observed L4 ISTs. The satellite-derived L4 T2m product provides an important supplement to the sparse in situ air temperature network in the Arctic and to the existing model-based air temperatures. It has a large potential to be used for assimilation, global surface temperature reconstructions or for evaluation of global reanalyses and climate models.