Arctic Sea and Sea Ice Surface Temperature anomaly time series based on reprocessed observations

'''DEFINITION '''

The OMI_CLIMATE_SST_IST_ARCTIC_sst_ist_area_averaged_anomalies product includes time series of monthly mean SST/IST anomalies over the period 1982-2024, relative to the 1991-2020 climatology (30 years), averaged for the Arctic Ocean. The SST/IST Level 4 analysis products that provide the input to the monthly averages are taken from the reprocessed product SEAICE_ARC_PHY_CLIMATE_L4_MY_011_016 with a recent update to include 2024. The product has a spatial resolution of 0.05  degrees in latitude and longitude. 
The OMI time series runs from Jan 1, 1982 to December 31, 2024 and is constructed by calculating monthly average anomalies from the reference climatology from 1991 to 2020, using the daily level 4 SST analysis fields of the SEAICE_ARC_PHY_CLIMATE_L4_MY_011_016 product. The climatological period used is defined according to the WMO recommendation (WMO, 2017) and recent U.S. National Oceanic and Atmospheric Administration practice (https://wmo.int/media/news/updated-30-year-reference-period-reflects-changing-climate,). See the Copernicus Marine Service Ocean State Reports (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018) for more information on the temperature OMI product. The times series of monthly anomalies have been used to calculate the trend in surface temperature (combined SST and IST) using Sen’s method with confidence intervals from the Mann-Kendall test (section 3 in Von Schuckmann et al., 2018).

'''CONTEXT'''
SST and IST are essential climate variables that act as important input for initializing numerical weather prediction models and fundamental for understanding air-sea interactions and monitoring climate change. Especially in the Arctic, SST/IST feedbacks amplify climate change (AMAP, 2021). In the Arctic Ocean, the surface temperatures play a crucial role for the heat exchange between the ocean and atmosphere, sea ice growth and melt processes (Key et al, 1997) in addition to weather and sea ice forecasts through assimilation into ocean and atmospheric models (Rasmussen et al., 2018). 
The Arctic Ocean is a region that requires special attention regarding the use of satellite SST and IST records and the assessment of climatic variability due to the presence of both seawater and ice, and the large seasonal and inter-annual fluctuations in the sea ice cover which lead to increased complexity in the SST mapping of the Arctic region. Combining SST and ice surface temperature (IST) is identified as the most appropriate method for determining the surface temperature of the Arctic (Minnett et al., 2020). Previously, climate trends have been estimated individually for SST and IST records (Bulgin et al., 2020; Comiso and Hall, 2014). However, this is problematic in the Arctic region due to the large temporal variability in the sea ice cover including the overlying northward migration of the ice edge on decadal timescales, and thus, the resulting climate trends are not easy to interpret (Comiso, 2003). A combined surface temperature dataset of the ocean, sea ice and the marginal ice zone (MIZ) provides a consistent climate indicator, which is important for studying climate trends in the Arctic region.

'''KEY FINDINGS'''
The basin-average trend of SST/IST anomalies for the Arctic Ocean region amounts to 0.104±0.005 °C/year over the period 1982-2024 (43 years) which corresponds to an average warming of 4.47°C. The 2-d map of warming trends indicates these are highest for the Beaufort Sea, Chuckchi Sea, East Siberian Sea, Laptev Sea, Kara Sea, Barents Sea and parts of Baffin Bay. The 2d map of Arctic anomalies for 2024 reveals regional peak warming exceeding 6°C.

'''DOI (product):''' 
https://doi.org/10.48670/mds-00323