Global monthly sea surface temperature and sea ice reconstruction for historical AGCM simulations
- 1Oeschger Centre for Climate Change Research, University of Bern, Climatology, Switzerland.
- 2Institute of Geography, University of Bern, Switzerland.
We present a 50-member global monthly gridded Sea Surface Temperature (SST) and Sea Ice Concentration (SIC) dataset covering 850 years (1000–1849). The SST fields are based on an existing coarse-resolution ensemble of annual reconstructions and augmented with intra-annual and sub-grid scale variability, such that the annual means of the coarse resolution SST reconstructions are preserved. We utilize a large body of historical observational inputs from ICOADS (1780 – 1849) in an offline data assimilation approach.
Furthermore, the best sea ice analogs are selected based on a measure of similarity between subpolar and midlatitude SSTs of our reconstruction and HadISST SIC. The resulting SST and SIC fields will reflect a spatially and temporal consistent representation of the historical state of the ocean and are reconstructed to be used as forcing for AGCM simulations.
Reference:
Samakinwa, E., Valler, V., Hand, R. et al. An ensemble reconstruction of global monthly sea surface temperature and sea ice concentration 1000–1849. Sci Data 8, 261 (2021). https://doi.org/10.1038/s41597-021-01043-1
How to cite: Samakinwa, E., Valler, V., Hand, R., and Brönnimann, S.: Global monthly sea surface temperature and sea ice reconstruction for historical AGCM simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11664, https://doi.org/10.5194/egusphere-egu22-11664, 2022.
