Editing IPCC:AR6/WGI/Chapter-1 (section)

==== 1.5.2.2 Sparse Input Reanalyses of the Instrumental Era ====

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Although reanalyses such as ERA5 take advantage of new observational datasets and present a great improvement in atmospheric reanalyses, the issues introduced by the evolving observational network remain. Sparse input reanalyses, where only a limited set of reliable and long-observed records are assimilated, address these issues, with the limitation of fewer observational constraints. These efforts are sometimes called centennial-scale reanalyses. One example is the atmospheric 20th century Reanalysis ( [[#Compo--2011|Compo et al., 2011]] ; [[#Slivinski--2021|Slivinski et al., 2021]] ) which assimilates only surface and sea-level pressure observations, and is constrained by time-varying observed changes in atmospheric constituents, prescribed sea surface temperatures and sea ice concentration, creating a reconstruction of the weather over the whole globe every three hours for the period 1806–2015. The ERA-20C atmospheric reanalysis (covering 1900–2010; [[#Poli--2016|Poli et al., 2016]] ) also assimilates marine wind observations, and CERA-20C is a centennial-scale reanalysis that assimilates both atmospheric and oceanic observations for the 1901–2010 period ( [[#Laloyaux--2018|Laloyaux et al., 2018]] ). These centennial-scale reanalyses are often run as ensembles that provide an estimate of the uncertainty in the simulated variables over space and time. [[#Slivinski--2021|Slivinski et al. (2021)]] conclude that the uncertainties in surface circulation fields in version 3 of the 20th century Reanalysis are reliable and that there is also skill in its tropospheric reconstruction over the 20th century. Long-term changes in other variables, such as precipitation, also agree well with direct observation-based datasets (Sections 2.3.1.3 and 8.3.2.8).

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