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The European Centre for Medium-range Weather Forecasts (ECMWF) has produced the ocean-atmosphere coupled reanalysis for the twentieth century, CERA-20C, following on from the similar but atmosphere-only reanalysis ERA-20C. Here we demonstrate the capability of CERA-20C in producing more physically consistent ocean and atmosphere boundary conditions, by focusing on sea surface temperature (SST)-precipitation intraseasonal relationships. CERA-20C reproduces well the observed SST-precipitation correlations, while these relationships are poorly represented in ERA-20C, with the greatest discrepancies in the early 1900s. The improved relationships in CERA-20C are due to intraseasonal improvements in SST that are not present in the external HadISST2 product. In CERA-20C, SST-precipitation relationships are slightly weaker in the 1900s than in the 2000s, mainly due to differences in the assimilated observation density. We also find that the coupled model initialized from CERA-20C in the 2000s realistically simulates these relationships, while relaxing SST toward HadISST2 tends to damp these relationships. CERA-20C has improved mean and variance in precipitation over ERA-20C, but these are mostly due to improvements in the atmospheric model and not due to coupled feedbacks.

Plain Language Summary Climate reanalyses, reconstructions of past weather and climate conditions, are of importance in the climate research and forecasting community. The European Centre for Medium-range Weather Forecasts has recently launched its first ocean-atmosphere coupled reanalysis for the twentieth century, known as CERA-20C. Many users are expected. One of the main breakthroughs of this state-of-the-art data set is resolving the air-sea interactions via coupled modeling, while the ocean and atmosphere models are constrained separately by observations. This paper shows that the sea surface temperature-precipitation relationships are much better reproduced in CERA-20C than in its predecessors. Such significant improvement in CERA-20C is due to the ocean surface that more realistically reflects the intraseasonal variations in the atmosphere through the coupled processes. The results highlight the advances of coupled reanalysis in producing physically consistent ocean and atmosphere conditions, indicating that we are moving in the right direction on climate reanalysis. This could have an immediate impact on the plans for producing global climate reanalyses at some institutions. In addition, the metrics of lead-lag correlations applied here could be easily implemented to other climate data sets, to evaluate the quality of climate data.