New Land- vs. Ocean based Global Mean Temperature Reconstructions reveal high consistency except for early 20th Century Ocean Cold Anomaly

Global mean surface air temperature (GSAT) is a key diagnostic for understanding and constraining historical climate variability and change, and for climate policy. Yet, global temperature estimates (1) are usually based on blending sea surface temperatures (SST) with near-surface air temperature over land (LSAT), and (2) contain many missing values due to incomplete coverage in the historical record. While these issues are usually accounted for in model-observation comparisons, elucidating the consistency of LSAT and SST records, and their contribution to GSAT variability and change, remains difficult.

Here, we present a set of new GSAT reconstructions based separately on either the historical LSAT or SST record. The method is based on regularized linear regression models trained on climate model simulations to optimally predict GSAT from the climate model’s LSAT or SST patterns, respectively. We then predict GSAT from the HadSST4 and CRUTEM5 observational data, respectively, for each month from January 1850 up to December 2020.

We demonstrate that the land- or ocean based GSAT estimates show very similar variability and long-term changes, both in the early (1850-1900) as well as in the late record (post-1950). For example, GSAT of the past decade (2011-2020) increased by 1.15°C (LSAT-based) and 1.17°C (SST-based) relative to an early reference period (1850-1900), which is both well within IPCC AR6 estimates.However, the GSAT estimates show pronounced disagreement in the early 20th century (1900 up to around 1930), when the SST-based GSAT estimates appear on average around 0.3°C colder than the LSAT-based estimates. Decadal changes in the LSAT-based estimates are well explained by the multi-model mean of CMIP6 simulations driven with historical forcings, thus implying only a small role of unforced decadal global variability. In contrast, the SST-based estimate highlights pronounced variability during the early 20^th century cold anomaly, which may be related to concerns about instrumental cold biases in SST measurements, but overall reasons for the disagreement remain unclear. Further analysis based on physical reasoning, climate models, and proxy reconstructions, indicates that the ocean data may indeed be implausibly cold.

In conclusion, our methodology and results may help to constrain the magnitude of early 20th century warming, and thus to better understand and attribute decadal climate variability.