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Abstract Accurate historical records of Earth’s surface temperatures are central to climate research and policy development. Widely-used estimates based on instrumental measurements from land and sea are, however, not fully consistent at either global or regional scales. To address these challenges, we develop the Dynamically Consistent ENsemble of Temperature (DCENT), a 200-member ensemble of monthly surface temperature anomalies relative to the 1982–2014 climatology. Each DCENT member starts from 1850 and has a 5° × 5° resolution. DCENT leverages several updated or recently-developed approaches of data homogenization and bias adjustments: an optimized pairwise homogenization algorithm for identifying breakpoints in land surface air temperature records, a physics-informed inter-comparison method to adjust systematic offsets in sea-surface temperatures recorded by ships, and a coupled energy balance model to homogenize continental and marine records. Each approach was published individually, and this paper describes a combined approach and its application in developing a gridded analysis. A notable difference of DCENT relative to existing temperature estimates is a cooler baseline for 1850–1900 that implies greater historical warming. 

Instrumental observations of subsurface ocean warming imply that ocean heat uptake has slowed 20th-century surface warming. We present high-resolution records from subpolar North Atlantic sediments that are consistent with instrumental observations of surface and deep warming/freshening and in addition reconstruct the surface-deep relation of the last 1200 years. Sites from ~1300 meters and deeper suggest an ~0.5 degrees celsius cooling across the Medieval Climate Anomaly to Little Ice Age transition that began ~1350 ± 50 common era (CE), whereas surface records suggest asynchronous cooling onset spanning ~600 years. These data suggest that ocean circulation integrates surface variability that is transmitted rapidly to depth by the Atlantic Meridional Ocean Circulation, implying that the ocean moderated Earth’s surface temperature throughout the last millennium as it does today. 

Abstract A major uncertainty in reconstructing historical sea surface temperature (SST) before the 1990s involves correcting for systematic offsets associated with bucket and engine-room intake temperature measurements. A recent study used a linear scaling of coastal station-based air temperatures (SATs) to infer nearby SSTs, but the physics in the coupling between SATs and SSTs generally gives rise to more complex regional air–sea temperature differences. In this study, an energy-balance model (EBM) of air–sea thermal coupling is adapted for predicting near-coast SSTs from coastal SATs. The model is shown to be more skillful than linear-scaling approaches through cross-validation analyses using instrumental records after the 1960s and CMIP6 simulations between 1880 and 2020. Improved skill primarily comes from capturing features reflecting air–sea heat fluxes dominating temperature variability at high latitudes, including damping high-frequency wintertime SAT variability and reproducing the phase lag between SSTs and SATs. Inferred near-coast SSTs allow for intercalibrating coastal SAT and SST measurements at a variety of spatial scales. The 1900–40 mean offset between the latest SST estimates available from the Met Office (HadSST4) and SAT-inferred SSTs range between −1.6°C (95% confidence interval: [−1.7°, −1.4°C]) and 1.2°C ([0.8°, 1.6°C]) across 10° × 10° grids. When further averaged along the global coastline, HadSST4 is significantly colder than SAT-inferred SSTs by 0.20°C ([0.07°, 0.35°C]) over 1900–40. These results indicate that historical SATs and SSTs involve substantial inconsistencies at both regional and global scales. Major outstanding questions involve the distribution of errors between our intercalibration model and instrumental records of SAT and SST as well as the degree to which coastal intercalibrations are informative of global trends. Significance Statement To evaluate the consistency of instrumental surface temperature estimates before the 1990s, we develop a coupled energy-balance model to intercalibrate measurements of sea surface temperature (SST) and station-based air temperature (SAT) near global coasts. Our model captures geographically varying physical regimes of air–sea coupling and outperforms existing methods in inferring regional SSTs from SAT measurements. When applied to historical temperature records, the model indicates significant discrepancies between inferred and observed SSTs at both global and regional scales before the 1960s. Our findings suggest remaining data issues in historical temperature archives and opportunities for further improvements. 

Data published in Lu et al. 2023 and R script repository to reproduce published figures. Lu W., D. W. Oppo, G. Gebbie, D. J. R. Thornalley, Surface climate signals transmitted rapidly to deep North Atlantic throughout last millennium. Science, 382, 834-839 https://doi.org/10.1126/science.adf1646. 

Abstract Land surface air temperatures (LSAT) inferred from weather station data differ among major research groups. The estimate by NOAA’s monthly Global Historical Climatology Network (GHCNm) averages 0.02°C cooler between 1880 and 1940 than Berkeley Earth’s and 0.14°C cooler than the Climate Research Unit estimates. Such systematic offsets can arise from differences in how poorly documented changes in measurement characteristics are detected and adjusted. Building upon an existing pairwise homogenization algorithm used in generating the fourth version of NOAA’s GHCNm(V4), PHA₀, we propose two revisions to account for autocorrelation in climate variables. One version, PHA₁, makes minimal modification to PHA₀by extending the threshold used in breakpoint detection to be a function of LSAT autocorrelation. The other version, PHA₂, uses penalized likelihood to detect breakpoints through optimizing a model-selection problem globally. To facilitate efficient optimization for series with more than 1000 time steps, a multiparent genetic algorithm is proposed for PHA₂. Tests on synthetic data generated by adding breakpoints to CMIP6 simulations and realizations from a Gaussian process indicate that PHA₁and PHA₂both similarly outperform PHA₀in recovering accurate climatic trends. Applied to unhomogenized GHCNmV4, both revised algorithms detect breakpoints that correspond with available station metadata. Uncertainties are estimated by perturbing algorithmic parameters, and an ensemble is constructed by pooling 50 PHA₁- and 50 PHA₂-based members. The continental-mean warming in this new ensemble is consistent with that of Berkeley Earth, despite using different homogenization approaches. Relative to unhomogenized data, our homogenization increases the 1880–2022 trend by 0.16 [0.12, 0.19]°C century⁻¹(95% confidence interval), leading to continental-mean warming of 1.65 [1.62, 1.69]°C over 2010–22 relative to 1880–1900. Significance StatementAccurately correcting for systematic errors in observational records of land surface air temperature (LSAT) is critical for quantifying historical warming. Existing LSAT estimates are subject to systematic offsets associated with processes including changes in instrumentation and station movement. This study improves a pairwise homogenization algorithm by accounting for the fact that climate signals are correlated over time. The revised algorithms outperform the original in identifying discontinuities and recovering accurate warming trends. Applied to monthly station temperatures, the revised algorithms adjust trends in continental mean LSAT since the 1880s to be 0.16°C century⁻¹greater relative to raw data. Our estimate is most consistent with that from Berkeley Earth and indicates lesser and greater warming than estimates from NOAA and the Met Office, respectively. 

Abstract Oceanic transient tracers, such as chlorofluorocarbons (CFCs) and sulfur‐hexafluoride (SF₆), trace the propagation of intermediate‐to‐abyssal water masses in the ocean interior. Their temporal and spatial sparsity, however, has limited their utility in quantifying the global ocean circulation and its decadal variability. TheTime‐Correction Method(TCM) presented here is a new approach to leverage the available CFCs and SF₆observations to solve for the Green's functions (GFs) describing the steady‐state transport from the surface to the ocean interior. From the GFs, we reconstruct global tracer concentrations (and associated uncertainties) in the ocean interior at annual resolution (1940–2021). The spatial resolution includes 50 neutral density levels that span the water column along World Ocean Circulation Experiment/Global Ocean Ship‐Based Hydrographic Investigations Program lines. The reconstructed tracer concentrations return a global view of CFCs and SF₆spreading into new regions of the interior ocean, such as the deep north‐western Pacific. For example, they capture the southward spreading and equatorial recirculation of distinct North Atlantic Deep Water components, and the spreading of CFC‐rich Antarctic Bottom Water out of the Southern Ocean and into the North Pacific, East Indian, and West Atlantic. The reconstructed tracer concentrations fit the data in most locations (∼75%), indicating that a steady‐state circulation holds for the most part. Discrepancies between the reconstructed and observed concentrations offer insight into ventilation rate changes on decadal timescales. As an example, we infer decadal changes in Subantartic Mode Water (SAMW) and find an increase in SAMW ventilation from 1992 to 2014, highlighting the skill of the TCM in leveraging the sparse tracer observations. 

Abstract The last deglaciation (~20–10 kyr BP) was characterized by a major shift in Earth's climate state, when the global mean surface temperature rose ~4 °C and the concentration of atmospheric CO₂increased ~80 ppmv. Model simulations suggest that the initial 30 ppmv rise in atmospheric CO₂may have been driven by reduced efficiency of the biological pump or enhanced upwelling of carbon‐rich waters from the abyssal ocean. Here we evaluate these hypotheses using benthic foraminiferal B/Ca (a proxy for deep water [CO₃²⁻]) from a core collected at 1,100‐m water depth in the Southwest Atlantic. Our results imply that [CO₃²⁻] increased by 22 ± 2 μmol/kg early in Heinrich Stadial 1, or a decrease in ΣCO₂of approximately 40 μmol/kg, assuming there were no significant changes in alkalinity. Our data imply that remineralized phosphate declined by approximately 0.3 μmol/kg during Heinrich Stadial 1, equivalent to 40% of the modern remineralized signal at this location. Because tracer inversion results indicate remineralized phosphate at the core site reflects the integrated effect of export production in the sub‐Antarctic, our results imply that biological productivity in the Atlantic sector of the Southern Ocean was reduced early in the deglaciation, contributing to the initial rise in atmospheric CO₂.