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1. Monthly Sea-Surface Temperature, Sea Ice, and Sea-Level Pressure over 1850–2023 from Coupled Data Assimilation

   https://doi.org/10.1175/JCLI-D-25-0021.1  

   Cooper, Vincent T; Hakim, Gregory J; Armour, Kyle C (July 2025, Journal of Climate)

   Abstract Historical observations of Earth’s climate underpin our knowledge and predictions of climate variability and change. However, the observations are incomplete and uncertain, and existing datasets based on these observations typically do not assimilate observations simultaneously across different components of the climate system, yielding inconsistencies that limit understanding of coupled climate dynamics. Here we use coupled data assimilation, which synthesizes observational and dynamical constraints across all climate fields simultaneously, to reconstruct globally resolved sea-surface temperature (SST), near-surface air temperature (T), sea-level pressure (SLP), and sea-ice concentration (SIC), over 1850–2023. We use a Kalman filter and forecasts from an efficient emulator (Linear Inverse Model; LIM) to assimilate observations of SST, land T, marine SLP, and satellite-era SIC. We account for model error by training LIMs on eight CMIP6 models, and we use the LIMs to generate eight independent reanalyses with 200 ensemble members, yielding 1600 total members. Key findings in the Tropics include post-1980 trends in the Walker circulation that are consistent with past variability, whereas the tropical SST contrast (the difference between warmer and colder SSTs) shows a distinct strengthening since 1975. ENSO amplitude exhibits substantial low-frequency variability and a local maximum in variance over 1875–1910. In polar regions, we find a muted cooling trend in the Southern Ocean post-1980 and substantial uncertainty. Changes in Antarctic sea ice are relatively small between 1850 and 2000, while Arctic sea ice declines by 0.5±0.1 (1σ) million km²during the 1920s. 

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2. Observing Arctic Sea Ice

   Webster, Melinda A.; Rigor, Ignatius; Wright, Nicholas C. (March 2022, Oceanography)

   Our understanding of Arctic sea ice and its wide-ranging influence is deeply rooted in observation. Advancing technologies have profoundly improved our ability to observe Arctic sea ice, document its processes and properties, and describe atmosphere-ice-ocean interactions with unprecedented detail. Yet, our progress toward better understanding the Arctic sea ice system is mired by the stark disparities between observations that tend to be siloed by method, scientific discipline, and application. This article presents a review and philosophical design for observing sea ice and accelerating our understanding of the Arctic sea ice system. We give a brief history of Arctic sea ice observations and showcase the 2018 melt season within the context of five observational themes: spatial heterogeneity, temporal variability, cross-disciplinary science, scalability, and retrieval uncertainty. We synthesize buoy data, optical imagery, satellite retrievals, and airborne measurements to demonstrate how disparate data sets can be woven together to transcend issues of observational scale. The results show that there are limitations to interpreting any single data set alone. However, many of these limitations can be surmounted by combining observations that cross spatial and temporal scales. We conclude the article with pathways toward enhanced coordination across observational platforms in order to: (1) optimize the scientific, operational, and community return on observational investments, and (2) facilitate a richer understanding of Arctic sea ice and its role in the climate system. 

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3. The latitudinal temperature gradient and its climate dependence as inferred from foraminiferal δ ¹⁸ O over the past 95 million years

   https://doi.org/10.1073/pnas.2111332119  

   Gaskell, Daniel E.; Huber, Matthew; O’Brien, Charlotte L.; Inglis, Gordon N.; Acosta, R. Paul; Poulsen, Christopher J.; Hull, Pincelli M. (March 2022, Proceedings of the National Academy of Sciences)

   The latitudinal temperature gradient is a fundamental state parameter of the climate system tied to the dynamics of heat transport and radiative transfer. Thus, it is a primary target for temperature proxy reconstructions and global climate models. However, reconstructing the latitudinal temperature gradient in past climates remains challenging due to the scarcity of appropriate proxy records and large proxy–model disagreements. Here, we develop methods leveraging an extensive compilation of planktonic foraminifera δ 18 O to reconstruct a continuous record of the latitudinal sea-surface temperature (SST) gradient over the last 95 million years (My). We find that latitudinal SST gradients ranged from 26.5 to 15.3 °C over a mean global SST range of 15.3 to 32.5 °C, with the highest gradients during the coldest intervals of time. From this relationship, we calculate a polar amplification factor (PAF; the ratio of change in >60° S SST to change in global mean SST) of 1.44 ± 0.15. Our results are closer to model predictions than previous proxy-based estimates, primarily because δ 18 O-based high-latitude SST estimates more closely track benthic temperatures, yielding higher gradients. The consistent covariance of δ 18 O values in low- and high-latitude planktonic foraminifera and in benthic foraminifera, across numerous climate states, suggests a fundamental constraint on multiple aspects of the climate system, linking deep-sea temperatures, the latitudinal SST gradient, and global mean SSTs across large changes in atmospheric CO 2 , continental configuration, oceanic gateways, and the extent of continental ice sheets. This implies an important underlying, internally driven predictability of the climate system in vastly different background states. 

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4. Global and Regional Discrepancies between Early-Twentieth-Century Coastal Air and Sea Surface Temperature Detected by a Coupled Energy-Balance Analysis

   https://doi.org/10.1175/JCLI-D-22-0569.1  

   Chan, Duo; Gebbie, Geoffrey; Huybers, Peter (April 2023, Journal of Climate)

   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. 

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5. The Asymmetry of Daily Sea Ice Variations and Its Impacts on Surface Shortwave Radiation over Arctic during Summer

   https://doi.org/10.1175/JCLI-D-25-0036.1  

   Deng, Jiechun; Dai, Aiguo (February 2026, Journal of Climate)

   Abstract Arctic sea ice loss can affect surface energy balance during summer, but it is unclear how surface shortwave (SW) radiation can respond to natural variations of sea ice cover (SIC). Here, we propose a decomposition framework to approximately isolate the impact of daily SIC variations on surface net SW (SW_net) radiation mainly through the sea ice–cloud and sea ice–albedo feedbacks. Using model simulations under preindustrial conditions, we show that daily SIC anomalies exhibit an asymmetry in amplitude and occurrence frequency during June–August. Specifically, negative SIC anomalies occur less frequently but with larger amplitudes over north of the marginal ice zone (MIZ), similar to positive SIC anomalies over south of the MIZ. Regions with large negative SIC anomalies exhibit reduced lower-tropospheric stability, higher evaporation, and thus higher near-surface specific humidity, which increase low-level relative humidity and cloud fraction. These cloud anomalies lead to decreased mean surface downward SW (SW_dn) radiation over north of the MIZ. Regions with large positive SIC anomalies show roughly the opposite over south of the MIZ. This asymmetric effect ultimately causes a seasonal-mean SW_netchange over the Arctic. In reanalysis, the mean change of Arctic summer SW_netbetween two historical periods can also be decomposed into the asymmetric impact of daily SIC variations and the impact of the mean SIC change based on the proposed framework, which is qualitatively consistent with the model results. Our findings suggest that the asymmetry of daily SIC variations and the associated other anomaly fields can cause mean-state changes in Arctic surface energy fluxes during summer. Significance StatementArctic sea ice regulates the absorption of surface shortwave radiation during the warm season. While the impact of sea ice loss is well recognized, it is unclear whether and how daily sea ice fluctuations can influence Arctic mean surface shortwave radiation. Here, we investigate the asymmetry in daily sea ice variations and its relationship with cloudiness and surface downward shortwave radiation in summer using model simulations and reanalysis, together with the asymmetric impacts on surface-absorbed shortwave radiation using a decomposition framework. Our results highlight the importance of asymmetric daily sea ice variations in causing mean-state changes and have implications for future projections of Arctic climate as such variations will diminish when sea ice melts away under warmer climates. 

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