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1. Internal climate variability modulates decadal changes in ocean anthropogenic carbon storage

   https://doi.org/10.1088/1748-9326/ada2ad  

   Olivarez, Holly_C ; Lovenduski, Nicole_S ; Maroon, Elizabeth ; Müller, Jens_D ; Fay, Amanda_R ; Krumhardt, Kristen_M ; Levy, Michael_N ; Lindsay, Keith ; McKinley, Galen_A ; Rader, Jamin_K ( January 2025 , Environmental Research Letters)

   The ocean removes man-made (anthropogenic) carbon from the atmosphere and thereby mitigates climate change. Observations from global hydrographic surveys reveal the spatial and temporal evolution of the ocean inventory of anthropogenic carbon and suggest substantial decadal variability in historical storage rates. Here, we use a 100-member ensemble of an Earth system model to investigate the influence of external forcing and internal climate variability on historical changes in ocean anthropogenic carbon storage over 1994 to 2014. Our findings reveal that the externally forced, decadal changes in storage are largest in the Atlantic (2–4 mmol m⁻³decade⁻¹) and positive nearly everywhere. Internal climate variability modulates regional ocean anthropogenic carbon storage trends by up to 10 mmol m⁻³decade⁻¹. The influence of internal climate variability on decadal storage changes is most prominent at depths of ∼300 m and at the edges of the subtropical gyres. Internal variability in anthropogenic carbon in the extratropics has high spectral power on decadal to multi-decadal timescales, indicating that the approximately decadal repetitions of hydrographic surveys may produce storage change estimates that are heavily influenced by internal climate variability.

    

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2. Global-scale multidecadal variability missing in state-of-the-art climate models

   https://doi.org/10.1038/s41612-018-0044-6  

   Kravtsov, S. ; Grimm, C. ; Gu, S. ( November 2018 , npj Climate and Atmospheric Science)

   Reliability of future global warming projections depends on how well climate models reproduce the observed climate change over the twentieth century. In this regard, deviations of the model-simulated climate change from observations, such as a recent “pause” in global warming, have received considerable attention. Such decadal mismatches between model-simulated and observed climate trends are common throughout the twentieth century, and their causes are still poorly understood. Here we show that the discrepancies between the observed and simulated climate variability on decadal and longer timescale have a coherent structure suggestive of a pronounced Global Multidecadal Oscillation. Surface temperature anomalies associated with this variability originate in the North Atlantic and spread out to the Pacific and Southern oceans and Antarctica, with Arctic following suit in about 25–35 years. While climate models exhibit various levels of decadal climate variability and some regional similarities to observations, none of the model simulations considered match the observed signal in terms of its magnitude, spatial patterns and their sequential time development. These results highlight a substantial degree of uncertainty in our interpretation of the observed climate change using current generation of climate models.

    

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3. Quantifying Contributions of Internal Variability and External Forcing to Atlantic Multidecadal Variability Since 1870

   https://doi.org/10.1029/2020GL089504  

   Qin, Minhua ; Dai, Aiguo ; Hua, Wenjian ( November 2020 , Geophysical Research Letters)

   Identifying the mechanisms behind the Atlantic Multidecadal Variability (AMV) is crucial for understanding and predicting decadal climate change. However, what is behind the AMV is still debated. A key issue is the relative role of internal variability (IV) and external forcing in causing the AMV. By analyzing observations and a large number of climate model simulations, here we show that IV and volcanic and anthropogenic aerosols all influenced the AMV over the last ~150 years. Although the AMV since 1870 resulted mainly from IV, decadal variations in aerosol forcing happen to be in phase with the IV‐induced AMV and thus enlarged its amplitudes, especially since the late 1920s. Our results support the notion that the AMV resulted from both internal climate variability and decadal changes in aerosols but are inconsistent with the conclusion that the recent AMV is mainly a direct response to external forcing.

    

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4. Detecting Regional Modes of Variability in Observation‐Based Surface Ocean p CO 2

   https://doi.org/10.1029/2018GL081756  

   Landschützer, Peter ; Ilyina, Tatiana ; Lovenduski, Nicole S. ( March 2019 , Geophysical Research Letters)

   We use a neural network‐based estimate of the sea surface partial pressure of CO₂(pCO₂) derived from measurements assembled within the Surface Ocean CO₂Atlas to investigate the dominant modes ofpCO₂variability from 1982 through 2015. Our analysis shows that detrended and deseasonalized sea surfacepCO₂varies substantially by region and the respective frequencies match those from the major modes of climate variability (Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, multivariate ENSO index, Southern Annular Mode), suggesting a climate modulated air‐sea exchange of CO₂. We find that most of the regionalpCO₂variability is driven by changes in the ocean circulation and/or changes in biology, whereas the North Atlantic variability is tightly linked to temperature variations in the surface ocean and the resulting changes in solubility. Despite the 34‐year time series, our analysis reveals that we can currently only detect one to two periods of slow frequency oscillations, challenging our ability to robustly linkpCO₂variations to climate variability.

    

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5. The phase change in the annual cycle of sea surface temperature

   https://doi.org/10.1038/s41612-024-00591-8  

   Yang, Fucheng ; Wu, Zhaohua ( February 2024 , npj Climate and Atmospheric Science)

   In recent decades, many research efforts focused on global climate change, multidecadal, decadal, interannual variability, and the increasing extreme events of sea surface temperature. In contrast, the continuous evolution of the reference frame, the annual cycle of SST used to quantify the aforementioned variability and changes, has long been overlooked, resulting in difficulties in understanding the underlying physical mechanisms responsible for these variability and changes. In this study, we strive to bridge this gap on the phase changes in SST annual cycle. By devising a running correlation-based method, we can now quantify the non-sinusoidal shape of the evolving SST annual cycle, such as the advancing or delaying of summer and winter peaking times. It is revealed that the varying phases of summer or winter are more closely linked to multidecadal SST variability than to long-term climate change. Both the systematic shift of the phase and alterations in the annual cycle shape contribute to the phase changes, which explain 0.4~1.0 °C of monthly SST anomaly with respect to the climatological annual cycle in a multidecadal timescale. Furthermore, it is evident that the SST phases in historical simulations are better captured in winter than in summer and exhibit stronger variation compared with observation.

    

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