More Like this

1. Fingerprinting Low-Frequency Last Millennium Temperature Variability in Forced and Unforced Climate Models

   https://doi.org/10.1175/JCLI-D-22-0810.1  

   Cleveland Stout, Rebecca ; Proistosescu, Cristian ; Roe, Gerard ( October 2023 , Journal of Climate)

   Constraining unforced and forced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and last millennium Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability at multidecadal and longer time scales. This mismatch suggests that existing simulations underestimate either external or internal drivers of climate variability. In addition, large differences arise across GCMs in both the magnitude and spatial pattern of low-frequency climate variability. Dynamical understanding of forced and unforced variability is expected to contribute to improved interpretations of paleoclimate variability. To that end, we develop a framework for fingerprinting spatiotemporal patterns of temperature variability in forced and unforced simulations. This framework relies on two frequency-dependent metrics: 1) degrees of freedom (≡N) and 2) spatial coherence. First, we useNand spatial coherence to characterize variability across a suite of both preindustrial control (unforced) and last-millennium (forced) GCM simulations. Overall, we find that, at low frequencies and when forcings are added, regional independence in the climate system decreases, reflected in fewerNand higher coherence between local and global mean surface temperature. We then present a simple three-box moist-static-energy-balance model for temperature variability, which is able to emulate key frequency-dependent behavior in the GCMs. This suggests that temperature variability in the GCM ensemble can be understood through Earth’s energy budget and downgradient energy transport, and allows us to identify sources of polar-amplified variability. Finally, we discuss insights the three-box model can provide into model-to-model GCM differences.

   Forced and unforced temperature variability are poorly constrained and understood, particularly that at time scales longer than a decade. Here, we identify key differences in the time scale–dependent behavior of forced and unforced temperature variability using a combination of numerical climate models and principles of downgradient energy transport. This work, and the spatiotemporal characterizations of forced and unforced temperature variability that we generate, will aid in interpretations of proxy-based paleoclimate reconstructions and improve mechanistic understanding of variability.

    

   more » « less
2. Pattern Recognition Methods to Separate Forced Responses from Internal Variability in Climate Model Ensembles and Observations

   https://doi.org/10.1175/JCLI-D-19-0855.1  

   Wills, RCJ ; Battisti, DS ; Armour, KC ; Schneider, T ; Deser, C ( October 2020 , Journal of climate)

   Ensembles of climate model simulations are commonly used to separate externally forced climate change from internal climate variability. However, much of the information gained from running large ensembles is lost in traditional methods of data reduction such as linear trend analysis or large scale spatial averaging. This paper demonstrates a pattern recognition method (forced pattern filtering) that extracts patterns of externally forced climate change from large ensembles and identifies the forced climate response with up to 10 times fewer ensemble members than simple ensemble averaging. It is particularly effective at filtering out spatially coherent modes of internal variability (e.g., El Ni˜no, North Atlantic Oscillation), which would otherwise alias into estimates of regional responses to forcing. This method is used to identify forced climate responses within the 40-member Community Earth System Model (CESM) large ensemble, including an El-Ni˜no-like response to volcanic eruptions and forced trends in the North Atlantic Oscillation. The ensemble-based estimate of the forced response is used to test statistical methods for isolating the forced response from a single realization (i.e., individual ensemble members). Low-frequency pattern filtering is found to effectively identify the forced response within individual ensemble members and is applied to the HadCRUT4 reconstruction of observed temperatures, whereby it identifies slow components of observed temperature changes that are consistent with the expected effects of anthropogenic greenhouse gas and aerosol forcing. 

   more » « less
3. Reconciling Human and Natural Drivers of the Tripole Pattern of Multidecadal Summer Temperature Variations Over Eurasia

   https://doi.org/10.1029/2021GL093971  

   Hua, Wenjian ; Qin, Minhua ; Dai, Aiguo ; Zhou, Liming ; Chen, Haishan ; Zhang, Wanxin ( July 2021 , Geophysical Research Letters)

   The recent summer surface air temperature (SAT) changes over densely populated Eurasia exhibit a non‐uniform pattern with amplified warming over Europe and East Asia (EA) but weak warming over Central Asia (CA), forming a wave train‐like structure. However, the key factors that determine this non‐uniform warming pattern remain unclear. By analyzing observations and model simulations, here, we show that more than half of the SAT multidecadal variations from 1950 to 2014 over Europe‐west Asia and EA may have resulted from external forcing, rather than from internal variability in the Atlantic as previously thought. In contrast, the recent SAT over CA is influenced mainly by internal variations in the Atlantic and Pacific oceans. Large ensemble model simulations suggest that the forced SAT multidecadal variations over Eurasia are mainly caused by changes in greenhouse gases and aerosols. Our findings provide strong evidence for major impacts of external forcing on multidecadal climate variations over Eurasia.

    

   more » « less
4. Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends

   https://doi.org/10.1029/2019GB006453  

   Schlunegger, Sarah ; Rodgers, Keith B. ; Sarmiento, Jorge L. ; Ilyina, Tatiana ; Dunne, John P. ; Takano, Yohei ; Christian, James R. ; Long, Matthew C. ; Frölicher, Thomas L. ; Slater, Richard ; et al ( August 2020 , Global Biogeochemical Cycles)

   Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper‐ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.

    

   more » « less
5. Proxy‐Model Comparison for the Eocene‐Oligocene Transition in Southern High Latitudes

   https://doi.org/10.1029/2022PA004496  

   Tibbett, Emily J. ; Burls, Natalie J. ; Hutchinson, David K. ; Feakins, Sarah J. ( February 2023 , Paleoceanography and Paleoclimatology)

   The Eocene‐Oligocene transition (EOT) marks the shift from greenhouse to icehouse conditions at 34 Ma, when a permanent ice sheet developed on Antarctica. Climate modeling studies have recently assessed the drivers of the transition globally. Here we revisit those experiments for a detailed study of the southern high latitudes in comparison to the growing number of mean annual sea surface temperature (SST) and mean air temperature (MAT) proxy reconstructions, allowing us to assess proxy‐model temperature agreement and refine estimates for the magnitude of thepCO₂forcing of the EOT. We compile and update published proxy temperature records on and around Antarctica for the late Eocene (38–34 Ma) and early Oligocene (34–30 Ma). Compiled SST proxies cool by up to 3°C and MAT by up to 4°C between the timeslices. Proxy data were compared to previous climate model simulations representing pre‐ and post‐EOT, typically forced with a halving ofpCO₂. We scaled the model outputs to identify the magnitude ofpCO₂change needed to drive a commensurate change in temperature to best fit the temperature proxies. The multi‐model ensemble needs a 30 or 33% decrease inpCO₂, to best fit MAT or SST proxies respectively. These proxy‐model intercomparisons identify decliningpCO₂as the primary forcing of EOT cooling, with a magnitude (200 or 243 ppmv) approaching that of thepCO₂proxies (150 ppmv). However individual model estimates span a decrease of 66–375 ppmv, thus proxy‐model uncertainties are dominated by model divergence.

    

   more » « less