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1. Detecting climate signals in populations across life histories

   https://doi.org/10.1111/gcb.16041  

   Jenouvrier, Stéphanie; Long, Matthew C.; Coste, Christophe F. D.; Holland, Marika; Gamelon, Marlène; Yoccoz, Nigel G.; Sæther, Bernt‐Erik (January 2022, Global Change Biology)

   Abstract Climate impacts are not always easily discerned in wild populations as detecting climate change signals in populations is challenged by stochastic noise associated with natural climate variability, variability in biotic and abiotic processes, and observation error in demographic rates. Detection of the impact of climate change on populations requires making a formal distinction between signals in the population associated with long‐term climate trends from those generated by stochastic noise. The time of emergence (ToE) identifies when the signal of anthropogenic climate change can be quantitatively distinguished from natural climate variability. This concept has been applied extensively in the climate sciences, but has not been explored in the context of population dynamics. Here, we outline an approach to detecting climate‐driven signals in populations based on an assessment of when climate change drives population dynamics beyond the envelope characteristic of stochastic variations in an unperturbed state. Specifically, we present a theoretical assessment of the time of emergence of climate‐driven signals in population dynamics (). We identify the dependence ofon the magnitude of both trends and variability in climate and also explore the effect of intrinsic demographic controls on. We demonstrate that different life histories (fast species vs. slow species), demographic processes (survival, reproduction), and the relationships between climate and demographic rates yield population dynamics that filter climate trends and variability differently. We illustrate empirically how to detect the point in time when anthropogenic signals in populations emerge from stochastic noise for a species threatened by climate change: the emperor penguin. Finally, we propose six testable hypotheses and a road map for future research. 

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2. Climatic Drivers of Deglacial SST Variability in the Eastern Pacific

   https://doi.org/10.1029/2021PA004264  

   Meegan Kumar, Dervla; Tierney, Jessica E.; Bhattacharya, Tripti; Zhu, Jiang; McCarty, Logan; Murray, James W. (October 2021, Paleoceanography and Paleoclimatology)

   Abstract We explore the response of northeastern Pacific sea surface temperature (SST) to deglacial (16–7 ka) climate variability as recorded in‐based SST reconstructions spanning 65°N to 10°S. Included in the analysis is a new 23 kyr SST record from core NH8P from the northwest Mexican Margin. We isolate spatiotemporal patterns in regional SSTs with trend empirical orthogonal function (TEOF) analysis. The dominant TEOF mode reflects deglacial warming associated with rising. Tropical and subtropical SSTs correlated most strongly with this mode, suggesting that the thermodynamic response of the tropical eastern Pacific to greenhouse gas forcing was the dominant driver of regional SST change during deglaciation. The second TEOF mode reflects millennial‐scale variability and is most strongly expressed in subpolar SSTs. The synchronous timing between North Pacific and North Atlantic SST oscillations is evidence for the rapid transmission of millennial‐scale climate perturbations between the basins, likely through an atmospheric teleconnection. SSTs at NH8P have no correlation with either leading TEOF mode as there is minimal change in SST at this site after20 ka. A model simulation of the LGM indicates that glacial cooling was muted in much of the Eastern Pacific Warm Pool (EPWP), in which NH8P lies, due to reductions in latent heat flux. This suggests that the wind‐evaporation‐SST feedback was responsible for the attenuation of EPWP cooling. Overall, this study highlights the distinct latitudinal trends in the Pacific's response to deglaciation. 

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3. A probabilistic framework for quantifying the role of anthropogenic climate change in marine-terminating glacier retreats

   https://doi.org/10.5194/tc-16-2725-2022  

   Christian, John Erich; Robel, Alexander A.; Catania, Ginny (January 2022, The Cryosphere)

   Abstract. Many marine-terminating outlet glaciers have retreated rapidly in recent decades, but these changes have not been formally attributed to anthropogenic climate change. A key challenge for such an attribution assessment is that if glacier termini are sufficiently perturbed from bathymetric highs, ice-dynamic feedbacks can cause rapid retreat even without further climate forcing. In the presence of internal climate variability, attribution thus depends on understanding whether (or how frequently) these rapid retreats could be triggered by climatic noise alone. Our simulations with idealized glaciers show that in a noisy climate, rapid retreat is a stochastic phenomenon. We therefore propose a probabilistic approach to attribution and present a framework for analysis that uses ensembles of many simulations with independent realizations of random climate variability. Synthetic experiments show that century-scale climate trends substantially increase the likelihood of rapid glacier retreat. This effect depends on the timescales over which ice dynamics integrate forcing. For a population of synthetic glaciers with different topographies, we find that external trends increase the number of large retreats triggered within the population, offering a metric for regional attribution. Our analyses suggest that formal attribution studies are tractable and should be further pursued to clarify the human role in recent ice-sheet change. We emphasize that early-industrial-era constraints on glacier and climate state are likely to be crucial for such studies. 

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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)

   Abstract 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. 

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5. Climatic Asynchrony and Hydrologic Inefficiency Explain the Global Pattern of Water Availability

   https://doi.org/10.1029/2022GL101214  

   Jawitz, James W.; Klammler, Harald; Reaver, Nathan G. F. (December 2022, Geophysical Research Letters)

   Abstract The mechanisms underlying observed global patterns of partitioning precipitation () to evapotranspiration () and runoff () are controversially debated. We test the hypothesis that asynchrony between climatic water supply and demand is sufficient to explain spatio‐temporal variability of water availability. We developed a simple analytical model forthat is determined by four dimensionless characteristics of intra‐annual water supply and demand asynchrony. The analytical model, populated with gridded climate data, accurately predicted global runoff patterns within 2%–4% of independent estimates from global climate models, with spatial patterns closely correlated to observations (). The supply‐demand asynchrony hypothesis provides a physically based explanation for variability of water availability using easily measurable characteristics of climate. The model revealed widespread responsiveness of water budgets to changes in climate asynchrony in almost every global region. Furthermore, the analytical model using global averages independently reproduced the Budyko curve () providing theoretical foundation for this widely used empirical relationship. 

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