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The Arctic climate is sensitive to aerosol abundance, making accurate historical records of atmospheric aerosols essential for understanding the recent rapid Arctic warming. We present 235-year ice core records of sulfate (SO42-), nitrate (NO3-), chloride (Cl-) and other impurities from central Greenland, and compare them with emission inventories in the surrounding continents. The comparisons reveal a high correlation between the ice core records and North American emissions, consistent with that North America as the dominant pollution source region to Greenland. Since around 1970, SO42-, NO3- and Cl- exhibit divergent patterns relative to their pre-1970 increasing trends paralleling with anthropogenic emissions. In particular, SO42- declined in step with North American SO2 emissions but decreased more rapidly after ~1990, probably due to combined effects from the enhanced sulfate loss in the source regions due to intensified in-cloud sulfur oxidation and the reduced transport efficiency. Nitrate tracked NOX emissions since ~ 1900 until 1990, but remained high after 1990 when anthropogenic emissions in all source regions decreased. This post-1990 pattern may arise from the increasing natural NOX emissions in the Arctic, while feedbacks of atmospheric chemistry to a changing atmospheric acidity during this period may also contribute through affecting the phase partitioning and then long-range transport of nitrate. Chloride also paralleled with anthropogenic emissions since the 1960s but was further modulated by acid displacement processes, as indicated by the covariation of Cl- excess with reconstructed snow acidity. Our results demonstrate that Arctic aerosols reflect both emission controls and their modulation by atmospheric chemistry and transport. 

Abstract The recharge oscillator (RO) is a simple mathematical model of the El Niño Southern Oscillation (ENSO). In its original form, it is based on two ordinary differential equations that describe the evolution of equatorial Pacific sea surface temperature and oceanic heat content. These equations make use of physical principles that operate in nature: (a) the air‐sea interaction loop known as the Bjerknes feedback, (b) a delayed oceanic feedback arising from the slow oceanic response to winds within the equatorial band, (c) state‐dependent stochastic forcing from fast wind variations known as westerly wind bursts (WWBs), and (d) nonlinearities such as those related to deep atmospheric convection and oceanic advection. These elements can be combined at different levels of RO complexity. The RO reproduces ENSO key properties in observations and climate models: its amplitude, dominant timescale, seasonality, and warm/cold phases amplitude asymmetry. We discuss the RO in the context of timely research questions. First, the RO can be extended to account for ENSO pattern diversity (with events that either peak in the central or eastern Pacific). Second, the core RO hypothesis that ENSO is governed by tropical Pacific dynamics is discussed from the perspective of influences from other basins. Finally, we discuss the RO relevance for studying ENSO response to climate change, and underline that accounting for ENSO diversity, nonlinearities, and better links of RO parameters to the long term mean state are important research avenues. We end by proposing important RO‐based research problems. 

Marine phytoplankton are primary producers in ocean ecosystems and emit dimethyl sulfide (DMS) to the atmosphere. DMS emissions are the largest biological source of atmospheric sulfur and are one of the largest uncertainties in global climate modeling. DMS is oxidized to methanesulfonic acid (MSA), sulfur dioxide (SO2), and hydroperoxymethyl thioformate (HPMTF), all of which can be oxidized to sulfate. Ice core records of MSA are used to investigate past DMS emissions but rely on the implicit assumption that the relative yield of oxidation products from DMS remains constant. However, this assumption is uncertain because there are no long-term records that compare MSA to other DMS oxidation products. Here we share the first long-term record of both MSA and DMS-derived biogenic sulfate concentration in Greenland ice core samples from 1200 to 2006 CE. While MSA declines on average by 0.2 µg S kg-1 over the industrial era, biogenic sulfate from DMS increases by 0.8 µg S kg-1. This increasing biogenic sulfate contradicts previous assertions of declining North Atlantic primary productivity inferred from decreasing MSA concentrations in Greenland ice cores over the industrial era. The changing ratio of MSA to biogenic sulfate suggests that trends in MSA could be caused by time-varying atmospheric chemistry, and that MSA concentrations alone should not be used to infer past primary productivity. 

Anthropogenic sulfate aerosols are estimated to have offset sixty percent of greenhouse-gas-induced warming in the Arctic, a region warming four times faster than the rest of the world. However, sulfate radiative forcing estimates remain uncertain because the relative contributions from anthropogenic versus natural sources to total sulfate aerosols are unknown. Here we measure sulfur isotopes of sulfate in a Summit, Greenland ice core from 1850 to 2006 CE to quantify the contribution of anthropogenic sulfur emissions to ice core sulfate. We use a Keeling Plot to determine the anthropogenic sulfur isotopic signature (δ34Santhro = +2.9 ± 0.3 ‰), and compare this result to a compilation of sulfur isotope measurements of oil and coal. Using δ34Santhro, we quantify anthropogenic sulfate concentration separated from natural sulfate. Anthropogenic sulfate concentration increases to 68 ± 7% of non-sea-salt sulfate (65.1 ± 20.2 µg kg-1) during peak anthropogenic emissions from 1960 to 1990 and decreases to 45 ± 11% of non-sea-salt sulfate (25.4 ± 12.8 µg kg-1) from 1996 to 2006. These observations provide the first long-term record of anthropogenic sulfate distinguished from natural sources (e.g., volcanoes, dimethyl sulfide), and can be used to evaluate model characterization of anthropogenic sulfate aerosol fraction and radiative forcing over the industrial era. 

The Arctic is warming at almost four times the global rate. Cooling caused by anthropogenic aerosols has been estimated to offset sixty percent of greenhouse-gas-induced Arctic warming, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state-of-the-art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m-2), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic-induced Arctic climate change. 

Abstract The Arctic is warming at almost four times the global rate. An estimated sixty percent of greenhouse‐gas‐induced Arctic warming has been offset by anthropogenic aerosols, but the contribution of aerosols to radiative forcing (RF) represents the largest uncertainty in estimating total RF, largely due to unknown preindustrial aerosol abundance. Here, sulfur isotope measurements in a Greenland ice core show that passive volcanic degassing contributes up to 66 ± 10% of preindustrial ice core sulfate in years without major eruptions. A state‐of‐the‐art model indicates passive volcanic sulfur emissions influencing the Arctic are underestimated by up to a factor of three, possibly because many volcanic inventories do not include hydrogen sulfide emissions. Higher preindustrial volcanic sulfur emissions reduce modeled anthropogenic Arctic aerosol cooling by up to a factor of two (+0.11 to +0.29 W m⁻²), suggesting that underestimating passive volcanic sulfur emissions has significant implications for anthropogenic‐induced Arctic climate change. 

Uncertainties from deepening penetration of renewable energy resources have posed critical challenges to the secure and reliable operations of future electric grids. Among various approaches for decision making in uncertain environments, this paper focuses on chance-constrained optimization, which provides explicit probabilistic guarantees on the feasibility of optimal solutions. Although quite a few methods have been proposed to solve chance-constrained optimization problems, there is a lack of comprehensive review and comparative analysis of the proposed methods. We first review three categories of existing methods to chance-constrained optimization: (1) scenario approach; (2) sample average approximation; and (3) robust optimization based methods. Data-driven methods, which are not constrained by any particular distributions of the underlying uncertainties, are of particular interest. Key results of the analytical reformulation approach for specific distributions are briefly discussed. We then provide a comprehensive review on the applications of chance-constrained optimization in power systems. Finally, this paper provides a critical comparison of existing methods based on numerical simulations, which are conducted on standard power system test cases. 

Abstract The superτ-charm facility (STCF) is an electron–positron collider proposed by the Chinese particle physics community. It is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of 0.5 × 10³⁵cm⁻²·s⁻¹or higher. The STCF will produce a data sample about a factor of 100 larger than that of the presentτ-charm factory — the BEPCII, providing a unique platform for exploring the asymmetry of matter-antimatter (charge-parity violation), in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions, as well as searching for exotic hadrons and physics beyond the Standard Model. The STCF project in China is under development with an extensive R&D program. This document presents the physics opportunities at the STCF, describes conceptual designs of the STCF detector system, and discusses future plans for detector R&D and physics case studies.