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Abstract Contemporary food and agricultural systems degrade soils, pollute natural resources, and contribute to greenhouse gas emissions. The waste output from these systems, however, can be repurposed as an agricultural input, reducing emissions associated with organics disposal while actively sequestering atmospheric carbon in soils—thus transitioning the sector from a carbon source to a carbon sink. This research estimates the near-term technical and economic potential of utilizing composted organic feedstocks as a soil amendment to mitigate climate change and improve long-term soil quality, in line with California’s organics diversion policies, by connecting food scraps and organics residuals in California’s municipal solid waste to existing infrastructure and working lands in the state. The multi-objective spatial optimization results indicate considerable carbon sequestration benefits in the range of −1.9 ± 0.5 MMT CO₂eq annually, by applying compost to 6 million hectares of California rangelands at a price of approximately $200 per ton, presenting a cost-effective climate change mitigation strategy within proposed federal sequestration credits. Expanding composting capacity is predicted to increase the total amount of carbon sequestered while reducing the cost per ton and per hectare treated. This model aids decision makers in considering the technical, economic, and institutional potential of actively managing the State’s organic materials in municipal waste streams for climate change mitigation. 

Abstract Global climate models (GCMs) are unable to produce detailed runoff conditions at the basin scale. Assumptions are commonly made that dynamical downscaling can resolve this issue. However, given the large magnitude of the biases in downscaled GCMs, it is unclear whether such projections are credible. Here, we use an ensemble of dynamically downscaled GCMs to evaluate this question in the Sierra‐Cascade mountain range of the western US. Future projections across this region are characterized by earlier seasonal shifts in peak flow, but with substantial inter‐model uncertainty (−25 ± 34.75 days, 95% confidence interval (CI)). We apply the emergent constraint (EC) method for the first time to dynamically downscaled projections, leading to a 39% (−28.25 ± 20.75 days, 95% CI) uncertainty reduction in future peak flow timing. While the constrained results can differ from bias corrected projections, the EC is based on GCM biases in historical peak flow timing and has a strong physical underpinning. 

Abstract Downslope wind‐driven fires have resulted in many of the wildfire disasters in the western United States and represent a unique hazard to infrastructure and human life. We analyze the co‐occurrence of wildfires and downslope winds across the western United States (US) during 1992–2020. Downslope wind‐driven fires accounted for 13.4% of the wildfires and 11.9% of the burned area in the western US yet accounted for the majority of local burned area in portions of southern California, central Washington, and the front range of the Rockies. These fires were predominantly ignited by humans, occurred closer to population centers, and resulted in outsized impacts on human lives and infrastructure. Since 1999, downslope wind‐driven fires have accounted for 60.1% of structures and 52.4% of human lives lost in wildfires in the western US. Downslope wind‐driven fires occurred under anomalously dry fuels and exhibited a seasonality distinct from other fires—occurring primarily in the spring and fall. Over 1992–2020, we document a 25% increase in the annual number of downslope wind‐driven fires and a 140% increase in their respective annual burned area, which partially reflects trends toward drier fuels. These results advance our understanding of the importance of downslope winds in driving disastrous wildfires that threaten populated regions adjacent to mountain ranges in the western US. The unique characteristics of downslope wind‐driven fires require increased fire prevention and adaptation strategies to minimize losses and incorporation of changing human‐ignitions, fuel availability and dryness, and downslope wind occurrence to elucidate future fire risk. 

Abstract Despite the f₀(980) hadron having been discovered half a century ago, the question about its quark content has not been settled: it might be an ordinary quark-antiquark ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$) meson, a tetraquark ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$) exotic state, a kaon-antikaon ($${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$) molecule, or a quark-antiquark-gluon ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$) hybrid. This paper reports strong evidence that the f₀(980) state is an ordinary$${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$meson, inferred from the scaling of elliptic anisotropies (v₂) with the number of constituent quarks (n_q), as empirically established using conventional hadrons in relativistic heavy ion collisions. The f₀(980) state is reconstructed via its dominant decay channel f₀(980) →π⁺π⁻, in proton-lead collisions recorded by the CMS experiment at the LHC, and itsv₂is measured as a function of transverse momentum (p_T). It is found that then_q= 2 ($${{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}$state) hypothesis is favored overn_q= 4 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{q}}}\overline{{{\rm{q}}}}$$ $q\overline{q}q\overline{q}$or$${{\rm{K}}}\overline{{{\rm{K}}}}$$ $K\overline{K}$states) by 7.7, 6.3, or 3.1 standard deviations in thep_T< 10, 8, or 6 GeV/cranges, respectively, and overn_q= 3 ($${{\rm{q}}}\overline{{{\rm{q}}}}{{\rm{g}}}$$ $q\overline{q}g$hybrid state) by 3.5 standard deviations in thep_T< 8 GeV/crange. This result represents the first determination of the quark content of the f₀(980) state, made possible by using a novel approach, and paves the way for similar studies of other exotic hadron candidates. 

Abstract Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confidence intervals on model parameters, but it only applies under certain conditions. These conditions, such as nested hypotheses and unbounded parameters, are often violated in neutrino oscillation measurements and other experimental scenarios. Monte Carlo methods can address these issues, albeit at increased computational cost. In the presence of nuisance parameters, however, the best way to implement a Monte Carlo method is ambiguous. This paper documents the method selected by the NOvA experiment, the profile construction. It presents the toy studies that informed the choice of method, details of its implementation, and tests performed to validate it. It also includes some practical considerations which may be of use to others choosing to use the profile construction. 

ABSTRACT Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions. 

Abstract A search is presented for the pair production of new heavy resonances, each decaying into a top quark (t) or antiquark and a gluon (g). The analysis uses data recorded with the CMS detector from proton–proton collisions at a center-of-mass energy of 13$$\,\text {Te}\hspace{-.08em}\text {V}$$ $\text{Te}\text{V}$at the LHC, corresponding to an integrated luminosity of 138$$\,\text {fb}^{-1}$$ ${\text{fb}}^{-1}$. Events with one muon or electron, multiple jets, and missing transverse momentum are selected. After using a deep neural network to enrich the data sample with signal-like events, distributions in the scalar sum of the transverse momenta of all reconstructed objects are analyzed in the search for a signal. No significant deviations from the standard model prediction are found. Upper limits at 95% confidence level are set on the product of cross section and branching fraction squared for the pair production of excited top quarks in the$$\text {t}^{*} \rightarrow {\text {t}} {\text {g}} $$ $\text{t}_{}^{\ast }\to \text{tg}$decay channel. The upper limits range from 120 to 0.8$$\,\text {fb}$$ $\text{fb}$for a$$\text {t}^{*} $$ $\text{t}_{}^{\ast }$with spin-1/2 and from 15 to 1.0$$\,\text {fb}$$ $\text{fb}$for a$$\text {t}^{*} $$ $\text{t}_{}^{\ast }$with spin-3/2. These correspond to mass exclusion limits up to 1050 and 1700$$\,\text {Ge}\hspace{-.08em}\text {V}$$ $\text{Ge}\text{V}$for spin-1/2 and spin-3/2$$\text {t}^{*} $$ $\text{t}_{}^{\ast }$particles, respectively. These are the most stringent limits to date on the existence of$$\text {t}^{*} \rightarrow {\text {t}} {\text {g}} $$ $\text{t}_{}^{\ast }\to \text{tg}$resonances.