Teff (Eragrostis tef) is an underutilized cereal grown primarily by small-scale farmers in Ethiopia, where it thrives under arid conditions unsuitable for other grain crops. Incomplete selection of classic domestication traits such as lodging, panicle architecture, and seed density contribute to the low yields observed in teff compared to leading cereals. To investigate the phenotypic basis of lodging tolerance in teff, we surveyed domestication related traits across a diversity panel of 265 teff wild relatives, landraces, and cultivars in Michigan. Panicle architecture and lodging score were collected in the field. To strengthen ground truth data and identify spectral signatures of plant height and subsequent lodging, LIDAR and hyperspectral images were collected with an unmanned aerial vehicle. A tiller imaging box was designed to maintain plant architecture from the field in a controlled lab environment. Morphological features including panicle height, panicle width, spikelet density, panicle angle, and tiller angle will be calculated using PlantCV and ImageJ. Feature evaluation via Pearson’s correlation and analysis of variance will be conducted for structural and morphological traits. This data will be used in a genome wide association study to identify phenotypes underlying lodging tolerance, and superior breeding material will be isolated for future studies.

This article provides a commentary about the state of integrated, coordinated, open, and networked (ICON) principles in Earth and Planetary Science Processes (EPSP) and discussion on the opportunities and challenges of adopting them. This commentary focuses on the challenges with current inclusive, equitable, and accessible science and highlights how research undertaken in the earth and planetary surface processes community currently benefit from and would be able to grow as a discipline with more directed implementation of ICON principles.

Evaluation of the climatic water balance (CWB) – i.e. precipitation minus potential evapotranspiration – has strong potential as a tool for investigating patterns of variability and change in the water cycle since it estimates the (im)balance of atmospheric moisture near the land surface. Using observations from a middle-Himalaya weather station at Mukteshwar (29.474°N, 79.646°E, Uttarakhand state) in India, we demonstrate a CWB-based set of analytical procedures can robustly characterise local climate variability. Use of the CWB circumvents uncertainties in the soil water balance stemming from limited data on subsurface properties. We also focus on three key input variables used to calculate the CWB: precipitation, mean temperature and diurnal temperature range. We use local observations to evaluate the skill of gridded datasets –specifically meteorological reanalyses – in representing local conditions. Reanalysis estimates of Mukteshwar climate showed large absolute biases but accurately captured the timing and relative amplitude of the annual cycle of these three variables and the CWB. This suggests that the reanalyses can provide insight regarding climate processes in data-sparse regions, but caution is necessary if extracting absolute values. While the local observations at Mukteshwar show clear annual cycles and substantial interannual variability, results from investigation of their time-dependency were quite mixed. Pragmatically this implies that while “change is coming, variability is now.” If communities can adapt to the observed historical hydroclimate variability they will have built meaningful adaptive capacity to cope with on-going environmental change. This follows a ‘low regret’ approach advocated when facing a substantially uncertain future.

A novel method to simulate the wind and turbulence around obstacles, such as buildings, has been developed for use in a computer model that was previously used only to study turbulence and clouds over flat Earth surface. The method, called the Quasi-Solid Box Method, forces the simulated flow to stop in the model grid-cells that are inside an obstacle. The accuracy of the method is tested using cases of a flow past an idealized single rectangular building, a cubic building rotated by 45o, and a building in the form of a cylinder. The simulations are compared with wind tunnel observations around a small model building and to results from other models. The modeled gas tracer dispersion around the building also agrees quite well observations. We also report results for successful simulation of a flow around a cubic building rotated by 45o relative to the flow, and around a building in the form of a cylinder of aspect ratio of one. The main appeal of the new method is its simplicity that requires very minor modifications to the model code. The improved model can be used for detailed studies of the impact of climate change on urban environments.

Volcanic eruptions are potentially hazardous natural events. Understanding how magma accumulates, migrates, and erupts is important to understanding and, eventually, predicting volcanic eruptions. However, the variation in the scale of volcanoes, co-occurrence of earthquakes, and the duration of the eruption makes understanding these events difficult. Ambient noise interferometry is becoming an increasingly more popular tool to study and monitor active volcanoes. We use this method to characterize the variations of subsurface seismic velocities associated with different stages of the eruption process at the Great Sitkin Volcano in the central Aleutian volcanic arc. This volcano initially erupted in May 2021 with elevated seismicity and gas release, followed by the formation of a new lava dome starting July 2021. The volcano had an increase in seismicity in February 2020 but without any eruption activity reported. Measuring the variation of seismic velocities from August 2019 to March 2022, we observe a local decrease in velocity leading up to the eruption and an increase in velocity following the emplacement of the lava dome. We do not observe any velocity variations preceding the non-eruptive increase of seismic activity in February 2020. Despite its remote location and relatively small scale, the findings of this study at the Great Sitkin volcano have significant implications for understanding volcanism and the development and prediction of volcanic eruptions in general.

The severity and frequency of wildfires have risen dramatically in recent years, drawing attention to the term ‘wildland-urban interface’ (WUI), the region where man-made constructions meet flammable vegetation. Herein, we mapped a finer-scale, novel linear WUI for California (CA) based on the intersection of boundaries of wildland vegetation and building footprint. The direct intersection is referred to as a direct WUI, whereas the intersection at 100-m is known as an indirect WUI. More fires were ignited closer to direct WUI than indirect WUI due to their proximity to communities. However, the overlap of past fire perimeters with indirect WUI is greater than that with direct WUI which shows that more areas were burned in the indirect WUI due to embers transported by strong wind gusts during large wildfires. The study’s findings will help land managers and policymakers in controlling fire dangers, land-use planning, and reducing threats to fire-prone communities.

Of immediate widespread concern is the accelerating transition from Holocene-like weather patterns to unknown, and likely unstable, Anthropocene patterns. A fell example is irreversible Arctic phase change. It is not clear if existing AOGCMs are adequate to model anticipated global impacts in detail; however, the GISS ModelE AOGCM can be used to locally compare and extend the PIOMAS Arctic ocean historical ice-volume dataset into the near future. Arctic Amplification (AA) mechanisms are poorly understood; to enable timely results, a simple linear, Arctic TOA grid-boundary energy-input is used to enforce AA, avoiding the perils of arbitrary modification of relatively well-studied parameterizations (e.g., restriction of cloud-top height to induce local warming). Only PIOMAS springtime/max and fall/min Arctic ice-volume decadal, linear trends were enforced. This temporally-broad grid-boundary modification produces a surprisingly detailed consonance with monthly trends in the historical PIOMAS dataset from 2003 to 2021, and is integrated to 2050. The result is a zero-ice-volume, summer/fall half-year, beginning ca. 2035 (onset 1-sigma of ± ~5 years), with mean annual Arctic temperatures increasingly trending above freezing. Persistent, Arctic phase change follows this half-year transition about 20 years later. Also present in later stages, the 500 hPa height minimum is no longer nearly-coincident with the pole, suggesting jet stream disruption and its consequences. Hypothesized large clathrate-methane releases likely associated with Arctic temperature and phase change are also examined. This work establishes a reasonably detailed timeline for the Arctic phase change based on well-studied AOGCM physics, slightly tuned to decades of PIOMAS data. This result also points to the Arctic as a key, near-term site for localized, nondestructive intervention to mitigate Arctic phase change (e.g., Stjern [2018]), thereby slowing the Holocene -> Anthropocene growing-season disruption. Although such an intervention cannot itself accomplish the requirements of the IPCC SP-15 [2018], nor Planetary Boundaries theory, delaying the Arctic phase change will likely extend the time-window for accomplishing those critical tasks and ultimately to at least slow the rate of increase of climate emergencies.

Although adequately detailed kerosene chemical-combustion Arrhenius reaction-rate suites were not readily available for combustion modeling until ca. the 1990’s (e.g., Marinov [1998]), it was already known from mass-spectrometer measurements during the early Apollo era that fuel-rich liquid oxygen + kerosene (RP-1) gas generators yield large quantities (e.g., several percent of total fuel flows) of complex hydrocarbons such as benzene, butadiene, toluene, anthracene, fluoranthene, etc. (Thompson [1966]), which are formed concomitantly with soot (Pugmire [2001]). By the 1960’s, virtually every fuel-oxidizer combination for liquid-fueled rocket engines had been tested, and the impact of gas phase combustion-efficiency governing the rocket-nozzle efficiency factor had been empirically well-determined (Clark [1972]). Up until relatively recently, spacelaunch and orbital-transfer engines were increasingly designed for high efficiency, to maximize orbital parameters while minimizing fuels and structural masses: Preburners and high-energy atomization have been used to pre-gasify fuels to increase (gas-phase) combustion efficiency, decreasing the yield of complex/aromatic hydrocarbons (which limit rocket-nozzle efficiency and overall engine efficiency) in hydrocarbon-fueled engine exhausts, thereby maximizing system launch and orbital-maneuver capability (Clark; Sutton; Sutton/Yang). The combustion community has been aware that the choice of Arrhenius reaction-rate suite is critical to computer engine-model outputs. Specific combustion suites are required to estimate the yield of high-molecular-weight/reactive/toxic hydrocarbons in the rocket engine combustion chamber, nonetheless such GIGO errors can be seen in recent documents. Low-efficiency launch vehicles also need larger fuels loads to achieve the same launched mass, further increasing the yield of complex hydrocarbons and radicals deposited by low-efficiency rocket engines along launch trajectories and into the stratospheric ozone layer, the mesosphere, and above. With increasing launch rates from low-efficiency systems, these persistent (Ross/Sheaffer [2014]; Sheaffer [2016]), reactive chemical species must have a growing impact on critical, poorly-understood upper-atmosphere chemistry systems.

In 2018–2019, Central Europe experienced an unprecedented multi-year drought with severe impacts on society and ecosystems. In this study, we analyzed the impact of this drought on water quality by comparing long-term (1997-2017) nitrate export with 2018–2019 export in a heterogeneous mesoscale catchment. We combined data-driven analysis with process-based modelling to analyze nitrogen retention and the underlying mechanisms in the soils and during subsurface transport. We found a drought-induced shift in concentration-discharge relationships, reflecting exceptionally low riverine nitrate concentrations during dry periods and exceptionally high concentrations during subsequent wet periods. Nitrate loads were up to 70% higher compared to the long-term load-discharge relationship. Model simulations confirmed that this increase was driven by decreased denitrification and plant uptake and subsequent flushing of accumulated nitrogen during rewetting. Fast transit times (<2 months) during wet periods in the upstream sub-catchments enabled a fast water quality response to drought. In contrast, longer transit times downstream (>20 years) inhibited a fast response but potentially contribute to a long-term drought legacy. Overall, our study reveals that severe multi-year droughts, which are predicted to become more frequent across Europe, can reduce the nitrogen retention capacity of catchments, thereby intensifying nitrate pollution and threatening water quality.

Extensive loss of salt marshes in back-barrier tidal embayments is undergoing worldwide as a consequence of land-use changes, wave-driven lateral marsh erosion, and relative sea-level rise compounded by mineral sediment starvation. However, how salt-marsh loss affects the hydrodynamics of back-barrier systems and feeds back into their morphodynamic evolution is still poorly understood. Here we use a depth-averaged numerical hydrodynamic model to investigate the feedback between salt-marsh erosion and hydrodynamic changes in the Venice Lagoon, a large microtidal back-barrier system in northeastern Italy. Numerical simulations are carried out for past morphological configurations of the lagoon dating back up to 1887, as well as for hypothetical scenarios involving additional marsh erosion relative to the present-day conditions. We demonstrate that the progressive loss of salt marshes significantly impacted the Lagoon hydrodynamics, both directly and indirectly, by amplifying high-tide water levels, promoting the formation of higher and more powerful wind waves, and critically affecting tidal asymmetries across the lagoon. We also argue that further losses of salt marshes, partially prevented by restoration projects and manmade protection of salt-marsh margins against wave erosion, which have been put in place over the past few decades, limited the detrimental effects of marsh loss on the lagoon hydrodynamics, while not substantially changing the risk of flooding in urban lagoon settlements. Compared to previous studies, our analyses suggest that the hydrodynamic response of back-barrier systems to salt-marsh erosion is extremely site-specific, depending closely on the morphological characteristics of the embayment as well as on the external climatic forcings.

Observations reveal end of summer Arctic sea ice extent is declining at an accelerating rate. Model projections underestimate this decline and continue to have a broad spread in forecasted September sea ice extent. This suggests some important summer processes, such as melt pond formation and evolution, may not be properly represented in current models. Melt ponds form on the sea ice surface as snow melts, and pools in low lying areas on the sea ice surface. The evolution of the ponds depends on snow depth, ice thickness, and surface conditions. Melt water may spread across a level surface, or be confined to depressions between sea ice ridges. Ponds decrease the albedo of the surface and enhance the positive ice albedo feedback, accelerating further melt. Until recently, Arctic-wide observations of individual melt ponds were not available. ICESat-2, a photon counting laser altimeter launched in 2018, provides high resolution detail of sea ice and snow topography due to its unique combination of a small footprint (~12 m) and high-resolution along-track sampling (0.7 m). The green laser (532 nm) is able to penetrate water, enabling melt pond depth measurements. We have developed methods to track the melt pond surface and bathymetry in ICESat-2 data to determine melt pond depth. We also track melt pond evolution through application of a sea ice classification algorithm to 10 m resolution Sentinel-2 imagery. The combination of these two datasets allows for an evolving, three-dimensional view of the melting sea ice surface. We focus on the evolution of summer melt on multiyear ice in the Central Arctic north of Greenland and Canada in 2020. Our findings are put in context of existing literature on melt pond depth, volume, and evolution. We also discuss our results in relation to the melt pond fraction north of the Fram Strait, where we expect different ice conditions in the vicinity of the 2020 MOSAiC field studies. Observational data products comprising melt pond fraction and pond depth are being developed for public distribution. These products may be of interest to those studying under-ice light and biology, as well as modelers who are interested in understanding the evolution of melt pond parameters for model initialization and validation.

Along the lateral margins of floating ice shelves in Greenland and Antarctica, ice flow past confining margins and pinning points is often accompanied by extensive rifting. Rifts in zones of marginal decoupling (“detachment zones’) typically propagate inward from the margins and result in many of Earth’s largest calving events. Velocity maps of detachment zones indicate that flow through these regions is spatially transitioning from confined to unconfined shelf flow. We employ the software package \textit{icepack} to demonstrate that longitudinally decreasing marginal resistance reproduces observed transitions in flow regime, and we show that these spatial transitions are accompanied by near-margin tension sufficient to explain full-thickness rifts. Thus, we suggest that zones of progressive decoupling are a primary control on ice shelf calving. The steadiness of detachment zone positions may be a good indicator of ice shelf vulnerability, with migratory or thinning detachment zones indicating shelves at risk of dynamic speedup and increased fracture.

Extreme precipitation events are intensifying due to a warming climate, which, in some cases, is leading to increases in flooding. Detection of flood extent is essential for flood disaster management and prevention. However, it is challenging to delineate inundated areas through most publicly available optical and short-wavelength radar data, as neither can “see” through dense forest canopies. The 2018 Hurricane Florence produced heavy rainfall and subsequent record-setting riverine flooding in North Carolina, USA. NASA/JPL collected daily high-resolution full-polarized L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data between September 18th and 23rd. Here, we use UAVSAR data to construct a flood inundation detection framework through a combination of polarimetric decomposition methods and a Random Forest classifier. Validation of the established models with compiled ground references shows that the incorporation of linear polarizations with polarimetric decomposition and terrain variables significantly enhances the accuracy of inundation classification, and the Kappa statistic increases to 91.4% from 64.3% with linear polarizations alone. We show that floods receded faster near the upper reaches of the Neuse, Cape Fear, and Lumbee Rivers. Meanwhile, along the flat terrain close to the lower reaches of the Cape Fear River, the flood wave traveled downstream during the observation period, resulting in the flood extent expanding 16.1% during the observation period. In addition to revealing flood inundation changes spatially, flood maps such as those produced here have great potential for assessing flood damages, supporting disaster relief, and assisting hydrodynamic modeling to achieve flood-resilience goals.

Oxygen availability is decreasing in many lakes and reservoirs worldwide, raising the urgency for understanding how anoxia (low oxygen) affects coupled biogeochemical cycling, which has major implications for water quality, food webs, and ecosystem functioning. Although the increasing magnitude and prevalence of anoxia has been documented in freshwaters globally, the challenges of disentangling oxygen and temperature responses have hindered assessment of the effects of anoxia on carbon, nitrogen, and phosphorus concentrations, stoichiometry (chemical ratios), and retention in freshwaters. The consequences of anoxia are likely severe and may be irreversible, necessitating ecosystem-scale experimental investigation of decreasing freshwater oxygen availability. To address this gap, we devised and conducted REDOX (the Reservoir Ecosystem Dynamic Oxygenation eXperiment), an unprecedented, seven-year experiment in which we manipulated and modeled bottom-water (hypolimnetic) oxygen availability at the whole-ecosystem scale in a eutrophic reservoir. Seven years of data reveal that anoxia significantly increased hypolimnetic carbon, nitrogen, and phosphorus concentrations and altered elemental stoichiometry by factors of 2-5 relative to oxic periods. Importantly, prolonged summer anoxia increased nitrogen export from the reservoir by six-fold and changed the reservoir from a net sink to a net source of phosphorus and organic carbon downstream. While low oxygen in freshwaters is thought of as a response to land use and climate change, results from REDOX demonstrate that low oxygen can also be a driver of major changes to freshwater biogeochemical cycling, which may serve as an intensifying feedback that increases anoxia in downstream waterbodies. Consequently, as climate and land use change continue to increase the prevalence of anoxia in lakes and reservoirs globally, it is likely that anoxia will have major effects on freshwater carbon, nitrogen, and phosphorus budgets as well as water quality and ecosystem functioning.

A short watercolor comic about the broken connection between humans and mountains. Funded by Sharing Science grants of the AGU, 2021

Now published: https://doi.org/10.1088/1748-9326/ac3b19 Anthropogenic aerosols over South and East Asia currently have a stronger impact on the Asian Summer Monsoon (ASM) than greenhouse gas emissions, yet projected aerosol emission changes in these regions are subject to considerable uncertainty in timescale, location, emission type, and even the sign of the change, implying large uncertainties in future ASM change. In addition, aerosol changes in either South or East Asia cause circulation anomalies that affect both countries and neighbouring regions. We use a circulation/climate model to demonstrate that the sum of ASM responses to individual aerosol emission reductions in each region is very different to the response to simultaneous reductions in both regions, implying the ASM response to aerosol emissions reductions is highly nonlinear. The phenomenon is independent of whether aerosols are scattering or absorbing, and is driven by large-scale teleconnections between the two regions. The nonlinearity represents a new source of uncertainty in projections of ASM changes over the next 30-40 years, and limits the utility of country-dependent aerosol trajectories when considering their Asia-wide effects. To understand likely changes in the ASM due to aerosol reductions, countries will need to accurately take account of emissions reductions from across the wider region, rather than approximating them using simple scenarios and emulators. The nonlinearity in the response to forcing therefore presents a regional public goods issue for countries affected by the ASM, as the costs and benefits of aerosol emissions reductions are not internalised; in fact, forcings from different countries work jointly to determine outcomes across the region.

California is one of the only states actively managing trash in its rivers. Several community groups in the Pinole, CA and a scientist collaborated on a Thriving Earth Exchange community science project. Its purpose was to assess the trash in Pinole Creek and identify policy opportunities for the Pinole City Council. The key scientific questions were: how much trash was in the creek, what types of trash were most abundant, and where were areas of highest concern? The team enlisted additional community volunteers at in-person local events and local nonprofit listservs. We used a randomized sampling design and a community science adapted version of The Trash Monitoring Playbook, to survey the trash in the creek. We estimated there were 37 m 3 and 47,820 pieces of total trash in the creek channel with an average concentration of 2 m 3 per km 2697 pieces per kilometer. This gave the community an understanding of the scale of the problem and the resources needed to address it. Plastic and single-use trash were most abundant, and the community members expressed high concern about plastic single-use food packaging and tobacco-related waste. The community used the data to identify locations in the creek where trash was abundant and prioritize follow-up study locations. Seven new policies were recommended to the Pinole City Council. The City Council unanimously voted for the proposed policies to be reviewed by the Municipal Code Ad-Hoc Committee. And that is when community science turned to policy.

Extreme weather conditions are associated with a variety of water quality issues that can pose harm to humans and aquatic ecosystems. Under dry extremes, contaminants become more concentrated in streams with a greater potential for harmful algal blooms, while wet extremes can cause flooding and broadcast pollution. Developing appropriate interventions to improve water quality in a changing climate requires a better understanding of how extremes affect watershed processes, and which places are most vulnerable. We developed a Soil and Water Assessment Tool model of the Cape Fear River Basin (CFRB) in North Carolina, USA, representing contemporary land use, point and non-point sources, and weather conditions from 1979 to 2019. The CFRB is a large and complex river basin undergoing urbanization and agricultural intensification, with a history of extreme droughts and floods, making it an excellent case study. To identify intervention priorities, we developed a Water Quality Risk Index (WQRI) using the load average and load variability across normal conditions, dry extremes, and wet extremes. We found that the landscape generated the majority of contaminants, including 90.1% of sediment, 85.4% of total nitrogen, and 52.6% of total phosphorus at the City of Wilmington’s drinking water intake. Approximately 16% of the watershed contributed most of the pollutants across conditions—these represent high priority locations for interventions. The WQRI approach considering risks to water quality across different weather conditions can help identify locations where interventions are more likely to improve water quality under climate change.

Unsteady transit time distribution (TTD) theory is a promising new approach for merging hydrologic and water quality models at the catchment scale. A major obstacle to widespread adoption of the theory, however, has been the specification of the StorAge Selection (SAS) function, which describes how the selection of water for outflow is biased by age. In this paper we hypothesize that some unsteady hydrologic systems of practical interest can be described, to first-order, by a “shifted-uniform” SAS that falls along a continuum between plug flow sampling (for which only the oldest water in storage is sampled for outflow) and uniform sampling (for which water in storage is sampled randomly for outflow). For this choice of SAS function, explicit formulae are derived for the evolving: (1) age distribution of water in storage; (2) age distribution of water in outflow; and (3) breakthrough concentration of a conservative solute under either continuous or impulsive addition. Model predictions conform closely to chloride and deuterium breakthrough curves measured previously in a sloping lysimeter subject to periodic wetting, although refinements of the model are needed to account for the reconfiguration of flow paths at high storage levels (the so-called inverse storage effect). The analytical results derived in this paper should lower the barrier to applying TTD theory in practice, ease the computational demands associated with simulating solute transport through complex hydrologic systems, open up new opportunities for real-time control, and provide physical insights that might not be apparent from traditional numerical solutions of the governing equations.

Water scarcity is a growing problem around the world, and regions such as California are working to develop diversified, interconnected, and flexible water supply portfolios. To meet their resilient water portfolio goals, water utilities and irrigation districts will need to cooperate across scales to finance, build, and operate shared water supply infrastructure. However, planning studies to date have generally focused on partnership-level outcomes (i.e., highly aggregated mean cost-benefit analyses), while ignoring the heterogeneity of benefits, costs, and risks across the individual investing partners. This study contributes an exploratory modeling analysis that tests thousands of alternative water supply investment partnerships in the Central Valley of California, using a high-resolution simulation model to evaluate the effects of new infrastructure on individual water providers. The viability of conveyance and groundwater banking investments are as strongly shaped by partnership design choices (i.e., which water providers are participating, and how do they distribute the project’s debt obligation?) as by extreme hydrologic conditions (i.e., floods and droughts). Importantly, most of the analyzed partnership structures yield highly unequal distributions of water supply and financial risks across the partners, limiting the viability of cooperative partnerships. Partnership viability is especially rare in the absence of groundwater banking facilities, or under dry hydrologic conditions, even under explicitly optimistic assumptions regarding climate change. These results emphasize the importance of high-resolution simulation models and careful partnership structure design when developing resilient water supply portfolios for institutionally complex regions confronting scarcity.

Atmospheric aerosol plays a critical role in global climate and public health. Recent laboratory experiments showed that new particle formation is significantly enhanced by rapid condensation of nitric acid and ammonia at low temperatures. Amines are derivatives of ammonia with a significant presence in the atmosphere. For example, the wide implementation of amine-based Post-Combustion Carbon Capture (PCCC) units may significantly increase the ambient alkanolamine and polyamine levels. Using thermodynamic simulations, the condensation of alkylamines, alkanolamines and polyamines with nitric acid at various temperatures was systematically evaluated. Alkylamines will condense with nitric acid at temperatures comparable to that of ammonia. However, with additional hydrogen bonding groups, alkanolamines and polyamines may condense with nitric acid at room temperature, suggesting a new potential pathway to remove these amines from the atmosphere. Our results suggest the potentially critical role of amines in the atmospheric new particle formation via condensation with nitric acid to rapidly grow freshly nucleated clusters over their critical size at a higher temperature than ammonia. The condensed amines and nitric acid can also facilitate water uptake by aerosol particles at low relative humidity, which may alter their subsequent atmospheric transformations.

Well-dated lacustrine records are essential to establish the timing and drivers of regional hydroclimate change. Searles Basin, California records the depositional history of a fluctuating saline-alkaline lake in the terminal basin of the Owens River system draining the eastern Sierra Nevada. Here we establish a U-Th chronology for the ~76-m-long SLAPP-SLRS17 core collected in 2017 based on dating of evaporite minerals. 98 dated samples comprising 9 different minerals were evaluated based on stratigraphic, mineralogic, textural, chemical and reproducibility criteria. After application of these criteria, a total of 37 dated samples remained as constraints for the age model. A lack of dateable minerals between 145-110 ka left the age model unconstrained over the penultimate glacial termination (Termination II). We thus established a tie point between plant wax δD values in the core and a nearby speleothem δ18O record at the beginning of the Last Interglacial. We construct a Bayesian age model allowing stratigraphy to inform sedimentation rate inflections. We find the >210 ka SLAPP-SRLS17 record contains five major units that correspond with prior work. The new dating is broadly consistent with previous efforts but provides more precise age estimates and a detailed evaluation of evaporite depositional history. We also offer a substantial revision of the age of the Bottom Mud-Mixed Layer contact, shifting it from ~130 ka to 178±3 ka. The new U-Th chronology documents the timing of mud and salt layers and lays the foundation for climate reconstructions.

Coastal flooding associated with hurricanes and other major storm events along the U.S. Coast results from complex interactions between freshwater flows, tides, storm surge, and wave effects. We have developed a two-way coupled model consisting of the National Water Model (NWM), the Advanced Circulation Ocean Model (ADCIRC), and WAVEWATCH III (WWIII) to quantify these interactions and compute total water levels in the coastal zone after significant riverine and coastal flooding events. This coupled continental coastal model covers the US Gulf and Atlantic Coasts, extending from the US-Canada border to the US-Mexico border. The Delft3D FM, D-Flow Flexible Mesh (D-Flow FM) model simulates coastal flooding on a 2D unstructured mesh within the National Water Model (NWM)/ADCIRC/WWIII coupled system. We developed a high quality 2D unstructured mesh using a sizing function that assigns element sizes based on proximities of coastal features at given spatial locations. Data sources used to identify relevant coastal features included NWM streamlines, the National Hydrography Dataset (NHD), and United States Army Corps of Engineers (USACE) data, allowing integration of D-Flow FM with the NWM and optimization of the number of computational points. The system obtains freshwater inflow boundary conditions to D-Flow FM from the NWM channel network. Offshore water levels boundary conditions for D-Flow FM come from the coupled ADCIRC-WWIII model. Domain sub-setting keeps runtimes within reasonable limits, as it does execution of the detailed hydrodynamic model within a user-defined area enclosing the storm landfall site. The advantage of this approach comes from the fact that the same coupled model setup allows simulation of coastal flooding for different storm events; only the sub-setting enclosure and the atmospheric forcing require updating from case to case. Model validation, consisting of water level comparisons against observations from simulations using the coupled system for historical storm events. The model simulations satisfactorily reproduced observed spatial and temporal variations of total water levels. In conclusion, this study presents performance of the sub-setting approach in reducing runtime considerably without compromising the accuracy of the coupled modeling system solution.

Projections of nonstationary climate risks can vary considerably from one source to another, posing considerable communication and decision-analytical challenges. One such challenge is how to present trade-offs under deep uncertainty in a salient and interpretable manner. Some common approaches include analyzing a small subset of projections or treating all considered projections as equally likely. These approaches can underestimate risks, hide deep uncertainties, and are mostly silent on which assumptions drive decision-relevant outcomes. Here we introduce and demonstrate a transparent Bayesian framework for synthesizing deep uncertainties to inform climate risk management. The first step of this workflow is to generate an ensemble of simulations representing possible futures and analyze them through standard exploratory modeling techniques. Next, a small set of probability distributions representing subjective beliefs about the likelihood of possible futures is used to weight the scenarios. Finally, these weights are used to compute and characterize trade-offs, conduct robustness checks, and reveal implicit assumptions. We demonstrate the framework through a didactic case study analyzing how high to elevate a house to manage coastal flood risks.