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The Soberanes Fire burned 53,470 ha (132,127 acres) along the central California coast between 22 July and 12 October 2016, generating dense smoke and a variety of gaseous compounds that drifted eastward into the San Joaquin Valley Air Basin (SJVAB), an "extreme" nonattainment area for ozone (O3). These gases included nitrogen oxides (NOx) and volatile organic compounds, the photochemical precursors of O3. The fire started during the California Baseline Ozone Transport Study, a field campaign that brought aircraft, surface, and remote sensing measurements of O3 and related species to central California. In this paper, we use the California Baseline Ozone Transport Study measurements to assess the impact of the Soberanes Fire on ozone and particulate air quality in the SJVAB. We focus our analysis on 27 July to 2 August when the smoke haze was heaviest and the highest O3 concentrations in the SJVAB during 2016 were recorded. Our analyses suggest that while 40 to 60 ppbv of fire‐generated O3 was transported to the eastern SJVAB in the 1‐ to 3‐km‐altitude range, relatively little smoke or fire‐generated O3 reached the surface in the Visalia area. Key Points: Aircraft and remote sensing measurements are used to investigate impacts of the Soberanes Fire on air quality in the San Joaquin ValleyOzone enhancements in excess of 50 ppbv were measured by both lidar and aircraft between 1 and 3 km above the surfaceNo significant enhancements in surface ozone were observed [ABSTRACT FROM AUTHOR]

High temperature alone would lead to a well‐understood loss of crop yields, but the compounding effects by other global change factors are much less well understood and can either amplify or reduce temperature‐driven yield change. Analysis focusing on U.S. maize yield shows that the concurrent changes in precipitation have nonnegligible influence on temperature‐yield relations. For the country as a whole, ~27% of the observed strength of temperature‐yield relation relates to the compounding precipitation effects. Further analysis shows that precipitation exerted the compounding effects mainly through its direct influence on yields rather than indirectly from its feedback to temperature. Under 2 and 1.5°C global warming, maize yield for the country as a whole is projected to decrease by ‐13.53 to ‐14.37% and ‐9.02 to ‐9.29%, respectively, with the magnitude of change depending on the climate model. Around 30% of the benefit by constraining global warming to 1.5°C would be contributed by the compounding precipitation effects, pointing to the important role of precipitation in regulating the impacts of temperature rise on yields. The results can greatly improve our understanding and interpretation of the important but uncertain temperature‐yield relations. Plain Language Summary: This paper assesses the precipitation effect in modulating maize yield response to temperature rise in the United States within the context of global warming. Results show that excluding the effect of precipitation does not lead to significant change in the spatial distribution pattern of temperature‐driven maize yield changes but can alter the magnitudes substantially. For the country as a whole, concurrent changes in precipitation lead to a decrease in the sensitivity of maize yield to growing‐season temperature from ‐7.48 to ‐5.47%/k. Constraining global warming to 1.5°C can benefit maize yield by reducing temperature‐driven loss from ‐13.53 to ‐14.37% under 2°C to ‐9.02 to ‐9.29%. However, the estimated benefit by limiting global warming to 1.5°C versus 2°C would be altered considerably, when the effects induced by precipitation changes are excluded. This study highlights the important role of precipitation in regulating temperature impact on crop yields, which are subject to substantial uncertainties. Key Points: U.S. maize yield is projected to decrease by ‐13.53 to ‐14.37% and ‐9.02 to ‐9.29% under 2 and 1.5 degrees Celsius global warming, respectivelyThe compounding precipitation effect is substantial in modulating temperature impact on maize yield under global warmingSuch effects are exerted mainly through the direct influence on yields than indirectly through its covariance with temperature [ABSTRACT FROM AUTHOR]

With the 2011 promulgation of the Mercury and Air Toxics Standards by the U.S. Environmental Protection Agency, and the successful negotiation by the United Nations Environment Program of the Minamata Convention, emissions of mercury (Hg) have declined in the United States. While the declines in atmospheric Hg concentrations in North America are encouraging, linking the declines to changing domestic and global source portfolios remains challenging. To address these research gaps, the U.S. Geological Survey initiated the first national‐scale effort to establish a baseline of total gaseous mercury stable isotope values at 31 sites distributed across the United States. Results indicated that unique Hg sources, such as Hg evasion from an elemental Hg contaminated site or free tropospheric intrusions in high altitude sites, were distinguishable from background atmospheric values. Minor gradients were observed across the nation, with regions of heavy industrial activity demonstrating lower δ202Hg, but no consistent changes in other isotopes such as Δ199Hg and Δ200Hg were observed. Furthermore, δ202Hg was impacted by foliar uptake and senescence but trends varied between forested regions in the northeastern and midwestern United States. These data demonstrate regional emission sources and other environmental variables can impact total gaseous Hg (TGM) isotope values, highlighting the need to characterize atmospheric Hg isotopes over larger geographical areas to evaluate changes related to national and international Hg regulations. Plain Language Summary: A simple, economic total gaseous mercury analyzer was deployed across the United States to determine if atmospheric sources of mercury were distinguishable across regions and seasons using mercury stable isotope values. Results indicated that heavily contaminated sites and high elevation sites did have different mercury isotope values, but overall values across the country were similar. Further application of these measurements may aid in assessing the impact and changing sources of mercury because of federal and global initiatives, including the Minamata Convention on Mercury. Key Points: Mercury isotope values were measured on a national scale across a wide range of environmentsSource proximity and seasonal variables dictate Hg isotope values for total gaseous mercuryExtreme industrial contributions can be distinguished from background atmospheric mercury [ABSTRACT FROM AUTHOR]

The radiative effects of the large‐scale air traffic slowdown during April and May 2020 due to the international response to the COVID‐19 pandemic are estimated by comparing the coverage (CC), optical properties, and radiative forcing of persistent linear contrails over the conterminous United States and two surrounding oceanic air corridors during the slowdown period and a similar baseline period during 2018 and 2019 when air traffic was unrestricted. The detected CC during the slowdown period decreased by an area‐averaged mean of 41% for the three analysis boxes. The retrieved contrail optical properties were mostly similar for both periods. Total shortwave contrail radiative forcings (CRFs) during the slowdown were 34% and 42% smaller for Terra and Aqua, respectively. The corresponding differences for longwave CRF were 33% for Terra and 40% for Aqua. To account for the impact of any changes in the atmospheric environment between baseline and slowdown periods on detected CC amounts, the contrail formation potential (CFP) was computed from reanalysis data. In addition, a filtered CFP (fCFP) was also developed to account for factors that may affect contrail formation and visibility of persistent contrails in satellite imagery. The CFP and fCFP were combined with air traffic data to create empirical models that estimated CC during the baseline and slowdown periods and were compared to the detected CC. The models confirm that decreases in CC and radiative forcing during the slowdown period were mostly due to the reduction in air traffic, and partly due to environmental changes. Plain Language Summary: Contrails produced by aircraft flying in cold but humid air both warm the atmosphere by reducing infrared radiation emitted back into space and cool it by increasing reflected sunlight. Due to the decrease in air traffic during the first months of the COVID pandemic, fewer satellite‐detectable contrails were produced compared to pre‐pandemic times, and thus the radiative effects of contrails were also diminished. But changes in the overall temperature and humidity at aircraft cruise altitudes also affect contrail formation and might explain at least some of the observed decrease in contrail coverage during April and May 2020. Analysis of satellite imagery showed that the thickness and ice‐crystal size of the contrails during the COVID period did not change much from pre‐pandemic contrails. The regional contrail coverage was accurately simulated from a combination of the estimated air traffic activity at cruise altitude and the probable frequency of when atmospheric conditions were favorable for contrail formation. This simulation confirms that most of the decrease in contrails and their radiative effects during the COVID‐related slowdown period were due to the reduction in air traffic, and to a lesser extent to changes in temperature and humidity at cruise altitude during April and May 2020. Key Points: Contrail coverage during the start of the COVID pandemic was reduced significantly over the study area, mostly due to less air trafficMonthly mean coverage was accurately estimated from a simple relation between air traffic and contrail formation probabilityThe relation confirms that the decrease in contrail radiative effects is greater than that expected from the decrease in air traffic alone [ABSTRACT FROM AUTHOR]

A lightning nitrogen oxides (LNOx) emissions model using satellite‐observed lightning optical energy is introduced for utilization in Air Quality modeling systems. The effort supports assessments of air‐quality/climate coupling as related to the influence of LNOx on atmospheric chemistry. The Geostationary Lightning Mapper (GLM), International Space Station Lightning Imaging Sensor (ISS‐LIS), and the Tropical Rainfall Measuring Mission (TRMM) LIS data are used to examine the efficacy of the method, extend the previously derived LNOx record, and demonstrate a path for using ISS‐LIS observations to cross‐calibrate regional LNOx estimates from the future global constellation of geostationary lightning observations. A detailed evaluation of the GLM data set is provided to establish the robustness of observations for LNOx estimates and to make preliminary assessments of the LNOx emissions model. Seasonal and geographical variation, land/ocean contrast, and annual fluctuation in the GLM observed lightning activity and flash optical energy are provided. GLM detection substantially degrades with the increase in the field of view, resulting in 44% more flashes and 40% less optical energy observation by GLM‐16 (compared to GLM‐17) to the east of the middle‐longitude between the two mappers (106.2°W). Regular horizontal striations are found in the optical energy product. On average, GLM flashes matched to the cloud‐to‐ground flashes have ∼30% longer duration, 50%–70% more extension, and ≥100% higher optical energy compared to the unmatched flashes (assumed to be intra‐cloud). The results from summer‐long chemical transport simulations using LNOx generated from the emission model agrees with previous studies and shows consistency across the GLM/LIS data sets. Plain Language Summary: A three‐dimensional lightning nitrogen oxides (LNOx) emissions model is introduced for use in Air Quality modeling. This model uses satellite‐observed lightning optical energy with the empirical vertical distribution. By using the observed optical energy, the model generates the actual LNOx features for intra‐cloud/cloud‐to‐ground flash fluctuations as well as geographic, land/ocean, and seasonal variations. The model performed consistently when tested using data from the Geostationary Lightning Mapper (GLM), the International Space Station Lightning Imaging Sensor (ISS‐LIS), and the Tropical Rainfall Measuring Mission (TRMM) LIS. This experiment paves the way for cross‐calibrating regional LNOx estimates using ISS‐LIS data for future global geostationary lightning observations. In our detailed analysis of the GLM data set, we found significant detection degradation near the edge of the instrument's field of view. East of the midpoint between the two mappers over the contiguous United States (106.2°W), GLM‐16 (east) detected 44% more lightning strikes and 40% less optical energy than that detected by GLM‐17 (west). Additionally, we found consistent horizontal striations in the optical energy product. Applications utilizing the data may have to compensate for these deficiencies. Key Points: Detailed Geostationary Lightning Mapper (GLM) data evaluation that shows the GLM detection efficiency, field of view edge detection degradation, striation artifacts in detected lightning optical energyGeographical and temporal variation in lightning activity and flash optical energyLNOx emission model that mirrors geographical, land/ocean, seasonal, and intra‐cloud/cloud‐to‐ground variabilities exhibited in the detected flash optical energy [ABSTRACT FROM AUTHOR]

Heat waves are among the deadliest natural hazards affecting the United States (US). Therefore, understanding the physical mechanisms modulating their occurrence is essential for improving their predictions and future projections. Using observational data and model simulations, this study finds that the interannual variability of the tropical Atlantic warm pool (AWP, measured as the area enclosed by the 28.5°C sea surface temperature isotherm) modulates heat wave occurrence over the US Great Plains during boreal summer. For example, a larger than normal AWP enhances atmospheric convection over the Caribbean Sea, driving an upper tropospheric anticyclonic anomaly over the Gulf of Mexico and Great Plains, which strengthens subsidence, reduces cloud cover, and increases surface warming. This circulation anomaly thus weakens the Great Plains low‐level jet and associated moisture transport into the Great Plains, leading to drought conditions and increased heat wave occurrence for most of the US east of the Rockies. Plain Language Summary: Extreme heat is responsible for the most weather‐related deaths in the United States (US). Using observations and numerical model experiments, this study investigates the potential predictability of heat waves determined by the state of the tropical Atlantic sea surface temperature (SST). During boreal summer (June‐July‐August), a larger than normal area of warm SST produces an atmospheric response over the US Great Plains, leading to increased clear‐sky conditions, rainfall deficits, surface temperature, and heat wave events. The results of this study suggest a potential seasonal predictability of high‐impact extreme heat events, owing to the longer prediction skill of SST. Key Points: This work investigates oceanic drivers of interannual variability of North American heat wavesA larger than normal tropical Atlantic warm pool increases the likelihood of heat wave occurrenceThe inherently longer predictability of tropical Atlantic sea surface temperature anomalies could extend predictions of United States heat waves [ABSTRACT FROM AUTHOR]

Extreme precipitation events, including those associated with weather fronts, have wide‐ranging impacts across the world. Here we use a deep learning algorithm to identify weather fronts in high resolution Community Earth System Model (CESM) simulations over the contiguous United States (CONUS), and evaluate the results using observational and reanalysis products. We further compare results between CESM simulations using present‐day and future climate forcing, to study how these features might change with climate change. We find that detected front frequencies in CESM have seasonally varying spatial patterns and responses to climate change and are found to be associated with modeled changes in large scale circulation such as the jet stream. We also associate the detected fronts with precipitation and find that total and extreme frontal precipitation mostly decreases with climate change, with some seasonal and regional differences. Decreases in Northern Hemisphere summer frontal precipitation are largely driven by changes in the frequency of different front types, especially cold and stationary fronts. On the other hand, Northern Hemisphere winter exhibits some regional increases in frontal precipitation that are largely driven by changes in frontal precipitation intensity. While CONUS mean and extreme precipitation generally increase during all seasons in these climate change simulations, the likelihood of frontal extreme precipitation decreases, demonstrating that extreme precipitation has seasonally varying sources and mechanisms that will continue to evolve with climate change. Plain Language Summary: Extreme precipitation can have devastating impacts on communities and ecosystems around the world. One source of extreme precipitation is weather fronts, or the boundaries between different types of air masses which can also give rise to high winds, rain, and thunderstorms. Machine learning can be used to automatically detect weather fronts in observations and model simulations. In this work, we use a machine learning algorithm to detect weather fronts in a climate model, and compare present day fronts with those detected in simulations with future climate change. We also compare detected fronts with total and extreme precipitation, to better understand sources of extreme precipitation and how they are changing with climate change. Key Points: A deep learning algorithm is applied to detect weather fronts in climate model simulations over the contiguous United StatesDetected fronts have seasonally varying spatial patterns of front frequencies and responses to climate changeTotal and extreme precipitation associated with fronts mostly decreases with climate change, largely driven by changes in fronts [ABSTRACT FROM AUTHOR]

Mineral dust is among the top contributors to global aerosol loads. Ability of non‐photosynthetic vegetation (NPV) to suppress dust emission has been widely acknowledged but a realistic representation of NPV has not been tested with regional‐to‐global scale models. In this study, we implemented a satellite‐based total vegetation data set, which included NPV, into a regional atmospheric chemistry model and conducted simulations for the year 2016 over the conterminous United States. To test the response of dust simulations to the NPV coverage, we conducted a control simulation incorporating only the photosynthetic vegetation (PV). Simulated dust emissions decrease by 10%–70% over most of the southwestern US from spring to autumn due to NPV. Reductions in dust concentrations are the largest in spring, which attenuate the overpredictions of fine soil concentrations, but accentuate the underpredictions in summer. Overall, the mean errors and correlations of annual simulations are slightly improved with NPV. NPV modulates dust emissions mainly by sheltering the surface and increasing the threshold velocity through drag partitioning. Moreover, we investigated the effect of vegetation height and addressed its uncertainties through a series of sensitivity tests. We observed that a 50% variation in predefined vegetation heights results in small changes in soil concentrations over majority of southwestern US, but causes up to 30% changes at local hotspots. This study highlights the significance of including NPV into the dust model and points out the importance of validation of total vegetation datasets as well as more realistic representation of vegetation heights and seasonality. Plain Language Summary: Severe dust‐emission events can interrupt traffic, damage infrastructure, and incur cleaning expenses locally. Dust particles that are lifted into the air by wind are also associated with global health problems and climate effects. Most of the global dust emissions come from arid or semi‐arid environments where the brown vegetation is abundant, and dust emissions are thus modulated by the presence of brown vegetation. However, most of the current atmospheric models omit brown vegetation because it cannot be detected easily similar to green vegetation. In this study, we provided a total vegetation (sum of green and brown vegetation) data set as an input to an atmospheric chemistry model, and simulated annual dust emissions over the conterminous United States. We find that the brown vegetation reduces the dust concentrations in air by above 10% over most of the southwestern US from spring to autumn. The reductions are mainly because the brown vegetation directly protects the surface from wind erosion, as well as reduces the drag on the surface such that a minimum wind speed needed to initiate dust emissions becomes higher. Meanwhile, we found that changes in vegetation height can moderately change dust emissions over certain areas. Key Points: A satellite‐based total (photosynthetic and non‐photosynthetic) vegetation data set is implemented in a dust emission modelNon‐photosynthetic vegetation reduces simulated dust concentrations by 10%–70% in most areas of the southwestern US from spring to autumnVegetation height has important local effects on simulated dust concentrations [ABSTRACT FROM AUTHOR]

Several locations across the United States in noncompliance with the national standard for ground‐level ozone (O3) are thought to have sizable influences from distant extra‐regional emission sources or natural stratospheric O3, which complicate the design of local emission control measures. To quantify the amount of long‐range‐transported O3 (LRT O3), its origin, and change over time, we conduct and analyze detailed sensitivity calculations characterizing the response of O3 to emissions from different source regions across the Northern Hemisphere in conjunction with multidecadal simulations of tropospheric O3 distributions and changes. Model calculations show that the amount of O3 at any location attributable to sources outside North America varies both spatially and seasonally. On a seasonal‐mean basis, during 1990–2010, LRT O3 attributable to international sources steadily increased by 0.06–0.2 ppb yr−1 at locations across the United States and arose from superposition of unequal and contrasting trends in individual source‐region contributions, which help inform attribution of the trend evident in O3 measurements. Contributions of emissions from Europe steadily declined through 2010, while those from Asian emissions increased and remained dominant. Steadily rising NOx emissions from international shipping resulted in increasing contributions to LRT O3, comparable to those from Asian emissions in recent years. Central American emissions contribute a significant fraction of LRT O3 in southwestern United States. In addition to the LRT O3 attributable to emissions outside of North America, background O3 across the continental United States is composed of a sizable and spatially variable fraction that is of stratospheric origin (29%–78%). Plain Language Summary: Though implementation of control measures and technological advances have reduced ground‐level ozone pollution across the United States, increasing amounts of ozone pollution inter‐continentally transported from other world regions with increasing emissions, combined with changing and uncertain amounts of natural ozone from variability in stratosphere‐troposphere exchange processes, can confound design and implementation of local air pollution abatement strategies. "Background" or amount not produced locally constitutes a larger fraction of the ozone pollution at a location as local control measures are implemented. Detailed model calculations are analyzed to explain the role of the dominant source regions that drive the 1990–2010 changes noted in observed ground‐level ozone measurements across the United States. In recent years, the contributions of shipping emissions to ozone imported to the U.S. troposphere are comparable to those from the transport of ozone attributable to East Asian emissions and could be higher in the future if commercial shipping operations were to increase in response to anticipated growth in seaborne trade. In addition to the O3 attributable to emissions from different world regions, air masses entering the North American domain have sizable contributions of natural ozone of stratospheric origin, variability in which needs improved quantification to guide background ozone assessments and policy deliberations. Key Points: Changes in global emission patterns have and continue to alter long‐range transport and background O3 air pollution levelsLong‐range‐transported O3 to North America has a prominent contribution from open sea shipping emissions and needs improved quantificationStratospheric O3 (ranging between 6 and 20 ppb) constitutes 29%–78% of the estimated Spring‐time background O3 across the continental United States [ABSTRACT FROM AUTHOR]

Strengthened land‐atmosphere coupling in the northeastern United States (NEUS), accompanied by a positive soil moisture‐rainfall feedback, may lead to more drought. Coupling between the land and atmosphere emerges when low soil moisture values limit surface latent heat flux, or evapotranspiration, so that a majority of absorbed solar radiation is emitted from the surface as sensible heat. In this study, the Weather Research and Forecasting model was run with four prescribed soil moisture levels across 7 years to elucidate the strength of land‐atmosphere coupling under potential, future soil moisture states in the NEUS. Under drier conditions, land‐atmosphere coupling strengthens, and a positive soil moisture‐precipitation feedback develops in all years despite differences in the amount of moisture advected into the study domain. As snowpack decreases and evaporative demand increases, soil conditions may become drier in future summers over the NEUS, resulting in the more frequent development of drought. Key Points: The strength of land‐atmosphere coupling in the northeastern United States (NEUS) may increase under drier soil moisture conditionsA positive soil moisture‐rainfall feedback may develop under land‐atmosphere coupling, increasing the risk for droughtWith decreased snowpack and increased evapotranspiration in the NEUS expected, drought may become more common under climate change [ABSTRACT FROM AUTHOR]

Global trends in tropospheric nitrogen dioxide (NO2) have changed dramatically in the past decade. Here, we investigate tropospheric NO2 variabilities over United States, Europe, and E. China in 2005–2018 to explore the mechanisms governing the variation of this critical pollutant. We found large uncertainties in the trends of anthropogenic nitrogen oxides (NOx) emissions, for example, the reductions of NOx emissions, derived with different approaches and data sets, are in the range of 35%–50% over the United States and 15%–45% over Europe in 2005–2018. By contrast, the analysis in this work indicates declines of anthropogenic NOx emissions by about 40% and 25% over the United States and Europe, respectively, in 2005–2018, and about 20% over E. China in 2012–2018. However, the shift of major NOx sources from power generation to industrial and transportation sectors has led to noticeable diminishing effects in emission controls. Furthermore, satellite measurements exhibit the influence of NO2 background levels over the United States and Europe, which offset the impacts of anthropogenic emission declines, resulting in flatter trends of tropospheric NO2 over the United States and Europe. Our analysis further reveals underestimation of background NO2 by chemical transport models, which can lead to inaccurate interpretations of satellite measurements. We use surface in‐situ NO2 observations to diagnose the satellite‐observed NO2 trends and find top‐down NOx emissions over urban grids represent the changes in anthropogenic NOx emissions better. This work highlights the importance of comprehensive applications of different analysis approaches to better characterizing atmospheric composition evolution. Plain Language Summary: Nitrogen oxides (NOx) are one of the important air pollutants and play a key role in the tropospheric environment. Therefore, a correct understanding of the variation of global tropospheric NOx in recent years seems extremely important. Here, we use different approaches and data sets to obtain the trends of anthropogenic NOx emissions and explore the mechanisms governing the variation of tropospheric NOx over the United States, Europe, and E. China during 2005–2018. We found large uncertainties in the trends of anthropogenic NOx emissions derived with these approaches and data sets, due to the insufficient understanding of real‐world reduction efficiencies of emission control technologies and the impacts of non‐anthropogenic NOx changes. After considering these issues, we found significant decreases of anthropogenic NOx emissions by about 40% and 25% over the United States and Europe in 2005–2018, and about 20% over E. China in 2012–2018. This work highlights the importance of comprehensive applications of different analysis approaches to better characterizing atmospheric composition evolution. Key Points: Shift of major NOx sources from power generation to industrial and transportation has led to diminishing effects in emission controlsThe growing importance of transportation in China poses a significant barrier to reducing anthropogenic NOx in the near futureSatellite‐based top‐down NOx emissions over urban grids provide better representation for the changes in anthropogenic NOx emissions [ABSTRACT FROM AUTHOR]

The Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) deployed the NSF/NCAR C‐130 aircraft in summer 2018 across the western U.S. to sample wildfire smoke during its first days of atmospheric evolution. We present a summary of a subset of reactive oxidized nitrogen species (NOy) in plumes sampled in a pseudo‐Lagrangian fashion. Emissions of nitrogen oxides (NOx = NO + NO2) and nitrous acid (HONO) are rapidly converted to more oxidized forms. Within 4 h, ∼86% of the ΣNOy is in the form of peroxy acyl nitrates (PANs) (∼37%), particulate nitrate (pNO3) (∼27%), and gas‐phase organic nitrates (Org N(g)) (∼23%). The average e‐folding time and distance for NOx are ∼90 min and ∼40 km, respectively. Nearly no enhancements in nitric acid (HNO3) were observed in plumes sampled in a pseudo‐Lagrangian fashion, implying HNO3‐limited ammonium nitrate (NH4NO3) formation, with one notable exception that we highlight as a case study. We also summarize the observed partitioning of NOy in all the smoke samples intercepted during WE‐CAN. In smoke samples intercepted above 3 km above sea level (ASL), the contributions of PANs and pNO3 to ΣNOy increase with altitude. WE‐CAN also sampled smoke from multiple fires mixed with anthropogenic emissions over the California Central Valley. We distinguish samples where anthropogenic NOx emissions appear to lead to an increase in NOx abundances by a factor of four and contribute to additional PAN formation. Key Points: NOx and HONO are rapidly converted to other species. The average e‐folding time (distance) for NOx is ∼90 min (∼40 km)In 4 h, PANs contribute ∼37% of the ΣNOy species in smoke; pNO3 is the second largest (∼27%) contributorIn 4 h, Org N(g) constitute a large portion (∼23%) of the ΣNOy in the plumes sample during WE‐CAN [ABSTRACT FROM AUTHOR]

Wildfires in the western United States are large sources of particulate matter, and the area burned by wildfires is predicted to increase in the future. Some particles released from wildfires can affect cloud formation by serving as ice‐nucleating particles (INPs). INPs have numerous impacts on cloud radiative properties and precipitation development. Wildfires are potentially important sources of INPs, as indicated from previous measurements, but their abundance in the free troposphere has not been quantified. The Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen campaign sampled free tropospheric immersion‐freezing INPs from smoke plumes near their source and downwind, along with widespread aged smoke. The results indicate an enhancement of INPs in smoke plumes relative to out‐of‐plume background air, but the magnitude of enhancement was both temperature and fire dependent. The majority of INPs were inferred to be predominately organic in composition with some contribution from biological sources at modest super cooling, and contributions from minerals at deeper super cooling. A fire involving primarily sagebrush shrub land and aspen forest fuels had the highest INP concentrations measured in the campaign, which is partially attributed to the INP characteristics of lofted, uncombusted plant material. Electron microscopy analysis of INPs also indicated tar balls present in this fire. Parameterization of the plume INP data on a per‐unit‐aerosol surface area basis confirmed that smoke is not an efficient source of INPs. Nevertheless, the high numbers of particles released from, and ubiquity of western US wildfires in summertime, regionally elevate INP concentrations in the free troposphere. Key Points: Wildfires are sources of ice‐nucleating particles (INPs) to the free troposphereINP compositions from sampled wildfires were dominated by organicsContributions of tar ball composition INPs evidenced a secondary formation mechanism [ABSTRACT FROM AUTHOR]

Reactive nitrogen (Nr) within smoke plumes plays important roles in the production of ozone, the formation of secondary aerosols, and deposition of fixed N to ecosystems. The Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) field campaign sampled smoke from 23 wildfires throughout the western U.S. during summer 2018 using the NSF/NCAR C‐130 research aircraft. We empirically estimate Nr normalized excess mixing ratios and emission factors from fires sampled within 80 min of estimated emission and explore variability in the dominant forms of Nr between these fires. We find that reduced N compounds comprise a majority (39%–80%; median = 66%) of total measured reactive nitrogen (ΣNr) emissions. The smoke plumes sampled during WE‐CAN feature rapid chemical transformations after emission. As a result, within minutes after emission total measured oxidized nitrogen (ΣNOy) and measured total ΣNHx (NH3 + pNH4) are more robustly correlated with modified combustion efficiency (MCE) than NOx and NH3 by themselves. The ratio of ΣNHx/ΣNOy displays a negative relationship with MCE, consistent with previous studies. A positive relationship with total measured ΣNr suggests that both burn conditions and fuel N content/volatilization differences contribute to the observed variability in the distribution of reduced and oxidized Nr. Additionally, we compare our in situ field estimates of Nr EFs to previous lab and field studies. For similar fuel types, we find ΣNHx EFs are of the same magnitude or larger than lab‐based NH3 EF estimates, and ΣNOy EFs are smaller than lab NOx EFs. Plain Language Summary: Smoke from large wildfires in the western U.S. degrades air quality across the whole U.S. Smoke contains a mixture of many different gases and particles, including carbon compounds like carbon dioxide and carbon monoxide, as well as nitrogen compounds such as ammonia and nitrogen oxides. Gases containing nitrogen are important for the production of ozone and the formation of more or larger particles as the smoke moves downwind. During the summer of 2018, we used the National Science Foundation/National Center for Atmospheric Research C130 research aircraft to fly through smoke across the western U.S. and measure many of the most abundant nitrogen compounds. We find that the smoke plumes we sampled emitted more nitrogen in a reduced form than in an oxidized form, and chemical reactions change the form and phase of nitrogen very quickly in the smoke. We compare our field measurements with laboratory measurements with the goal of using them together to improve our forecasts of how and where wildfire smoke will impact air quality. Key Points: Normalized excess mixing ratios of nitrogen species are reported for western U.S. wildfires; median of 66% of emissions are in reduced formWithin minutes after emission, rapid chemistry changes the distribution (species/amount/phase) of reactive nitrogen in fresh smoke plumesFor similar fuel types, NHx emissions factors are similar to or higher than lab‐based estimates; NOy emission factors are smaller [ABSTRACT FROM AUTHOR]

We introduce the idea of simultaneous heavy precipitation events (SHPEs) to understand whether extreme precipitation has a spatial organization manifested as specified tracks or contiguous fields with inherent scaling relationships. For this purpose, we created a database of SHPEs using ground‐based precipitation observations recorded by the daily Global Historical Climatology Network across the conterminous United States during 1900–2014. SHPEs are examined for their seasonality, spatial manifestation, orientation, and areal extent. We quantified the spatial distribution of the centroids and principal axes of SHPEs and their quasi‐elliptical manifestations, azimuthal orientations, and areal extents on the ground. Four seasons, December‐January‐February (DJF), March‐April‐May (MAM), June‐July‐August (JJA), and September‐October‐November (SON) are considered to examine the spatial patterns and associated large‐scale atmospheric circulations. Results indicate that there are 54, 58, 103, and 204 SHPEs in DJF, MAM, JJA, and SON seasons, and their longest stretches range on average between 650 and 1,600, between 850 and 1,500, between 950 and 1,550, and between 750 and 1,450 km, respectively. SHPEs in the DJF, MAM, and JJA seasons occur mostly over the Pacific coast and central and midwestern United States, respectively. The atmospheric circulation patterns and mechanisms of precipitable water vapor and moisture transport in the atmosphere are also discussed in relation to these SHPEs. Power laws explain SHPEs' underlying area scaling behavior in all the four seasons, with stronger evidence in DJF and MAM. A seasonal spatial risk model is developed to predict the likelihood of SHPEs. Quantifying the characteristics of SHPEs and modeling their footprints can improve the projections of flood risk and understanding of damages to interconnected infrastructure systems. Plain Language Summary: We present a new approach to quantify extreme regional precipitation considering the spatial structure of extreme events. Defined as simultaneous heavy precipitation events (SHPEs), they measure the central location, spatial extent, and the orientation of widespread heavy rains on the land. These characteristics are derived for four seasons over the entire 20th and early 21st centuries (115 years). We interpret the features of SHPEs over the Pacific Coast, Midwest, and the Northeastern United States using a combination of atmospheric circulation and moisture transport features. A seasonal spatial risk model is also developed to identify the probability of any region experiencing SHPEs. The framework and findings presented in this study can help in developing improved flood risk management methods by public/private planners and agencies. The database can be used by the Earth system scientists working on extreme events to explore new avenues of research. Key Points: The location, area, and orientation of widespread precipitation extremes (SHPEs) vary seasonally and spatially across the United StatesThe longest stretch of SHPEs range on average between 650 and 1,600 km, and the frequency distribution of their areal extents follows a power lawA combination of a strong upper‐level wave and moisture convergence are the most common elements of the atmosphere required for the SHPEs [ABSTRACT FROM AUTHOR]

Both groundwater lateral flow (GLF) and human water regulation (HWR) significantly impact hydrological processes, climate, and even socioeconomic sustainable development. Reasonably representing these processes in climate system models is vital for improving hydrological predication and climate modeling. In this study, schemes including GLF and HWR were implemented into the Flexible Global Ocean‐Atmosphere‐Land System model grid‐point version 3 (CAS‐FGOALS‐g3) to investigate the hydroclimatic effects of GLF and HWR. Three groups of simulations using CAS‐FGOALS‐g3 were conducted for the period from 1976 to 2010. Comparisons between the simulations and the observations show their good performance in reproducing the hydrological processes. Results show that soil moisture and latent heat flux increased when GLF was included in the western United States, northern Australia, and northern South America, along with a shallower water table depth. The largest increases in latent flux are located in regions without water and energy limitations. Increased summer precipitation occurred in the western United States due to the wetting and cooling effects of GLF. Latent heat flux significantly increases in three key regions of the world (central United States, north China plain, and northern India), caused by wetting surface soil due to irrigation. The atmosphere also responded to HWR, with cooling at the 850 hPa level over northern India and Pakistan. Decreased precipitation occurred in India because the upward movement was weaker as a result of HWR. GLF can replenish the groundwater depression cone caused by overexploitation, especially in thick aquifers. Plain Language Summary: Groundwater lateral flow and human water regulation significantly impact hydrological processes and climate. In this study, we implemented the schemes including groundwater lateral flow and human water regulation into the Flexible Global Ocean‐Atmosphere‐Land System model to investigate the hydroclimatic effects of groundwater lateral flow and human water regulation. Comparisons between the simulations and the observations show their good performance in reproducing the hydrological processes. Groundwater lateral flow can replenish the groundwater depression cone caused by overexploitation, especially in thick aquifers. Human water regulation weakens the upward movement in India and reduces the summer precipitation. Both groundwater lateral flow and human water regulation affect soil moisture and energy fluxes at the land surface. These results suggest that groundwater lateral flow and human water regulation, which are generally simplified or excluded in climate system models, may provide missing parts for modeling water and energy fluxes and improving water management. Key Points: Schemes including groundwater lateral flow and human water regulation were coupled with CAS‐FGOALS‐g3 to study the hydroclimate effectsBoth groundwater lateral flow and human water use affect land energy fluxes by changing soil moistureHuman water use weakens the upward movement in India and reduces the summer precipitation [ABSTRACT FROM AUTHOR]

Mean magnitudes and temporal trends in aerosol optical depth (AOD) from satellite observations and an aerosol reanalysis exhibit a negative‐positive east‐northwest dipole across the contiguous United States with large magnitude negative trends over the eastern United States while small magnitude positive trends over the northwestern states. Based on analyses of Modern‐Era Retrospective Analysis for Research and Applications version 2, the AOD reduction over the eastern United States appears to be largely attributable to reductions in aerosol sulfate, while there have been marked increases in aerosol‐organic and elemental carbon over almost all of the contiguous United States and particularly the northwestern states. Long‐term trends of high aerosol pollution events (HAPEs; days with AOD over the long‐term local 90th daily AOD percentile) during 2000–2017 also indicate that over the eastern United States, both the frequency and spatial scale of summer HAPEs exhibit significant negative trends, while those of moderate aerosol events (days with AOD between the local 30th and 70th AOD percentiles) exhibit weak upward trends. Opposing trends, of smaller magnitude, are derived in the northwestern United States and southwestern Canada. Net and shortwave solar radiation show positive trends at the surface and top of atmosphere under clear‐sky conditions over the eastern United States consistent with the reduction in AOD. However, skin temperatures do not indicate significant trends during all days or HAPEs, indicating that the aerosol‐induced radiation trends are not sufficient to manifest trends in surface temperature. Precipitation during HAPEs appears to have increased during 2000–2017 over the eastern and central United States, indicating that the reduction in aerosol may already be enhancing the precipitation through aerosol‐cloud interactions. Plain Language Summary: This study quantifies changes in aerosol burdens and composition during this century and their effects on meteorological variables (e.g., sunlight, clouds, surface temperature, and rainfall) particularly during high pollution days. These high aerosol pollution days are becoming less frequent and intense over the eastern United States but more intense in the western United States during summer, which is consistent with decreasing anthropogenic sulfur emissions and increasing wildfires in the eastern and western United States, respectively. The changes in aerosol burden over the eastern United States have resulted in statistically significant increase in radiation reaching the Earth's surface, but changes in surface temperature are not significant due to the presence of other changes in the land surface. Rainfall during high pollution summer days is increasing consistent with changes in aerosol‐cloud interactions and reduced availability of hygroscopic cloud condensation nuclei. Key Points: High aerosol pollution events are declining in magnitude and spatial scale over the eastern United States but increasing in the northwestSurface net radiation during high aerosol pollution events exhibits significant positive trends over the eastern United StatesThere is evidence of increasing precipitation during high aerosol pollution events over the eastern United States and Northwest Atlantic Ocean [ABSTRACT FROM AUTHOR]

Extreme precipitation events influence watershed, agriculture, and urban management. The probability of extreme precipitation is estimated for storm water management using precipitation intensity‐duration‐frequency (PIDF) curves. This study explores developing PIDF curves from dynamically downscaled 36‐ and 12‐km simulations using the Weather Research and Forecasting (WRF) model. Three modeled data sets are examined: 36‐km WRF model forced with 2.5° (~275‐km) NCEP–DOE AMIP‐II Reanalysis (R2); 36‐km WRF model forced with 0.75° (~80‐km) ERA‐Interim; and 12‐km WRF model forced with ERA‐Interim. The WRF outputs are verified against historical observations for three cities in the Eastern United States using a 23‐year period (1988–2010). The 36‐km WRF data set driven by R2 produced PIDF curves that were acceptable at the 12‐ to 24‐hr durations, but those WRF data could not realistically simulate extremes represented by the high‐intensity, short‐duration precipitation events. Increasing the resolution of WRF's driving data from R2 to ERA‐Interim did not improve WRF's representation of precipitation events. Using 12‐km grid spacing enhances WRF's ability to reproduce PIDF curves developed from observations. Finer grid spacing dramatically improves the frequency and intensity of the 1‐ to 3‐hr events and improves the 6‐ to 24‐hr events. However, improvements with the 12‐km WRF data did not apply equally to all study sites, suggesting further modifications to the WRF configuration and/or methodology are necessary. Although imperfect, the results here lend confidence to using modeled data to construct PIDF curves, which could be valuable for projecting changes to parameters used in urban and environmental planning. Key Points: PIDF curves can be developed from WRF model output provided the grid spacing is fine enoughThirty‐six kilometers WRF output cannot represent high‐intensity, short‐duration events, but 12‐km WRF output canMultiple observations and multiple WRF grid cells should be used to develop PIDF curves for a given metropolitan area [ABSTRACT FROM AUTHOR]

Sulfur dioxide (SO2) is emitted in large quantities from coal‐burning power plants and leads to various harmful health and environmental effects. In this study, we use plume intercepts from the Wintertime INvestigation of Transport, Emission and Reactivity (WINTER) campaign to estimate the oxidation rates of SO2 under wintertime conditions and the factors that determine SO2 removal. Observations suggest that OH governs the rate SO2 oxidation in the eastern United States during winter. The range of mean oxidation rates during the day from power plants were 0.22–0.71%/hr, producing SO2 lifetimes of 13–43 days, if SO2 consumption is assumed to occur during 10.5 hr of daylight in cloudless conditions. Though most nighttime rate measurements were zero within uncertainty, there is some evidence of nighttime removal, which suggests alternate oxidation mechanisms. The fastest nighttime observed SO2 oxidation rate was 0.25±0.07%/hr, producing a combined day/night SO2 lifetime of 8.5–21 days. The upper limit of the oxidation rate (the mean+1σ of the fastest day and night observations) is 16.5%/day, corresponding to a lifetime of 6.1 days. The analysis also quantifies the primary emission of sulfate from power plants. The median mole percentage of SO4‐2 from observed plumes was 1.7% and the mean percentage sulfate was 2.8% for intercepts within 1 hr of transit to power plants. The largest value observed from close intercepts was over 7% sulfate, and the largest extrapolated value was 18%, based on intercepts further from their source and fastest observed oxidation rate. Key Points: The daytime conversion rate of SO2 to SO4‐2 was 0.22‐0.71%/hr in winter under clear‐sky conditions, with lifetimes of 140‐450 hrFor 10.5 hr of daylight, the upper limit of the oxidation rate is 16.5%/day, corresponding to a lifetime of 6.1 daysDirect emissions of SO4‐2 relative to total sulfur (SO2 + SO4‐2) had mean and median values of 1.7% and 2.8%, respectively [ABSTRACT FROM AUTHOR]

Atmospheric ammonia plays an important role in a number of environmental issues, including new particle formation and aerosol indirect radiative forcing. Over the United States, atmospheric ammonia has seen an increasing trend due in most part to the declining SO2 and NOx emissions. We conduct the first comprehensive assessment of multiyear Goddard Earth Observing System (GEOS)‐Chem simulated ammonia concentration ([NH3]) over conterminous United States along with surface observations from all 90 National Atmospheric Deposition Program Ammonia Monitoring Network (AMoN) sites that have at least 2 years of continuous measurements. Model‐simulated [NH3] is along empirically expected lines with regard to temporal trends, seasonal variations, and spatial distribution. GEOS‐Chem‐simulated [NH3], compared to AMoN observed values, has weighted average correlation (τ) of 0.50 ± 0.15 and mean fractional bias (MFB) of −8.8 ± 56%. Most sites (63 out of 90) have −60% < MFB < +60%. The deviations from observed values vary spatially and seasonally, and there is significant wintertime underestimation (−44 ± 58%) across most of conterminous United States (except the Pacific states). The largest positive deviations occur in the Pacific states (101 ± 46%) and the largest negative deviations in the Southern Plain states (−73 ± 39%) and the Mountain states (−73 ± 84%), both in the winter months. Over the Great Plains region, GEOS‐Chem simulated [NH3] shows a much stronger dependence to emissions than AMoN observed [NH3], indicating scope for improved representation of emissions for the region. Over Southeast United States, there appears to be the strong effect of the changing emissions of SO2 and NOx in both modeled and observed [NH3]. Key Points: Modeled atmospheric ammonia concentrations is in good spatiotemporal agreement with 90 surface stations across the United States from 2007‐2017Model underestimation is dominant in winter (–44 ± 58% bias) across the United States, except the Pacific states (+101 ± 46% bias)Model‐observation correlation of seasonality is good; simulated concentrations appear more emission dominated than observations [ABSTRACT FROM AUTHOR]

Projections of multivariate climate extremes require methodological approaches that can maintain relationships among variables. Here we apply a piecewise multivariate quantile mapping approach to temperature and humidity projections from a subset of models from the Fifth Coupled Model Intercomparison Project and analyze the resulting climatology of extreme heat days (EHDs) with explicit consideration of the prevailing humidity. The piecewise multivariate bias correction method shows good fidelity in reproducing the frequency of different types of extreme heat events in the historical period. Projections for U.S. regions and individual cities for both the middle and end of the century are characterized by increases in the frequency of EHDs, and especially those characterized by high humidity. For many regions and individual cities, there is no overlap between the frequency of high‐humidity EHDs in general circulation model ensembles from the historical and future periods, indicating that increases in extreme heat are robust. Analysis of 500‐mb height, sea‐level pressure, and low‐level circulation composites for historical and future periods indicates that the Fifth Coupled Model Intercomparison Project models reproduce basic large‐scale circulation features associated with EHDs in U.S. regions and that future changes in extreme heat are related primarily to large‐scale warming rather than enhancement of regional circulation anomalies. Key Points: The frequency of dry and humid temperature extremes varies by location and interannuallyBias‐corrected projections from CMIP5 models indicate a transition toward more extreme heat days, driven largely by more humid extremes [ABSTRACT FROM AUTHOR]

Natural gas production in the United States has increased rapidly over the past decade, along with concerns about methane (CH4) fugitive emissions and its climate impacts. Quantification of CH4 emissions from oil and natural gas (O&NG) operations is important for establishing scientifically sound policies for mitigating greenhouse gases. We use the aircraft mass balance approach for three flight experiments in August and September 2015 to estimate CH4 emissions from O&NG operations over the southwestern Marcellus Shale. We estimate a mean CH4 emission rate as 21.2 kg/s with 28% coming from O&NG operations. The mean CH4 emission rate from O&NG operations was estimated to be 1.1% of total NG production. The individual best‐estimate emission rates from the three flight experiments ranged from 0.78 to 1.5%, with overall limits of 0% and 3.5%. These emission rates are at the low end of other top‐down studies, but consistent with the few observational studies in the Marcellus Shale region as well as the U.S. Environmental Protection Agency CH4 inventory. A substantial source of CH4 (~70% of observed CH4 emissions) was found to contain little ethane, possibly due to coalbed CH4 emitted either directly from coal mines or from wells drilled through coalbed layers in O&NG operations. Recent regulations requiring capture of gas from the completion‐venting step of hydraulic fracturing appear to have reduced the atmospheric release of CH4. Our study suggests that for a 20‐year time scale, energy derived from the combustion of natural gas extracted from this region likely exerts a net climate benefit compared to coal. Plain Language Summary: In this study methane (CH4) emission rates were estimated for the southwest Marcellus Shale based on airborne observations. A mean emission rate of ~21 kg CH4/s was observed from a 4,200‐km2 study area. A significant portion (~70%) of the emitted CH4 was found to originate likely from coalbeds. Our mean estimated emission rate of 1.1% of total natural gas production indicates a climate benefit of natural gas combustion compared to coal, but the full range includes values above the 2.4% break‐even point for the CH4 global warming potential over a 20‐year time horizon. Key Points: A CH4 emission rate of ~21 kg/s from a 4200 km2 area of the southwestern Marcellus in 2015 with the bulk of the CH4 coming from coalbedsWe estimate a mean CH4 emission rate of 1.1% of total natural gas production with a lower limit of 0% and an upper limit of 3.5%The mean emission rate indicates a climate impact of CH4 combustion below that of coal, but the full range includes values above this point [ABSTRACT FROM AUTHOR]

Global multiconstituent concentration and emission fields obtained from the assimilation of the satellite retrievals of ozone, CO, NO2, HNO3, and SO2 from the Ozone Monitoring Instrument (OMI), Global Ozone Monitoring Experiment 2, Measurements of Pollution in the Troposphere, Microwave Limb Sounder, and Atmospheric Infrared Sounder (AIRS)/OMI are used to understand the processes controlling air pollution during the Korea‐United States Air Quality (KORUS‐AQ) campaign. Estimated emissions in South Korea were 0.42 Tg N for NOx and 1.1 Tg CO for CO, which were 40% and 83% higher, respectively, than the a priori bottom‐up inventories, and increased mean ozone concentration by up to 7.5 ± 1.6 ppbv. The observed boundary layer ozone exceeded 90 ppbv over Seoul under stagnant phases, whereas it was approximately 60 ppbv during dynamical conditions given equivalent emissions. Chemical reanalysis showed that mean ozone concentration was persistently higher over Seoul (75.10 ± 7.6 ppbv) than the broader KORUS‐AQ domain (70.5 ± 9.2 ppbv) at 700 hPa. Large bias reductions (>75%) in the free tropospheric OH show that multiple‐species assimilation is critical for balanced tropospheric chemistry analysis and emissions. The assimilation performance was dependent on the particular phase. While the evaluation of data assimilation fields shows an improved agreement with aircraft measurements in ozone (to less than 5 ppbv biases), CO, NO2, SO2, PAN, and OH profiles, lower tropospheric ozone analysis error was largest at stagnant conditions, whereas the model errors were mostly removed by data assimilation under dynamic weather conditions. Assimilation of new AIRS/OMI ozone profiles allowed for additional error reductions, especially under dynamic weather conditions. Our results show the important balance of dynamics and emissions both on pollution and the chemical assimilation system performance. Plain Language Summary: Global multi‐constituent concentration and emission fields obtained from the assimilation of the satellite retrievals are used to understand the processes controlling air pollution during the Korea U.S.‐Air Quality (KORUS‐AQ) campaign. Our results show the important balance of dynamics and emissions both on pollution and the chemical assimilation system performance. Key Points: Multiconstituent data assimilation during KORUS‐AQ showed that emissions in South Korea were 0.42 Tg N for NOx and 1.1 Tg CO for COThese emissions were 40% and 83% higher, respectively, than the a priori bottom‐up inventories and increased ozone by up to 7.5 ± 1.6 ppbvMean ozone concentration was persistently higher over Seoul (75.1 ± 7.6 ppbv) than the broader KORUS‐AQ domain (70.5 ± 9.2 ppbv) at 700 hPa [ABSTRACT FROM AUTHOR]