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We assess the detectability of COVID‐like emissions reductions in global atmospheric CO2 concentrations using a suite of large ensembles conducted with an Earth system model. We find a unique fingerprint of COVID in the simulated growth rate of CO2 sampled at the locations of surface measurement sites. Negative anomalies in growth rates persist from January 2020 through December 2021, reaching a maximum in February 2021. However, this fingerprint is not formally detectable unless we force the model with unrealistically large emissions reductions (2 or 4 times the observed reductions). Internal variability and carbon‐concentration feedbacks obscure the detectability of short‐term emission reductions in atmospheric CO2. COVID‐driven changes in the simulated, column‐averaged dry air mole fractions of CO2 are eclipsed by large internal variability. Carbon‐concentration feedbacks begin to operate almost immediately after the emissions reduction; these feedbacks reduce the emissions‐driven signal in the atmosphere carbon reservoir and further confound signal detection., Key Points Climate model simulations suggest a lagged response in the global growth rate of atmospheric CO2 due to COVID‐19 emissions reductionsDetection of this reduction in observations is hampered by internal variability combined with reduced ocean and land uptake of CO2 Our results foreshadow the challenges of detecting the effects of CO2 mitigation efforts to meet the Paris climate agreement

Global aviation dropped precipitously during the covid‐19 pandemic, providing an unprecedented opportunity to study aviation‐induced cirrus (AIC). AIC is believed to be responsible for over half of aviation‐related radiative forcing, but until now, its radiative impact has only been estimated from simulations. Here, we show that satellite observations of cirrus cloud do not exhibit a detectable global response to the dramatic aviation reductions of spring 2020. These results indicate that previous model‐based estimates may overestimate AIC. In addition, we find no significant response of diurnal surface air temperature range to the 2020 aviation changes, reinforcing the findings of previous studies. Though aviation influences the climate through multiple pathways, our analysis suggests that its warming effect from cirrus changes may be smaller than previously estimated., Key Points Aviation reductions during COVID‐19 provide an opportunity to test the impact of aviation on cirrus cloud and diurnal temperature rangeNeither variable exhibits a detectable large‐scale response in satellite observationsComparison with previous model analyses of contrail cirrus suggests that warming by aviation‐induced cirrus may have been overestimated

The Southern Hemisphere zonal circulation manifests a downward influence of the stratosphere on the troposphere from late spring to early summer. However, the strength and timescale of the connection, given the stratospheric state, have not been explicitly quantified. Here, SH zonal wind reanalysis time series are analyzed with a methodology designed to detect the minimal set of statistical predictors of multiple interacting variables via conditional independence tests. Our results confirm from data that the variability of the stratospheric polar vortex is a predictor of the tropospheric eddy‐driven jet between September and January. The vortex variability explains about 40% of monthly mean jet variability at a lead time of 1 month and can entirely account for the observed jet persistence. Our statistical model can quantitatively connect the multidecadal trends observed in the vortex and jet during the satellite era. This shows how short‐term variability can help understand statistical links in long‐term changes., Key Points Autocorrelation of stratospheric polar vortex variability inflates persistence of cross correlations with the tropospheric eddy‐driven jetA conditional analysis identifies the vortex as statistical predictor for 40% of monthly jet variability in spring/summerThe inferred statistical model explains the enhanced jet persistence and connects the vortex and jet trends observed in the satellite era

There is growing evidence that the atmospheric dynamics of the Euro‐Atlantic sector during winter is driven in part by the presence of quasi‐persistent regimes. However, general circulation models typically struggle to simulate these with, for example, an overly weakly persistent blocking regime. Previous studies have showed that increased horizontal resolution can improve the regime structure of a model but have so far only considered a single model with only one ensemble member at each resolution, leaving open the possibility that this may be either coincidental or model dependent. We show that the improvement in regime structure due to increased resolution is robust across multiple models with multiple ensemble members. However, while the high‐resolution models have notably more tightly clustered data, other aspects of the regimes may not necessarily improve and are also subject to a large amount of sampling variability that typically requires at least three ensemble members to surmount., Key Points Climate models have difficulty representing Euro‐Atlantic regime structure correctlyIncreasing horizontal resolution improves the significance of regime clustering across multiple modelsSpatial patterns and persistence levels of regimes do not necessarily improve with increased resolution

The changing risk of extreme precipitation is difficult to project. Events are rare by definition, and return periods of heavy precipitation events are often calculated assuming a stationary climate. Furthermore, ensembles of climate model projections are not large enough to fully categorize the tails of the distribution. To address this, we cluster the contiguous United States into self‐similar hydroclimates to estimate changes in the expected frequency of extremely rare events under scenarios of global mean temperature change. We find that, although there is some regional variation, record events are projected in general to become more intense, with 500‐year events intensifying by 10–50% under 2 °C of warming and by 40–100% under 4 °C of warming. This analysis could provide information to inform regional prioritization of resources to improve the resilience of U.S. infrastructure., Key Points Spatial clustering can be used to create stable projections of extreme precipitation eventsAnalysis over the United States suggests 1,000‐year events will be up to 5 times more frequent under 2 degree C warmingDifferences in projections between regions are evident, with the U.S. East Coast and mountain regions showing large intensification

The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016, providing an unprecedented opportunity to obtain ocean surface wind speeds including wind estimates over the hurricane inner‐core region. This study demonstrates the influence of assimilating an early version of CYGNSS observations of ocean surface wind speeds on numerical simulations of two notable landfalling hurricanes, Harvey and Irma (2017). A research version of the National Centers for Environmental Prediction operational Hurricane Weather Research and Forecasting model and the Gridpoint Statistical Interpolation‐based hybrid ensemble three‐dimensional variational data assimilation system are used. It is found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for both hurricane cases, especially for the weak phase of a hurricane, implying potential benefits of using such data for future research and operational applications., Key Points The NASA Cyclone Global Navigation Satellite System (CYGNSS) provides an unprecedented opportunity to obtain ocean surface wind data over a hurricane inner‐core regionThis study found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for two notable landfalling hurricanes, Harvey and Irma (2017)

By injecting a mixture of gas and pyroclasts into the atmosphere, explosive volcanic eruptions frequently generate vortex rings, which are toroidal vortices formed by the jet's initial momentum. Here, we report high‐speed imaging and acoustic measurements of vortex rings sourcing from gas‐rich eruptive jets at Stromboli volcano (Italy). Volcanic vortex rings (VVRs) form at the vent together with an initial compression acoustic wave, VVRs maximum rise velocity being directly proportional to the amplitude and inversely proportional to the duration of the compression wave. The axial rise and acoustic signature of VVRs match well those predicted by recent fluid‐dynamic experiments. This good match allows using the high‐frequency (80–1,000 Hz) component of the jet sound and the time‐dependent rise of VVRs to retrieve two key eruption parameters: the Mach number of the eruptive jets (, Key Points Volcanic vortex rings are formed by gas‐rich, jet‐forming Strombolian‐style explosionsThe explosion acoustic signals bear the signature of the vortex rings and reveal supersonic eruptive jets with Mach number up to 1.5Vent diameter can be estimated from the time‐dependent rise of vortex rings at 0.7 m, in agreement with direct observation from Uncrewed Aerial Vehicle

Extreme temperature and pressure conditions on the surface of Venus present formidable technological challenges against performing ground‐based seismology. Efficient coupling between the Venusian atmosphere and the solid planet theoretically allows the study of seismically generated acoustic waves using balloons in the upper atmosphere, where conditions are far more clement. However, earthquake detection from a balloon has never been demonstrated. We present the first detection of an earthquake from a balloon‐borne microbarometer near Ridgecrest, CA in July 2019 and include a detailed analysis of the dependence of seismic infrasound, as measured from a balloon on earthquake source parameters, topography, and crustal and atmospheric structure. Our comprehensive analysis of seismo‐acoustic phenomenology demonstrates that seismic activity is detectable from a high‐altitude platform on Earth, and that Rayleigh wave‐induced infrasound can be used to constrain subsurface velocities, paving the way for the detection and characterization of such signals on Venus., Key Points First detection of a natural earthquake using balloon‐borne infrasound dataRayleigh wave‐induced infrasound dispersion characteristics provide constraints on subsurface velocitiesShallow waveguides, focal mechanism, and subwavelength topographic changes control infrasound amplitude and dispersion by weak earthquakes

Responses to COVID‐19 have resulted in unintended reductions of city‐scale carbon dioxide (CO2) emissions. Here, we detect and estimate decreases in CO2 emissions in Los Angeles and Washington DC/Baltimore during March and April 2020. We present three lines of evidence using methods that have increasing model dependency, including an inverse model to estimate relative emissions changes in 2020 compared to 2018 and 2019. The March decrease (25%) in Washington DC/Baltimore is largely supported by a drop in natural gas consumption associated with a warm spring whereas the decrease in April (33%) correlates with changes in gasoline fuel sales. In contrast, only a fraction of the March (17%) and April (34%) reduction in Los Angeles is explained by traffic declines. Methods and measurements used herein highlight the advantages of atmospheric CO2 observations for providing timely insights into rapidly changing emissions patterns that can empower cities to course‐correct CO2 reduction activities efficiently., Key Points Atmospheric CO2 observations can be used to detect the onset of the COVID‐19 response in Los Angeles and Washington DC/BaltimoreRelative reductions in April 2020 associated with COVID‐19 are ∼30% when compared to emissions in 2018 and 2019Decreases in vehicular traffic do not completely explain observed emissions reductions in both Los Angeles and Washington DC/Baltimore

Responding to the 2020 COVID‐19 outbreak, China imposed an unprecedented lockdown producing reductions in air pollutant emissions. However, the lockdown driven air pollution changes have not been fully quantified. We applied machine learning to quantify the effects of meteorology on surface air quality data in 31 major Chinese cities. The meteorologically normalized NO2, O3, and PM2.5 concentrations changed by −29.5%, +31.2%, and −7.0%, respectively, after the lockdown began. However, part of this effect was also associated with emission changes due to the Chinese Spring Festival, which led to ∼14.1% decrease in NO2, ∼6.6% increase in O3 and a mixed effect on PM2.5 in the studied cities that largely resulted from festival associated fireworks. After decoupling the weather and Spring Festival effects, changes in air quality attributable to the lockdown were much smaller: −15.4%, +24.6%, and −9.7% for NO2, O3, and PM2.5, respectively., Key Points The Chinese Spring Festival led to a 14.1% decrease in NO2, 6.6% increase in O3 and a mixed effect on PM2.5 across China in 2015–2019The 2020 lockdown resulted in −15.4%, −17.0%, −14.5%, −7.6%, −9.7%, and +24.6% changes for NO2, SO2, CO, PM10, PM2.5, and O3, respectivelyFireworks emissions contributed to haze in many cities such as an additional 29 μg m−3 PM2.5 in Beijing on the first lunar day of 2020

Coastal boulder deposits (CBD) provide what are sometimes the only remaining signatures of wave inundation on rocky coastlines; in recent decades, CBD combined with initiation of motion (IoM) analyses have repeatedly been used as primary evidence to infer the existence of ancient tsunamis. However, IoM storm wave heights inferred by these studies have been shown to be highly inaccurate, bringing some inferences into question. This work develops a dimensionless framework to relate CBD properties with storm‐wave hindcasts and measurements, producing data‐driven relations between wave climate and boulder properties. We present an elevation‐density‐size‐inland distance‐wave height analysis for individual storm‐transported boulders which delineates the dynamic space where storm‐wave CBD occur. Testing these new relations against presumed tsunami CBD demonstrates that some fall well within the capabilities of storm events, suggesting that some previous studies might be fruitfully reexamined within the context of this new framework., Key Points Size, elevation, and distance inland in storm‐wave‐generated coastal boulder deposits are all functions of climatological wave heightsClear data ranges exist where storm wave coastal boulder deposits do/do not existSome coastal boulder deposits previously identified as having tsunami origin may have been generated by storm waves

Many nations responded to the corona virus disease‐2019 (COVID‐19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial‐condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near‐surface temperature or rainfall during 2020–2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID‐19‐related emission reductions on near‐term climate., Key Points Lockdown restrictions during COVID‐19 have reduced emissions of aerosols and greenhouse gases12 CMIP6 Earth system models have performed coordinated experiments to assess the impact of this on climateAerosol amounts are reduced over southern and eastern Asia but there is no detectable change in annually averaged temperature or precipitation

Intensive observations and WRF‐Chem simulations are applied in this study to investigate the adverse impacts of regional transport on the PM2.5 (fine particulate matter; diameter ≤2.5 μm) changes in Shanghai during the Coronavirus Disease 2019 lockdown. As the local atmospheric oxidation capacity was observed to be generally weakened, strong regional transport carried by the frequent westerly winds is suggested to be the main driver of the unexpected pollution episodes, increasing the input of both primary and secondary aerosols. Contributing 40%–80% to the PM2.5, the transport contributed aerosols are simulated to exhibit less decreases (13.2%–21.8%) than the local particles (37.1%–64.8%) in urban Shanghai due to the lockdown, which largely results from the less decreased industrial and residential emissions in surrounding provinces. To reduce the influence of the transport, synergetic emission control, especially synergetic ammonia control, measures are proved to be effective strategies, which need to be considered in future regulations., Key Points PM2.5 pollution in Shanghai were mostly attributed to the regional transport carried by frequent westerly winds during the COVID‐lockdownThe transport contributed aerosols in Shanghai are less affected by the lockdown measures due to the less decreased surrounding emissionsSynergetic emission control measures, especially those on ammonia emissions, are effective in mitigating the adverse transport impacts

Supraglacial debris affects glacier mass balance as a thin layer enhances surface melting, while a thick layer reduces it. While many glaciers are debris‐covered, global glacier models do not account for debris because its thickness is unknown. We provide the first globally distributed debris thickness estimates using a novel approach combining sub‐debris melt and surface temperature inversion methods. Results are evaluated against observations from 22 glaciers. We find the median global debris thickness is ∼0.15 ± 0.06 m. In all regions, the net effect of accounting for debris is a reduction in sub‐debris melt, on average, by 37%, which can impact regional mass balance by up to 0.40 m water equivalent (w.e.) yr‐1. We also find recent observations of similar thinning rates over debris‐covered and clean ice glacier tongues is primarily due to differences in ice dynamics. Our results demonstrate the importance of accounting for debris in glacier modeling efforts., Key Points We produce the first distributed global debris thickness estimatesAccounting for debris significantly reduces regional glacier mass lossThe similar thinning rates of debris‐covered and clean ice glaciers in High Mountain Asia is primarily caused by differences in ice dynamics

The COVID‐19 pandemic led to a 72% reduction of air traffic over Europe in March–August 2020 compared to 2019. Modeled contrail cover declined similarly, and computed mean instantaneous radiative contrail forcing dropped regionally by up to 0.7 W m−2. Here, model predictions of cirrus optical thickness and the top‐of‐atmosphere outgoing longwave and reflected shortwave irradiances are tested by comparison to Meteosat‐SEVIRI‐derived data. The agreement between observations and modeled data is slightly better when modeled contrail cirrus contributions are included. The spatial distributions and diurnal cycles of the differences in these data between 2019 and 2020 are partially caused by differences in atmospheric and surface conditions, particularly for solar radiation in the spring of 2020. Aviation signals become discernible in the observed differences of these data between 2019 and 2020 when subtracting numerical weather prediction model results that approximate the atmosphere and surface conditions without contrails., Key Points Air traffic reduction during the COVID‐19 pandemic is used for testing aviation contrail cirrus and related radiative forcing modelingCirrus optical depth and top‐of‐atmosphere irradiances from satellite observations and model results show reasonable correlationsAviation contrail signatures are identifiable in spite of strongly different atmosphere and surface conditions in 2019 and 2020

The decline in global emissions of carbon dioxide due to the COVID‐19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID‐related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global‐scale ΔpCO2 that is attributable to COVID, though the fingerprint is difficult to detect in individual model realizations unless we force the model with a scenario that has four times the observed emissions reduction., Key Points COVID‐related emissions reductions will be imperceptible in surface ocean pH observationsThe CanESM5 COVID ensemble predicts a unique fingerprint of COVID‐related emissions reductions in global mean ΔpCO2 (pCO2oc ‐ pCO2atm)The fingerprint is potentially detectable in global‐scale observations of ΔpCO2, but only with large emissions reductions

10 pags., 4 figs., Many Chemistry-Climate Models (CCMs) include a simplified treatment of brominated very short-lived (VSL) species by assuming CHBr as a surrogate for VSL. However, neglecting a comprehensive treatment of VSL in CCMs may yield an unrealistic representation of the associated impacts. Here, we use the Community Atmospheric Model with Chemistry (CAM-Chem) CCM to quantify the tropospheric and stratospheric changes between various VSL chemical approaches with increasing degrees of complexity (i.e., surrogate, explicit, and full). Our CAM-Chem results highlight the improved accuracy achieved by considering a detailed treatment of VSL photochemistry, including sea-salt aerosol dehalogenation and heterogeneous recycling on ice-crystals. Differences between the full and surrogate schemes maximize in the lowermost stratosphere and midlatitude free troposphere, resulting in a latitudinally dependent reduction of ∼1–7 DU in total ozone column and a ∼5%–15% decrease of the OH/HO ratio. We encourage all CCMs to include a complete chemical treatment of VSL in the troposphere and stratosphere., This study has been funded by the European Union's Horizon 2020 Re-search and Innovation program (Project ‘ERC-2016-COG 726349 CLIMAHAL’), and supported by the Consejo Superior de Investigaciones Científicas of Spain. Computing resources and support are provided by the Computational and Information System Laboratory (CISL,2017). R. P. Fernandez would like to thank financial support from CONICET, ANPCyT (PICT 2015-0714), UNCuyo (SeCTyP M032/3853) and UTN (PID 4920-194/2018). NCAR is sponsored by NSF under grant number 1852977. R. J. Salawitch appreciates support from the NASA (grant ACMP 80NSSC19K0983). The authors thank two anonymous reviewers for their constructive comments

Anthropogenic emissions were greatly constrained during COVID‐19 lockdown in China. Nevertheless, observations still showed high loadings of fine particles (PM2.5) over northern China with secondary aerosols increasing by 15 μg/m3 yet a ∼10% drop in light‐absorbing black carbon (BC). Such a chemical transition in aerosol composition tended to make the atmosphere more scattering, indicated by satellite‐retrieved aerosol absorption optical depth falling by 60%. Comparison between weather forecast and radiosonde observations illustrated that, without upper‐level heating induced by BC, the stabilized stratification diminished, which was conducive for planetary boundary layer (PBL) mixing and thus near‐surface pollution dispersion. Furthermore, coupled dynamic‐chemistry simulations estimated that emission reduction during the lockdown weakened aerosol‐PBL interaction and thus a reduction of 25 μg/m3 (∼50%) in PM2.5 enhancement. Based on the unique natural experiment, this work observationally confirmed and numerically quantified the importance of BC‐induced meteorological feedback, further highlighting the priority of BC control in haze mitigation., Key Points Heavy haze still engulfed northern China despite great emission reductions during COVID‐19 lockdownEnhanced secondary aerosols and decreased black carbon (BC) led to a more scattering atmosphere and weakened aerosol‐planetary boundary layer interactionObservational evidences and quantitative modeling confirmed the importance of BC during the unique natural experiment

We introduce new parameterizations for autoconversion and accretion rates that greatly improve representation of the growth processes of warm rain. The new parameterizations capitalize on machine‐learning and optimization techniques and are constrained by in situ cloud probe measurements from the recent Atmospheric Radiation Measurement Program field campaign at Azores. The uncertainty in the new estimates of autoconversion and accretion rates is about 15% and 5%, respectively, outperforming existing parameterizations. Our results confirm that cloud and drizzle water content are the most important factors for determining accretion rates. However, for autoconversion, in addition to cloud water content and droplet number concentration, we discovered a key role of drizzle number concentration that is missing in current parameterizations. The robust relation between autoconversion rate and drizzle number concentration is surprising but real, and furthermore supported by theory. Thus, drizzle number concentration should be considered in parameterizations for improved representation of the autoconversion process., Key Points Machine‐learning trained by in situ data constrains autoconversion and accretion rates with uncertainty of 15% and 5%, respectivelyThere is a surprising relation between autoconversion rate and drizzle number concentration that significantly improves parameterizationsThe exponent of autoconversion rate dependence on cloud number concentration is 0.75, lower than that in existing parameterizations

The ocean's “biological pump” significantly modulates atmospheric carbon dioxide levels. However, the complexity and variability of processes involved introduces uncertainty in interpretation of transient observations and future climate projections. Much research has focused on “parametric uncertainty,” particularly determining the exponent(s) of a power‐law relationship of sinking particle flux with depth. Varying this relationship's functional form introduces additional “structural uncertainty.” We use an ocean biogeochemistry model substituting six alternative remineralization profiles fit to a reference power‐law curve, to systematically characterize structural uncertainty, which, in atmospheric pCO2 terms, is roughly 50% of parametric uncertainty associated with varying the power‐law exponent within its plausible global range, and similar to uncertainty associated with regional variation in power‐law exponents. The substantial contribution of structural uncertainty to total uncertainty highlights the need to improve characterization of biological pump processes, and compare the performance of different profiles within Earth System Models to obtain better constrained climate projections., Key Points Six alternative flux profiles fit to a Martin Curve yield large differences in atmospheric carbonStructural uncertainty comprises one‐third of total uncertainty in the ocean's biological pumpVarying particle attenuation with depth may account for half of the biological pump's overall carbon drawdown

A reduced‐physics model is employed at 1/25° to 1/100° global resolution to determine (a) if linear dynamics can reproduce the observed low‐mode M2 internal tide, (b) internal‐tide sensitivity to bathymetry, stratification, surface tides, and dissipation parameterizations, and (c) the amount of power transferred to the nonstationary internal tide. The simulations predict 200 GW of mode‐1 internal‐tide generation, consistent with a general circulation model and semianalytical theory. Mode‐1 energy is sensitive to damping, but a simulation using parameterizations for wave drag and wave‐mean interaction predicts 84% of satellite observed sea‐surface height amplitude variance on a 1° × 1° grid. The simulation energy balance indicates that 16% of stationary mode‐1 energy is scattered to modes 2–4 and negligible energy propagates onto the shelves. The remaining 84% of energy is lost through parameterizations for high‐mode scattering over rough topography (54%) and wave‐mean interactions that transfer energy to the nonstationary internal tide (29%)., Key Points Global mode‐1 internal tides are predictable from a linearized, reduced physics modelThe choice of damping parameterizations predetermines mode‐1 internal‐tide energySimulations with damping by wave drag and wave‐mean interactions largely agree with satellite data

We use a global transport model and satellite retrievals of the carbon dioxide (CO2) column average to explore the impact of CO2 emissions reductions that occurred during the economic downturn at the start of the Covid‐19 pandemic. The changes in the column averages are substantial in a few places of the model global grid, but the induced gradients are most often less than the random errors of the retrievals. The current necessity to restrict the quality‐assured column retrievals to almost cloud‐free areas appears to be a major obstacle in identifying changes in CO2 emissions. Indeed, large changes have occurred in the presence of clouds and, in places that were cloud‐free in 2020, the comparison with previous years is hampered by different cloud conditions during these years. We therefore recommend to favor all‐weather CO2 monitoring systems, at least in situ, to support international efforts to reduce emissions., Key Points Covid‐19 impacted the CO2 column mostly in the vicinity of a few emission locations that changed over time.These places have not been well observed by the OCO‐2 satellite because of frequent or persistent cloud conditions.To support the Paris Agreement on climate, priority should be given on the development of all‐weather carbon‐monitoring systems.

We use TROPOMI (TROPOspheric Monitoring Instrument) tropospheric nitrogen dioxide (NO2) measurements to identify cropland soil nitrogen oxide (NOx = NO + NO2) emissions at daily to seasonal scales in the U.S. Southern Mississippi River Valley. Evaluating 1.5 years of TROPOMI observations with a box model, we observe seasonality in local NOx enhancements and estimate maximum cropland soil NOx emissions (15–34 ng N m−2 s−1) early in growing season (May–June). We observe soil NOx pulsing in response to daily decreases in volumetric soil moisture (VSM) as measured by the Soil Moisture Active Passive (SMAP) satellite. Daily NO2 enhancements reach up to 0.8 × 1015 molecules cm−2 4–8 days after precipitation when VSM decreases to ~30%, reflecting emissions behavior distinct from previously defined soil NOx pulse events. This demonstrates that TROPOMI NO2 observations, combined with observations of underlying process controls (e.g., soil moisture), can constrain soil NOx processes from space., Key Points Daily TROPOMI data provide new opportunities to observe regional cropland NOx emissions from spaceSoil NOx pulsing is identified throughout the growing season with a NOx maximum observed when soils dry to ~30% volumetric soil moistureCropland NOx emissions peak at the onset of the growing season as determined by TROPOMI NO2 enhancements and a box model framework

African dust exhibits strong variability on a range of time scales. Here we show that the interhemispheric contrast in Atlantic SST (ICAS) drives African dust variability at decadal to millennial timescales, and the strong anthropogenic increase of the ICAS in the future will decrease African dust loading to a level never seen during the Holocene. We provide a physical framework to understand the relationship between the ICAS and African dust activity: positive ICAS anomalies push the Intertropical Convergence Zone (ITCZ) northward and decrease surface wind speed over African dust source regions, which reduces dust emission and transport. It provides a unified framework for and is consistent with relationships in the literature. We find strong observational and proxy‐record support for the ICAS‐ITCZ‐dust relationship during the past 160 and 17,000 years. Model‐projected anthropogenic increase of the ICAS will reduce African dust by as much as 60%, which has broad consequences., Key Points The ICAS drives African dust change at decadal and longer time scalesA unified framework supports the ICAS drive of African dust, and observations also support the ICAS‐dust‐ITCZ relationshipsClimate models suggest strong reduction in African dust due to increase in ICAS driven by global warming

We present an assessment of the impacts on atmospheric composition and radiative forcing of short‐lived pollutants following a worldwide decrease in anthropogenic activity and emissions comparable to what has occurred in response to the COVID‐19 pandemic, using the global composition‐climate model United Kingdom Chemistry and Aerosols Model (UKCA). Emission changes reduce tropospheric hydroxyl radical and ozone burdens, increasing methane lifetime. Reduced SO2 emissions and oxidizing capacity lead to a decrease in sulfate aerosol and increase in aerosol size, with accompanying reductions to cloud droplet concentration. However, large reductions in black carbon emissions increase aerosol albedo. Overall, the changes in ozone and aerosol direct effects (neglecting aerosol‐cloud interactions which were statistically insignificant but whose response warrants future investigation) yield a radiative forcing of −33 to −78 mWm−2. Upon cessation of emission reductions, the short‐lived climate forcers rapidly return to pre‐COVID levels; meaning, these changes are unlikely to have lasting impacts on climate assuming emissions return to pre‐intervention levels., Key Points Emission reductions are likely to have led to a global reduction in short‐lived climate forcers and tropospheric oxidizing capacityReductions in O3 and aerosol from both lower emissions and decreased sulfate oxidation resulted in a net negative radiative forcingThe radiative impacts are small and short‐lived. Longer term climate impacts must come through future sustained emission reductions

After the 2020 Lunar New Year, the Chinese government implemented a strict nationwide lockdown to inhibit the spread of the Coronavirus Disease 2019 (COVID‐19). Despite the abrupt decreases in gaseous emissions caused by record‐low anthropogenic activities, severe haze pollution occurred in northern China during the COVID lockdown. This paradox has attracted the attention of both the public and the scientific community. By analyzing comprehensive measurements of air pollutants, planetary boundary layer (PBL) height, and surface meteorology, we show that the severe air pollution episode over northern China coincided with the abnormally low PBL height, which had reduced by 45%, triggering strong aerosol‐PBL interactions. After dynamical processes initiated the temperature inversion, the Beijing metropolitan area experienced a period with continuously shallow PBLs during the lockdown. This unprecedented event provided an experiment showcasing the role of meteorology, in particular, aerosol‐PBL interactions in affecting air quality., Key Points Based on nationwide observations, variations in air pollution and meteorology are discussed during the COVID lockdown.The severe air pollution during the lockdown coincided with abnormally shallow PBL triggering strong aerosol‐PBL interactions.Beijing experienced a period with continuously shallow PBLs initiated by dynamical processes, which warrant the formation of haze event.

Strong links are seen in observations between convective clustering and several properties of the Intertropical Convergence Zone (ITCZ). These links suggest that biases in how climate models simulate the ITCZ may be related to model biases in convective clustering or that there may be biases in how models represent the relationship between clustering and the ITCZ. We investigate these issues by analyzing convective clustering, and the link between clustering and ITCZ properties in 18 climate models. We find that the links between variability in convective clustering and variability of ITCZ properties are generally weaker and less robust in models than in observations. By contrast, model biases in the climatological convective clustering explain a substantial fraction of the climatological double‐ITCZ bias, though they do not explain biases in the climatological ITCZ width., Key Points Climate models underestimate the link between zonal convective clustering and the ITCZ widthModel biases in convective clustering explain double‐ITCZ biases, but not ITCZ width biasesSeveral factors may play a role in linking convective clustering and the ITCZ width, but no dominant mechanism was found

This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, https://creativecommons.org/licenses/by-nc/4.0/, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes., Submicrosecond (0.476 μs per frame with an exposure time of 160 ns) high-resolution (0.38 nm) time-resolved spectra of laboratory-produced lightning-like electrical discharges have been recorded for the first time within the visible spectral range (645–665 nm). The spectra were recorded with the GrAnada LIghtning Ultrafast Spectrograph (GALIUS), a high-speed imaging spectrograph recently developed for lightning research in the IAA-CSIC. Unprecedented spectral time dynamics are explored for meter long laboratory electrical discharges produced with a 2.0 MV Marx generator. The maximum electron density and gas temperature measured in a timescale of ≤0.50 μs (160 ns) were, respectively, ≃1018 cm−3 and ≃32,000 K. Overpressure in the lightning-like plasma channel, black-body dynamics, and self-absorption in spectral lines were investigated. © 2020. The Authors., This work was supported by the Spanish Ministry of Science and Innovation, MINECO, under Projects ESP2017-86263-C4-4-R and PID2019-109269RB-C43 and the FEDER program. Additionally, this work has received funding from the European Union Horizon 2020 Framework Programme under the Marie Sk?odowska-Curie Grant Agreement SAINT 722337. F.?J.?P.-I. acknowledges the sponsorship provided by the Federal Ministry for Education and Research of Germany through the Alexander von Humboldt Foundation. A.?L. was supported by the European Research Council (ERC) under European Union Horizon 2020 Framework Programme/ERC Grant Agreement 681257. N.?K., F.?J.?G.-V., M.?P., J.?S., and A.?L. acknowledge financial support from the State Research Agency of the Spanish MCIU through the Center of Excellence Severo Ochoa award for the Instituto de Astrof?sica de Andaluc?a (SEV-2017-0709). N.?K. acknowledges a PhD contract through the Project SAINT 722337. The authors acknowledge LABELEC for having granted access to their high-voltage facilities in Terrassa (Spain). We also acknowledge Prof. P. Teulet of Paul Sabatier University (Toulouse, France) for providing equilibrium composition for air thermal plasmas.

We report the first simultaneous, common‐volume lidar observations of thermosphere‐ionosphere Fe (TIFe) and Na (TINa) layers in Antarctica. We also report the observational discovery of nearly one‐to‐one correspondence between TIFe and aurora activity, enhanced ionization layers, and converging electric fields. Distinctive TIFe layers have a peak density of ~384 cm−3 and the TIFe mixing ratio peaks around 123 km, ~5 times the mesospheric layer maximum. All evidence shows that Fe+ ion‐neutralization is the major formation mechanism of TIFe layers. The TINa mixing ratio often exhibits a broad peak at TIFe altitudes, providing evidence for in situ production via Na+ neutralization. However, the tenuous TINa layers persist long beyond TIFe disappearance and reveal gravity wave perturbations, suggesting a dynamic background of neutral Na, but not Fe, above 110 km. The striking differences between distinct TIFe and diffuse TINa suggest differential transport between Fe and Na, possibly due to mass separation., Key Points First simultaneous lidar observations show striking differences between distinct TIFe and diffuse TINa, suggesting differential transportWe report the observational discovery of the correlation of TIFe with aurora and enhanced ionization, revealing plasma‐neutral couplingAll observational evidence points to the Fe+ ion‐neutralization origin of TIFe while suggesting a background of neutral Na above 110 km

Weather forecasts play essential parts in economic activity. Assimilation of meteorological observations from aircraft improves forecasts greatly. However, global lockdown during the COVID‐19 pandemic (March to May 2020) has eliminated 50‐75% aircraft observations and imperiled weather forecasting. Here, we verify global forecasts against reanalysis to quantify the impact of the pandemic. We find a large deterioration in forecasts of surface meteorology over regions with busy air flights, such as North America, southeast China, and Australia. Forecasts over remote regions are also substantially worse during March to May 2020 than 2017–2019, and the deterioration increases for longer‐term forecasts. This could handicap early warning of extreme weather and cause additional economic damage on the top of that from the pandemic. The impact over Western Europe is buffered by the high density of conventional observations, suggesting that introduction of new observations in data‐sparse regions would be needed to minimize the impact of global emergencies on weather forecasts., Key Points The COVID‐19 pandemic eliminated 50–75% of aircraft meteorological observationsAccuracy of weather forecast reduced significantly especially over southeast China and USA, and error develops as forecast goes longerThis could handicap early warning of extreme weather; establishing more meteorology stations can buffer the impact of global emergencies

Summertime low clouds are common in the Pacific Northwest (PNW), but spatiotemporal patterns have not been characterized. We show the first maps of low cloudiness for the western PNW and North Pacific Ocean using a 22‐year satellite‐derived record of monthly mean low cloudiness frequency for May through September and supplemented by airport cloud base height observations. Domain‐wide cloudiness peaks in midsummer and is strongest over the Pacific. Empirical orthogonal function (EOF) analysis identified four distinct PNW spatiotemporal modes: oceanic, terrestrial highlands, coastal, and northern coastal. There is a statistically significant trend over the 22‐year record toward reduced low cloudiness in the terrestrial highlands mode, with strongest declines in May and June; however, this decline is not matched in the corresponding airport records. The coastal mode is partly constrained from moving inland by topographic relief and migrates southward in late summer, retaining higher late‐season low cloud frequency than the other areas., Key Points Summer low cloudiness separates into four distinct spatiotemporal sectors: oceanic, terrestrial highlands, coastal, and northern coastal modesLow cloudiness is strongest over the Pacific, where it peaks in midsummer; terrestrial and coastal areas peak in late summerSatellite records suggest a terrestrial highlands decline in low cloudiness over time, but airport records do not

Convectively injected water vapor (H2O) in the North American (NA) summer lowermost stratosphere results in significant outliers in the 100‐hPa H2O measurements from the Aura Microwave Limb Sounder (MLS). MLS statistics from 15 years confirm that the NA region contains over 60% of global 100‐hPa H2O > 12 ppmv, despite having only ∼1.8% of all MLS observations. A profile sampled in August 2019 stands out, with H2O=26.3 ppmv, far exceeding the prior record and the median ∼4.5‐ppmv abundance in NA. This particular outlier is associated with a large overshooting convective event (OCE) that spanned multiple U.S. states and persisted for several hours. Colocation of the MLS data over NA with cloud observations from Aqua's Moderate Resolution Imaging Spectroradiometer (MODIS) reveals the unique character of this case, as only 2.3% of MLS profiles are as close to an OCE and only 0.024% of OCEs cover as large an area within a 500‐km perimeter of a profile., Key Points A profile with unprecedented stratospheric humidity is associated with large overshooting convectionLarge lower stratospheric humidity outliers are in close proximity to strong overshooting convectionMLS humidity indicates trend toward larger stratospheric outliers and strengthening of North American monsoon

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere‐only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050., Key Points Biases in tropical cyclone distribution, frequency, and intensity are generally reduced in models at 25 km resolutionNorthern Hemisphere basins show mixed responses to future forcing, while Southern Indian Ocean activity projected to declineFuture changes in 10 m wind speed in coupled models are mixed, and models with lower bias suggest small increases

The retreat of glaciers in response to global warming has the potential to trigger landslides in glaciated regions around the globe. Landslides that enter fjords or lakes can cause tsunamis, which endanger people and infrastructure far from the landslide itself. Here we document the ongoing movement of an unstable slope (total volume of 455 × 106 m3) in Barry Arm, a fjord in Prince William Sound, Alaska. The slope moved rapidly between 2010 and 2017, yielding a horizontal displacement of 120 m, which is highly correlated with the rapid retreat and thinning of Barry Glacier. Should the entire unstable slope collapse at once, preliminary tsunami modeling suggests a maximum runup of 300 m near the landslide, which may have devastating impacts on local communities. Our findings highlight the need for interdisciplinary studies of recently deglaciated fjords to refine our understanding of the impact of climate change on landslides and tsunamis., Key Points This study quantifies the motion of a large periglacial landslideIt is unique that such a landslide is detected before potential failureThis study calls attention to the glacier‐retreat‐landslide‐tsunami hazards cascade

TROPOMI satellite data show substantial drops in nitrogen dioxide (NO2) during COVID‐19 physical distancing. To attribute NO2 changes to NOX emissions changes over short timescales, one must account for meteorology. We find that meteorological patterns were especially favorable for low NO2 in much of the U.S. in spring 2020, complicating comparisons with spring 2019. Meteorological variations between years can cause column NO2 differences of ~15% over monthly timescales. After accounting for sun angle and meteorological considerations, we calculate that NO2 drops ranged between 9.2 – 43.4% among twenty cities in North America, with a median of 21.6%. Of the studied cities, largest NO2 drops (>30%) were in San Jose, Los Angeles, and Toronto, and smallest drops (, Plain‐Language Summary Nitrogen dioxide (NO2) is an air pollutant whose prevalence in urban areas is linked to fossil fuel combustion. The NO2 concentrations in our atmosphere are primarily a function of the magnitude of nitrogen oxide (NOx) emissions and weather factors such as sun angle, wind speed, and temperature. In this work, we developed two novel methods to account for weather impacts on daily pollution levels during COVID‐19 precautions. Once we accounted for favorable weather conditions that in some cases kept air pollution low independent of tail‐pipe emissions, calculated air pollutant emission reductions varied dramatically (9 – 43%) among twenty North American cities. Results can be used to understand factors contributing to inconsistent NO2 changes during physical distancing, which can inform the effectiveness of COVID‐19 protocols and aid future policy development. These methodologies will allow us to respond more quickly in future unintended experiments when emissions change suddenly.

We investigate the forces and atmosphere‐ionosphere coupling that create atmospheric dynamo currents using two rockets launched nearly simultaneously on 4 July 2013 from Wallops Island (USA), during daytime Sq conditions with ΔH of −30 nT. One rocket released a vapor trail observed from an airplane which showed peak velocities of >160 m/s near 108 km and turbulence coincident with strong unstable shear. Electric and magnetic fields and plasma density were measured on a second rocket. The current density peaked near 110 km exhibiting a spiral pattern with altitude that mirrored that of the winds, suggesting the dynamo is driven by tidal forcing. Such stratified currents are obscured in integrated ground measurements. Large electric fields produced a current opposite to that driven by the wind, believed created to minimize the current divergence. Using the observations, we solve the dynamo equation versus altitude, providing a new perspective on the complex nature of the atmospheric dynamo., Key Points Comprehensive observations of the daytime Sq dynamo electrodynamics have been gathered for the first timeObserved daytime winds in the dynamo region are much larger than expected yet their currents are reduced by those of DC electric fieldsWinds and currents exhibit an interleaved spiral pattern indicative of tidal forcing

Different climate drivers influence precipitation in different ways. Here we use radiative kernels to understand the influence of rapid adjustment processes on precipitation in climate models. Rapid adjustments are generally triggered by the initial heating or cooling of the atmosphere from an external climate driver. For precipitation changes, rapid adjustments due to changes in temperature, water vapor, and clouds are most important. In this study we have investigated five climate drivers (CO2, CH4, solar irradiance, black carbon, and sulfate aerosols). The fast precipitation responses to a doubling of CO2 and a 10‐fold increase in black carbon are found to be similar, despite very different instantaneous changes in the radiative cooling, individual rapid adjustments, and sensible heating. The model diversity in rapid adjustments is smaller for the experiment involving an increase in the solar irradiance compared to the other climate driver perturbations, and this is also seen in the precipitation changes., Key Points Separation of instantaneous and rapid adjustment contributions to precipitation changesContributions of rapid adjustments to precipitation changes differ substantially between climate driversRadiative kernels are applied to understand individual rapid adjustment terms

As global temperatures increase, sea ice loss will increasingly enable commercial shipping traffic to cross the Arctic Ocean, where the ships' gas and particulate emissions may have strong regional effects. Here we investigate impacts of shipping emissions on Arctic climate using a fully coupled Earth system model (CESM 1.2.2) and a suite of newly developed projections of 21st‐century trans‐Arctic shipping emissions. We find that trans‐Arctic shipping will reduce Arctic warming by nearly 1 °C by 2099, due to sulfate‐driven liquid water cloud formation. Cloud fraction and liquid water path exhibit significant positive trends, cooling the lower atmosphere and surface. Positive feedbacks from sea ice growth‐induced albedo increases and decreased downwelling longwave radiation due to reduced water vapor content amplify the cooling relative to the shipping‐free Arctic. Our findings thus point to the complexity in Arctic climate responses to increased shipping traffic, justifying further study and policy considerations as trade routes open., Key Points Climatic responses to projected trans‐Arctic shipping emissions are simulated using a fully coupled Earth system model (CESM 1.2.2)Shipping emissions reduce Arctic warming by nearly 1 °C by 2099 due to sulfate‐driven liquid water cloud formationSea ice growth‐induced albedo increases and reduced atmospheric water vapor amplify cooling relative to control runs

Global climate models present systematic biases, among others, a tendency to overestimate hot and dry summers in midlatitude regions. Here we investigate the origin of such biases in the Community Earth System Model. To disentangle the contribution of dynamics and thermodynamics, we perform simulations that include nudging of horizontal wind and compare them to simulations with a free atmosphere. Prescribing the observed large‐scale circulation improves the modeled weather patterns as well as many related fields. However, the larger part of the temperature and precipitation biases of the free atmosphere configuration remains after nudging, in particular, for extremes. Our results suggest that thermodynamical processes, including land‐atmosphere coupling and atmospheric parameterizations, drive the errors present in Community Earth System Model. Our result may apply to other climate models and highlight the importance of distinguishing thermodynamic and dynamic sources of biases in present‐day global climate models., Key Points Thermodynamical versus dynamical sources of biases can be identified using atmospheric nudging of horizontal winds in a climate modelAtmospheric nudging improves simulated temperature and precipitation in CESM; however, more than half of the initial bias remainsFor temperature and precipitation extremes the larger part of the biases remains after correcting for the dynamics

Bursts of X‐rays and γ‐rays are observed from lightning and laboratory sparks. They are bremsstrahlung from energetic electrons interacting with neutral air molecules, but it is still unclear how the electrons achieve the required energies. It has been proposed that the enhanced electric field of streamers, found in the corona of leader tips, may account for the acceleration; however, their efficiency is questioned because of the relatively low production rate found in simulations. Here we emphasize that streamers usually are simulated with the assumption of homogeneous gas, which may not be the case on the small temporal and spatial scales of discharges. Since the streamer properties strongly depend on the reduced electric field E/n, where n is the neutral number density, fluctuations may potentially have a significant effect. To explore what might be expected if the assumption of homogeneity is relaxed, we conducted simple numerical experiments based on simulations of streamers in a neutral gas with a radial gradient in the neutral density, assumed to be created, for instance, by a previous spark. We also studied the effects of background electron density from previous discharges. We find that X‐radiation and γ‐radiation are enhanced when the on‐axis air density is reduced by more than ∼25%. Pre‐ionization tends to reduce the streamer field and thereby the production rate of high‐energy electrons; however, the reduction is modest. The simulations suggest that fluctuations in the neutral densities, on the temporal and spacial scales of streamers, may be important for electron acceleration and bremsstrahlung radiation., Key Points Air perturbations significantly increase the velocity of streamer frontsAir perturbations facilitate the emission of X‐rays from streamer dischargesPre‐ionization moderately lowers the maximum energy of electrons and photons

The evolution of near‐surface air temperature is influenced by various dynamical, radiative, and surface‐atmosphere exchange processes whose contributions are still not completely quantified. Applying stepwise multiple linear regression to Coupled Model Intercomparison Project phase 5 (CMIP5) model simulations and focusing on radiation (diagnosed by incoming shortwave and incoming longwave radiation) and land surface conditions (diagnosed by soil moisture and albedo) about 79% of the interannual variability and 99% of the multidecadal trend of monthly mean daily maximum temperature over land can be explained. The linear model captures well the temperature variability in middle‐to‐high latitudes and in regions close to the equator, whereas its explanatory potential is limited in deserts. While radiation is an essential explanatory variable over almost all of the analyzed domain, land surface conditions show a pronounced relation to temperature in some confined regions. These findings highlight that considering local‐to‐regional processes is crucial for correctly assessing interannual temperature variability and future temperature trends., Key Points The used linear regression model explains about 79% of interannual temperature variability and 99% of multidecadal temperature trendRadiation explains on average about 75% to 85% of the total explained variance, while land surface conditions contribute about 15% to 25%Radiation is essential for explaining temperature variability almost everywhere, land surface conditions in some confined regions

Multimodel ensembles are widely analyzed to estimate the range of future regional climate change projections. For an ensemble of climate models, the result is often portrayed by showing maps of the geographical distribution of the multimodel mean results and associated uncertainties represented by model spread at the grid point scale. Here we use a set of CMIP5 models to show that presenting statistics this way results in an overestimation of the projected range leading to physically implausible patterns of change on global but also on regional scales. We point out that similar inconsistencies occur in impact analyses relying on multimodel information extracted using statistics at the regional scale, for example, when a subset of CMIP models is selected to represent regional model spread. Consequently, the risk of unwanted impacts may be overestimated at larger scales as climate change impacts will never be realized as the worst (or best) case everywhere., Key Points The spread in projected climate change is inflated at the global scale when multimodel ensembles are analyzed using grid point statisticsIf the largest regional changes projected by the model ensemble are selected in each region, this is not consistent at the global scaleImpact analyses based on grid point statistics may indicate a risk of unwanted future impacts that are not physically realizable

The tide‐gauge record from the North American East Coast reveals significant accelerations in sea level starting in the late twentieth century. The estimated post‐1990 accelerations range from near zero to ∼0.3 mm yr−2. We find that the observed sea level acceleration is well modeled using several processes: mass change in Greenland and Antarctica as measured by the Gravity Recovery and Climate Experiment satellites; ocean dynamic and steric variability provided by the GECCO2 ocean synthesis; and the inverted barometer effect. However, to achieve this fit requires estimation of an admittance for the dynamical and steric contribution, possibly due to the coarse resolution of this analysis or to simplifications associated with parameterization of bottom friction in the shallow coastal areas. The acceleration from ice loss alone is equivalent to a regional sea level rise in one century of 0.2 m in the north and 0.75 m in the south of this region., Key Points Understanding sea level acceleration requires consideration of multiple spatially varying physical processesRecent acceleration is well modeled using Greenland and Antarctic ice loss and ocean dynamicsAcceleration from ice loss alone translates to regional rise of 0.2–0.75 m in one century, depending on location

Climate models have consistently projected a drying trend in the southwestern United States, aiding speculation of increasing dust storms in this region. Long‐term climatology is essential to documenting the dust trend and its response to climate variability. We have reconstructed long‐term dust climatology in the western United States, based on a comprehensive dust identification method and continuous aerosol observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. We report here direct evidence of rapid intensification of dust storm activity over American deserts in the past decades (1988–2011), in contrast to reported decreasing trends in Asia and Africa. The frequency of windblown dust storms has increased 240% from 1990s to 2000s. This dust trend is associated with large‐scale variations of sea surface temperature in the Pacific Ocean, with the strongest correlation with the Pacific Decadal Oscillation. We further investigate the relationship between dust and Valley fever, a fast‐rising infectious disease caused by inhaling soil‐dwelling fungus (Coccidioides immitis and C. posadasii) in the southwestern United States. The frequency of dust storms is found to be correlated with Valley fever incidences, with a coefficient (r) comparable to or stronger than that with other factors believed to control the disease in two endemic centers (Maricopa and Pima County, Arizona)., Key Points The frequency of locally originated windblown dust storms has increased 240% in 1990‐2011 in the Southwest United StatesThe dust trends are likely driven by large‐scale variations of sea surface temperature in the Pacific OceanThe dust trend is spatially and temporally correlated with incidences of valley fever, an infectious disease caused by soil‐dwelling fungus

Past observations and modeling of Jupiter's thermosphere have, due to their limited resolution, suggested that heat generated by the aurora near the poles results in a smooth thermal gradient away from these aurorae, indicating a quiescent and diffuse flow of energy within the subauroral thermosphere. Here we discuss Very Large Telescope‐Cryogenic High‐Resolution IR Echelle Spectrometer observations that reveal a small‐scale localized cooling of ~200 K within the nonauroral thermosphere. Using Infrared Telescope Facility NSFCam images, this feature is revealed to be quasi‐stable over at least a 15 year period, fixed in magnetic latitude and longitude. The size and shape of this “Great Cold Spot” vary significantly with time, strongly suggesting that it is produced by an aurorally generated weather system: the first direct evidence of a long‐term thermospheric vortex in the solar system. We discuss the implications of this spot, comparing it with short‐term temperature and density variations at Earth., Key Points The detection of a Great Cold Spot in Jupiter's upper atmosphere, which is quasi‐stable over a 15 year periodThe Great Cold Spot is approximately fixed in magnetic latitude and longitude but changes in shape and size on moderate timescalesWe interpret this as direct evidence of the first long‐term thermospheric vortex in the solar system: an aurorally generated weather system

Black carbon (BC) aerosols from incomplete combustion generally warm the climate, but the magnitudes of their various interactions with climate are still uncertain. A key knowledge gap is their role as ice nucleating particles (INPs), enabling ice formation in clouds. Here we assess the global radiative impacts of BC acting as INPs, using simulations with the Community Earth System Model 2 climate model updated to include new laboratory‐based ice nucleation parameterizations. Overall, we find a moderate cooling through changes to stratiform cirrus clouds, counteracting the well‐known net warming from BC's direct scattering and absorption of radiation. Our best estimates indicate that BC INPs generally thin cirrus by indirectly inhibiting the freezing of solution aerosol, with a global net radiative impact of −0.13 ± 0.07 W/m2. Sensitivity tests of BC amounts and ice nucleating efficiencies, and uncertainties in the environment where ice crystals form, show a potential range of impacts from −0.30 to +0.02 W/m2., Key Points Anthropogenic black carbon (BC) thins cirrus clouds by inhibiting homogeneous nucleation, inducing moderate global coolingThe cooling impact saturates at high BC number and nucleating efficiency, due to cirrus thickening via enhanced heterogeneous ice formationBC cooling by cirrus thinning requires colocation of the aerosol with abundant, medium‐thickness homogeneously formed cirrus

Small volcanic eruptions and their effects have recently come into research focus. While large eruptions are known to strongly affect stratospheric temperature, the impacts of smaller eruptions are hard to quantify because their signals are masked by natural variability. Here, we quantify the temperature signals from small volcanic eruptions between 2002 and 2016 using new vertically resolved aerosol data and precise temperature observations from radio occultation. We find characteristic space‐time signals that can be associated with specific eruptions. In the lower stratosphere, robust warming signals are observed, while in the midstratosphere also cooling signals of some eruptions appear. We find that the volcanic contribution to the temperature trend is up to 20%, depending on latitude and altitude. We conclude that detailed knowledge of the vertical structure of volcanic temperature impacts is crucial for comprehensive trend analysis in order to separate natural from anthropogenic temperature changes., Key Points The imprints of minor volcanic eruptions on stratospheric temperature are precisely quantifiedVertically high resolved aerosol and temperature observations facilitate the accurate detection of volcanic signals in space and timeMinor volcanic eruptions clearly affect the short‐term temperature trend in the lower stratosphere

Global mean precipitation changes due to climate change were previously shown to be relatively small and well constrained by the energy budget. However, local precipitation changes can be much more significant. In this paper we propose that for large enough scales, for which the water budget is closed (precipitation [P] roughly equals evaporation [E]), changes in P approach the small global mean value. However, for smaller scales, for which P and E are not necessarily equal and convergence of water vapor still plays a role, changes in P could be much larger due to dynamical contributions. Using 40 years of two reanalysis data sets, 39 Coupled Model Intercomparison Project Phase 5 (CMIP5) models and additional numerical simulations, we identify the scale of transition in the importance of the different terms in the water budget to precipitation to be ~3,500–4,000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change., Key Points The present‐day characteristic scale of the hydrological cycle predicts the spatial scale of precipitation changes under climate changeUsing reanalysis data sets and CMIP5 models, we identify the characteristic scale of the hydrological cycle to be ~3,500–4,000 kmThese results suggest that changes in precipitation on the continental scale could be much larger than the global mean change

The impact of Mars's 2018 Global Dust Storm (GDS) on surface and near‐surface air temperatures was investigated using an assimilation of Mars Climate Sounder observations. Rather than simply resulting in cooling everywhere from solar absorption (average surface radiative flux fell 26 W/m2), the globally averaged result was a 0.9‐K surface warming. These diurnally averaged surface temperature changes had a novel, highly nonuniform spatial structure, with up to 16‐K cooling/19‐K warming. Net warming occurred in low thermal inertia regions, where rapid nighttime radiative cooling was compensated by increased longwave emission and scattering. This caused strong nightside warming, outweighing dayside cooling. The reduced surface‐air temperature gradient closely coupled surface and air temperatures, even causing local dayside air warming. Results show good agreement with Mars Climate Sounder surface temperature retrievals. Comparisons with the 2001 GDS and free‐running simulations show that GDS spatial structure is crucial in determining global surface temperature effects., Key Points Mars's 2018 Global Dust Storm caused a 0.9‐K globally averaged surface warming but with local 16‐K cooling/19‐K warmingThe magnitude of dayside cooling was controlled by atmospheric dust, and nightside warming by surface thermal inertiaThe effects were strongly nonuniform, with high dust loading causing net warming (cooling) over low (high) thermal inertia continents