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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

Gravity waves (GWs) generated by tropical convection are important for the simulation of large‐scale atmospheric circulations, for example, the quasi‐biennial oscillation (QBO), and small‐scale phenomena like clear‐air turbulence. However, the simulation of these waves still poses a challenge due to the inaccurate representation of convection, and the high computational costs of global, cloud‐resolving models. Methods combining models with observations are needed to gain the necessary knowledge on GW generation, propagation, and dissipation so that we may encode this knowledge into fast parameterized physics for global weather and climate simulation or turbulence forecasting. We present a new method suitable for rapid simulation of realistic convective GWs. Here, we associate the profile of latent heating with two parameters: precipitation rate and cloud top height. Full‐physics cloud‐resolving WRF simulations are used to develop a lookup table for converting instantaneous radar precipitation rates and echo top measurements into a high‐resolution, time‐dependent latent heating field. The heating field from these simulations is then used to force an idealized dry version of the WRF model. We validate the method by comparing simulated precipitation rates and cloud tops with scanning radar observations and by comparing the GW field in the idealized simulations to satellite measurements. Our results suggest that including variable cloud top height in the derivation of the latent heating profiles leads to better representation of the GWs compared to using only the precipitation rate. The improvement is especially noticeable with respect to wave amplitudes. This improved representation also affects the forcing of GWs on large‐scale circulation., Key Points Use of an idealized numerical model forced with radar‐derived latent heat profiles to simulate convective gravity waves in the tropicsRelating latent heat to rain rate and echo top height leads to improved representation of tropical GWs compared to satellite observationsApproach could improve prediction of tropical gravity waves for weather forecasting and climate applications

Riparian environments are highly dynamic ecosystems that support biodiversity and numerous services and that are conditioned by anthropogenic activities and climate change. In this work, we propose an integrated methodology that combines different research approaches—field studies and numerical and analytical modeling—in order to calibrate an ecohydrological stochastic model for riparian vegetation. The model yields vegetation biomass statistics and requires hydrological, topographical, and biological data as input. The biological parameters, namely, the carrying capacity and the flood‐related decay rate, are the target of the calibration as they are related to intrinsic features of vegetation and site‐specific environmental conditions. The calibration is here performed for two bars located within the riparian zone of the Cinca River (Spain). According to our results, the flood‐related decay rate has a spatial dependence that reflects the zonation of different plant species over the study site. The carrying capacity depends on the depth of the phreatic surface, and it is adequately described by a right‐skewed curve. The calibrated model well reproduces the actual biogeography of the Cinca riparian zone. The overall percentage absolute difference between the real and the computed biomass amounts to 9.3% and 3.3% for the two bars. The model is further used to predict the future evolution of riparian vegetation in a climate‐change scenario. The results show that the change of hydrological regime forecast by future climate projections may induce dramatic reduction of vegetation biomass and strongly modify the Cinca riparian biogeography., Key Points We combined remote sensing, field data, and numerical and stochastic modeling to study a riparian areaTopography and water level fluctuations condition the long‐term distribution of riparian vegetationSpatial clusters based on the probability of inundation detect areas of homogeneous vegetation

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

Convective clustering, the spatial organization of tropical deep convection, can manifest itself in two ways: through a decrease in the total area covered by convection and/or through a decrease in the number of convective areas. Much of our current understanding of convective clustering comes from simulations in idealized radiative convective equilibrium (RCE) configurations. In these simulations the two forms of convective clustering tend to covary, and their individual effects on the climate are thus hard to disentangle. This study shows that in aquaplanet simulations with more realistic boundary conditions, such as meridional gradients of surface temperature and rotational forces, the two aspects of convective clustering are not equivalent and are associated with different impacts on the large‐scale climate. For instance, reducing the convective area in the equatorial region in the aquaplanet simulations results in broader meridional humidity and rain distributions and in lower tropospheric temperatures throughout the tropics. By contrast, the number of convective regions primarily impacts the zonal variance of humidity‐related quantities in the aquaplanet simulations, as the distribution of convective regions affects the size of the subsidence regions and thereby the moistening influence of convective regions. The aquaplanet simulations confirm many other qualitative results from RCE simulations, such as a reduction of equatorial tropospheric humidity when the area covered by convection diminishes., Key Points The impact of convective clustering on tropical climate depends on both the total convecting area and on the number of convective clustersThe total convective area affects the meridional distribution of water; the number of convective regions affects the zonal variance of waterMany findings from radiative convective equilibrium studies are confirmed in aquaplanet simulations with realistic sea surface temperatures

Cloud and precipitation systems are simulated with a multi‐scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar‐defined Precipitation Features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to produce simulated precipitation features (PFs) from the output of the embedded two‐dimensional (2D) cloud‐resolving models (CRMs) within an MMF. Despite the limitations of 2D CRMs, the simulated population distribution, horizontal and vertical structure of PFs, and the geographical location and local rainfall contribution of mesoscale convective systems (MCSs) are in good agreement with the TRMM observations. However, some model discrepancies are found and can be identified and quantified within the PF distributions. Using model biases in relative population and rainfall contributions, PFs can be characterized into four size categories: small, medium to large, very large, and extremely large. Four different major mechanisms might account for the model biases in each different category: (1) the two‐dimensionality of the CRMs, (2) a positive convection‐wind‐evaporation feedback loop, (3) an artificial dynamic constraint in a bounded CRM domain with cyclic boundaries, and (4) the limited CRM domain size. The second and fourth mechanisms tend to contribute to the excessive tropical precipitation biases commonly found in most MMFs, whereas the other mechanisms reduce rainfall contributions from small and very large PFs. MMF sensitivity experiments with various CRM domain sizes and grid spacings showed that larger domains (higher resolutions) tend to shift PF populations toward larger (smaller) sizes., Key Points Many characteristics of simulated rain features are in reasonable agreement with satellite observationsFour different major mechanisms might account for the rainfall and precipitation feature biases in the modelMedium to large rain features contribute the most to the model tropical precipitation biases

The goal of this study is to understand the mechanisms controlling the isotopic composition of the water vapor near the surface of tropical oceans, at the scale of about a hundred kilometers and a month. In the tropics, it has long been observed that the isotopic compositions of rain and vapor near the surface are more depleted when the precipitation rate is high. This is called the “amount effect.” Previous studies, based on observations or models with parameterized convection, have highlighted the roles of deep convective and mesoscale downdrafts and rain evaporation. But the relative importance of these processes has never been quantified. We hypothesize that it can be quantified using an analytical model constrained by large‐eddy simulations. Results from large‐eddy simulations confirm that the classical amount effect can be simulated only if precipitation rate changes result from changes in the large‐scale circulation. We find that the main process depleting the water vapor compared to the equilibrium with the ocean is the fact that updrafts stem from areas where the water vapor is more enriched. The main process responsible for the amount effect is the fact that when the large‐scale ascent increases, isotopic vertical gradients are steeper, so that updrafts and downdrafts deplete the subcloud layer more efficiently., Key Points The precipitation is more depleted when the precipitation rate is higher only if it is associated with stronger large‐scale ascentUpdrafts are responsible for most of the depletion of the near‐surface water vapor relative to equilibrium with the oceanWith large‐scale ascent, the near‐surface water vapor is more depleted because updrafts export enriched water more efficiently

This study examines the modifications of air‐sea coupling processes by dust‐radiation‐cloud interactions over the North Atlantic Ocean using a high‐resolution coupled atmosphere‐wave‐ocean‐dust (AWOD) regional model. The dust‐induced mechanisms that are responsible for changes of sea surface temperature (SST) and latent and sensible heat fluxes (LHF/SHF) are also examined. Two 3‐month numerical experiments are conducted, and they differ only in the activation and deactivation of dust‐radiation‐cloud interactions. Model results show that the dust significantly reduces surface downward radiation fluxes (SDRF) over the ocean with the maximum change of 20–30 W m−2. Over the dust plume region, the dust effect creates a low‐pressure anomaly and a cyclonic circulation anomaly, which drives a positive wind stress curl anomaly, thereby reducing sea surface height and mixed layer depth. However, the SST change by dust, ranging from −0.5 to 0.5 K, has a great spatial variation which differs from the dust plume shape. Dust cools SST around the West African coast, except under the maximum dust plume ridge, and extends westward asymmetrically along the northern and southern edges of the dust plume. Dust unexpectedly warms SST over a large area of the western tropical North Atlantic and north of the dust plume. These SST changes are controlled by different mechanisms. Unlike the SST change pattern, the LHF and SHF changes are mostly reduced underneath the dust plume region, though they are different in detail due to different dominant factors, and increased south of the dust plume over the tropic., Key Points Dust‐radiation‐cloud interactions mainly cool SST offshore the North Africa and warm SST over the southwestern dust plume regionDust reduces upward LHF and SHF underneath the dust plume region and increases the values south of the dust plumeChanges of SST/LHF/SHF by dust are not only attributed to the dust‐induced SDRF reduction but also changes of WSC and upper‐ocean dynamic

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

Studies of the Madden‐Julian Oscillation (MJO) have progressed considerably during the past decades in observations, numerical modeling, and theoretical understanding. Many theoretical attempts have been made to identify the most essential processes responsible for the existence of the MJO. Criteria are proposed to separate a hypothesis from a theory (based on the first principles with quantitative and testable assumptions, able to predict quantitatively the fundamental scales and eastward propagation of the MJO). Four MJO theories are selected to be summarized and compared in this article: the skeleton theory, moisture‐mode theory, gravity‐wave theory, and trio‐interaction theory of the MJO. These four MJO theories are distinct from each other in their key assumptions, parameterized processes, and, particularly, selection mechanisms for the zonal spatial scale, time scale, and eastward propagation of the MJO. The comparison of the four theories and more recent development in MJO dynamical approaches lead to a realization that theoretical thinking of the MJO is diverse and understanding of MJO dynamics needs to be further advanced., Key Points A theory for the Madden‐Julian Oscillation (MJO) must explain its most fundamental features of temporal‐spatial scales and eastward propagationFour theories provide contrasting explanations for the MJO based on different assumptions and treatment of physical processesThese MJO theories represent a general progress toward understanding the MJO and also the need to further advance such understanding

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

Two successive mesospheric bores were observed over northeastern Canada on 13 July 2018 in high‐resolution imaging and Rayleigh lidar profiling of polar mesospheric clouds (PMCs) performed aboard the PMC Turbo long‐duration balloon experiment. Four wide field‐of‐view cameras spanning an area of ~75 × 150 km at PMC altitudes captured the two evolutions occurring over ~2 hr and resolved bore and associated instability features as small as ~100 m. The Rayleigh lidar provided PMC backscatter profiling that revealed vertical displacements, evolving brightness distributions, evidence of instability character and depths, and insights into bore formation, ducting, and dissipation. Both bores exhibited variable structure along their phases, suggesting variable gravity wave (GW) source and bore propagation conditions. Both bores also exhibited small‐scale instability dynamics at their leading and trailing edges. Those at the leading edges comprised apparent Kelvin‐Helmholtz instabilities that were advected downward and rearward beneath the bore descending phases extending into an apparently intensified shear layer. Instabilities at the trailing edges exhibited alignments approximately orthogonal to the bore phases that resembled those seen to accompany GW breaking or intrusions arising in high‐resolution modeling of GW instability dynamics. Collectively, PMC Turbo bore imaging and lidar profiling enabled enhanced definition of bore dynamics relative to what has been possible by previous ground‐based observations, and a potential to guide new, three‐dimensional modeling of bore dynamics. The observed bore evolutions suggest potentially important roles for bores in the deposition of energy and momentum transported into the mesosphere and to higher altitudes by high‐frequency GWs achieving large amplitudes., Key Points Mesospheric bores are dramatic events that dominate local instability dynamics accompanying their passageMesospheric bores can exhibit significant variability in their evolution in time and along their phasesMesospheric bores can exhibit significant instability dynamics at smaller spatial scales at their leading and trailing edges

Spaceborne radars offer a unique three‐dimensional view of the atmospheric components of the Earth's hydrological cycle. Existing and planned spaceborne radar missions provide cloud and precipitation information over the oceans and land difficult to access in remote areas. A careful look into their measurement capabilities indicates considerable gaps that hinder our ability to detect and probe key cloud and precipitation processes. The international community is currently debating how the next generation of spaceborne radars shall enhance current capabilities and address remaining gaps. Part of the discussion is focused on how to best take advantage of recent advancements in radar and space platform technologies while addressing outstanding limitations. First, the observing capabilities and measurement highlights of existing and planned spaceborne radar missions including TRMM, CloudSat, GPM, RainCube, and EarthCARE are reviewed. Then, the limitations of current spaceborne observing systems, with respect to observations of low‐level clouds, midlatitude and high‐latitude precipitation, and convective motions, are thoroughly analyzed. Finally, the review proposes potential solutions and future research avenues to be explored. Promising paths forward include collecting observations across a gamut of frequency bands tailored to specific scientific objectives, collecting observations using mixtures of pulse lengths to overcome trade‐offs in sensitivity and resolution, and flying constellations of miniaturized radars to capture rapidly evolving weather phenomena. This work aims to increase the awareness about existing limitations and gaps in spaceborne radar measurements and to increase the level of engagement of the international community in the discussions for the next generation of spaceborne radar systems., Key Points Current spaceborne radars offer a unique three‐dimensional view of the atmospheric component of the Earth's hydrological cycleCurrent spaceborne radar have limitations with respect to observations of low‐level clouds, midlatitude/high‐latitude precipitation, and convectionRecent advances in radar technology will enable filling current science gaps

Following the emergence of a novel coronavirus in Wuhan, China instituted shutdown measures starting in late January and continuing into February 2020 to arrest the spread of disease. This resulted in a sharp economic contraction unparalleled in recent Chinese history. Satellite retrievals show that nitrogen dioxide pollution declined by an unprecedented amount (~50% regionally) from its expected unperturbed value, but regional‐scale column aerosol loadings and cloud microphysical properties were not detectably affected. The disparate impact is tied to differential economic impacts of the shutdown, in which transportation, a disproportionate source of nitrogen oxide emissions, underwent drastic declines (~90% reductions in passenger traffic), whereas industry and power generation, responsible for >90% of particulate emissions, were relatively less affected (~20% reductions in electricity and thermal power generation). A combination of anomalously warm and humid meteorological conditions and complex chemical interactions further decreased nitrogen dioxide concentrations but likely enhanced secondary aerosol formation., Key Points Rapid economic collapse in February 2020 due to the COVID‐19 pandemic and partial recovery in March 2020 are unique in recent Chinese historyRegional decline in NO2 pollution is unprecedented in the satellite record, but no change in aerosol or cloud properties is detectedDifferent economic impacts by sector, meteorology, and complex chemical interactions help explain differences in NOx and aerosol response

Various transboundary river basins are facing increased pressure on water resources in near future. However, little is known ab out the future drivers globally, namely, changes in natural local runoff and natural inflows from upstream parts of a basin, as well as local and upstream water consumption. Here we use an ensemble of four global hydrological models forced by five global climate models and the latest greenhouse‐gas concentration (RCP) and socioeconomic pathway (SSP) scenarios to assess the impact of these drivers on transboundary water stress in the past and future. Our results show that population under water stress is expected to increase by 50% under a low population growth and emissions scenario (SSP1‐RCP2.6) and double under a high population growth and emission scenario (SSP3‐RCP6.0), compared to the year 2010. As changes in water availability have a smaller effect when water is not yet scarce, changes in water stress globally are dominated by local water consumption—managing local demand is thus necessary in order to avoid future stress. Focusing then on the role of upstream changes, we identified upstream availability (i.e., less natural runoff or increased water consumption) as the dominant driver of changes in net water availability in most downstream areas. Moreover, an increased number of people will be living in areas dependent on upstream originating water in 2050. International water treaties and management will therefore have an increasingly crucial role in these hot spot regions to ensure fair management of transboundary water resources., Key Points Water stress will mostly intensify in areas already under stress in all future scenarios for most transboundary river basinsChanges in water stress are dominated by local water consumption—managing local demand is thus a key strategy to alleviate future stressLess natural runoff or increased water consumption in upstream areas is the dominant driver of changes in downstream net water availability

The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) “Indicators” Tiger Team collaboration between NASA‐supported scientists and civil society stakeholders aimed to develop satellite‐derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge., Key Points The NASA Health and Air Quality Applied Science Team “Indicators” Tiger Team developed satellite‐based air quality and climate indicatorsParticipatory knowledge production can lead to more useful information for stakeholders but requires continuous engagement and flexibilityGround measurements are still needed, and sustained collaboration between the researchers and stakeholders over time remains a challenge

Vb cyclones typically emerge in the Western Mediterranean and propagate to the Northeast into Central Europe. This paper explores the temporal characteristics of Vb cyclone occurrence based on cyclone tracks identified at the atmospheric levels of Z700 and sea level pressure, using JRA‐55 reanalysis data for the period 1959–2015. The risk of Vb occurrence was significantly high in the 1960s and has remained at a lower level since then. Vb cyclones do not occur fully randomly according to a Poisson point process. Eleven well‐separated and distinct clusters as well as 11 hiatus periods are identified, with average occurrence rates of 21.5 and 5.2 yrea−1, respectively. During the event of Vb, the large‐scale atmospheric circulation is changed into a state favoring the development of successive Vb cyclones. Clustering is very prominent in the case of Genoan Vb cyclones in summer as well as those Vb cyclones developing over the Iberian Peninsula or the North African Coast in winter. Superposition of the polar and the subtropical jet stream over the Western Mediterranean is identified as a main feature at the onset of Vb cyclones. Vb cyclone occurrence appears to be synchronized with the Northern Atlantic Oscillation (NAO; at Z500) and Arctic Oscillation (AO; at Z1000). Clusters have occurred when both NAO and AO were negative. This relation applies to Western Mediterranean cyclones not following a Vb track as well, however to a much weaker extent. In contrast, Vb cyclone frequency was particularly low from 1988 to 1997 during a sustained positive phase of both NAO and AO., Key Points In the past 50 years, the frequency of Vb cyclones was high in the 1960s and lower since thenVb cyclones were strongly synchronized with NAO and AO; high frequency clusters occurred when NAO and AO were negativeThe coupling of the polar and the subtropical jet stream over the Western Mediterranean is a driving mechanism of the onset of Vb cyclones

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)

The ability of FLake, WRF‐Lake, and CoLM‐Lake models in simulating the thermal features of Lake Nam Co in Central Tibetan Plateau has been evaluated in this study. All the three models with default settings exhibited distinct errors in the simulated vertical temperature profile. Then model calibration was conducted by adjusting three (four) key parameters within FLake and CoLM‐Lake (WRF‐Lake) in a series of sensitive experiments. Results showed that each model's performance is sensitive to the key parameters and becomes much better when adjusting all the key parameters relative to tuning single parameter. Overall, setting the temperature of maximum water density to 1.1 °C instead of 4 °C in the three models consistently leads to improved vertical thermal structure simulation during cold seasons; reducing the light extinction coefficient in FLake results in much deeper mixed layer and warmer thermocline during warm seasons in better agreement with the observation. The vertical thermal structure can be clearly improved by decreasing the light extinction coefficient and increasing the turbulent mixing in WRF‐Lake and CoLM‐Lake during warm seasons. Meanwhile, the modeled water temperature profile in warm seasons can be significantly improved by further replacing the constant surface roughness lengths by a parameterized scheme in WRF‐Lake. Further intercomparison indicates that among the three calibrated models, FLake (WRF‐Lake) performs the best to simulate the temporal evolution and intensity of temperature in the layers shallower (deeper) than 10 m, while WRF‐Lake is the best at simulating the amplitude and pattern of the temperature variability at all depths., Key Points The performance of three one‐dimensional lake models in simulating the thermal structure of Nam Co Lake is evaluated and improvedKey processes related to the simulated thermal regime of alpine lakes on the Tibetan Plateau are indicated and revealed

In the first 20 orbits of the Juno spacecraft around Jupiter, we have identified a variety of wave‐like features in images made by its public‐outreach camera, JunoCam. Because of Juno's unprecedented and repeated proximity to Jupiter's cloud tops during its close approaches, JunoCam has detected more wave structures than any previous surveys. Most of the waves appear in long wave packets, oriented east‐west and populated by narrow wave crests. Spacing between crests were measured as small as ~30 km, shorter than any previously measured. Some waves are associated with atmospheric features, but others are not ostensibly associated with any visible cloud phenomena and thus may be generated by dynamical forcing below the visible cloud tops. Some waves also appear to be converging, and others appear to be overlapping, possibly at different atmospheric levels. Another type of wave has a series of fronts that appear to be radiating outward from the center of a cyclone. Most of these waves appear within 5° of latitude from the equator, but we have detected waves covering planetocentric latitudes between 20°S and 45°N. The great majority of the waves appear in regions associated with prograde motions of the mean zonal flow. Juno was unable to measure the velocity of wave features to diagnose the wave types due to its close and rapid flybys. However, both by our own upper limits on wave motions and by analogy with previous measurements, we expect that the waves JunoCam detected near the equator are inertia‐gravity waves., Key Points In the first 20 orbits of the Juno mission, over 150 waves and wave‐like features have been detected by the JunoCam public‐outreach cameraA wide variety of wave morphologies were detected over a wide latitude range, but the great majority were found near Jupiter's equatorBy analogy with previous studies of waves in Jupiter's atmosphere, most of the waves detected are likely to be inertia‐gravity waves

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.

The development of a unified similarity scaling has so far failed over complex surfaces, as scaling studies show large deviations from the empirical formulations developed over flat and horizontally homogeneous terrain as well as large deviations between the different complex terrain data sets. However, a recent study of turbulence anisotropy for flat and horizontally homogeneous terrain has shown that separating the data according to the limiting states of anisotropy (isotropic, two‐component axisymmetric and one‐component turbulence) improves near‐surface scaling. In this paper we explore whether this finding can be extended to turbulence over inclined and horizontally heterogeneous surfaces by examining near‐surface scaling for 12 different data sets obtained over terrain ranging from flat to mountainous. Although these data sets show large deviations in scaling when all anisotropy types are examined together, the separation according to the limiting states of anisotropy significantly improves the collapse of data onto common scaling relations, indicating the possibility of a unified framework for turbulence scaling. A measure of turbulence complexity is developed, and the causes for the breakdown of scaling and the physical mechanisms behind the turbulence complexity encountered over complex terrain are identified and shown to be related to the distance to the isotropic state, prevalence of directional shear with height in mountainous terrain, and the deviations from isotropy in the inertial subrange., Key Points A pathway toward a unified theory of near‐surface atmospheric turbulence is providedThe separation according to the limiting states of anisotropy significantly improves the collapse of data onto common scaling relationsPhysical processes responsible for turbulence complexity are identified

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems., Key Points Airborne lidar can be used to inform about degradation‐driven changes in structure to vegetation modelsForest degradation typically depletes evapotranspiration and productivity and increases flammabilityExtreme droughts reduce functional differences between degraded and intact tropical forests

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

Estimates of high‐resolution greenhouse gas (GHG) emissions have become a critical component of climate change research and an aid to decision makers considering GHG mitigation opportunities. The “Vulcan Project” is an effort to estimate bottom‐up carbon dioxide emissions from fossil fuel combustion and cement production (FFCO2) for the U.S. landscape at space and time scales that satisfy both scientific and policy needs. Here, we report on the Vulcan version 3.0 which quantifies emissions at a resolution of 1 km2/hr for the 2010–2015 time period. We estimate 2011 FFCO2 emissions of 1,589.9 TgC with a 95% confidence interval of 1,367/1,853 TgC (−14.0%/+16.6%), implying a one‐sigma uncertainty of ~ ±8%. Per capita emissions are larger in states dominated by electricity production and industrial activity and smaller where onroad and building emissions dominate. The U.S. FFCO2 emissions center of mass (CoM) is located in the state of Missouri with mean seasonality that moves on a near‐elliptical NE/SW path. Comparison to ODIAC, a global gridded FFCO2 emissions estimate, shows large total emissions differences (100.4 TgC for year 2011), a spatial correlation of 0.68 (R2), and a mean absolute relative difference at the 1 km2 scale of 104.3%. The Vulcan data product offers a high‐resolution estimate of FFCO2 emissions in every U.S. city, obviating costly development of self‐reported urban inventories. The Vulcan v3.0 annual gridded emissions data product can be downloaded from the Oak Ridge National Laboratory Distributed Active Archive Center (Gurney, Liang, et al., 2019, https://doi.org/10.3334/ORNLDAAC/1741)., Key Points Vulcan v3.0 is the first U.S.‐wide bottom‐up FFCO2 emissions data product at 1 km2/hourly for multiple yearsComparison to satellite‐driven global FFCO2 emissions shows large spatial differences with a mean gridcell absolute relative difference of 104.3%Vulcan can provide an immediate Scope 1 FFCO2 inventory for every city in the United States saving city time and resources

In 2018 and 2019, heatwaves set all‐time temperature records around the world and caused adverse effects on human health, agriculture, natural ecosystems, and infrastructure. Often, severe impacts relate to the joint spatial and temporal extent of the heatwaves, but most research so far focuses either on spatial or temporal attributes of heatwaves. Furthermore, sensitivity of heatwaves characteristics to the choice of the heatwave thresholds in a warming climate are rarely discussed. Here, we analyze the largest spatiotemporal moderate heatwaves—that is, three‐dimensional (space‐time) clusters of hot days—in simulations of global climate models. We use three different hazard thresholds to define a hot day: fixed thresholds (time‐invariant climatological thresholds), seasonally moving thresholds based on changes in the summer means, and fully moving thresholds (hot days defined relative to the future climatology). We find a substantial increase of spatiotemporally contiguous moderate heatwaves with global warming using fixed thresholds, whereas changes for the other two hazard thresholds are much less pronounced. In particular, no or very little changes in the overall magnitude, spatial extent, and duration are detected when heatwaves are defined relative to the future climatology using a temporally fully moving threshold. This suggests a dominant contribution of thermodynamic compared to dynamic effects in global climate model simulations. The similarity between seasonally moving and fully moving thresholds indicates that seasonal mean warming alone can explain large parts of the warming of extremes. The strong sensitivity of simulated future heatwaves to hazard thresholds should be considered in the projections of potential future heat‐related impacts. Plain Language Summary Heatwaves, such as the worldwide events that occurred in 2018 and 2019, can be associated with substantial impacts on humans, ecosystems, and the economy. These impacts are often caused by the joint temporal and spatial dimensions of the events. However, these properties of the heatwaves are rarely studied jointly. Furthermore, heatwaves are often defined based on exceedance above a fixed threshold, which might overestimate future heatwave impacts in a warming climate. Therefore, we compute here moderate heatwaves considering their true time‐space structure based on three hazard thresholds. We then investigate future changes of these moderate heatwaves for different warming levels. We detect a strong increase in the overall magnitude, spatial extent, and duration of heatwaves if we use fixed hazard thresholds. In the case with seasonally and fully moving hazard thresholds, we find no or only little changes of heatwave characteristics. This strong threshold sensitivity should be considered when estimating impacts associated with future heatwaves in a warming climate., Journal of Geophysical Research: Atmospheres, 125 (9)

Human activities are elevating atmospheric carbon dioxide concentrations to levels unprecedented in human history. The majority of anticipated impacts of anthropogenic CO2 emissions are mediated by climate warming. Recent experimental studies in the fields of indoor air quality and cognitive psychology and neuroscience, however, have revealed significant direct effects of indoor CO2 levels on cognitive function. Here, we shed light on this connection and estimate the impact of continued fossil fuel emissions on human cognition. We conclude that indoor CO2 levels may indeed reach levels harmful to cognition by the end of this century, and the best way to prevent this hidden consequence of climate change is to reduce fossil fuel emissions. Finally, we offer recommendations for a broad, interdisciplinary approach to improving such understanding and prediction., Key Points Atmospheric carbon dioxide concentrations are reaching levels never experienced by Homo sapiens Recent experiments have linked high indoor carbon dioxide concentrations to reduced cognitive functionOur models predict that future carbon emissions will increase indoor concentrations to levels harmful to human cognition

To quantitatively determine the effect of Xiluodu Reservoir on the temperature of the surrounding mountains, the temperature differences between various locations and the reservoir were calculated based on Landsat 8 thermal infrared sensor (TIRS) data. Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factors, and the most significant grid size used to explore the effect of reservoir on the surrounding mountains was determined by spatial analysis and partial correlation analysis. The effect of the Xiluodu Reservoir on the surrounding mountains' temperature was then quantitatively studied while accounting for the effect of water surface width on temperature. The results are summarized as follows. The most significant grid size for determining the influence of Xiluodu Reservoir on the surrounding mountains' temperature is 90 m. The effect range threshold of the entire reservoir on the temperature of the surrounding mountains is approximately 600 m, and the partial correlation coefficient in each buffer area decreases gradually with increasing distance from the reservoir. The effect threshold of the reservoir on the temperature of the surrounding mountains is approximately 1,500 m in the head area with a water surface width approximately 1,000 m, but it is negligible in the tributary area where the width is approximately 60 m., Key Points Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factorsTo overcome the scale‐dependence of LST, the most significant grid size was determined by spatial analysis and partial correlation analysisStudy the effect of reservoir on the surrounding mountains' temperature while accounting for the effect of water surface width

Terrestrial gamma ray flashes (TGFs) are sub‐millisecond bursts of high energetic gamma radiation associated with intracloud flashes in thunderstorms. In this paper we use the simultaneity of lightning detections by World Wide Lightning Location Network to find TGFs in the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) data that are too faint to be identified by standard search algorithms. A similar approach has been used in an earlier paper, but here we expand the data set to include all years of RHESSI + World Wide Lightning Location Network data and show that there is a population of observationally weak TGFs all the way down to 0.22 of the RHESSI detection threshold (three counts in the detector). One should note that the majority of these are “normal” TGFs that are produced further away from the subsatellite point (and experience a 1/r 2 effect) or produced at higher latitudes with a lower tropoause and thus experience increased atmospheric attenuation. This supports the idea that the TGF production rate is higher than currently reported. We also show that compared to lightning flashes, TGFs are more partial to ocean and coastal regions than over land., Key Points We show that there is a fluence distribution of TGFs down to 0.22 of the detection threshold, and we do not see a cutoff in the RHESSI TGF distributionWe find that there are six times as many TGFs inside of RHESSI's field of view, than can be identified by current search algorithmsWe find that observationally weak TGFs largely originate at larger radial distances and higher latitudes from the subsatellite point

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., 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

Emission inventories of anthropogenic transition metals, which contribute to aerosol oxidative potential (OP), in Asia (Δx = 0.25°, monthly, 2000–2008) and Japan (Δx = 2 km, hourly, mainly 2012) were developed, based on bottom‐up inventories of particulate matters and metal profiles in a speciation database for particulate matters. The new inventories are named Transition Metal Inventory (TMI)‐Asia v1.0 and TMI‐Japan v1.0, respectively. It includes 10 transition metals in PM2.5 and PM10, which contributed to OP based on reagent experiments, namely, Cu, Mn, Co, V, Ni, Pb, Fe, Zn, Cd, and Cr. The contributions of sectors in the transition metals emission in Japan were also investigated. Road brakes and iron‐steel industry are primary sources, followed by other metal industry, navigation, incineration, power plants, and railway. In order to validate the emission inventory, eight elements such as Cu, Mn, V, Ni, Pb, Fe, Zn, and Cr in anthropogenic dust and those in mineral dust were simulated over East Asia and Japan with Δx = 30 km and Δx = 5 km domains, respectively, and compared against the nation‐wide seasonal observations of PM2.5 elements in Japan and the long‐term continuous observations of total suspended particles (TSPs) at Yonago, Japan in 2013. Most of the simulated elements generally agreed with the observations, while Cu and Pb were significantly overestimated. This is the first comprehensive study on the development and evaluation of emission inventory of OP active elements, but further improvement is needed., Key Points Emission inventories of transition metals, which contribute to aerosol oxidative potential (OP), in Asia and Japan were developedMost of simulated elements (Mn, V, Ni, Fe, Zn, and Cr) agreed with observation, while Cu and Pb were significantly overestimatedRoad brakes and iron‐steel industry are primary sources, followed by metal industry, navigation, incineration, power plants, and railway

This study evaluates the impact of assimilating moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data using different data assimilation (DA) methods on dust analyses and forecasts over North Africa and tropical North Atlantic. To do so, seven experiments are conducted using the Weather Research and Forecasting dust model and the Gridpoint Statistical Interpolation analysis system. Six of these experiments differ in whether or not AOD observations are assimilated and the DA method used, the latter of which includes the three‐dimensional variational (3D‐Var), ensemble square root filter (EnSRF), and hybrid methods. The seventh experiment, which allows us to assess the impact of assimilating deep blue AOD data, assimilates only dark target AOD data using the hybrid method. The assimilation of MODIS AOD data clearly improves AOD analyses and forecasts up to 48 hr in length. Results also show that assimilating deep blue data has a primarily positive effect on AOD analyses and forecasts over and downstream of the major North African source regions. Without assimilating deep blue data (assimilating dark target only), AOD assimilation only improves AOD forecasts for up to 30 hr. Of the three DA methods examined, the hybrid and EnSRF methods produce better AOD analyses and forecasts than the 3D‐Var method does. Despite the clear benefit of AOD assimilation for AOD analyses and forecasts, the lack of information regarding the vertical distribution of aerosols in AOD data means that AOD assimilation has very little positive effect on analyzed or forecasted vertical profiles of backscatter., Key Points Assimilating MODIS AOD data improves AOD forecasts up to 48 hr, but the improvement can last for only 30 hr when deep blue data are excludedThe hybrid and EnSRF methods can produce better AOD analyses and forecasts than the 3D‐Var method doesAssimilation of MODIS AOD data has very little impact on analyses and/or forecasts of aerosol backscatter profile

Trade‐wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as flowers, fish, gravel, and sugar. We show that these four patterns can be identified objectively from satellite observations by analyzing the spatial distribution of infrared brightness temperatures. By applying this analysis to 19 years of data, we examine relationships between cloud patterns and large‐scale environmental conditions. This investigation reveals that on daily and interannual timescales, the near‐surface wind speed and the strength of the lower‐tropospheric stability discriminate the occurrence of the different organization patterns. These results, combined with the tight relationship between cloud patterns, low‐level cloud amount, and cloud‐radiative effects, suggest that the mesoscale organization of shallow clouds might change under global warming. The role of shallow convective organization in determining low‐cloud feedback should thus be investigated., Key Points Prominent mesoscale patterns of shallow convection are identified from satellite observationsMesoscale patterns exhibit strong relationships with surface wind speed and lower‐tropospheric stabilityOwing to their differences in low‐cloud fraction, mesoscale patterns exert different impacts on the top‐of‐atmosphere radiation budget

Bulk‐surface partitioning of surface active species affects both cloud droplet activation by aerosol particles and heterogeneous atmospheric chemistry. Various approaches are given in the literature to capture this effect in atmospheric models. Here we present a simple, yet physically self‐contained, monolayer model for prediction of both composition and thickness of the surface layer of an aqueous droplet. The monolayer surface model is based on assuming a finite surface layer and mass balance of all species within the droplet. Model predictions are presented for binary and ternary aqueous surfactant model systems and compared to both experimental and model data from the literature and predictions using a common Gibbsian model approach. Deviations from Gibbsian surface thermodynamics due to volume constraints imposed by the finite monolayer lead to stronger predicted surface tension reduction at smaller droplet sizes with the monolayer model. Process dynamics of the presented monolayer model are also contrasted to other recently proposed approaches to treating surface partitioning in droplets, with different underlying assumptions., Key Points We present a physically consistent model for predicting composition and thickness of a surface monolayer on aqueous solution dropletsModel predictions are presented for binary and ternary water‐surfactant‐salt systems and compared to a Gibbsian model and experimental dataThe monolayer model predicts lower surface tensions than the Gibbsian model for droplet sizes relevant for atmospheric cloud activation

The biological carbon pump exports carbon fixed by photosynthesis out of the surface ocean and transfers it to the deep, mostly in the form of sinking particles. Despite the importance of the pump in regulating the air‐sea CO2 balance, the magnitude of global carbon export remains unclear, as do its controlling mechanisms. A possible sinking flux of carbon to the mesopelagic zone may be via the mixed‐layer pump: a seasonal net detrainment of particulate organic carbon (POC)‐rich surface waters, caused by sequential deepening and shoaling of the mixed layer. In this study, we present a full year of daily small‐particle POC concentrations derived from glider optical backscatter data, to study export variability at the Porcupine Abyssal Plain (PAP) sustained observatory in the Northeast Atlantic. We observe a strong seasonality in small‐particle transfer efficiency, with a maximum in winter and early spring. By calculating daily POC export driven by mixed‐layer variations, we find that the mixed‐layer pump supplies an annual flux of at least 3.0 ± 0.9 g POC·m−2·year−1 to the mesopelagic zone, contributing between 5% and 25% of the total annual export flux and likely contributing to closing a gap in the mesopelagic carbon budget found by other studies. These are, to our best knowledge, the first high‐frequency observations of export variability over the course of a full year. Our results support the deployment of bio‐optical sensors on gliders to improve our understanding of the ocean carbon cycle on temporal scales from daily to annual., Key Points Gliders captured a full annual cycle of high‐frequency POC variability over the upper mesopelagic zoneSmall‐particle transfer efficiency displayed a strong seasonality, peaking in winter and early springThe data indicate a significant annual carbon supply to the mesopelagic zone by small particles through the mixed‐layer pump

Understanding the geographic distribution of mosquito‐borne disease and mapping disease risk are important for prevention and control efforts. Mosquito‐borne viruses (arboviruses), such as West Nile virus (WNV), are highly dependent on environmental conditions. Therefore, the use of environmental data can help in making spatial predictions of disease distribution. We used geocoded human case data for 2004–2017 and population‐weighted control points in combination with multiple geospatial environmental data sets to assess the environmental drivers of WNV cases and to map relative infection risk in South Dakota, USA. We compared the effectiveness of (1) land cover and physiography data, (2) climate data, and (3) spectral data for mapping the risk of WNV in South Dakota. A final model combining all data sets was used to predict spatial patterns of disease transmission and characterize the associations between environmental factors and WNV risk. We used a boosted regression tree model to identify the most important variables driving WNV risk and generated risk maps by applying this model across the entire state. We found that combining multiple sources of environmental data resulted in the most accurate predictions. Elevation, late‐season humidity, and early‐season surface moisture were the most important predictors of disease distribution. Indices that quantified interannual variability of climatic conditions and land surface moisture were better predictors than interannual means. We suggest that combining measures of interannual environmental variability with static land cover and physiography variables can help to improve spatial predictions of arbovirus transmission risk., Key Points Integrating multiple types of geospatial data improves risk maps for West Nile virus transmissionElevation, land cover, soils, summer climate, and remotely sensed spring land surface moisture were associated with West Nile virus casesIndices measuring interannual variability of climate and land surface moisture were important predictors of West Nile virus risk

While the impact of climate on regional geopolitical stability and large‐scale conflict has garnered increased visibility in recent years, the effects of climate variability on interpersonal violent crime have received only limited scientific attention. Though earlier studies have established a modest correlation between temperature and violent crime, the underlying seasonality in both variables was often not controlled for and spatial heterogeneity of the statistical relationships has largely been overlooked. Here a method of spatial aggregation is applied to the United States, enabling a systematic investigation into the observed relationships between large‐scale climate variability and regionally aggregated crime rates. This novel approach allows for differentiation between the effects of two previously proposed mechanisms linking climate and violent crime, the Routine Activities Theory and Temperature‐Aggression Hypothesis. Results indicate large and statistically significant positive correlations between the interannual variability of wintertime air temperature and both violent and property crime rates, with negligible correlations emerging from summertime data. Results strongly support the Routine Activities Theory linking climate and violent crime, with climate variability explaining well over a third of the variance of wintertime violent crime in several broad regions of the United States. Finally, results motivate the development of observationally constrained empirical models and their potential application to seasonal and potentially longer‐term forecasts., Key Points The observed covariability between climate and crime rates was analyzed; regional and monthly averaging is critical for climate signal detectionInterannual regional violent crime rates are influenced by climate variability; strongest correlations exist with wintertime temperaturesFindings support Routine Activities Theory as the primary causal mechanism of this relationship linking climate and violent crime

The direct radiative forcing of black carbon aerosol (BC) on the Earth system remains unsettled, largely due to the uncertainty with physical properties of BC throughout their lifecycle. Here we show that ambient chamber measurements of BC properties provide a novel constraint on the crude BC aging representation in climate models. Observational evidence for significant absorption enhancement of BC can be reproduced when the aging processes in the four‐mode version of the Modal Aerosol Module (MAM4) aerosol scheme in the Community Atmosphere Model version 5 are calibrated by the recent in situ chamber measurements. An observation‐based scaling method is developed in the aging timescale calculation to alleviate the influence of biases in the simulated model chemical composition. Model sensitivity simulations suggest that the different monolayer settings in the BC aging parameterization of MAM4 can cause as large as 26% and 24% differences in BC burden and radiative forcing, respectively. We also find that an increase in coating materials (e.g., sulfate and secondary organic aerosols) reduces BC lifetime by increasing the hygroscopicity of the mixture but enhances its absorption, resulting in a net increase in BC direct radiative forcing. Our results suggest that accurate simulations of BC aging processes as well as other aerosol species are equally important in reducing the uncertainty of BC forcing estimation., Key Points Atmospheric black carbon aging processes in CAM5 are constrained by chamber experimentsThe calibrated model shows that coating results in net enhancement in BC forcing in spite of a reduction in BC lifetimeModeled BC direct radiative forcing varies up to 26% due to the uncertainties in BC aging parameterization and coating aerosol mass

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

This research contrasts the environmental conditions, meteorological drivers, and air quality impacts of human‐ and lightning‐ignited wildfires in the southeastern and western United States, the two continental U.S. regions with the most wildfire burn area. We use the Fire Program Analysis Wildfire Occurrence Data (FPA FOD) to determine wildfire abundance and ignition sources between 1992 and 2015. We investigate specific ecoregions within these two U.S. regions and find that in the majority of ecoregions, annual lightning‐ and human‐ignited wildfire burn area have similar relationships with key meteorological parameters. We investigate the fuel moisture values where wildfires occur segregated by ignition type and show that within a given ecoregion, the differences in median fuel moisture between ignition types are generally smaller than the differences between ecoregions. Our results suggest that annual wildfire burn area for human‐ and lightning‐ignited wildfires within a given ecoregion are modulated by environmental conditions, and climate change may similarly impact wildfires of both ignition types. Finally, we estimate fine particulate matter emissions for Fire Program Analysis Wildfire Occurrence Data wildfires using the Fire INventory from NCAR model framework. We show that emissions of fine particulate matter from human‐ignited wildfires is significant and of a similar total magnitude between the west and southeastern United States. Additionally, the west and southeast have a similar number of wildfires associated with National Weather Service air quality smoke forecasts., Key Points Across U.S. ecoregions, annual human‐ and lightning‐ignited wildfire burn areas are similarly correlated with environmental conditionsClimate‐driven changes in temperature, precipitation, and humidity will likely impact both human‐ and lightning‐ignited wildfires similarlyThe total mass of particulate matter emissions from human‐ignited wildfires is similar in the west and southeastern United States

We have implemented a parameterization for forming ice in large‐scale cirrus clouds that accounts for the changes in updrafts associated with a spectrum of waves acting within each time step in the model. This allows us to account for the frequency of homogeneous and heterogeneous freezing events that occur within each time step of the model and helps to determine more realistic ice number concentrations as well as changes to ice number concentrations. The model is able to fit observations of ice number at the lowest temperatures in the tropical tropopause but is still somewhat high in tropical latitudes with temperatures between 195°K and 215°K. The climate forcings associated with different representations of heterogeneous ice nuclei (IN or INPs) are primarily negative unless large additions of IN are made, such as when we assumed that all aircraft soot acts as an IN. However, they can be close to zero if it is assumed that all background dust can act as an INP irrespective of how much sulfate is deposited on these particles. Our best estimate for the forcing of anthropogenic aircraft soot in this model is −0.2 ± 0.06 W/m2, while that from anthropogenic fossil/biofuel soot is −0.093 ± 0.033 W/m2. Natural and anthropogenic open biomass burning leads to a net forcing of −0.057 ± 0.05 W/m2., Key Points A new version of the CAM/IMPACT atmospheric model that includes gravity waves and the effect of aerosols on cirrus clouds is presentedThe best representation of the particles that act as ice nuclei results in a climate forcing of −0.2 W/m2 for aircraft sootThe use of all dust particles as ice nuclei lowers this forcing to near zero

This study aims to understand the nature of the tropical intraseasonal oscillations (ISOs) in an aquaplanet simulation performed using Geophysical Fluid Dynamics Laboratory's AM2.1 with a uniform sea surface temperature within the deep tropics. The simulated ISO resembles the observed Madden‐Julian Oscillation in that the spectral peak in precipitation appears at zonal wave number 1 and a period of ~60 days. Vertically integrated moist static energy budget of the simulated ISO shows that enhanced latent heat flux to the east of anomalously active convection causes eastward propagation of the ISO mode, which is weakly opposed by horizontal moisture advection. A series of mechanism denial experiments are conducted either by homogenizing select variables—surface wind stress, longwave radiative heating, and surface evaporation—with their zonal means from the control simulation or by suppressing free‐tropospheric moisture variation. Results of the mechanism denial experiments show that the simulated ISO disappears when the interactive surface evaporation is disabled, suggesting that the wind‐induced surface heat exchange (WISHE) mechanism is essential to the simulated ISO. Longwave cloud‐radiation feedbacks and moisture‐convection feedbacks affect horizontal scale and phase speed of the simulated ISO, respectively. Our results strongly suggest that the simulated ISO is the linear WISHE‐moisture mode of Fuchs and Raymond under horizontally uniform boundary conditions., Key Points An aquaplanet simulation exhibits a mode of planetary‐scale (wave number 1), eastward propagating intraseasonal variabilityMoist static energy budget and mechanism denial experiments suggest that this mode is the linear WISHE‐moisture mode of Fuchs and RaymondThe WISHE and longwave cloud‐radiation feedbacks serve as scale selection mechanisms for the intraseasonal variability

This paper presents measurements of the amplitudes and timings of the combined, annual, and semiannual variations of thermospheric neutral density, and a comparison of these density variations with measurements of the infrared emissions from carbon dioxide and nitric oxide in the thermosphere. The density values were obtained from measurements of the atmospheric drag experienced by the Challenging Minisatellite Payload, Gravity Recovery and Climate Experiment A, Gravity field and Ocean Circulation Explorer, and three Swarm satellites, while the optical emissions were measured with the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. These data span a time period of 16 years. A database containing global average densities that were derived from the orbits of about 5,000 objects (Emmert, 2009, https://doi.org/10.1029/2009JA014102, 2015b, https://doi.org/10.1002/2015JA021047) was employed for calibrating these density data. A comparison with the NRLMSISE‐00 model was used to derive measurements of how much the density changes over time due to these seasonal variations. It is found that the seasonal density oscillations have significant variations in amplitude and timing. In order to test the practicality of using optical emissions as a monitoring tool, the SABER data were fit to the measured variations. Even the most simple fit that used only filtered carbon dioxide emissions had good correlations with the measured oscillations. However, the density oscillations were also well predicted by a simple Fourier series, contrary to original expectations. Nevertheless, measurements of the optical emissions from the thermosphere are expected to have a role in future understanding and prediction of the semiannual variations., Key Points Four satellite missions are used to derive thermosphere density variations caused by annual and semiannual oscillations over a 16‐year periodVariations in thermospheric density are compared with emissions from carbon dioxide and nitric oxide measured with the SABER instrumentThe carbon dioxide emissions and simple Fourier series fits have good correlations with thermosphere density oscillations

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

We use the Weather Research and Forecast model using the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) dust module (WRF‐CHEM) to simulate the particulate matter (PM) variations in the Sahel during the winter seasons (January–March) of 1960–2014. Two simulations are undertaken where the direct aerosol feedback is turned off, and only transport is considered and where the direct aerosol feedback is turned on. We find that simulated Sahelian PM10 and PM2.5 concentrations were lower in the 1960s and after 2003 and higher during the period between 1988 and 2002. Higher Sahelian PM10 concentrations are due to stronger winds between the surface and 925 hPa over the Sahara, which transport dust into the Sahel. Negative PM10 concentration anomalies are found over the Bodele Depression and associated with weaker 925 wind anomalies after 1997 through 2014. Further west, positive PM10 concentration anomalies are found across the Adrar Plateau in the Sahara and responsible for dust transport to the Western Sahel. The North Atlantic Oscillation (NAO) is positively correlated to Sahelian dust concentrations especially during the periods of 1960–1970 and 1988–2002. The temporal/spatial patterns of PM10 concentrations have significant respiratory health implications for inhabitants of the Sahel., Key Points Decadal variations in Sahelian PM10 and PM2.5 concentrations are strongly related to Saharan wind speed magnitude anomalies between the surface and 925 hPaThe highest correlations among the North Atlantic Oscillation and simulated Sahelian and Saharan PM10 seasonal anomalies between 1960–1970 and 1988–2002 are observedImproved ambient air pollution and health monitoring is a critical need for determining the connections between particulate matter and respiratory disease in the Sahel

Cold pools influence convective initiation and organization, dust lofting, and boundary layer properties, but little is known about their interactions with the land surface, particularly in dry continental environments. In this study, two‐way cold pool‐land surface interactions are investigated using high‐resolution idealized simulations of an isolated, transient cold pool evolving in a dry convective boundary layer. Results using a fully interactive land surface demonstrate that sensible heat fluxes are suppressed at the center of the cold pool but enhanced at the edge due to the spatial patterns of land surface cooling and the air temperature and wind speed perturbations. This leads to cold pool dissipation from the edge inward. Latent heat fluxes are primarily suppressed within the cold pool, and the magnitude of this suppression is controlled by competition between atmospheric and land surface effects. By comparing the fully interactive land surface simulation to a simulation with imposed surface fluxes, the land surface‐cold pool feedbacks are shown to reduce the cold pool lifetime, extent, and intensity by up to 50% and influence the pattern of boundary layer turbulent kinetic energy recovery, which have significant implications for cold pool‐induced convective initiation., Key Points An isolated cold pool evolving in a dry convective boundary layer is simulated at high resolutionSensible heat fluxes are enhanced at the cold pool's edge and suppressed in the center, leading to dissipation from the edge inwardLand surface interactions reduce the cold pool lifetime, area, and intensity by up to 50% and affect the boundary layer evolution

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

Understanding the context from which evidence emerges is of paramount importance in reaching robust conclusions in scientific inquiries. This is as true of the present as it is of the past. In a trans‐disciplinary study such as More et al. (2017, https://doi.org/10.1002/2017GH000064) and many others appearing in this and similar journals, a proper analysis of context demands the use of historical evidence. This includes demographic, epidemiological, and socio‐economic data—common in many studies of the impact of anthropogenic pollution on human health—and, as in this specific case, also geoarchaeological evidence. These records anchor climate and pollution data in the geographic and human circumstances of history, without which we lose a fundamental understanding of the data itself. This article addresses Hinkley (2018, https://doi.org/10.1002/2017GH000105) by highlighting the importance of context, focusing on the historical and archaeological evidence, and then discussing atmospheric deposition and circulation in the specific region of our study. Since many of the assertions in Bindler (2018, https://doi.org/10.1002/2018GH000135) are congruent with our findings and directly contradict Hinkley (2018), this reply refers to Bindler (2018), whenever appropriate, and indicates where our evidence diverges., Key Points Historical and archaeological evidence and context are crucially important in understanding past health, climate, and pollution dataGeographic context and proximity to sources of lead (Pb) mining and smelting have a significant impact on the ice core record