JGR–Atmospheres

We conduct a global assessment of the spatial heterogeneity of cloud phase within the temperature range where liquid and ice can coexist. Single-shot Cloud-Aerosol Lidar with Orthogonal Polarization lidar retrievals are used to examine cloud phase at scales as fine as 333 m, and horizontal heterogeneity is quantified according to the frequency of switches between liquid and ice along the satellite's path. In the global mean, heterogeneity is greatest between −15 and −4°C with a peak at −5°C, when small patches of ice are prevalent within liquid-dominated clouds. Heterogeneity “hot spots” are typically found over the extratropical continents, whereas phase is relatively homogeneous over the Southern Ocean and the eastern subtropical ocean basins, where supercooled liquid clouds dominate. Even at a fixed temperature, heterogeneity undergoes a pronounced annual cycle that, in most places, consists of a minimum during autumn or winter and a maximum during spring or summer. Based on this spatial and temporal variability, it is hypothesized that heterogeneity is affected by the availability of ice nucleating particles. These results can be used to improve the representation of subgrid-scale heterogeneity in general circulation models, which has the potential to reduce longstanding model biases in cloud phase partitioning and radiative fluxes.

A high-resolution model in conjunction with realistic background wind and temperature profiles has been used to simulate gravity waves (GWs) that were observed by an atmospheric radar at Syowa Station, Antarctica on 18 May 2021. The simulation successfully reproduces the observed features of the GWs, including the amplitude of vertical wind disturbances in the troposphere and vertical fluxes of northward momentum in the lower stratosphere. In the troposphere, ship-wave responses are seen along the coastal topography, while in the stratosphere, critical-level filtering due to the directional shear causes significant change of the wave pattern. The simulation shows the multi-layer structure of small-scale turbulent vorticity around the critical level, where turbulent energy dissipation rates estimated from the radar spectral widths were large, indicative of GW breaking. Another interesting feature of the simulation is a wave pattern with a horizontal wavelength of about 25 km, whose phase lines are aligned with the front of turbulent wake downwind of a hydraulic jump that occurs over steep terrain near the coastline. It is suggested that the GWs are likely radiated from the adiabatic lift of an airmass along an isentropic surface hump near the ground, which explains certain features of the observed GWs in the lower stratosphere.

This study examines 40 years of monthly precipitation data in Senegal (1979–2018) using Climatic Research Unit observations and ERA5 reanalyzes, aiming to understand the influence of oceanic and atmospheric factors on Senegal's precipitation in July, August and September (JAS). The variability of Senegal's precipitation is first compared with that of the broader Sahel region: although they share a significant portion of their variance, Senegal appears more closely related to the Northeastern Tropical Atlantic (NETA) Sea Surface Temperature (SST). A detailed examination of this region reveals that Senegal's increased precipitation is linked to the northward shift of the InterTropical Convergence Zone, consistent with numerous previous studies. Over the continent, this shift corresponds to a northward shift of the African Easterly Jet (AEJ) and, consequently, the mesoscale convective systems (MCSs) responsible for most precipitation. It seems primarily driven by the northward shift of the Heat Low. Over the ocean just west of Senegal, there is a comparable shift of the AEJ, accompanied by an increase in low-level moisture transport convergence within the West African Westerly Jet (WAWJ) which explains the majority of the increase in JAS precipitation in Senegal. This phenomenon is triggered by a negative pressure anomaly in the NETA, located above a positive SST anomaly: we suggest that the latter is the origin of the former, forming a feedback mechanism that potentially significantly influences Senegal's precipitation. The mechanism involves a geostrophic adjustment of the WAWJ to the southern gradients of the SST anomaly.

Motivated by numerous lower atmosphere climate model hindcast simulations, we performed simulations of the Earth's atmosphere from the surface up through the thermosphere-ionosphere to reveal for the first time the century scale changes in the upper atmosphere from the 1920s through the 2010s using the Whole Atmosphere Community Climate Model—eXtended (WACCM-X v. 2.1). We impose solar minimum conditions to get a clear indication of the effects of the long-term forcing from greenhouse gas increases and changes of the Earth's magnetic field and to avoid the requirement for careful removal of the 11-year solar cycle as in some previous studies using observations and models. These previous studies have shown greenhouse gas effects in the upper atmosphere but what has been missing is the time evolution with actual greenhouse gas increases throughout the last century, including the period of less than 5% increase prior to the space age and the transition to the over 25% increase in the latter half of the 20th century. Neutral temperature, density, and ionosphere changes are close to those reported in previous studies. Also, we find high correlation between the continuous carbon dioxide rate of change over this past century and that of temperature in the thermosphere and the ionosphere, attributed to the shorter adjustment time of the upper atmosphere to greenhouse gas changes relative to the longer time in the lower atmosphere. Consequently, WACCM-X future scenario projections can provide valuable insight in the entire atmosphere of future greenhouse gas effects and mitigation efforts.

No abstract is available for this article.

Saharan dust exerts profound impacts on the genesis and intensification of tropical cyclones (TCs). Such impacts on various stages of the TCs have yet to be explored. In this study, we utilize the Cloud-Resolving weather research and forecasting model (WRF) to investigate the relative importance of the microphysical and radiative effects of dust on two hurricanes (Earl and Danielle) at different life stages under similar dynamical conditions in 2010. Both TCs were embedded in a dusty environment throughout their lifetime. A new dust ice nucleation scheme was implemented into the aerosol-aware Texas A&M University two-moment microphysical scheme in WRF. Moreover, the dust radiative effect was included in the Goddard Shortwave Scheme of WRF. Our sensitivity experiments show that the radiative effect of dust (DRAD) amplified the mid-level ridge in the Central Atlantic Ocean through temperature perturbation, changing the tracks of Danielle and Earl. Further analyses reveal an early shift of Danielle's maximum intensity for 12 hours but a significantly suppressed Earl in DRAD. In addition, the microphysical effect of dust had little impact on the large-scale dynamical fields and storm tracks. The inclusion of dust as ice nucleation particles results in more variations in the intensity of Danielle and Earl than in other scenarios. This is owing to the higher maximum diabatic heating rate in the rainband region that perturbs the size of the TC. This study shows the dominant dust radiative effects on both intensity and track of the storm. In addition, there is evidence that dust suppresses the early stage TC but provides favorable conditions for matured TC. Both findings have profound implications for hurricane forecast and address the importance of accounting for detailed cloud microphysics and aerosol-TC interactions in the operational forecasting models.

In the present study, the Morrison and Thompson microphysics schemes in the Weather Research and Forecasting model were improved and used to simulate a record-breaking heavy rainfall event occurred in Henan Province over central China during 19–21 July 2021. In the modified schemes, the terminal velocity of graupel and initial cloud droplet concentration were adjusted based on sensitivity tests. Results showed that the modified Morrison scheme (MORR_MOD) better captured the spatial distribution and temporal evolution of precipitation than the original scheme (MORR). Specifically, it produced a 40-hr cumulative rainfall amount of 963 mm and an extreme hourly rainfall rate of 157.7 mm, which were closer to observations than MORR. Analysis of the dynamic and microphysical structures of the extreme-rain-producing convective clusters revealed that MORR_MOD predicted stronger updrafts, higher rain mass content and larger mean mass diameter of raindrops than MORR. By analyzing the tendencies of rain mass and number concentration, it was found that MORR_MOD predicted stronger accretion rates of cloud droplets by rain and weaker auto-conversion rates of cloud droplets than MORR, which contributed to the high rain mixing ratio and low number concentration, respectively. In addition, MORR_MOD predicted stronger diabatic heating rates than MORR, which were primarily attributed to stronger condensation of water vapor, and may have been the reason why MORR_MOD simulated stronger updrafts.

More and more optical records have exhibited that multiple upward leaders (MULs) occur frequently on a building in the flash attachment process. An interesting issue is why a building can continue to launch upward leader (UL) after the first one appears. This phenomenon is analyzed in the present paper. Considering the influence of the leader behaviors on the ambient electric field, an improved 3-D fine-resolution lightning attachment model with MULs is established to simulate cloud-to-ground flash events with diverse leader spatial morphologies. The simulation results show that MULs may initiate almost simultaneously or with an obvious delay and the variation range of UL length is large. From this, the flash events of lightning terminating on a building are divided into four scenarios and each scenario is analyzed. It was found that the spatial location of downward leader, the length and propagation direction of the first UL and the time interval from the inception of the first UL to final jump significantly affect the electric fields at top corners of building and further affect the inception of the second UL. Based on qualitative analysis, four factors are proposed to explain why the above four scenarios happen.

Reanalysis data reveal a weak warming trend in the midwinter Arctic stratosphere, contrary to the cooling expectation based on the greenhouse gas effect. This trend is also influenced by the occurrence of sudden stratospheric warmings (SSWs). Using Phase 6 of the Coupled Model Intercomparison Project (CMIP6) we investigate temperature trends over a similar timescale as ERA5 and find that CMIP6 models can replicate the positive midwinter temperature trend in the mid-lower stratosphere. However, when considering the multi-model mean, this positive temperature trend is much weaker than ERA5. Extrapolating to the future, we find that the SSW-driven positive temperature trend will likely not continue in the future based on the SSP2-4.5 and SSP5-8.5 climate scenarios. Instead, the models project there will be widespread cooling throughout the Arctic winter stratosphere regardless of the occurrence of SSWs. Using a subsample of CMIP6 models which replicate the seasonality of the Arctic winter stratosphere most similarly to that of ERA5, we also find that the zonal wind strength during SSWs correlates the most with the temperature trends found there. However, trends in the zonal wind strength alone cannot account for the observed temperature trends among the CMIP6 models.

We report on the mountain top observation of three terrestrial gamma-ray flashes (TGFs) that occurred during the summer storm season of 2021. To our knowledge, these are the first TGFs observed in a mountaintop environment and the first published European TGFs observed from the ground. A gamma-ray sensitive detector was located at the base of the Säntis Tower in Switzerland and observed three unique TGF events with coincident radio sferic data characteristic of TGFs seen from space. We will show an example of a “slow pulse” radio signature (Cummer et al., 2011, https://doi.org/10.1029/2011GL048099; Lu et al., 2011, https://doi.org/10.1029/2010JA016141; Pu et al., 2019, https://doi.org/10.1029/2019GL082743; Pu et al., 2020, https://doi.org/10.1029/2020GL089427), a −EIP (Lyu et al., 2016, https://doi.org/10.1002/2016GL070154; Lyu et al., 2021, https://doi.org/10.1029/2021GL093627; Wada et al., 2020, https://doi.org/10.1029/2019JD031730), and a double peak TGF associated with an extraordinarily powerful and complicated positive-polarity sferic, where each TGF peak is possibly preceded by a short burst of stepped leader emission.

Dimethyl sulfide (DMS) is the predominant natural sulfur source and plays a pivotal role in regulating global climate. However, the current method for estimating seawater DMS concentrations has limitations, and the existing DMS-induced radiative effect heavily relies on bottom-up DMS climatologies. This study aims to improve the method for estimating seawater DMS concentrations as well as to evaluate its induced aerosol direct radiative effect (DRE) and indirect radiative effect (IRE) using a state-of-the-art aerosol microphysics scheme integrated with a chemical transport model. The predicted seawater DMS concentrations based on data-driven methods were verified with multi-year in situ measurements, revealing a marked reduction in mean bias by over 80%. Results show that our estimates generally indicate lower seawater DMS concentrations (1.48–1.88 μmol/m3) compared to previous seawater DMS climatologies, with differences ranging from −37% to 11%, and that interannual variability in DMS concentrations is varies significantly, particularly in polar regions. The DRE and cloud-albedo IRE induced by DMS were −0.06 and −0.19 W/m2, respectively, representing a cooling effect on radiative effect that was weaker by 31.4% and 27.0% of those derived from the commonly used bottom-up DMS climatology. The comprehensive evaluation of the model's performance of atmospheric DMS prediction based on global-scale observations shows a significant improvement after using our estimates. Thus, we conclude that the global DMS fluxes provided in the past are overestimated, including its resulting DMS radiative effect, which highlights the need for refining the estimation of global aerosol radiative effect to enhance the accuracy of assessing aerosol-induced climate impacts.

The tropical climate variabilities, such as Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO), are accompanied by changes in the tropical deep convection which can influence the atmospheric circulation in the Southern Hemisphere (SH). To investigate each role of IOD and ENSO in the September-November (SON) circulation, we examine teleconnection patterns associated with IOD and ENSO events using the ERA5 monthly averaged data from 1979 to 2020. Our approach is to calculate the power spectral density (PSD) of the sea level pressure (SLP) and meridional wind and geopotential height at 300 hPa that are decomposed by zonal wave numbers (ZWNs), and to compute their correlations with IOD and ENSO at each latitudinal band. The main results are that IOD (ENSO) is negatively (positively) correlated with PSDs of ZWN2 and ZWN3 (ZWN1) at 300 hPa in the SH middle latitudes. Considering the Rossby wave train, IOD (ENSO) considerably affects the variability of the ZWN3 (ZWN1) pattern, which influences the meridional exchange of momentum. Additionally, the relationship between IOD and ZWN3 has become tighter in recent years, which is not seen in that with ENSO. The IOD and ENSO events also modify the SLP patterns and meridional surface winds, modulating the sea ice extent in the Southern Ocean. During the highly positive 2019 IOD event, the variability of the middle latitudes atmospheric circulation was considerably larger than climatology, suggesting a higher chance of more extreme weather patterns associated with more frequent intense IOD events in the warming climate.

Snowpacks are natural water reservoirs providing a considerable amount of water for humans and ecosystems. However, current global snow products (e.g., ESA GlobSnow v3.0), lack high spatial resolution and regional calibrations necessary to capture the high heterogeneity of snow water equivalents (SWEs) in complex Asian mountainous terrains. Therefore, our understanding of snow drought characteristics in China remains limited. Herein, we used an improved SWE product calibrated specifically for China to explore the characteristics of snow droughts, delineated by a standardized SWE index (SWEI) between 1993 and 2019. Our analysis was focused over three main snow-covered regions of China: Qinghai–Tibet Plateau (QTP), northern Xinjiang, Northeast China. Especially during the period from 1993 to 2010, we found that the SWEI increased significantly at rates of 0.022/yr (Northeast China), 0.017/yr (northern Xinjiang), and 0.011/yr (QTP) (p < 0.01, Mann-Kendall trend test). Increased SWEI contributed to decreasing snow drought events across China, with an obvious short-term characteristic, whilst area proportion of the identified 1-month snow droughts was above 46.5% across three regions. Furthermore, we found that the occurrence of snow droughts was likely mediated by large-scale atmospheric circulation, since increased water vapor transport caused a significant vapor flux convergence in cold seasons over three regions, especially in northern Xinjiang and Northeast China.

Radar data can be of significant utility in investigating characteristics of rainfall events that cannot be studied with rain gauges alone. The recent establishment of a long-term, quality-controlled data set covering most of the radars on the Australian continent enables a deeper characterization of rainfall, including heavy rainfall events. This study develops a methodology to identify and characterize rainfall events from radar data and tests its utility by applying it to the regions surrounding the major cities of Brisbane, Sydney, and Melbourne. The event characteristics studied include rainfall accumulation and intensity, event duration and spatial extent, and the contribution convective areas make to the overall event rainfall. Rainfall events in Brisbane and Sydney are found to be more intense, more convective, and smaller in extent whilst producing larger rainfall accumulations than Melbourne rainfall events. Rainfall event duration and total accumulated rainfall are strongly positively correlated, as are the overall event intensity and the intensity of convective rainfall. The events that produce the largest rainfall accumulations exhibit significant differences from the events that produce the highest rainfall intensities. Overall, the study demonstrates that long-term radar data sets in Australia provide an invaluable and rich source to study rainfall characteristics in a variety of regions at a high spatial and temporal resolution.

Ship emission impacts ambient air quality, especially in coastal regions, by emitting air pollutants such as fine particles, nitrogen oxides (NOx), and sulfur dioxide (SO2), yet its contributions to volatile organic compounds (VOCs) and the formation of secondary organic aerosol (SOA) and ozone (O3) are much less constrained with the challenge in distinguish ship emission from land diesel emission. In this study, we conducted a 1-year online measurement of VOCs with a 1-hr resolution at a coastal site in south China's Pearl River Delta region, which holds three of the world's top 10 container ports. The results revealed that C10–C12 n-alkanes, as typical diesel-related emission tracers, were significantly enhanced and strongly related to oceanic air masses. Receptor modeling revealed two diesel-related sources of land diesel emission and ship emission, which could be differentiated based on their source profiles, seasonal trends and air mass back trajectories. Ship emissions contributed 6.4%, 5.0%, and 13.6% of total VOC mixing ratios, ozone formation potentials (OFPs), and secondary organic aerosol formation potentials (SOAFPs), while these percentages were 3.4%, 14.7%, and 15.9% for land diesel emission, respectively. In particular, in July, ship emissions could contribute 21.7%, 14.6%, and 31.2% of VOCs, OFPs, and SOAFPs, respectively. Our results highlight the important contribution of diesel-related emission VOCs in forming O3 and SOA in coastal regions, and ship emission is a non-negligible source of VOCs, particularly after the strict control of land emission sources.

Permafrost in the Qinghai-Tibet Plateau (QTP) is sensitive to climate warming, but the associated degradation risk still lacks accurate evaluation. To address this issue, machine learning (ML) models are established to simulate the mean annual ground temperature (MAGT) and active layer thickness (ALT), and climate data from shared socioeconomic pathways (SSPs) are prepared for evaluation in the future period. Based on the projections, permafrost is expected to remain relatively stable under the SSP1-2.6 scenario, and large-scale permafrost degradation will occur after the 2050s, resulting in area losses of 30.15% (SSP2-4.5), 58.96% (SSP3-7.0), and 65.97% (SSP5-8.5) in the 2090s relative to the modeling period (2006–2018). The average permafrost MAGT (ALT) is predicted to increase by 0.50°C (59 cm), 0.67°C (89 cm), and 0.79°C (97 cm) in the 2090s with respect to the modeling period under the SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Permafrost in the Qilian Mountains and Three Rivers Source region are fragile and vulnerable to degradation. In the future period, permafrost on the sunny slopes is more prone to degradation and the sunny-shade slope effect of permafrost distribution will be further enhanced under climate warming. The lower limit of permafrost distribution is expected to rise by about 100 m in the 2050s under the SSP2-4.5 scenario. These findings can provide valuable insights about future permafrost changes in the QTP.

The near-surface boundary layer can mediate the response of mountain glaciers to external climate, cooling the overlying air and promoting a density-driven glacier wind. The fundamental processes are conceptually well understood, though the magnitudes of cooling and presence of glacier winds are poorly quantified in space and time, increasing the forcing uncertainty for melt models. We utilize a new data set of on-glacier meteorological measurements on three neighboring glaciers in the Swiss Alps to explore their distinct response to regional climate under the extreme 2022 summer. We find that synoptic wind origins and local terrain modifications, not only glacier size, play an important role in the ability of a glacier to cool the near-surface air. Warm air intrusions from valley or synoptically-driven winds onto the glacier can occur between ∼19% and 64% of the time and contribute between 3% and 81% of the total sensible heat flux to the surface during warm afternoon hours, depending on the fetch of the glacier flowline and its susceptibility to boundary layer erosion. In the context of extreme summer warmth, indicative of future conditions, the boundary layer cooling (up to 6.5°C cooler than its surroundings) and resultant katabatic wind flow are highly heterogeneous between the study glaciers, highlighting the complex and likely non-linear response of glaciers to an uncertain future.

The Geostationary Lightning Mapper (GLM) is an instrument on the NOAA Geostationary Operational Environmental Satellites-R (GOES-R) Series. The GLM data are processed by the Lightning Cluster Filter Algorithm which filters the GLM data and clusters it into a series of events, groups, and flashes. One of the current filters in the GLM algorithm (as of June 2023) removes all flashes that have only a single group. Combining the flashes (including the flashes with only single group) from two of the GLMs (the GLM on GOES-16 and the GLM on GOES-17) in the region where they overlap produces a unique data set of coincident flashes (detected by both GLMs) and non-coincident flashes (detected by only one GLM). Coincident flashes detected by both GLMs are very unlikely to be from noise sources. This data set allows us to estimate the impact of the single group flashes on the Detection Efficiency (DE) and the False Alarm Rate (FAR). We find that the single group flash filter does greatly improve the FAR but does slightly decrease the DE. Subsequent analysis shows that some of the removed flashes with single groups are from true lightning. A simple modification to the single group flash filter to only remove flashes with a single event increases the FAR without a corresponding improvement in DE. A more complex algorithm is needed to recover the single group flashes that are likely from lightning without adding back single group flashes that are from noise sources.

Chlorinated very short-lived substances (Cl-VSLS) are ubiquitous in the troposphere and can contribute to the stratospheric chlorine budget. In this study, we present measurements of atmospheric dichloromethane (CH2Cl2), tetrachloroethene (C2Cl4), chloroform (CHCl3), and 1,2-dichloroethane (1,2-DCA) obtained during the National Aeronautics and Space Administration (NASA) Atmospheric Tomography (ATom) global-scale aircraft mission (2016–2018), and use the Community Earth System Model (CESM) updated with recent chlorine chemistry to further investigate their global tropospheric distribution. The measured global average Cl-VSLS mixing ratios, from 0.2 to 13 km altitude, were 46.6 ppt (CH2Cl2), 9.6 ppt (CHCl3), 7.8 ppt (1,2-DCA), and 0.84 ppt (C2Cl4) measured by the NSF NCAR Trace Organic Analyzer (TOGA) during ATom. Both measurements and model show distinct hemispheric gradients with the mean measured Northern to Southern Hemisphere (NH/SH) ratio of 2 or greater for all four Cl-VSLS. In addition, the TOGA profiles over the NH mid-latitudes showed general enhancements in the Pacific basin compared to the Atlantic basin, with up to ∼18 ppt difference for CH2Cl2 in the mid troposphere. We tagged regional source emissions of CH2Cl2 and C2Cl4 in the model and found that Asian emissions dominate the global distributions of these species both at the surface (950 hPa) and at high altitudes (150 hPa). Overall, our results confirm relatively high mixing ratios of Cl-VSLS in the UTLS region and show that the CESM model does a reasonable job of simulating their global abundance but we also note the uncertainties with Cl-VSLS emissions and active chlorine sources in the model. These findings will be used to validate future emission inventories and to investigate the fast convective transport of Cl-VSLS to the UTLS region and their impact on stratospheric ozone.

We compared short-term cloud feedback, defined at the top of the atmosphere (TOA), the atmospheric column (ATM), and the surface (SFC), between observations and models participating in Atmospheric Model Intercomparison Project Phase 6 (AMIP6) for the period 2000–2014. The globally averaged net cloud feedbacks observed at TOA, ATM, and SFC are −0.06 ± 0.63, −0.17 ± 0.70, and 0.11 ± 0.81 W m−2 K−1, respectively. While most models produced TOA cloud feedbacks that agreed with the observations within uncertainty ranges, the intermodel spread at SFC and within ATM was relatively larger. This demonstrates that models are diverse in how their TOA feedback is distributed between ATM and SFC. Because short-term cloud feedback is mainly driven by El Niño–Southern Oscillation (ENSO), the global-mean cloud feedback was further decomposed into components from the ENSO and non-ENSO regions. Results show that cloud feedback in these two regions tends to be inversely related. Compared to observations, almost all models overestimated the longwave cloud feedback in the ENSO region due to the overestimation of cloud amount changes for high-topped clouds. For these models, it is the offset between deviations in ENSO and non-ENSO regions that leads to the overall agreement of global mean with observations. Sensitivity tests show that the main conclusions still hold when alternative kernels are used in estimating cloud feedback.