JGR–Atmospheres

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.

This study quantifies the contribution of individual cloud feedbacks to the total short-term cloud feedback in satellite observations over the period 2002–2014 and evaluates how they are represented in climate models. The observed positive total cloud feedback is primarily due to positive high-cloud altitude, extratropical high- and low-cloud optical depth, and land cloud amount feedbacks partially offset by negative tropical marine low-cloud feedback. Seventeen models from the Atmosphere Model Intercomparison Project of the sixth Coupled Model Intercomparison Project are analyzed. The models generally reproduce the observed moderate positive short-term cloud feedback. However, compared to satellite estimates, the models are systematically high-biased in tropical marine low-cloud and land cloud amount feedbacks and systematically low-biased in high-cloud altitude and extratropical high- and low-cloud optical depth feedbacks. Errors in modeled short-term cloud feedback components identified in this analysis highlight the need for improvements in model simulations of the response of high clouds and tropical marine low clouds. Our results suggest that skill in simulating interannual cloud feedback components may not indicate skill in simulating long-term cloud feedback components.

The Early Eocene Climatic Optimum (EECO) may be a potentially useful analog for future global warming under high CO2 concentrations. However, a paucity of orbital-scale terrestrial records limits our understanding of how the hydrological cycle responded during this protracted (∼4 Myr) interval of global warmth. In this study, we combine zircon U-Pb dating and cyclostratigraphy to establish a high-resolution astronomical timescale spanning the EECO (∼52.9 Ma to ∼49.9 Ma) through a >1 km fluviolacustrine succession from the Gonjo Basin, Southeast Tibet. Our results suggest that hydroclimate variability in the region during this interval was strongly controlled by eccentricity forcing (∼405 Kyr, ∼135–100 Kyr, and possibly ∼200 Kyr cycles). The dominance of eccentricity forcing in our record is consistent with coeval marine records, and indicates that modulation of low-latitude summer insolation through nonlinear interactions with the global carbon cycle likely controlled hydroclimate and paleolake level in the Gonjo basin during the EECO. Our study offers new perspectives for the forcing mechanisms of terrestrial hydroclimate changes of East Asia in response to subtle changes in insolation during the EECO.