JGR–Atmospheres

Southeastern New Mexico's Carlsbad Caverns National Park (CAVE) has increasingly experienced summertime ozone (O3) exceeding an 8-hr average of 70 parts per billion by volume (ppbv). The park is located in the western part of the Permian oil and natural gas (O&G) basin, where production rates have increased fivefold in the last decade. We investigate O3–precursor relationships by constraining the F0AM box model to observations of nitrogen oxides (NOx = NO + NO2) and a suite of volatile organic compounds (VOCs) collected at CAVE during summer 2019. O&G-related VOCs dominated the calculated VOC reactivity with hydroxyl radicals (OH) on days when O3 concentrations were primarily controlled by local photochemistry. Radical budget analysis showed that NOx levels were high enough to impose VOC sensitivity on O3 production in the morning hours, while subsequent NOx loss through photochemical consumption led to NOx-sensitive conditions in the afternoon. Maximum daily O3 was responsive to both NOx and O&G-related VOC reductions, with NOx reductions proving most effective. The model underestimated observed O3 during a 5-day high O3 episode that was influenced by photochemically aged O&G emissions, as indicated by back-trajectory analysis, low i-/n-pentane ratios, enhanced secondary VOCs, and low ratios of NOx to total reactive oxidized nitrogen (NOy). Model-observation agreement was improved by constraining model NOx with observed NOy, which approximates NOx at the time of emission, indicating that a large fraction of O3 during this episode was formed nonlocally.

Given the important role of Atmospheric River precipitation (ARP) in the global hydrological cycle, accurate representation of ARP is significant. However, general circulation models (GCMs) demonstrate bias in simulating ARP. The target of this study is to quantify the performance of ARP intensity/frequency for CMIP6 simulations, and further to improve ARP estimation of CMIP6 using Cycle-Consistent Generative Adversarial Networks (CycleGAN) with highlighting the more accurate ARP features under the global warming background. The findings of this study are as follows: (a) although ARP intensity/frequency in reserved-optimal CMIP6 overall reproduces the observation, it is still underestimated at the stronger Atmospheric river (AR) scales, particularly for the AR highly active mid-latitude regions. (b) The CycleGAN-based bias correction approach markedly diminishes the bias of the CMIP6 simulations within most of the AR scales among both global and the four AR highly active regions. Moreover, the performance of the ARP in AR highly active regions is significant improvement, which is mainly due to the reduction of the bias at the strongest scale. (c) Relative to reference period (1986–2005), ARP intensity/frequency at the strongest scale increase notably under 3°C warming level, with an average value of 373.3% in intensity and 415.9% in frequency for global and the four key regions before correction, and the value is 451.9% and 492.5% after bias correction. The results illustrate that CycleGAN can effectively improve the ARP simulations of GCMs, and an early warning implies that future strong extreme ARP should potentially surpass the current expected.

The Turkana Jet plays a pivotal role in the meteorology of East Africa across timescales, and owes its existence to both large-scale dynamics and the representation of intricate local-scale processes. However, much of our understanding of the jet relies on reanalysis, and these along with climate models that produce important projections do not represent these local-scale processes. We systematically investigate the impact of changing model horizontal and vertical resolution in simulating the Turkana Jet, and associated local and large-scale processes. We perform simulations to coincide with the Radiosonde Investigation For the Turkana Jet (RIFTJet) campaign, enabling direct model-sonde comparisons in unprecedented detail. We find that increasing horizontal model resolution significantly increases the strength of the jet throughout the channel by up to 30%, while vertical resolution changes have little impact. Horizontal resolutions finer than 2.2 km produce a nocturnal jet ∼2 m/s stronger than observed but perform better during the day. The elevated inversion, which is strongly tied to the strength of the jet, is much better represented in resolutions as high as 1.1 km, whereas the global model at resolution O(∼10 km) is unable to produce any nocturnal elevated inversion. Predictions of jet strength are improved at higher resolution, indicating an important role of local process given that models inherit the same large-scale state. Despite further improvements at resolutions finer than 4.4 km, we recommend that 4.4 km is the minimum horizontal resolution required to capture realistic interactions between these processes. Underestimation of the Turkana Jet could cause considerable errors in moisture advection into Africa.

Temperatures and pressures from high explosive detonations far exceed atmospheric conditions in typical combustion reactions, and consequently, detonation soot forms with physiochemical properties distinct from soot formed by combustion. In this study, samples of detonation soot from two high explosives, PBX 9502 and Composition B-3, were analyzed. Ice nucleation experiments on soot collected after controlled detonations were conducted in the laboratory to probe immersion and contact mode freezing. Samples nucleated ice at temperatures warmer than commercially available nanodiamonds, which has a mean nucleation temperature of −20.7°C. Ice nucleation rate coefficients increase rapidly by two to three orders of magnitude below −20°C for every sample. Size-selected 137 μm diameter particles produced during detonation in an ambient air atmosphere yield bimodal distributions of freezing temperature with primary and secondary nucleation modes centered at −20°C and −13°C, respectively. The presence of a secondary mode allows for enhanced ice nucleation rate coefficients (one to two orders of magnitude greater than samples without a secondary mode) at temperatures outside the influence of the primary mode (>−17°C). Given the observed onset nucleation temperatures of −9.2°C, our results imply that detonation soot of the type studied here would only need to reach an altitude of approximately 4 km to facilitate ice formation.

The Atmospheric InfraRed Sounder (AIRS) aboard Aqua provides essential long-term data on vertical cloud fraction, particularly valuable in the Arctic region. This study offers a comprehensive assessment of Arctic vertical cloud fraction derived from AIRS through a comparison with independent ground- and space-based radar and lidar observations. In comparison to the measurements at the North Slope Alaska site, results reveal a significant underestimation of low-level cloud cover by AIRS, especially for near-surface clouds, while mid- and high-level cloud fractions show better consistency. In comparison to the satellite-based product from 3S-GEOPROF-COMB, the accuracy varies across different underlying surfaces (land vs. sea) and seasons. AIRS shows significant positive biases in mid-level cloud fraction over sea surfaces with sea ice concentration below 15%, indicating potential limitations in the cloud retrieval algorithm in regions with large sea ice variations. The issue of low-level clouds identification is primarily caused by the limited penetrating capability of infrared hyperspectral sensing and the accuracy of preceding surface and atmospheric state products, which diminish the accuracy of AIRS low-level cloud fraction.

The Stratospheric Total Aerosol Counter (STAC) is a lightweight balloon-borne instrument that utilizes condensational growth techniques to measure the total aerosol concentration. STAC is a miniaturized version of the legacy Wyoming condensation particle counter that operated from 1974 through 2020 in the middle latitudes and polar regions, with a few measurements in the tropics. Here we provide a description of the STAC instrument and the total aerosol measurement record, demonstrating that typical total aerosol profiles exhibit a peak in number mixing ratio, with values between 800 and 2,000 particles per mg of air (mg−1), just below the lapse rate tropopause (LRT). In the tropics and middle latitudes, mixing ratios decrease above the LRT likely due to coagulation and scavenging that results in a transfer of mass to the fewer but larger aerosol particles of the Junge layer. Exceptions to this occur in the spring time in the middle latitudes where a new particle layer between 20 and 25 km is frequently observed. In the poles, total aerosol profiles exhibit two distinct features: new particle formation in austral spring, and an increasing mixing ratio above 17 km likely due to the presence of meteoric smoke that has been concentrated within the polar vortex. High observed stratospheric particle mixing ratios, in excess of 2,000 mg−1, are observed in the polar new particle layer and at the top of polar profiles.

Accurately simulating moisture transport in summer over the TP is uncertain for current numerical models with one important factor being horizontal resolution. In this study, in order to investigate the moisture transport across scales, three experiments are conducted for summer of 2015 using a global variable-resolution model (MPAS-A), including one with globally quasi-uniform resolution of 60 km (U60km) and two with regional refinements over the TP at resolutions of 16 km (V16km) and 4 km (V4km). The wet bias of summer rainfall within the TP increase from U60km to V16km but is significantly improved in V4km. One important source of rainfall bias is the moisture transport across scales. The differences in moisture transport among three simulations are significantly influenced by the changes in wind fields through the Himalayas and eastern TP in two layers, 700–600 and 600–400 hPa, which is largely modulated by their difference in large-scale circulations particularly monsoon depression. At convection-parameterized scale (from 60 to 16 km), the scale-aware Grell-Freitas convection scheme produces more rainfall and latent heat due to its large sensitivity to the integrating timestep. This sensitivity along with further resolved dynamical processes, collectively strengthen the monsoon depression to the south of TP and make it shift northward in conjunction with the mid-latitude westerlies. With resolution increasing to convection-permitting scale (from 16 to 4 km), the resolved moist convection releases significantly less latent heat and then reproduces a weaker monsoon depression. This causes a discrepancy that exceeds the resolution-related difference at convection-parameterized scale.

Observing system simulation experiments are carried out to investigate the added value of radio occultation (RO) refractivity observations with various spatial sampling scenarios on regional weather predictions across the Indian region. A full summer monsoon season (June through September 2020) was used to demonstrate how varying the numbers and horizontal resolutions of RO data impacted regional-scale weather forecasting. The MPAS (Model for Prediction Across Scales) was used to produce a nature run at a maximum horizontal resolution of 10 km. Then the WRF model with 12-km horizontal resolution was used to carry out assimilation/forecast experiments with varying number of simulated RO observations. When the performance of the experiments is taken into account for moisture, temperature, winds and rainfall, as well as prediction lengths, the results show that RO observations with 50-km resolution assimilated every 6 hr would provide the best results. Increasing the horizontal resolution to 25 km per 6 hr shows little overall improvement. Furthermore, RO data with horizontal resolutions lower than 100 km per 6 hr have only a small impact on the regional numerical weather prediction system. The number of low Earth orbit satellites in low-inclination orbits required to achieve occultations every 6 hr with 50-km resolution based on the COSMIC-2 mission is approximately 700. This work is relevant for the deployment of the cost-effective RO observing system for improved weather forecasting over the Indian region.

Shallow convective clouds play a crucial role in Earth's energy budget, as they modulate the radiative transfer in the atmosphere and participate in the vertical transport of aerosols, energy, and humidity. The parameterizations representing these complex, vital players in weather and climate models are mostly based on a description of steady-state plumes and are a source of major uncertainty. Recently, several studies have shown that buoyant thermals are inherent in atmospheric convection and contain a toroidal (ring) vortex. This work studies those vortices in growing shallow cumulus (Cu) clouds using high-resolution (10 m) Large Eddy Simulations that resolve these vortices in much detail. Recent analysis of such data showed that small-scale turbulent diffusion is unable to explain the large diluted portion of the cloud. Here we advocate for the important role of the Cu toroidal vortex (TV) in cloud dilution and present the complex dynamics and structure of a Cu TV. Nevertheless, since the vortex dominates the cloud's dilution, simplicity emerges when considering the cloud's lateral mass flux profile. The cloud mixing is quantified using direct flux calculations and Eulerian tracers. In addition, Lagrangian tracers are used to identify the origin of the entrained air and its thermodynamic properties. It shows that most of the air entrained by the vortex is not recycled by the vortex, yet is significantly more humid than the environment. We suggest that the development of new models describing thermals, together with their toroidal vortices, might improve cloud parameterizations in weather and climate models.

No abstract is available for this article.

The Millennium Eruption of Changbaishan Volcano is heralded as one of the largest explosive eruptions in the Late Holocene and produced huge quantities of tephra. The petrogeochemical method estimates that the Millennium Eruption emitted up to 45 Tg of sulfur into the atmosphere—more than in the Tambora eruption in 1815 CE, which caused “a year without a summer” across the Northern Hemisphere in 1816 CE. Despite such massive emissions, evidence for this eruption's climate impact in East Asia remains elusive. To explain this contradiction, this study used 67 high-resolution tree-ring-width records from the Northern Hemisphere spanning the past two millennia, complemented by volcanic sensitivity experiments conducted with the Community Earth System Model. Results reveal a prevailing decreasing/negative trend in the proxy records during the potential eruption period, with 945 CE marking the most notable negative anomaly, suggesting that the Millennium Eruption likely occurred in 945 CE rather than 946 CE. Sensitivity experiments, corroborated by proxy records, demonstrate that the Millennium Eruption induced substantial negative temperature anomalies at middle and high latitudes, alongside an increase in Meiyu-Baiu-Changma precipitation in the middle and lower reaches of the Yangtze River and southwestern Japan and a decrease in precipitation in India, northern China, and the South China Sea in the first post-eruption year. This study offers a novel perspective on the climate impact of the Millennium Eruption, reconciling previous discrepancies regarding its climate impact.

Large volcanic eruptions are known to influence the climate through a variety of mechanisms including aerosol-forced cooling and warming via emitted CO2. The January 2022 Hunga shallow underwater eruption caused an increase in stratospheric water vapor, and demonstrated how the associated positive radiative forcing can be an important component of an eruption's climate forcing. We present interactive stratospheric aerosol model simulations of super-volcanic eruptions with a range of SO2 emissions that can produce climate warming through feedback effects produced by a large igneous province (or “flood basalt”) mid-latitude super-eruption using Goddard Earth Observing System Chemistry Climate Model climate model simulations. The model experiments suggest total SO2 emissions ≳4,000 Tg/4 Gt generate a multi-year period of sustained aerosol absorptive local-heating of the upper troposphere and lower stratosphere and hence produce net climate warming after strong initial cooling. The eruptions produce stratospheric water vapor increases of factors of 8–600. The initiation of these feedbacks within the simulations suggest they could occur for individual stratovolcano eruptions of the scale of the Toba or Tambora eruptions. We note the sensitivity of our results to volcanic sulfate aerosol microphysics and model chemistry.

This study investigates the impact of dust on radiation over the Arabian Peninsula (AP) during the reported high, low, and normal dust seasons (March–August) of 2012, 2014, and 2015, respectively. Simulations were performed using the Weather Research and Forecasting model coupled to a Chemistry module (WRF-Chem). The simulated seasonal horizontal and vertical dust concentrations, and their interannual distinctions, match well with those from two ground-based AERONET observations, and measurements from MODIS and CALIOP satellites. The maximum dust concentrations over the dust-source regions in the southern AP reach vertically upto 700 hPa during the high dust season, but only upto 900–950 hPa during the low/normal dust seasons. Stronger incoming low-level winds along the southern Red Sea and those from Iraq bring in higher-than-normal dust during the high dust summers. We conducted a sensitivity experiment by switching-off the dust module to assess the radiative perturbations due to dust. The results suggest that active dust-module improved the fidelity of simulated radiation fluxes distributions at the surface and top of the atmosphere vis-à-vis Clouds and the Earth's Radiant Energy System (CERES) measurements. Dust results in a 26 Wm−2 short-wave (SW) radiative forcing in the tropospheric-column over the AP. The SW radiative forcing increases by another 6–8 Wm−2 during the high dust season due to the increased number of extreme dust days, which also amplifies atmospheric heating. During extreme dust days, the heating rate exhibits a dipolar structure, with cooling over the Iraq region and warming of 40%–60% over the southern-AP.

The Great Arctic Cyclone 2012 (AC12) is used to understand the role of initial condition errors in the predictability at 2–3-day forecast range of a high-impact summer Arctic Cyclone (AC). Ensemble sensitivity analysis (ESA) is first performed to identify potentially sensitive regions of the cyclone evolution using an ensemble baseline forecast with conventional in situ observations assimilated. A pseudo-observation method is then introduced to investigate impacts of hypothetical observations in these sensitive but unobserved regions. In the baseline experiments with in situ observations assimilated, the forecasted AC12 reaches its peak intensity 18 hr earlier than in the verifying Global Forecast System Analysis (GFS-ANL) and the cyclone track is biased toward the southwest. Using ESA, the time of peak intensity and the cyclone track error are identified to be sensitive to the upstream trough, downstream ridge, and the tropopause polar vortex (TPV) to the northeast (NE TPV) of the AC12. These features were not observed by the in situ observation networks. To examine the impact of the observation gaps, pseudo-observations drawn from GFS-ANL are assimilated. Pseudo-observations sample the three features separately to study the impact of the initial condition error on the predictability of AC12. The cyclone peak intensity timing error and track error are greatly reduced when the initial condition error is reduced near the NE TPV. A southward expansion of the NE TPV and the corresponding southward shifting low-level front lead the forecasted AC12 to progress to the east, which better agrees with the verifying GFS-ANL.

We analyze the sources for spread in the response of the Northern Hemisphere wintertime stratospheric polar vortex (SPV) to global warming in Climate Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) model projections. About half of the intermodel spread in SPV projections by CMIP6 models, but less than a third in CMIP5 models, can be attributed to the intermodel spread in stationary planetary wave driving. In CMIP6, SPV weakening is mostly driven by increased upward wave flux from the troposphere, while SPV strengthening is associated with increased equatorward wave propagation away from the polar stratosphere. We test hypothesized factors contributing to changes in the upward and equatorward planetary wave fluxes and show that an across-model regression using projected global warming rates, strengthening of the subtropical jet and basic state lower stratospheric wind biases as predictors can explain nearly the same fraction in the CMIP6 SPV spread as the planetary wave driving (r = 0.67). The dependence of the SPV spread on the model biases in the basic state winds offers a possible emergent constraint; however, a large uncertainty prevents a substantial reduction of the projected SPV spread. The lack of this dependence in CMIP5 further calls for better understanding of underlying causes. Our results improve understanding of projected SPV uncertainty; however, further narrowing of the uncertainty remains challenging.

Anthropogenic CO2 emission reduction strategies depend on how well we track emission enhancements at the urban scale. The estimation system, based on inverse modeling, relies on our knowledge of atmospheric transport and prior flux distributions. Hence, the analysis framework must account for uncertainties associated with each component in order to interpret the variations in observed CO2. Using an ensemble of simulations, we quantify the uncertainties in simulating anthropogenic CO2 mixing ratio enhancements at 15 locations in India. Differences in the representation of transport mechanisms and prior emission in the forward model induce a consistently large model spread of 62.2% and 41.9%, respectively, in the simulated mixing ratio over cities. The analysis reports an average uncertainty of 2.2 ppm with a maximum of 8 ppm for representing diurnally averaged anthropogenic CO2 enhancement. Diurnal variations in emissions and transport induce a rectification effect in those enhancements. The outcome of this study can thus inform future atmospheric CO2 inversion modeling at an urban scale on the expected forward model uncertainties, which are the essential components in the Bayesian inversion framework, typically lacking in the Indian region. The first-order inversion experiments show that the change in the transport model induces significant uncertainty (up to 84.9%) in anthropogenic CO2 flux estimation at the national scale. Hence, the confidence level of inverse-based emission estimation in India depends considerably on the accuracy of atmospheric transport modeling.

The dominant influence of precession-induced changes in summer insolation on orbital-scale variability of the Asian summer monsoon (ASM) during the Holocene has been widely proposed; however, it remains unclear why the decline of the ASM started several thousand years after the peak summer insolation. Through comparisons of climate simulations and proxy records, our study reveals that the abrupt decline in the ASM coincided with an increase in spring insolation at the equator. The reduced spring insolation resulted in a cooler tropical Indian Ocean, which weakened and shifted northward the westerly jet due to decreased meridional thermal gradient. The South Asian high moved northward in conjunction with the westerly jet, causing anomalous upwards over northern South Asia, the Tibetan Plateau, as well as southwestern and northern China. The associated anomalous cyclone over the Tibetan Plateau enhanced the monsoonal moisture transport, subsequently intensifying the ASM circulation and precipitation. The ASM was enhanced by the decrease in spring insolation and was weakened by the opposite. The abrupt decline of the ASM was associated with an increase in spring insolation superimposed on a decrease in summer insolation. Consequently, orbital-scale ASM variability is dominated by the precession not only via insolation changes in summer but also changes in spring.

Entrainment and detrainment rates (ε and δ) constitute the most critical free parameters in mass flux schemes commonly employed for cumulus parameterizations. Recently, Zhu et al. (2021) introduced a new approach that utilizes aircraft observations to simultaneously estimate ε and δ for cumulus clouds, overcoming the limitation of other observation-based approaches that solely yield ε without offering insights into δ. This study aims to comprehensively evaluate the reliability of this new approach. First, evaluation using an Explicit Mixing Parcel Model demonstrates the capability of the new approach to back-calculate predetermined ε and δ based on the physical properties before and after the entrainment mixing. Second, evaluation using large-eddy simulations illustrates that the new approach yields consistent ε and δ profiles compared to the traditional approach. Sensitivity tests indicate a weak sensitivity of the estimated δ with the new approach to the entrained air source. A decrease in the proportion of cloudy air in the assumed detrained air leads to a reduction in the estimated δ, while ε remains unaffected. Finally, the most appropriate assumptions for entrained and detrained air are discussed. Estimating ε for cumulus parameterizations involves acquiring ambient air more than 500 m away from the cloud edge as entrained air. Due to implicit mean field approximations in the traditional approach, determining the optimal assumption for detrained air properties proves challenging. This study confirms the reliability of the new approach in estimating ε and δ, providing confidence in its application to extensive observational data and advancement in parameterization.

Understanding how aerosols affect cloud cover is critical for reducing the large uncertainty of the aerosol-cloud interaction (ACI). The 2014 Holuhraun effusive eruption in Iceland resulted in a significant increase in cloud drop number concentration (N d ) relative to the climatological N d observed during periods of relatively infrequent volcanic activity. Previous studies show a significant “Twomey” effect during this eruption; however, aerosol-induced changes in cloud fraction (Cf) appeared negligible. This leads to the question of why changes in aerosols do not cause Cf changes. To address this question, prediction models were derived to predict Cf based on N d and meteorological parameters. These validated models allow us to investigate aerosol perturbations on Cf in various N d scenarios by controlled meteorological conditions. Here our analysis unveiled that the increase in N d was primarily observed under polluted conditions where N d surpassing the threshold of 60 cm−3. After this point, cloud cover stops increasing even as N d increases. On the contrary, the cloud cover did increase by 9.0% under conditions of clean backgrounds (N d  < 60 cm−3). Accordingly, the aerosol-driven cloud adjustment is hidden behind the seemingly insignificant cloud cover effect in areas with large background N d . These findings provide insights into the importance of considering background N d and the saturation status of cloud covers in ACI studies.

Researchers have recently focused on the interplay of the urban heat island (UHI) effect and heat waves (HWs). However, the synergies of these two phenomena remains inconclusive at present. To address this gap, this study investigated UHIs and HWs synergies during the last 30 years in the Tokyo metropolitan area, through a unique and novel approach named Land-Surface-Physics-Based Downscaling (LSP-DS). LSP-DS integrates the widely used Noah-Multiparameterization (Noah-MP) land-surface model coupled with urban canopy-process physics, aiming to conduct high-resolution, long-term urban-specific simulations with much less computational resources. Our comprehensive analysis combining observation data and numerous LSP-DS simulations confirms exacerbated UHIs during HWs. Specifically, HWs amplify the temperature differences between urban and rural environments, which is quantified by UHI intensity (UHII). During HWs, UHII increased more at night in inland areas and more during daytime in coastal areas. HWs present especially a heightened threat to coastal regions where daytime UHII increased by approximately 1°C during HWs. The Bowen ratio can explain the increase in the daytime UHII, and the daytime accumulated storage heat increase during HWs can explain the increase in nighttime UHII. Based on future projections of the increasing frequency of high temperatures, our findings highlight the impending heat-related health challenges faced by urban residents.