JGR–Atmospheres

The physicochemical properties and origins of atmospheric aerosols in the Tibetan Plateau (TP) region are a research topic of great interest, but an in-depth understanding of this topic is challenging, partially due to a lack of intensive in situ observations. Thus, a field campaign was conducted over Yadong, a remote area on the south slope of the TP from June 11 to 31 August 2021. The aerosol loading was low, with a black carbon mass concentration of 147.4 ± 98.4 ng·m−3. Aerosol single-scattering albedo was low (0.73 ± 0.11 at 550 nm) and increased from 450 to 700 nm wavelength. Organic matter (OM) accounting for 69.6% of the total aerosol mass and relatively high secondary organic carbon ratios, highlighting the importance of secondary formation. An interesting phenomenon observed was that the evolution of aerosols was mainly characterized by diurnal variation, which could not be explained by large-scale atmospheric processes such as Indian summer monsoon. Instead, it was found that regional mountain-valley winds between the Himalayas and South Asia transported polluted air masses toward the TP, especially in the afternoon when regional valley wind are expected to be the strongest and the boundary layer in South Asia is deepest. Additionally, daytime local valley wind further elevated these aerosols to higher altitudes on the TP. This paper provides insights into the transport mechanisms of aerosols from South Asia to the TP. These findings are of great importance since aerosols exhibit significant diurnal variations in the TP region.

Stratospheric ozone intrusions can have a significant impact on regional near-surface ozone levels. Especially in summer, intrusions can contribute to extreme ozone events because of preexisting high ozone levels near the surface and cause serious health issues. Considering the increasing trend of surface ozone level, an understanding of stratospheric ozone intrusion is necessary. From a 19-year Whole Atmosphere Community Climate Model, version 6 simulation and a stratospheric origin ozone tracer, we identify the global hotspots of stratospheric intrusions based on extreme tracer concentrations near the surface: North America, Africa, the Mediterranean, and the Middle East. We investigate the common underlying large-scale mechanisms of the stratospheric intrusions over the identified hotspots from the lower stratosphere to the lower troposphere. From the trajectory analysis, we find that the upper-level jet drives isentropic mixing near the jet axis and initiates stratospheric ozone intrusion. Subsequently, climatological descent at the lower troposphere brings the ozone down to the surface, which explains the spatial preference of summertime stratospheric intrusion events.

In water vapor-sensitive satellite imagery, small-scale wave-like perturbations of brightness temperature can be attributed to the presence of trapped internal waves in the troposphere. We present a method for detecting these local perturbations with wavelengths of about 10 km and apply it to imagery from the Advanced Baseline Imager on board the geostationary satellite GOES-16. The algorithm allows us to analyze 4 years of sub-hourly data in the southern part of the tropical eastern Pacific, where only a relatively low amount of medium and high clouds obscures the scene. By combining a measure of wave activity/trapping with ERA5 reanalysis data, we connect the occurrence of trapping with the presence of an increased upper-tropospheric wind shear. This connection is more evident during December, January and February, when upper-tropospheric jets are more likely. Our work supports existing case and model studies and is a step forward in the statistical and automated analysis of trapped small-scale internal waves in the atmosphere.

The soil surface wind friction velocity (u s*) is an essential parameter for predicting sediment transport on rough surfaces. However, this parameter is difficult and time-consuming to obtain over large areas due to its spatiotemporal heterogeneity. The albedo-based approach calibrates normalized shadow retrieved from any source of albedo data with laboratory measurements of aerodynamic properties. This enables direct and cross-scale u s* retrieval but has not been evaluated against field measurements for different cover types. We evaluated the approach's performance using wind friction velocity (u *) measurements from ultrasonic anemometers. We retrieved coincident field pyranometer and satellite albedo at 48 sites that were spread over approximately 1,800 km on the Inner Mongolia Plateau, including grassland, artificial shrubland, open shrubland, and gobi land. For all cover types, u * estimates from ultrasonic anemometers were close to the albedo-based results approach. Our results confirm and extend the findings that the approach works across scales from lab to field measurements and permits large-area assessments using satellite albedo. We compared the seasonal sediment transport across the region calculated from albedo-based u s* with results from an exemplar traditional transport model (Q T ) driven by u * with aerodynamic roughness length varying with land cover type and fixed over time. The traditional model could not account for spatiotemporal variation in roughness elements and considerably over-estimated sediment transport, particularly in partially vegetated and gravel-covered central and western parts of the Inner Mongolia Plateau. The albedo-based sediment transport (Q A ) estimates will enable dynamic monitoring of the interaction between wind and surface roughness to support Earth System models.

Increasing the horizontal resolution of an ocean model is frequently seen as a way to reduce the model biases in the North Atlantic, but we are often limited by computational resources. Here, a two-way nested ocean model configuration (VIKING10) that consists of a high-resolution (1/10°) component and covers the northern North Atlantic, is embedded in a 1/2° ocean grid as part of the global chemistry-climate model, FOCI (called FOCI-VIKING10). This configuration yields a significantly improved path of the North Atlantic current (NAC), which here reduces the North Atlantic cold bias by ∼50%. Compared with the coarse-resolution, non-eddying model, the improved thermal state of upper ocean layers and surface heat fluxes in a historical simulation based on FOCI-VIKING10 are beneficial for simulating the subdecadal North Atlantic Oscillation (NAO) variability (i.e., a period of 8 years). A northward drift of the NAO-forced ocean thermal anomalies as seen in observations and the eddying FOCI-VIKING10, provide a lagged ocean feedback to the NAO via changes in the net surface heat flux, leading to the NAO periodicity of 8 years. This lagged feedback and the 8 years variability of the NAO cannot be captured by the non-eddying standard FOCI historical simulation. Furthermore, the argumentative responses of the North Atlantic to the 11-year solar cycle are re-examined in this study. The reported solar-induced NAO-like responses are confirmed in the 9-member ensemble mean based on FOCI but with low robustness among individual members. A lagged NAO-like response is only found in the nested eddying simulation but absent from the non-eddying reference simulation, suggesting North Atlantic biases importantly limit climate model capability to realistically solar imprints in North Atlantic climate.

The unprecedented 2022 Yangtze River Basin (YRB) heatwave is a threat to human society and natural ecology, so the understanding of its underlying drivers is critical to regional climate adaptation and resilience. Here we conducted a multi-method attribution analysis on the contribution of atmospheric circulation change and anthropogenic impacts to the occurrence probability and intensity of this extreme heatwave. Based on the nonstationary statistical analysis, the 2022 YRB heatwave is a 1-in-900-year event and a 1-in-110-year event with and without considering the 2022 YRB heatwave in the fitting, respectively. The large-scale meteorological condition analysis shows that the 2022 YRB heatwave is featured with an anomalous high-pressure system that favors a hot and dry atmospheric column, overlaid by anomalous subsidence and clear skies which leads to warming and greater solar heating. The ensemble constructed circulation analogue analyses show that the circulation anomaly fails to explain the observed 2022 YRB SAT anomalies fully. Specifically, 46% (0.132 ± 0.027°C decade−1) of the observed SAT trend during 1979–2022 (0.290 ± 0.048°C decade−1) is caused by anthropogenic warming and the associated thermodynamic feedback, while the remaining 54% (0.157 ± 0.038°C decade−1) of the trend is caused by changes in the large-scale atmospheric circulation. Our findings on changes in atmospheric circulation patterns associated with YRB heatwave and anthropogenic contributions to YRB heatwave could provide valuable information for climate adaptation and mitigation strategies in the context of a warming climate.

Most tropical cyclone (TC) forecasting centers have implemented a probabilistic circle to represent track uncertainty at a specified lead time. Recent studies suggest that probability ellipses constructed from ensemble prediction systems can convey the anisotropy of track predictability. In this study, a new probability ellipse model is developed to interpret the extent of forward speed and heading uncertainties in ensemble forecasts by selecting an equal proportion of members in the along- and cross-track directions. This method is validated using the 2019–2021 western North Pacific (WNP) TC track forecasts from the ensemble predictions of the European Centre for Medium-Range Weather Forecasts, the United States National Centers for Environmental Prediction, and the Korea Meteorological Administration. When the proportion of ensemble members in the ellipse is set to 70%, more than one-half (50.0%–73.6%) of the forecasts, depending on the lead time, indicate reduced area compared with that of the circle. The mean areas of the probability ellipses are 4.9%, 7.0%, 10.0%, and 11.5% smaller than those of the circle in 48-, 72-, 96-, and 120-hr forecasts, respectively. The forward speed shows greater uncertainty than the heading, as evidenced by the along-track radii being larger than the cross-track counterpart in ∼60% of the samples, regardless of the lead time. In addition, the regional distribution of the along-track/cross-track ratio in the probability ellipses can explain the dominant direction of the track error in a particular location. The proposed probability ellipse shows potential for application in operational TC track predictions.

Streamflow flash droughts (SFDs), characterized by a rapid decline in streamflow over a relatively short period, affect water availability, hydropower generation, and the ecosystem. However, atmospheric and land processes that drive SFDs in the monsoonal climate of India remain unexplored. Using observations, reanalysis data sets, and model simulations, we examined the critical drivers of SFDs in 64 catchments in India during the 1971–2018 period. We identified meteorological flash droughts (MFDs) using precipitation and SFDs using in situ observations and model simulations of streamflow. We show that precipitation deficit and anomalous high temperature, driven mainly by the summer monsoon breaks, lead to the development of MFDs. Antecedent baseflow conditions play a major role in the propagation of MFDs to SFDs. Favorable atmospheric conditions (driven by the monsoon breaks) cause MFDs, which translate to SFDs. High and low baseflow conditions limit the rapid decline in streamflow, which controls the occurrence of streamflow flash drought. On the other hand, favorable atmospheric conditions combined with moderate baseflow can trigger SFDs in India during the summer monsoon season. Moreover, humid catchments are more prone to propagation from MFDs to SFDs during the monsoon season in India. Understanding the crucial role of atmospheric and land drivers can assist in examining the occurrence of streamflow flash drought with implications for water resources planning and management.

Ocean surface rain layers (RLs) form when relatively colder, fresher, less dense rain water stably stratifies the upper ocean. RLs cool sea surface temperature (SST) by confining surface evaporative cooling to a thin near-surface layer, and generate sharp SST gradients between the cool RL and the surrounding ocean. In this study, ocean-atmosphere coupled simulations of the November 2011 Madden-Julian Oscillation (MJO) event are conducted with and without RLs to evaluate two pathways for RLs to influence the atmosphere. The first, termed the “SST gradient effect,” arises from the hydrostatic adjustment of the boundary layer to RL-enhanced SST gradients. The second, termed the “SST effect,” arises from RL-induced SST reductions impeding the development of deep atmospheric convection. RLs are found to sharpen SST gradients throughout the MJO suppressed and suppressed-to-enhanced convection transition phases, but their effect on convection is only detected during the MJO suppressed phase when RL-induced SST gradients enhance low-level convergence/divergence and broaden the atmospheric vertical velocity probability distribution below 5 km. The SST effect is more evident than the SST gradient effect during the MJO transition phase, as RLs reduce domain average SST by 0.03 K and narrow vertical velocity distribution, thus delaying onset of deep convection. A delayed SST effect is also identified, wherein frequent RLs during the MJO transition phase isolate accumulated subsurface ocean heat from the atmosphere. The arrival of strong winds at the onset of the MJO active phase erodes RLs and releases subsurface ocean heat to the atmosphere, supporting the development of deep convection.

No abstract is available for this article.

Stratospheric aerosol injection (SAI) is suggested as a potential measure for alleviating global warming. The potential effects of SAI on global temperature and precipitation have been extensively discussed, but its impact on drought has received little attention. Based on the simulations from the G6sulfur experiment that employs SAI to reduce the global mean surface temperature from the level of high-tier forcing (Shared Socioeconomic Pathways SSP5-8.5) scenario to that of medium-tier forcing (SSP2-4.5) scenario, we investigate the drought response to SAI via the standardized precipitation evapotranspiration index. During 2081–2100, SAI effectively offsets the greenhouse gas-induced aridity trend by increasing the climate water balance at the global scale. Drought duration and severity decrease but drought frequency increases under SAI forcing. Robust wetting responses occur over most regions, especially the Sahara, South America, southern Africa and Australia, while Alaska, Greenland, Southeast Asia, and tropical Africa face enhanced drought due to SAI. Relative to the SSP2-4.5 scenario, the regional drying and wetting patterns in G6sulfur are remarkably different. Notably, in tropical Africa, SAI reverses the wetting caused by greenhouse gases and induces severer drought. The drought pattern changes are largely due to evaporative demand alterations caused by the vapor pressure deficit response.

Due to limited direct measurements, regional or global terrestrial evapotranspiration (ET) is generally derived from a combination of meteorological and satellite observations. Although the inhomogeneity of the observed climate data has been widely reported, its impact on the calculated ET has not been adequately quantified. This study aimed to calculate ET using the modified Penman-Monteith (MPM) model with raw and homogenized meteorological data. Additionally, we compared the calculated ET with those estimates from variable methods (water balance, satellite-based, and reanalysis) in China and its six major river basins from 1982 to 2020. During the overlapping period of 1997–2018, ET calculated from raw input data decreased slightly at −0.39 mm yr−2 (p = 0.64) in China, whereas homogenized ET showed a significant increasing trend of 0.93 mm yr−2 (p = 0.02), with a better agreement with water balance ET (1.93 mm yr−2, p = 0). Global Land Evaporation Amsterdam Model (GLEAM) and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2) could reproduce the increasing trends with 2.08 mm yr−2 (p = 0) and 2.59 mm yr−2 (p = 0). The intercomparison of input variables (solar radiation, relative humidity, wind speed, precipitation, and air temperature) among ET products revealed substantial differences, which can account for the discrepancies in ET estimates. Homogenized ET, GLEAM and MERRA2 exhibited significant increasing trends in China and most river basins from 1982 to 2020. Our findings underscore the importance of utilizing homogenized input data for more accurate ET estimation.

The reproducibility of Atmospheric General Circulation Model (AGCM) results in the current climate was evaluated to assess annual and monthly mean climate values from a hydrological perspective and to elucidate factors affecting them. Reproducibility was confirmed for precipitation, air temperature, and runoff, which were compared with basin-average values to describe deviations in reproduced AGCM data. AGCMs have been successively applied over 65 years in the current climate, and annual mean values of precipitation generally have a positive bias in most basins and those of air temperature have a negative bias. However, runoff shows no clear pattern of bias. For monthly means, precipitation has positive and negative biases in July in the Northern Hemisphere. In January in the Southern Hemisphere, precipitation has a positive bias. In both months, air temperature has a negative bias. Factors contributing to this bias are discussed. From a hydrologic perspective, the annual mean bias in air temperature performs better in explaining the apparent evapotranspiration (i.e., precipitation minus runoff) than the bias in precipitation. In the tropics, the air temperature bias has a correlation coefficient of −0.176 with the precipitation bias and −0.406 with apparent evapotranspiration (negative values indicate a better correlation). However, this was not the case for the monthly average air temperature bias, possibly because of climatological influences or the inadequate representativeness of runoff in land surface models. The results show that runoff bias may contribute to air temperature bias. Accordingly, we propose a new method for comparing runoff bias and climate bias.

We use high temporal-resolution mesoscale imagery from the Geostationary Operational Environmental Satellite-R (GOES-R) series to track the Lamb and gravity waves generated by the 15 January 2022 Hunga Tonga-Hunga Ha'apai eruption. The 1-min cadence of these limited area (∼1,000×1,000 km2) brightness temperatures ensures an order of magnitude better temporal sampling than full-disk imagery available at 10-min or 15-min cadence. The wave patterns are visualized in brightness temperature image differences, which represent the time derivative of the full waveform with the level of temporal aliasing being determined by the imaging cadence. Consequently, the mesoscale data highlight short-period variations, while the full-disk data capture the long-period wave packet envelope. The full temperature anomaly waveform, however, can be reconstructed reasonably well from the mesoscale waveform derivatives. The reconstructed temperature anomaly waveform essentially traces the surface pressure anomaly waveform. The 1-min imagery reveals waves with ∼40–80 km wavelengths, which trail the primary Lamb pulse emitted at ∼04:29 UTC. Their estimated propagation speed is ∼315 ± 15 m s−1, resulting in typical periods of 2.1–4.2 min. Weaker Lamb waves were also generated by the last major eruption at ∼08:40–08:45 UTC, which were, however, only identified in the near field but not in the far field. We also noted wind effects such as mean flow advection in the propagation of concentric gravity wave rings and observed gravity waves traveling near their theoretical maximum speed.

Non-methane hydrocarbons (NMHCs) are ubiquitous trace gases and profoundly affect the Earth's atmosphere and climate change. Mixing ratios of light NMHCs were measured over the northern Indian Ocean during winter-2018 as part of the Integrated Campaign for Aerosols, gases, and Radiation Budget (ICARB-2018). Higher levels of NMHCs over the coastal regions were due to the efficient transport of anthropogenic and biogenic air masses and higher air-sea exchanges due to the higher biological productivity. Although oceanic emissions dominated the open ocean, the transport of aged continental air also influenced the levels of some NMHCs. The higher and lower propane/ethane ratios of 2.41 ± 0.34 and 1.13 ± 0.78 ppbv ppbv−1 over coastal and open oceans indicated the prevalence of fresh and aged air masses, respectively. Ethene and propene show a strong correlation, but the ethene/propene ratios over open ocean (2.2 ± 0.25 ppbv ppbv−1) were slightly lower than the coastal region (2.5 ± 0.34 ppbv ppbv−1). Principal component analysis reveals the major associated sources identified in this study are from oceanic and nearby anthropogenic sources, explaining nearly 51% and 21% of variance. Light alkenes accounted for ∼70% of the total ozone and secondary organic aerosol formation potential. A higher alkene/alkane ratio, strong correlation of alkene with organic aerosol mass, and new particle formation events highlight the role of alkenes in secondary aerosol formation over the equatorial Indian Ocean. Overall, the levels of NMHCs were much higher than those measured nearly two decades ago during the Indian Ocean Experiment (INDOEX)-1999.

Recent findings showed that midlatitude oceanic fronts in the Kuroshio-Oyashio Extension (KOE) region may significantly influence the overlying atmosphere on the decadal timescale. However, the exact mechanism and the combined effects of both the Kuroshio Extension Front (KEF) and the Oyashio Extension Front (OEF) are still largely unknown. Here we use front-resolving ERA5 reanalysis data to investigate the characteristics and mechanisms of the atmospheric response to decadal fluctuations of the KEF and OEF in a consistent way. It is found that the atmospheric response is equivalent barotropic with upper-level intensification in terms of both basic flow and storm track. The geopotential height and storm track responses over western subpolar North Pacific are of opposite signs driven by intensifying KEF and OEF. Diagnosis showed that eddy vorticity feedback is responsible for the basic flow response at upper levels, whereas direct linear response to surface thermal forcing dominates at lower levels. The upper-level eddy response is realized by midlevel diabatic conversion which is forced by changes of near-surface background baroclinicity. In total, the decadal modulation by the KEF and OEF explains 19% (12%) of the variance of geopotential height (storm track) variability at 250 hPa (500 hPa), which is much higher than found in previous studies, presumably due to the higher resolution and the consideration of both fronts.

Arctic cyclone activity is an important component of the local climate, and the frequent occurrence of extreme summer storms has raised widespread scientific interest. In this paper, we investigated the distinctive structural characteristics of intense summer Arctic cyclones by utilizing ERA-Interim reanalysis data and employing a deep learning algorithm for cyclone detection. We found that the northern edge of Eurasia (i.e., the marginal ice zone (MIZ)) and the Alpha Ridge of Arctic Ocean (AR, i.e. central Arctic) are the two most active regions for intense Arctic cyclone activities in summer (from June to September). However, the surface conditions and coupling frequency between surface cyclone and tropopause polar vortices (TPVs) are distinct over these two regions. By further analysis of 100 intense cyclone activities in these two areas, respectively, we found that cyclones in MIZ are often smaller in size but higher in intensity at their maximum intensity, and their life cycles are generally shorter. MIZ cyclones are typically accompanied by a large Eady growth rate and frontal structure in the lower troposphere and their intensification primarily attributed to the thermal-baroclinic process. In contrast, cyclones in AR are more frequently associated with higher potential vorticity (PV) values and pronounced PV downward intrusion from the stratosphere, as well as notable “upper warm-lower cold” structures. The downward intrusion of TPVs and stratosphere vortices contribute to a decrease in the upper and column air mass deficit, leading to the intensification of surface Arctic cyclones in these regions.

The Amazon Basin, which plays a critical role in the carbon and water cycle, is under stress due to changes in climate, agricultural practices, and deforestation. The effects of thermodynamic and microphysical forcing on the strength of thunderstorms in the Basin (75–45°W, 0–15°S) were examined during the pre-monsoon season (mid-August through mid-December), a period with large variations in aerosols, intense convective storms, and plentiful flashes. The analysis used measurements of radar reflectivity, ice water content (IWC), and aerosol type from instruments aboard the CloudSat and CALIPSO satellites, flash rates from the ground-based Sferics Timing and Ranging Network, and total aerosol optical depth (AOD) from a surface network and a meteorological re-analysis. After controlling for convective available potential energy (CAPE), it was found that thunderstorms that developed under dirty (high-AOD) conditions were 1.5 km deeper, had 50% more IWC, and more than two times as many flashes as storms that developed under clean conditions. The sensitivity of flashes to AOD was largest for low values of CAPE where increases of more than a factor of three were observed. The additional ice water indicated that these deeper systems had higher vertical velocities and more condensation nuclei capable of sustaining higher concentrations of water and large hydrometeors in the upper troposphere. Flash rates were also found to be larger during periods when smoke rather than dust was common in the lower troposphere, likely because smoky periods were less stable due to higher values of CAPE and AOD and lower values of mid-tropospheric relative humidity.

In this study, we identified heat index-based spatiotemporally contiguous heatwaves (HI-STHWs) in China based on meteorological observations and Coupled Model Intercomparison Project Phase 6 global climate model simulations. We analyzed the spatiotemporal patterns of changes in HI-STHWs in the past and future and quantitatively attributed these changes to anthropogenic activities. The results show that the duration, severity, average, maximum, and total impacted area of the annual strongest HI-STHWs during the present period of 1991–2014 are 1.77, 2.0, 1.05, 1.14, and 1.89 times the historical period of 1961–1990, respectively. In the fingerprint results, the anthropogenic greenhouse gases (GHG) signal is significantly detected, while the aerosol (AER) and natural (NAT) signals are not. GHG is the primary factor driving the intensification of HI-STHWs, which alone explains about 130%, 122%, 112%, 111%, and 114% of the above changes. The reason for GHG contribution exceeding 100% is that AER might have a negative contribution although nonsignificant. In the future warming climate, anthropogenic activities are projected to lead to more unprecedented HI-STHWs. Under the high emissions scenario of SSP585, by 2100, the annual strongest HI-STHW in China is projected to last almost the whole year and influence 96% regions of China in the most serious day. Meanwhile, its duration and total impacted area are 24.5 [17.2, 31.6] (90% confidence interval) and 107.2 [70, 129.9] times the preindustrial period. However, if the warming level could be limited to 2/1.5°C, those values would be 3.4/5.4 and 8.2/16.2 times smaller than that under the SSP585 scenario by 2100.

Urban morphological change impacts the land surface temperature (LST) through modifying the net radiation, convective heat transfer, evapotranspiration, and heat storage on the ground. It is essential to quantify the contributions of these physical changes on LST changes. In this work, we conduct simulations using a weather research and forecasting model for the Chengdu–Chongqing urban agglomeration to identify causes of LST changes due to urban morphological changes through different morphological parameters: the aspect ratio, building plan area fraction, and average building height. A new method is proposed and used to quantify the contribution of these physical changes on LST changes. The results show as the aspect ratio increases, an increase of the average LST is induced by variations in radiation, and daytime cooling and nighttime warming are induced by variations in heat storage. There is warming associated with an increase in the building plan area fraction, which is mostly caused by a decrease in the efficiency of the long-wave radiant heat emitted from the surface to the atmosphere. We also find that an increase in the average building height enhance the efficiency of convective heat transfer, which results in cooling. These results are important for the management of urban thermal environments.