Journal of Geophysical Research: Atmospheres最新文献

Sustained near-surface ozone pollution despite stringent emission controls in China has drawn wide attention. However, how such rapid regional emission reductions affect global tropospheric ozone remains unexplored. Here, using an ensemble of measurements and global model simulations, we find Chinese emission reductions during 2013–2020 have increased domestic surface ozone; particularly in North China, they have decreased the global tropospheric ozone burden by 2.7 Tg (54% of China's anthropogenic contribution and 7% of global anthropogenic contribution in 2019) and ozone radiative forcing by 8.8 mW m⁻² (64% of China's anthropogenic contribution and 9% of global anthropogenic contribution in 2019). Nitrogen oxides (NO_x) associated nonlinear chemistry and height-dependent atmospheric transport patterns primarily cause the contrasting impacts. Future Chinese NO_x emission controls would continue to decrease global tropospheric ozone, while regional surface ozone may still increase unless NO_x reductions exceed ∼53% of the 2019 level. Our results reveal the substantial benefit of regional emission reductions in China on global tropospheric ozone mitigation.

Dust emissions from land-air interaction in arid and semi-arid regions are crucial for predicting the global dust cycle. However, a comprehensive understanding of the complex physical mechanisms contributing to dust emissions from Gobi surfaces remains elusive. The expansive Gobi Desert, spanning northern China and Mongolia, significantly intensifies sandstorms in East Asia. Although researchers use models to study global dust transport, current models primarily depend on the aerodynamic roughness of the Gobi Desert. They often overlook the particle-bed collision processes unique to the Gobi bed surface, which differ significantly from those of desert surfaces, thus compromising the accuracy of global dust cycle simulations. In this article, we establish a numerical model for drift sand in the Gobi based on existing theoretical and experimental studies. The model accurately simulates the wind-blown sand in the Gobi and been used to investigate the saltation structure of sand transport. Simulations reveal an exponential decay of mass concentration with height, with an average attenuation rate of 0.00385 in the Gobi compared to 0.00806 in sandy deserts. The horizontal velocity of saltating particles increases with height following a power law. Through quantitative analysis of this structure, we present a saltation flux formula suitable for the Gobi.

Integrated measurements of aerosol, radiation, cloud, and turbulent transport in the planetary boundary layer (PBL) are essential for understanding and modeling climate and air quality. Here, we developed a new technique for the identification of convective turbulent regions and deriving the vertical distribution of aerosol turbulent mass fluxes within PBL. The algorithm uses retrievals from coherent Doppler lidars and a high spectral resolution lidar. The technique was applied to study particle mass fluxes over 2 months (November–December 2020) during the campaign conducted at the DOE Atmospheric Radiation Measurement Southern Great Plains (SGP) site in Lamont, Oklahoma. The algorithm developed here is capable of continuously deriving vertically resolved (curtains) aerosol mass fluxes. Our data analysis shows that at the site, the 30-min averaged fluxes at 135 m above the surface were mainly positive (upward) at ∼1 μg m⁻² s⁻¹, suggesting that the surface is the primary source of the particle mass supplied to the boundary layer at the SGP site. Analyses of the individual case studies have revealed that not all the derived fluxes can be linked to surface emissions. Both positive and negative values in a range of ±5 μg m⁻² s⁻¹ can be caused by convective thermals interacting between the residual layer and the mixed layer and by rotation of the horizontal wind with the height. Large erroneous negative fluxes can also be caused by drizzling/precipitating clouds. We anticipate that the application of the current technique will lead to a more realistic representation of aerosol mass budgets and bidirectional mixing rates.

Accurate fog prediction in densely urbanized cities poses a challenge due to the complex influence of urban morphology on meteorological conditions in the urban roughness sublayer. This study implemented a coupled WRF-Urban Asymmetric Convective Model (WRF-UACM) for Delhi, India, integrating explicit urban physics with Sentinel-updated USGS land-use and urban morphological parameters derived from the UT-GLOBUS dataset. When evaluated against the baseline Asymmetric Convective Model (WRF-BACM) using Winter Fog Experiment (WiFEX) data, WRF-UACM significantly improved urban meteorological variables such as diurnal variations in 10-m wind speed, 2-m air temperature (T2), and 2-m relative humidity (RH2) during a fog event. UACM also demonstrates improved accuracy in simulating temperature and significantly reducing biases for wind speed and daytime RH2 under clear sky conditions. UACM reproduced the nighttime urban heat island effect within the city, showing realistic diurnal heating and cooling patterns that are important for accurate fog onset and duration. UACM effectively predicts the onset, evolution, and dissipation of fog, aligning well with observed data and satellite imagery. Compared to WRF-BACM, WRF-UACM reduces the cold bias soon after sunset, thus improving the fog onset error by ∼3 hr. This study highlights the UACM's potential to improve fog prediction and its application in operational settings. With further investigation into different fog types, the UACM can provide crucial insights for preventive measures and reducing disruptions in urban areas.

Using a 30–250 MHz VHF interferometer, we observed a previously unreported mode of initial lightning development inside thunderclouds. This mode is defined by continuous VHF radiation spanning several km within the first few milliseconds of lightning initiation. Following flash initiation through fast positive breakdown at high altitudes above 9 km, the VHF radiation front of upward negative streamers ascended continuously at a speed of ∼1.0 × 10⁶ m/s, forming a continuous initial breakdown burst (CIBB) about 2 km in length. For the two CIBBs analyzed, the long and narrow CIBB channel was traversed by dart leaders that occurred later in the flash, indicating that the CIBB channel belongs to what becomes the main conducting leader channel. In contrast to classic initial breakdown pulses (IBPs) with sub-pulses superimposed on the rising edge, CIBBs produced a series of discrete, narrow LF pulses (<10 μs) with an average time interval of 0.20 and 0.14 ms, respectively. We speculate that a CIBB is a continuously developing negative streamer system in the high electric field region at high altitudes, with connections of internal plasma channels producing LF pulses. These results have implications for physical conditions conducive to the formation of a long and continuous negative streamer system.

In the year 2019, the middle and lower reaches of the Yangtze River (MLRYR) experienced an unprecedented summer-autumn drought (SAD) driven by dry-hot conditions [high near-surface air temperatures (T) and low precipitation (P)], causing substantial agricultural and economic losses. However, the influence of anthropogenic climate change (ACC) on these dry-hot conditions and their impacts on SAD occurrences remains uncertain. Here, both observations and simulations show that an ACC-driven T increase led to the greater likelihood of dry-hot conditions from August to November 1901–2020 in MLRYR. Using the self-calibrating Palmer drought index (scPDSI) to assess SAD severity, we find an increasing likelihood of SAD occurrence (from 33.3% in 1901–2000 to 85.7% in 2001–2020) in MLRYR associated with more frequent dry-hot conditions. Under a business-as-usual scenario, future dry-hot association is projected to be stronger, with exceptional dry-hot conditions to increase by +10% per century. ACC-induced increase in dry-hot conditions would elevate the likelihood of SAD events like the 2019 event from 1.59% (1961–2020) to 17.82% (2041–2100). Therefore, effective measures are needed in MLRYR to adapt to increasing dry-hot conditions and associated SAD occurrences under anthropogenic warming.

It has been proven that assimilating winds from the Aeolus global Doppler Wind Lidar (DWL) would enhance the predictive skill of weather forecast models. In this study, we use a series of observing system experiments to examine how currently assimilated “operational” wind products and Aeolus winds impact environment and climate change Canada's global forecast system over the data-sparse Arctic region. Aeolus winds improve the tropospheric wind and temperature forecasts by about 0.7%–0.9% of error reduction (a 15%–20% effect compared to the impact of operational wind products) while having little impact on specific humidity. In particular, Aeolus winds have an impact on forecasts of strong wind days on the wind and temperature fields that is double the impact for weaker wind days. On the other hand, the operational wind products do not show as large a discrepancy in impact between forecasts of disturbed and normal days. These findings suggest significant potential for global DWL observations to enhance severe weather prediction in polar regions.