Journal of Geophysical Research: Atmospheres最新文献

This study reveals the significant Quasi-Biennial Oscillation (QBO) influences on the seasonal atmospheric river (AR) climatology around the globe. The North Pacific (NP) AR climatology in the boreal winter to early fall seasons in a QBO easterly (QBOE) phase is systematically shifted poleward compared with those in a QBO westerly (QBOW) phase, and such difference peaks in the local late spring season. We also find the similar poleward shift for the AR climatology over the South Pacific (SP) in the austral winter seasons in the QBOE phase. A significant equatorward shift and an overall enhancement of the AR climatology over the SP are observed in the QBOE phase during local spring and summer seasons, respectively. The QBO impacts on the AR climatology over the Atlantic Ocean are less organized. Strong QBO impacts exist in almost all seasons for the North Atlantic AR but only in the austral spring season for the South Atlantic AR. These QBO modulations of the AR climatology over the ocean basins also change the season-mean AR frequencies around coastal regions, suggesting significant QBO impacts on the local land-falling AR events. The QBO modulations of the seasonal background mean states and the MJO-teleconnections are two potential mechanisms mostly over the north hemisphere. The QBOE modulation of the Madden-Julian Oscillation (MJO)-teleconnection over the northern hemisphere is asymmetric between the MJO convection over the Indian Ocean and that over the Pacific Ocean, which is the key to explain the QBO influences on the AR activity on the seasonal timescale.

Arctic surface temperature rising has been three times faster than the globe, referred to as the Arctic amplification (AA). However, the changes of boreal summer rainfall in eastern China and associated physical mechanisms during the AA period are still under investigation. In this study, we explored the boreal summer meridional quadrupolar rainfall changes in eastern China during the AA period, distributed as positive-negative-positive-negative anomaly pattern form north to south in eastern China. This pattern is significantly linked with the heterogeneous variations of the polar front jet (PJ) and subtropical jet (SJ), as the PJ displaced poleward over the Eurasia and the SJ displaced equatorward from the North Atlantic to East Asia. Such movement of different branches of jets are referred as the wavier jets that can be maintained by the negative phase of East Atlantic-Europe Pacific teleconnection (−EAUP), which might be associated with the positive phase of the Victoria mode over the North Pacific, the tripole sea surface temperature mode over the North Atlantic, and the reduction of sea ice concentration over Arctic. This study has emphasized the role of the heterogeneous variations of PJ and SJ playing on boreal summer quadrupolar rainfall changes in eastern China during the AA period.

Marine droplets, as the largest natural aerosol source after sand and dust, can have a significant impact on climate change, air pollution, typhoons, and other disaster weather. At present, due to the lack of observational data and insufficient understanding of turbulent transport processes in the air-sea boundary layer, there is considerable uncertainty in the generation function of sea spray droplets, especially for droplets with a particle size greater than 20 μm, most of the generation functions underestimate them. The multiple experiments on observing droplets were conducted in the air-sea boundary layer using a self-developed droplet spectrometer. The concentration and upward velocity of large droplets with particle sizes ranging from 25μm to 1.6 mm were obtained. The sea spray generation function was analyzed using the observed data, and the results showed that the sea salt aerosol (SSA) flux of large droplets was much higher than that given by existing sea spray generation functions, providing a new generation function for large droplets in calculating SSA flux in ocean models.

Extreme climate events significantly impact ecosystems and society. The assessments of extreme events often rely on percentile-based indices using a 30-year baseline period. In China, the Blue Book on Climate Change has traditionally been based on the 1981–2010 baseline period, and it began to use the 1991–2020 baseline period since 2024. However, the impact of baseline changes on assessing extremes in China remains unclear. This study examines how baseline period updates influence the detection of long-term climate change in China, particularly in estimating the Time of Emergence (ToE) for climate change signals. The results show that for temperature extremes, updating the baseline period leads to more (10%∼38%) cold extremes identified by 10th percentile indices and fewer (−32%∼−11%) warm extremes identified by 90th percentile indices across China. It slows the increase in identified warm extremes and accelerates the decrease in cold extremes. It delays the ToE for warm events and advances the ToE for cold events. For precipitation extremes, the update leads to fewer (−12%∼−1%) but more intense (at most 4%) extreme precipitation events identified by 95th and 99th percentile indices across China with slower increases in frequency and faster rises in intensity. The baseline period update advances the ToE for extreme precipitation intensity and delays it for frequency. The update of the baseline significantly affects the assessment of changes in climate extremes in China due to the background warming and wetting in 1991–2020 compared to 1981–2010.

Black carbon (BC) and brown carbon (BrC) are light-absorbing aerosols with significant climate impacts, but their absorption properties and direct radiative effect (DRE) remain uncertain. We simulated BC and BrC absorption during the intense Canadian boreal wildfires in June 2023 using an enhanced version of CHIMERE chemical and transport model. The study focused on a domain extending from North America to Eastern Europe, including the Arctic up to 85°N. The enhanced model includes an update treatment for BC absorption enhancement and a BrC aging scheme accounting for browning and blanching through oxidation. Validation against Aerosol Robotic Network and satellite data showed the model accurately reproduced aerosol optical depth (AOD) at multiple wavelengths, both near wildfire sources and during transoceanic transport to Europe. Improvements were observed in simulations of absorbing AOD (absorbing aerosol optical) compared with the baseline model. Significant enhancements were achieved in capturing the spatial distribution of aerosol absorption in areas affected by wildfire emissions. For June 2023, the regional all-sky DRE attributed to Canadian wildfires was reduced from −2.1 W/m² in the control model to −1.9 W/m² in the enhanced model. This corresponded to an additional warming effect of +0.2 W/m² (+10%) due to the advanced treatment of BC and BrC absorption. These results indicate the importance of accurate aerosol absorption modeling in regional climate predictions, during large-scale biomass burning events. They also highlight potential overestimations of cooling effects in traditional models, emphasizing the need of improved aerosol parameterization to better simulate the DRE and for evaluating the impacts of mitigation strategies.

Atmospheric mineral dust deposition is an important source of nutrients for ocean and tropical island ecosystems. Direct deposition measurements are generally more reliable at local scale than dust deposition models, even those based on aerosol concentration measurements. Whatever the scale, relevant local observations are necessary for model evaluation. We present here the results obtained by direct measurement of atmospheric aerosols and total atmospheric deposition using a 14-month time series from the Caribbean region. Total deposition velocity, lifetime, and scavenging ratio of major and trace elements were determined. Comparing total deposition fluxes of aluminum (dust proxy) and sea-salt sodium (sea-salt proxy) with Community Atmosphere Model (CAM6) outputs shows that the modeled total deposition rate is underestimated by a factor of two for dust and by a factor of eight for sea salt, while model aerosol concentration is larger than concentration measured near ground level. This result is due to wet deposition being underestimated in the model. The scavenging ratio (w/w) of Saharan dust elements ranges from 95 to 1,390, with a median of 530, close to the geometric mean value of 513. Sea salt presents a greater range of scavenging ratio values, from 325 to 2,355, with a median of 1,180, close to the geometric mean value of 1,030. The lead isotope ratio ²⁰⁶Pb/²⁰⁷Pb clearly highlights differences in lead origin between aerosols and deposits, revealing that aerosol samples are enriched by anthropogenic sources.

Atmospheric organosulfur species (OrgS) were investigated at four different sites (urban, rural, forest, and remote mountain) in the Guanzhong basin of northwest China to probe their chemical diversity and distribution profiles. The organic molecular composition in ambient PM_2.5 samples was measured using an ultrahigh performance liquid chromatograph coupled with an electrospray ionization Orbitrap high-resolution mass spectrometer. We found that OrgS (including CHOS and CHONS herein) were ubiquitously present across these environments and predominated the number of organic species assigned in negative ionization mode. The fractions of OrgS (mean 41%–45%) in total number of organic species over the Guanzhong basin were at the upper range compared with those in worldwide areas (12%–37%), primarily attributing to the high levels of anthropogenic pollutants (SO₂, NO_x, sulfate, etc.) across this region. Organosulfates and nitrooxy-organosulfates in aliphatic-like structures from long-chain alkanes and biogenic precursors constituted a majority number of OrgS, yet with distinct molecular characteristics in each environment. The distribution of the number of carbon atoms in the molecules revealed that OrgS mainly originated from complex mixed sources at the urban site, whereas biogenic precursors were more prevalent at the non-urban sites. The production of OrgS resulted from synergistic interactions of multiple influencing factors in different conditions. Our results highlight the importance of anthropogenic pollution in modifying organic aerosol composition under various atmospheric environments.

Wildfires are a major natural source of atmospheric aerosols, leading to air quality degradation and adverse human health effects. Accurate prediction of air quality effects from wildfires remains challenging due to uncertainties in fire emission estimates. To enhance the accuracy of fire emissions used in air quality forecast models, we developed a method that utilizes satellite aerosol optical depth (AOD) observations and air quality simulations to calculate dynamic emission scaling factors and improve wildfire air quality forecasts. TROPOMI (TROPOspheric Monitoring Instrument) UV Aerosol Index (UVAI) data are employed to fill AOD gaps under thick smoke using two approaches: a regression model and an artificial intelligence model. The scaling factor method was applied to NOAA blended Global Biomass Burning Emissions Product. The emission scaling factors exhibited significant variability across different fire points, highlighting the need for point-specific scaling factors. On average, scaling factors were less than 1.0 (indicating emission overestimation) during the initial stages of fire events but exceeded 1.0 (suggesting underestimation) after 7 days of fire duration. An inverse relationship between scaling factors and fire radiative power (FRP) was observed, with emission underestimation for low-intensity fires (FRP <5 MW) and substantial overestimation for high-intensity fires (FRP >500 MW). The improved fire emissions were employed in the air quality model for the 2020 US Gigafire event. Utilizing emission scaling factors reduced model bias, increased the correlation and hit rate of PM_2.5 exceedance prediction, demonstrating the potential of using emission scaling factors for improving air quality forecasting during wildfire events.

Lightning strokes emit electromagnetic pulses that interact with the lower ionosphere. One manifestation of this interaction are elves: Ring-shaped light emissions from altitudes around 85 km above ground produced by active thunderstorms. Perturbations to the conductivity at those altitudes relax with time-scales longer than 10 min and therefore one strong pulse may affect the features of subsequent pulses. Here we develop a simplified model to investigate this possibility. We apply this model to thunderstorms with a copious production of high-peak-current strokes, finding changes in the altitude profile of light emissions for elves at different stages of the thunderstorm evolution.

The ENSO Transition Mode (ETM) is a distinct driver of ENSO multidecadal climate variability. The ETM plays an important role in influencing ENSO's seasonal transition from boreal winter to the following summer by affecting zonal winds in the central-eastern equatorial Pacific Ocean during boreal spring. In this study, we show that ETM's spatial pattern and seasonality are robustly captured by the CMIP6 models' historical simulations. However, they struggle to capture its multidecadal variability. Nonetheless, these models effectively depict ETM's influence on equatorial winds, thereby affecting the seasonal transition of ENSO from boreal winter to the following summer (ΔT). We further demonstrate that the models that more accurately represent the relationship between ETM and ΔT (referred to as “Good ETM models”) are those in which ΔT is less influenced by the preceding winter Niño3.4 sea-surface temperature anomalies (N34DJF) and largely influenced by phases of ETM. Additionally, these models better capture the 2–7-year spectral peak observed in N34DJF. On the contrary, Bad ETM models are characterized by a dominant higher-frequency, 2–3-year quasi-biennial peak. Consequently, Good ETM models render ENSO states that align more closely with observations compared with Bad ETM models. This study underscores, through CMIP6 models, the significance of boreal winter ENSO amplitude in influencing how extratropical climate affects the seasonal transitions of ENSO.