Journal of Geophysical Research: Atmospheres最新文献

Low clouds significantly influence Earth's energy budget by reflecting solar radiation. Consequently, inadequate representation of these clouds in models introduces the largest uncertainty in predicting future climate change. This study investigates low cloud cover (LCC) variation using 6 years (2014–2019) of high-precision ground-based Ka-band Zenith Radar (KAZR) observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). We analyze the relationship between observed low cloud properties and four large-scale meteorological factors: 700 hPa relative humidity, estimated inversion strength, low-level wind shear, and 700 hPa vertical velocity. These factors are identified as key parameters influencing low cloud evolution over this semi-arid region. We utilize principal component analysis to integrate these parameters into a single meteorological predictor (PC1) and establish a robust linkage between meteorological conditions and low cloud properties. By comparing LCC fluctuations derived from the meteorological factors with those directly simulated by models over the same period, we assess the projected LCC trends under various carbon emission scenarios. Contrary to the declining LCC projected by CMIP6 models outcomes, the LCC form PC1 shows a rising tendency by 2100 under global warming. This discrepancy implies that CMIP6 models may exaggerate the extent of future warming at the SACOL site. Our approach can be applied to a broader global distribution of low clouds to examine the differences between low cloud variations constrained by meteorological fields and those from direct model simulations. This will enhance our understanding of low cloud feedback on future climate change.

Organic aerosols (OA) significantly contribute to haze pollution, threaten human health, and affect the radiation balance. However, real-time tracking of OA evolution at the molecular level is limited, hindering a comprehensive understanding of their origins and behaviors. In this study, we investigated wintertime OA in a megacity in East China by combining simultaneous measurements from an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) and a high-resolution time-of-flight aerosol mass spectrometer (AMS) (HR-TOF-AMS). AMS results indicate that OA accounts for about 27% of non-refractory submicron particulate matter (NR-PM₁) on average. EESI-TOF data reveal that C_xH_yO_z and C_xH_yN_1–2O_z are the predominant OA components, contributing over 70% and 20%, respectively. Factorization analysis shows that while traffic, cooking, and biomass burning are major primary sources, most OA (>70% for EESI-TOF, >55% for AMS) originate from secondary production. EESI-TOF, although missing hydrocarbon-like OA, excels in providing molecular information on oxygenated OA, identifying aromatics and aliphatics as possible key precursors. It further differentiates less oxidized secondary organic aerosols (SOA) into two factors with distinct molecular compositions, likely due to diverse source regions. Importantly, EESI-TOF identifies two additional factors: one possibly related to plasticizers and another representing SOA formation from monoterpene oxidation by NO₃ radicals. In conclusion, EESI-TOF complements AMS by offering valuable molecular insights into the chemical processes underlying OA formation, especially in complex urban environments.

Increasing impacts of wildfires on Western US air quality highlights the need for forecasts of smoke emissions based on dynamic modeled wildfires. This work utilizes knowledge of weather, fuels, topography, and firefighting, combined with machine learning and other statistical methods, to generate 1- and 2-day forecasts of fire radiative energy (FRE). The models are trained on data covering 2019 and 2021 and evaluated on data for 2020. For the 1-day (2-day) forecasts, the random forest model shows the most skill, explaining 48% (25%) of the variance in observed daily FRE when trained on all available predictors compared to the 2% (<0%) of variance explained by persistence for the extreme fire year of 2020. The random forest model also shows improved skill in forecasting day-to-day increases and decreases in FRE, with 28% (39%) of observed increase (decrease) days predicted, and increase (decrease) days are identified with 62% (60%) accuracy. Error in the random forest increases with FRE, and the random forest tends toward persistence under severe fire weather. Sensitivity analysis shows that near-surface weather and the latest observed FRE contribute the most to the skill of the model. When the random forest model was trained on subsets of the training data produced by agencies (e.g., the Canadian or US Forest Services), comparable if not better performance was achieved (1-day R² = 0.39–0.48, 2-day R² = 0.13–0.34). FRE is used to compute emissions, so these results demonstrate potential for improved fire emissions forecasts for air quality models.

At mid-latitudes, a narrow band of near-surface wind convergence (NSWC) overlies the western boundary currents in long-term climatology as a response to steep sea surface temperature gradients. The underlying dynamics shaping mean convergence in the mid-latitude region have been investigated in detail. In polar regions, surface temperature gradients are intense along the sea ice edges. However, literature concerning NSWC near sea ice edges is limited. This study investigates time-mean NSWC along sea ice edges and its shaping processes, focusing on the Greenland Sea, based on atmospheric reanalysis. In cold-season climatology, positive NSWC overlies the sea ice edge, resulting in a localized upward motion reaching the free atmosphere. The mean NSWC was insensitive to sea ice thickness and surface roughness in the regional model. This study suggests that, in addition to local atmospheric boundary processes, extreme NSWC events play a vital role in shaping the mean distribution. Although these features are similar to those along the Gulf Stream, atmospheric fronts appear to play a relatively minor role in the Greenland Sea. Instead, the frequent cyclone generation near the sea ice edge and the anticyclonic circulation over Greenland in conjunction with the transient synoptic circulation seem essential. In the warm season, positive NSWC was virtually missing in the Greenland Sea, unlike in the Gulf Stream region, reflecting the shallow virtual temperature response to the surface thermal forcing. This study contributes to understanding the mechanisms by which sea ice variability affects large-scale atmospheric circulation in remote regions.

This study investigates the background rotational influences on the secondary eyewall formation (SEF) in tropical cyclones (TCs) in quiescent f-plane environments. For given initial structures, simulated vortices tend to experience earlier SEF at lower latitudes. Yet the size of the secondary eyewall does not change monotonically with the latitudes. Specifically, ∼20°N provides the optimal amount of background rotation for the largest secondary eyewall size without considering other environmental forcings. Different background rotation rates affect SEF mainly by modulating the outer-core convection as well as the wind structures. Specifically, the lower rotation rate causes more outer-core surface fluxes, thus facilitating the outer rainbands (ORBs) at larger radii. Yet the secondary eyewall does not necessarily form at larger radii at lower latitudes since the transition from the ORBs to secondary eyewall is localized in a region of boundary layer (BL) convergence preceded by accelerated tangential winds. Budget analysis reveals that the differences in the acceleration of outer-core tangential winds among vortices at different latitudes are dominated by the radial flux of absolute vorticity. Due to the non-uniform influences of background rotation on the BL inflow and absolute vorticity, the most efficient spin-up of outer-core tangential winds is achieved at a medium latitude of 20°N, which leads up to SEF at the largest radii. By comparison, for TCs at lower (higher) latitudes, the lower outer-core absolute vorticity (radial inflow) limits the acceleration of outer-core tangential winds, thus placing SEF at smaller radii.

The North Pacific Meridional Mode (PMM) is the strongest interannual air-sea coupled system in the subtropical northeastern Pacific, which can significantly impact the development of El Niño and Southern Oscillation (ENSO). This study examines performance of the second version of the Chinese Academy of Sciences Earth System Model (CAS-ESM2), developed primarily at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), in simulating the PMM, ENSO, and their relationship. It reveals that CAS-ESM2 can well reproduce the tropical climate mean states, including sea surface temperature (SST), surface winds, and precipitation. Furthermore, the model shows a good ability in reproducing the seasonal evolutions of the PMM and ENSO. Moreover, CAS-ESM2 effectively simulates the influence of the PMM on subsequent ENSO and the underlying physical mechanisms, including the wind-evaporation-SST feedback process, the trade wind charging mechanism and summer deep convection mechanism. However, some improvements are still needed, particularly in representing the periodicity of the PMM, an overestimation of the ENSO intensity and westward extension of ENSO-related SST anomalies in the tropical Pacific. The results obtained from the CAS-ESM2 showcase significant progress in understanding the interaction between air-sea interaction systems over the tropics and subtropics.

The Alaskan Layered Pollution and Chemical Analysis (ALPACA) field campaign included deployment of a suite of atmospheric measurements in January–February 2022 with the goal of better understanding atmospheric processes and pollution under cold and dark conditions in Fairbanks, Alaska. We report on measurements of particle composition, particle size, ice nucleating particle (INP) composition, and INP size during an ice fog period (29 January–3 February). During this period, coarse particulate matter (PM₁₀) concentrations increased by 150% in association with a decrease in air temperature, a stronger temperature inversion, and relatively stagnant conditions. Results also show a 18%–78% decrease in INPs during the ice fog period, indicating that particles had activated into the ice fog via nucleation. Peroxide and heat treatments performed on INPs indicated that, on average, the largest contributions to the INP population were heat-labile (potentially biological, 63%), organic (31%), then inorganic (likely dust, 6%). Measurements of levoglucosan and bulk and single-particle composition corroborate the presence of dust and aerosols from combustion sources. Heat-labile and organic INPs decreased during the peak period of the ice fog, indicating those were preferentially activated, while inorganic INPs increased, suggesting they remained as interstitial INPs. In general, INP concentrations were unexpectedly high in Fairbanks compared to other locations in the Arctic during winter. The fact that these INPs likely facilitated ice fog formation in Fairbanks has implications for other high latitude locations subject to the hazards associated with ice fog.

We investigate the position and intensity changes of the Intertropical Convergence Zone (ITCZ) over Asia (50°E−135°E) relative to the preindustrial period annually and seasonally during the Last Interglacial (LIG), Last Glacial Maximum (LGM), and mid-Holocene (MH) using available models from phases 3 and 4 of the Paleoclimate Modeling Intercomparison Project. The multi-model mean shows that the June–July–August ITCZ variations generally dominate the annual changes. The Asian ITCZ shifts northward over western Asia and southward over the eastern side in both the LIG and MH, and the opposite occurs in the LGM. Its intensity varies with longitude similarly for the LIG and MH and generally weakens in the LGM. Precipitation changes associated directly with ITCZ indices are primarily caused by the dynamic term in the LIG and MH, while both dynamic and thermodynamic terms play roles in the LGM, with major contributions from the convergence components.

The Eldgjá eruption is the largest basalt lava flood of the Common Era. It has been linked to a major ice-core sulfur (S) spike in 939–940 CE and Northern Hemisphere summer cooling in 940 CE. Despite its magnitude and potential climate impacts, uncertainties remain concerning the eruption timeline, atmospheric dispersal of emitted volatiles, and coincident volcanism in Iceland and elsewhere. Here, we present a comprehensive analysis of Greenland ice-cores from 936 to 943 CE, revealing a complex volatile record and cryptotephra with numerous geochemical populations. Transitional alkali basalt tephra matching Eldgjá are found in 939–940 CE, while tholeiitic basalt shards present in 936/937 CE and 940/941 CE are compatible with contemporaneous Icelandic eruptions from Grímsvötn and Bárðarbunga-Veiðivötn systems (including V-Sv tephra). We also find four silicic tephra populations, one of which we link to the Jala Pumice of Ceboruco (Mexico) at 941 ± 1 CE. Triple S isotopes, Δ³³S, spanning 936–940 CE are indicative of upper tropospheric/lower stratospheric transport of aerosol sourced from the Icelandic fissure eruptions. However, anomalous Δ³³S (down to −0.4‰) in 940–941 CE evidence stratospheric aerosol transport consistent with summer surface cooling revealed by tree-ring reconstructions. Tephra associated with the anomalous Δ³³S have a variety of compositions, complicating the attribution of climate cooling to Eldgjá alone. Nevertheless, our study confirms a major S emission from Eldgjá in 939–940 CE and implicates Eldgjá and a cluster of eruptions as triggers of summer cooling, severe winters, and privations in ∼940 CE.

The Atacama Desert is amongst the driest places on Earth yet large dust outbreaks seem rare. We present the first quantitative assessment of dust events in the Atacama for 1950–2021 based on station observations. A total of 1920 dust days were recorded with less than 10% being classified as dust storms. We calculated the wind speeds at 5%, 25% and 50% of the dust-event frequency distribution. The mean wind speed for the threshold of 5% is 10.9 ± 1.6 ms⁻¹ which is twice as large as the values in the Taklamakan, Western Sahel, and Sudan, and consistent with the perceptually infrequent dust activity despite the exceptional aridity. We see no overall long-term trend but increased dust activity for 1970–1978, 1984–1988 and 2013–2017. A combination of changes in the wind speed statistics and soil conditions, possibly including anthropogenic land-use changes have led to the variability in dust activity.