npj Climate and Atmospheric Science最新文献

This study explores how the mixing structures and coating compositions of black carbon (BC) particles influence their light absorption, focusing on liquid-liquid phase separation (LLPS), which separates organic and inorganic phases and redistributes BC from the inorganic core (Icore) to the organic coating (Ocoating). Using transmission electron microscopy and 3D-modeling, we found that the BC core’s position significantly impacts its light absorption. A BC core embedded within the Icore shows stronger light absorption at wavelengths below 600 nm compared to the same core in the Ocoating. When Ocoating is considered as brown carbon (BrC), it reduces BC core’s light absorption at 350 nm due to shielding effect, but its overall impact on the entire BC particle is minimal (–3.0% ± 1.6%). The result indicates that in LLPS particles, the BrC coating primarily enhances light absorption, emphasizing the need to consider both mixing structures and coating compositions of BC in atmospheric models.

The latitudinal distribution of winter extratropical precipitation is often regarded as being determined by the location and intensity of the storm track. Here, we compare the precipitation variability associated with the meridional eddy momentum flux (EMF) with that associated with an Eulerian storm track measure. Observations show that when the midlatitude EMF is anomalously poleward, the occurrence of moderate-to-heavy precipitation (1–33 mm day^-1) increases between 45°N and 70°N, while decreasing between 25°N and 45°N. This shift occurs mostly downstream of the climatological storm track maximum, with generally greater precipitation anomalies compared to those associated with storm track changes. The shift is tied to changes in horizontal moisture transport primarily by planetary scale waves. These results suggest that, in addition to the storm track intensity, dynamics of the horizontal wave tilts which affect the EMF intensity need to be considered when projecting future changes in precipitation variability.

The Arctic is experiencing heightened precipitation, affected by aerosols impacting rainfall and snowfall. However, sparse aerosol observations in the central Arctic cryosphere contribute to uncertainties in simulating aerosol-precipitation two-way interaction. This study examines aerosol-precipitation co-variation in various climate models during the Arctic spring and summer seasons from 2003 to 2011, leveraging satellite-based aerosol data and various CMIP6 climate models. Findings reveal significant spatio-temporal biases between models and observations. Snowfall dominance occurs in models where total AOD surpasses the observation by 121% (57–186%, confidence interval), intensifying simulated snowfall by two times compared to rainfall during summer. Consequently, climate models tend to underestimate central Arctic rainfall to the total precipitation ratio, suggesting a positive bias towards snowfall dominance. This highlights the importance of constraining total AOD and associated aerosol schemes in climate models using satellite measurements, which potentially could lead to a substantial reduction in snowfall contribution to the total precipitation ratio in the central Arctic, contrary to current multi-model simulations across various spatiotemporal scales.

We assess the relative contributions of land, atmosphere, and oceanic initializations to the forecast skill of root zone soil moisture (SM) utilizing the Community Earth System Model version 2 Sub to Seasonal climate forecast experiments (CESM2-S2S). Using eight sensitivity experiments, we disentangle the individual impacts of these three components and their interactions on the forecast skill for the contiguous United States. The CESM2-S2S experiment, in which land states are initialized while atmosphere and ocean remain in their climatological states, contributes 91 ± 3% of the total sub-seasonal forecast skill across varying soil moisture conditions during summer and winter. Most SM predictability stems from the soil moisture memory effect. Additionally, land-atmosphere coupling contributes 50% of the land-driven soil moisture predictability. A comparative analysis of the CESM2-S2S SM forecast skills against two other climate models highlights the potential for enhancing soil moisture forecast accuracy by improving the representation of soil moisture-precipitation feedback.

The Global Warming Potential-star (GWP*) approach is a way to convert the emissions of short-lived climate forcers to CO₂-equivalent emissions while maintaining consistency with temperature outcomes. Here we evaluate the performance of GWP* when it is used to account for non-CO₂ gases within the carbon budget framework. We convert methane (CH₄) emissions to CO₂-equivalent emissions via GWP* and calculate the temperature through simple climate models. We show that GWP* can accurately convert CH₄ emissions to reproduce the temperature until 2100 under a variety of scenarios, including overshoot scenarios, except those with a rapid decline in CH₄ emissions. Beyond 2100, however, the use of GWP* can lead to temperature overestimation since it extends beyond its calibration range. Furthermore, we find that under scenarios designed to achieve identical temperature targets but with varying overshoot profiles, cumulative CO₂-eq budgets (GWP*-basis) generally increase with overshoot length and magnitude. This is driven by the internal dynamics of our model, as characterized by its negative zero-emission commitment. While the use of GWP* enhances such effects with increasing overshoot length, it exerts opposite effects with increasing overshoot magnitude.

An unprecedented marine heatwave (MHW) struck the extratropical Northeastern Pacific during the summer of 2020. This study reveals that this event is characterized by a persistent atmospheric high-pressure anomaly in the MHW region, which leads to a decreased cloud cover, an increased surface shortwave radiation (SWR), a decreased mixed-layer depth, and an increased sea surface temperature (SST). The local net surface heat flux anomaly associated with the increased SWR primarily drives the increased SST, while the oceanic processes likely play a minor role. Both observations and simulations further demonstrate that the SST and high-pressure anomaly are closely associated with a large-scale wave train over the extratropical sector from Asia to the North Pacific which can be forced by the Tibetan Plateau heating change. According to our findings, the projection of a persistent warming Tibetan Plateau heightens the risk of escalating MHW events in the Northeastern Pacific under future scenarios.

Urban areas exhibit significant gradients in Fine Particulate Matter (PM_2.5) concentration variability. Understanding the spatiotemporal distribution and formation mechanisms of PM_2.5 is crucial for public health, environmental justice, and air pollution mitigation strategies. Here, we utilized machine learning and integrated air quality sensor monitoring networks consisting of 200 mobile cruising vehicles and 614 fixed micro–stations to reconstruct PM_2.5 pollution maps for Jinan’s urban area with a high spatiotemporal resolution of 500 m and 1 h. Our study demonstrated that pollution mapping can effectively capture spatiotemporal variations at the urban microscale. By optimizing the spatial design of monitoring networks, we developed a cost-effective air quality monitoring strategy that reduces expenses by nearly 70% while maintaining high precision. The results of multi-model coupling indicated that secondary inorganic aerosols were the primary driving factors for PM2.5 pollution in Jinan. Our work offers a unique perspective on urban air quality monitoring and pollution attribution.

Glacier collapse is one of the serious cryospheric hazards in the Tibetan Plateau (TP), especially in the southeast of TP. Recent studies on glacier change and glacier collapse events in this region show that the risk of glacier collapse disaster in Southeast Tibet is vague and not specific. Here, we assess the risk of glacier collapse by combining machine learning method, dangerous glacier identification and vulnerability analysis in the basin. This study considers that the glacier collapse events in this area in recent years are mainly driven by temperature, precipitation and seismic activity under the background of steep terrain. A total of 946 km² of glaciers in southeastern Tibet are potentially at hazard of collapse, with the largest area of about 320 km² in the southeastern region; The proportion of the southern region is the highest, about 55.6%. Eight basins are at extremely high risk, including 85 residential areas, 131 roads and 52 rivers. This study directly responds to the needs of the disaster prevention and mitigation strategy to determine the key areas, and emphasizes the necessity of coping with the threat of glacier collapse in the extremely high-risk basins in Southeast Tibet.

Mid-latitude weather systems play a significant role in causing floods, wind damage, and related societal impacts. Advances in numerical modeling and observational methods have led to the development of numerous conceptual models in mid-latitude synoptic and dynamical research. As these models proliferate, integrating new insights into a cohesive understanding can be challenging. This paper uses a kinematic perspective to interpret mid-latitude research in a way that synthesises various concepts and create a schematic diagram of an atmospheric river lifecycle. Our analysis demonstrates that, despite varying methods, definitions, and terminology used to describe extratropical cyclones, warm conveyor belt airflows, and atmospheric rivers, the underlying mechanisms driving their formation and development are consistent. Thus, while studying these features independently is valuable, it is important to recognise that they are all part of a larger atmospheric flow pattern. We hope this kinematic approach will serve as a bridge to link research on these phenomena.