npj Climate and Atmospheric Science最新文献

Severe convective storms and tornadoes rank among nature’s most hazardous phenomena, inflicting significant property damage and casualties. Near-surface weather conditions are closely governed by large-scale synoptic patterns. It is crucial to delve into the involved multiscale associations to understand tornado potential in response to climate change. Using clustering analysis, this study unveils that leading synoptic patterns driving tornadic storms and associated spatial trends are distinguishable across geographic regions in the U.S. Synoptic patterns with intense forcing featured by intense upper-level eddy kinetic energy and a dense distribution of Z500 fields dominate the increasing trend in tornado frequency in the southeast U.S., generating more tornadoes per event. Conversely, the decreasing trend noted in certain regions of the central Great Plains is associated with weak upper-level synoptic forcing. These findings offer an explanation of observational changes in tornado occurrences, suggesting that the physical mechanisms driving those changes differ across regions.

Extreme climate events have increasingly threatened global terrestrial ecosystems in recent decades. In spring 2023, Southwest China (SWC) experienced unprecedented heatwaves and droughts. Using multiple satellite-based datasets, we found that these events led to the most significant declines in gross primary productivity (GPP) and the enhanced vegetation index (EVI) for the past two decades, with lagged effects persisting until August in the drought-affected area. Unlike the widespread and persistent drought of 2010, the record-breaking heatwaves in April and May 2023 sustained and intensified the drought stress. Elevated temperatures and suppressed precipitation, driven by anomalous atmospheric circulations, exacerbated the soil moisture (SM) shortages and increased the atmospheric vapor pressure deficit (VPD), restricting water availability and carbon uptake for vegetation photosynthesis. Our findings reveal that, during the 2023 extreme event in SWC, the decreases in forest productivity were primarily driven by low SM anomalies, while the decreases in the grassland and cropland productivity mainly resulted from abnormally high VPDs. This study highlights the combined effects of low SM and high VPD anomalies caused by a compound heatwave–drought event on vegetation growth in SWC and provides valuable insights for future assessments of regional extreme climate events on vegetation growth.

Observations reveal Antarctic sea ice expansion and Southern Ocean surface cooling trends from 1979 to 2014, whereas climate models mostly simulate the opposite. Here I use historical ensemble simulations with multiple climate models to show that sea-ice natural variability enables the models to simulate an Antarctic sea ice expansion during this period under anthropogenic forcings. Along with sea-ice expansion, Southern Ocean surface and subsurface temperatures up to 50^oS, as well as lower tropospheric temperatures between 60^oS and 80^oS, exhibit significant cooling trends, all of which are consistent with observations. Compared to the sea-ice decline scenario, Antarctic sea ice expansion brings tropical precipitation changes closer to observations. Neither the Southern Annular Mode nor the Interdecadal Pacific Oscillation can fully explain the simulated Antarctic sea ice expansion over 1979–2014, while the sea-ice expansion is closely linked to surface meridional winds associated with a zonal wave 3 pattern.

The South Asian summer monsoon (SAM) bears significant importance for agriculture, water resources, economy, and environmental aspects of the region for nearly 2 billion people. To minimize the adverse impacts of global warming, Stratospheric Aerosol Intervention (SAI) has been proposed to lower surface temperatures by reflecting a portion of solar radiation back into space. However, the effects of SAI on SAM are still very uncertain. Our study identifies the main drivers leading to a reduction in the mean and extreme summer monsoon precipitation under SAI. These include SAI-induced lower stratospheric warming and the associated weakening of the northern hemispheric subtropical jet, changes in the upper-tropospheric wave activities, geopotential height anomalies, a reduction in the strength of the Asian Summer Monsoon Anticyclone, and, to some degree, local dust changes. As the interest in SAI research grows, our results demonstrate the urgent need to further understand SAM variability under different SAI scenarios.

Land use changes (LUC) and global warming (GW) significantly impact the Maritime Continent’s (MC) hydro-climate, but their effects on extreme precipitation events are underexplored. This study investigates the impacts of LUC and GW on wet and dry extremes in the MC using Community Earth System Model (CESM)simulations, analyzing 55 years for LUC and 200 years for GW. We find that LUC-induced deforestation increases surface warming, enhancing atmospheric instability and favoring local convection, leading to more frequent heavy precipitation. Meanwhile, GW amplifies the atmosphere’s water-holding capacity, further intensifying wet extremes. Our findings reveal a “wet-get-wetter, dry-get-drier” pattern driven by different mechanisms: dynamic processes primarily influence wet extremes under LUC, while changes in evapotranspiration control dry extremes. In contrast, under GW, wet extremes are driven by dynamic processes, while dry extremes are influenced by reduced moisture availability and weakened atmospheric circulation. This highlights the need for land management to address rising extreme risks.

More frequent and intense heatwave events (HWEs) on the Tibetan Plateau (TP) present substantial threats to the ecological and hydrological systems. However, understanding the changes in HWEs on the TP is limited, primarily from analyses at individual stations or single elements (glaciers, lakes). Here, using refined data, we quantify the heatwave magnitude by aggregating multiple indicators into a comprehensive index and explore the influence of environmental factors on the heatwave magnitude over the TP. Our findings indicate that the heatwave magnitude has significantly increased since the 21st century, especially in autumn. From 1979–2000 to 2001–2022, the heatwave magnitude hotspots migrated toward the northwestern TP, whereas the regions with the most rapid increase shifted in the opposite direction. During the inter-seasonal, from spring to winter, the migration direction of the heatwave magnitude hotspots changed from the northwest in the first 22 years (1979–2000) to the southeast in the recent 22 years (2001–2022). We also find that downward shortwave radiation plays a significant role in the spatial stratified heterogeneity (SSH) of the heatwave magnitude, while the trend of temperature plays a dominant role in the SSH of the trend of heatwave magnitude. Moreover, elevation is correlated with the heatwave magnitude variability. The elevation-dependence of the heatwave magnitude has become more pronounced in the recent 22 years, with a high-heatwave magnitude migrating to higher elevations. Furthermore, the difference in land cover type can also affect the intensity of the heatwave magnitude to some extent. Our findings underscore the migration patterns of the heatwave magnitude evolution around the 21st century and provide a scientific basis for understanding the interaction between environmental factors and the heatwave magnitude in different periods.

Given the significant environmental and health risks associated with near-surface nitrogen dioxide (NO₂), machine learning is frequently employed to estimate near-surface NO₂ concentrations (S_NO2) from satellite-derived tropospheric NO₂ column densities (C_NO2). However, data-driven methods often face challenges in explaining the complex relationships between these variables. In this study, the correlation between C_NO2 and S_NO2 is examined using vertical profile observations from China’s MAX-DOAS network. Cloud cover and air convection substantially weaken (R = −0.68) and strengthen (R = 0.71) the C_NO2-S_NO2 correlation, respectively. Meteorological factors dominate the correlation (R² = 0.58), which is 31% stronger in northern regions than in the southwest. Additionally, anthropogenic emissions impact S_NO2, while topographical features shape regional climate patterns. At the Chongqing site, the negative impacts of unfavorable meteorological conditions, high emissions, and basin topography lead to significant contrasts and delays in daily C_NO2 and S_NO2 variations. This study enhances understanding of the spatial and temporal dynamics and influencing mechanisms of C_NO2 and S_NO2, supporting improved air quality assessments and pollution exposure evaluations.