npj Climate and Atmospheric Science最新文献

Air pollution impacts on human health are of serious concern in northern India, and over the Delhi National Capital Region (NCR) in particular. The Kharif crop residue burning (CRB) is often blamed for degradation of Delhi-NCR’s seasonal air quality. However, the concentration of fine particulate matter (PM_2.5) remained stable in Delhi, while the fire detection counts (FDCs) from satellites over Punjab and Haryana declined by 50% or more during 2015–2023. We measured PM_2.5, carbon monoxide (CO) and related parameters over Delhi-NCR, Haryana and Punjab from a network of 30 low-cost sensors (CUPI-Gs) in a selected period (September–November) of 2022 and 2023. Measured PM_2.5 showed lower concentration in 2023 compared to 2022 at Punjab and Haryana sites, in compliance with FDC reductions. Using the CUPI-G measurements, airmass trajectories, particle dispersion and chemical-transport model simulations, we show that the CRB emissions over Punjab contributed only a meagre ~14% to the overall PM_2.5 over Delhi-NCR during October-November 2022. This indicates that there exists only a very weak coupling between PM_2.5 mass over Delhi-NCR and the CRB over Punjab, highlighting the effectiveness of the Graded Response Action Plan (GRAP) in controlling air pollution in the region.

Climate change is considered to affect wildfire spread both by increasing fuel dryness and by altering vegetation mass and structure. However, the direct effect of global warming on wildfires is hard to quantify due to the multiple non-climatic factors involved in their ignition and spread. By combining wildfire observations with the latest generation of climate models, here we show that more than half of the large wildfires (area>500 ha) occurring in the Iberian Peninsula between 2001 and 2021 present a significant increase in the rate of spread with respect to what it would have been in the pre-industrial period, attributable to global warming. The average acceleration of the rate of spread due to increased fuel dryness is between 2.0% and 8.3%, whereas the influence of enhanced vegetation growth since the pre-industrial period could potentially be even higher than the direct impact of temperature increase in fuel conditions.

Under climate change, China faces intensifying compound extreme events with serious socio-economic ramifications, yet their future variations remain poorly understood. Here, we estimate historical hotspots and future changes of two typical compound events, i.e., sequential heatwave and precipitation (SHP) and concurrent drought and heatwave (CDH) across China, leveraging a bivariate bias correction method to adjust projections from global climate models. Results show substantial future increases in frequency, duration, and magnitude for both events, with the durations projected to double nationwide. The increases are more evident under higher emission scenarios, and could be largely underestimated if neglecting variable dependence during bias correction process. The projected changes will escalate socio-economic exposure across China’s major urban clusters, among which Guangdong-Hong Kong-Macao will face the highest risk. Our findings underscore the necessity of carbon emission controls, and call for adaptive measures to mitigate the threats induced by rising compound hazards in a changing climate.

Uncertainties in land surface processes notably limit subseasonal heat wave (HW) onset predictions. A better representation of the uncertainties in land surface processes using ensemble prediction methods may be an important way to improve HW onset predictions. However, generating ensemble members that adequately represent land surface process uncertainties, particularly those related to land surface parameters, remains challenging. In this study, a conditional nonlinear optimal perturbation related to parameters (CNOP-P) approach was employed to generate ensemble members for representing the uncertainties in land surface processes resulting from parameters. Via six strong and long-lasting HW events over the middle and lower reaches of the Yangtze River (MLYR), HW onset ensemble forecast experiments were conducted with the Weather Research and Forecasting (WRF) model. The performance of the CNOP-P approach and the traditional random parameter perturbation ensemble prediction method was evaluated. The results demonstrate that the deterministic and probabilistic skills of HW onset predictions show greater excellence using the CNOP-P approach, leading to much better predictions of extreme air temperatures than those using the traditional method. This occurred because the ensemble members generated by the CNOP-P method better represented the uncertainties in important land physical processes determining HW onsets over the MLYR, notably vegetation process uncertainties, whereas the ensemble members generated by the random parameter perturbation method could not. This finding suggests that the CNOP-P method is suitable for producing ensemble members that more appropriately represent model uncertainties through more reasonable parameter error characterization.

This literature review synthesizes the role of soil moisture in regulating carbon sequestration and greenhouse gas emissions (CS-GHG). Soil moisture directly affects photosynthesis, respiration, microbial activity, and soil organic matter dynamics, with optimal levels enhancing carbon storage while extremes, such as drought and flooding, disrupt these processes. A quantitative analysis is provided on the effects of soil moisture on CS-GHG across various ecosystems and climatic conditions, highlighting a “Peak and Decline” pattern for CO₂ emissions at 40% water-filled pore space (WFPS), while CH₄ and N₂O emissions peak at higher levels (60–80% and around 80% WFPS, respectively). The review also examines ecosystem models, discussing how soil moisture dynamics are incorporated to simulate photosynthesis, microbial activity, and nutrient cycling. Sustainable soil moisture management practices, including conservation agriculture, agroforestry, and optimized water management, prove effective in enhancing carbon sequestration and mitigating GHG emissions by maintaining ideal soil moisture levels. The review further emphasizes the importance of advancing multiscale observations and feedback modeling through high-resolution remote sensing and ground-based data integration, as well as hybrid modeling frameworks. The interactive model-experiment framework emerges as a promising approach for linking experimental data with model refinement, enabling continuous improvement of CS-GHG predictions. From a policy perspective, shifting focus from short-term agricultural productivity to long-term carbon sequestration is crucial. Achieving this shift will require financial incentives, robust monitoring systems, and collaboration among stakeholders to ensure sustainable practices effectively contribute to climate mitigation goals.

An unexpected record-breaking cold event struck eastern China in December 2023, causing widespread transportation shutdowns, power supply shortages, and agricultural crop damage. The manner in which such an extraordinary cold event was formed under global warming is unclear, as is the way in which anthropogenic climate change may affect the present and future frequency and intensity of similar cold events. Here, we show that the large-scale atmospheric circulation associated with the warm Arctic was the main event driver, explaining 83 ± 2% of the intensity of the 2023 cold event, whereas the thermodynamic effect of climate change suppressed the event intensity by −6 ± 3% in ERA5 and −22 ± 2% in HadGEM3-A-N216. An attribution analysis based on coupled model simulations shows that, due to anthropogenic climate change, the frequency and intensity of 2023-like events decrease by 92.5 ± 2.5% and 1.9 ± 0.2 °C, respectively, under the 2023 climate state. The thermodynamic effect of anthropogenic climate change outweighs its dynamic effect. Future projections indicate that the frequency and intensity of these 2023-like events will further decrease by 95 ± 3% and 2.05 ± 0.25 °C by the end of this century under an intermediate-emissions scenario compared with estimates made under the present climate. In contrast, 2023-like events will be similar to present events when the 1.5 °C target of the Paris Agreement is achieved. These findings highlight the dampening effect of anthropogenic climate change on cold events, but adaptation measures for future risks of 2023-like cold events will be needed by the end of the century if carbon neutrality is achieved.

Anthropogenic aerosols could weaken the East Asian summer monsoon (EASM). This study investigated the regional effects of varying aerosol optical depth (AOD) on the EASM through qualitative and quantitative analyses for three subregions in eastern China. After assessing 38 CMIP6 models, four models (ACCESS-CM2, CanESM5, MIROC6, and MRI-ESM2-0) were selected for detailed analysis. Results showed that the weakening of EASM was predominantly attributed to anthropogenic aerosols. Increased AOD reduced land-sea temperature and pressure differences, weakening the EASM as indicated by the EASMI. Higher aerosol levels decreased surface shortwave radiation, land surface temperature, and evaporation, weakening the land-sea thermal contrast. Enhanced aerosol-induced cooling increased atmospheric stability and downward flow, suppressing upper air water vapor flux and precipitation. These findings underscore the critical role of anthropogenic aerosols in altering regional climate patterns and the importance of emission control to mitigate their effects on the EASM.

In this work, we examine connections between patterns of future Greenland precipitation and large-scale atmospheric circulation changes over the Northern Hemisphere. In the last three decades of the 21st century, CMIP5 and CMIP6 ensemble mean precipitation significantly decreases over the northern part of the North Atlantic Ocean with respect to 1951–1980. This drying signal extends from the ocean to the southeastern margin of Greenland. The 500 hPa geopotential height change shows a clear pattern including a widespread increase across the Arctic with a negative anomaly centered over Iceland and surrounding regions. To identify the mechanisms linking atmospheric circulation variability with Greenland precipitation, we perform a singular value decomposition (SVD) and center of action (COA) analysis. We find that a northeastward shift of the Icelandic Low (IL) under the SSP5‐8.5 warming scenario leads to the drying signal found in southeast Greenland. This implies that the IL location will have a strong influence on precipitation changes over southeast Greenland in the future, impacting projections of Greenland ice sheet surface mass balance.

Climate change poses direct and indirect threats to public health, including exacerbating air pollution. However, the influence of rising temperature on air quality remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions. Here, we examined the sensitivity of surface-level fine particulate matter (PM_2.5) and ozone (O₃) to summer temperature anomalies in the contiguous US as well as their decadal changes using high-resolution datasets generated by machine learning. Our findings demonstrate that in the eastern US, stringent emission control strategies have significantly reduced the positive responses of PM_2.5 and O₃ to summer temperature, thereby lowering the population exposure associated with warming-induced air quality deterioration. In contrast, PM_2.5 in the western US became more sensitive to temperature, highlighting the urgent need to manage and mitigate the impact of worsening wildfires. Our results have important implications for air quality management and risk assessments of future climate change.

Tropical cyclone (TC) precipitation has led to escalating urban flooding and transportation disruptions in recent years. The volatility of the TC rain rate (RR) over short periods complicates accurate forecasting. Here, we use satellite-based observational rainfall datasets from 1998 to 2019 to calculate changes in TC 24-h RR and quantify the temporal stability of TC precipitation. We demonstrate a significant global increase in the annual temporal stability of TC RR across the total rainfall area, inner-core, and rainband areas. Specifically, the probabilities of rapid RR increase and decrease events in the TC total rainfall area decreased at rates of –1.74 ± 0.57% per decade and –2.23 ± 0.55% per decade, respectively. Based on the reanalysis dataset, we propose that the synergistic effects of increased atmospheric stability and total column water vapor—both resulting from anthropogenic warming at low latitudes—are potentially associated with this trend.