Advances in Climate Change Research最新文献

Environmental factors are essential input variables for susceptibility assessment models of mountain geohazards. However, the existing literature provides a limited understanding of the relative contribution of these factors to the occurrence of geohazards with a warming climate, posing tremendous challenges for risk management in mountainous areas. Ya'an city is susceptible to hazards because of its steep terrain, abundant precipitation and active seismic activity. In this regard, we utilise the GeoDetector model to extract critical environmental factors affecting the spatial patterns of mountain geohazards (i.e., landslide, debris flow and rockfall) in Southwest China. The analysis indicates that the factors with the highest explanatory power for the spatial distribution of landslides, debris flows, and rockfalls are soil property, extreme precipitation and extreme temperature, respectively. Notably, we revealed the synergistic effects among factors given their larger q-value than individual ones. We further explored the responses of mountain geohazards to climate change, including the rising temperature and precipitation, because the frequent occurrence of mountain geohazards is closely related to a warming climate. The variation in snow water equivalent caused by antecedent snowfall and snowdrifts acts as a crucial indicator for geohazards, highlighting the significance of snow and wind observations in meteorological nowcasting and disaster prewarning. We disclose the phenomenon of the geohazard hysteresis to the precipitation peak resulting from the top–down (i.e., precipitation-runoff and surface-deep soil moisture) peak shifts. Our work is expected to enhance the precision of susceptibility assessment models and the reliability of short-term forecasts for mountain geohazards.

Urolithiasis is a heat-specific disease. Exploring heat-related urolithiasis susceptibility subtypes, economic burden, and modifying factors could assist governments in targeting interventions to reduce the heat-related health risks of urolithiasis morbidity. We collected data on 23,492 patients with upper urinary tract stones (main subtypes of urolithiasis) from 2013 to 2017 in Nanjing, China. We adopted generalized additive quasi-Poisson models to examine the associations between daily mean temperatures and morbidity of upper urinary tract stones, while generalized additive Gaussian models were used to explore the relationships between temperatures and log-transformed medical costs. We examined the modification effects of disease subtypes (kidney and ureteral calculus), sex, and age through stratified analyses and the modification effects of other meteorological factors by introducing interaction terms in the models. We found that short-term summer heat exposure has a statistically significant effect on ureteral calculus morbidity but not on kidney calculus morbidity. For ureter calculus, a 1 °C temperature increase was associated with a 4.36% (95% confidence interval [CI]: 1.94%, 6.83%) increase in daily hospitalization and a 5.44% (95% CI: 2.71%, 8.25%) increase in daily medical costs. The attributable fraction associated with heat (greater than the median value of daily mean temperature, 26.8 °C) was 7.85% (95% empirical confidence interval [eCI]: 3.64%, 11.44%) for hospitalization and 9.36% (95% eCI: 4.91%, 13.14%) for medical costs. The effects of heat on ureter calculus morbidity were significantly higher among the males and those with high sunshine duration than females and those with low sunshine duration. Short-term summer heat exposure was associated with increased morbidity and medical costs of ureteral calculus. Relevant government organizations should take effective intervention measures, including community health education, to reduce the health hazards and economic losses caused by heat.

Wind energy development in Central Asia can help alleviate drought and fragile ecosystems. Nevertheless, current studies mainly used the global climate models (GCMs) to project wind speed and energy. The simulated biases in GCMs remain prominent, which induce a large uncertainty in the projected results. To reduce the uncertainties of projected near-surface wind speed (NSW) and better serve the wind energy development in Central Asia, the Weather Research and Forecasting (WRF) model with bias-corrected GCMs was employed. Compared with the outputs of GCMs, dynamical downscaling acquired using the WRF model can better capture the high- and low-value centres of NSWS, especially those of Central Asia's mountains. Meanwhile, the simulated NSWS bias was also reduced. For future changes in wind speed and wind energy, under the Representative Concentration Pathway 4.5 (RCP4.5) scenario, NSWS during 2031–2050 is projected to decrease compared with that in 1986–2005. The magnitude of NSWS reduction during 2031–2050 will reach 0.1 m s⁻¹, and the maximum reduction is projected to occur over the central and western regions (>0.2 m s⁻¹). Furthermore, future wind power density (WPD) can reveal nonstationarity and strong volatility, although a downward trend is expected during 2031–2050. In addition, the higher frequency of wind speeds at the turbine hub height exceeding 3.0 m s⁻¹ can render the plain regions more suitable for wind energy development than the mountains from 2031 to 2050. This study can serve as a guide in gaining insights into future changes in wind energy across Central Asia and provide a scientific basis for decision makers in the formulation of policies for addressing climate change.

Numerical models serve as an essential tool to investigate the causes and effects of Arctic sea ice changes. Evaluating the simulation capabilities of the most recent CMIP6 models in sea ice volume flux provides references for model applications and improvements. Meanwhile, reliable long-term simulation results of the ice volume flux contribute to a deeper understanding of the sea ice response to global climate change. In this study, the sea ice volume flux through six Arctic gateways over the past four decades (1979–2014) were estimated in combination of satellite observations of sea ice concentration (SIC) and sea ice motion (SIM) as well as the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) reanalysis sea ice thickness (SIT) data. The simulation capability of 17 CMIP6 historical models for the volume flux through Fram Strait were quantitatively assessed. Sea ice volume flux simulated from the ensemble mean of 17 CMIP6 models demonstrates better performance than that from the individual model, yet IPSL-CM6A-LR and EC-Earth3-Veg-LR outperform the ensemble mean in the annual volume flux, with Taylor scores of 0.86 and 0.50, respectively. CMIP6 models display relatively robust capability in simulating the seasonal variations of volume flux. Among them, CESM2-WACCM performs the best, with a correlation coefficient of 0.96 and a Taylor score of 0.88. Conversely, NESM3 demonstrates the largest deviation from the observation/reanalysis data, with the lowest Taylor score of 0.16. The variability of sea ice volume flux is primarily influenced by SIM and SIT, followed by SIC. The extreme large sea ice export through Fram Strait is linked to the occurrence of anomalously low air temperatures, which in turn promote increased SIC and SIT in the corresponding region. Moreover, the intensified activity of Arctic cyclones and Arctic dipole anomaly could boost the southward sea ice velocity through Fram Strait, which further enhance the sea ice outflow.

Pine Island Glacier (PIG), the largest glacier in the Amundsen Sea Embayment of West Antarctica, has contributed to over a quarter of the observed sea level rise around Antarctica. In recent years, multiple observations have confirmed its continuous retreat, ice flow acceleration and profound surface melt. Understanding these changes is crucial for accurately monitoring ice mass discharge and future Antarctic contributions to sea level rise. Therefore, it is essential to investigate the complex interactions between these variables to comprehend how they collectively affect the overall stability of the intricate PIG system. In this study, we utilized high-resolution remote sensing data and deep learning method to detect and analyze the spatio-temporal variations of surface melt, ice shelf calving, and ice flow velocity of the PIG from 2015 to 2023. We explored the correlations among these factors to understand their long-term impacts on the glacier's stability. Our findings reveal a retreat of 26.3 km and a mass loss of 1001.6 km² during 2015–2023. Notably, extensive surface melting was observed, particularly in the 2016/2017 and 2019/2020 melting seasons. Satellite data vividly illustrate prolonged and intense melting periods, correlating with a significant retreat in the glacier's terminus position in 2019/2020. Furthermore, the comprehensive analysis of surface melting and the cumulative retreat of the ice shelf from 2017 to 2020 on the PIG shows a temporal relationship with subsequent significant changes in ice flow velocity, ranging from 10.9 to 12.2 m d⁻¹, with an average acceleration rate of 12%. These empirical findings elucidate the intricate relationship among surface melt, ice flow velocity, and consequential glacier dynamics. A profound understanding of these interrelationships holds paramount importance in glacier dynamic changes and modeling, providing invaluable insights into potential glacier responses to global climate change.

To ensure the long-term service performance of infrastructure such as railways, highways, airports and oil pipelines built on permafrost slope wetland sites, it is imperative to systematically uncover the long-term heat‒water changes of soil in slope wetlands environment under climate warming. More specifically, considering valuable field data from 2001 to 2019, the long-term heat and water changes in active layers of the slope wetland site along the Qinghai–Xizang Railway (QXR) are illustrated, the effect of thermosyphon measures in protecting the permafrost environment is evaluated, and the influences of climate warming and hydrological effects on the stability of slope wetland embankments are systematically discussed. The permafrost at the slope wetland site is rapidly degrading, demonstrating a reduction in active layer thickness of >3.7 cm per year and a permafrost temperature warming of >0.006 °C per year. The thermosiphon embankment developed by QXR has a specific cooling period; thus, to mitigate the long-term impacts of climate warming on the thermal stability of permafrost foundation, it is essential to implement strengthening measures for the thermosiphon embankment, such as adding a crushed-rock layer or sunshade board on the slope of thermosiphon embankment to creating a composite cooling embankment. Short-term seasonal groundwater seepage intensifies frost damage to the slope wetland embankment, while long-term seasonal supra-permafrost water and groundwater seepage exacerbates uneven transverse deformation of slope wetland embankment. Long-term climate warming and slope effects have altered the surface water and groundwater hydrological processes of slope wetlands, potentially leading to an increased occurrence of slope embankment instability. These results are crucial for improving our understanding of heat and water variation processes in the active layer of slope wetland sites located in permafrost regions and ensuring long-term service safety for the QXR.

Snow density is one of the basic properties used to describe snow cover characteristics, and it is critical for remote sensing retrieval, water resources assessment and modeling inputs. There are many instruments available to measure snow density in situ. However, there are measurement errors of snow density for bulk and layers or gravimetric and electronic instruments, which may affect the accuracy of remote sensing retrieval and model simulation. Especially in China, due to the noticeable heterogeneity of snowpacks, it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions. This study evaluated the performance of different snow density instruments: the Federal Sampler, the model VS–43 snow density cylinder (VS–43), the wedge snow density cutter (WC1000 and WC250), and the Snow Fork. The average bulk snow density of all instrument measurements was set as the reference value for evaluation. The results showed that as compared with the reference, the VS–43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE (11 kg m⁻³), BIAS (3 kg m⁻³), and MRE (1.6%). For layer observation, bulk snow density was overestimated by 8.1% with WC1000 and underestimated by 11.4% with Snow Fork which was the worst performance compared with the reference value, and there were greater measurement errors of snow density in the depth hoar than other snow layers. Compared with grassland, the uncertainty of snow density measurements was slightly lower in forests. Overall, the Federal Sampler and VS–43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China, and it is recommended to use WC1000, WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.

Global warming in tandem with surface albedo reduction caused by black carbon (BC) deposition on glaciers accelerated glacier melting; however, their respective contributions remain unclear. Glaciers in the Qilian Mountains are crucial for the development of oases in the Hexi Corridor; however, their area has decreased by more than 20% over the past half-century. Thus, this study developed a dynamic deposition model for light-absorbing particles (LAPs), coupled with a surface energy and mass balance model. We comprehensively assessed the effects of BC and warming on the melting of a typical glacier in the Qilian Mountains based on the coupled model. BC on the glacier surface caused 13.1% of annual glacier-wide melting, of which directly deposited atmospheric BC reduced the surface albedo by 0.02 and accounted for 9.1% of glacier melting. The air temperature during 2000–2010 has increased by 1.5 °C relative to that during the 1950s, accounting for 51.9% of current glacier melting. Meanwhile, BC emission have increased by 4.6 times compared to those of the early Industrial Revolution recorded in an ice core, accounting conservatively for 6.3% of current glacier melting. Mitigating BC emissions has a limited influence on current glacier melting; however, in the long-term, mitigation should exert a noteworthy impact on glacier melting through the self-purification of glaciers.