Advances in Climate Change Research最新文献

Mid-high latitude Northern Asia is one of the most vulnerable and sensitive areas to global warming, but relatively less studied previously. We used an ensemble of a regional climate model (RegCM4) projections to assess future changes in surface air temperature, precipitation and Köppen‒Trewartha (K‒T) climate types in Northern Asia under the 1.5–4 °C global warming targets. RegCM4 is driven by five CMIP5 global models over an East Asia domain at a grid spacing of 25 km. Validation of the present day (1986–2005) simulations shows that the ensembles of RegCM4 (ensR) and driving GCMs (ensG) reproduce the major characters of the observed temperature, precipitation and K‒T climate zones reasonably well. Greater and more realistic spatial detail is found in RegCM4 compared to the driving GCMs. A general warming and overall increases in precipitation are projected over the region, with these changes being more pronounced at higher warming levels. The projected warming by ensR shows different spatial patterns, and is in general lower, compared to ensG in most months of the year, while the percentage increases of precipitation are maximum during the cold months. The future changes in K‒T climate zones are characterized by a substantial expansion of Dc (temperature oceanic) and retreat of Ec (sub-arctic continental) over the region, reaching ∼20% under the 4 °C warming level. The most notable change in climate types in ensR is found over Japan (∼60%), followed by Southern Siberia, Mongolia, and the Korean Peninsula (∼40%). The largest change in the K‒T climate types is found when increasing from 2 to 3 °C. The results will help to better assess the impacts of climate change and in implementation of appropriate adaptation measures over the region.

Ice sheet serves as a crucial indicator for assessing climate change. Mass loss in recent remote sensing-based studies indicated that the Antarctic Peninsula has rapid rates of glacier retreat and speed up of surface velocity. However, observations of seasonal variability of ice speed are limited, and glacier-area changes require multi-temporal monitoring. This study investigated the changes in area and surface velocities of ∼375 glaciers on the northern Antarctic Peninsula (NAP) utilizing satellite images acquired by the Sentinel 1&2 satellites during 2018–2022. The results indicate that the glacier area reduced by approximately 166.1 ± 44.2 km² (−0.2% ± 0.1% per year) during the study period, with an acceleration after 2020 (−0.4% ± 0.3% per year), and the most dramatic reduction happened on the eastern NAP. The maximum annual ice speeds on the NAP generally exceeded 3500 m per year, while the ice speeds in 2021 were the highest (exceeded 4210 m per year). The ice speed variability in austral autumn was higher than in other seasons, meanwhile the summer ice speeds showed an increasing trend. The glacier G012158E47018N, McNeile Glacier, glacier G299637E64094S and Drygalski Glacier showed the most remarkable ice speed variations represented by high daily velocities and strong fluctuations on their termini. Our results demonstrated that the variations in glacier area and seasonal ice speed on the NAP were responsive to the ice–ocean–atmosphere processes. Therefore, seasonal velocity and area variations should be considered when conducting accurate mass balance calculations, model validations and change mechanism analyses under climate warming scenarios.

The Kherlen River is the main water source for Hulun Lake, the largest lake in northern China. Due to reduced inflow from the Kherlen River, Hulun Lake experienced rapid shrinkage at the beginning of the 21st century, posing a serious threat to the ecological security of northern China. However, there is still a significant lack of projections regarding future climate change and its hydrological response in the Kherlen River basin. This study analyzed the projected climate and streamflow changes in the Kherlen River basin, a vital yet vulnerable international semi-arid steppes type basin. A combination of multi-model ensemble projection techniques, and the soil and water assessment tool (SWAT) model was employed to examine the spatio‒temporal changes in precipitation, temperature, streamflow, and the associated uncertainties in the basin. The temperature (an increase of 1.84–6.42 °C) and the precipitation (an increase of 15.0–46.0 mm) of Kherlen River basin are projected to increase by 2100, leading to a rise in streamflow (1.08–4.78 m³ s⁻¹). The upstream of the Kherlen River exhibits remarkable increasing trends in precipitation, which has a dominant influence on streamflow of Kherlen River. Noteworthy increases in streamflow are observed in April, August, September, and October compared to the reference period (1971–2000). These findings suggest a partial alleviation of water scarcity in the Kherlen River, but also an increased likelihood of hydrological extreme events. The projected temperature increase in the Kherlen River basin exhibits the smallest uncertainty, while more pronounced uncertainties are found in precipitation and streamflow. The spread among the results of CMIP6 models is greater than that of CMIP5 models, with lower signal-to-noise ratio (SNR) values for temperature, precipitation, and streamflow.

Accurate prediction of future surface wind speed (SWS) changes is the basis of scientific planning for wind turbines. Most studies have projected SWS changes in the 21st century over China on the basis of the multi-model ensemble (MME) of the 6th Coupled Model Intercomparison Project (CMIP6). However, the simulation capability for SWS varies greatly in CMIP6 multi-models, so the MME results still have large uncertainties. In this study, we used the reliability ensemble averaging (REA) method to assign each model different weights according to their performances in simulating historical SWS changes and project the SWS under different shared socioeconomic pathways (SSPs) in 2015–2099. The results indicate that REA considerably improves the SWS simulation capacity of CMIP6, eliminating the overestimation of SWS by the MME and increasing the simulation capacity of spatial distribution. The spatial correlations with observations increased from 0.56 for the MME to 0.85 for REA. Generally, REA could eliminate the overestimation of the SWS by 33% in 2015–2099. Except for southeastern China, the SWS generally decreases over China in the near term (2020–2049) and later term (2070–2099), particularly under high-emission scenarios. The SWS reduction projected by REA is twice as high as that by the MME in the near term, reaching −4% to −3%. REA predicts a larger area of increased SWS in the later term, which expands from southeastern China to eastern China. This study helps to reduce the projected SWS uncertainties.

Observations and models indicate that human activities exert a considerable impact on the frequency and intensity of extreme temperature events, which are associated with global warming. However, changes in the duration of extreme temperature events and their association with human influence have not been considered in most studies. Thus, the possible relationship between the observed changes in the warm and cold spell duration (WSDI and CSDI) in hotspot regions during 1960–2014 and human influence was investigated based on the NCEP/NCAR reanalysis version 1 and Coupled Model Inter-comparison Project Phase 6 (CMIP6) data. Constraint projection based on these attribution results was also performed. The optimal fingerprinting technique was used to compare observed changes in WSDI and CSDI to simulated changes averaged across eight CMIP6 models. Results show that anthropogenic (ANT) forcing contributed to the observed increase in WSDI in the three hotspot regions (West Asia, South Asia and Southeast Asia), with the majority of the changes being attributed to greenhouse gas forcing. However, a generally weak ANT signal can be observed in the decreasing trend of CSDI and can be detected in South and Southeast Asia. The influence of aerosol forcing remains undetected in either WSDI or CSDI, which differs from the results for frequency and intensity of extreme temperatures. The attribution results revealed that the constrained projection of WSDI is lower than the raw projection for 2015–2100 in West Asia and Southeast Asia. However, no differences in future CSDI changes are found in Southeast Asia between the constrained and raw projections.

Developing a localized and consistent model framework for climate loss and damage assessment is crucial for the policy-making of climate change mitigation and adaptation. This study introduces a comprehensive, multidisciplinary Integrated Assessment Model (IAM) framework for evaluating climate damage in China, utilizing BCC-SESM climate model and FUND sectoral climate damage model under the SSP2-RCPs scenario. Employing a bottom-up approach, the research estimates climate damage across eight major sectors, recalibrates sectoral climate damage functions and parameters for China, and elucidates distinctions among direct climate loss, market climate loss, and aggregate climate loss. The findings reveal that the total climate damage function for China follows a quadratic pattern in response to temperature rise. By 2050, the estimated climate damage is projected to be 5.4%, 5.7%, and 8.2% of GDP under RCP2.6, RCP4.5, and RCP8.5, respectively. Additionally, both direct and market climate losses are projected to remain below 2% of GDP by 2050, while the aggregate climate loss could reach as high as 8.2%, which is predominantly attributed to non-market sectors. From a sectoral perspective, under the RCP8.5 scenario, human health damage constitutes the largest share (61.9%) of the total climate loss by 2050, followed by sea-level rise damage (18.6%). This study sheds lights on the adaptation policy that should attach importance to the non-market sectors, particularly focusing on human health and sea-level rise.

Warming and nitrogen (N) addition may impact soil nitrous oxide (N₂O) emissions, but the relationship between plant community composition and soil microbial activities remains unclear. For a two-year field study in the Qinghai‒Tibet Plateau, open-top chambers were used to quantify the effects of warming, N-addition, and their interactions on N₂O emissions. We found that the N-addition greatly increased N₂O emissions by 77.4% in 2018 when compared to the control group. In contrast, warming showed little effect on N₂O emissions but did increase the activity of enzymes associated with soil nitrification and denitrification. A combined effect of warming and N-addition of resulted in 208.6% (2018) and 90.8% (2019) increase in N₂O emissions, respectively, compared to the individual treatments of warming or N-addition. Global warming in alpine meadows is causally linked to increased legume biomass which is further intensified with the N-addition. Intensified legume biomass (p < 0.05), soil moisture (p < 0.001) and enzyme activity (p < 0.001) had a positive effect on N₂O emissions, while diminished microbial carbon/nitrogen (MBC/MBN) (p < 0.05) correlated with reduced N₂O emissions. Final results indicated that N-addition has a positive effect on N₂O emissions, and the addition of warming further intensifies this effect. The increased dominance of legumes and microbial N content contributes to this effect. These outcomes suggest that warming and atmospheric N deposition can stimulate N₂O emissions of alpine meadows in the future.

Despite experiencing a decadal shift towards drought conditions at the end of the 20th century, semiarid grasslands in northeast Asia (NEA) exhibited an evident greening trend from 1982 to 2020. However, the mechanism behind this phenomenon remains unclear. Hence, we analysed the interdecadal changes in vegetation response to drought on the basis of the standardised precipitation evapotranspiration index (SPEI) and Global Inventory Modelling and Mapping Studies LAI4g datasets, with an emphasis on the differences between direct and legacy effects (as measured by resilience), to explore the mechanism of persistent grassland greening. Results revealed that during the post-drought shift period (2000–2020), the sudden decrease in the water content of the intermediate soil layer triggered an intensified vegetation response to drought. Specifically, although direct effects and resilience were amplified, they exhibited asymmetric changes. Resilience was stronger than direct effects, and this difference increased with increasing drought (drought recovery) levels. These combined effects may account for persistent greening against intensified drying in the semiarid grasslands in NEA. Given the projected exacerbation of future droughts, this study holds notable importance for comprehending the long-term change dynamics of dryland ecosystems.

A widespread and prolonged hot extreme hit the Yangtze River basin in summer 2022, with 300 sites established new temperature records and nearly 96% stations endured more than 40 hot days. From the perspective of the combination effect of the global warming and La Niña condition, potential mechanisms of the hot extreme were investigated. Such a record-breaking hot extreme was caused by an extremely strong and westward-shifted western Pacific subtropical high (WPSH). The global warming effect contributed primarily to the abnormal hot days in the Yangtze River basin, coupled with the modulation of the La Niña condition. The sea surface temperature anomaly pattern under La Niña condition favored more convection activities over the western Pacific, encouraging an enhanced and westward-extended WPSH. In addition, an observation-based attribution analysis indicates that anthropogenic warming may increase the probability of such extensively persistent hot extreme by 1.8 times.