Advances in Climate Change Research最新文献

Quantification of the impact of winter wheat irrigation on the climate and the occurrence of extreme climatic events over North China is crucial for regional adaptation planning. Previous related studies mainly focused on the impact on surface processes; however, few focused on the effects of extreme events using high-resolution nonhydrostatic regional climate models. Here, the 9-km-resolution nonhydrostatic RegCM4.7 was coupled with a crop irrigation scheme and an updated winter wheat irrigation dataset to better simulate irrigation effects. Two experiments were conducted with and without winter wheat irrigation to isolate the effects of irrigation. Results showed that irrigation simulation reduces the model biases in temperature, precipitation, latent heat flux, soil moisture, sensitive heat flux, and top-layer soil moisture. Moreover, it also reduces the bias and increases the correlation with observations obtained in irrigated areas, especially in summer, indicating better representation of irrigation schemes. Winter wheat irrigation tends to cause substantial cooling of the local surface maximum, minimum, and mean air temperatures (by −1.68, −0.34, and −0.79 °C, respectively) over irrigated areas of North China, with the largest changes observed in relation to maximum temperature. Additionally, precipitation is found to increase during spring and summer, which is strongly related to water vapor transport in the lower levels of the atmosphere. Further analyses indicated that the number of annual mean hot days decrease (−13.9 d), whereas the number of both comfort days (+10.2 d) and rainy days (days with total precipitation greater than 1 mm: +6.6 d) increase over irrigated areas, demonstrating beneficial feedback to human perception and agriculture. Fortunately, although the heat wave risk increases (number of annual mean heat wave days: +5.8 d), the impact is limited to small areas within irrigated region. Additionally, no notable change was found in terms of heavy rainfall events and precipitation intensity, which might be an undereastimation caused by the less water use in model simulation. Although winter wheat irrigation does not have notable impact on the climate of the surrounding region, it is an important factor for the local-scale climate.

Permafrost is degrading globally, particularly those with low thermal stability on the Qinghai‒Tibet Plateau, owing to climate change. However, the inadequacy of direct research on permafrost degradation based on in-situ monitoring limits the prediction of permafrost degradation and engineering practices. This study explored the processes and modes of permafrost degradation into talik by analyzing ground temperature data from five points in the hinterland of the Qinghai‒Tibet Plateau from 2006 to 2021. The results showed that the degradation of the warm permafrost layer with a geothermal gradient of zero occurred simultaneously in the top and bottom directions. The rate of permafrost degradation from the top down and bottom up increase during the degradation process, but the increase of the former is more drastic after the formation of thawed interlayer. Additionally, the construction of the Qinghai‒Tibet Railway changed the degradation modes of the permafrost in adjacent natural sites through horizontal heat transfer, particularly after through talik formation under the embankment. The findings suggest that taking countermeasures before or immediately after forming thawed interlayer is more effective. When evaluating the thermal impact of projects in warm permafrost regions, special attention should be given to the horizontal heat transfer process that may result from the formation of a through talik.

This study provides a comprehensive overview of the challenges to achieving carbon neutrality at the county level in China and offers targeted recommendations, laying the groundwork for future specialized research in this area. A total of 283 relevant studies (2004–2023) were analyzed to assess county-level carbon emissions through three phases: bibliometric analysis, frontier analysis, and future prospects. Bibliometric findings reveal that publication trends were largely influenced by domestic and foreign policies. Keyword cluster discerns ten primary themes, ranging from conceptual frameworks to research methodologies. The frontier analysis of the literature highlights the leading research areas, which include carbon neutrality pathway, driving factors, spatiotemporal variation of carbon emissions, the co-effects of pollutants and carbon reduction, and carbon emissions in China's rural areas. Drawing from the results of bibliometric and frontier analyses, this study elucidates the recommendations for achieving carbon neutrality at the county level from three perspectives: effective regional policy guidance, emphasis on ecological conservation, and the deployment of advanced carbon reduction and sequestration technologies. This study enriches the body of knowledge on carbon emissions at the county level and holds significant implications for China's comprehensive push towards achieving its carbon neutrality objectives.

Frozen ground (FG) plays an important role in global and regional climates and environments through changes in land freeze‒thaw processes, which have been conducted mainly in different regions. However, the changes in land surface freeze‒thaw processes under climate change on a global scale are still unclear. Based on ERA5-Land hourly land skin temperature data, this study evaluated changes in the global FG area, global land surface first freeze date (FFD), last freeze date (LFD) and frost-free period (FFP) from 1950 to 2020. The results show that the current FG areas (1991–2020 mean) in the Northern Hemisphere (NH), Southern Hemisphere (SH), and globe are 68.50 × 10⁶, 9.03 × 10⁶, and 77.53 × 10⁶ km², which account for 72.4%, 26.8%, and 60.4% of the exposed land (excluding glaciers, ice sheets, and water bodies) in the NH, SH and the globe, respectively; further, relative to 1951–1980, the FG area decreased by 1.9%, 8.8%, and 2.8%, respectively. Seasonally FG at lower latitudes degrades to intermittently FG, and intermittently FG degrades to non-frozen ground, which caused the global FG boundary to retreat to higher latitudes from 1950 to 2020. The annual FG areas in the NH, SH, and globe all show significant decreasing trends (p < 0.05) from 1950 to 2020 at −0.32 × 10⁶, −0.22 × 10⁶, and −0.54 × 10⁶ km² per decade, respectively. The FFP prolongation in the NH is mainly influenced by LFD advance, while in the SH it is mainly controlled by FFD delay. The prolongation trend of FFP in the NH (1.34 d per decade) is larger than that in the SH (1.15 d per decade).

The Qinghai–Tibet Plateau (QTP) has experienced rapid environmental changes, including climate warming and wetting, since the 1980s. These environmental changes significantly impact the shallow soil hydrothermal conditions, which have key roles in land–atmosphere feedback and ecosystem functions. However, the spatial variations and responses of soil hydrothermal conditions to environmental changes over the QTP with permafrost (PF) and seasonal frost (SF) remain unclear. In this study, we investigated the spatial variations in soil temperature (ST) and soil moisture (SM) changes over the QTP from 2000 to 2020 using 99 in-situ sites with observations at 4 depths (i.e. 10, 40, 100 and 200 cm). The main environmental controlling factors were further identified using a calibrated statistical model. Results showed that significant (p < 0.05) soil warming occurred at multiple soil layers during 2000–2020 with a wide variation (i.e. 0.033–0.039 °C per year on average), whereas the warming rates at PF sites were two times greater than those at SF sites. In addition, the soil wetting rate was high over the SF region, whereas the soil wetting rate was low over the PF region. Aside from air temperature, changes in thawing degree days and solar radiation (Srad) contributed most to soil warming in the PF region, whereas changes in rainfall, Srad and evaporation (EVA) have been identified as the key factors in the SF region. As for soil wetting, changes in snowfall, freezing degree days and vegetation have noticeable nonlinear effects over the PF region, whereas changes in EVA, Srad and rainfall highlighted distinct linear and nonlinear effects in the SF region. These findings enhance our understanding of the hydrothermal impacts of future environmental changes over the QTP.

Reliable monitoring and thorough spatiotemporal prediction of meteorological drought are crucial for early warning and decision-making regarding drought-related disasters. The utilisation of multiscale methods is effective for a comprehensive evaluation of drought occurrence and progression, given the complex nature of meteorological drought. Nevertheless, the nonlinear spatiotemporal features of meteorological droughts, influenced by various climatological, physical and environmental factors, pose significant challenges to integrated prediction that considers multiple indicators and time scales. To address these constraints, we introduce an innovative deep learning framework based on the shifted window transformer, designed for executing spatiotemporal prediction of meteorological drought across multiple scales. We formulate four prediction indicators using the standardized precipitation index and the standard precipitation evaporation index as core methods for drought definition using the ERA5 reanalysis dataset. These indicators span time scales of approximately 30 d and one season. Short-term indicators capture more anomalous variations, whereas long-term indicators attain comparatively higher accuracy in predicting future trends. We focus on the East Asian region, notable for its diverse climate conditions and intricate terrains, to validate the model's efficacy in addressing the complexities of nonlinear spatiotemporal prediction. The model's performance is evaluated from diverse spatiotemporal viewpoints, and practical application values are analysed by representative drought events. Experimental results substantiate the effectiveness of our proposed model in providing accurate multiscale predictions and capturing the spatiotemporal evolution characteristics of drought. Each of the four drought indicators accurately delineates specific facets of the meteorological drought trend. Moreover, three representative drought events, namely flash drought, sustained drought and severe drought, underscore the significance of selecting appropriate prediction indicators to effectively denote different types of drought events. This study provides methodological and technological support for using a deep learning approach in meteorological drought prediction. Such findings also demonstrate prediction issues related to natural hazards in regions with scarce observational data, complex topography and diverse microclimate systems.

Loss and damage caused by extreme climate events have attracted increasing attention. The 28th Conference of the Parties to the United Nations Framework Convention on Climate Change (hereinafter referred to as the Convention) has agreed to adopt Loss and Damage Fund agreement, which identified the source of funding and the funds to be entrusted to the World Bank. However, there is still ambiguous that how to allocate the funds could accelerate the effectiveness of meeting the needs for developing countries. Pre-disaster prevention and preparedness is one of the most effective measures to deal with loss and damage, which closely related to adaptation. Previous studies rarely analyzed quantitatively the financial needs of pre-disaster prevention and preparedness relating to adaptation to reduce loss and damage. Based on the official reports submitted by countries under the Convention, this study analyzes the annual change in the total financial support provided by developed countries to developing countries, the proportion of pre-disaster prevention and preparedness in the adaptation needs of developing countries, and the progress in raising the current annual funding target of 100 billion USD for developed countries, to reveal the financial and technical challenges facing by developing countries on addressing loss and damage. The results show that by 2030, the total adaptation financial needs of developing countries are estimated to be about 3.8 trillion USD, of which pre-disaster prevention matters account for about 9%. Therefore, by 2030, developing countries will need about 342 billion USD in pre-disaster prevention and preparedness finance to withstand loss and damage. In addition, developing countries face a lack of technical methods to quantify information about their needs. Based on the above analysis, this study puts forward countermeasures and suggestions, including strengthening the allocation amount of loss and damage fund on pre-disaster warning, prevention and control actions, and establishing track modalities on the finance provided by developed countries to developing countries based on the principles of the principle of Common but Differentiated Responsibilities and Respective Capabilities (CBDR-RC), to provide favorable guarantee for accelerating the effectiveness of international climate governance.

The climate in the Tibetan Plateau (TP) has undergone significant change in recent decades, mainly in thermal and water conditions, which plays a crucial role in phenological changes in vegetation spring phenology. However, how the start of the thermal growing season (SOS-T) and the start of the rainy season (SORS) as key climatic factors affect vegetation green-up remains unclear. Given that these factors characterize thermal and water conditions required for vegetation green-up, this study investigated changes in the SOS-T and SORS from 1961 to 2022, using observation-based datasets with long time series. We found that the SOS-T and SORS have advanced across the TP in 1961–2022 and have shown a spatial pattern of advancement in the east and delay in the west in 2000–2022. Further, the co-effect of temperature and precipitation change on the start of vegetation growing season (SOS-V) in 2000–2022 was observed. Averaged across TP, the SOS-V had an early onset of 1.3 d per decade during 2000–2022, corresponding to advanced SOS-T and SORS. Regionally, the SOS-V generally occurred nearly at the same time as the SOS-T in the high-altitude meadow region. A substantial delay in the SOS-V relative to the SOS-T was observed in the desert, shrub, grassland and forest regions and generally kept pace with the SORS. Furthermore, for 50% of the vegetated regions on the TP, inter-annual variation in the delay in the SOS-V relative to the SOS-T was dominated by precipitation change, which was profound in warm-climate regions. This study highlights the co-regulation of precipitation and temperature change in the SOS-V in different vegetation cover regions in the TP, offering a scientific foundation for comprehending the impact of climate change and prospects for vegetation phenology on the TP.

Recognizing the relationship between gross primary production (GPP) and precipitation in eastern China, the East Asian Summer Monsoon (EASM) plays a crucial role in shaping GPP. Despite confirmation of the strong link between EASM and GPP, there remains a notable research gap in understanding the specific impact of the EASM on GPP in different regions of eastern China. Here we used simulations from Trends in Net Land–Atmosphere Carbon Exchanges (TRENDY) models from 1951 to 2010 and divided eastern China into five subregions for the study. We also used the New East Asian Summer Monsoon Index (NEWI) as a quantitative metric to distinguish between periods of strong and weak EASM. Building on this, this study aims to investigate the response of GPP in different subregions of eastern China. Regionally, under strengthened EASM years (1954, 1957, 1965, 1969, 1977, 1980, 1983, 1987, 1993 and 1998), East China experienced the most pronounced increase in GPP at 12 ± 21 (mean ± 1 sigma) gC m⁻² mon⁻¹ compared to the weak EASM years (1958, 1961, 1972, 1973,1978, 1981, 1985, 1994, 1997 and 2004). In contrast, Southwest China showed a decline in GPP at −4 ± 10 gC m⁻² mon⁻¹. Moreover, GPP also increased in Northeast and North China when EASM strengthened, while South China showed a decline in GPP. This indicated that GPP changed with monsoon intensity. According to the mechanism analysis, during strong EASM, there was intense moisture convergence through alterations in the atmospheric circulation field over East China and abundant precipitation, which further contributed to the increase in GPP. Downward solar radiation in Southwest China decreased with EASM enhancement, which suppressed GPP and hindered vegetation growth. Overall, the results highlight the importance of accurately predicting the impact of different EASM intensities of regional carbon fluxes.

Retrogressive thaw slumps (RTSs) caused by the thawing of ground ice on permafrost slopes have dramatically increased and become a common permafrost hazard across the Northern Hemisphere during previous decades. However, a gap remains in our comprehensive understanding of the spatial controlling factors, including the climate and terrain, that are conducive to these RTSs at a global scale. Using machine learning methodologies, we mapped the current and future RTSs susceptibility distributions by incorporating a range of environmental factors and RTSs inventories. We identified freezing-degree days and maximum summer rainfall as the primary environmental factors affecting RTSs susceptibility. The final ensemble susceptibility map suggests that regions with high to very high susceptibility could constitute (11.6 $\pm$ 0.78)% of the Northern Hemisphere's permafrost region. When juxtaposed with the current (2000–2020) RTSs susceptibility map, the total area with high to very high susceptibility could witness an increase ranging from (31.7 $\pm$ 0.65)% (SSP585) to (51.9 $\pm$ 0.73)% (SSP126) by the 2041–2060. The insights gleaned from this study not only offer valuable implications for engineering applications across the Northern Hemisphere, but also provide a long-term insight into the potential change of RTSs in permafrost regions in response to climate change.