Advances in Climate Change Research最新文献_第10页

Calibrating the simulated summer precipitation trend over the southern slope of the Tibetan Plateau in CMIP6 models using a sub-selection method CMIP6模式对青藏高原南坡夏季降水趋势模拟的亚选择校正

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2025.01.005

Hao-Lin Luo , Deliang Chen , Song Yang , Wei Yu , Zi-Qian Wang

Precipitation on the Tibetan Plateau (TP) is crucial for Asian water balance and global climate patterns. The southern slope of the TP (SSTP), a precipitation center in summer, has experienced a long-term drying trend in recent decades. Accurate simulations and projections of the change in summer precipitation over the SSTP are critical for future sustainable development. However, the multi-model ensemble (MME) from the current state-of-art Coupled Model Intercomparison Project Phase 6 indicates a wetting trend (∼2.58 mm per month per decade) over the SSTP during the period 1965–2014, contradicting the observations (∼−2.95 mm per month per decade). This discrepancy can be attributed to an overestimation of the stimulating impact of greenhouse gas (GHG) on precipitation trend in CMIP6 models. The traditional MME shows limited capability in capturing the response of atmospheric vertical motions and water vapor to the GHG forcing across the SSTP, resulting in wetting biases by the vertical moisture advection and thermodynamically controlled horizontal moisture advection. A sub-selection method is introduced to calibrate the historical simulated wetting trend at each grid point, through which the selected MME (SMME) more reasonably characterizes the precipitation response to GHG forcing and reproduces the observed drying trend, showing a value about −1.95 mm per month per decade. As GHGs are expected to be the major external forcing in the future, this method is extended to future projections. For the anticipated future wetting trend over the SSTP, the SMME results are constrained to 61.8% and 76.4% in the moderate- and high-emission scenarios, respectively, for the period 2050–2099.

青藏高原降水对亚洲水平衡和全球气候格局至关重要。青藏高原南坡是夏季降水中心，近几十年来经历了长期的干旱趋势。SSTP夏季降水变化的准确模拟和预估对未来的可持续发展至关重要。然而，来自当前最先进的耦合模式比对项目第6阶段的多模式集合（MME）表明，在1965-2014年期间，SSTP的湿润趋势（每十年每月~ 2.58 mm）与观测值（每十年每月~ - 2.95 mm）相矛盾。这种差异可归因于CMIP6模式对温室气体（GHG）对降水趋势的刺激作用的高估。传统的MME在捕捉大气垂直运动和水汽对SSTP上温室气体强迫的响应方面能力有限，导致垂直水汽平流和热力控制的水平水汽平流对湿化产生偏湿。采用子选择方法对各栅格点的历史模拟湿润趋势进行校正，所选的MME （SMME）更合理地表征了降水对温室气体强迫的响应，并再现了观测到的干燥趋势，其值约为- 1.95 mm /月/ 10年。由于预计温室气体将是未来的主要外部强迫，因此将这种方法推广到未来的预估中。在中等排放和高排放情景下，SMME的预测结果在2050-2099年期间分别为61.8%和76.4%。

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引用次数: 0

The sensitivity of the Asian summer monsoon simulation to horizontal resolution and air‒sea coupling in the FGOALS-f climate system model FGOALS-f气候系统模式下亚洲夏季风模拟对水平分辨率和海气耦合的敏感性

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2025.01.008

Xin-Yu He , Bian He , Qing Bao , Yi-Min Liu , Jian-Dong Li , Xiao-Cong Wang , Xiao-Chen Chen , Guo-Xiong Wu

The relative importance between horizontal resolution and air‒sea coupling on improving Asian summer monsoon (ASM) simulation skill remains unclear. In this study, we investigated the sensitivity of ASM to horizontal resolution and air‒sea coupling via simulations using a series of versions of the FGOALS-f model. The possible causes of bias are further analyzed. The results show that the Atmospheric Model Intercomparison Project (AMIP) run of high model resolution (25 km) achieves the highest skill on capturing ASM pattern, while the AMIP run of low model resolution (100 km) appears the lowest skill. Further analysis of the hydrological cycle and monsoon dynamics suggested that the simulation of the vertical moisture transport term was the primary contributor to excessive precipitation over the western Pacific. In addition, the excessive release of latent heat and strong ASM circulation are also responsible for the strong precipitation intensity in the AMIP simulation. Importantly, although the air‒sea coupled simulation exhibited the higher skill level, the simulated sea surface temperature (SST) exhibited an overall cold bias. This cold bias partly counteracted excessive moisture transport after air‒sea interaction is considered. Thus, increasing resolution could be helpful for more accurate simulation of advection, and together with the use of prescribed observed daily SST could play more important roles than only considering air‒sea coupling on improving ASM simulations.

水平分辨率和海气耦合对提高亚洲夏季风模拟水平的相对重要性尚不清楚。在这项研究中，我们通过使用一系列版本的FGOALS-f模型进行模拟，研究了ASM对水平分辨率和海气耦合的敏感性。进一步分析了产生偏倚的可能原因。结果表明，高模式分辨率（25 km）的大气模式比对项目（AMIP）对ASM模式的捕获能力最强，而低模式分辨率（100 km）的AMIP捕获能力最低。进一步的水文循环和季风动力学分析表明，垂直水汽输送项的模拟是西太平洋过度降水的主要原因。此外，潜热的过度释放和强ASM环流也是造成AMIP模拟中强降水强度的原因。重要的是，虽然海气耦合模拟表现出更高的技能水平，但模拟的海表温度（SST）总体上表现出冷偏。这种偏冷部分抵消了海气相互作用后的过量水分输送。因此，提高分辨率有助于更准确地模拟平流，并且与使用规定的日观测海温一起使用比仅考虑海气耦合对改进ASM模拟更重要。

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引用次数: 0

The interaction between thermokarst lake drainage and ground subsidence accelerates permafrost degradation 热岩溶湖排水与地面沉降的相互作用加速了多年冻土的退化

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2025.01.003

Yi-Ning Yu , Feng-Ming Hui , Yu Zhou , Xiao Cheng , Ming-Hu Ding

Since it is not viable to directly evaluate permafrost change based on remote sensing, thermokarst lake drainage (TLD) and ground subsidence serve as indicators for depicting permafrost degradation. Unfortunately, the interaction between these two land surface processes as well as their joint effect remain unclear. In this study, based on a homogenized Landsat-Sentinel archive, TLD was detected in the Lena Basin during 2000–2022 thawing seasons using the modified LandTrendr algorithm. Only 9.7% of thermokarst lakes (TLs) experienced remarkable drainage, TLs larger than 30 hm² were more prone to undergone drainage processes. The drainage proportion among TLs with different extents all exceeded 10% during 2013–2015, suggesting the gradual drainage which lasted for three years or longer was likely to be the dominating type. The subsidence rates (−1.64 ± 0.89 to −1.94 ± 1.41 mm per year) surrounding drained TLs were higher than regional average (−1.40 ± 1.19 to −1.60 ± 1.26 mm per year). As the distance to drained TLs decreased, the proportion of subsidence measurements, rates, and seasonal subsidence magnitude exhibited consistent increasing trends. The subsidence rate was higher in the direction of more intense drainage than that in other directions. The ground subsidence trigger TLD by providing meltwater and reducing structural support, while TLD in turn contributes to ground subsidence by forming drainage channels. More importantly, our findings proved that their interaction further accelerates permafrost degradation, which is critical for more accurately modeling the complex permafrost degradation processes under the warmer and wetter Arctic climate.

由于遥感无法直接评价多年冻土的变化，热岩溶湖排水（TLD）和地面沉降可作为描述多年冻土退化的指标。不幸的是，这两个陆面过程之间的相互作用以及它们的联合效应仍然不清楚。本研究基于均一化的Landsat-Sentinel档案，利用改进的LandTrendr算法在2000-2022年融化季节对勒拿河流域的TLD进行了检测。只有9.7%的热岩溶湖（TLs）经历了显著的排水过程，大于30 hm2的热岩溶湖更容易发生排水过程。2013-2015年不同程度tl的排水比例均超过10%，表明3年以上的渐进式排水可能为主导类型。排水隧道周边沉降速率（- 1.64±0.89 ~ - 1.94±1.41 mm /年）高于区域平均沉降速率（- 1.40±1.19 ~ - 1.60±1.26 mm /年）。随着与排水tl距离的减小，沉降量所占的比例、速率和季节沉降幅度均呈一致的增加趋势。沉降速率在排水强度较大的方向大于其他方向。地面沉降通过提供融水和减少构造支撑而引发TLD，而TLD又通过形成排水通道而导致地面沉降。更重要的是，我们的研究结果证明，它们的相互作用进一步加速了永久冻土的退化，这对于更准确地模拟更温暖、更潮湿的北极气候下复杂的永久冻土退化过程至关重要。

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引用次数: 0

Climate warming and wetting poses a severe threat to permafrost engineering stability on the Qinghai‒Xizang Plateau 气候增湿对青藏高原多年冻土工程稳定性构成严重威胁

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2025.02.001

Xiao-Ming Xu , Zhong-Qiong Zhang , Bo-Wen Tai , Si-Ru Gao , Yu-Zhong Yang , Qing-Bai Wu

Permafrost underpins engineering in cold regions but is highly sensitive to climate change. The mechanisms linking climate warming, precipitation changes, and permafrost degradation to infrastructure stability remain poorly understood on the Qinghai‒Xizang Plateau (QXP). Here, we present a multi-factor framework to quantify climate impacts on permafrost engineering stability. Our findings reveal a 26.7% decline in permafrost engineering stability from 2015 to 2100, with areas of extremely poor stability expanding by 0.3 × 10⁴ km² per decade (SSP2-4.5) and 0.6 × 10⁴ km² per decade (SSP5-8.5). Meanwhile, regions with relatively better stability shrink by 2.0 × 10⁴ km² and 2.9 × 10⁴ km² per decade, respectively. These changes driven primarily by a warming and wetting climate pattern. Moreover, engineering stability is maintained in northwestern and interior regions, whereas warmer, ice-saturated areas in the central plateau and southern Qilian Mountains degrade rapidly. Notably, cold permafrost is warming faster than warm permafrost, increasing its vulnerability. These insights provide a critical basis for guiding the future design, construction, and maintenance of permafrost infrastructure, enabling the development of adaptive engineering strategies that account for projected climate change impacts.

冻土是寒冷地区工程的基础，但对气候变化高度敏感。青藏高原气候变暖、降水变化和永久冻土退化与基础设施稳定性之间的联系机制尚不清楚。在这里，我们提出了一个多因素框架来量化气候对多年冻土工程稳定性的影响。研究结果表明，从2015年到2100年，冻土工程稳定性下降26.7%，稳定性极差的区域每10年增加0.3 × 104 km2 （SSP2-4.5）和0.6 × 104 km2 （SSP5-8.5）。稳定性较好的区域每10年分别收缩2.0 × 104 km2和2.9 × 104 km2。这些变化主要是由变暖和湿润的气候模式驱动的。西北和内陆地区保持工程稳定，而中部高原和祁连山南部较温暖、冰饱和地区退化较快。值得注意的是，寒冷的永久冻土比温暖的永久冻土变暖得更快，从而增加了其脆弱性。这些见解为指导未来冻土基础设施的设计、建设和维护提供了重要基础，使适应气候变化影响的工程策略得以发展。

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引用次数: 0

Assessing the added value of convection-permitting modeling for urban climate research: A case study in eastern China 城市气候研究中对流允许模式的附加价值评估：以中国东部地区为例

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2025.01.004

Lin Pei , Shi-Guang Miao , Xiang-Yu Huang , Zhong-Wei Yan , Deliang Chen

Accurate urban-resolving climate data are essential for urban climate research and applications. However, General Circulation Models (GCMs) often lack the resolution and urban representation needed to provide reliable fine-scale climate information over urban areas. Convection-permitting modeling (CPM) has emerged as a promising solution to this challenge, despite its computational demands. Evaluating the added value of CPM for specific regions is crucial. In this study, we utilized the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model, as a regional climate model, to assess the performance and added value of CPM at both regional (urban clusters) and local (megacity) scales. With an optimized dynamic downscaling scheme, we conducted 3-km-resolution CPM and 9-km-resolution dynamic downscaling modeling (DDM) during the summer of 2020 in eastern China, where most cities and urban clusters are located. At the local scale, CPM well reproduced observed precipitation rates at daily and sub-daily time scales, greatly improved the overestimation of drizzle-to-light rainfall events and underestimation of heavy-to-torrential rain events in ERA5 reanalysis data. Additionally, CPM effectively captured diurnal variations in precipitation across six sub-regions of eastern China, a capability lacking in DDM and ERA5. Moreover, CPM successfully reproduced the observed urban heat island intensity in Beijing by capturing the heterogeneous air temperature distribution, outperforming ERA5 and DDM. Our findings highlight the considerable added value of CPM in simulating sub-daily precipitation variations and urban heat island intensity over urban areas of China. These insights will greatly enhance future high-resolution regional climate simulations and climate change projections over urban areas in China.

准确的城市分辨气候数据是城市气候研究和应用的基础。然而，一般环流模式（GCMs）往往缺乏提供可靠的城市地区精细尺度气候信息所需的分辨率和城市代表性。对流允许建模（CPM）已经成为解决这一挑战的一个很有前途的解决方案，尽管它的计算要求很高。评估特定区域CPM的附加值至关重要。在本研究中，我们利用天气研究与预报（WRF）模型和单层城市冠层模型作为区域气候模型，评估了区域（城市群）和地方（特大城市）尺度上CPM的表现和附加值。利用优化后的动态降尺度方案，在中国东部地区开展了2020年夏季3 km分辨率CPM和9 km分辨率动态降尺度模拟（DDM）。在局地尺度上，CPM较好地再现了日和次日时间尺度的观测降水率，极大地改善了ERA5再分析资料中小雨到小雨事件的高估和暴雨到暴雨事件的低估。此外，CPM有效捕获了中国东部6个分区降水的日变化，这是DDM和ERA5所缺乏的能力。CPM通过捕获非均匀的气温分布，成功地再现了北京城市热岛强度，优于ERA5和DDM。研究结果表明，CPM在模拟中国城市地区亚日降水变化和城市热岛强度方面具有相当大的附加价值。这些见解将极大地增强未来中国城市地区的高分辨率区域气候模拟和气候变化预测。

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引用次数: 0

Wind power correction model designed by the quantitative assessment for the impacts of forecasted wind speed error 通过设计风电修正模型，对风速预报误差的影响进行定量评估

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2024.12.006

Zhi-Qi Xu , Tong Xue , Xin-Yu Chen , Jin Feng , Gu-Wei Zhang , Cheng Wang , Chun-Hui Lu , Hai-Shan Chen , Yi-Hui Ding

The errors in wind power forecast will incur additional cost. It is critical to quantify the relationship between forecasting error in wind speed and power output. Unlike previous works that have rarely considered the speed error, we propose a comprehensive and repeatable wind power forecast correction model that quantitatively assess the impacts of speed error on power error, based on the power curves, speed predictions and distribution of speed forecast error. In this correction model, the power forecast error is obtained by calculating the mathematical expectation. The mathematical expectation of the wind power error is equal to the integral of the wind power error multiplied by its associated probability. Additionally, power forecast error and its probability are constructed as a function of speed forecast error and speed forecast error probability, respectively. To evaluate the model performance, numerical simulations are carried out in Guilin, Xiangyang and Xihai. The results suggest that the model can reduce the biases between observed and forecasted power, with the correlation coefficients increasing by over 15% in Guilin and Xihai. Furthermore, the root mean square error exhibits notable decline, with a reduction of over 35%, from 0.34 to 0.21 MW, from 0.42 to 0.27 MW and from 0.39 to 0.24 MW in the three aforementioned locations, respectively. This study contributes to enhancing the efficiency of wind power generation.

风电预测的误差将产生额外的费用。对风速预报误差与输出功率之间的关系进行量化是至关重要的。与以往很少考虑速度误差的工作不同，本文基于功率曲线、速度预测和速度预测误差分布，提出了一种全面、可重复的风电预测修正模型，定量评估速度误差对功率误差的影响。在该修正模型中，通过计算数学期望得到功率预测误差。风力误差的数学期望等于风力误差乘以其相关概率的积分。另外，将功率预测误差及其概率分别构造为速度预测误差和速度预测误差概率的函数。为了评价模型的性能，在桂林、襄阳和西海进行了数值模拟。结果表明，该模型可以减小观测值与预测值之间的偏差，桂林和西海的相关系数提高了15%以上。此外，在上述三个地点，均方根误差分别从0.34兆瓦降至0.21兆瓦、从0.42兆瓦降至0.27兆瓦和从0.39兆瓦降至0.24兆瓦，降幅超过35%。本研究有助于提高风力发电效率。

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引用次数: 0

Evaluation of the performance of WRF9km in simulating climate over the upper Yellow River Basin WRF9km模拟黄河上游气候的性能评价

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2024.12.003

Yi-Jia Li , Xue-Jia Wang , Xiao-Hua Gou , Qi Wang , Tinghai Ou , Guo-Jin Pang , Mei-Xue Yang , Lan-Ya Liu , Li-Ya Qie , Tao Wang , Jia-Yu Wang , Si-Hao Wei , Xiao-Lai Cheng

Understanding the current climate in the Yellow River Basin is essential for accurately predicting future climate change and assessing its impacts on water resources and ecosystems; however, existing models exhibit notable biases in this region, primarily due to low resolution and errors in driving data and model domains. Using in-situ station observation data, CN05.1 gridded meteorological observation dataset, along with the ERA5 and MERRA2 reanalysis datasets, the performance of the WRF9km in simulating temperature and precipitation from 1980 to 2016 was comprehensively evaluated. Results indicate that the WRF9km model effectively captures the spatial pattern of air temperature, with a spatial correlation exceeding 0.86 (at the 95% confidence level) and a cold bias of −2.8 °C compared to CN05.1. This bias is primarily due to the underestimation of downward radiation and the overestimation of surface albedo. However, the WRF9km model fails to reproduce the observed warming trend across the entire region, especially during the summer. For precipitation, the WRF9km model generally reproduces the observed spatial pattern, with spatial correlation coefficients above 0.80 for all seasons except winter (at the 95% confidence level). However, the model overestimates precipitation relative to CN05.1 and underestimates it when compared to MERRA2. The precipitation bias is mainly attributed to the misrepresentation of wind fields and moisture by the WRF9km model. Regarding precipitation trends, different datasets yield divergent results, indicating substantial inter-annual variability that is difficult for the WRF9km to capture. Compared to the driving ERA5 data, the WRF9km model reduces cold biases between November and December, as well as wet biases across all seasons. The model also better simulates the winter warming trend in the western part of the UYRB and the summer wetting trend in the northern part. The evaluation of the WRF9km model provides valuable insights for the development of dynamical downscaling in terrain complex regions, especially for improving the surface albedo scheme and input driving data.

了解黄河流域当前气候变化对准确预测未来气候变化、评估其对水资源和生态系统的影响至关重要；然而，现有的模型在这一区域表现出明显的偏差，主要是由于驾驶数据和模型域的低分辨率和错误。利用站内观测资料、CN05.1格网气象观测数据集以及ERA5和MERRA2再分析数据集，对WRF9km模拟1980 - 2016年气温和降水的性能进行了综合评价。结果表明，WRF9km模式有效捕获了气温的空间格局，空间相关系数超过0.86（95%置信水平），与CN05.1相比，冷偏差为−2.8°C。这种偏差主要是由于对向下辐射的低估和对地表反照率的高估。然而，WRF9km模式无法重现整个地区观测到的变暖趋势，特别是在夏季。对于降水，WRF9km模式总体上再现了观测到的空间格局，除冬季外，其余季节的空间相关系数均在0.80以上（95%置信水平）。然而，该模式相对于CN05.1高估了降水，而相对于MERRA2低估了降水。降水偏倚的主要原因是WRF9km模式对风场和湿度的误报。关于降水趋势，不同的数据集产生不同的结果，表明WRF9km难以捕捉到大量的年际变化。与ERA5数据相比，wrf9公里模型减少了11月至12月之间的寒冷偏倚，以及所有季节的潮湿偏倚。该模式较好地模拟了西部冬季增暖趋势和北部夏季湿润趋势。WRF9km模式的评价为地形复杂地区动态降尺度的发展，特别是对地表反照率方案和输入驱动数据的改进提供了有价值的见解。

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引用次数: 0

Future climatic risks faced by the Beautiful China Initiative: A perspective for 2035 and 2050 美丽中国面临的未来气候风险：2035年和2050年展望

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2025.01.002

Zhong-Xue Ma , Hui-Juan Cui , Quan-Sheng Ge

Identifying high-risk areas for climatic disasters and their overlaps during the implementation of the Beautiful China Initiative fills a critical gap in disaster risk research, which often lacks quantitative analyses of the combined risks from multiple disasters. This study evaluates key climatic risks and their overlaps, including heavy storms, heatwaves, and droughts, that may affect the Beautiful China Initiative objectives in 2035 and 2050. The analysis is based on three shared socioeconomic pathways (SSP126, SSP370, and SSP585), incorporating vulnerability, disaster risks, and exposure levels. The findings indicate that the severity of climatic risks in China will intensify over time and with climate warming. The western regions will face more severe single-climate risks, while the eastern regions will encounter increasingly severe comprehensive climatic risks. In the western regions, by 2035, the Tarim Basin in Xinjiang is projected to experience heatwave risks exceeding Level 5, while Tibet and Qinghai will face drought risks above Level 6. By 2050, more areas will escalate to Level 6 and 7 risks. In the eastern regions, by 2035, Shandong, Henan, the Pearl River Delta, and the Beijing, Tianjin, Hebei region are expected to face comprehensive risks from heavy storms, heatwaves, and droughts. By 2050, the overlapping high-risk areas will expand, covering the eastern parts of the Yangtze River Economic Belt. Furthermore, higher radiative forcing scenarios are associated with increased risks. This study provides critical insights for developing targeted disaster prevention and management systems across different regions of China, offering guidance for the effective implementation of the Beautiful China Initiative.

在“美丽中国”的实施过程中，确定气候灾害高发地区及其重叠区域，填补了灾害风险研究的一个关键空白，这一空白往往缺乏对多种灾害综合风险的定量分析。本研究评估了可能影响2035年和2050年“美丽中国”目标的主要气候风险及其重叠部分，包括暴雨、热浪和干旱。该分析基于三个共享的社会经济路径（SSP126、SSP370和SSP585），包括脆弱性、灾害风险和暴露水平。研究结果表明，随着时间的推移和气候变暖，中国气候风险的严重程度将加剧。西部地区将面临更加严峻的单一气候风险，东部地区将面临更加严峻的综合气候风险。在西部地区，预计到2035年，新疆塔里木盆地将经历超过5级的热浪风险，而西藏和青海将面临超过6级的干旱风险。到2050年，更多地区将升级为6级和7级风险。在东部地区，到2035年，山东、河南、珠江三角洲和京津冀地区预计将面临暴雨、热浪和干旱的综合风险。到2050年，重叠的高风险区域将扩大，覆盖长江经济带东部。此外，较高的辐射强迫情景与风险增加有关。本研究为中国不同地区制定有针对性的灾害预防和管理系统提供了重要见解，为有效实施“美丽中国”倡议提供了指导。

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引用次数: 0

Traditional ecological knowledge in High Mountain Asia: A pathway to climate resilience in agriculture amidst changing climates 亚洲高山地区的传统生态知识：气候变化中农业气候适应能力的途径

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2025.01.009

Lavanya Witharana , Deliang Chen , Julia Curio , Anders Burman

Traditional Ecological Knowledge (TEK) often represents centuries of empirical observation and adaptation to specific ecological conditions, which is relevant to meaningful nature-human relations. Yet, TEK is rarely taken into account. This study examines the role of TEK-based agriculture in promoting adaptation and resilience to climate change in the mountain agricultural systems of the Hindu Kush Himalaya (HKH) region. Through an extensive literature review, it identifies and synthesizes TEK-based agricultural practices, with a focus on soil and fertility management, strategies to manage agroecological disruptions and agroforestry. The findings indicate that these practices align with the climate change adaptation priorities of HKH countries, particularly in developing water- and nutrient-efficient crop cultivation systems and enhancing soil organic matter. While TEK-based agricultural methods can support regional climate change adaptation and resilience, the alteration or loss of traditional practices due to socio-economic factors may worsen the impacts of climate change. Therefore, recognizing and validating TEK within regional and local adaptation frameworks are essential for maintaining the resilience of traditional agriculture in the HKH region.

传统的生态知识（TEK）往往代表了几个世纪的经验观察和对特定生态条件的适应，这与有意义的自然与人的关系有关。然而，TEK很少被考虑在内。本研究探讨了兴都库什-喜马拉雅（HKH）地区山地农业系统在促进气候变化适应和恢复力方面的作用。通过广泛的文献综述，它确定并综合了基于技术的农业实践，重点是土壤和肥力管理、管理农业生态破坏的战略和农林业。研究结果表明，这些做法符合HKH国家适应气候变化的优先事项，特别是在发展节水和营养高效的作物种植系统和提高土壤有机质方面。虽然以技术为基础的农业方法可以支持区域气候变化适应和恢复能力，但由于社会经济因素而改变或丧失传统做法可能会加剧气候变化的影响。因此，在区域和地方适应框架内认识和验证TEK对于保持HKH地区传统农业的复原力至关重要。

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引用次数: 0

Climatic impacts on electricity consumption of urban residential buildings in China 气候对中国城市住宅用电量的影响

IF 6.4 1区地球科学 Q1 ENVIRONMENTAL SCIENCES

Advances in Climate Change Research

Pub Date : 2025-02-01 DOI: 10.1016/j.accre.2024.12.004

Yang-Yang Guo , Mei-Xuan Teng , Chen Zhang , Sheng-Nan Wang , Yi-Ming Wei

Evaluating the effects of climate change is crucial for developing effective strategies for both mitigation and adaptation policies. However, a comprehensive quantification of the precise effects of climate change on electricity consumption in China's urban residential buildings has been hampered by the scarcity of data. Here, we employ a verified county-level unbalanced panel dataset to estimate the effect of cooling degree days (CDD) and heating degree days (HDD) on the electricity consumption of urban residential buildings in China. The results indicate that a 1% increase in CDD and HDD is linked to a corresponding rise of 0.114% and 0.457% in electricity consumption per unit of floor space in urban residential buildings, respectively. However, these effects are diminished as income increases, implying residents have more strategies to adapt to climate change as income rises. The impacts of temperature fluctuations exhibit variability across different climate zones, building heights, and construction years. Specifically, buildings in regions characterized by hot summers and cold winters, as well as those with hot summers and warm winters, exhibit greater sensitivity to temperature fluctuations compared to the buildings located in regions with severe cold and predominantly cold climates. Additionally, low-rise buildings tend to consume more electricity than multi-story and mid-to-high-rise buildings in response to temperature variation. Interestingly, new buildings are more vulnerable to temperature fluctuations than older buildings. These findings offer a comprehensive and accurate assessment of climatic impacts in different climate zones, enabling a more profound comprehension of climate change. This study provides empirical evidence that the effect of climate change on building energy use varies with building heights, addressing a critical gap in prior research.

评估气候变化的影响对于制定缓解和适应政策的有效战略至关重要。然而，由于数据匮乏，对气候变化对中国城市住宅用电量的精确影响的全面量化一直受到阻碍。本文采用一个经过验证的县级非平衡面板数据集，对中国城市住宅用电量的制冷度日（CDD）和供暖度日（HDD）的影响进行了估算。结果表明，CDD和HDD每增加1%，城市住宅单位建筑面积用电量分别相应增加0.114%和0.457%。然而，这些影响随着收入的增加而减弱，这意味着随着收入的增加，居民有更多的策略来适应气候变化。温度波动的影响在不同气候带、建筑高度和施工年份之间表现出差异。具体而言，夏热冬冷地区以及夏热冬暖地区的建筑物对温度波动的敏感性高于严寒和以寒冷为主的地区的建筑物。此外，低层建筑对温度变化的响应往往比多层和中高层建筑消耗更多的电力。有趣的是，新建筑比旧建筑更容易受到温度波动的影响。这些发现对不同气候带的气候影响提供了全面和准确的评估，使人们能够更深刻地理解气候变化。本研究提供了气候变化对建筑能源使用的影响随建筑高度而变化的实证证据，解决了以往研究中的一个关键空白。

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引用次数: 0