Explore the vast range of titles available.

Taking the megacity of Beijing as an example, a short‐time Fourier transform (STFT) method was employed to extract the multi‐timescale evolution pattern of the canopy urban heat island intensity (CUHII) during 2000–2020. The STFT of CUHII showed a close relationship between the evolution of the CUHII in Beijing and the background meteorological forcing at intra‐annual, weather and intra‐daily scales. The intra‐annual‐scale spectrum of CUHII exhibited an increasing trend with obvious seasonal variation of the canopy urban heat island (CUHI). The intra‐daily‐scale spectrum of CUHII showed an increasing trend with the nighttime CUHI developing faster. Increasing Western Pacific Subtropical High intensity can enhance the seasonal and diurnal fluctuations of CUHII. The weather‐scale spectrum of CUHII is controlled by weather system evolution, showing that the frequency of cold/heat waves (CWs/HWs) in Beijing was significantly negatively correlated with the weather‐scale spectral intensity of the CUHII. CWs and HWs can increase the CUHII for a long duration. Plain Language Summary The canopy urban heat island (CUHI) phenomenon can affect human health and the ecological environment, and its multi‐timescale variability brings great uncertainty to the study of urban climates worldwide. In this study, taking the megacity of Beijing as an example, a novel short‐time Fourier transform (STFT) method was used to extract the multi‐timescale pattern of the CUHI intensity (CUHII) during 2000–2020. The STFT of CUHII showed a close relationship between the CUHI and the background meteorological forcing at intra‐annual, weather and intra‐daily scales. The intra‐annual spectrum of CUHII showed an increasing trend with a V‐shaped mode. The local climatic backgrounds of different cities can lead to differences in the seasonal development of the CUHI. The intra‐daily spectrum of CUHII showed an increasing trend due to the asymmetry in the day/night development of the CUHI. Increasing Western Pacific Subtropical High Intensity can enhance the seasonal and diurnal fluctuations of CUHII. The weather‐scale spectrum of CUHII was mainly controlled by weather system evolution, showing that cold waves and heat waves can increase the CUHII over a long duration. Our findings indicate that the evolution of CUHII is a nonlinear and complex process that is directly related to multi‐timescale background climate forcing. Key Points Using a short‐time Fourier transform to study the multi‐timescale evolution of the canopy urban heat island intensity (CUHII) Close relationships existed between CUHII and the background meteorological forcing at intra‐annual, intra‐daily, and weather scales The frequency of cold/heat waves in Beijing showed a significant negative correlation with the weather‐scale spectral intensity of the CUHII

An unprecedented cold wave intruded into East Asia in early January 2021 and led to record-breaking or historical extreme low temperatures over vast regions. This study shows that a major stratospheric sudden warming (SSW) event at the beginning of January 2021 exerted an important influence on this cold wave. The major SSW event occurred on 2 January 2021 and subsequently led to the displacement of the stratospheric polar vortex to the East Asian side. Moreover, the SSW event induced the stratospheric warming signal to propagate downward to the mid-to-lower troposphere, which not only enhanced the blocking in the Urals–Siberia region and the negative phase of the Arctic Oscillation, but also shifted the tropospheric polar vortex off the pole. The displaced tropospheric polar vortex, Ural blocking, and another downstream blocking ridge over western North America formed a distinct inverted omega-shaped circulation pattern (IOCP) in the East Asia–North Pacific sector. This IOCP was the most direct and impactful atmospheric pattern causing the cold wave in East Asia. The IOCP triggered a meridional cell with an upward branch in East Asia and a downward branch in Siberia. The meridional cell intensified the Siberian high and low-level northerly winds, which also favored the invasion of the cold wave into East Asia. Hence, the SSW event and tropospheric circulations such as the IOCP, negative phase of Arctic Oscillation, Ural blocking, enhanced Siberian high, and eastward propagation of Rossby wave eventually induced the outbreak of an unprecedented cold wave in East Asia in early January 2021.

Climate change is creating a new era of infectious disease crises, further exacerbated by extreme weather. However, the relationship between extreme weather and infectious disease remain unclear. Here, we provide a new quantitative study on the impact of cold wave on COVID‐19 as an example. We found that during cold waves, extreme cold temperatures coupled with rapid aerosol transport accelerated COVID‐19 outbreaks. It directly increased the number of COVID‐19 cases in Beijing by 28.1% in the winter of year 2022. More urgently, cold temperatures led to a higher risk of death during infectious disease outbreaks, with a 7.07% increase in confirmed deaths and a 16.61% increase in excess mortality. Our findings emphasize the urgent need to promote a synergistic policy for responding to infectious diseases during cold wave disasters in order to minimize the risk of death among the elderly and those with underlying diseases. Plain Language Summary The sudden drop in temperature and rapid spread of aerosols during cold waves resulted in a higher prevalence of infectious diseases. At the same time, low temperatures resulted in a higher risk of death due to infectious diseases and a variety of other factors during the epidemic. Key Points The rapid dispersion of aerosols during cold waves hastens the transmission of infectious diseases Low temperatures contribute to higher risk of death during infectious disease outbreaks

Cardiovascular disease is the most common cause of death globally. Examining the relationship between the extreme temperature events (e.g. heat and cold waves) and cardiovascular mortality has profound public significance. However, this evidence is scarce, particularly those from China. We collected daily data on cardiovascular mortality and meteorological conditions from 31 major Chinese cities during the maximum period of 2007-2013. A two-stage analysis was used to estimate the effects of heat and cold waves, and the potential effect modification of their characteristics (intensity, duration, and timing in season) on cardiovascular mortality. Firstly, a generalized quasi-Poisson regression combined with distributed lag nonlinear model was used to evaluate city-specific effects. Then, the meta-analysis was performed to pool effect estimates at the national scale. Overall, cardiovascular mortality risk increased by 19.03% (95%CI: 11.92%, 26.59%) during heat waves and 54.72% (95%CI: 21.20%, 97.51%) during cold waves. The effect estimates varied by the wave's characteristics. In heat wave days, the cardiovascular mortality risks increased by 3.28% (95%CI: −0.06%, 6.73%) for every 1 °C increase in intensity, 2.84% (95%CI: 0.92%, 4.80%) for every 1-d more in duration and −0.07% (95%CI: −0.38%, 0.24%) for every 1-d late in the staring of heat wave; the corresponding estimates for cold wave were 1.82% (95%CI: −0.04%, 3.72%), 1.52% (95%CI: 0.60%, 2.44%) and −0.26% (95%CI: −0.67%, 0.16%). Increased susceptibility to heat and cold waves was observed among patients with ischemic heart disease, females, the elderly, and those with lower education level. And consistent vulnerable populations were found for the effects of changes in cold and heat wave's characteristics. The findings have important implications for the development of early warning systems and plans in response to heat and cold waves, which may contribute to mitigating health threat to vulnerable populations.

Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk.

Two supercold waves straddling 2020 and 2021 successively hit China and caused record-breaking extremely low temperatures. In this study, the distinct features of these two supercold waves are analyzed on the medium-range time scale. The blocking pattern from the Kara Sea to Lake Baikal characterized the first cold wave, while the large-scale tilted ridge and trough over the Asian continent featured the second cold wave. Prior to the cold waves, both the northwest and hyperpolar paths of cold air contributed to a zonally extensive cold air accumulation in the key region of Siberia. This might be the primary reason why strong and extensive supercold waves occur even under the Arctic amplification background. The two cold waves straddling 2020 and 2021 exhibited distinct features: (1) the blocking circulation occurred to the north or the east of the Ural Mountains and was not confined only to the Ural Mountains as it was for the earlier cold waves; (2) the collocation of the Asian blocking pattern and the polar vortex deflection towards East Asia preferred the hyperpolar path of cold air accumulation and the subsequent southward outburst; and (3) both high- and low-frequency processes worked in concert, leading to the very intense cold waves. The cold air advance along the northwest path, which coincides with the southeastward intrusion of the Siberian High (SH) front edge, is associated with the high-frequency process, while the cold air movement along the hyperpolar path, which is close to the eastern edge of the SH, is controlled by the low-frequency process.

Cold wave (CW) and Severe Cold wave (SCW) prevail over India as a seasonal episode during winter season. The present study analyzes the changing spatio-temporal characteristics and trends of cold waves over India's meteorological subdivisions from 1951 to 2021 (Dec–Feb). It uses minimum temperature data obtained from the India Meteorological Department (IMD) at a spatial resolution of 0.5° × 0.5°. A declining trend in both CW and SCW days is found with a decrease of − 0.29 days/decade in CW days and 0.02 days/decade in SCW days. The study also explored the trend of spells of three, five and seven days of CW and SCW and found a significantly decreasing trend of − 0.02 days/decade and − 0.05 days/decade in 3 and 5-day SCW spell respectively. A consistent significant increase of 0.027 °C/decade in minimum temperature post 1980s is also reported in the study with a simultaneous decrease in cold wave. While the northwestern and northern meteorological subdivision record highest CW and SCW spells, a declining trend is reported in these regions, highest being in West Rajasthan (− 1.3 days/decade) and Punjab (− 1.3 days/decade). A significant increasing trend has been observed in CW, SCW days/spells in the eastern, eastern coastal and southern subdivisions such as Bihar (0.16 days/decade), Jharkhand (0.05 days/decade) and Odisha (0.2 days/decade). Overall, the study reports a decline in cold waves and identifies new cold wave-prone regions in the country. The study also highlights the emerging severe impact on agriculture sector in the scenario of declining cold extremes over major wheat producing belts.

Given the increasing health risks associated with climate change, particular attention is focused on the elderly as a vulnerable group. This study aimed to analyze how these climate extremes impact the health and hospitalization rates of these patients. In this ecological time series study, daily Meteorological and environmental pollutants data for Dezful and hospitalization records for cardiovascular diseases based on International Classification of Diseases, 10th codes were collected from 2013 to 2019. Definitions for heat waves and cold waves were established Based on previous studies in this field. The study utilized a combination of Distributed Lag Nonlinear Models and Quasi Poisson analysis to investigate the association between each definition of cold and heat waves and hospitalization. The results indicate that heat waves are associated with an increased risk of hospital admissions due to cardiovascular disease in individuals over 75 years of age. Additionally, cold waves significantly increase the risk of hospitalization due to cardiovascular disease in individuals aged 65 to 74 years. Specifically, in the section on added effects, the results show that Cold Wave impacts the risk of hospitalization in patients aged 56 to 74 years (added effects: lags of 0, 0–2, 0–6, and 0–13). This study highlights the significant impact of heat and cold waves on the risk of hospitalization for cardiovascular diseases in Dezful. Older adults, especially those over 65, are particularly vulnerable to these climate-related health risks. As climate change progresses, it is essential to implement public health strategies that protect at-risk populations during extreme weather events.

Aiming at the gross error and data missing in the monitoring sequence of concrete dam, the variational mode decomposition method and the gated recurrent unit depth learning algorithm are respectively used to extract the effective information of the monitoring sequence. On the basis of the research on the characteristics of the traditional concrete dam structural behavior characterization model, the paper explores the expression mode of the effect of cold wave, freeze-thaw, wintering layer and other influencing factors. In order to reflect the correlation between the monitoring measurement values, the space coordinate variable is introduced to establish the monitoring measurement change characterization model, so as to realize the characterization and analysis of the structural behavior changes of concrete dams in cold regions and the quantitative analysis of various influencing factors. Based on the research in this article, we can fully understand the operation status of the dam, identify hidden dangers, and carry out relevant risk investigation and reinforcement. It can reduce the risk of dam failure to a certain extent.

Extreme cold waves frequently occur in east of China that dramatically endanger ecological agriculture, power infrastructure and human life. In this study, we found that the 'Warm Arctic-Cold Siberia' pattern (WACS) significantly enhanced cold waves in east of China according to daily composites from 1979 to 2018. During the winter 2020/21, a record-breaking cold wave broke out following a noticeable WACS phenomenon and induced the record-low surface air temperature at 60 meteorological stations since they were established (nearly 60 years). On 3 January 2021, the difference in temperature anomaly between the Barents–Kara Sea and Siberia reached 20 °C, the peak of winter 2020/21. With a shrinking meridional temperature gradient, the atmospheric baroclinicity weakened correspondingly. The accompanying atmospheric anomalies, i.e. the persistent Ural Blocking High and Baikal deep trough effectively transported stronger cold air than the sole impact from Arctic warming. After 4 d, the east of China experienced a severe surface air temperature decrease of more than 8 °C, covering an area of 2500 000 km2. During the same winter, a record-breaking warm event occurred in February 2021, and the 'Cold Arctic-Warm Eurasia' pattern also appeared as a precursory signal. Furthermore, on the interannual scale, the connection between winter-mean temperature anomalies in east of China and the WACS pattern also existed and even performed more strongly in both observations and simulation data of CMIP6.