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Reconstructing high-resolution climate data from historical documents is hindered by subjectivity and a lack of standardization. This study develops and validates a novel framework to overcome these challenges. In this paper, a historical weather classification lexicon is constructed by optimizing natural language processing (NLP) techniques. Leveraging semantic clustering and dynamic expansion, this lexicon effectively captures the linguistic diversity associated with weather events across different regions and intensity levels. Building on this lexicon, we propose a multi-dimensional index system to quantify historical weather grades. This system includes indicators such as weather intensity, agricultural impact, economic impact, social impact, and population casualties. For each indicator, scientific and objective weights are assigned using the entropy method combined with expert judgment. To validate the effectiveness of our approach, we extracted low-temperature weather records from historical documents of Guangdong and Hebei provinces in China. The results show that the overall trend of low-temperature weather in these two provinces is consistent with existing research on climate change during the Qing Dynasty. Moreover, the provincial trend maps reveal not only synchronous change patterns but also significant regional differences. A Random Forest model was employed to validate our index, achieving a classification accuracy of 94.0%, with Area Under the Curve(AUC) scores exceeding 0.98 for low-grade events. This data-driven methodology offers a replicable and scalable tool for converting qualitative historical narratives into high-resolution quantitative climate data, thereby enhancing our understanding of past climate variability and its societal impacts.

Adapting to climate change is not a new phenomenon for the Arab world. For thousands of years, the people in Arab countries have coped with the challenges of climate variability by adapting their survival strategies to changes in rainfall and temperature. Their experience has contributed significantly to the global knowledge on climate change and adaptation. But over the next century global climatic variability is predicted to increase, and Arab countries may well experience unprecedented extremes in climate. Temperatures may reach new highs, and in most places there may be a risk of less rainfall. Under these circumstances, Arab countries and their citizens will once again need to draw on their long experience of adapting to the environment to address the new challenges posed by climate change. This report prepared through a consultative process with Government and other stakeholders in the Arab world assesses the potential effects of climate change on the Arab region and outlines possible approaches and measures to prepare for its consequences. It offers ideas and suggestions for Arab policy makers as to what mitigating actions may be needed in rural and urban settings to safeguard key areas such as health, water, agriculture, and tourism. The report also analyzes the differing impacts of climate change, with special attention paid to gender, as a means of tailoring strategies to address specific vulnerabilities. The socioeconomic impact of climate change will likely vary from country to country, reflecting a country's coping capacity and its level of development. Countries that are wealthier and more economically diverse are generally expected to be more resilient. The report suggests that countries and households will need to diversify their production and income generation, integrate adaptation into all policy making and activities, and ensure a sustained national commitment to address the social, economic, and environmental consequences of climate variability. With these coordinated efforts, the Arab world can, as it has for centuries, successfully adapt and adjust to the challenges of a changing climate.

This paper is focused on the palaeoclimatic significance of snow-avalanche (snow-flow) activity and palaeobotanical data derived frompostglacial colluvium. It is based on a series of case studies from western Norway, with emphasis on sedimentary facies and radiocarbon dating of the deposits. The present data demonstrate that the colluvial sedimentary successions bear important palaeoclimatic signals related to extreme weather events, and the record of snow avalanches reveals, in particular, a detailed pattern of winter climatic conditions (snow fall rates and the frequency of winter storms). The Late Weichselian record shows some snow avalanching around 12 300–12 000 BP, suggesting occurrence of major winter storms at that time. An overwhelming amount of data demonstrates the dramatic increase in snow-flow processes during the Younger Dryas chronozone, documenting that this phase was characterized by severe winter storms with distinct snowfall rates. The Holocene record of snow avalanching shows in general a good correspondence with the regional record of glacier fluctuations, indicating that both the avalanche and the glacier records were controlled primarily by winter climatic conditions. Snow-flow sedimentation has been recorded from c. 7000 BP (7800 cal. BP), but the records show highly fluctuating winter climatic conditions throughout the Holocene period. Both the avalanche activity and the pollen data suggest a clear deterioration in the winter climate from c. 4700 BP (5400 cal. BP), corresponding with other palaeoclimatic records in Scandinavia. The period between 3900 and 3100 BP (4350–3350 cal. BP) seems to have been one of the most severe phases in the Holocene, documented by a dramatic increase in snow-flow processes resulting in opening of the local forests. Two phases of snow avalanching have been identified during the'Little Ice Age' (ad 1450–1920).These data further indicate that episodes characterized by heavy snowfall and strong winds were more frequent in some phases of the Holocene than they are today.

A 350-cm-long sediment core sequence from Dahu Swamp situated in the eastern Nanling Mountains was selected for high-resolution paleoclimatic reconstruction since the Late Glacial period. The multi-proxy records of this paper reveal several evidently dry and cold events that may coincide with the Oldest Dryas, the Older Dryas, the Younger Dryas in the late deglacial period. Two relatively wetter and warmer phases occurred in ca. 15,000-14,400 cal yr B.P. and 13,500-12,800 cal yr B.P. respectively may correspond to the Boiling and Allerod warming events. The Younger Dryas event （ca. 12,800-11,500 cal yr B.P.） revealed by multi-proxies was characterized by relatively colder and drier climate. A warmer and wetter climate, occurred in ca. 10,000~5000 cal yr B.P., was consistent with the Holoeene Optimum, which coincided with the maximum Northern Hemisphere insolation. The ＂8.2kyr cool event＂ and even the ＂8.8kyr cool event＂ were indicated as well from our sediment core. A dry mid-Holocene period （ca. 60000 3000 cal yr B.P.） indicated by multi-proxies does not follow the traditional concept of the wet mid-Holocene conditions observed in other regions in China.

A preliminary study on the advance and the retreat of Qingtu Lake and its climatic records of the Holocene lacustrine deposits has been made through comprehensive analysis. The study shows that the modes characteristics of climatic change in Eastern Hexi Corridor was provided with the corresponding relationship of warm-moist and cold-dry during the scale longer than hundred years. As a result of climatic changes and human activities, Qingtu-Lake cycle has undergone four lake-retreated and three lake-advanced stages since 6000 a B. P. Based on the study on lacustrine sedimentary color, grain size, Fe^sup 3+^/Fe^sup 2+^ and organic matter, the authors put forward that a warm period existed during the phase of 335-480 A. D. in the studied area. This warm period could be further testified by a lot of evidences obtained from the historical documents and the natural records of Qingtu Lake. In brief, the evolution of lakes in Eastern Hexi Corridor is characterized by sedimentary continuity, fast sedimentary rate and high resolution, it not only indicate the paleoenvironmental and climatic change in Holocene, but also can reflect the intensity of Eastern Asia monsoon.[PUBLICATION ABSTRACT]

Understanding the dynamics and physics of climate extremes will be a critical challenge for twenty-first-century climate science. Increasing temperatures and saturation vapor pressures may exacerbate heat waves, droughts, and precipitation extremes. Yet our ability to monitor temperature variations is limited and declining. Between 1983 and 2016, the number of observations in the University of East Anglia Climatic Research Unit (CRU) T max product declined precipitously (5900 → 1000); 1000 poorly distributed measurements are insufficient to resolve regional T max variations. Here, we show that combining long (1983 to the near present), high-resolution (0.05°), cloud-screened archives of geostationary satellite thermal infrared (TIR) observations with a dense set of ~15 000 station observations explains 23%, 40%, 30%, 41%, and 1% more variance than the CRU globally and for South America, Africa, India, and areas north of 50°N, respectively; even greater levels of improvement are shown for the 2011–16 period (28%, 45%, 39%, 52%, and 28%, respectively). Described here for the first time, the TIR T max algorithm uses subdaily TIR distributions to screen out cloud-contaminated observations, providing accurate (correlation ≈0.8) gridded emission T max estimates. Blending these gridded fields with ~15 000 station observations provides a seamless, high-resolution source of accurate T max estimates that performs well in areas lacking dense in situ observations and even better where in situ observations are available. Cross-validation results indicate that the satellite-only, station-only, and combined products all perform accurately ( R ≈ 0.8–0.9, mean absolute errors ≈ 0.8–1.0). Hence, the Climate Hazards Center Infrared Temperature with Stations (CHIRTS max ) dataset should provide a valuable resource for climate change studies, climate extreme analyses, and early warning applications.

Aedes aegypti and Ae. albopictus are the primary vectors that transmit several arboviral diseases, including dengue, chikungunya, and Zika. The world is presently experiencing a series of outbreaks of these diseases, so, we still require to better understand the current distributions and possible future shifts of their vectors for successful surveillance and control programs. Few studies assessed the influences of climate change on the spatial distributional patterns and abundance of these important vectors, particularly using the most recent climatic scenarios. Here, we updated the current potential distributions of both vectors and assessed their distributional changes under future climate conditions. We used ecological niche modeling approach to estimate the potential distributions of Ae. aegypti and Ae. albopictus under present-day and future climate conditions. This approach fits ecological niche model from occurrence records of each species and environmental variables. For each species, future projections were based on climatic data from 9 general circulation models (GCMs) for each representative concentration pathway (RCP) in each time period, with a total of 72 combinations in four RCPs in 2050 and 2070. All ENMs were tested using the partial receiver operating characteristic (pROC) and a set of 2,048 and 2,003 additional independent records for Ae. aegypti and Ae. albopictus, respectively. Finally, we used background similarity test to assess the similarity between the ENMs of Ae. aegypti and Ae. albopictus. The predicted potential distribution of Ae. aegypti and Ae. albopictus coincided with the current and historical known distributions of both species. Aedes aegypti showed a markedly broader distributional potential across tropical and subtropical regions than Ae. albopictus. Interestingly, Ae. albopictus was markedly broader in distributional potential across temperate Europe and the United States. All ecological niche models (ENMs) were statistically robust (P < 0.001). ENMs successfully anticipated 98% (1,999/2,048) and 99% (1,985/2,003) of additional independent records for both Ae. aegypti and Ae. albopictus, respectively (P < 0.001). ENMs based on future conditions showed similarity between the overall distributional patterns of future-day and present-day conditions; however, there was a northern range expansion in the continental USA to include parts of Southern Canada in case of Ae. albopictus in both 2050 and 2070. Future models also anticipated further expansion of Ae. albopictus to the East to include most of Europe in both time periods. Aedes aegypti was anticipated to expand to the South in East Australia in 2050 and 2070. The predictions showed differences in distributional potential of both species between diverse RCPs in 2050 and 2070. Finally, the background similarity test comparing the ENMs of Ae. aegypti and Ae. albopictus was unable to reject the null hypothesis of niche similarity between both species (P > 0.05). These updated maps provided details to better guide surveillance and control programs of Ae. aegypti and Ae. albopictus. They have also significant public health importance as a baseline for predicting the emergence of arboviral diseases transmitted by both vectors in new areas across the world.

Climatic instability, especially on decadal to multi-decadal time scales, has a profound impact on societal development and human welfare in semi-arid and arid regions. Previous work suggested that arid northwestern China was characterized by a dry Medieval Warm Period (MWP, from ca. 1000 to 1300 AD) and a wet Little Ice Age (LIA, from ca. 1400 to 1850 AD), but there is a lack of studies addressing the issue of climatic variability during the last millennium. Here, we present results from a diverse range of proxy records from northwestern China with the aim of evaluating the time variation of hydroclimatic variability during the MWP and LIA. Within the context of an overall cold climate, we detected a pattern of higher moisture variability during the LIA compared to the MWP. A comparison of the proxy records of climatic instability during the LIA from northwestern China with the major modes of SST and atmospheric variability, which affect moisture/precipitation in Asia, suggests that the instability of the North Atlantic Oscillation (NAO) from middle- to high-latitude regions during the LIA was a major driving factor. The westerlies may play an important role in linking the unstable climatic conditions observed in the above-mentioned regions. Our results support the concept that climatic instability was above the norm during cold periods, in contrast with present observations that demonstrate the occurrence of increasingly extreme climatic events with ongoing global warming.

A database is described that has been designed to fulfill the need for daily climate data over global land areas. The dataset, known as Global Historical Climatology Network (GHCN)-Daily, was developed for a wide variety of potential applications, including climate analysis and monitoring studies that require data at a daily time resolution (e.g., assessments of the frequency of heavy rainfall, heat wave duration, etc.). The dataset contains records from over 80 000 stations in 180 countries and territories, and its processing system produces the official archive for U.S. daily data. Variables commonly include maximum and minimum temperature, total daily precipitation, snowfall, and snow depth; however, about two-thirds of the stations report precipitation only. Quality assurance checks are routinely applied to the full dataset, but the data are not homogenized to account for artifacts associated with the various eras in reporting practice at any particular station (i.e., for changes in systematic bias). Daily updates are provided for many of the station records in GHCN-Daily. The dataset is also regularly reconstructed, usually once per week, from its 20+ data source components, ensuring that the dataset is broadly synchronized with its growing list of constituent sources. The daily updates and weekly reprocessed versions of GHCN-Daily are assigned a unique version number, and the most recent dataset version is provided on the GHCN-Daily website for free public access. Each version of the dataset is also archived at the NOAA/National Climatic Data Center in perpetuity for future retrieval.

Recent climate extremes have broken long-standing records by large margins. Such extremes unprecedented in the observational period often have substantial impacts due to a tendency to adapt to the highest intensities, and no higher, experienced during a lifetime. Here, we show models project not only more intense extremes but also events that break previous records by much larger margins. These record-shattering extremes, nearly impossible in the absence of warming, are likely to occur in the coming decades. We demonstrate that their probability of occurrence depends on warming rate, rather than global warming level, and is thus pathway-dependent. In high-emission scenarios, week-long heat extremes that break records by three or more standard deviations are two to seven times more probable in 2021–2050 and three to 21 times more probable in 2051–2080, compared to the last three decades. In 2051–2080, such events are estimated to occur about every 6–37 years somewhere in the northern midlatitudes.Changes in extreme heat are often calculated as anomalies above a reference climatology. A different definition—week-day heatwaves surpassing the current record by large margins—shows that their occurrence probabilities depend on warming rate, not level, and are higher than during recent decades.