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Surface ozone (O3) pollution under global climate change has become one of the top environmental issues. In this study, we focused on the coastal region in Southeast China with relatively low O3 precursor's emissions and complicated synoptic conditions, where the O3 trends and meteorological contributions remain unclear. An increasing trend of O3 concentrations in the cities (0.3–4.6 μg m−3 yr−1) from 2015 to 2020 was observed. Twenty‐three synoptic patterns were clustered based on weather typing method, in which cyclone‐related types and southwesterly type were generally associated with low O3 concentrations, and high O3 levels occurred with anticyclone‐related types. Considering both frequency and intensity of synoptic patterns, reconstructed O3 series captured 46.0%–58.3% of the observed variability. Using Kolmogorov‐Zurbenko filter, an increasing trend of long‐term O3 was found. By implementing the multiple linear regression model between O3 concentrations and meteorological factors, the meteorological contributions to O3 variabilities (44.7%–66.1%) were quantified. The results indicated the meteorological conditions were particularly important in O3 pollution with the reductions of O3 precursor's emissions, among which relative humidity, boundary layer height, solar radiation along with low cloud cover were proved to play important roles. The weakening southwest winds along with more anti‐cyclone systems under climate change could increase surface O3. This study elucidated the crucial meteorological drivers on the O3 variability in relatively clean areas and implied the challenges for local governments to mitigate O3 pollution under global climate change. Plain Language Summary: Ozone (O3) pollution has become one of the top environmental issues in recent years and can be affected not only by O3 precursors (volatile organic compounds and nitrogen oxides) but also meteorological condition. Under global climate change, there is a need to deeply understand the impact of meteorological factors on surface O3 concentrations with the decrease of O3 precursors. In this study, we focus on the coast area of Southeast China with relatively low O3 precursors emissions and influenced by the East Asia monsoon. Temporal and spatial variations of O3 concentrations along with the meteorological impacts on O3 variabilities from 2015 to 2020 were analyzed. The results show that the relative meteorological contributions on O3 trends were 44.7%–66.1%. The higher temperature, lower relative humidity, more solar radiation, weakening southwest winds along with more anti‐cyclone systems under climate change could increase surface O3. This study is beneficial to understand different mechanisms of meteorological impacts on O3 variations in the relatively clean areas, and find out the key drivers to cause O3 pollution with the decrease of O3 precursors emissions and climate change. Key Points: Temporal and spatial variations of O3 concentrations in the coastal of southeast China from 2015 to 2020 were analyzedWeather typing was applied to identify the dominant synoptic patterns and related meteorological factors lead on high O3 concentrationThe contributions of synoptic patterns and meteorological factors on long‐term O3 trends were quantified [ABSTRACT FROM AUTHOR]

The impacts and corresponding mechanisms of land use/cover change (LUCC), mainly crops and pasture, on the spatial patterns of summer precipitation over eastern China at the decadal timescale during the last millennium are investigated, using a set of land use/cover sensitivity experiments from the Community Earth System Model (CESM) Last Millennium Ensemble (LME) archive. Two leading modes of summer precipitation over eastern China at decadal scale before (with slight LUCC) and after (with drastic LUCC) 1750 AD are compared. The results show that the LUCC plays an important role in modulating the spatial patterns of summer precipitation over eastern China at decadal scale. Before 1750 AD, the first leading mode exhibits a meridional dipole pattern, while the second leading mode exhibits a meridional tripole pattern. After 1750 AD, the order of the spatial patterns switches, that is, the tripole pattern as the first leading mode and the dipole pattern as the second leading mode. During both periods, the "dry north‐wet south" dipole pattern is associated with an anomalous "A‐C" (anticyclone‐cyclone) low‐level circulation pattern and the related water vapour divergence‐convergence pattern from north to south over the eastern part of East Asia, whereas the tripole pattern corresponds to an anomalous "A‐C‐A" (anticyclone‐cyclone‐anticyclone) circulation pattern along with the corresponding tripole pattern of water vapour divergence/convergence. The regressions of sea surface temperature (SST) during boreal winter resemble obvious Pacific decadal oscillation (PDO) or Atlantic multi‐decadal oscillation (AMO) modes. In addition, the AMO index displays a decreasing trend during the last millennium under the LUCC forcing, while the PDO index does not show an obvious changing trend. The possibility of coupled PDO‐AMO anti‐phase (in‐phase) increases (decreases) after 1750 AD, leading to the increased (decreased) possibility of the tripole (dipole) pattern in eastern China. Our findings confirm the necessity of including LUCC as an important forcing factor in predictions of future climate changes, especially at the regional scale and also at longer timescales. [ABSTRACT FROM AUTHOR]

Based on hourly temperature data collected from 2,307 meteorological stations over China and two sets of climate change simulations over East Asia using the regional climate model version 4.4 (RegCM4.4) driven by the global models of HadGEM2‐ES and MPI‐ESM‐MR, future changes of heating and cooling degree‐hours (HDH and CDH) at the end of the 21st century under RCP4.5 scenario are investigated. Compared against the observation, the spatial distribution, magnitude and annual cycle of present‐day HDH and CDH at different times, as well as the diurnal cycle of them can be realistically simulated by the model. Meanwhile, some bias can also be found and it varies with the times, especially for CDH. At the end of the century, significant decrease of HDH can be found over the Tibetan Plateau, the northern part of Northeast China, and Northwest China at each times while increase of CDH are observed at all the times except some parts of the Tibetan Plateau where the CDH remains zero due to the cold climate there. But for different times, some differences are found in HDH decrease and CDH increase. For example, the changes of HDH at the fifth to the seventh times present a weaker decrease in the northwestern basins compared to other times and the CDH increase are more significant at the fifth and the sixth times. The regional mean changes of HDH and CDH over China in the 21st century (2006–2098) also diverge among different times, which indicates the degree‐hours is needed to precisely calculate the hourly heating and cooling energy demand and then the heating and cooling degree days. [ABSTRACT FROM AUTHOR]

The last few years have seen a surge of scholarly interest in how cultures have been influenced by climate, climatic changes, and extremes of weather. This "cultural turn" of climate history draws from the archives of society, rather than the archives of nature, and is heavily influenced by interpretative and methodological frameworks drawn from the humanities fields. Attention has been largely focused on European contexts and cultures. This article aims to show, however, that the climate history of Asia is on the cusp of developing its own strong cultural turn and that strong foundations and precedents have already been set. This article has two main objectives. The first is to explore approaches in the history of the climate in East Asia that claim to investigate interactions between climatic changes or extreme events and society and culture. Many of these are macro studies, comparing climatic changes with dramatic events in history. Then, it will take a closer look at scholarship that has focused closely on the ideas and beliefs that characterize a society, showing how regional customs and philosophical systems have developed in relation to weather. It will argue that better integration between the two approaches is needed if we are to fully grasp the interdependence of people and climate, a question that becomes ever more critical as we move further into the Anthropocene. This article is categorized under:Climate, History, Society, Culture > World Historical Perspectives [ABSTRACT FROM AUTHOR]

This study examines potential benefits of performance‐based multi‐model ensembles (MMEs) in projecting the impacts of climate change on extreme precipitation indices over East Asia (EA) using the data from 19 GCMs in the coupled model intercomparison project 5 (CMIP5). The Taylor skill score is adopted as the measure of the model skills in simulating the spatial and interannual variability of the selected extreme precipitation indices over four EA regions. The overall rank based on the total skill score (TSC) is used to construct two skill‐based MMEs, MME of high‐skill, MMH (MME of low‐skill, MML) that include the top (bottom) seven models, in addition to the simple ensemble of all 19 GCMs (ENS). Inter‐GCM consistency is measured using the signal‐to‐noise ratio (SNR). In the present‐day period, MMH yields higher skill scores than MML and ENS for almost all extreme precipitation indices as well as regions. Regional variations in biases, inter‐model consistency, and TSC are large. The inter‐model consistency is highest for Northern China and Manchuria and is lowest for Southern China. The most notable differences in the key properties of climate change signals from the three MMEs among the three ensembles are that the climate change signals from MMH and ENS exceed the 90% significance level in much larger areas than those from MML. However, the differences in the climate change signals between MMH and MML are generally below the 90% significance level. The SNR of the projected climate change signals shows that MMH yields more consistent climate change signals than ENS/MML. Both the SNR differences and the area in which statistical significance exceed the 90% level suggest that constructing climate change signals from a group of higher‐skill models may yield more reliable projections than constructing MMEs from the entire models or a group of lower‐skilled models. The domains used in the study (SOUTH: 110°–140°E, 20°–30°N, MIDDLE: 110°–140°E, 30°–40°N), NORTH: 110°–140°E, 40°–50°N, EA: 110°–140°E, 20°–50°N) [ABSTRACT FROM AUTHOR]