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There have been fruitful publications on thermal comfort of urban residential buildings in China. However, there is a lack of reviews on this topic to perform a comprehensive analysis and find opportunities to meet occupants' thermal comfort needs while improving building energy efficiencies. This paper addresses this issue by presenting a systematic review on the advancements in research on thermal comfort in urban residential buildings in China. Firstly, two common thermal comfort research approaches, i.e., field studies and laboratory studies, are discussed. Secondly, eleven main thermal comfort evaluation indicators are summarized. Finally, this paper analyzes the thermal comfort survey data from different researchers, discusses the impacts of adaptive behaviors on human thermal comfort, and provides recommendations for future research on urban residential thermal comfort. It was found that people have higher and higher requirements for their indoor thermal environment as time goes by, especially in the winter; the thermoneutral temperature is higher in warmer climate regions in the summer but lower in the winter than in colder climate regions; the thermoneutral temperature tends to increase with the indoor air temperature due to an adaptation to the indoor thermal environment. The outcomes of this paper provide valuable information on thermal comfort behaviors of urban residents in different climate zones in China, which can serve as a resource for the academic community conducting future research on thermal comfort and assist policymakers in enhancing building energy efficiencies without compromising the occupants' comfort. [ABSTRACT FROM AUTHOR]

Separating existing historical precipitation data into solid and liquid precipitation remains a challenge in the study of climate change, extreme precipitation, and hydrological modelling. Based on historical daily air temperature and precipitation data, as well as visual observations of precipitation phase (weather phenomena records) in China mainland, this study proposed a snow‐day direct definition method (SDDM) to determine the threshold air temperature (TAT) of rainfall and snowfall, and analysed the spatial pattern and its influential factors. The main findings include: (1) the TAT based on the SDDM varied from −1.2 to 6.3°C, with a mean value of 2.8°C for the entire study region; (2) TAT was generally higher and more variable in the low‐latitude areas, and the Qinghai‐Tibet Plateau was characterized by an abnormally high average TAT of 5.2°C, almost twice as large as that of the eastern monsoon region; (3) TAT exhibited a significant positive correlation with altitude and negative correlation with precipitation and relative humidity. The results presented in this paper have potential application for studies of large‐scale snowfall climatology and climate change, weather forecasting techniques, and hydrological model parameterization in areas with complex and diverse geographical and climatic conditions. [ABSTRACT FROM AUTHOR]

The impact of climate change on asphalt pavement infrastructure has become increasingly apparent. This paper investigated how climate change impacts the selection of asphalt binder for freeway pavement in China. The climate data predicted by the Global Climate Model were employed to select the appropriate performance grade for asphalt binder. The predicted air temperature converted pavement temperature, and performance grade distribution of the country was analysed. It is suggested that the performance grade of asphalt binder for freeways' pavement should be determined based on ten years' predicted climate data. This study concluded the following four major findings. Firstly, the selection of the appropriate asphalt binder performance grade needs to take into account the effects of future climate change. Secondly, the change in the standard deviation of temperature has a greater impact on the change in asphalt performance grade, as compared to the change in average air temperature. Thirdly, climate change affects the low-temperature performance grade more than the high-temperature performance grade in China. Finally, by 2050s, 15.2% of freeway asphalt pavement needs to upgrade high-temperature performance grade limit, and 17.3% of freeway asphalt pavement needs to upgrade to low-temperature performance grade limit. [ABSTRACT FROM AUTHOR]

Plum Rains Season (PRS) has the typical characteristics of outdoor air temperature dramatic changes and high air humidity in the hot summer and cold winter region in China. When the outdoor temperature rises rapidly during PRS, the building envelope surface temperature is probably lower than the indoor air dew point temperature, resulting in moisture condensation. This paper evaluates the influence of geographical location and outdoor meteorological parameters on the indoor humidity environment. The effects of critical parameters such as altitude, average temperature, relative humidity, total precipitation, total precipitation days, atmospheric pressure, and wind speed on the building envelope moisture condensation in nine typical cities in the hot summer and cold winter region were simulated and analyzed. The results show that the Condensation Frequency (CFn) in the western, central, and eastern regions reached the highest in April, May, and June, respectively. Among the nine typical cities, Changsha has the highest Condensation Risk (CR). In addition, the altitude, total precipitation, and atmospheric pressure have little effect on the indoor humidity environment, and it is not directly related to CR; The average temperature and total precipitation days were not related to CR in the western and eastern regions and positively correlated with CR in the central region; The wind speed was positively correlated with CR in the western and central regions and negatively correlated in the eastern region; The relative humidity can affect the indoor humidity environment and moisture condensation on the inner surface of walls, when the relative humidity increases, the CR increases. [ABSTRACT FROM AUTHOR]

The long-term height-resolved wind trend in China under global warming still needs to be discovered. To fill this gap, in this paper we examined the climatology and long-term (1979–2021) trends of the wintertime wind speed at the near-surface and upper atmosphere in China based on long-term radiosonde measurements. At 700, 500, and 400 hPa, much higher wind speed was found over eastern China, compared with western China. At 300, 200, and 100 hPa, maximum wind speed was observed in the latitude zone of around 25–35°N. Furthermore, westerly winds dominated most parts of China between 20°N and 50°N at altitudes from 700 hPa to 100 hPa. A stilling was revealed for the near-surface wind from 1979–2003. From 2004 onward, the near-surface wind speed reversed from decreasing to increasing. This could be largely due to the joint impact of reduced surface roughness length, aerosol optical depth (AOD), and increased sensible heat flux in the ground surface. The decrease of AOD tended to reduce aerosol radiative forcing, thereby destabilizing the planetary boundary layer (PBL). By comparison, the wintertime wind in the upper atmosphere exhibited a significant monotonic upward trend, albeit with varying magnitude for different altitudes. In the upper troposphere, the wintertime maximum wind was observed along a westerly jet stream, with a pronounced upward trend within the zone approximately bounded by latitudes of 25–50°N, particularly above 500 hPa. This accelerating wind observed in the upper troposphere and lower stratosphere could be closely associated with the large planetary-scale meridional temperature trend gradient. Besides, the direction for the wind at the near-surface and lower troposphere (925 and 850 hPa) exhibited a larger variance over the period 1979–2021, which could be associated with the strong turbulence of PBL caused by the heterogeneous land surface. For those pressure levels higher than 850 hPa, large wind directional variance was merely found to the south of 25 °N. The findings from long-term radiosonde measurements in winter over China shed light on the changes in wind speed on the ground and upper atmosphere under global warming from an observational perspective. [ABSTRACT FROM AUTHOR]

The paper took Guang'an City in Sichuan Province of China as a research region, and it built an evaluation index system based on 14 evaluation indices according to four criteria, namely, ecological background, ecological structure, ecological benefits, and ecological stress. The Delphi algorithm and entropy weight (a combination of subjective and objective methods) were used to calculate the weight value of each evaluation index, and an ideal point model was used to calculate the ideal point value. The ideal point ecological grade was classified, and the principal component analysis method was used to obtain the main control factors of each year, which revealed the relationship between the ecological distribution of ideal points and the environmental impact factor, with the changing characteristics of the ecology in the research region according to the hotspot model of the spatial differentiation of land ecological quality as the main control factor. Lastly, the paper also analyzed the land ecological quality of Guangan City in 2000, 2005, 2010, and 2015. The study results show that the overall land ecological quality in Guang'an City generally increased from 2005 to 2015. The proportion of forest land area and the temperature were the most important main control factors. The air temperature and the land ecological quality were positively correlated. [ABSTRACT FROM AUTHOR]

The intense ultraviolet radiation and large amount of saline-alkali soil in the Golmud region of Province, China, have deteriorated the performance of asphalt pavement. Given the effect of adverse conditions in this area, this paper investigated the collective and interaction effects of salt chemicals, air temperature, and ultraviolet radiation on asphalt and asphalt mixture through laboratory experiments under controlled conditions. In particular, using different concentrations of Na2SO4 and NaCl solutions, simulated salt chemicals for asphalt and asphalt mixture performance impact. The mechanism of performance deterioration of the asphalt mixture suffered from salt attack was explored. The results show that the original asphalt's storage and loss modulus are higher than the modified asphalt at different temperatures with the multi-factors effect. In addition, the modified asphalt's phase angle is 5%∼10% higher than the original asphalt below −2°C. At the same time, strength loss rates of asphalt mixture increase with the cycles and solution concentration, varying from 20%−40%. Wet-dry cycles and the concentration of salt solution are positively correlated with the deterioration of asphalt mixture strength. This research provides the durability prediction and the more reasonable composition design of the asphalt mixture applied in salt enrichment regions. [ABSTRACT FROM AUTHOR]

The impact of climate change on asphalt pavement infrastructure has become increasingly apparent. This paper investigated how climate change impacts the selection of asphalt binder for freeway pavement in China. The climate data predicted by the Global Climate Model were employed to select the appropriate performance grade for asphalt binder. The predicted air temperature converted pavement temperature, and performance grade distribution of the country was analysed. It is suggested that the performance grade of asphalt binder for freeways' pavement should be determined based on ten years' predicted climate data. This study concluded the following four major findings. Firstly, the selection of the appropriate asphalt binder performance grade needs to take into account the effects of future climate change. Secondly, the change in the standard deviation of temperature has a greater impact on the change in asphalt performance grade, as compared to the change in average air temperature. Thirdly, climate change affects the low-temperature performance grade more than the high-temperature performance grade in China. Finally, by 2050s, 15.2% of freeway asphalt pavement needs to upgrade high-temperature performance grade limit, and 17.3% of freeway asphalt pavement needs to upgrade to low-temperature performance grade limit. [ABSTRACT FROM AUTHOR]

Diffuse light is produced by clouds and aerosols in the atmosphere. Exploring the effects of diffuse light on ecosystem productivity is important for understanding the terrestrial carbon (CO2) cycle. Here, 2 years of gross ecosystem primary productivity (GEP) from a (winter) wheat cropland in China was assessed using eddy covariance technology to explore the effects of diffuse photosynthetic active radiance (PAR) on wheat GEP. Wheat GEP increased significantly and positively along with diffuse PAR. In addition, wheat GEP was significantly affected by total PAR, air temperature, and vapor press deficit in different diffuse PAR fraction (fDIF) change stages. Because significant autocorrelations existed among the controlling factors, a path analysis was used to quantify the effects of diffuse light on GEP. Diffuse PAR was the primary and secondary importance factors affecting GEP with direct path coefficients of 0.54 and 0.48, respectively, in different fDIF change stages. A multilayer canopy model revealed that the middle and lower canopy levels intercepted more light when diffuse PAR increased. This resulted in the photosynthetic enhancement of middle and lower canopy levels, which contributed approximately 65% and 35%, respectively, to the increase in photosynthesis for the entire canopy (~ 30.5%). Overall, our study provided new evidence regarding the importance of diffuse light for CO2 uptake in agroecosystems, which is important for predicting the responses of ecosystem CO2 budgets to future climate-related light changes. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The GRAPES (Global/Regional Assimilation and Prediction System) global medium-range ensemble forecast system (GRAPES_GFS) is a new generation numerical weather forecast model developed by the China Meteorological Administration (CMA). However, the forecasts of surface latent heat fluxes and surface air temperature have systematic biases, which affect the forecasts of atmospheric dynamics by modifying the lower boundary conditions and degrading the application of GRAPES_GFS since the 2 m air temperature is one of the key components of weather forecast products. Here, we add a soil resistance term to reduce soil evaporation, which ultimately reduces the positive forecast bias of the land surface latent heat flux. We also reduce the positive forecast bias of the ocean surface latent heat flux by considering the effect of salinity in the calculation of the ocean surface vapor pressure and by adjusting the parameterizations of roughness length for the exchanges in momentum, heat, and moisture between the ocean surface and atmosphere. Moreover, we modify the parameterization of the roughness length for the exchanges in heat and moisture between the land surface and atmosphere to reduce the cold bias of the nighttime 2 m air temperature forecast over areas with lower vegetation height. We also consider the supercooled soil water to reduce the warm forecast bias of the 2 m air temperature over northern China during winter. These modified parameterizations are incorporated into the GRAPES_GFS and show good performance based on a set of evaluation experiments. This paper highlights the importance of the representations of the land/ocean surface and boundary layer processes in the forecasting of surface heat fluxes and 2 m air temperature. [ABSTRACT FROM AUTHOR]

The global climate shows an obvious warming trend, and the impact on water resources is increasing. Abrupt temperature change and warming hiatus are two important states of temperature change. The quantitative impacts of temperature change and warming hiatus on surface runoff remain unclear. Based on the measured runoff data from 60 representative hydrological stations in China from 1956 to 2016 and the Water Balance Model developed by the Research Center for Climate Change (RCCC-WBC), this paper analyzes the quantitative impacts of abrupt temperature change and warming hiatus on surface runoff. The results showed that the effects of three types of abrupt temperature changes on runoff in different basins in China are significantly different. The effects of abrupt temperature changes and warming stagnation on runoff in northern China are greater than those in southern China, and the effects of abrupt temperature changes and warming stagnation on runoff in the upper, middle, and lower reaches of the same basin are also different. Before the abrupt change in temperature, the influence of temperature on the surface runoff was less than 9%, and the influence of temperature on the runoff in some southern areas was weaker, only affecting less than 3% of the runoff. When the temperature changes abruptly, the influence of air temperature on the surface runoff in a small part of the arid region is up to 30%. The abrupt change in mean maximum temperature has both positive and negative driving effects on runoff in China, and the negative driving effect is concentrated in the areas with abrupt warming, affecting about 8% of the runoff on average. The average influence of abrupt mean temperature change on runoff in China is about 10%, and the area with a large influence on runoff change is concentrated in the area north of 40° N. The abrupt change in temperature in the middle and lower reaches of the Yellow River Basin has a great influence on the runoff change, up to 13%. The maximum impact of abrupt mean minimum temperature on runoff is concentrated in Northeast China, ranging from 9% to 12%. During the period of temperature stagnation, air temperature and runoff showed an obvious reverse trend. During this period, the average negative influence of drastic changes in air temperature on runoff was about 15%, but precipitation and runoff still maintained a good consistency, which may be due to the effect of other influencing factors which offset the negative driving effect of air temperature. [ABSTRACT FROM AUTHOR]

It is well known that El Niño–Southern Oscillation (ENSO) can influence the East Asian winter climate by modifying the atmospheric circulation over the western North Pacific (WNP). While the impact on precipitation in southeastern China has been extensively studied, the ENSO signal in surface air temperature (SAT) remains overlooked. In this paper, we identify robust ENSO footprints in the winter daily minimum SAT in southeastern China, with El Niño winters generally accompanied by warmer-than-normal minimum SAT anomalies. In contrast, the responses of maximum SAT are weak and negligible, suggesting a diurnal cycle–dependent ENSO influence. Further analysis indicates that this diurnal cycle dependence stems primarily from the disparate surface radiative heating between day and night induced by ENSO-related local total cloud cover (TCC) change. The warmer minimum SAT occurring in the early morning of El Niño winters is mainly caused by the enhanced surface downward longwave radiative heating as a result of the TCC increase. However, in the afternoon of El Niño winters, although the anomalous horizontal advection of warm air plays a role, there is surface radiative cooling as the weakening of solar radiation due to TCC reflection overwhelms the increase in downward longwave radiation, which leads to a weakened sensible heat flux and thus has a cooling effect on the SAT. Ultimately, these two processes effectively cancel each other out and together produce insignificant maximum SAT responses. Our conclusions carry important implications for the seasonal to interannual winter climate prediction in southeastern China. Significance Statement The purpose of this study is to better understand how ENSO influences winter surface air temperature in southeastern China. Despite insignificant responses of winter daily maximum temperature to ENSO, we find here a robust ENSO influence on the daily minimum temperature, with warm anomalies tending to occur during El Niño events. Further evidence suggests that this diurnal cycle–dependent ENSO influence is mainly caused by ENSO-induced change in local cloudiness, which has a different radiative heating effect between day and night. Our findings are of great importance for improving regional climate prediction, which will benefit social and economic activities. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper describes the construction of a 0.25° × 0.25° daily soil temperature (TS) data set at six soil depths (i.e., 0, 5, 10, 15, 20, and 40 cm) based on a homogenized TS at more than 2,000 meteorological stations across mainland of China for 1960–2017. First, at each station, the observed TS is split into a daily climatology of 1981–2010 and a daily anomaly for 1960–2017. Then, they are respectively interpolated to 0.25° × 0.25° horizontal resolution by using the thin‐plain spline and the angular distance weight interpolation methods. Finally, a gridded multilayer TS data set is constructed from the sum of the above two gridded products. Latitude, longitude, and high‐resolution digital elevation models are explicitly incorporated into the interpolation processes. Selectivity tests indicate that the optimal interpolation distance for the TS anomaly field is 500 km, where the gridded data set may have maximum coverage of the entire Chinese mainland. The results show that the gridded TS climatology is slightly lower than the station observations. The differences between gridded and the station‐based TS varies ±3°C, with relatively large in SW and TIBET. For the gridded anomaly fields, the cross‐validation shows that the mean absolute errors between gridded and station‐based TS are generally less than 0.6°C in the YZ, SW, and SC, but they are above 1.0°C in the NW and TIBET due to the sparse station distribution and large topographic relief. From 1961 to 2016, the seasonal variability of the gridded TS is generally consistent with that of the surface air temperature. The gridded TS over the majority of land displays significantly positive trends in both summer and winter (p > 95%), indicating an overall warming land surface in China. The long‐term gridded TS data not only preserves the spatial features represented in the station observations, but also provides a spatio‐temporal continuous long‐term product of mainland China. Thus, it may be used in future studies, for example, evaluation of land surface model simulations, validation of satellite retrievals, land‐atmosphere interactions, and climate change. [ABSTRACT FROM AUTHOR]

Mg/Ca ratio in stalagmites primarily serves as an indicator of past hydrological conditions rather than temperature variations. Here, we present an Mg/Ca ratio record in a stalagmite from northern China, spanning ice age termination II. A unique finding is that Mg/Ca ratio shows a moderately strong positive correlation with cave air temperature obtained from clumped isotopes data in the same stalagmite. The stable hydrogeochemistry of source water and high temperature sensitivity of Mg partition coefficient plausibly explain this temperature dependence. Furthermore, we establish an Mg/Ca‐temperature calibration for stalagmites from mid‐latitudes, encompassing a temperature range between ∼2 and ∼15°C, where Mg/Ca = 14.221 × e0.073×T (R2 = 0.40). Applying this function to Mg/Ca ratio from similar stalagmites could tentatively provide a quantitative regional temperature record over millennial and centennial timescales. This research highlights Mg/Ca ratio in stalagmites as a potential palaeo‐temperature proxy and introduces, for the first time, a tentative Mg/Ca‐temperature calibration function for speleothems. Plain Language Summary: Stalagmite is one type of speleothems that grow from the floor of caves. The geochemical indexes within stalagmites, such as Mg/Ca ratio, can help us to understand the past climate changes. Here, we conducted a study on a stalagmite from northern China during ice age termination II. Traditionally, Mg/Ca ratios in stalagmites have been used to investigate past hydrological conditions. However, we found that Mg/Ca ratio matches the cave air temperature obtained from clumped isotopes data within the same stalagmite. This correlation was explained by the stable chemistry of the source water and the sensitivity of Mg partition coefficient to temperature. We also developed a tentative formula to calculate past temperature from Mg/Ca ratio in similar speleothems. Key Points: A Chinese stalagmite at termination II shows moderately strong positive correlation between Mg/Ca ratio and clumped isotopes‐temperatureStable drip water hydrogeochemistry and high temperature sensitivity of Mg partition coefficient may explain this temperature dependenceWe tentatively establish, for the first time, an Mg/Ca‐temperature calibration function for speleothems [ABSTRACT FROM AUTHOR]

While previous studies have largely focused on anthropogenic warming characterized by surface air temperature, little is known about the behaviors of human‐perceived temperature (HPT), which describe the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity and/or wind speed. Here we adopted an optimal fingerprinting method to compare seasonal mean HPTs in China with those from simulations conducted with multiple climate models participating in the Coupled Model Intercomparison Project Phase 6. We found clear anthropogenic signals in the observational records of changes in both summer and winter HPTs over the period 1971–2020. Moreover, the anthropogenic greenhouse gas influence was robustly detected, with clear separation from natural and anthropogenic aerosol forcings. The anthropogenic greenhouse gas forcing plays the dominant role (>90%) of human‐perceived warming. Urbanization effects contribute slightly and moderately to the estimated trends in summer and winter HPTs, respectively, in addition to the effects of external forcing. Plain Language Summary: Human influences have been identified in the observed warming quantified by surface air temperature (SAT), but SAT alone is inadequate as a metric for human thermal comfort. Here we focus on human‐perceived temperature (HPT), which describes the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity, and/or wind speed. We isolate anthropogenic impacts on the observed increase in summer and winter HPTs in China during 1971–2020 by comparing observations with state‐of‐the‐art climate models. Results show that the influence of anthropogenic greenhouse gas is detected, with clear separation from other external forcings such as solar and volcanic activities and anthropogenic aerosols. The human‐induced greenhouse gas increases are also found to explain most (>90%) of the observed human‐perceived warming. Along with the effects of large‐scale anthropogenic forcing, urbanization effects also have a slight to moderate influence on the estimated trends in summer and winter HPTs. Our work is an early attempt to provide quantitative evidence for the physiological impacts of anthropogenic global warming and local urbanization on human beings. Key Points: The warming is quantified by human‐perceived temperature that considers the joint effects of temperature, humidity and/or wind speedHuman influence could be robustly detected in both summer and winter human‐perceived warmingThe observed increase in human‐perceived temperature is mostly attributed to anthropogenic greenhouse gas increases [ABSTRACT FROM AUTHOR]

Introduction: The components of nighttime sap flux (En), which include transpiration (Qn) and stem water recharge (Rn), play important roles in water balance and drought adaptation in plant communities in water-limited regions. However, the quantitative and controlling factors of En components are unclear. Methods: This study used the heat balance method to measure sap flow density in Vitex negundo on the Loess Plateau for a normal precipitation year (2021) and a wetter year (2022). Results: The results showed that the mean values were 1.04 and 2.34 g h-1 cm-2 for Qn, 0.19 and 0.45 g h-1 cm-2 for Rn in 2021 and 2022, respectively, and both variables were greater in the wetter year. The mean contributions of Qn to En were 79.76% and 83.91% in 2021 and 2022, respectively, indicating that the En was mostly used for Qn. Although the vapor pressure deficit (VPD), air temperature (Ta) and soil water content (SWC) were significantly correlated with Qn and Rn on an hourly time scale, they explained a small fraction of the variance in Qn on a daily time scale. The main driving factor was SWC between 40-200 cm on a monthly time scale for the Qn and Rn variations. Rn was little affected by meteorological and SWC factors on a daily scale. During the diurnal course, Qn and Rn initially both declined after sundown because of decreasing VPD and Ta, and Qn was significantly greater than Rn, whereas the two variables increased when VPD was nearly zero and Ta decreased, and Rn was greater than Qn. Discussion: These results provided a new understanding of ecophysiological responses and adaptation of V. negundo plantations to increasing drought severity and duration under climate changes. [ABSTRACT FROM AUTHOR]

There are few studies on the climate and glacial scale in the mountains east of the Qinghai–Tibet Plateau. So, we used glacial features to determine the range of the area's paleoglaciers and the equilibrium line altitude (ELA) of theGlA modern and paleoglaciers in the Tianchi area of the Changbai Mountains. Then, the GlaRe toolbox 2015 () was used to reconstruct the surface of the paleoglaciers. The probable air temperature during the glacial advances of the LGM was calculated by applying the P-T and LR models. The results showed the following: (1) the change in ELA is 950 m in the Tianchi area of the Changbai Mountains; (2) glacial coverage in the Tianchi area of the Changbai Mountains during the LGM period was ~27.05 km2 and the glacial volume was ~9.94 km3; and (3) the mean temperature in the Tianchi area of the Changbai Mountains during the LGM was 6.6–9.0 °C lower than today's, and was the principal factor controlling the growth of glaciers. There is a difference in the climate change in monsoon-influenced mountains during the LGM, and this difference may be related to the precipitation in the mountains. [ABSTRACT FROM AUTHOR]

An extreme high-temperature event occurred in North China on 22 June 2023, with the maximum temperature reaching 41.8 °C. The high-temperature centers preferentially occurred at the foothills of the Taihang and Yanshan Mountains, indicating an important role of the underlying orography. In the present work, we study the orographic effects of this extreme high-temperature event according to high-resolution numerical simulations using the Weather Research and Forecasting model. The results show that the presence of the mountains in North China contributed notably to the high-temperature event, which can enhance the 2 m air temperature by up to 3 °C. In the daytime, the enhancement of temperature is primarily due to the diabatic heating of sensible heat flux at the terrain surface caused by solar shortwave radiation, whereas the well-known foehn effect has little contribution. Indeed, the dynamically forced downslope flow of foehn is totally suppressed by the upslope flow of the thermally driven mountain-plain circulation. In the nighttime, the sensible heat flux at the terrain surface changes to weakly negative, given the cooling of land surface longwave radiation. As a result, the enhancement of near-surface temperature at the terrain foothill is dominated by the adiabatic warming of downslope flow. Yet, the near-surface temperature far away from the mountain is enhanced by the subsidence warming of a synoptic anomalous anti-cyclone, which is induced by the diabatic heating over the mountains in the daytime. These findings help improve the understanding of the thermal and dynamical effects of orography on the occurrence of high-temperature events. [ABSTRACT FROM AUTHOR]

Based on the multi-model ensemble mean of CMIP6 simulations, the future changes in frequency, intensity and duration of Compound (both daytime and nighttime) heatwaves (HWs) in summer over China at various global warming levels (GWLs) under the SSP3-7.0 and SSP5-8.5 are assessed. HWs over China become more frequent and hotter, and the duration of HWs becomes longer compared to those in the recent climate. The magnitudes of these changes are primarily dependent on GWLs, but they are not very sensitive to the scenarios. At 4 ℃ GWL, the frequency of HWs increases by more than fivefold under both scenarios, and the intensity (duration) of HWs averaged under the two scenarios is 2.28 ℃ hotter (3.59 days longer) than the one in the recent climate over the entire China. Meanwhile, the maximum duration of HW events can reach more than 25 days in summer in comparison with 8 days in the recent climate. The changes in HW properties are regionally dependent at the four GWLs. For example, the largest increase in HW frequency is over the Northwest China, the largest increase in intensity in HWs is seen over the Northeast and Northwest, and the largest increase in HW duration is over the Southwest China. The extreme rare events (50-year and 100-year events) in the recent climate would become the norm over China and four sub-regions at 4 ℃ GWL. Overall, seasonal mean warming dominates the changes in HW properties over China at the different GWLs. The seasonal mean warming in summer across China is related to the increases of longwave radiation, partly due to increase in greenhouse gas forcing and partly resulted from increased water vapor and the increase of shortwave radiation (under the SSP5-8.5) over eastern China related to decreases in aerosols and total cloud cover. Furthermore, the regional variations in the water vapor over China are consistent with atmospheric circulation changes. The seasonal mean surface warming results in enhanced upward sensible and latent heat fluxes, leading to increased summer mean daily maximum and minimum of near-surface air temperature and the enhancement of HWs properties over the entire China. Changes of shortwave radiation tend to play a weaker role for surface warming under the SSP3-7.0 than those under the SSP5-8.5, which is related to increased aerosol changes under the SSP3-7.0. [ABSTRACT FROM AUTHOR]

Near-land surface air temperature (NLSAT) is an important meteorological and climatic parameter widely used in climate change, urban heat island and environmental science, in addition to being an important input parameter for various earth system simulation models. However, the spatial distribution and the limited number of ground-based meteorological stations make it difficult to obtain a large range of high-precision NLSAT values. This paper constructs neural network, long short-term memory, bi-directional long short-term memory, support vector machine, random forest, and Gaussian process regression models by combining MODIS data, DEM data, and meteorological station data to estimate the NLSAT in China's mainland and compare them with actual NLSAT observations. The results show that there is a significant correlation between the model estimates and the actual temperature observations. Among the tested models, the random forest performed the best, followed by the support vector machine and the Gaussian process regression, then the neural network, the long short-term memory, and the bi-directional long short-term memory models. Overall, for estimates in different seasons, the best results were obtained in winter, followed by spring, autumn, and summer successively. According to different geographic areas, random forest was the best model for Northeast, Northwest, North, Southwest, and Central China, and the support vector machine was the best model for South and East China. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Surface air temperature is a critical element in the surface–atmosphere interaction, energy exchange, and water cycle. Multi-source fusion reanalysis products (hereafter referred to as reanalysis) have spatiotemporal continuity and broad applicability that can provide key data support for various studies such as glacier melting, soil freeze-thaw and desertification, ecosystem, and climate change in the alpine region of the Qinghai–Tibet Plateau (QTP). Surface air temperature observations collected at 17 weather stations in the High-cold region Observation and Research Network for Land Surface Process and Environment of China (HORN) over the period of 2017–2018 are implemented to evaluate the advanced and widely used surface air temperature reanalysis datasets, which include the European Centre for Medium-Range Weather Forecasts (ECMWF) Fifth Generation Land Surface Reanalysis (ERA5L), the U.S. Global Land Data Assimilation System (GLDAS), and China Meteorological Administration Land Data Assimilation System (CLDAS). Results are as follows: (1) Evaluation results of temporal changes and spatial distribution characteristics indicate that the three reanalysis datasets are consistent with in-situ observations in the alpine region of the QTP. CLDAS is more consistent with observations and can better describe details of temperature distribution and variation than ERA5L and GLDAS. (2) For the evaluation period, CLDAS is 0.53 °C higher than the in-situ observation, while ERA5L and GLDAS are lower than the in-situ observation by −3.45 °C and −1.40 °C, respectively. (3) The accuracy of CLDAS is better than ERA5L and GLDAS under different elevations and land covers. We resampled three reanalysis datasets with a spatial resolution of 0.25° and used the two most common interpolation methods to analyze the impact of spatial resolution and different interpolation methods on the evaluation results. We found that the impact is small. In summary, the three reanalysis datasets all have certain applicability in the alpine region of the QTP, and the accuracy of CLDAS is significantly higher than ERA5L and GLDAS. The results of the present paper have important implications for the selection of reanalysis data in the studies of climate, ecosystem, and sustainable development in the QTP. [ABSTRACT FROM AUTHOR]

As an important part of the Earth's environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way. [ABSTRACT FROM AUTHOR]

A key element for reducing energy consumption and improving thermal comfort on high-speed rail is controlling air-conditioning temperature. Accurate prediction of air supply temperature is aimed at improving control effects. Existing studies of supply air temperature prediction models are interdisciplinary, involving heat transfer science and computer science, where the problem is defined as time-series prediction. However, the model is widely accepted as a complex model that is nonlinear and dynamic. That makes it difficult for existing statistical and deep learning methods, e.g., autoregressive integrated moving average model (ARIMA), convolutional neural network (CNN), and long short-term memory network (LSTM), to fully capture the interaction between these variables and provide accurate prediction results. Recent studies have shown the potential of the Transformer to increase the prediction capacity. This paper offers an improved temporal fusion transformers (TFT) prediction model for supply air temperature in high-speed train carriages to tackle these challenges, with two improvements: (i) Double-convolutional residual encoder structure based on dilated causal convolution; (ii) Spatio-temporal double-gated structure based on Gated Linear Units. Moreover, this study designs a loss function suitable for general long sequence time-series forecast tasks for temperature forecasting. Empirical simulations using a high-speed rail air-conditioning operation dataset at a specific location in China show that the temperature prediction of the two units using the improved TFT model improves the MAPE by 21.70% and 11.73%, respectively the original model. Furthermore, experiments demonstrate that the model effectively outperforms seven popular methods on time series computing tasks, and the attention of the prediction problem in the time dimension is analyzed. [ABSTRACT FROM AUTHOR]

Atmospheric weighted mean temperature (Tm) is a key parameter used by the Global Navigation Satellite System (GNSS) for calculating precipitable water vapor (PWV). Some empirical Tm models using meteorological or non-meteorological parameters have been proposed to calculate PWV, but their accuracy and reliability cannot be guaranteed in some regions. To validate and determine the optimal Tm model for PWV retrieval in China, this paper analyzes and evaluates some typical Tm models, namely, the Linear, Global Pressure and Temperature 3 (GPT3), the Tm model for China (CTm), the Global Weighted Mean Temperature-H (GTm-H) and the Global Tropospheric (GTrop) models. The Tm values of these models are first obtained at corresponding radiosonde (RS) stations in China over the period of 2011 to 2020. The corresponding Tm values of 87 RS stations in China are also calculated using the layered meteorological data and regarded as the reference. Comparison results show that the accuracy of these five Tm models in China has an obvious geographical distribution and decreases along with increasing altitude and latitude, respectively. The average root mean square (RMS) and Bias for the Linear, GPT3, CTm, GTm-H and GTrop models are 4.2/3.7/3.4/3.6/3.3 K and 0.7/−1.0/0.7/−0.1/0.3 K, respectively. Among these models, Linear and GPT3 models have lower accuracy in high-altitude regions, whereas CTm, GTm-H and GTrop models show better accuracy and stability throughout the whole China. These models generally have higher accuracy in regions with low latitude and lower accuracy in regions with middle and high latitudes. In addition, Linear and GPT3 models have poor accuracy in general, whereas GTm-H and CTm models are obviously less accurate and stable than GTrop model in regions with high latitude. These models show different accuracies across the four geographical regions of China, with GTrop model demonstrating the relatively better accuracy and stability. Therefore, the GTrop model is recommended to obtain Tm for calculating PWV in China. [ABSTRACT FROM AUTHOR]

This paper looks at regional water security in eastern China in the context of global climate change. The response of runoff to climate change in the Qinhuai River Basin, a typical river in eastern China, was quantitatively investigated by using the Soil and Water Assessment Tool (SWAT) model and the ensemble projection of multiple general circulation models (GCMs) under three different shared socioeconomic pathways (SSPs) emission scenarios. The results show that the calibrated SWAT model is applicable to the Qinhuai River Basin and can accurately characterize the runoff process at daily and monthly scales with the Nash–Sutcliffe efficiency coefficients (NSE), correlation coefficients (R), and the Kling–Gupta efficiency (KGE) in calibration and validation periods being above 0.75 and relative errors (RE) are ±3.5%. In comparison to the baseline of 1980–2015, the mean annual precipitation in the future period (2025–2060) under the three emission scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5 will probably increase by 5.64%, 2.60%, and 6.68% respectively. Correspondingly, the multiple-year average of daily maximum and minimum air temperatures are projected to rise by 1.6–2.1 °C and 1.4–2.0 °C, respectively, in 2025–2060. As a result of climate change, the average annual runoff will increase by 16.24%, 8.84%, and 17.96%, respectively, in the period of 2025–2060 under the three SSPs scenarios. The increase in runoff in the future will provide sufficient water supply to support socioeconomic development. However, increases in both rainfall and runoff also imply an increased risk of flooding due to climate change. Therefore, the impact of climate change on flooding in the Qinhuai River Basin should be fully considered in the planning of flood control and the basin's development. [ABSTRACT FROM AUTHOR]

This study employs computational fluid dynamics to analyze the natural ventilation conditions of university student dormitories in the northeastern region of China under various outdoor wind directions, wind speeds, and temperature conditions. By separately simulating room natural ventilation efficiency under four different outdoor wind speeds (1.5 m/s, 3.3 m/s, 5.4 m/s and 7.9 m/s) at different outdoor temperatures (−10 °C, 0 °C, 10 °C and 20 ℃), curves of indoor pollutant removal rates (VOA-Time) are established for different wind directions. The study also determines the minimum ventilation time required for rooms under different environmental conditions (TVOA=70%). The data indicate that, despite the promotion of ventilation efficiency with increasing wind speed or indoor-outdoor temperature difference, the wind direction determines the extent to which these factors enhance room ventilation efficiency. Furthermore, there are corresponding mathematical relationships between TVOA=70%, outdoor temperature, wind speed, and different wind directions, allowing for predictions related to the rate of indoor carbon dioxide change. The research findings will assist students in formulating more effective ventilation strategies under complex outdoor environmental conditions. [ABSTRACT FROM AUTHOR]

The applications of conventional heat pipes have been hindered by a few weaknesses, such as the low heat recovery effectiveness, the cross-pollution of fresh and exhaust air, and the difficult switch modes between winter and summer working conditions. In order to find solutions for those problems, a three-dimensional heat pipe exchanger was developed, and an experimental platform was built to test the heat recovery effectiveness of this heat pipe exchanger under different working conditions. Moreover, the operating performances of the three-dimensional heat pipe exchanger unit were monitored throughout one year in a hospital located in the hot summer and cold winter region of China. The field measurement results indicated that the heat recovery effectiveness could be effectively improved by reducing the air volume and the up-wind speed, increasing the cold air and hot air inlet temperature, and increasing the rows of pipes. According to optimizing the structure and operation parameters, the heat recovery efficiencies of the three-dimensional heat pipe exchanger increased by 65~85%. The recommended operation parameters of the three-dimensional heat pipe exchanger in winter and summer for indoor exhaust air temperature were 20 ± 2 °C and 22 ± 2 °C, respectively. The heat recovery effectiveness could reach up to 66% and 64.5% when the indoor and outdoor air temperature differences were higher than 11 °C and 5 °C in winter and summer, respectively. This study provides effective, reliable, and easily implementable methods for the application of three-dimensional heat pipe heat recovery devices in building HVAC systems. It offers guidance for the future design of heat pipe heat recovery devices. [ABSTRACT FROM AUTHOR]

Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe. [ABSTRACT FROM AUTHOR]

A passive microwave instrument will be carried by China's geostationary microwave satellite. A microwave hyper-spectral band included by the instrument ranges from 52.6 to 57.3 GHz, and totally has 89 channels in this spectral domain. The design of the hyper-spectral band is described from the aspects of scientific objectives and specifications. The weighting functions for each channel are calculated utilizing radiative transfer simulations under clear sky conditions. Then, the information content as well as the degree of freedom for signal are computed and analyzed to characterize this hyper-spectral sounding for atmospheric temperature profiling. Both the vertical distribution of the weighting functions and the width of retrieval averaging kernels indicate that the hyper-spectral band can provide more denser sampling for atmospheric temperature. The information content for the hyper-spectral band is approximately 46% higher than that of the ATMS-type channel 3 to 15, indicating that hyper-spectral measurement can improve the accuracy of retrieval. The most informative channels mainly locate near 57 GHz, having good consistency with the existing channels. The height range where the retrieval using the hyper-spectral observations is sensitive to the true profile, begins from about 800 to 1 hPa. Some channels can be considered as alternatives to each other since they have very similar information content and weighting functions. These results are expected to provide a valuable reference for future applications of the microwave hyper-spectral measurements. [ABSTRACT FROM AUTHOR]

Cold surge (CS) is considered a favorable weather process to improve air quality and is widely recognized. However, there is no detailed study on the differences in the dispersion ability of different types of CSs in relation to haze days in eastern China (HD EC). This paper uses the hierarchical clustering algorithm to classify the cool-season (November to February of the following year) CSs across eastern China into blocking CSs and wave-train CSs and compares their influences on the number of HD EC from 1980 to 2017. Results show that the wave-train CSs can significantly improve the visibility in eastern China and generally improve air quality for about 2 d longer than the blocking CSs, which indicates that the blocking CSs have a weaker ability to dissipate HD EC compared with the wave-train CSs. The CSs affect the HD EC by changing meteorological elements like thermal inversion potential, horizontal surface wind, sea level pressure (SLP), and surface air temperature (SAT). A period of 4 d after the outbreak of CSs, the variations of thermal inversion potential and horizontal surface wind of two types of CSs tend to be consistent. However, the negative SAT anomalies and the positive SLP anomalies caused by the blocking CSs lasted shorter than those caused by the wave-train CSs, forming favorable conditions for the rapid growth of HD EC. Furthermore, results show that in recent years, especially after the 1990s, the frequency of wave-train CSs has decreased significantly, while the frequency of blocking CSs has slightly increased, indicating that the overall ability of CSs to dissipate HD EC has weakened in general. This work may provide reference for the future formulation of haze control policies in East Asia. [ABSTRACT FROM AUTHOR]

The development of an effective drying method to extend the shelf life of raw Chinese hickory (Carya cathayensis) is a major postharvest processing in the nut industry. In this paper, the effect of seed size and drying temperature on hot air drying kinetics and quality of Chinese hickory were detected. Our results reveal that the seed size greatly affects the final equilibrium moisture content of Chinese hickory. So, we predict that a larger Chinese hickory must be dried at a higher temperature. An Arrhenius‐type relationship is found between effective diffusivity (Deff) of Chinese hickory and drying temperature where the activation energy is 40.85 kJ/mol. Accelerated storage results show that Chinese hickory drying at 35 and 45°C have lower acid values, peroxide values, higher content of unsaturated fatty acids than those of 55 and 65°C. We suggested that 45°C is a suitable temperature for the industrial‐scale drying of Chinese hickory. Practical applications: In China, the annual output of Chinese hickory is about 21,500 metric tons. After harvest, fresh Chinese hickory is susceptible to decay and germinate during storage. Recently, the proportion of cracked Chinese hickory and kernel products is constantly rose in the market. So the requirements for the quality of raw materials are increased. Drying is the most critical step after harvest. Traditionally, the drying of Chinese hickory is performed in the presence of the natural sun. In rainy days, Chinese hickory often cannot be dried in time. Hot air drying is a common drying method in industry. However, limited reports are available on hot air drying and its effect on the product quality of Chinese hickory seeds. The results of this paper will help to establish an effective industrial‐scale drying method of Chinese hickory. In addition, the effect of seed size on hot air drying kinetics was also first investigated. [ABSTRACT FROM AUTHOR]

In this paper, the spatial and temporal characteristics of convective precipitation (CP) and large-scale precipitation (LSP) in southern China during 1980–2020 are analyzed using monthly mean precipitation data from MERRA-2. In addition, the possible effects of relative humidity on CP and LSP are explored. The results indicate the following. (1) The LSP dominates the proportion of total precipitation (TP). Both LSP and CP are more prevalent in the south and less prevalent in the north, but there is a difference in the regions of their maximum centers. (2) Significant interannual and seasonal variations are observed in precipitation. TP and LSP tended to be higher than average after the 1990s, while for the CP, a significant negative trend has dominated the past ten years. There are significant increasing trends for TP and LSP, with area-averaged linear trends of 78.1 mm/decade and 85.9 mm/decade, respectively, while that of CP is − 17.1 mm/decade. The increasing trends of LSP are mainly contributed by the precipitation of summer and autumn. (3) The variations of LSP are affected by relative humidity in the troposphere, while CP is only influenced by the changes in relative humidity due to air temperature or specific humidity. The trend of relative humidity is − 0.33%/decade, mainly due to rising temperature in the troposphere. (4) Changes in relative humidity caused by temperature or specific humidity alone act on large-scale precipitation through both interannual and interdecadal processes, causing large-scale precipitation to increase, and the convective precipitation is mainly affected by the interdecadal processes. [ABSTRACT FROM AUTHOR]

This paper aims to provide data support for rural sustainable development through analyzing the spatio-temporal characteristics of the interactions of the outdoor thermal environment. The ordinary and representative rural settlements in the Guanzhong area were selected to analyze the dynamic process of the rural thermal environment through field measurements and numerical simulations. RMSE (root mean square error) and MAPE (mean absolute percentage) were used to verify the numerical simulation model, and physiological equivalent temperature (PET) was used to evaluate the outdoor thermal environment. Results show that the ENVI-met model reliably predicts the thermal environment of a rural settlement, as the air temperature and relative humidity values range of the RMSE and MAPE were 0.85–1.79 and 2.04–5.11%, respectively. Moreover, the air temperature rose by 3.08% and relative humidity dropped by 4.42% from 2003 to 2018 as the amount of artificial surfaces increased by 35.4% and the PET index gradually increased by 27.43% at daytime and 34.03% at nighttime. Furthermore, trees could improve the outdoor thermal environment significantly, mainly because the average air temperature decreased by 3.6% and relative humidity increased by 8%, and the PET index decreased by 12.4% and 13.1%, respectively, for daytime and nighttime. This case study is representative of rural settlements in the Guanzhong plain, and thus is an appeal to rural planners to pay attention to the thermal environment issues caused by increased artificial underlay surfaces and to focus on trees in rural areas. [ABSTRACT FROM AUTHOR]

The arid region of northwest China (ARNC) is one of the most sensitive areas to global warming. However, the performance of new Global Climate Models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating climate in this region, especially in the subregions, is not clear yet. Based on the temperature dataset from historical runs of CMIP6, this paper analyzed and evaluated the simulation ability of 29 GCMs in reproducing the annual mean temperature (tas), annual mean maximum temperature (tasmax) and annual mean minimum temperature (tasmin) in the ARNC and subregions from 1961 to 2014. The results show that (1) the correlation coefficients (CCs) between simulation and observation time series for the mean of two model ensembles (MME for equal-weight multi-model ensemble and PME for preferred-model ensemble) are generally better than those of 29 individual GCMs, with CCs ranging from 0.38 to 0.87 (p < 0.01). (2) All the models can simulate the significant warming trend of the three temperature elements in the study area well. However, the warming magnitude simulated by most of the models (41%) is smaller than the observations except for tasmax, which is also shown in the MME. (3) The spatial pattern of the three temperature elements can be better reflected by most models. Model simulation ability for the ARNC is better compared to that of the four subregions, with a spatial CC greater than 0.7 (p < 0.01). Among the subregions, the simulation performance of the north of Xinjiang for spatial pattern is superior to that of the other regions. (4) The preferred models for each subregion are various and should be treated differently when used. Overall, the PME outperforms both the MME and the individual models; it can not only simulate the linear trend accurately but also reduce the deviation effectively. [ABSTRACT FROM AUTHOR]

Comprehensive bridge design should consider simultaneous actions of wind and temperature. The current load combination method of directly superposing extreme wind and temperature actions ignores the correlation between wind and temperature, resulting in too conservative bridge load estimates, and limiting the further development of the bridge span. Therefore, this paper proposes a method to determine the joint distribution of wind speed, wind direction, and air temperature actions on long-span bridges based on trivariate metaelliptical and Plackett copulas. First, the technique of establishing the trivariate joint distribution via trivariate metaelliptical and Plackett copulas is introduced. Next, the conditional joint distributions of wind speed and air temperature under the specific wind directions are derived from these. Using the concept of conditional bivariate Kendall return period (KRP) proposed in this paper, the conditional KRP isolines of wind speed and air temperature for specific wind directions are constructed. Then, conditional joint estimates of wind speed and air temperature actions for several specific wind directions are obtained using the following principle: the conditional bivariate design return period should be equal to the conditional univariate one. The method feasibility is verified by the case study of the Changtai Yangtze River Bridge in China, which is currently under construction and will be the largest cable-stayed bridge in the world. The results show that the joint actions of wind and temperature on the bridge greatly reduce as compared with the simple superposition of extreme wind and temperature actions specified in the design code. Moreover, a significant contribution of wind direction in the above joint distribution on the large-span bridge load is proved. [ABSTRACT FROM AUTHOR]

Accurate and high‐resolution air temperature prediction is important in many different applications. Hourly air temperature forecasting in mountainous areas is necessary and important because mountainous areas are becoming increasingly important areas of human activities. At present, scientists successfully employ numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, to achieve reliable forecasts. However, air temperature forecasting and modeling over complex geographical zones are still difficult tasks. The WRF model is a mesoscale model and does not adequately account for the influence of terrain on the air temperature. It is important to downscale larger‐scale models to a much finer scale. In this paper, a statistical temperature downscaling method based on geographically weighted regression (GWR) and diurnal temperature cycle (DTC) models is proposed. A statistical downscaling scheme of WRF simulation data is designed to forecast the hourly air temperature from 1‐km spatial resolution to 30 m, up to 24 hr in advance. The combined downscaling model's root‐mean‐square error (RMSE) decreased by 0.87°C at the automatic weather station (AWS) level and 0.62°C over the domain when compared to WRF simulations, and the mean absolute error (MAE) decreased by 0.71°C and 0.51°C, respectively, at these two levels. The results reveal that the combined downscaling model performs very well in correcting and downscaling the air temperature in WRF simulations in the study areas. Key Points: A statistical downscaling scheme was designed for weather research and forecasting (WRF) simulationsTo downscale the hourly air temperature from 1‐km spatial resolution to 30‐m, up to 24 hr in advance in a mountainous areaCompared to WRF simulation results, root‐mean‐square error (RMSE) and mean absolute error (MAE) of WRF‐downscaled results decreased by 0.87°C and 0.71°C, respectively, at the automatic weather station (AWS) level [ABSTRACT FROM AUTHOR]

This study investigated the contribution of Arctic sea ice concentration (SIC) on decadal variations of the dominant mode of summer precipitation over eastern China during 1981–2020. The spatial pattern of leading empirical orthogonal function mode has changed from a dipole pattern with negative anomalies over Jianghuai Valley and positive anomalies over southern China during 1981–2001 to the Yangtze River Valley (YRV) pattern during 2002–2020. Spring SIC over Kara Sea was significantly related to the dipole pattern, through influencing Eurasian snow depth. The associated anomalous temperature gradient and atmospheric circulation affected the meridional displacement of the East Asian subtropical jet, which favored the dipole pattern of summer precipitation. For the YRV pattern, spring SIC over Greenland Sea has an impact on the sea surface temperature anomalies in the western Pacific by triggering a wave train that influenced the precipitation through the establishment of the Pacific–Japan pattern. The results of this study may provide reference value for the prediction of summer precipitation over eastern China. Plain Language Summary: As Eastern China has a high level of national economic development and experiences significant variations in summer precipitation, it is crucial to comprehend the patterns and trends of rainfall. However, it is challenging to accurately predict the decadal variations of precipitation due to the intricate physical processes involved. Therefore, we consider exploring the causes of the decadal variations from the perspective of Arctic SIC. The study demonstrates the dominant mode of eastern China summer precipitation (ECSP) undergone a decadal variation at the early 2000s, and spring SIC over Kara Sea and Greenland Sea play great impacts on it. These results may have potential implications for ECSP forecasting. Key Points: Dominant mode of the summer precipitation over eastern China (ECSP) experienced a decadal variation at the early 2000sSpring sea ice concentration (SIC) over Kara Sea contributed to the dipole pattern of ECSP by influencing the Eurasian snow depth during 1981–2001Spring SIC over Greenland Sea impacted the Yangtze River Valley pattern through the western Pacific sea surface temperature during 2002–2020 [ABSTRACT FROM AUTHOR]

Fengyun-4B (FY-4B) is the first operational satellite from China's latest generation of geostationary meteorological satellites. It is equipped with the Geostationary Interferometric Infrared Sounder (GIIRS), which is able to obtain highly accurate atmospheric temperature and humidity profiles through hyperspectral detection in long- and mid-wave infrared spectral bands. In this study, the accuracy of the FY-4B/GIIRS temperature and humidity profile retrievals over two months is evaluated using radiosonde observations and ERA5 reanalysis data. We go a step further to investigate the impact of the satellite retrievals on assimilation and forecasts for Typhoons Chaba and Ma-on in 2022. Results reveal that the root-mean-square difference (RMSD) for the FY-4B/GIIRS temperature and humidity profile retrievals were within 1 K and 1.5 g/kg, respectively, demonstrating high overall accuracy. Moreover, assimilating temperature and humidity profiles from FY-4B/GIIRS positively impacts model analysis and prediction, improving typhoon track and intensity forecasts. Additionally, improvements have been discovered in predicting precipitation, particularly with high-magnitude rainfall events. [ABSTRACT FROM AUTHOR]

Spring snow cover variability over Northeast China (NEC) has a profound influence on the local grain yield and even the food security of the country, but its drivers remain unclear. In the present study, we investigated the spatiotemporal features and the underlying mechanisms of spring snow cover variability over NEC during 1983–2018 based on the satellite-derived snow cover data and atmospheric reanalysis products. The empirical orthogonal function (EOF) analysis showed that the first EOF mode (EOF1) explains about 50% of the total variances and characterizes a coherent snow cover variability pattern over NEC. Further analyses suggested that the formation of the EOF1 mode is jointly affected by the atmospheric internal variability and the sea surface temperature (SST) anomaly at the interannual timescale. Specifically, following a negative phase of the atmospheric teleconnection of the Polar–Eurasian pattern, a prominent cyclonic circulation appears over NEC, which increases the snowfall over the east of NEC by enhancing the water vapor transport and decreases the air temperature through reducing the solar radiation and intensifying the cold advection. As a result, the snow cover has increased over NEC. Additionally, the tripole structure of the North Atlantic spring SST anomaly could excite a wave-train-type anomalous circulation propagating to NEC that further regulates the snow cover variability by altering the atmospheric dynamic and thermodynamic conditions and the resultant air temperature and snowfall. Our results have important implications on the understanding of the spring snow cover anomaly over NEC and the formulation of the local agricultural production plan. [ABSTRACT FROM AUTHOR]

Meteorological disasters have increasingly become one of the important interferences limiting vegetation growth and productivity recent years, especially in ecologically fragile regions. However, it is unknown how much the impact of meteorological disaster on the vegetation in ecologically fragile area under the changing climate. This study aims to identify the spatial and temporal distribution of four meteorological disasters (drought, rainstorm, high temperature, and low temperature) as well as net primary productivity (NPP) reduction rate in Guangxi province, China, which has large ecologically fragile Karst areas. We also aim to quantify the relative impact of each disaster on NPP loss. During the last 20 years (2000–2019), there was a decreasing trend for drought indicator (drought days), but an increasing trend for rainstorm (cumulated rainfall for daily rainfall higher than 50 mm and less than 99.9 mm), high temperature (daily maximum air temperature higher than 35°C and less than 37°C days), and low temperature (cumulated thermal time for daily minimum temperature less than 0°C) indictors. In the northeast area of study region, all the intensity of rainstorm, high- and low-temperature disasters showed an increasing trend. Under the more intense and frequent meteorological disasters, 87% study sites (60 stations/69 stations in total) showed an increasing trend in terms of NPP reduction rate. Results on grey correlation between each meteorological disaster and NPP reduction rate showed that high-temperature disaster had the greatest impact (27%) on vegetation growth, followed by drought (25%) and rainstorm (25%) disaster, and then low-temperature (23%) disaster. Our results would be helpful for meteorological disasters warning, vegetation protecting as well as policies making for governments. [ABSTRACT FROM AUTHOR]

Heat waves, particularly humid heat waves that occur together with high temperatures and humidity, pose a severe hazard to human health in the context of global warming. In this work, daily observations from more 1500 sites are used to define dry and humid heat waves in a warm season (May to September) and assess their spatiotemporal characteristics during 1960–2015. Dry heat waves are identified with daily maximum temperatures, while humid heat waves are identified based on the wet bulb temperature, derived from both temperature and humidity. We compare dry and humid heat waves from various aspects based on multiple heat wave indices, including their frequency, duration, and intensity. Results suggest that the occurrence of both dry and humid heat wave days in China is higher in the southern than in the northern part of China, due to the higher air temperature and humidity therein. Compared to dry heat waves, humid heat waves are of higher amplitude but shorter duration. The long-term trend analysis shows that the occurrence of both dry and humid heat waves has increased overall over the last 50 years, with an especially rapid increase in the last 20 years, which may be related to China's rapid warming since the late 1980s. The future projections with multiple global climate models indicate that China will experience more frequent, stronger, and longer-duration dry and humid heat waves in the future, under both intermediate and high-emission pathways. [ABSTRACT FROM AUTHOR]

Prolonged low temperature significantly threatens transportation and planting in populous areas and is closely linked to slowly varying forcing such as sea surface temperature (SST). In this study, we reveal the impact of the north–south dipole pattern in extra-tropical North Atlantic SST (DNA) anomaly on surface air temperature (SAT) over southern China in February. The positive phase of the DNA is favorable for a positive North Atlantic Oscillation-like pattern at the troposphere via synoptic eddy vorticity forcing and triggers a southeastward-propagating Rossby wave train associated with the deepened East Asian trough and the strengthened Siberian high, which are conducive to enhancement of the East Asian winter monsoon. A stronger monsoon leads to lower-than-normal SAT over southern China by intensifying southward cold air outbreaks. Considerably, the extremely low temperature over southern China in February 2022 is explainable by this physical mechanism. Furthermore, experiments with a linear baroclinic model verify that the proposed downstream propagating Rossby wave train is mainly associated with the midlatitude North Atlantic SST anomaly. These results emphasize that the extra-tropical North Atlantic SST anomaly should be focused when interpreting and predicting the late winter SAT over southern China. [ABSTRACT FROM AUTHOR]

Extreme heat events happen frequently in East Asia, and may cause great damage to the ecosystem and society. The synergistic effect of the summer positive North Atlantic Oscillation (pNAO) and positive northwest Pacific (pNWP) sea surface temperature anomaly (SSTA) on the interannual variability of the extreme heat events in the central–eastern China (CEC) is investigated in this study. The two factors act synergistically in strengthening the extreme heat events in the CEC via a series of atmospheric bridges, and the CEC is likely to experience a hotter summer when both the summer pNAO and pNWP SSTA occur. The pNWP SSTA increases the strength of pNAO via the eastward propagating Rossby wave from the western Pacific. The enhanced pNAO induces a stronger eastward Rossby wave propagation across the Eurasian continent, and leads to a strong anomalous anticyclone over the CEC. The significantly increased atmosphere thickness increases the air temperature of the layer, and favors the extreme heat events in the CEC. Besides, the pNWP SSTA also has adjacent effect on the atmospheric circulation over the CEC, which could lead to a positive geopotential height anomaly. Therefore, the summer pNAO and pNWP SSTA act synergistically in influencing the atmospheric circulation over the CEC, and thereby significantly increase the extreme heat events in the CEC. [ABSTRACT FROM AUTHOR]

The systematic simulated cold biases in models for surface air temperature (SAT) over China have been under discussion for a long time, but the related attribution is still unclear. In this study, we investigate the main contributors and relevant physical processes of SAT biases over China based on 31 models participating in the sixth phase of the Coupled Model Intercomparison Project from a surface energy budget perspective. On annual and seasonal scales, less downward clear‐sky longwave radiation in the models, which is due to the underestimated tropospheric temperature and water vapor amount, is the main cause of cold biases over the Tibetan Plateau, Tarim Basin, Sichuan Basin, and most of eastern China. Meanwhile, the simulation biases in surface albedo and sensible heat flux induce cold biases depending on regions and seasons. In winter and spring, the overestimated surface albedo in association with more snow cover leads to prevalent cold biases over the western Tibetan Plateau and Northeast China. Excessive sensible heat release caused by the overestimated ground–air temperature difference facilitates SAT underestimation in the Sichuan Basin during summer and autumn. In addition, the cold biases in winter and spring are larger than those in summer and autumn, due to the stronger snow cover overestimation and tropospheric temperature underestimation. Plain Language Summary: The global climate model is a complex system used for describing the atmosphere, land surface, ocean, sea ice components, and their interactions. It has been widely applied to investigate climate change and its associated mechanisms. However, there are still deficiencies in current models for surface air temperature (SAT) simulations. The underlying cause for insufficient simulation is a hot topic of research. In past decades, many studies have shown prevalent SAT cold biases over China in most models, while the related mechanisms remain unknown. Based on the state‐of‐the‐art models, we investigate the causes of the cold biases over China from the perspective of a surface energy budget. The results indicate that the downward clear‐sky longwave radiation simulation error due to the bias of atmospheric states is the primary reason, and the cold biases induced by surface albedo and sensible heat flux vary among regions and seasons. Key Points: We investigate the reasons for the simulated surface air temperature cold biases in sixth phase of the Coupled Model Intercomparison Project models over ChinaLess downward clear‐sky longwave radiation due to underestimated tropospheric temperature and water vapor amount is the main causeCold biases induced by surface albedo and sensible heat flux vary among regions and seasons [ABSTRACT FROM AUTHOR]

Human activities have released a large amount of nitric oxides (NOx) into the atmosphere, leading to elevated regional atmospheric NOx concentration and nitrogen (N) deposition. Several studies have observed a downward NOx or NOy (NOx and its oxidation products) flux to the forest canopy, but attributed it to the photochemical reactions and conversion from gaseous N to particulate N. Here, we focus on the possibility of NOx sink by forest canopy based on an observed downward NOx flux of 0.28 kg N ha−1 yr−1 in a temperate forest of northeastern China, using hourly monitoring of NOx fluxes. In combination with results from previous studies, we find that the downward NOx or NOy fluxes ranged from 0.2 to 1.4 kg N ha−1 yr−1 in temperate forests and from 5.3 to 8.5 kg N ha−1 yr−1 in subtropical forests and they were positively related to atmospheric NOx concentration, mean annual air temperature and annual precipitation across eight forest sites from around the world. If assuming 50% of downward NOx or NOy was directly taken up by the canopy, we estimate a NOx or NOy sink of 0.2 and 1.1 Tg N yr−1 by global respective temperate and subtropical forests, representing an effective scavenger of atmospheric NOx and a considerable N source to forests. We suggest that interception of NOx or NOy by forest canopy should be considered in global NOx budgets and their contribution to the global forest N pool in global Earth System's models. Plain Language Summary: Canopy interception of reactive N has gained wide attention in recent several years, however, its quantification is still unclear. In the present work, we demonstrate the NOx downward movement in a typical temperate forest in northeastern China was partially driven by canopy biological uptake, and then combined results of our in situ observation of canopy NOx flux with other existing 10 monitoring sites worldwide. We estimated an N input of 0.2 and 1.1 Tg N yr−1 in global respective temperate and subtropical forests via downward NOx movement, representing an effective scavenger of atmospheric NOx and a considerable N source to forests. Key Points: The potential importance of canopy NOx uptake by forests for atmospheric NOx concentration and forest N pools is unclearCombining present and previous study results, we estimated a canopy N input of 0.2–1.1 Tg yr−1 in global temperate and subtropical forestsWe suggest that interception of NOx by forest canopy should be considered in global NOx budgets and forest N pools [ABSTRACT FROM AUTHOR]