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The increasing ocean warming due to climate change significantly threatens regional marine ecosystems by raising the frequency and severity of extreme temperature events. This study examines patterns and trends of maximum annual sea surface temperature (Tmax) in the Eastern China Seas from 1985 to 2022. The results show a significant warming trend in Tmax, exceeding the global average, with notable differences between southern and northern regions. The northern Tmax warming rate is faster, with occurrence times significantly advancing, while the southern Tmax warming rate is slower, with occurrence times significantly delayed. The southern Tmax and its timing are closely correlated with the annual maximum air temperature and its timing. In the north, Tmax timing is influenced by latent heat flux (QLH); a significant increase in August QLH inhibits the continued rise of SST, causing Tmax to advance. The study also highlights a significant increase in marine heatwaves at Tmax timing, with higher Tmax indicating a higher occurrence probability. By elucidating these Tmax trends and dynamics, our study enhances understanding of regional climate impacts, supporting targeted conservation efforts and adaptive ecosystem management strategies in the Eastern China Seas. [ABSTRACT FROM AUTHOR]

This study explores aerosol direct, indirect, and feedback effects on meteorology and fine particulate matter during heat waves of August 2022 over eastern China by using an online coupled regional climate–chemistry–aerosol model. In this period, aerosols exerted mean direct (DRE) and indirect (IRE) radiative effects of −3.9 Wm−2 and −2.4 Wm−2 at TOA, which totally caused a decrease in average surface air temperature by 0.3 °C over east China, accompanied by decreases in PBLH (planetary boundary layer height) and precipitation and an increase in PM2.5 concentration. With the anthropogenic emission reduction from 2013 to 2022, DRE apparently decreased while IRE changed little, leading to a decrease in total aerosol radiative effect (TRE) by 27% at TOA. The weakened TRE resulted in increases in surface air temperature and precipitation by 0.14 °C and 2.7 mm, respectively, on average over east China, with the maximum warming exceeding 0.5 °C in BTH (Beijing–Tianjin–Hebei province). This study highlights a warming trend due to weakened TRE, which may exacerbate heat wave, and an increasing importance of aerosol IRE relative to DRE due to weak sensitivity of cloud properties to aerosol change during the emission reduction. [ABSTRACT FROM AUTHOR]

The unprecedented growth in population and swift industrial advancements exert considerable strains on the ecosystem, particularly within medium-sized and large urban landscapes. The critical investigation into the intricate links between current and prospective land utilization, as well as the ecosystem service value (ESV), holds considerable empirical relevance for the calibration of land usage frameworks, thereby contributing to the sustainable evolution of extensive urban zones. Utilizing GlobeLand 30 data, the present research probes into the pattern of land transformation and the spatial-temporal dispersal of ESV in Henan's Yellow River vicinity over a span from 2000 to 2020. For the enhancement of land usage alignment, a Markov-PLUS fusion model was devised to gauge three disparate ESV transition scenarios slated for 2030, namely, natural development scenario (NDS), cropland protection scenario (CPS), and ecological protection scenario (EPS). The principal determinants of land transformation within the 2000-2020 period were recognized as elevation, populace concentration, and atmospheric temperature. Amid the rapid accretion of construction land engulfing substantial cropland and grassland areas, there was an ESV diminution to the tune of 1.432 billion RMB between 2000 and 2020. The ESV's high-value regions were discerned within relatively undisturbed ecosystem zones, with the lower-value sections identified in cropland and constructed areas, where human interventions exerted pronounced effects on the ecosystem. In accordance with the 2030 land usage simulations and analyses, in contrast to alternative scenarios, the EPS exhibited the least fluctuation in land type alterations in 2030, demonstrated the most pronounced escalation in cold spot concentration, and reached a peak agglomeration level. This underscores that the EPS not only offers a refinement in land utilization configuration but also mediates the equilibrium between economic and ecological considerations. The insights derived from this investigation afford innovative evaluative methods for spatial planning, ecological recompense, and sustainable land exploitation within largeand medium-scale urban domains. [ABSTRACT FROM AUTHOR]

In mid-June to July 2023, North China witnessed extreme heatwaves, marked by intense near-surface warming with an advanced seasonal cycle of local air temperature. An unconventional upper-tropospheric cold vortex in early June, deviating from conventional "heat dome" patterns, preceded the heatwave extremes. The zonal SSTA gradient in Indo-Pacific warm pool initially suppressed Indian summer monsoon convection, which stimulated the cold vortex around North China via a tropical-extratropical teleconnection. This anomaly intensified the air-land thermal contrast, leading to increased sensible heating and reduced soil moisture in situ. The drier soil conditions maintained and further augmented sensible heating, escalating surface air temperature, and culminating in extraordinary heatwaves. The air column was then destabilized to mitigate the upper-level cold vortex. Historical records corroborate the extremity of the air-sea interactions in 2023. The ECMWF real-time subseasonal-to-seasonal (S2S) forecasts successfully capture the air-land feedback in both cold vortex and heatwave stages, albeit with an underestimation of heatwave intensity due to biases in soil moisture anomalies. Consequently, the initial cold vortex condition and air-land-sea interactions yield S2S predictability to the historic 2023 heatwaves in North China. [ABSTRACT FROM AUTHOR]

Drylands, where the water supplies are scarce relative to the atmospheric moisture demands, occupy approximately half of the area of China. With global warming, the response of atmospheric water cycle is a crucial concern for sustainable development in China's drylands. This study investigates the characteristics of the water cycle in China's drylands during 1980–2019, as well as future projections estimated by the Community Earth System Model (CESM) during 2020–2100. The results show that the air temperature in China's drylands has increased significantly since 1980, especially after 2000, with greater warming in the warm season. Meanwhile, China generally tend to be drier from 1980 to 2019 as a whole, especially in the cold season. Both precipitation (P) and evapotranspiration (E) have increased, but the net effect is that drylands become drier (negative P-E) and wetlands become wetter (positive P-E), respectively. In the future, drylands are projected to become more humid due to increased precipitation, showing a pattern of "western wetter and eastern drier" during 2020–2100. These results could improve understanding of the water cycle and provide some guidance for adapting to climate change in drylands. [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]

Evidence of climate change can be observed in multiple climate variables, including air temperature rises and precipitation pattern changes. To manage water resources and agriculture effectively, it's important to project climate variables' changes at the local level, as these changes can vary depending on the specific area. The baseline weather data trend was analyzed using the percentage change (PC) method and the Innovative Trend Analysis (ITA) technique at three cluster levels: cluster 1 (PC: 0–20%), cluster 2 (PC: 21–80%), and cluster 3 (PC: 81–100%). The precipitation (Prec.), maximum (Tmax), and minimum (Tmin) temperatures showed downward trends in 9, 4, and 6 stations out of 24 stations, respectively. The SDSM model performed best in predicting Prec., while the LARS-WG model was more effective in predicting Tmax, Tmin, and solar radiation (SR). The average monthly Prec. percentage change shows both rising and falling trends in different weather areas for all three time periods (2040, 2060, and 2090) and for both RCPs (RCP4.5 and RCP8.5). In contrast to precipitation, both Tmax and Tmin consistently showed an upward trend across all meteorological stations for both RCPs and three-time frames. Across the four distinct plain regions, the overall projection suggests a slight increase in precipitation. The study predicts the highest increase in precipitation to occur in June across all meteorological stations. Seasonally, the greatest increase in precipitation is projected during summer (JJA) by 5.10%, while the largest decrease is expected during winter (DJF) by 3.29%. Additionally, precipitation variability shows an increase from RCP4.5 to RCP8.5 and from near-term (2040) to long-term (2090), with the northern Jiangsu Plain exhibiting the highest variation. The biggest rise in Tmax/Tmin was observed at RCP 8.5, by 2.69/2.39 °C, and in the long term (2090), by 3.25/2.86 °C. This was compared to RCP 4.5 by 1.73/1.51 °C, in the near term (2040) by 1.24/1.08 °C, and in the mid-term (2060) by 2.14/1.90 °C. The highest increase in Tmax is expected compared to Tmin, leading to the highest diurnal temperature (DTR) at all three periods and both RCPs. Seasonally, the highest increase is projected in the autumn for both Tmax and Tmin. Similar to Tmax and Tmin, the longest time period (2090) exhibits the highest increase in solar radiation, followed by the midterm (2060) and then the short term (2040). Unlike Tmax and Tmin, the highest increase in SR is predicted during the summer season (JJA), while the lowest increase is projected during the winter season (DJF). The future projections highlight the expectation of a wettest and hottest summer, along with the driest and coldest winter. These findings provide valuable insights for water resource planners, agricultural managers, and policymakers, as these climate variables play a significant role in crop production and water allocation decisions. [ABSTRACT FROM AUTHOR]

Multiple lines of evidence confirm a widespread increase in vegetation growth across China over the past few decades. The relationship between vegetation growth and water availability is thought to be becoming stronger under climate change, that is, water constraints on vegetation growth have been increasing. However, our understanding of how water constraints have influenced these vegetation greening trends, especially those climate change‐driven ones, remains limited. Here, we conduct a comprehensive evaluation of recent water constraints and their implications for vegetation growth in China between 1982 and 2015. By analyzing the spatiotemporal patterns of the relationship between vegetation growth and water availability, we reveal recent water constraints and their changes hidden within an overall greening trend in China. Further analysis demonstrates that two climate change‐related categories, defined broadly as "climate" (e.g., air temperature, precipitation, and so on) and "CO2" (i.e., atmospheric carbon dioxide), have exerted varying levels of importance in regulating vegetation growth across different water constraints. With increasing water constraints, the proportion of the climate‐dominated area has significantly risen, while that of the CO2‐dominated area has sharply declined. Our findings highlight that water constraints can mediate the dominance of climate and atmospheric CO2 on vegetation growth. This has the great potential to exacerbate the uncertainty surrounding current and future sustainable vegetation greening trends. Plain Language Summary: China's vegetation growth has shown a broad increase under climate change and human activities over the past few decades. At the same time, changes in vegetation water demand, terrestrial water availability, and climatic factors are expected to lead to increasing water constraints on vegetation growth. However, whether water constraints have influenced climate change‐driven vegetation greening trends remains unclear. In this study, we provide a comprehensive assessment of recent water constraints and their implications for vegetation growth in China between 1982 and 2015. To do this, we analyze the spatiotemporal patterns of the relationship between vegetation growth and water availability to reveal recent water constraints hidden within China's vegetation greening. Further analysis shows that climate and atmospheric CO2 have exerted varying levels of importance in regulating vegetation growth across different water constraints. With increasing water constraints, more regions become climate‐dominated and fewer become CO2‐dominated. Overall, our findings highlight that water constraints can mediate the dominance of climate and atmospheric CO2 on vegetation growth. This will help decision‐makers recognize the uncertainty of sustainable vegetation greening trends. Key Points: We reveal recent water constraints and their changes hidden within China's widespread vegetation greeningClimate and atmospheric CO2 have exerted varying levels of importance in regulating vegetation growth across different water constraintsWith increasing water constraints, more of China's vegetated regions become climate‐dominated and fewer become CO2‐dominated [ABSTRACT FROM AUTHOR]

The effect of climate warming on rice production in China is profound, yet there has been limited research on how it affects the grain yield, nitrogen (N) uptake, and N utilization efficiency (NUtE) of the double-cropping indica rice in South China. To address this gap, we conducted a free air temperature increase (FATI) experiment in Guangdong province during 2020 and 2021. Our findings revealed that warming led to a significant reduction in grain yield, with early rice (ER) and late rice (LR) experiencing average decreases of 5.2% and 6.3%, respectively, compared to control treatments. This decline was primarily attributed to the reduced grain weight of ER and the fewer spikelet numbers per panicle of LR under warming conditions. Although the dry matter translocation, harvest index, and N translocation efficiency of ER remained unchanged under warming conditions, these of LR decreased by an average of 58.1%, 8.8%, and 22.3%, respectively. Additionally, while warming did not affect the N uptake in ER at maturity, it significantly increased the N uptake in LR by an average of 11.0%. Therefore, under warming conditions, the NUtE of both ER and LR was markedly decreased by 6.9% and 15.5% over the two years. These results indicate that climate warming may have significant negative impacts on the grain yield and the NUtE of indica rice within double-rice cropping systems in South China. Understanding these dynamics is vital for maintaining the stability of rice yields in anticipation of future climate warming. [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]

Introduction: Arid and semi-arid regions are climate-sensitive areas, which account for about 40% of the world's land surface area. Future environment change will impact the environment of these area, resulting in a sharp expansion of arid and semi-arid regions. Cotoneaster multiflorus is a multi-functional tree species with extreme cold, drought and barren resistance, as well as ornamental and medicinal functions. It was found to be one of the most important tree species for ecological restoration in arid and semi-arid areas. However, bioclimatic factors play an important role in the growth, development and distribution of plants. Therefore, exploring the response pattern and ecological adaptability of C. multiflorus to future climate change is important for the longterm ecological restoration of C. multiflorus in arid and semi-arid areas. Methods: In this study, we predicted the potential distribution of C. multiflorus in China under different climate scenarios based on the MaxEnt 2.0 model, and discussed its adaptability and the major factors affecting its geographical distribution. Results: The major factors that explained the geographical distribution of C. multiflorus were Annual precipitation (Bio12), Min air temperature of the coldest month (Bio6), and Mean air temperature of the coldest quarter (Bio11). However, C. multiflorus could thrive in environments where Annual precipitation (Bio12) >150 mm, Min air temperature of the coldest month (Bio6) > -42.5°C, and Mean air temperature of the coldest quarter (Bio11) > -20°C, showcasing its characteristics of cold and drought tolerance. Under different future climate scenarios, the total suitable area for C. multiflorus ranged from 411.199x104 km² to 470.191x104 km², which was 0.8~6.14 percentage points higher than the current total suitable area. Additionally, it would further shift towards higher latitude. Discussion: The MaxEnt 2.0 model predicted the potential distribution pattern of C. multiflorus in the context of future climate change, and identified its ecological adaptability and the main climatic factors affecting its distribution. This study provides an important theoretical basis for natural vegetation restoration in arid and semi-arid areas. [ABSTRACT FROM AUTHOR]

Few studies have investigated the spatial patterns of the air temperature urban heat island (AUHI) and its controlling factors. In this study, the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers. A total of 355 urban clusters were used. We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation. The results show that the midday AUHI is negatively correlated with climate wetness (humid: 0.34 K; semi-humid: 0.50 K; semi-arid: 0.73 K). The annual mean midnight AUHI does not show discernible spatial patterns, but is generally stronger than the midday AUHI. The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid (0.32 ± 0.09 K) and the semi-arid (0.36 ± 0.11 K) climate zones. The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones. The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations. A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land. [ABSTRACT FROM AUTHOR]

With increased atmospheric temperature, temperatures in the shade of trees in parks also increase, and people are faced with high temperature challenges. In this study, thermal comfort in the shade of the trees of an urban park during summer in China was assessed. The subjective responses of the respondents were recorded via questionnaires, and environment parameters were measured. The results show that the air temperature in the shade was 31.1 ± 3.0 °C during the day, and that it peaked at 36.9 °C; the globe temperature was 31.3 ± 3.1 °C, and it peaked at 40.1 ℃. Respondents' clothing insulation was 0.31 ± 0.08 clo, and the effect of clothing adjustment on thermal adaptation was limited. Thermal sensation is linearly related to standard effective temperature (SET), and the upper limit of 80% acceptable SET was 32.1 °C. At different temperature values, the proportion of expected airflow enhancement exceeded 50%. The respondents preferred a neutral-warm sensation. Moreover, there was an obvious thermal adaptation, with thermal history and psychological adaptation being the main factors affecting thermal comfort. This study confirmed the value of shade and provided us with guidance for park planning and design. [ABSTRACT FROM AUTHOR]

Qiongzhuea tumidinoda stands out as an endemic bamboo species of significant conservation importance in Southwest China, particularly in the upper reaches of the Yangtze River. It holds a pivotal role in poverty alleviation through the commercialization of its wood and bamboo shoots. However, the suitable area of this species is undergoing rapid changes due to climate change, resulting in species redistribution and potential losses for bamboo farmers. We utilized 209 presence records and 25 environmental variables from 1987 to 2012 to predict the potentially suitable habitats for Q. tumidinoda using MaxEnt (version 3.4.1), ArcGIS (version 10.8.2), and R (4.3.3). We rigorously screened the recorded data for reliability and accuracy through expert consultations and observer interviews. We performed pre-processing to select the variables with high contributions for modeling, and 11 variables were selected for the final modeling. Our findings reveal that the top three most influential variables associated with Q. tumidinoda's distribution were the mean monthly potential evapotranspiration (Pet), annual range of air temperatures (Bio7), and mean diurnal air temperature range (Bio2), and the rates of contributions from 1987 to 2012 were 4.8333, 3.5833, and 1.7000. There was a southeastward shift and an elevation increase in the potentially suitable habitats for Q. tumidinoda. The area of potentially suitable habitats in the study region exhibited fluctuating growth, expanding from 3063.42 km2 to 7054.38 km2. The mean monthly potential evapotranspiration (Pet) emerged as a critical determinant shaping the distribution of potentially suitable habitats for Q. tumidinoda. Our study sheds light on the response of Q. tumidinoda to climate change, offering valuable insights for the development and management of plantation industries associated with this species. In the future, to enhance prediction accuracy, researchers could equally consider both organic and inorganic environmental variables. For better preservation of environment and development, Q. tumidinoda could be introduced into nature restoration projects in areas with a suitable habitat or as a commodity that participates in forest carbon sink trading. [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]

Relative soil moisture is of great significance to the growth and yield of sugarcane. In this study, we use the relative soil moisture from the China Meteorological Administration Land Data Assimilation System (CLDAS) to dynamically evaluate the water requirement of sugarcane and its growth adaptability at different growth stages. Based on the data of relative soil moisture, air temperature, precipitation, and soil temperature, a sugarcane yield model is established to analyze the projected change trends of sugarcane yield in China from 2020 to 2100 under three future scenarios. Analysis results show that sugarcane requires more water during the elongation stage but less water at the ripening stage. The relative soil moisture from the CLDAS can be used to calculate the proportion of the daily suitable area to the total planting area. The combining of relative soil moisture data and water requirement indicators can better characterize the water requirement during sugarcane growth. Suitable relative soil moisture during the tillering and elongation stages is the most critical factor that directly affects the sugarcane yield. From 2020 to 2100, sugarcane yield will increase first and then decrease sharply. The increase in emissions can lead to an apparent downward trend in sugarcane yield. Based on the CLDAS data and water requirement indicators, a new method for monitoring the sugarcane growth throughout the growth period is proposed in this study. In the SSP370 and SSP460 scenarios, the sugarcane yield showed a downward trend, and there were mutations in 2064 and 2052, respectively. After the mutation, the yield decline trend was more obvious. Under the SSP585 scenario model, the sugarcane production showed an upward trend from 2022 to 2033 and a downward trend after 2033, and a mutation occurred in 2051. After the mutation, the downward trend of sugarcane production was more obvious. [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]

The climatic warming-induced shrinking of permafrost currently encompasses 65% of alpine areas in North China, where a large population relies on its water and land resources. With increasing recognition of the economic and ecological impacts of permafrost basins, forecasts of environmental vulnerability have gained prominence. However, the links between permafrost and winter water resources remain inadequately explored, with most studies focusing on in-situ measurements related to snow cover and frozen layer thickness. Evaluating more complex phenomena, such as the magnitude and persistence of air temperature or low streamflow, depends on numerous climate-driven factors interacting through various subsurface flow mechanisms, basin drainage mechanics, and hydro-climatic correlations at a macroscale. The present study focuses on winter warming, flow increases, and their teleconnections in Xinjiang, China. The research analyzes their links to the atmospheric cycle of the Siberian High (SH) using long-term data spanning 55 years from two large alpine permafrost basins. Changes in variability and correlation persistence were explored for the past decades, and significant variability and connections were constructed using statistical correlation. The years 1980 and 1990 were a turning point when both winter temperatures and winter river flow began to exhibit a notable and consistent upward trend. Subsequently, the period from the mid-1990s to 2013 was characterized by high variability and persistence in these trends. The influence of the SH plays a dominant role in regard to both winter temperatures and river flow, and these variabilities and correlations can be utilized to estimate and predict winter flow in ungauged permafrost rivers in Xinjiang China. [ABSTRACT FROM AUTHOR]

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]

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]

The affiliation between vegetation phenology and seasonal climate (start and end times of the growing season, or SOS and EOS) provides a basis for acquiring insight into the dynamic response of terrestrial ecosystems to the effects of climate change. Although climate warming is an important factor affecting the advancement or delay of plant phenology, understanding the sensitivity of phenology to seasonal variation in climate factors (e.g., local air temperature, precipitation) is generally lacking under different climate backgrounds. In this study, we investigated the interannual variability of grassland phenology and its spatial variation in temperate regions of China based on satellite-derived products for the normalized difference vegetation index (NDVI) and weather data acquired from 2001 to 2020. We found that due to differences in local climate conditions, the effects of seasonal warming and precipitation on phenology were divergent or even opposite during the 20 years. The sensitivities of the start of growing season (SOS) to both spring temperature and last-winter precipitation was controlled by mean annual precipitation in terms of spatial variation. The SOS in the semi-humid (200–400 mm) region was most sensitive to spring temperature, advancing 5.24 days for each 1 °C rise in the average spring temperature (p < 0.05), while it was most sensitive to last-winter precipitation in arid regions (<200 mm), with SOS advancing up to 2.23 days for every 1 mm increase in the last-winter precipitation (p < 0.05). The end of growing season (EOS) was sensitive to autumn temperature, being delayed 10.13 days for each 1 °C rise in the average autumn temperature in regions with temperatures between −10 °C and −5 °C (p < 0.05). The uncertainty in the determination of the EOS could conceivably be greater than the determination of the SOS due to the dual effects of pre-autumn climate and growth constraints induced by declining fall temperatures. The effect of atmospheric warming on grassland phenology was lessened with increased atmospheric and soil aridity, suggesting that the interaction of regional drought and climate warming is an important source for local-to-regional differences and uncertainties in grass phenological response. [ABSTRACT FROM AUTHOR]

Surface freezing and thawing processes pose significant influences on surface water and energy balances, which, in turn, affect vegetation growth, soil moisture, carbon cycling, and terrestrial ecosystems. At present, the changes in surface freezing and thawing states are hotspots of ecological research, but the variations of surface frozen days (SFDs) are less studied, especially in the permafrost areas covered with boreal forest, and the influence of the environmental factors on the SFDs is not clear. Utilizing the Advanced Microwave Scanning Radiometer for EOS (AMSRE) and Microwave Scanning Radiometer 2 (AMSR2) brightness temperature data, this study applies the Freeze–Thaw Discriminant Function Algorithm (DFA) to explore the spatiotemporal variability features of SFDs in the Northeast China Permafrost Zone (NCPZ) and the relationship between the permafrost distribution and the spatial variability characteristics of SFDs; additionally, the Optimal Parameters-based Geographical Detector is employed to determine the factors that affect SFDs. The results showed that the SFDs in the NCPZ decreased with a rate of −0.43 d/a from 2002 to 2021 and significantly decreased on the eastern and western slopes of the Greater Khingan Mountains. Meanwhile, the degree of spatial fluctuation of SFDs increased gradually with a decreasing continuity of permafrost. Snow cover and air temperature were the two most important factors influencing SFD variability in the NCPZ, accounting for 83.9% and 74.8% of the spatial variation, respectively, and SFDs increased gradually with increasing snow cover and decreasing air temperature. The strongest explanatory power of SFD spatial variability was found to be the combination of air temperature and precipitation, which had a coefficient of 94.2%. Moreover, the combination of any two environmental factors increased this power. The findings of this study can be used to design ecological environmental conservation and engineer construction policies in high-latitude permafrost zones with forest cover. [ABSTRACT FROM AUTHOR]

In winter, the water transfer channel of the Middle Route of South-to-North Water Transfer Project (MR-StNWTP) in China always encounters ice problems. The preciously simulation and prediction of water temperature is essential for analyzing the ice condition, which is important for the safety control of the water transfer channel in winter. Due to the difference of specific heat between water and air, when the air temperature rises and falls dramatically, the range of change of water temperature is relatively small and has a lag, which often affects the accuracy of simulation and prediction of water temperature based on air temperature. In the present study, a new approach for simulating and predicting water temperature in water transfer channels in winter has been proposed. By coupling the neural network theory to equations describing water temperature, a model has been developed for predicting water temperature. The temperature data of prototype observations in winter are preprocessed through the wavelet decomposition and noise reduction. Then, the wavelet soft threshold denoising method is used to eliminate the fluctuation of certain temperature data of prototype observations, and the corresponding water temperature is calculated afterward. Compared to calculation results using both general neural network and multiple regression approaches, the calculation results using the proposed model agree well with those of prototype measurements and can effectively improve the accuracy of prediction of water temperature. [ABSTRACT FROM AUTHOR]

The frequency and duration of observed concurrent hot and dry events (HDEs) over China during the growing season (April–September) exhibit significant decadal changes across the mid-1990s. These changes are characterized by increases in HDE frequency and duration over most of China, with relatively large increases over southeastern China (SEC), northern China (NC), and northeastern China (NEC). The frequency of HDEs averaged over China in the present day (PD, 1994–2011) is double that in the early period (EP, 1964–81); the duration of HDEs increases by 60%. Climate experiments with the Met Office Unified Model (MetUM-GOML2) are used to estimate the contributions of anthropogenic forcing to HDE decadal changes over China. Anthropogenic forcing changes can explain 60%–70% of the observed decadal changes, suggesting an important anthropogenic influence on HDE changes over China across the mid-1990s. Single-forcing experiments indicate that the increase in greenhouse gas (GHG) concentrations dominates the simulated decadal changes, increasing the frequency and duration of HDEs throughout China. The change in anthropogenic aerosol (AA) emissions significantly decreases the frequency and duration of HDEs over SEC and NC, but the magnitude of the decrease is much smaller than the increase induced by GHGs. The changes in HDEs in response to anthropogenic forcing are mainly due to the response of climatological mean surface air temperatures. The contributions from changes in variability and changes in climatological mean soil moisture and evapotranspiration are relatively small. The physical processes associated with the response of HDEs to GHG and AA changes are also revealed. [ABSTRACT FROM AUTHOR]

Based on eddy covariance (EC) measurements during 2016–20, the effects of sky conditions on the net ecosystem productivity (NEP) over a subtropical "floating blanket" wetland were investigated. Sky conditions were divided into overcast, cloudy, and sunny conditions. On the half-hourly timescale, the daytime NEP responded more rapidly to the changes in the total photosynthetic active radiation (PARt) under overcast and cloudy skies than that under sunny skies. The increase in the apparent quantum yield under overcast and cloudy conditions was the greatest in spring and the least in summer. Additionally, lower atmospheric vapor pressure deficit (VPD) and moderate air temperature were more conducive to enhancing the apparent quantum yield under cloudy skies. On the daily timescale, NEP and the gross primary production (GPP) were higher under cloudy or sunny conditions than those under overcast conditions across seasons. The daily NEP and GPP during the wet season peaked under cloudy skies. The daily ecosystem light use efficiency (LUE) and water use efficiency (WUE) during the wet season also changed with sky conditions and reached their maximum under overcast and cloudy skies, respectively. The diffuse photosynthetic active radiation (PARd) and air temperature were primarily responsible for the variation of daily NEP from half-hourly to monthly timescales, and the direct photosynthetic active radiation (PARb) had a secondary effect on NEP. Under sunny conditions, PARb and air temperature were the dominant factors controlling daily NEP. While daily NEP was mainly controlled by PARd under cloudy and overcast conditions. [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]

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]

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]

As an important woody oilseed species in China, Triadica sebifera is not only concerned with the substitution of traditional energy sources, but also plays a considerable role in coping with energy shortages. Accurately predicting the potential geographic distribution of Triadica sebifera in China and understanding its ecological needs are crucial for alleviating the energy crisis and effectively implementing energy substitution strategies. In this study, the potential geographic distribution of Triadica sebifera in China at contemporary and future periods was predicted based on the distribution data of Triadica sebifera in China and the environmental factor variables by Maxent model and ArcGIS software. The combination of important factors governing the potential geographic distribution of Triadica sebifera was assessed by the contribution of environmental factor variables. The accuracy of Maxent model's predictions was assessed by AUC values, TSS values and Kappa statistics. The results show that: High AUC and TSS values indicate high accuracy and performance of the model. The crucial environmental factors limiting the potential geographic distribution of Triadica sebifera are the temperature factor (mean air temperature of the driest quarter), precipitation factor (precipitation of the coldest quarter, precipitation of the wettest month), and the intensity of human activities (hf). The total suitable area for Triadica sebifera is 233.64 × 104 km2, primarily located in Yunnan, Sichuan, Hubei, Guizhou, Jiangxi, Guangdong province and Guangxi Zhuang Autonomous Region; its high suitability area is 30.89 × 104 km2, accounting for 13.22% of the total suitable area, mainly distributed in Jiangxi, Sichuan and Hunan provinces in the shape of a cake. Under the four typical greenhouse gas emission concentration patterns in the 2050s and 2070s, the areas of high and medium suitable areas for Triadica sebifera will increase, while the area of its low suitable area will decrease. However, the total suitable area will remain relatively unchanged. Its potential suitable habitats show a trend of shifting towards lower latitudes and southeast regions. The study predicted the pattern of Triadica sebifera under different climate change conditions, which can provide guidance for future cultivation of Triadica sebifera as well as for biofuel development and utilization. [ABSTRACT FROM AUTHOR]

This study aims to explore the roles of multiple gust fronts (i.e., outflow boundaries) during a short-lived extreme rainfall that occurred in the Greater Bay Area of South China in the afternoon of 1 August 2021. Through the use of microbarographs and Doppler weather radars, the research highlights how the interactions of five gust fronts, approaching the region from different directions, have contributed to the high precipitation efficiency and damaging surface winds during the event. The close convergence of these gust fronts funneled unstable air masses into the region of interest, priming the mesoscale convective environment. Some isolated convection initiated before the gust fronts' arrival. Preceding the arrival of these gust fronts, subtle wave-like pressure jumps were identified from the high-frequency (1 Hz) microbarograph observations. The amplitude of the pressure jump is approximately 40 Pa with minimal changes in air temperature. During the early stage of the gust front passages, very high-frequency oscillations in surface pressure are recognized, indicating interaction between the density currents and the low-level troposphere. As suggested through numerical simulations, the subtle pressure jumps are associated with upward displacements of isentropic surfaces aloft, deepening the moist layer and enhancing the lapse rate that are conducive to convective development. The simulated vertical profiles show no evident capping inversion above the dry neutral boundary layer, suggesting that the pressure jumps are likely to be dynamically induced through the collision of the outflows and environmental air masses. The findings of this study suggest the potential application of microbarographs in the nowcasting of the convective development associated with gust fronts. [ABSTRACT FROM AUTHOR]

In spring 2022, strong temperature whiplash events occurred in eastern China (EC), characterized by enhanced subseasonal variability in surface air temperature (SAT). Our results show that extreme temperature fluctuations are dominated by the amplified Eurasian wave train on a biweekly timescale as a possible response to increased sea ice concentrations (SICs) over the Barents‐Kara Seas (BK) in previous winter. Increased winter SICs weaken the upward planetary waves and enhance the stratospheric polar vortex. In spring, the downward propagation of enhanced polar vortex intensifies the polar front jet, increasing kinetic energy gain of the North Atlantic wave train and guiding it to travel farther eastward. The Eurasian wave train strengthens through an upstream development and enhanced local baroclinicity and enhances subseasonal SAT variability over EC. Therefore, the state of BK SICs in previous winter could be a useful signal for the enhanced likelihood of spring extreme temperature whiplash events. Plain Language Summary: In spring 2022, extremely cold and warm spells alternately affected eastern China (EC) and caused drastic temperature whiplash events, featured by the enhanced subseasonal variability of surface air temperature (SAT). We find the subseasonal SAT variability is directly associated with the Eurasian wave train, and its intensity is correlated with sea ice concentrations (SICs) over the Barents‐Kara Seas (BK) in previous winter. Increased SICs reduce the heat transfer from ocean to atmosphere, induce a cyclone anomaly aloft, and diminish the climatological planetary wavenumber‐1 component. The weakened upward wave activity flux strengthens the stratospheric polar vortex, which spreads downward until spring. Hence, the polar front jet in the North Atlantic is enhanced, and the meridional temperature gradient in northern Europe increases, providing a favorable background for atmospheric disturbance development. The North Atlantic wave train propagates farther eastward after gaining more kinetic energy from the accelerated jet and intensifies the following Eurasian wave train. Due to stronger local baroclinic energy conversion, the Eurasian wave train further strengthens, resulting in enhanced subseasonal SAT variability over EC. Therefore, the extremely increased winter BK SICs could be a useful initial signal for the probability of temperature whiplash events over EC in the following spring. Key Points: Record‐breaking subseasonal variability of surface air temperature (SAT) prevails in eastern China in spring 2022Sea ice concentrations over the Barents‐Kara Seas in previous winter strengthen mean state of North Atlantic circulation via the delayed role of the stratosphereThe upstream interaction between mean state and eddies reinforces the Eurasian wave train and enhances subseasonal SAT variability [ABSTRACT FROM AUTHOR]

The Daxing'anling forest region represents a crucial forestry hub in China and confronts some of the nation's most severe freezing–thawing hazards. This study delved into the temporal trends and spatial distributions of various parameters related to freezing and thawing, including air temperature, ground surface temperature, freezing index, thawing index, and freezing–thawing frequency. Furthermore, this study assessed and delineated freezing–thawing hazards within the research area. The findings revealed a rapid increase in air temperature and ground surface temperature within the Daxing'anling forest region yet a lower rate of increase in ground surface temperature compared to Northeast China. Latitude had the strongest influence on mean annual air temperature, mean annual ground surface temperature, air freezing index, air thawing index, ground surface freezing index, ground surface thawing index, air freezing–thawing frequency, and ground surface freezing–thawing frequency, followed by longitude and elevation. Overall, freezing index, and air freezing–thawing frequency increased from south to north, whereas mean annual air temperature, mean annual ground surface temperature, air thawing index, ground surface thawing index, and ground surface freezing–thawing frequency decreased from south to north. The assessment outcomes underscore the importance of closely monitoring freezing–thawing hazards in regions north of the 50th parallel. [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]

The building parameters of Chinese solar greenhouse (CSG) directly affect the front roof lighting and indoor thermal environment. In order to obtain the optimal parameter combination, a building parameter optimization method based on computational fluid dynamics (CFD) simulation and entropy weight method was proposed. Firstly, a three-dimensional thermal and humidity environment model of CSG was constructed considering the coupling effect of soil, crop, and back wall based on CFD. The reliability of the model was validated through experiments in a CSG of Yongqing County, Hebei Province of China. Then, the indoor air temperature rise rate, air temperature and humidity uneven coefficient, and average air temperature and humidity were selected as the evaluation indicators of CSG thermal and humidity environment. The ridge height, back wall height and the horizontal projection of back roof of CSG were selected as the three factors of the orthogonal test plan, and a three-factor and four-level plan was designed, resulting in 16 different parameter combinations. By use of CFD simulation, the thermal and humidity environment evaluation indicators under different parameter combinations were calculated. The entropy weight method was used to assign weights to the evaluation indicators, and the comprehensive evaluation indicators of CSG thermal and humidity environment were obtained based on the linear weighting principle. By comparing comprehensive evaluation indicators, the optimal combination of building parameters was obtained with a ridge height of 5.72 m, a back wall height of 3.2 m, and a horizontal projection of 2.1 m on the back roof. The research results can provide a practical and feasible method for optimizing the building parameters of CSG, and provided theoretical guidance for the structural design and optimization of CSG. [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]

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]

Cotton (Gossypium hirsutum L.) is an economically important crop in China, and responses of cotton yield in different regions to separate and joint changes in natural and anthropogenic factors are the foundation for sustainable development under climate change; however, these remain uncertain. Here, we analyzed the spatiotemporal evolution and heterogeneity of cotton cultivation in China from 1949 to 2020 and quantified the response of cotton yield variations in air temperature, precipitation, solar radiation, disaster, and crop management factors between 1980 and 2020 by the Pettitt mutation test and GeoDetector. Multi-site meteorological data were obtained from different cotton-growing regions and corresponding cotton yield and phenology data were obtained from provinces. Our findings showed that all 17 Chinese provinces experienced advancements in cotton yield. Relative to 1949–1967, China's cotton production in 2007–2020 increased by 400% while cotton yield increased by 420%. Increases in factors such as minimum temperature (TES), average temperature (ADT), effective accumulated temperature (EAT), precipitation (PP), daily solar radiation (SSD), non-farm employment opportunities (O), disaster area (D), geographic region (GEO) and agricultural technologies like fertilizer usage (F), genetically modified varieties (Bt), and mechanized farming (M) have contributed to the enhanced cotton yield. The importance of single factors influencing cotton yield of China in descending order was as follows: F > Bt > M > GEO > EAT > O > PP > TES > ADT > SSD > D. However, the effects of different climatic and agriculture technological elements on cotton yield are spatially heterogeneous by region, and the combined effects of those elements are higher than those of single elements. The effects of driving factors vary across regional scales. The most significant interaction effects were observed between chemical fertilizer use and other driving factors. Specifically, the interaction between F and TES has the greatest explanatory influence in Northwest China. Our findings provide a reference for the development of more accurate adaptation strategies and management measures in different regions. We recommend that policymakers prioritize measures such as improving climate-resilient cotton varieties, encouraging technological advancements, and implementing policies that support equitable distribution of cultivation. [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]

This study observed the characteristics and influencing factors of the carbon fluxes of the Momoge salt marsh ecosystem over four years, which behaves as a CO2 sink. The daily, seasonal, and interannual variations in CO2 fluxes in the Momoge salt marshes were observed using the eddy covariance method and were compared with various environmental factors. An overall daily "U"-shaped distribution was observed, with uptake during the day (negative values) and release at night (positive values). Annually, the carbon fluxes in the study area roughly exhibited a "V" shape. The carbon fluxes during the non-growing season predominantly showed positive values, indicating the release of CO2 into the atmosphere. Photosynthetically active radiation was the primary influencing factor affecting the hourly and daytime variations in net ecosystem exchange (NEE) during the growing season, while temperature was the main factor influencing nighttime NEE dynamics. The air temperature, soil temperature, photosynthetically active radiation, precipitation, and water level all had significant impacts on the daily net CO2 exchange. At the monthly scale, larger values of soil temperature, air temperature, photosynthetically active radiation, and aboveground biomass corresponded to a stronger carbon absorption capacity of the ecosystem. Overall, temperature remains the primary factor for carbon fluxes in the Momoge wetlands. [ABSTRACT FROM AUTHOR]

Climate and topography are pivotal factors influencing snow cover variation, highlighting the significance of investigating the altitudinal response of snow cover to climate change. This study adopted a new MODIS snow cover extent product over China, reanalysis climate data, and digital elevation model (DEM) data to analyze the variation characteristics of snow cover frequency (SCF) and climatic factors with elevation in the Keriya River Basin (KRB) during the hydrological years from 2000 to 2020. The Partial Least Squares Regression (PLSR) method was utilized to explore the elevation-based relationships between SCF and climatic factors. Our findings can be summarized as follows: (1) The SCF exhibited an "increasing–decreasing–increasing–decreasing" pattern intra-annually, with insignificant monthly inter-annual variations. Only November, January, April, and May demonstrated upward trends, whereas October and December remained relatively stable, and other months exhibited declines. (2) Vertical variations in SCF and climatic factors revealed fluctuating upward trends in SCF and wind speed. On the other hand, the air temperature consistently decreased at a lapse rate ranging from 0.60 to 0.85 °C/100 m. Precipitation demonstrated "rising–falling" or "rapidly rising–slowly rising" patterns, bounded by 3821 m (range 3474–4576 m). (3) A new decision scheme, which took into account the alteration of the primary SCF controlling factors and shifts between positive and negative impacts caused by these factors, was used to determine five threshold elevation zones: 2585 m (range 2426–2723 m), 3447 m (range 3125–3774 m), 4251 m (range 4126–4375 m), 5256 m (range 4975–5524 m), and 5992 m (range 5874–6425 m). These threshold elevation zones were evident in spring, with four of these appearing in autumn (excluding 4251 m) and summer (excluding 2585 m). Only two threshold elevation zones were observed in winter with elevation values of 3447 m and 5992 m, respectively. Our findings are crucial for a deeper understanding of snow cover variation patterns at different elevations and offer essential insights for the responsible management of regional water resources. [ABSTRACT FROM AUTHOR]

Global warming poses a significant environmental challenge, which is primarily driven by the increase in greenhouse gas concentrations. In this study, we aimed to investigate the factors influencing CH4/N2O emissions from agricultural soils over Hainan Island, China, from 2009 to 2018. To achieve this, we selected air temperature, precipitation, and solar radiation as climate factors and categorized farmland as paddy or non-paddy, using revised EDGAR greenhouse gas datasets involving the bias correction method, and geographical detector analysis, multiple linear regression models, and bias sensitivity analysis were used to quantify the sensitivity of climate and land use. The maximum air temperature emerged as the primary factor influencing CH4 emissions, while the mean air temperature predominantly affected N2O emissions. The ratio of paddy field area to city area emerged as the second most influential factor impacting CH4/N2O emissions. The mean CH4/N2O emission intensity from paddy fields was significantly higher (0.42 t·hm−2/0.0068 t·hm−2) compared to that of non-paddy fields (0.04 t·hm−2/0.002 t·hm−2). Changes in maximum air temperature under global warming and crop irrigation practices profoundly affect greenhouse gas emissions on Hainan Island. Specifically, the emission intensities of CH4 and N2O increased by 14.2% and 11.14% for each Kelvin warmer, respectively. [ABSTRACT FROM AUTHOR]

The variation of surface air temperature is one of the most direct manifestations of global warming. Current research on this variable mainly focuses on climatology and extreme temperatures; however, the daily to monthly variation of temperature across extratropical regions is significantly affected by the annual cycle. Climate models play a key role in simulating the historical climate and assessing climate variability. This study investigated the temperature annual cycle and its variation in China from 1961 to 2014, using the observations collected at meteorological stations and the outputs of CMIP6 models. Regional differences and model discrepancies were evaluated to reveal the capabilities of CMIP6 models. The phase-max, phase-min, and amplitude were used to represent the annual cycle, after Fourier transformation was applied to daily temperature to filter high-frequency noise. The climatology, interannual variability, and long-term trends of the three above-mentioned parameters simulated in CMIP6 models were compared with those obtained from observations over the whole study area and in selected regions. The results showed that the models could reasonably describe the climatological temperature annual cycle from 1961 to 2014, although the values were underestimated relative to meteorological observations. Station observation and CMIP6 models also showed a similar spatial distribution of the phase-max, phase-min, and amplitude values, with an obvious north–south gradient. Station observations exhibited a large interannual variability, an advance in phase-max and phase-min, and a decrease in amplitude, which were poorly revealed by the CMIP6 models. [ABSTRACT FROM AUTHOR]

The growing concern surrounding climate change has gradually drawn attention to the influence of climate factors on drought occurrence. In order to effectively prevent the occurrence of drought and reasonably utilize water resources, the vegetation health index (VHI) was used to characterize drought in North China Plain (NCP) in this study. Furthermore, six climate factors: air temperature (AT), precipitation (P), evapotranspiration (ET), specific humidity (SH), soil moisture (SM), and soil temperature (ST) were selected. The pole symmetric mode decomposition (PSMD) and improved gridded trend test (IGT) were used to analyze the spatial–temporal characteristics of drought and climate factors in NCP from 1982 to 2020. By calculating the cumulative climatic factors of 0 months, 1 month, 2 months, and 3 months, the correlation between drought and the climatic factors with different cumulative scales was analyzed. The results showed that: (1) from 1982 to 2020, the drought in NCP showed a downward trend and the climate factors showed an upward trend; (2) with the increase in AT, P, ET, SH, SM, and ST, VHI showed an upward trend, and SM showed the strongest correlation with VHI; (3) the optimal cumulative lag time (CLT) for AT, P, ET, SH, SM, and ST were 1.67 months, 1.48 months, 1.95 months, 1.69 months, 0.89 months, and 1.81 months, respectively; and (4) AT was the main driving factor of drought in NCP. This study contributes to the early warning and prediction of drought events, providing a scientific basis for water management authorities in drought management and decision making, and mitigating the negative impacts of drought on socio-economic aspects. [ABSTRACT FROM AUTHOR]

China's marine satellite infrared radiometer SST remote sensing observations began relatively late. Thus, it is essential to evaluate and correct the SST observation data of the Ocean Color and Temperature Scanner (COCTS) onboard the China HY-1C satellite in the Southeast Asia seas. We conducted a quality assessment and correction work on the SST of the China COCTS/HY-1C in Southeast Asian seas based on multisource satellite SST data and temperature data measured by Argo buoys. The accuracy evaluation results of the COCTS SST indicated that the bias, Std, and RMSE of the daytime SST data for HY-1C were −0.73 °C, 1.38 °C, and 1.56 °C, respectively, while the bias, Std, and RMSE of the nighttime SST data were −0.95 °C, 1.57 °C, and 1.83 °C, respectively. The COCTS SST accuracy was significantly lower than that of other infrared radiometers. The effect of the COCTS SST zonal correction was most significant, with the Std and RMSE approaching 1 °C. After correction, the RMSE of the daytime SST and nighttime SST data decreased by 32.52% and 42.04%, respectively. [ABSTRACT FROM AUTHOR]

Irrigation has excellent potential for altering surface characteristics and the local climate. Although studies using site observations or remote sensing data have demonstrated an irrigation cooling effect (ICE) on the air temperature (Tem) and land surface temperature (LST), it is difficult to eliminate other stress factors due to different backgrounds. We characterized the irrigation effect as the differences (Δ) of LST and DCT (DCT = LST − Tem) between irrigated and adjacent non-irrigated areas. An improved method was proposed to detect it over the North China Plain (NCP) based on satellite observations. We also investigated the effects of irrigation on Tem, precipitation, NDVI, and ET, and explored the relationships between them. The results show that irrigation induced a decrease in the daytime/nighttime LST and DCT (−0.13/−0.09 and −0.14/−0.07 °C yr−1), Tem (−0.023 °C in spring), and precipitation (−1.461 mm yr−1), and an increase in NDVI (0.03 in spring) and ET (0.289 mm yr−1) across the NCP. The effect on nighttime LST and NDVI increased by 0.04 °C 10 yr−1 and 0.003 10 yr−1, and that on ET weakened by 0.23 mm 10 yr−1 during 2000–2015. The ICE on the LST had evident spatiotemporal heterogeneity, which was greater in the daytime, in the spring, and in the northern area of the NCP (dry–hot conditions). The daytime ICE in the NCP and northern NCP was 0.37 and 0.50 °C during spring, respectively, with the strongest ICE of 0.60 °C in Henan; however, the ICE was less evident (<0.1 °C) in the southern NCP throughout the year. The ΔNDVI, ΔET, and ΔTem were the main factors driving ICE, explaining approximatively 22%, 45%, and 25% of the daytime ICE, respectively. For every unit of these measures that was increased, the daytime ICE increased by about 7.3, 4.6, and 1.5 °C, respectively. This study highlights the broad irrigation effect on LST, ET, NDVI, and the climate, and provides important information for predicting climate change in the future. The improved method is more suitable for regions with uneven terrain and a varying climate. [ABSTRACT FROM AUTHOR]

A number of previous studies have contributed to a better understanding of the thermal impacts of dam-related reservoirs on stream temperature, but very few studies have focused on air temperature, especially at the catchment scale. In addition, due to the lack of quantitative analysis, the identification of the effects of water impoundment on regional air temperature is still lacking. We investigated the impacts of reservoirs on the regional air temperature changes before and after two large dam constructions in the lower Jinsha River located in southwest China, by using a 40 year record of reanalysis data at 90 m resolutions. Furthermore, the long short-term memory (LSTM) model was also employed to construct an impoundment effect on the temperature (IET) index. Research results indicate that compared to the pre-impoundment period (1980–2012), the variations in the air temperature at the catchment scale were reduced during the post-impoundment period (2013–2019). The annual maximum air temperature decreased by 0.4 °C relative to the natural regimes. In contrast, the cumulative effects of dam-related reservoirs increased the annual mean and minimum air temperature by 0.1 °C and 1.0 °C, respectively. Warming effects prevailed during the dry season and in the regions with high elevations, while cooling effects dominated within a 4 km buffer of the reservoirs. Therefore, this study offers important insights about the impacts of anthropogenic impoundments on air temperature changes, which could be useful for policymakers to have a more informed and profound understanding of local climate changes in dammed areas. [ABSTRACT FROM AUTHOR]

Studying the distribution characteristics of bioaerosols and their interaction with the environment is crucial for dairy farms. The distribution of aerosols differs in dairy farming from farming of other livestock, and their sensitivity to environmental factors varies across sites. Field experiments were conducted in an intensive commercial dairy farm in Northern China to investigate the horizontal and vertical distribution of culturable bacterial bioaerosols. Concentration levels and particle size ranges were analyzed, and the impact of multiple environmental factors on culturable bacterial bioaerosols was assessed. Significant variations in culturable bacterial bioaerosol concentrations were observed across eight functional zones, ranging from 1.14 × 103 to 7.35 × 103 CFU/m3. Culturable bacterial bioaerosols exhibited consistent carrier distribution patterns across six different size ranges. Vertical analysis revealed significantly higher culturable bacterial bioaerosol concentrations at a 1 m height compared to 4 m (p < 0.05), while similar size distributions were observed at different heights of the same sampling location. The top three environmental factors influencing culturable bacterial bioaerosol concentrations were PM100 concentration, wind direction, and air temperature. This study provides insights into the distribution characteristics of culturable bacterial bioaerosols on dairy farms and their response to environmental factors. The findings serve as a reference for evaluating bioaerosol emissions and establishing daily disinfection management measures on dairy farms. [ABSTRACT FROM AUTHOR]