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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]

Evapotranspiration (ET) is a key component of the hydrological cycle, but traditional monitoring approaches are always based on measurements, which cannot satisfy the requirements of research on a regional scale. Hence, ET estimation by remote sensing is essential. MOD16 is a remote-sensing model based on the P-M equation and has good applicability. However, it describes soil moisture indirectly by RH, etc., which may cause uncertainties in ET estimating, so this study attempts to utilize the NDWI as a supplement to soil moisture information and makes improvements on the MOD16 model (with the resultant new model being named MOD16-sm). Specific work includes two aspects: one is model verification through making comparisons between ET estimates and measurements, and the other is a model application effect test analyzing the spatiotemporal characteristics of ET and exploring how ET responds to climate and land-use changes. Model verification indicated that the accuracy of the improved MOD16-sm model increased, with a higher R2 of 0.71, a lower RMSE 0.9 mm, and a lower MAE 0.91 mm, and that the improved MOD16-sm model was convincing. The application effect test of the MOD16-sm model showed that the average relative change rate of annual ET was 1.7%, showing an upward trend, and areas with growth trends of ET also had high vegetation coverage. As for the impacts of climate and land-use changes on ET, ET was positively correlated with precipitation, whereas it had no relevant correlation with air temperature in most areas, and the ET of all land-use types displayed significant increasing trends resulting from climate change. The application effect test demonstrated that ET estimates by the improved MOD16-sm model were reasonable. [ABSTRACT FROM AUTHOR]

Climate change exhibits great variation on different flanks and at different elevations in the same mountain range. To investigate the complexity of the geographic patterns of climate and phenology in the Qinling–Daba mountains (QDM), in the North–South transition zone of China, this study analyzed the spatiotemporal distribution characteristics of daily air temperature and precipitation data measured at 118 national weather stations (1969–2018). The principal findings were as follows. (1) Overall, a significant trend of warming was detected in all seasons over the past 50 years, with rates of increase of 0.347, 0.125, 0.200 and 0.302 °C/10a, in spring, summer, autumn and winter, respectively. Precipitation did not show significant variation at most stations in different seasons. (2) The rising rate of air temperature varied considerably between different flanks. Generally, air temperature change on northern flanks was greater than on southern flanks in all seasons. The tendency of air temperature change was greater in spring and winter than in summer and autumn on different flanks in the QDM. (3) The rate of increase in high-elevation regions was greater than in low-elevation regions in summer, autumn and winter, e.g., 0.440, 0.390 and 0.456 °C/10a at 3000–4000 m and 0.205, 0.218 and 0.303 °C/10a at 0–1000 m, respectively. However, in spring, the rate of increase in low-elevation regions were higher than in high-elevation regions, e.g., 0.369 °C/10a at 0–1000 m and 0.317 °C/10a at 3000–4000 m. [ABSTRACT FROM AUTHOR]

The impact of soil freezing‐thawing processes on August rainfall in Southern China (SC) during 1979–2008 and related physical mechanisms are investigated using the coupled land‐atmosphere model Grid‐Point Atmospheric Model version 2.0—Community Land Model version 2.0 (GAMIL2.0‐CLM2.0). The moisture‐budget analysis is employed to quantify the contributions of different factors to the change of precipitation in SC. The results indicate that the vertical moisture advection and its dynamic component play an essential role in the long‐term trends of August rainfall. The possible physical mechanism is that the model which includes the supercooled water simulates much higher soil/air temperature in August, especially in the north of 40°N, which is not only weakened the meridional thermal contrast but also induced an anomaly "north high–south low" circulation pattern in the middle and high latitude of Eurasia. Both resulted in the 200 hPa zonal winds weakening, and 850 hpa northerly wind southward moved. Meanwhile, a convergence anomaly cyclone is initiated in the lower troposphere over SC regions, accompanied by enhanced ascending and strong moisture flux convergence, which is beneficial to the increased precipitation. This study provides a new interpretation of the "southern flooding" during 1979–2008 from the point of frozen soil changing. Key Points: The coupled land‐atmosphere model (Grid‐Point Atmospheric Model version 2.0‐Community Land Model version 2.0) with the consideration of supercooled water reproduces the trend of the August rainfall in Southern ChinaThe dynamic processes of the vertical moisture advection play a vital role in the long‐term trend of the August rainfallThe decreasing soil ice content has contributed to the wetter of Southern China in August over 1979–2008 [ABSTRACT FROM AUTHOR]

Meteorologically observed air temperature (Ta) is limited due to low density and uneven distribution that leads to uncertain accuracy. Therefore, remote sensing data have been widely used to estimate near-surface Ta on various temporal scales due to their spatially continuous characteristics. However, few studies have focused on instantaneous Ta when satellites overpass. This study aims to produce both daily and instantaneous Ta datasets at 1 km resolution for the Jingjinji area, China during 2018–2019, using machine learning methods based on remote sensing data, dense meteorological observation station data, and auxiliary data (such as elevation and normalized difference vegetation index). Newly released Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 surface Downward Shortwave Radiation (DSR) was introduced to improve the accuracy of Ta estimation. Five machine learning algorithms were implemented and compared so that the optimal one could be selected. The random forest (RF) algorithm outperformed the others (such as decision tree, feedforward neural network, generalized linear model) and RF obtained the highest accuracy in model validation with a daily root mean square error (RMSE) of 1.29 °C, mean absolute error (MAE) of 0.94 °C, daytime instantaneous RMSE of 1.88 °C, MAE of 1.35 °C, nighttime instantaneous RMSE of 2.47 °C, and MAE of 1.83 °C. The corresponding R2 was 0.99 for daily average, 0.98 for daytime instantaneous, and 0.95 for nighttime instantaneous. Analysis showed that land surface temperature (LST) was the most important factor contributing to model accuracy, followed by solar declination and DSR, which implied that DSR should be prioritized when estimating Ta. Particularly, these results outperformed most models presented in previous studies. These findings suggested that RF could be used to estimate daily instantaneous Ta at unprecedented accuracy and temporal scale with proper training and very dense station data. The estimated dataset could be very useful for local climate and ecology studies, as well as for nature resources exploration. [ABSTRACT FROM AUTHOR]

In-depth understanding and accurate simulation of hydrological processes are of great significance for sustainable development and management of water resources. The study focused on a semi-arid catchment, the upper Tang River catchment in northern China, and investigated the performance of the RCCC-WBM model based on the detection results of trend, mutation, and periodicity. Results show that (1) as a result of climate change and intensive human activities, the observed runoff series after TFPW (trend-free pre-whiting) pretreatment presented a significant downward trend with the mutation point in 1996; (2) the abrupt change of air temperature series was also in 1996 with a significant rising trend, while the annual precipitation series exhibited an insignificant declining trend with no obvious mutation during 1973–2014; (3) the precipitation and runoff series had periodic variations roughly 7a multiples with the periodic oscillation strongest around 14a, while the air temperature series showed only one dominant period of 28a; (4) the RCCC-WBM model performed well in discharge simulation before the mutation year but gradually lost its stability after 1996, which was mainly affected by anthropogenic activities. It is essential to accurately identify the characteristics of hydrological elements and improve the applicability of hydrological models in the changing environment in future studies. [ABSTRACT FROM AUTHOR]

River flow regulations and thermal regimes have been altered by human-induced interventions (such as dam construction) or climate change (such as air temperature variations). It is of great significance to adopt a well-performed data-driven model to accurately quantify the impact of human-induced interventions or climate change over river water temperature (WT), which can help understand the underlying evolution mechanism of the river thermal regimes by dam operation or climate change. This research applied the Bayesian network-based model (BNM), which can easily identify inherently stronger associated variables with a target variable from multiple influencing variables to predict the daily WT and make a quantitative assessment of the effect produced by Three Gorges Reservoir (TGR) construction in the Yangtze River, China. A comparative study between the proposed model and two other models was implemented to verify the predicted accuracy of the BNM. With the help of the BNM model, the impact of reservoir impoundment over water temperature was quantitatively analyzed by calculating the difference between reconstructed water temperature series and observed series during the post-TGR period. The construction of the TGR posed more impact on variations in WT than the impact induced by the climate change according to results. The effect of TGR on WT can be concluded as follows: WT from October to January in post-TGR showed a remarkable warming tendency and an increase in released warmer water volumes than before, while WT showed a cooling tendency during March to June because of the hysteretic effect of WT response to increasing air temperature. The proposed BNM model shows great potential for WT prediction and ecological risk management of rivers. [ABSTRACT FROM AUTHOR]

Climate change has greatly impacted hydrologic regimes of lakes in sub-tropical and tropical areas. However, three major challenges impede the accuracy of hydrological simulation and impact assessment processes, namely avoiding uncertainties caused by climate scenarios, selecting comprehensive hydrological indicators, and enhancing spatiotemporal precision of hydrological simulation. To address these issues, the current case study used the Lake Dianchi Basin (LDB) to demonstrate a sub-catchment scale and detailed integrated model framework. This framework was generated based on localized climate change possibilities, detailed hydrological simulation results, and a comprehensive assessment of the impacts of climate change on hydrologic regimes. The results showed that (1) the sub-tropical LDB has hydrologic regimes that are significantly impacted by climate change with changes in precipitation exerting a greater impact than air temperature changes. (2) The annual scale runoff, as well as 16 other hydrological indicators exhibit large variation among the 18 climate scenarios. Wet season and 1/3/7-day minimums/maximums may be more significantly impacted by climate change than dry season and other indicators. (3) The hydrologic regimes of the LDB is vulnerable to climate change, which may pose enormous ecological and socio-economic risk to the LDB. Among all six sub-catchments, Sub_06, characterized by a hilly landscape, would be impacted the most by climate change. Collectively, the findings of this study indicate that regions with complex climatic conditions and topography have different responses in annual scale runoff and extreme indicators, which must be fully considered. [ABSTRACT FROM AUTHOR]

As a direct manifestation of global warming, the air temperature has been reported to rise significantly during the last several decades. Meanwhile, precipitation around the world has also changed profoundly. Therefore, it is important to unravel the long‐term changes in temperature and precipitation as well as their relationship. This study investigates the characteristics of temperature and precipitation in China from 1961 to 2018. Based on theoretical simulations, the effect of cloud droplet growth and precipitation formation on cloud temperature change has been determined. It has been found that for a specific cloud, the change in surface tension with temperature can increase the supersaturation rate in the cloud, which promotes precipitation by about 10%·K−1. A real dataset was then used to analyse the state change in temperature and precipitation under climate change. Precipitation showed an increasing trend by 13.9%·K−1 throughout China with increasing temperature, which reflects the combined effect of the decrease in rainfall frequency and the increase in rainfall intensity. This indicates that the theoretical simulations could provide a reference model to analyse the actual precipitation–temperature relationship (PTR). In addition, the PTR showed large regional variations: 5.1%·K−1 in North China, 5.6%·K−1 in the Northeast region, 19.6%·K−1 in the Yangtze River valley, 20.4%·K−1 in the Southeast, 14.1%·K−1 in the Southwest, and 9.2%·K−1 in the Northwest, which may be limited by the relative humidity. [ABSTRACT FROM AUTHOR]

Evapotranspiration is one of the critical processes in the terrestrial hydrological cycle, and the assessment of evapotranspiration is essential for understanding the regional hydrological cycle. In this study, the Minjiang River Basin, a typical watershed in the humid subtropical climate zone, is selected as the study region. The Penman-Monteith equation and the dual crop coefficient method are used to calculate the actual evapotranspiration (ETa) at seven meteorological stations within the study basin. Meanwhile, the applicability of the Global Land Data Assimilation System-Noah (GLDAS-Noah) ETa data in the Minjiang River Basin is evaluated based on stations P-M equation results, then to analyze the changes of the ETa in the Minjiang River Basin from 2000 to 2019. The results show that the GLDAS-Noah ETa data are well applicable in the Minjiang River Basin (R2 > 0.9 and NSE > 0.8). The ETa in the basin shows an increasing trend since 2000, and the increasing rate is 3.60 mm·yr−1 (p < 0.01). The seasonal variation results show that ETa tends to increase in winter and spring, with increasing rates of 1.10 mm·yr−1 (p < 0.01) and 2.60 mm·yr−1 (p < 0.01), respectively, while the ETa did not change significantly in summer and autumn. Annual air temperature has the largest effect on annual ETa (59.6%), followed by precipitation at 33.9%. ETa increased in spring was mainly influenced by increasing temperatures (89.4%) in the Minjiang River Basin from 2000 to 2019. The research results are of great benefit to further improve the understanding of ETa variations in the basin under global warming. [ABSTRACT FROM AUTHOR]

The increasing application of floor heating technology promotes the development of floor radiant cooling technology (abbreviated as FRC technology). Many office buildings in northern China try to use FRC technology to cool in summer, but thermal comfort is the key problem restricting the promotion of this technology. The thermal comfort problems of an office room with floor radiant cooling were studied in this paper by the methods of numerical simulation, control variable, and data fitting, and the experimental results were verified in multiple ways. It was found that, for an office room using floor radiant cooling, the effect of the floor surface temperature on thermal comfort was about 16%, while the effect of indoor air temperature was about 84%, and relative humidity had little effect on thermal comfort. A simplified thermal comfort calculation model was proposed, which could be used as an indicator to adjust the floor surface and indoor air temperature, or could be used to calculate the PMV-PPD value. The findings have guiding significance for the design and control of FRC technology. [ABSTRACT FROM AUTHOR]

Slate dwellings are known as the "living fossil of primitive dwellings" in China. Energy-saving strategies are crucial to slate dwellings for sustainability as well as maintaining thermal comfort. In this research, a subjective satisfaction analysis on the indoor thermal environment in Daziliang village, China, was conducted. It was found that neutral temperature is 20.92 °C in summer, 8.92 °C in winter, and the actual operating temperature in winter is too low to meet the 80% acceptable range. Therefore, a series of improvement strategies in winter were proposed. The results showed that adding external thermal insulation material—expanded polystyrene board with a thickness of 80 mm on the roof and outside walls—and sunspace depth of 1.5 m are better in terms of energy-saving effects. In addition, the slate dwelling's daily energy-saving rate of the heating day is 44.26% lower than the original state through these strategies. The air temperature of Bedroom D in winter non-heating days increases by 3.82 °C after improvement and the mean radiant temperature increased by 2.54 °C. Our approach puts forward specific energy-saving improvement measures and provides feasible suggestions for the protection and development of slate dwellings in this area. [ABSTRACT FROM AUTHOR]

Seasonal abandonment in the previously rice‐based rotation system is increasingly prevalent worldwide particularly in southern China. Assessing the effect of this abandonment on evapotranspiration (ET) and water resources is of major importance for regional water cycle change and agricultural water management. This study analyzed the ET characterization of rice‐winter rape and rice‐winter fallow rotation systems and its relation to weather factors in a humid lowland region, southern China based on a half‐hourly ET measurement with Bowen ratio energy balance system from 2017 to 2020. Then the strategic modeling experiment combining ET and rainfall‐runoff models was used to explore the land abandoning effect on ET and water resources. The results showed that the daily ET values of the rice, rape, and fallow seasons were 3.30 ± 1.89, 1.31 ± 1.31, and 1.55 ± 1.19 mm/d, respectively. The averaged summed ET values of the rice‐winter rape and rice‐fallow rotation systems were 652.3 and 737.8 mm, respectively. Net radiation (Rn) was identified as the most critical weather factor for ET of all seasons. Air temperature and water vapor pressure deficit mainly affected ET indirectly through the path of Rn. Compared with the previously winter rape, the change in daily ET caused by seasonal abandonment was 0.13 ± 0.11 mm/d. This abandonment‐induced ET change increased the average daily storage deficit by 12.0% and groundwater depth by 4.5%, while reduced the daily runoff by 20.3%. Plain Language Summary: Effect of seasonal cropland abandonment on ET and water resources in the humid lowland region. Key Points: The evapotranspiration (ET) of rice, rape, and fallow were compared using Bowen ratio energy balance observationThe modeling strategies with field experiment quantified the seasonal abandonment effectSeasonal abandonment increased ET and decreased surface water and groundwater resources relative to the previous winter rape [ABSTRACT FROM AUTHOR]

Understanding the formation and causes of cropland abandonment is crucial for developing effective strategies to mitigate this process. However, studies on cropland abandonment often look at one spatial scale, although the relationship between abandonment and evaluated factors may change depending on the specific scale, which limits our understanding of the process of cropland abandonment. Taking mountainous Southern Sichuan of China as an example, we utilized satellite-derived cropland abandonment maps to assess the evolving patterns of cropland abandonment from 2003 to 2018 across various scales. We then carried out a multi-scale (parcel, local and regional) assessment of the relationships between selected 17 variables representing natural, location and socioeconomic conditions and cropland abandonment. Results showed, the cropland abandonment rate increased from 2 % in 2003 to 15 % by 2018, and cropland abandonment always showed a higher concentration in the central part of the study area. At different scales, a combination of factors, which determined cropland abandonment, differed. We also found the distance to the nearest county center was scale-dependent factor and statistically significant factor of cropland abandonment only at the local scale. Among the factors with large contributions, topography mattered at all three scales; cropland per capita, aging and agricultural labor per unit of cropland mattered at the parcel and regional scales. Cropland fragmentation, air temperature and distance to the nearest settlement mattered at the local scale; the distance to the nearest water system, the distance to nearest county center and agricultural mechanization mattered at the regional scale. This multi-scale assessment framework embodied with multi-variable and multi-temporal could provide a new perspective to reveal the complex nonlinear relationship between the determinants and cropland abandonment, and further help to predict future cropland abandonment hotspots and identify relevant land-use policies. • The clustering of cropland abandonment was revealed across multiple scales. • Abandonment patterns at various scales were explained by various determinants. • The topography factor mattered at parcel, local and regional scales. • Observed a nonlinear relationship between the determinants and land abandonment. [ABSTRACT FROM AUTHOR]

By analyzing environmental and meteorological monitoring data over recent years of 2015–2022, the Twain-Hu Basin (THB) in central China was identified as a regional O 3 pollution center over China with the highest increasing trend at 1.10 %⸱yr−1 in interannual variations of O 3 concentrations with deteriorating O 3 pollution over recent years. We explored the spatiotemporal variations in O 3 pollution in the THB with ozone suppression (OS) under high air temperature over metropolitan, small urban, and mountainous areas. The bipolarized interannual trends in interannual O 3 variations in urban and mountainous areas over central China were characterized with the increasing and decreasing 90th percentiles of the daily maximum 8-h (MDA8-90) O 3 concentrations respectively in polluted urban areas and clean mountainous areas over recent eight years. The changes of the near-surface O 3 concentrations with air temperature exhibited the inflection points of OS from increasing to decreasing O 3 at air temperature of 30.5 °C in mountainous areas, 32.5 °C in small urban areas, and 34.5 °C in metropolitan areas, and the intensity of OS was estimated in the ranking with mountainous areas (−2.30 μg⸱m−3⸱°C−1) > small urban areas (−1.96 μg⸱m−3⸱°C−1) > metropolitan areas (−1.54 μg⸱m−3⸱°C−1), indicating that the OS was more significant over the lower-O 3 mountainous areas. This study has implications for understanding O 3 pollution variations with the meteorological drivers. An O 3 pollution center has developed over central China in recent years with the bipolarized O 3 change trends in urban () increase and mountainous () decrease, and the more significant ozone suppression with the low inflection point and high intensity in mountainous areas. [Display omitted] • The THB has become an O 3 pollution center over central China in recent years. • The bipolarized trends in interannual O 3 variations in urban and mountainous areas. • The ozone suppression was more significant in the lower-O 3 mountainous areas. [ABSTRACT FROM AUTHOR]

• The satellite-derived air temperature was utilized to characterize heat hazards. • Gridded population density was spatialized to describe human exposure. • A more stable weighting method that combines objective and subjective methods was used. A quantitative and comprehensive assessment method was proposed for heat health risk. • The dominant factors in high-risk areas were identified and analyzed. With frequent extreme heat events (EHEs), rapid urbanization, and uneven social development, comprehensive assessment of heat-related health risks is important for tolerating hot weather. This paper proposed a quantitative method for assessing heat-related health risks at the grid scale. A combination of multisource remote sensing and socio-economic data was utilized to develop an integrated heat health risk index (HRI) considering three dimensions of heat hazards, exposure, and vulnerability in the Yangtze River Delta (YRD), China. Compensating for the limitations of land surface temperature (LST) and station data, daily air temperatures were retrieved to calculate heat hazard index. Gridded population density data were developed using nighttime light data to calculate the exposure index. By combining them and other indicators, an HRI map of the YRD was developed. Furthermore, the spatial heterogeneity and dominant factors of the heat health risk were examined. The results showed that 13.2 % of the areas in the YRD were in high and medium high risk, while 58.6 % were in low and medium low risk. The high-risk areas were primarily concentrated in the Shanghai-Hangzhou Bay urban agglomeration, suggesting synergy between increased exposure and hazards in these metropolitan areas. The high-risk areas were predominantly dominated by hazard/exposure (H-E) and exposure/vulnerability (E-V), accounting for 27.2 % and 21.9 % of the YRD's total area respectively. This study contributes to the identification of areas vulnerable to heat stress and provides references for optimizing heat risk management strategies. [ABSTRACT FROM AUTHOR]

Farmland shelterbelts provide an ecological barrier to oases, but their growth is inhibited or even dies under water scarcity. Therefore, it is necessary to understand the response of farmland shelterbelts to environmental changes for their own survival in order to promote the long-term healthy development of agroforestry systems and improve water management in oases in the northwest arid region. In this study, we measured the sap flow and environmental factors to determine the transpiration dynamics and its influencing factors. The seasonal variations in water use strategy of Populus alba var. pyramidalis Bunge were identified by using stable isotopes of δ18O in xylem, soil water and groundwater coupled with the Iso-Source model. The results showed that the transpiration of the populus was significantly higher in the growing season (more than 80% of the total transpiration) than in the non-growing season, and the transpiration was closely related to air temperature, vapor pressure deficit, soil water content, and soil temperature. The water use strategy had seasonal variations. The populus obtained water predominantly from 0–40 cm soil water (approximately 75%) in the wet spring and then switched to deeper water sources (40–150 cm soil water and groundwater) as the season progressed. The contribution of deeper water sources increased to 84–92% in summer and autumn. This suggested that Populus alba var. pyramidalis Bunge has ecological plasticity, as it could explore deeper water sources as the water stress increased. The ability to switch rapidly among different water sources could put a plant at an advantage if competition for water occurs within the ecosystem. Our findings can provide insights into temporal transpiration dynamics as well as the strategy adopted by farmland shelterbelts to counteract the drought stress associated with the shallow soils in desert oasis ecosystems. [Display omitted] • The growing season's shelterbelt transpiration accounted for about 80% of total annual transpiration. • Transpiration in the desert oasis shelterbelt is more sensitive to deep soil water. • Shelterbelt water sources changed from 0–40 cm soil water to deeper sources as the season progressed. • The shelterbelt coped with variations in soil water availability through root plasticity. [ABSTRACT FROM AUTHOR]

The middle and lower reaches of the Yangtze River (MLRYR) exhibit notable interannual variability in seasonal-mean air temperature amid ongoing global warming. This study elucidates the specific mechanisms governing anomalous air temperatures during early (June) and late summer (July to August) in the MLRYR. Early summer temperatures arise from anomalous sinking driven by negative anomalies in moist enthalpy advection in the lower troposphere, as a response to warm sea surface temperature anomalies (SSTA) in the tropical western Pacific. This induces a low-level cyclone anomaly over Southeast Asia, reducing specific humidity and determining anomalous vertical motion over the MLRYR. In contrast, late summer temperatures are induced by mid-upper tropospheric descending anomalies over the MLRYR. The combined influence of SSTA in the western Pacific and North Atlantic sustains warmer air by reinforcing a barotropic anticyclone over North China through a mid-latitude wave train. Subsequent anomalous negative potential vorticity advection in the upper troposphere strengthens sinking motion over the MLRYR. The seasonal evolution of the East Asian summer monsoon and SSTA is pivotal in the distinct mechanisms governing warmer air temperatures over the MLRYR. While numerical experiments capture general features, the regulation of SSTA is subject to uncertainty due to the atmospheric intrinsic patterns. This research distinguishes predictability sources of air temperature anomalies over the MLRYR between early and late summer, emphasizing the combined influence of SSTA beyond the ENSO domain on East Asian climate. • Hotter summers in the MLRYR primarily come from the persistent higher temperature in situ. • The mechanisms for the MLRYR higher temperature are distinct between early and late summer. • SSTA outside the ENSO domain determines monthly evolution of summer air temperature anomalies over the MLRYR. [ABSTRACT FROM AUTHOR]

• Evaporative fraction increased by 16–49 % on cloudy days compared with clear days. • Clearness index controlled evaporative fraction through direct and indirect paths. • High NDVI reduced evaporative fraction response to cloudiness. Cloudiness influences gross primary productivity and evapotranspiration in terrestrial ecosystems by increasing diffuse radiation and improving the photosynthesis of shaded leaves. However, the effect of cloudiness on energy partitioning in terrestrial ecosystems is not well understood. Using latent heat (LE) and sensible heat (H) datasets observed by the eddy covariance systems and meteorological variables, the regulation of biophysical factors on energy partitioning under different sky conditions was investigated at 6 plantation ecosystems (2 deciduous broadleaf and 4 coniferous plantations) in eastern China from 2019 to 2021. The averages of evaporative fraction (EF) during the growing season were 0.34±0.06–0.50±0.04. The EF values increased by 16−49% on cloudy days, which was attributed to the lower decrease in LE compared to H. On the half-hourly scale, EF was mainly driven by air temperature (T a), relative extractable soil water (REW) and clearness index (CI) (i.e., a metric to quantify cloudiness). For plantation ecosystems, CI had an indirect effect on EF mainly through net radiation (R n). Moreover, the positive effect of cloudy sky conditions on EF was higher under low T a , vapor pressure deficit (VPD) and REW conditions. The increment of EF on cloudy days was weaker at high normalized difference vegetation index, which may be explained by higher T a and VPD limiting canopy transpiration during the mid-growing season. Cloudiness can also influence energy partitioning by regulating stomatal behavior in plantation ecosystems. These results contribute to understanding the drivers of energy partitioning in response to cloudiness in plantation ecosystems. [ABSTRACT FROM AUTHOR]

Anthropogenic heat (AH) emissions have rapidly increased in recent decades and are now critical for studying urban thermal environments; however, AH datasets composed of multiple heat sources with fine and accurate spatiotemporal characteristics at large scales are lacking. This study obtained annual, monthly, and hourly AH of multiple heat sources in China for 2019 at 500 m resolution. We first corrected the top-down inventory method for China, which is based on official energy consumption data. Then, we considered features such as the national building height, weighted factory density, and weighted road density to better represent the spatial characteristics of multi-source AH. Based on the above data preparation, a stacking framework was employed to integrate multiple machine-learning algorithms to construct an efficient and accurate AH estimation model. Finally, besides the comparative validation, the results were further tested by participating in a short-term climate numerical simulation for both winter and summer. The resulting data showed a reasonable AH composition and the total amount and composition of AH varied notably from region to region. The spatial and temporal characteristics of the AH from different sources differed greatly and were more detailed and accurate than those reported in previous studies. Air temperature simulations in winter were improved by the AH dataset input, but the uncertainties of climate simulations also limit its validity in AH validation. Because of its large spatial extent and detailed spatiotemporal characteristics, the new dataset strongly supports urban climate research and sustainable development. [Display omitted] [ABSTRACT FROM AUTHOR]

During 1998–2013, global surface air temperature increased more slowly than greenhouse gas concentrations, and therefore this period was defined as a "global warming hiatus." The characteristics of climate extremes in China during this period are still not clear. In this study, based on 2,841 meteorological station observations in China, the trends of precipitation and temperature extremes during the global warming hiatus were investigated relative to the reference period (RF) (1982–1997) and the whole historical period (HIS) (1982–2017). Machine learning was used to capture the nonlinear regression of climate extremes, and the Theil–Sen method with the Mann–Kendall significant test was used to calculate the slopes of their linear trends. During the global warming hiatus, annual and summer (JJA) warmest days TXx and the number of summer days SU over the whole of China and most of its four subregions were found to decrease relative to the HIS and RF periods. Annual and winter (DJF) coldest nights TNn over China and its four subregions were found to decrease moderately relative to the HIS and RF periods, whereas the number of frost days FD increased consistently. Precipitation extremes showed more temporal and spatial variability than temperature extremes. Trends of annual and JJA wet extremes during the hiatus were found to decrease relative to the HIS and RF periods, whereas the dry extreme index during the hiatus was found to increase generally over China and in most subregions. Lighter winds and lower relative humidity over most areas of China might have contributed to less pronounced trends of wet extremes during the hiatus period. [ABSTRACT FROM AUTHOR]

As a land–atmosphere coupling "hot spot", the northern China climate transition zone has a sharp spatial gradient of hydrothermal conditions, which plays an essential role in shaping the spatial and temporal pattern of evapotranspiration-precipitation coupling, but whose mechanisms still remain unclear. This study analyzes the spatial and temporal variation in land–atmosphere coupling strength (CS) in the climate transitional zone of northern China and its relationship with soil moisture and air temperature. Results show that CS gradually transitions from strong positive in the northwest to negative in the southeast and northeast corners. The spatial distribution of CS is closely related to climatic hydrothermal conditions, where soil moisture plays a more dominant role: CS increases first, and then decreases with increasing soil moisture, with the threshold of soil moisture at 0.2; CS gradually transitions from positive to negative at soil moisture between 0.25 and 0.35; CS shows an exponential decreasing trend with increasing temperature. In terms of temporal variation, CS is strongest in spring and weakens sequentially in summer, autumn, and winter, and has significant interdecadal fluctuations. The trend in CS shifts gradually from significantly negative in the west to a non-significant positive in the east. Soil moisture variability dominates the intra-annual variability of CS in the study regions, and determines the interannual variation of CS in arid and semi-arid areas. Moreover, the main reason for the positive and negative spatial differences in CS in the study area is the different driving regime of evapotranspiration (ET). ET is energy-limited in the southern part of the study area, leading to a positive correlation between ET and lifting condensation level (LCL), while in most of the northern part, ET is water-limited and is negatively correlated with LCL; LCL has a negative correlation with P across the study area, thus leading to a negative ET-P coupling in the south and a positive coupling in the north. [ABSTRACT FROM AUTHOR]

A physical retrieval approach based on the one-dimensional variational (1D-Var) algorithm is applied in this paper to simultaneously retrieve atmospheric temperature and humidity profiles under both clear-sky and partly cloudy conditions from FY-4A GIIRS (geostationary interferometric infrared sounder) observations. Radiosonde observations from upper-air stations in China and level-2 operational products from the Chinese National Satellite Meteorological Center (NSMC) during the periods from December 2019 to January 2020 (winter) and from July 2020 to August 2020 (summer) are used to validate the accuracies of the retrieved temperature and humidity profiles. Comparing the 1D-Var-retrieved profiles to radiosonde data, the accuracy of the temperature retrievals at each vertical level of the troposphere is characterized by a root mean square error (RMSE) within 2 K, except for at the bottom level of the atmosphere under clear conditions. The RMSE increases slightly for the higher atmospheric layers, owing to the lack of temperature sounding channels there. Under partly cloudy conditions, the temperature at each vertical level can be obtained, while the level-2 operational products obtain values only at altitudes above the cloud top. In addition, the accuracy of the retrieved temperature profiles is greatly improved compared with the accuracies of the operational products. For the humidity retrievals, the mean RMSEs in the troposphere in winter and summer are both within 2 g kg−1. Moreover, the retrievals performed better compared with the ERA5 reanalysis data between 800 hPa and 300 hPa both in summer and winter in terms of RMSE. [ABSTRACT FROM AUTHOR]

China's climate has been warming since the 1950s, with surface air temperature increasing at a rate higher than the global average. Changes in climate have exerted substantial impacts on water resources, agriculture, ecosystems and human health. Attributing past changes to causes provides a scientific foundation for national and international climate policies. Here, we review recent progress in attributing the observed climate changes over past decades in China. Anthropogenic forcings, dominated by greenhouse gas emissions, are the main drivers for observed increases in mean and extreme temperatures. Evidence of the effect of anthropogenic forcings on precipitation is emerging. Human influence has increased the probability of extreme heat events, and has likely changed the occurrence probabilities for some heavy precipitation events. The way a specific attribution question is posed and the conditions under which the question is addressed present persistent challenges for appropriately communicating attribution results to non-specialists. [ABSTRACT FROM AUTHOR]

Near-surface air temperature (Ta) is an important physical parameter that reflects climate change. Many methods are used to obtain the daily maximum (Tmax⁡), minimum (Tmin⁡), and average (Tavg) temperature, but are affected by multiple factors. To obtain daily Ta data (Tmax⁡ , Tmin⁡ , and Tavg) with high spatio-temporal resolution in China, we fully analyzed the advantages and disadvantages of various existing data. Different Ta reconstruction models were constructed for different weather conditions, and the data accuracy was improved by building correction equations for different regions. Finally, a dataset of daily temperature (Tmax⁡ , Tmin⁡ , and Tavg) in China from 1979 to 2018 was obtained with a spatial resolution of 0.1 ∘. For Tmax⁡ , validation using in situ data shows that the root mean square error (RMSE) ranges from 0.86 to 1.78 ∘ , the mean absolute error (MAE) varies from 0.63 to 1.40 ∘ , and the Pearson coefficient (R2) ranges from 0.96 to 0.99. For Tmin⁡ , the RMSE ranges from 0.78 to 2.09 ∘ , the MAE varies from 0.58 to 1.61 ∘ , and the R2 ranges from 0.95 to 0.99. For Tavg , the RMSE ranges from 0.35 to 1.00 ∘ , the MAE varies from 0.27 to 0.68 ∘ , and the R2 ranges from 0.99 to 1.00. Furthermore, various evaluation indicators were used to analyze the temporal and spatial variation trends of Ta , and the Tavg increase was more than 0.03 ∘ C yr -1 , which is consistent with the general global warming trend. In summary, this dataset has high spatial resolution and high accuracy, which compensates for the temperature values (Tmax⁡ , Tmin⁡ , and Tavg) previously missing at high spatial resolution and provides key parameters for the study of climate change, especially high-temperature drought and low-temperature chilling damage. The dataset is publicly available at 10.5281/zenodo.5502275 (Fang et al., 2021a). [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]

Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high-spatial-resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. Firstly, the observed environmental parameters, e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF), around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 ∘ C. Then, the spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the decreasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high spatial and temporal resolution (30 m and 1 h) CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments. [ABSTRACT FROM AUTHOR]

Soil temperature (ST) is one of the key variables in land–atmosphere interactions. The response of ST to atmospheric changes and subsequent influence of ST on atmosphere can be recognized as the processes of signals propagation. Understanding the storing and releasing of atmospheric signals in ST favors the improvement of climate prediction and weather forecast. However, the current understanding of the lagging response of ST to atmospheric changes is very insufficient. The analysis based on observation shows that both the storage of air temperature signals in deep ST even after 4 months and the storage of precipitation signals in shallow ST after 1 month are widespread phenomena in China. Air temperature signals at 2 m can propagate to the soil depths of 160 and 320 cm after 1 and 2 months, respectively. The storages of antecedent air temperature and precipitation signals in ST are slightly weaker and stronger during April–September, respectively, which is related to more precipitation during growing season. The precipitation signals in ST rapidly weaken after 2 months. Moreover, the effects of accumulated precipitation and air temperature on the signal storage in ST have significant monthly variations and vary linearly with soil depth and latitude. The storage of antecedent air temperature or precipitation signals in ST exhibits an obvious decadal variation with a period of more than 50 years, and it may result from the modulation of the global climate patterns which largely affect local air temperature and precipitation. [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 contradiction between the shortage of urban land and the demand for urban green space needs to be solved reasonably. Different from urban parks, the cooling effect of small green space (SGs) has not been paid enough attention or fully evaluated. The major objective of this research was to explore the cooling and energy saving benefits of SGs with administrative units. The ENVI-met and EnergyPlus models were built based on field measurements on the green space of Xi'an Jiaotong University Qujiang Campus. Field measurement shows that the closer an area to the green space, the lower the air temperature and the higher the relative humidity, especially in the daytime. The ENVI-met results showed that the SGs can reduce the temperature by 0.66 °C within the range of 1260 m × 1350 m compared with the building scene at noon, the EnergyPlus simulation results showed that the building 100 m away from the SGs can reduce the air conditioning energy consumption by 2.1% compared with the distance of 150 m. The research can improve the planning and design standards of urban green space, clarify the cooling and energy saving benefits of SGs, and promote the ecological urban design. [ABSTRACT FROM AUTHOR]

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The daily highest air temperature (Tmax) is a key parameter for global and regional high temperature analysis, which is very difficult to be obtained in areas where there are no meteorological observation stations. This study proposes an estimation framework for obtaining high-precision Tmax. Firstly, we build a near surface air temperature diurnal variation model to estimate Tmax for China from 1979 to 2018 based on multi- source data. Then in order to further improve the estimation accuracy, we divided China into six regions according to climate conditions and topography, and established calibration models for different region. The analysis shows that the mean absolute error (MAE) of the dataset ( https://doi.org/10.5281/zenodo.5602897) is about 1.07 °C and RMSE is 1.52 °C, which improves the accuracy of the traditional method by nearly 1 °C. The spatial-temporal variations analysis of Tmax in China indicated that the annual and seasonal mean Tmax in most areas of China showed an increasing trend. In summer and autumn, the Tmax in northeast China increased the fastest among the six regions, which were 0.4 °C/10a and 0.39 °C/10a, respectively. The number of summer days and warm days showed an increasing trend in all regions, while the number of icing days and cold days showed a decreasing trend. The abnormal temperature changes mainly occurred in El Niño years or La Niña years. We found that the influence of the Indian Ocean Basin Warming (IOBW) on air temperature in China were generally greater than those of the North Atlantic Oscillation and the NINO3.4 area sea surface temperature after making analysis of ocean climate modal indices with air temperature. In general, this Tmax dataset and analysis are of great significance to the study of climate change in China, especially for environmental protection. [ABSTRACT FROM AUTHOR]

The anticyclonic anomaly over the Ural Mountains, or the Ural high (UH), has recently received much attention as a factor related to weather anomalies across Eurasia. Here we studied how the UH affects the occurrence of cold wintertime episodes over eastern Europe and northern China. By employing three methods to identify the UH, we found that a method based on the sea level pressure anomaly captures a stronger cooling signal over eastern Europe and this method includes nonblocking cases associated with low-level anticyclones that do not affect the upper troposphere. However, with UH occurrence, a stronger cooling over northern China is detected by a method based on 500-hPa geopotential height fields. Cold events over eastern Europe typically occur when UH formation is associated with a Rossby wave breaking in the upper level. Our results show that the horizontal temperature advection plays an important role in formation of cold episodes in both eastern Europe and northern China. The advection is balanced by diabatic processes, which show an opposite sign to the temperature advection in both regions. Also adiabatic warming contributes to balancing the advection in northern China. We find that the exact location of the positive SLP anomaly during UH episodes is the most important factor controlling whether or not eastern Europe or northern China will experience a cold episode. If the positive SLP anomaly develops more northwest than usual, eastern Europe will experience a cold episode. When the anomaly moves eastward, northern China will be cold. [ABSTRACT FROM AUTHOR]

A theoretical model was proposed to implement the heat transfer, moisture content, and momentum in the cylinder-shaped silos, where rice was stored. A yellowing model of rice was also developed, according to the kinetics of color change. A field experiment was then carried out to evaluate the present model. A systematic investigation was then made on the temporal and spatial distribution of temperature, moisture content, and yellowness of stored rice within the concrete silo in the Nanchang area of China during storage without and with mechanical ventilation in the whole year. The simulation results show that the temperature of bulk rice near the inner wall of the silo had fluctuated with the local atmospheric temperature, and the mean temperature of bulk rice in the silo was rising during sealed storage without mechanical ventilation. Since the grain was a very good insulator, the center of the silo stayed much warmer with the longer storage. The temperature of bulk rice was more than 35.0℃ in the most area of the silo, due to the heat transfer between the silo with the local atmosphere and the exothermic heat of the grain respiration in the silo, where the rice was very easy to turn yellow during the sealed storage without mechanical ventilation. Moisture migration also occurred in the rice storage silo, resulting from some differences in grain under air temperatures. The cold air on the outside of the bin (cold air was much heavier) pushed the warm air into the center of the silo in autumn, where the warm air moved upward and eventually encountered the cool air at the top. The currents of natural convection were formed by the displacement of hot air by the dense cold air. The moisture content of grain bulk migrated to the vicinity of the grain surface by the natural air currents, resulting in the condensation and crusting in the surface of the bulk grain. The opposite process was found in spring and summer, particularly with the condensation and spoilage at the bottom of the bin. Therefore, mechanical ventilation was used to alternately alleviate the natural air currents and the moisture migration for the sealed storage. In this case, the higher temperature area of the grain bulk was observed near the south wall, and the grain surface on the south side, due to the solar radiation, where the rice was relatively yellowish. The internal temperature of grain bulk dropped significantly during ventilation, particularly after a period of sealed storage. The yellowness of rice was relatively lower than before for the sealed storage during ventilation over the whole year, indicating that the temperature posed a predominant effect on the color change. Meanwhile, the ventilation can widely be expected to balance the temperature differences in the bulk rice, the natural current, and moisture migration during storage. The findings can also provide a strong reference and theoretical basis for grain storage. [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]

The two leading modes of winter surface air temperature (SAT) over China during 1961–2017 are a spatially consistent pattern and a north-south dipole pattern. Based on the two leading modes, the characteristics of the extreme cold and warm days in the two patterns, defined by the standard deviation larger than 1.28 or smaller than −1.28 in the time series of the two leading modes, are analyzed. With the increase of winter SAT during 1961–2017, the number of spatially consistent extreme cold days decreased and their occurrence was restricted to late December to early January, whereas the number of spatially consistent extreme warm days increased significantly in January and February. Global warming is associated with an increase in the spatially consistent extreme warm days and a decrease in spatially consistent extreme cold days, but has little relation to the sum of extreme cold and warm days of either the spatially consistent or north-south dipole pattern. The Siberian High (SH) is the main factor controlling the sum of spatially consistent extreme warm and cold days. The strong (weak) SH before (after) the 1990s corresponds to an increase (decrease) in the sum of the spatially consistent extreme warm and cold days. The occurrences of extreme south-cold-north-warm and extreme south-warm-north-cold days are related to the north-south difference of the SH. When the center of the SH is in mid-high latitudes, the extreme south-warm-north-cold (south-cold-north-warm) days occur more (less) often. During the winters of 1961–2017, the total number of extreme cold and warm days of the north-south dipole pattern changes negligibly. The North Atlantic meridional overturning circulation (AMOC) may be the main factor affecting the sum of the extreme cold and warm days of the two types of SAT pattern in China. [ABSTRACT FROM AUTHOR]

The deep blue sky is an indicator of a lower concentration of aerosols and a cloudless sky. With increasing human emissions, a trend towards days with fewer deep blue skies might indicate a decline in a good living environment for humans. This study investigates the long-term changes of the deep blue sky in China from 1980 to 2018. Due to a lack of direct measurements, we use atmospheric visibility and low cloud cover to classify blue sky days into three grades: light blue day, medium blue day, and deep blue day. Climatologically, annual deep blue days increase from southeast China to northwest China, with the maximum number in Xinjiang and eastern Inner Mongolia and the minimum number in western Qinghai and southern Hebei. From 1980 to 2018, annual deep blue days show a prominent decreasing trend in most of China, with area-mean annual deep blue days decreasing by −0.48 days per year (d/y) in China, and the variation becomes more obvious after 2013. The maximum decreasing trend is observed in eastern China. The most prominent decreases of deep blue days are seen in winter. Both air pollution and the change in meteorological conditions contribute to the decrease of wintertime deep blue days in China. Specifically, the decrease in surface wind speed hinders the cleaning of air by winds, the increase in surface air temperature, and decrease in relative humidity is favorable for low cloud increase, and the increasing emission of pollution reduces atmospheric visibility. [ABSTRACT FROM AUTHOR]

Rainfall and snowfall have different effects on energy balance calculations and land–air interactions in terrestrial models. The identification of precipitation types is crucial to understand climate change dynamics and the utilization of water resources. However, information regarding precipitation types is not generally available. The precipitation obtained from meteorological stations across China recorded types only before 1979. This study parameterized precipitation types with air temperature, relative humidity, and atmospheric pressure from 1960 to 1979, and then identified precipitation types after 1980. Results show that the main type of precipitation in China was rainfall, and the average annual rainfall days (amounts) across China accounted for 83.08% (92.55%) of the total annual precipitation days (amounts). The average annual snowfall days (amounts) in the northwestern region accounted for 32.27% (19.31%) of the total annual precipitation days (amounts), which is considerably higher than the national average. The average annual number of rainfall and snowfall days both displayed a downward trend while the average annual amounts of these two precipitation types showed an upward trend, but without significance at 0.1 levels. The annual number of rainfall and snowfall days in the southwestern region decreased significantly (−2.27 and −0.31 day decade−1, p < 0.01). The annual rainfall amounts in the Jianghuai region increased significantly (40.70 mm decade−1, p < 0.01), and the areas with the most significant increase in snowfall amounts were the northwestern (3.64 mm decade−1, p < 0.01). These results can inform our understanding of the distribution and variation of precipitation with different types in China. [ABSTRACT FROM AUTHOR]

Quantifying the microclimate of a tall and complex tropical forest is quite challenging because of the difficulty in accessing the canopy. Traditional ground-referenced methods may underestimate the contribution of canopy heterogeneity to structuring the vertical profiles of forest microclimate. The present study examined how the reference height affects vertical variation of microclimate in a tropical rainforest in southwest China, based on both ground- and canopy-referenced approaches. The results show that the canopyreferenced approach yielded a higher model fit than did the ground-referenced method, and only canopy-referenced method could detect two thresholds in the leaf area index at approximately -22.6 ± 2.7 m and -36.6 ± 6.6 m below the canopy top; the higher threshold is consistent with thresholds of the annual mean temperature, the diurnal ranges of air temperature, and the relative humidity in the vertical profile; while the lower threshold is similar with the breakpoints of annual mean relative humidity, the annual ranges of air temperature and the relative humidity along the profile. The discontinuous variance in the microclimatic factors was due to the canopy structure in the vertical profile. Selecting the top of the canopy as the reference height could be a better approach for quantifying the microclimatic profiles in the studied forest, and this approach can improve our understanding of the effects of the vertical stratification of microclimates on species composition and diversity in this forest. [ABSTRACT FROM AUTHOR]

An unprecedented cold event occurred in Central and eastern Eurasia during the 2020/21 winter, including five episodes of consecutive cold spells (EP1–5). Through analysis of both observational and simulations, we show that the concurrent Arctic sea-ice loss and extratropical Pacific decadal oscillation (EPDO) warming are potential drivers for the cold event. Their relative contributions to the intraseasonal evolutions of atmospheric circulation and concomitant cold surges are thoroughly investigated. The circulation anomalies highlight the gradual development of the negative Arctic oscillation, accompanied by strengthened Siberian high and deepened Aleutian low. Stratospheric pathways were integrally involved in the dynamical response and the timing of episodes. Our results suggest that the sea-ice, irrespective of seasonality, and autumn EPDO experiments can generally capture the spatial patterns of atmospheric circulation and temperature in observation, albeit weaker in magnitude. Autumn (winter) sea-ice loss led to the EP1–3 (EP2–3) cold spells, and autumn EPDO led to the EP1–3 cold surges; whereas the EP4–5 cold spells induced by autumn SIC and PDO were not statistically robust. The Eurasian cooling response to winter PDO is weak due to the extensive warming over southern China and Eurasian highlatitudes that offsets the midlatitude cooling. The largest coolings were found in SIC and EPDO combined experiments, suggesting their synergic importance in driving such cold events. Our results have implications for the potential predictability of winter extreme events over Eurasia in the context of ongoing sea-ice decline and a recent shift to the positive PDO phase. [ABSTRACT FROM AUTHOR]

Global Positioning System (GPS) radio occultation measurements have been widely used to estimate global planetary boundary layer heights (H) using the minimum refractivity gradient method. This method is directly tested here using radiosonde data in China and is found to overestimate summer daytime H over land primarily in the presence of multi‐inversions in the lower troposphere. This deficiency is largely reduced by adding a constraint with lifting condensation level (LCL) in the derivation of H, particularly for LCL < 2 km (usually over humid regions). The primary reason is that our new method effectively avoids estimating H near the strong inversion corresponding to the minimum refractivity gradient in the free atmosphere. Applying our new method to the GPS radio occultation data, with LCL derived from surface automatic weather stations, yields more reasonable daytime variation and spatial distribution of H over land in China as compared to the ERA5 reanalysis and radiosonde data. Plain Language Summary: The radio signals from Global Positioning System (GPS) satellites have been widely used to estimate global planetary boundary layer heights (H) by computing the minimum refractivity variation with height. This method is directly tested here using radiosonde data in China and is found to overestimate summer daytime H over land primarily in the presence of multi‐inversions (where air temperature increases with height) in the lower troposphere. We use a new method to largely reduce this deficiency by combining the original method with lifting condensation level (LCL) in the derivation of H, particularly for LCL < 2 km (usually over humid regions). LCL is the level at which a parcel becomes saturated, representing a reasonable estimate of cloud base height. Our new method effectively avoids the misidentification of H near the top of deep clouds. We then apply our method to the GPS satellite data, with LCL derived from surface automatic weather stations. The new results show more reasonable daytime variation and spatial distribution of H over land in China as compared to the radiosonde observations and ERA5 reanalysis that makes consistent use of observational data from surface, aircraft, and satellite measurements. Key Points: Gradient method using Global Positioning System radio occultation data overestimates boundary layer height when multilocal minimum refractivity gradients existThis issue is addressed by combining the original method with lifting condensation level (LCL) in the derivation of boundary layer heightThe above deficiency for summer daytime boundary layer height is largely reduced over land for LCL < 2 km, usually over humid regions [ABSTRACT FROM AUTHOR]

Freezing level height (FLH) is the altitude of a location where the air temperature is 0°C. The FLH denotes the approximate position for water phase transitions from liquid (or vapour) to solid but not vapour to liquid. Based on temperature and height data on the ground surface to heights with an atmospheric pressure of 400 hPa, the monthly FLH at 118 radiosonde stations located in China are derived for the 1958–2017 period. The monthly and annual climatology during 1981–2010 and the seasonal, intra‐annual and decadal variabilities of the FLH during 1958–2017, along with its long‐term trends, were quantitatively evaluated at the regional scale and for individual stations. FLH climatology is generally related to season, zone and topography. The annual FLH anomalies decline initially, followed by a rise, with synchronous changes in the temperature in the lower and middle troposphere; the anomalies in south‐eastern China are partly associated with El Niño–Southern Oscillation events. The increasing trends of FLH are closely associated with tropospheric warming and show evident regional and seasonal differences. Stronger increasing trends are observed in northern and western China in autumn or winter (particularly in recent decades). The changes in FLH have implications on long‐term trends in equilibrium line altitude (ELA) of glaciers in Tianshan Mountains, snow cover extent in melt season and hail frequency in China especially in high‐elevations. During recent decades, the evolution of the FLH and major composition in the cryosphere has accelerated as a response to tropospheric warming. The study on FLH change can provide valuable information for the evaluation of glaciers, snow cover extent and hail frequency in China from a new perspective; which is helpful for understanding regional hydrological processes and climate changes better. Further application of FLH in cryosphere monitoring can improve water management and flood forecasting in headwater regions in China. [ABSTRACT FROM AUTHOR]

As an intrinsic feature of daily surface air temperature (SAT) variability found in station measurements, temporal asymmetry (TA) can be taken as an evaluation metric to access the quality of SAT re-analysis product. In this study, TA calculated from four SAT variables, i.e., daily mean SAT (Tmean), daily maximum SAT (Tmax), daily minimum SAT (Tmin) and diurnal temperature range (TDTR = Tmax − Tmin), is applied to evaluate synoptic-scale performance of four reanalysis products (NCEP-2, JRA-55, ERA-I, and ERA-5) over China. The results show that four re-analyses overall overestimate the TA of daily Tmax and Tmin variability over China, but with a comparatively consistent estimated TA for Tmean. Moreover, the TA of Tmean variability for these four re-analyses shares high spatial consistency with those from the observation. However, four re-analyses own the similar region-dependent spatial patterns of overestimated TA for Tmax and Tmin variability, especially for Tmax. Since high TA is an indicator for strong nonlinear feature, only Tmean reanalysis is the most suitable to explore synoptic-scale extreme events, such as heat waves and cold waves, which are highly related to the strong nonlinear processes. [ABSTRACT FROM AUTHOR]

Here we investigate the key features of early and late South China Sea summer monsoon (SCSSM) onset. To carry out the investigation, we select five extreme early and nine extreme late onset years (14 days or more, before and after the normal onset date are considered "late" and "early" onset years, respectively). Since the mean SCSSM onset occurs in May, we analyze the changes in composite mean meteorological fields during May. Next, we examine the differences in daily evolution (from 10 to 2 days before the onset) of various vital variables between the early and late SCSSM onset years. We demonstrate that during the early SCSSM onset years, surface air temperature (SAT) is warmer over the North Pacific Ocean, South China Sea (SCS), and Northern China, which gradually extend towards East Asia. These SAT anomalies over Northern China, East Asia, and SCS are due to the advection of warm anomalies from the North Pacific Ocean. Consequently, a dipole-like sea level pressure (SLP) pattern had developed, with lower SLP over East Asia, Northern China, SCS, and North Pacific Ocean, and higher SLP over the Indian Ocean. It subsequently brought moisture-laden wind from the Indian Ocean towards SCS and East Asian landmass and is responsible for early SCSSM onset. [ABSTRACT FROM AUTHOR]

Long-term continuous monitoring of precipitation isotopes has great potential to advance our understanding of hydrometeorological processes that determine stable isotope variability in the monsoon regions. This study presents 4-yr daily precipitation isotopes from Yungui Plateau in southwestern China that are influenced by Indian summer monsoon and East Asian monsoon. The local meteoric water line (LMWL; δ2H = 8.12δ18O + 11.2) was first established at the Tengchong (TC) site, which was close to the global meteoric water line (GMWL; δ2H = 8δ18O + 10), indicating little secondary subcloud evaporation in the falling rain. Precipitation δ18O values exhibited significant inverse relationships with precipitation amount (r = −0.42), air temperature (r = −0.43), and relative humidity (r = −0.41) with lower correlation coefficients throughout the entire period, which indicated that precipitation isotopic variability in TC could not be well explained by the local meteorological factors but influenced by other combined factors of regional precipitation amount and upstream rainout. Precipitation δ18O values showed a clear V-shaped trend throughout the observation period, characterized by higher δ18O values during the premonsoon period whereas lower values during the postmonsoon period. This seasonal variation of precipitation δ18O values was associated with the seasonal movement of the intertropical convergence zone and seasonal changes in moisture transport. Combined with backward trajectory analysis, precipitation δ18O values were estimated by a Rayleigh distillation model showing that upstream rainout processes from the Bay of Bengal (BoB) toward land (Myanmar) and recycling moisture over land were key factors affecting the isotopic compositions of the TC precipitation. These findings could enhance our understanding of atmospheric dynamics and moisture source in the monsoon regions and will potentially facilitate the interpretation of numerous isotopic proxy records from this region. SIGNIFICANCE STATEMENT: The variability of the summer monsoon and its onset, duration, and failure directly determine the strong rainfall and drought in a given region and have great impacts on regional societies and agriculture. To better understand this variability, this study presented a 4-yr daily dataset of precipitation isotopes on the Yungui Plateau of southwestern China to explore atmospheric processes and moisture sources that drive isotopic variability in this region. Precipitation δ18O exhibited remarkably seasonal variability, with higher values in premonsoon period and lower values in the postmonsoon period. During the Indian summer monsoon period, moisture sources primarily originated from the BoB toward the TC site, experiencing rainout processes and local moisture recycling over land using a Rayleigh fractionation model. These findings shed new light on the temporal variations of precipitation stable isotopes and facilitate our understanding of hydrological cycle in the monsoon regions. [ABSTRACT FROM AUTHOR]

GLDAS2.0 provides long‐term fine resolution gridded hydrometeorological data sets, which are necessary for water‐related studies, particularly in some transboundary rivers that are partially without observation. Yet, GLDAS2.0 has only been validated at limited locations, and few studies have been conducted to develop approaches to correct the GLDAS2.0 data for transboundary rivers. This work assessed the GLDAS2.0 data and developed approaches to correct their uncertainties for studies in large transboundary rivers in the Tibetan Plateau and Northeast China (NC). To achieve these goals, observational data from 1982 to 2010 and a water and energy budget‐based distributed hydrological model including biosphere after calibration and validation were employed. We find that the GLDAS2.0 data (except for wind speed) can reasonably replicate observed seasonal variations. However, its specific humidity and wind speed have large uncertainty, and precipitation has large uncertainty in summer. In NC, the trends of its precipitation, air temperature, downward longwave radiation, and wind speed are consistent with the observations. In the Yarlung Tsangpo, Lancang, and Nu Rivers, the trends of all GLDAS2.0 data reproduce the observation very well, that is, wetting, warming, and dimming trends. Validations show that the corrections are effective and the corrected forcing data can be successfully used in hydrological simulation with improved performance than the raw GLDAS2.0 data, which demonstrates the usefulness of the methodology and corrected forcing data to hydrometeorological studies in transboundary rivers in China as well as in other nearby regions/countries. Plain Language Summary: GLDAS2.0 provides long‐term hydrometeorological data sets, which are necessary for water‐related studies, particularly in some transboundary rivers that are partially without observation. This work assessed GLDAS2.0 data and developed approaches to correct their uncertainties for studies in large transboundary rivers in the Tibetan Plateau (TP) and Northeast China (NC). In NC, the trends of GLDAS2.0 precipitation, air temperature, downward longwave radiation, and wind speed are consistent with observations. In TP, the trends of all the GLDAS2.0 data reproduce observation very well. Validations show that the corrections are effective and the corrected data have improved performance than raw GLDAS2.0 data in hydrological simulation. Key Points: Specific humidity and wind speed have large uncertainty, and precipitation has large uncertainty in summerTrends of precipitation, air temperature, downward longwave radiation, and wind speed are consistent with observationEquations are developed to reduce forcing data uncertainty, and validations show that the equations are effective [ABSTRACT FROM AUTHOR]

An accurate spatially continuous air temperature dataset is crucial for multiple applications in environmental and ecological sciences. Existing spatial interpolation methods have relatively low accuracy and the resolution of available long-term gridded products of air temperature for China is coarse. Point observations from meteorological stations can provide long-term air temperature data series but cannot represent spatially continuous information. Here, we devised a method for spatial interpolation of air temperature data from meteorological stations based on powerful machine learning tools. First, to determine the optimal method for interpolation of air temperature data, we employed three machine learning models: random forest, support vector machine, and Gaussian process regression. Comparison of the mean absolute error, root mean square error, coefficient of determination, and residuals revealed that Gaussian process regression had high accuracy and clearly outperformed the other two models regarding interpolation of monthly maximum, minimum, and mean air temperatures. The machine learning methods were compared with three traditional methods used frequently for spatial interpolation: inverse distance weighting, ordinary kriging, and ANUSPLIN. Results showed that the Gaussian process regression model had higher accuracy and greater robustness than the traditional methods regarding interpolation of monthly maximum, minimum, and mean air temperatures in each month. Comparison with the TerraClimate, FLDAS, and ERA5 datasets revealed that the accuracy of the temperature data generated using the Gaussian process regression model was higher. Finally, using the Gaussian process regression method, we produced a long-term (January 1951 to December 2020) gridded monthly air temperature dataset with 1 km resolution and high accuracy for China, which we named GPRChinaTemp1km. The dataset consists of three variables: monthly mean air temperature, monthly maximum air temperature, and monthly minimum air temperature. The obtained GPRChinaTemp1km data were used to analyse the spatiotemporal variations of air temperature using Theil-Sen median trend analysis in combination with the Mann-Kendall test. It was found that the monthly mean and minimum air temperatures across China were characterized by a significant trend of increase in each month, whereas monthly maximum air temperature showed a more spatially heterogeneous pattern with significant increase, non-significant increase, and non-significant decrease. The GPRChinaTemp1km dataset is publicly available at https://doi.org/10.5281/zenodo.5112122 (He et al., 2021a) for monthly maximum air temperature, at https://doi.org/10.5281/zenodo.5111989 (He et al., 2021b) for monthly mean air temperature and at https://doi.org/10.5281/zenodo.5112232 (He et al., 2021c) for monthly minimum air temperature. [ABSTRACT FROM AUTHOR]

Uneven and sparse surface air temperature (Ta) observations challenge the understanding of the atmosphere‐land interactions and global environmental changes. Lapse rate (γ) is thought of with great potential to obtain accurate long‐term and high‐resolution Ta dataset. However, previous studies on γ over China were solely based on observed data, which limited our understanding since few stations are distributed in western China. In this study, an improved procedure for estimating γ by combining sparse observations and newly released ERA5 reanalysis data was proposed. The spatial heterogeneity in γ over China and its influencing factors (e.g., topography, climate, and vegetation) were then explored. A re‐examination of long‐term spatiotemporal variations in γ and its potential driving forces over China was also performed at grid scales. The results demonstrated that our γ estimations reproduced similar patterns to those derived from observations. The subsequent analyses revealed that the annual and seasonal variability in γ varied substantially among different altitude gradients, land cover types, and climate zones. The vital role played by vegetation covers in regulating local γ was emphasized in this study, which was poorly assessed previously. Moreover, γ in low altitude zones showed lower values but strong temporal fluctuations and contributed more to the interannual variability in γ over China, which could be mainly attributed to human activities. The present findings can provide an alternative method for estimating γ and be further used to assess regional or global temperature changes. [ABSTRACT FROM AUTHOR]

Based on the daily maximum air temperature (Tmax) data from the China Meteorological Data Network and the NCEP/DOE reanalysis data, the intra-seasonal circulation and evolution of an extreme high temperature event (EHTE) in the middle reaches of the Yangtze River (MYR) from August 9-21, 2011 were explored, as well as the influence of diabatic heating on the position variation of the Western Pacific subtropical high (WPSH). Results show that the daily Tmax in the MYR exhibits a vigorous intraseasonal oscillation (ISO) of 10-25 days in the extended summer of 1980-2018. The main factors affecting the EHTE in the summer of 2011 are the low-frequency wave train propagating southeastward in the mid-latitude of the upper troposphere and the low-frequency anticyclone moving northwestward in the lowlatitude of the mid-lower troposphere. The diagnosis of 925hPa thermodynamic equation indicates that the ISO features of the Tmax in the core region is determined by the intra-seasonal variation of the adiabatic variation. In addition, the variations of the WPSH correspond well to the distribution of apparent heat source. In the early stage of the high temperature process, the apparent heat source in the north of the Bay of Bengal is a certain indicator for the westward extension of the WPSH. [ABSTRACT FROM AUTHOR]