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We estimate the relationship between high‐temperature exposure and land transaction using daily transaction data from 2013 to 2018 in China. Standard hedonic price method is used to perform multidimensional fixed effects regression on 458,564 transaction samples. This study shows that each additional day of the extremely high temperature increases the average bid price by 0.6%, which is equivalent to an additional annual increase of 15.018 billion yuan in land transaction costs. The effect of high temperature on land prices is considerably stronger for residential and commercial lands. We further find that high‐temperature‐induced changes of mood and cognition play a role. Extreme gradient boosting (XGBoost) algorithm is used to calculate price deviation, which overcome missing eigenvalues and reduce nonlinear measurement error. Our findings indicate that heat can make investors more aggressive, which occurs when bidders continue to raise prices to win. The number of bidding behavior will not drop due to the hidden costs of land transactions. Specially, bidding experience offsets the cognitive output bias. This study contributes to the behavioral finance and decision‐making literature, helps investors make better investment management decisions, and alleviates the negative effect of land transaction premium on the real estate market. Plain Language Summary: Extreme temperatures are becoming more frequent due to climate change. Extreme temperature can affect people's cognitive performance. Using large‐scale land transaction data and a fixed‐effects model, this paper analyzes the impact of extreme temperature on decision‐making. Results show that each additional day of extremely high temperature increases the average bid price by 0.6%, which is equivalent to an additional annual increase of 15.018 billion yuan in land transaction costs. This paper analyzes the impact of extreme temperature on human cognitive performance from the perspective of e climate change and uses land transaction behavior as a measure of decision‐making to reveal the mechanism of climate change affecting cognitive performance. Key Points: Each additional day of the extremely high temperature increases the average bid price by 0.6%Heat can make investors more aggressive, which occurs when bidders continue to raise prices to winBidding experience offsets the cognitive output bias [ABSTRACT FROM AUTHOR]

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

This paper investigates the impact of Chinese firms' environmental, social, and governance (ESG) performance on their financial constraint and financing activities. We find a negative association between firms' ESG performance and their financial constraint driven by the Chinese government's commitment to tackling climate change. Compared with state‐owned enterprises (SOEs), non‐SOEs have alleviated their financial constraint through both equity and debt issuance, thanks to the stock price appreciation and green credit. High‐pollution firms benefit from both equity and debt issuance, while low‐pollution firms mainly finance through equity issuance. Our findings demonstrate the leading role of the Chinese government in its domestic capital markets. [ABSTRACT FROM AUTHOR]

An analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Plain Language Summary: China is a vulnerable country to climate change due to its dense population, unbalanced social and economic development, shortage of water resources, and fragile ecosystems. How future precipitation will change over the region is of great concern for the general public and decision makers. This paper presents a first analysis of precipitation simulations from a set of five RCM (RegCM4) 21st century climate change projections, driven by coarse resolution general circulation models (GCMs) over China. We find that the spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by a precipitation underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in north China by both the GCMs and RegCM4 in all seasons except summer, when, weak correlations of the projected change patterns are found between the GCMs and nested RegCM4, indicating the greater role of the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Key Points: The spatial patterns of bias show common features between the GCMs and RegCM4RegCM4 provides greater spatial detail of present day precipitation simulation compared to the GCMs and finer structures of future changesThe change patterns across the RegCM4 projections show a high correlation, but not always between each pair of driving GCM and RegCM4 [ABSTRACT FROM AUTHOR]

Quantifying the carbon budget in rice paddy ecosystems is fundamental to understanding the role of paddy fields as carbon sinks or sources and to mitigating global climate change. This study used a process‐based model of the denitrification‐decomposition (DNDC) model to estimate greenhouse gas (GHG) emissions and carbon sinks in the paddy ecosystem across China. The simulation results showed that the GHG emissions were 0.147 Pg C‐equivalent year−1 and that the carbon sequestration in rice plants and soils reached 0.253 Pg C year−1 in 2016, indicating high carbon sequestration potential of the Chinese paddy ecosystem. Land management had a great influence on carbon budgets, among which straw residue incorporation rate and nitrogen fertilizer applications had a stronger influence on carbon budgets, particularly for double cropping rice. These results indicate that appropriate tillage practices can reduce GHG emissions and increase carbon sequestration of rice ecosystems while ensuring rice yields. [ABSTRACT FROM AUTHOR]

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere‐based and land‐based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in‐situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC) and DOC concentrations (CDOC) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC, as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual‐scale estimates and large rivers. Results show that over the period 2001–2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2, p =.01), but little change in CDOC (−0.001 mg/L/year, p >.10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p <.05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (−0.043 and −0.014 mg/L/year, p =.01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio‐temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC, the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate. [ABSTRACT FROM AUTHOR]

Understanding future dry and wet changes under global climate change is of great regional significance in China. Based on six Global Climate Models (GCM) from the Coupled Model Intercomparison Project phase 6 (CMIP6), we project the changes of dry‐wet climate regions in China in the 21st century under the three SSP‐RCP (shared socioeconomic pathway‐representative concentration pathway) scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), and further identify the key climatic factors that lead to the transition of dry‐wet climate regions. The results show the area of humid and subhumid regions in China will show an upward trend in the future, while the area of semiarid and arid regions will show a downward trend. Especially under the SSP5‐8.5 scenario, the area of the subhumid region has the largest increase trend (0.042% per year), and the area of the arid region has the largest decline trend (−0.048% per year). The three main transfer directions of dry‐wet climate regions are from arid to semiarid regions, from semiarid to subhumid regions, and from subhumid to humid regions in the future. Due to the future extensive wetting trend in the north, the future dry‐wet climate regions will shift to wetter types in Tibet, North China, the Qinling‐Huaihe regions and the northeast. In addition, the key climatic factors for the transition of dry‐wet climate regions are mainly precipitation, maximum temperature and solar radiation. The increase of precipitation plays a dominant role for areas projected to change to wetter types, and the increase of potential evapotranspiration (PET) plays a dominant role for areas projected to change to drier types. The PET changes in changed areas of dry‐wet climate regions are mainly dominated by maximum temperature and solar radiation. Our research has important implications for future water resource management and reconsideration of climate mitigation and adaptation policies. [ABSTRACT FROM AUTHOR]

Consecutive extreme wet days (CEWDs) typically affect the likelihood of flooding and landslides and have negative effects on both natural and artificial ecosystems; however, the spatiotemporal changes in their features are still unclear at the national scale. Investigating changes in the frequency and intensity of such events is essential for climate risk management. Here, this study thoroughly analysed CEWD features in China from 1980 to 2020 using the daily observation dataset. We also evaluated and compared the ability of two widely used precipitation products, the European Centre for Medium‐Range Weather Forecasts Reanalysis 5th Generation (ERA5) and the Multi‐Source Weighted‐Ensemble Precipitation version 2 (MSWEP), to detect CEWD features. According to the observation data, the frequency and intensity of CEWD events are related to local climate and present "high eastern and low western" spatial patterns across China. Since 1980, more than half of China's mainland has experienced increases in both the frequency and intensity of CEWDs. Some stations detected decreasing trends in CEWD frequency and amounts, which are primarily located in the eastern coastal regions and southwest of warm temperate humid/subhumid regions. The ERA5 precipitation product generally outperforms MSWEP data in detecting CEWD events, and the latter significantly underestimates the annual frequency and amounts of CEWDs. These findings provide basic and valuable information regarding CEWD features across China and where such studies can be conducted based on precipitation datasets. Furthermore, these findings will also aid policymakers in managing extreme precipitation‐related natural hazards. [ABSTRACT FROM AUTHOR]

Various climatic factors and their interactions affect China's snow depth alterations. However, a measure of the relative importance of climatic factors regarding the variance in snow depth is lacking. Here, we use a heretofore largest dataset, quality‐controlled daily observations from 1,665 meteorological stations, and statistical analyses to identify proxy drivers and their contributions regarding regional variability and trends in China's snow depth and snow depth‐climate relationships from 1951 to 2019. Results show that seasonal snow depth alterations are substantial in China and caused by various climatic drivers. In winter, observed positive trends in the northwest and northeast of China mainly respond to augmentation in solid precipitation and snow accumulation in fall. For the Tibetan Plateau, the negative snow depth anomaly seems to respond to the rising air temperature below the freezing point along with some secular changes in solid precipitation and shallower fall snowpacks. All these trends in winter snow depth over the northwest, northeast, and Tibetan Plateau of China account approximately for 30% of the total interannual variance in spring snow depth in these regions. In the milder central north and south of China, snow accumulation is not evident. Besides solid precipitation and rising air temperature below the freezing point, atmospheric humidity is also notable for its effect on the interannual variance in winter snow depth in these regions. In spring and fall, however, the negative effect of warming climate on snow depth becomes remarkably more important. It seems that about 13–33% (12–50%) of the total interannual variance in the widespread decrease (insignificant perturbation), except for some weak increases in the northeast region (decreases in the Tibetan Plateau), of China's spring (fall) snow depth are caused by the rising air temperature below the freezing point. [ABSTRACT FROM AUTHOR]

The energy sector matters the sustainable development directly and is sensitive to climate change. A few empirical studies concentrate on how climate change influences firm performance. Climate change brings higher production costs and lower efficiency on the supply side and leads to beneficial sale performance and improves profit. However, it is ambiguous to the relationship of supply–demand and revenue‐cost levels, and their change is not consistent. Using panel data of 99 China‐listed firms active in the energy sector over the period 2000–2020, this study aims to identify the causal relation between climate change and the profitability of energy firms while controlling for firm‐specific and energy market‐related factors. The quantile regression results show that temperature deviation (TDEV) positively impacts the profitability of energy firms, and this impact varies at different quantiles of the profitability distribution. These findings remain unchanged by four robustness checks. Moreover, mechanism results indicate that revenue and cost have different interaction effects on the causal relation. The findings of this study can provide forward‐thinking expectations and assess climatic adaptation and risks, particularly inspired stakeholder engagements. [ABSTRACT FROM AUTHOR]

Climate warming is steadily increasing drought risk in many regions of the world. However, the contribution of warming over the past few decades to drought evolution in China remains unclear. This study used the self‐calibrating Palmer drought severity index (sc‐PDSI) and a detrending experiment to quantify the contribution of warming to severe drought (sc‐PDSI < −3.0) characteristics (intensity, frequency, and duration) over China from 1980 to 2019. Differences in drought characteristics calculated from original and detrended temperature data were attributed to warming effects. The results showed that 93.8% of areas in China have experienced a significant (p <.05) warming trend from 1980 to 2019. Warming remarkably intensified severe drought characteristics across China. Without warming, the extent, frequency, and duration of severe droughts in China would reduce by 2.04%, 2.0%, and 0.82 months. In addition, there are apparent regional differences in the response of severe drought characteristics to warming. Severe drought characteristics in high elevations and high latitudes are more sensitive to warming than in other regions. [ABSTRACT FROM AUTHOR]

China's surface air temperature is increasing due to global warming, so it is interesting that how low temperatures would be changed during the growth period of winter wheat in future. We focused on the low temperatures of winter wheat from 2021 to 2050, using temperatures under the high emission scenario Representative Concentration Pathway 8.5 (RCP8.5) projected by the RegCM4.4 regional climate model. The results showed that the annual mean temperature was projected to increase by 0.42°C⋅decade−1 in the northern and by 0.35°C⋅decade−1 in the southern winter wheat region. Furthermore, the temperature was expected to increase rapidly in spring, which could advance the dates of flowering and the start of the grain‐filling period. Using the genetic parameters determined by the calibration and validation of WOFOST and bias‐corrected projected meteorological data, simulations of winter wheat growth were performed over the winter wheat region for 2021–2050. The simulated number of days to the flowering period of winter wheat for 2041–2050 was on average 6.5 days less than in 2021–2030, due to the spring warming. Because of the earlier start of the growing season, winter wheat could face negative effects by being subjected to low temperatures. Indeed, the number of low‐temperature days was projected to increase by 110% from 2041 to 2050 compared to 2021–2030, and the number of killing degree days (KDDs) is projected to increase by 120% at the same time. If the number of days to flowering did not change, the number of low‐temperature days and KDDs only changed slightly, showing that the negative influence of low temperature was mainly caused by the advancement of the flowering date. The effect of low temperature on growth was underestimated when the response of winter wheat growth to global warming was not considered. [ABSTRACT FROM AUTHOR]

A heavy rainfall trajectory (HRT) is defined as the trajectory formed by the movement of the rainstorm centre of a heavy rainfall event over time. Based on this definition, the dispersion degree (DD) of HRTs is applied based on the Euclidean distance and an empirical orthogonal function (EOF) to quantify the spatiotemporal distribution and evolution characteristics of HRTs in China. The results show that (a) the spatial distribution and length of HRTs in China have distinct geographical and seasonal characteristics, which are strongly influenced by the East Asian summer monsoon. (b) From southeast China to northwest China, the DDs increased to 8 and the length of HRTs decreased by 53,925 m. (c) According to EOF analysis, the direction angle change of northeast‐oriented HRTs shows a significant negative trend across the country, while those of southeast‐, southwest‐ and northwest‐oriented HRTs show a significant positive trend. From 2008 to 2019, HRTs flattened in the northeast and southwest directions, while HRTs steepened in the southeast and northwest directions. This research provides certain scientific guidance for the prevention and mitigation of regional disasters and provides necessary theoretical support for the changing patterns of the climate system under the impact of climate change. [ABSTRACT FROM AUTHOR]

The evolution of the frequency of dry/wet spells is a hot topic in global climate change research. The synergistic effects of dry/wet spells make their consequences far more significant than a single disaster, having considerable impacts on hydrology, ecology, and economies, especially in the context of global warming. In this study, the standardized precipitation evapotranspiration index (SPEI)‐based identification of dry/wet spells was used to explore the evolution of the frequency of dry/wet abrupt alternation (DWAA) events in the past four decades in China, makes up for the lack of research on the evolution of such compound disasters. China has been affected by dry/wet spells in many areas for a long time. Studies found that high‐frequency DWAA areas are concentrated in densely populated areas, China's essential food bases and core areas for economic development. Dry‐to‐wet (D–W) events and wet‐to‐dry (W–D) events basically increased or decreased at the same pace in this period. We innovatively find DWAA events (D–W events and W–D events) are projected to occur increasingly in a wider region of China. The frequency of D–W events across China has increased from 2.35 in the 1980s to 3.56 in the last decade, a 50% increase. On the other hand, W–D events increased from 2.6 to 3.23, increasing 24%. The three regions with the most remarkable changes in the past four decades are Inner Mongolia, northwest China, and north China, where D–W events increased by 121, 61, and 58%, respectively, and W–D events increased by 71, 57, and 61%, respectively. Hereby, it is vital to implement effective prevention against DWAA events in the area which has been neglected in the past decades because of lower frequency. These results may help policymakers develop suitable disaster mitigation plans for reducing the potential risks of extreme compound natural events. [ABSTRACT FROM AUTHOR]

The last millennium (LM, 1000–1850 AD) is crucial for studying historical climate change on decadal to multidecadal timescales. The summer surface air temperature (SAT) evolutions on regional scales (e.g. over China) are more uncertain than the globe/Northern Hemisphere, especially in response to external forcing factors and internal climate variability. Here, we provide one‐signal (full‐forcing) fingerprints of summer SAT in China derived from three large ensemble model archives with a multi‐proxy reconstruction during the LM, Little Ice Age (LIA, 1451–1850 AD), and Medieval Climate Anomaly (MCA, 1000–1250 AD), respectively. Our results show that (a) SATs in the northeast, southeast, northwest, and Tibetan Plateau (TP) regions of China show evident decreasing trends during the LM. External forcing response from all model archives agrees with the regional SAT reconstruction but underestimates variability in northwest China at the multidecadal timescale. (b) During the LIA, the summer regional SAT exhibits a cold condition in the reconstruction and simulations, especially in the northeast and northwest regions of China. External forcing responses in most model archives are the dominant factor on multidecadal SAT evolutions in the southeast, northeast, and TP regions of China and decadal SAT evolutions in northwest China. (c) During the MCA, detection and attribution of SAT shows that internal climate variability dominates in southeast, northeast, and TP regions of China, but external forcing dominates in northwest China at decadal to multidecadal timescales. These results contribute to a better understanding of the causes and mechanisms of regional climate change. [ABSTRACT FROM AUTHOR]

To support future solar energy deployment in China, long‐term changes in solar energy resources over China were investigated based on high‐resolution dynamical downscaling simulations under three emission scenarios. First, an evaluation of model performance was conducted through comparison with station and ERA5 data, which indicated that although consistent overestimation was found, the spatial distribution and intra‐annual variation of solar radiation were captured well by ensemble simulation, showing added value over regions with complex topography as well. Then, the trends of the solar power output from photovoltaic (PV) systems during 2020–2099 were projected, characterized by an increase in east and central China, and a consistent decrease in the solar‐energy‐abundant regions (e.g., northeast China, the Tibetan Plateau, and northwest China) under the three scenarios. Except for under the low emission scenario, the regional averaged trends of PV were projected to decrease consistently over China in all four seasons, with significant magnitude apparent in both spring and winter. In addition, a more intense magnitude of decline was found under the higher emission scenario, with more subregions with a significant trend and higher intra‐annual and inter‐annual variability. However, it seems that the emission scenarios impact the spatial pattern only remarkably in the late century, however strengthened the decreasing magnitude in all future periods. In addition, results indicate decline in the future PV potential over most of subregions of China due to reduced radiation and increased temperature, but for the decrease over Tibetan Plateau the reduced wind speed also act as an important factor. Plain Language Summary: The long‐term goal of carbon neutrality in China involves new requirements for the development and utilization of solar energy. The present study was motivated by supporting future solar energy deployment at local scales. However, due to data limitations, relatively little effort has been made to project long‐term changes in solar energy over different subregions of China. Accordingly, we investigated this based on a set of high‐resolution dynamical downscaling simulations under different climate scenarios, and found that the higher emission scenarios reinforce the magnitude of the decline in solar energy and result in higher inter‐annual variability. These findings suggest an increased need for constraining emissions for the benefit of solar energy. In addition, we found that radiation will likely be the most important factor related to future changes in solar resources over most of subregions under RCP2.6 scenario, however the effect of wind speed should not be ignored over Tibetan Plateau. Key Points: Despite some overestimation, the spatial distribution and intra‐annual variation of solar radiation were captured well, showing added valuesFuture solar power were projected to generally increase in east and central China but decrease in solar‐energy‐abundant regionsRadiation was the most robust factor for future solar energy trend over China, however wind speed can not be ignored over Tibetan Plateau [ABSTRACT FROM AUTHOR]

Concurrent hot extremes and droughts undoubtedly aggravate the impacts of droughts on agriculture, natural environment, and human society. Recent studies mainly focus on the trends and changes in frequency and severity of compound drought and hot extreme events. However, relatively little attention has been paid to the changes in mean temperature during drought conditions. In this study, we investigated the mean temperature changes during droughts in observed and projected periods across China on a century time‐scale and explored the possible contributions of land surface‐atmosphere interactions or atmospheric moisture conditions to these changes. China experienced reduced rather than amplified warming under droughts both in observations and future projections. A drier condition or a higher emission scenario was projected to result in a larger range of mean temperature changes under droughts in the future. We attributed the reduced mean temperatures under droughts to increasing winter droughts and higher atmospheric moisture conditions. This study provides a reference for water resource management, drought risk reduction, as well as mitigation of agricultural crop loss and public health damage. Plain Language Summary: Previous climate studies generally focus on the trend analysis of concurrent droughts and hot extremes, especially in summer. There are gaps in our knowledge on how does the mean temperature under droughts change under climate warming, and what are the underlying driving factors? We investigated the changes in mean temperature during droughts across China using monthly observed data and projected data. China experienced reduced rather than amplified warming under droughts both in observations and future projections. A drier condition or a higher emission scenario could result in a larger range of mean temperature changes under droughts in the future. Increasing winter droughts and higher atmospheric moisture conditions resulted in the reduced mean temperatures under droughts. Our study provides references for policymakers to inform water resource management, drought risk reduction, and mitigation of agricultural crop loss. Key Points: China experienced reduced rather than amplified warming under drought conditions both in observations and future projectionsA drier condition or a higher emission scenario resulted in a larger range of mean temperature changes under future droughtsWe attributed the reduced mean temperatures under droughts to increasing winter droughts and higher atmospheric moisture conditions [ABSTRACT FROM AUTHOR]

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