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Numerical weather prediction (NWP), when accessible, is a crucial input to short-term solar power forecasting. WRF-Solar, the first NWP model specifically designed for solar energy applications, has shown promising predictive capability. Nevertheless, few attempts have been made to investigate its performance under high aerosol loading, which attenuates incoming radiation significantly. The North China Plain is a polluted region due to industrialization, which constitutes a proper testbed for such investigation. In this paper, aerosol direct radiative effect (DRE) on three surface shortwave radiation components (i.e., global, beam, and diffuse) during five heavy pollution episodes is studied within the WRF-Solar framework. Results show that WRF-Solar overestimates instantaneous beam radiation up to 795.3 W m−2 when the aerosol DRE is not considered. Although such overestimation can be partially offset by an underestimation of the diffuse radiation of about 194.5 W m−2, the overestimation of the global radiation still reaches 160.2 W m−2. This undesirable bias can be reduced when WRF-Solar is powered by Copernicus Atmosphere Monitoring Service (CAMS) aerosol forecasts, which then translates to accuracy improvements in photovoltaic (PV) power forecasts. This work also compares the forecast performance of the CAMS-powered WRF-Solar with that of the European Centre for Medium-Range Weather Forecasts model. Under high aerosol loading conditions, the irradiance forecast accuracy generated by WRF-Solar increased by 53.2% and the PV power forecast accuracy increased by 6.8%. Significance Statement: Numerical weather prediction (NWP) is the "go-to" approach for achieving high-performance day-ahead solar power forecasting. Integrating time-varying aerosol forecasts into NWP models effectively captures aerosol direct radiation effects, thereby enhancing the accuracy of solar irradiance forecasts in heavily polluted regions. This work not only quantifies the aerosol effects on global, beam, and diffuse irradiance but also reveals the physical mechanisms of irradiance-to-power conversion by constructing a model chain. Using the North China Plain as a testbed, the performance of WRF-Solar on solar power forecasting on five severe pollution days is analyzed. This version of WRF-Solar can outperform the European Centre for Medium-Range Weather Forecasts model, confirming the need for generating high spatial–temporal NWP. [ABSTRACT FROM AUTHOR]

Wetland loss and climate change are known to alter regional and global methane (CH4) budgets. Over the last six decades, an extensive area of marshland has been converted to cropland on the Sanjiang Plain in Northeast China, and a significant increase in air temperature has also been observed there, while the impacts on regional CH4 budgets remain uncertain. Through model simulation, we estimated the changes in CH4 emissions associated with the conversion of marshland to cropland and climate change in this area. Model simulations indicated a significant reduction of 1.1 Tgyr-1 from the 1950s to the 2000s in regional CH4 emissions. The cumulative reduction of CH4 from 1960 to 2009 was estimated to be ~ 36Tg relative to the 1950s, and marshland conversion and the climate contributed 86% and 14% of this change, respectively. Interannual variation in precipitation (linear trend with P > 0.2) contributed to yearly fluctuations in CH4 emissions, but the relatively lower amount of precipitation over the period 1960-2009 (47 mmyr-1 lower on average than in the 1950s) contributed ~91% of the reduction in the area-weighted CH4 flux. Global warming at a rate of 0.3 °C per decade (P < 0.001) has increased CH4 emissions significantly since the 1990s. Relative to the mean of the 1950s, the warming-induced increase in the CH4 flux has averaged 19 kg ha-1 yr-1 over the last two decades. For the RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios of the fifth IPCC assessment report (AR5), the CH4 flux is predicted to increase by 36 %, 52 %, 78% and 95 %, respectively, by the 2080s compared to 1961-1990 in response to climate warming and wetting. [ABSTRACT FROM AUTHOR]

Melting layer usually exists in precipitation where ice particles gradually melt into liquid particles. Utilizing the detection from the Dual-frequency Precipitation Radar onboard Global Precipitation Measurement Mission Core Observatory during 2018-2022, this paper investigates the quasi-global climatological features of Melting layer over 65°S ~65°N and analyzes the relationships with elevation in the golden case involving the section along 32.5°N across China. The distribution of Melting layer is latitude-dependent: Melting layer is higher in 30°S~30°N and decrease toward the mid-and high-latitude, which are generally lower in 30°S~65°S throughout the year. The height and thickness of Melting layer change more dramatically in mid-and high latitudes than in low latitudes for diurnal variations. The higher elevation terrain has the lower Melting layer top height than other terrains, yet the geometric thickness of Melting layer is also thinner. A golden case is selected to represent the analysis of Melting layer play role in rainfall. When the Melting layer grow thinner with steeply rising elevation due to the thermal change and orographic uplift, there is weak rain with a greater number of smaller raindrops in the golden case. However, Melting layer can get widen and raindrops can get sufficient growth as the elevation declines. [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]

Architectural research often considers buildings as local material adaptations to climate, particularly when it comes to the analysis of architecture in rural and small-scale settlements. Based on ethnographic data from the rapidly urbanizing oasis metropolis Ürümchi in China's northwestern borderlands, this paper goes beyond such a localized view of climate responsiveness. It analyzes how individual thermal practices of residents are linked to the interests of the state and to socio-cultural notions of thermal comfort. Through the classification of Xinjiang as part of China's northern "Heating Zone," the keeping warm of individual bodies becomes part of a territorializing strategy. There are, however, clear seasonal differences in how indoor residential spaces are regulated to maintain bodily comfort. In winter, apartment owners and residents enjoy the amenities of the state-financed heating infrastructure. In summer, cooling strategies depend on more neoliberalized, individual, social, and architectural ways to lower indoor temperatures. This paper unfolds the diversity of thermal discourses and practices that characterize Ürümchi citizens' creation of comfortable residential spaces throughout the seasons. The data outlines that houses as infrastructures are far from being simple containers that keep residents' bodies warm. Instead, the socio-technical organization of thermal spaces interferes with territorial strategies and ethnic place-making. [ABSTRACT FROM AUTHOR]

Based on four reanalysis datasets including CMA-RA, ERA5, ERA-Interim, and FNL, this paper proposes an improved intelligent method for shear line identification by introducing a second-order zonal-wind shear. Climatic characteristics of shear lines and related rainstorms over the Southern Yangtze River Valley (SYRV) during the summers (June-August) from 2008 to 2018 are then analyzed by using two types of unsupervised machine learning algorithm, namely the t-distributed stochastic neighbor embedding method (t-SNE) and the k-means clustering method. The results are as follows: (1) The reproducibility of the 850 hPa wind fields over the SYRV using China's reanalysis product CMARA is superior to that of European and American products including ERA5, ERA-Interim, and FNL. (2) Theory and observations indicate that the introduction of a second-order zonal-wind shear criterion can effectively eliminate the continuous cyclonic curvature of the wind field and identify shear lines with significant discontinuities. (3) The occurrence frequency of shear lines appearing in the daytime and nighttime is almost equal, but the intensity and the accompanying rainstorm have a clear diurnal variation: they are significantly stronger during daytime than those at nighttime. (4) Half (47%) of the shear lines can cause short-duration rainstorms (=20 mm (3h)-1), and shear line rainstorms account for one-sixth (16%) of the total summer short-duration rainstorms. Rainstorms caused by shear lines are significantly stronger than that caused by other synoptic forcing. (5) Under the influence of stronger water vapor transport and barotropic instability, shear lines and related rainstorms in the north and middle of the SYRV are stronger than those in the south. [ABSTRACT FROM AUTHOR]

The planetary boundary layer is crucial for the turbulence mixing and exchange of heat flux, momentum, and atmospheric pollutants between the atmosphere and Earth's surface. Nevertheless, the estimated boundary layer height (BLH) varies greatly by data sources and algorithms. This paper seeks to characterize the convective BLHs from 1‐s radiosonde measurements of China Radiosonde Network (CRN) for the 2012–2020 period at 1400 Beijing time, by using eight well‐known algorithms, wherein the newly established Thorpe method is theoretically fundamental on turbulence analysis and is in remarkable agreement with the parcel and bulk Richardson number methods. BLHs obtained by eight methods, ranging from 1.2 to 2.5 km, strongly vary with methods based on different kinetic or thermodynamic theories. The significant offsets among methods motivate the present study to propose a merged algorithm, to minimize the spread of BLH estimate. The merged BLH contains more physical information than that retrieved from a single method and can significantly lower the uncertainty. The BLH climatology exhibits a spatial pattern of "Southwest‐High Southeast‐Low," ascending from 0.6 km over southeastern China to 2.3 km over southwestern China, which could be largely attributed to the variations in the integrated surface sensible heat flux, soil moisture, total cloud cover, land cover, synoptic forcing, and terrain‐induced flow. Of interest is that land surface properties could be the major driver for the development of CBL. Also noteworthy is that the smallest BLH is expected under the strongest synoptic forcing condition. Plain Language Summary: The planetary boundary layer (PBL), where the exchanges of heat, moisture, momentum, and mass mainly occur with a variety of physical and chemical processes involved, is the lowest part of the troposphere in direct contact with the ground surface. However, the determination of boundary layer height (BLH) tends to be dramatically influenced by the dataset and methods used. Few studies have been conducted to evaluate the discrepancy of nationwide daytime BLH over China originating from the methods used. In particular, eight well‐known methods, including the novel Thorpe method and seven other traditional methods, are applied to estimate BLHs from high‐resolution soundings from the China Radiosonde Network. However, BLH derived by eight methods vary from approximately 1.2 to 2.5 km, strongly depending on the method. Therefore, to compile a more convincing BLH dataset eight methods are selected and composed as a merged BLH. The climatology of the merged BLH for the period 2012–2020 shows a well‐defined "Southwest‐High Southeast‐Low " pattern, which could be attributed to the diversities in sensible heat flux, soil moisture, land cover, total cloud cover, synoptic forcing, and terrain‐induced flow across China. Key Points: The merged boundary layer height (BLH) is synthesized from eight methods and it carries more planetary boundary layer (PBL) information and can considerably lower the uncertaintiesThe "Southwest‐High Southeast‐Low" pattern of BLH could be attributed to land properties, synoptic forcing, and terrain‐induced flowUnder weak synoptic forcing condition the development of convective PBL is more susceptible to the variation of land surface properties [ABSTRACT FROM AUTHOR]

Chen, J.; Lu, L.; Lu, J., and Luo, Y., 2015. An early-warning system for shipping market crisis using climate index. The shipping market is always in volatility according to complex impact factors. This paper develops a new operational early warning system (EWS) model based on the economy cycle theory for predicting shipping market crises. To achieve this goal this paper analyses and extends the early warning system by constructing the 'climate index'. Taking industry capacity and profit level into account, several indicators are selected for the synthesis of climate index. These indicators are divided into three categories of the leading, coincident and lagging with time difference correlation analysis and cluster analysis approach. Advantageously accessible to extensive resources, multiple datasets are available for the selected indicators. In terms of the economic cycle theory, diffusion and composite indices of global shipping prosperity are presented by using the factor analysis, predicts composite indices and market situation with the climate index curve and signals. As an empirical example, a climate index for Shanghai container shipping market is developed in order to demonstrate its potential usefulness as an early warning system. It turns out this model can provide a powerful tool for the operators and investors to understand the market trend and avoid the price risk. Additionally, early warning software is developed to put this idea into practice. [ABSTRACT FROM AUTHOR]

This research focuses on a bibliometric analysis of research on aerosols' impact on the glaciers in the Himalayan glacier region published in journals from all subject categories based on the Science Citation Index Expanded, collected from the Web of Science and Scopus database between January 2002 and April 2022. The indexing phrases like "aerosol," "glacier," and "snow" are commonly used terms and have been utilized to collect the related publications for this investigation. The document selections were based on years of publication, authorship, the scientific output of authors, distribution of publication by country, categories of the subjects, and names of journals in which scholarly papers were published. The number of articles on aerosols accelerating the melting of glaciers shows a notable increase in recent years, along with more glacier melting results from countries involved in climate science research. People's Republic of China (382) was the country with the highest publication output on aerosols impacting the melting of glaciers. The USA (367) was the most cited country, with about 17,500 total citations and 80.40 average citations per year from January 2002 to April 2022. The results reveal that research trends in the glaciers on aerosols' impact on the glaciers have been attractive in recent years, and the number of articles in this field keeps increasing fast. This study offers opportunities to track research trends, identify collaboration prospects, and inform climate policy. Integrating data sources and engaging the public will further enhance the impact and relevance of this critical research field. [ABSTRACT FROM AUTHOR]

As clean, renewable energy, photovoltaic (PV) energy can reduce the ozone-layer loss and climate deterioration caused by the use of traditional types of energy to generate electricity. At present, most PV energy products involve the influence of cloud cover on solar radiation. However, the resolution and precision of most cloud cover data are not fine enough to reflect the actual cloud distribution in local areas. This leads to incorrect distribution results of PV energy in areas with high-spatial-variability clouds. Using high-resolution and high-precision cloud cover data obtained by satellite remote sensing to estimate the distribution of PV energy can solve this problem. In this study, the Global Land High-Resolution Cloud Climatology (GLHCC), a 10-day cloud frequency product with a resolution of 1 km and located in China, was used to construct a cloud-based solar radiation estimation model. Using the inverse relationship between cloud cover and solar radiation, the GLHCC was converted into sunshine percentage data. Using meteorological station data in China, a Least Squares Fit (LSF) and error check were carried out on the A-P, Lqbal, Bahel and Sen Models to determine the optimal solar radiation estimation model (Sen Model). Based on the sunshine percentage data, the Sen Model and terrain shielding factors, the distribution of PV energy in China was estimated. Finally, comparing to the Global Horizontal Irradiance (GHI) of the World Bank and the yearly average global irradiance of the Photovoltaic Geographic Information System (PVGIS), PV energy data in this paper more accurately reflected the distribution of PV energy in China, especially in areas with high-spatial-variability clouds. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are important warm-season precipitation systems in eastern China. However, our knowledge of their climatology and capability in their simulation is still insufficient. This paper examines their characteristics over the 2008–2017 warm seasons using convection-permitting climate simulations (CPCSs) with a 3-km grid spacing that explicitly resolves MCSs, as well as a high-resolution gauge-satellite merged precipitation product. An object-based tracking algorithm is applied to identify MCSs. Results indicate that the MCS genesis and occurrence are closely related to the progression of the East Asian monsoon and are modulated by the underlying topography. On average, about 243 MCSs are observed each season and contribute 19% and 47% to total and extreme warm-season precipitation. The climatological attributes and variabilities are reasonably reproduced in the CPCS. The major model deficiencies are excessive small MCS occurrence and overmuch MCS rainfall, consequently overestimating the precipitation contributions, whereas observational uncertainties may play a role too. Both the observed and simulated MCS precipitation feature a nocturnal or morning maximum and an eastward delayed diurnal peak east of the Tibetan Plateau, in contrast to the dominant afternoon peak of non-MCS precipitation. The favorable comparison with observations demonstrates the capability of CPCSs in simulating MCSs in the Asian monsoon climate, and its usefulness in projecting the future changes of MCSs under global warming. The finding that non-MCS precipitation is responsible for the high biased afternoon precipitation provides helpful guidance for further model improvement. [ABSTRACT FROM AUTHOR]

As global warming intensifies, efforts to understand the changes in extreme climate events have increased in recent years. A combined analysis of the changes in extreme temperature and precipitation events is presented in this paper. Using observational data from 1961 to 2015, a set of hotter and wetter (HW) events is defined, and we examine the changes in these events across China. The results show that more HW events occur in Central and Eastern China than in other subregions, especially in South China (SC). The rate of increase in HW events is 2.7 and 1.9 per decade in SC and East China (EC), respectively. In China, most HW events occurred in the last 20 years of the study period, indicating that China entered a period of high-frequency HW events. Indeed, the range in anomalies in the torrential rain days is greater than that of the high-temperature days in Northwest China (NWC), Central China (CC), and EC after the mid- to late 1990s. The opposite pattern is found in Northeast China (NEC), Southwest China-region 1 (SWC1), Southwest China-region 2 (SWC2), and SC. Finally, the increase in HW events in most regions of China is closely associated with warming. [ABSTRACT FROM AUTHOR]

Abstract: Dust storms occurring in arid and semi-arid regions play a main role in the evolution of landscapes. Climate is generally regarded to be important factors influencing the occurrence of dust storm, however, the way of climate controlling dust storms had been poorly understood. In this paper, we present the Ew Index model to describe the relationship between climate variables and dust storm frequency using the available meteorological data from three meteorological stations in Maowusu Desert. This index model explains 83.6%, 69.5% and 65.09% of the variance of dust storm frequency in three regions from the north to the south, respectively and this difference is probably caused by the difference of the human disturbance. The Ew Index model is an effective predictor of dust storm frequency and provides us a quite good understanding on the occurrence of dust storms in Maowusu Desert. [ABSTRACT FROM AUTHOR]

Low-level temperature inversions play crucial roles in inhibiting vertical exchange of energy and mass, and may lead to air pollutants accumulation. The climatological study of them provides a fundamental overview of the static stability of atmosphere and is indispensable for air pollution controls. Based on high-vertical-resolution radiosondes at 00 and 12 UTC during 2011–2018, this work comprehensively examined the spatial and temporal variability of three characteristics (occurrences, strengths, and depths) of low-level inversions in China. Results revealed that inversions are prevalent (more than 80% of the observation records) over Eastern China. The northern part of Eastern China is dominated by the thick strong surface-based inversions with median thickness and strength of 200 m and 3 K, while the southern part by thin weak elevated ones of 80 m and 0.8 K. Tibetan Plateau experiences rare inversions (less than 50% of the time) which tend to be strong thick surface-based inversions with median depth and intensity of 170 m and 4 K. Inversion depths and strengths are positively correlated. The three properties of inversions present remarkable seasonal variations. Generally, inversions are strongest, thickest, and most frequent in winter and least so in summer, with median intensity and depth ranging from 0.3 K and 80 m to 5 K and 220 m. This paper also analyzed the monthly variations of inversions of four representative stations (Harbin, Urumqi, Beijing, and Chongqing) in details. These four cities are known for frequent severe air pollution events. The quantitative investigations of inversions may play a significant role in atmospheric environmental management. [ABSTRACT FROM AUTHOR]

The pre-summer rainy season (PSRS; April–June) is the period of most frequent strong precipitation in South China (SC). Persistent strong precipitation events (PSPEs) can cause greater loss of life and property than short-lived strong precipitation. This paper investigates extended-range signals near the tropopause preceding two persistent positive climatological intraseasonal oscillations (PPCISOs) in precipitation corresponding to two climatological PSPEs in SC during the PSRS, using the CISO analysis of isentropic potential vorticity (IPV). It is found that precursor signals can be better seen in IPV CISOs than in unfiltered IPV. The first rainfall PPCISO is caused by an eastward propagation of high-IPV CISOs along the dynamical tropopause originating from the Arctic region and west of the Tibetan Plateau. The second is the most persistent (13 days). Its high-IPV CISOs originate over the Arctic region and the tropical monsoon region, respectively, 20 or more days prior to the rainfall CISO peak. The west of the Tibetan Plateau and the northern region of the East Asian westerly jet near the tropopause are two transit points where extratropical high-IPV CISOs strengthen and then change their propagation direction. The southward high-IPV CISOs and the northward positive IPV CISO caused by the monsoon begin to interact about 10 days prior to rainfall peak. Since then, the interaction leads a narrow meridional positive PV channel on the inclined 345 K isentropic surface. A specific CISO pattern, characterized by an elongated high-IPV CISO isolated by three negative IPV CISOs (the South Asian, the Okhotsk and the western Pacific subtropical highs), is responsible for the long duration of the second rainfall PPCISO. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

Employees' work well-being (WWB) is vital to employees' performance and organizations' sustainable development. This study aims to explore the role of psychological safety and error management climate (EMC) between humble leadership and WWB in Chinese organizations. Drawing upon social information processing theory, a multi-level study was conducted to test the underlying mechanisms between humble leadership and employees' WWB. A time-lagged data of 221 team members was collected from 12 small and medium sized companies in China. Results showed that team-level humble leadership was positively related to WWB. Psychological safety and EMC both played a partial mediating role linking humble leadership and WWB. EMC positively moderated the relationship between humble leadership and psychological safety. This paper contributes to revealing the multi-level effects of humble leadership on work well-being. These findings also provide some important implications for managerial practices. [ABSTRACT FROM AUTHOR]

There has been a growing focus on uncertainty as a distinct concept in the risk literature. This paper is concerned with how those involved in the design and implementation of climate change policy conceptualize risk and uncertainty. Based on interviews with policy and industry elites in Australia, China and the UK, it finds that participants did not distinguish between "risk" and "uncertainty" in their conceptualization of climate threats. For the majority of them, politics was the most significant source of risk and uncertainty in climate policy, but delegation of otherwise political decisions to the market was seen as the best solution. The conclusion suggests that the conceptual distinction between risk and uncertainty is less important, for policy and industry elites, than the need to develop mechanisms that account for both persistent scientific uncertainties as well as interpretive and moral ambiguities in climate policy design and implementation. [ABSTRACT FROM AUTHOR]

This paper reinvestigated the climate-crop yield relationship with the statistical model at crops' growing stage scale. Compared to previous studies, our model introduced monthly climate variables in the production function of crops, which enables separating the yield changes induced by climate change and those caused by inputs variation and technique progress, as well as examining different climate effects during each growing stage of crops. By applying the fixed effect regression model with province-level panel data of crop yields, agricultural inputs, and the monthly climate variables of temperature and precipitation from 1985 to 2015, we found that the effects of temperature generally are negative and those of precipitation generally are positive, but they vary among different growth stages for each crop. Specifically, GDDs (i.e., growing degree days) have negative effects on spring maize's yield except for the sowing and ripening stages; the effects of precipitation are negative in September for summer maize. Precipitation in December and the next April is significantly harmful to the yield of winter wheat; while, for the spring wheat, GDDs have positive effects during April and May, and precipitation has negative effects during the ripening period. In addition, we computed climate-induced losses based on the climate-crop yield relationship, which demonstrated a strong tendency for increasing yield losses for all crops, with large interannual fluctuations. Comparatively, the long-term climate effects on yields of spring maize, summer maize, and spring wheat are more noticeable than those of winter wheat. [ABSTRACT FROM AUTHOR]

Two skilful 2‐month‐leading hybrid downscaling prediction schemes in October for winter surface air temperature (SAT) over China are proposed in this paper. The schemes are based on the year‐to‐year increment approach and the coupled climate patterns between the winter SAT over China and its predictors. Observed North Pacific sea surface temperature (SST) from the preceding July to September, Arctic sea ice concentration (SIC) in the preceding August and winter sea level pressure (SLP) over pan Eurasia from version 2 of the Climate Forecast System (CFSv2) are selected as the predictors based on the fundamental physics. Individual‐predictor schemes (IP‐schemes), that is, SLP‐scheme, SST‐scheme, SIC‐scheme, indicate that these predictors exhibit prediction skills in different regions. Multi‐predictor scheme I (MP‐schemeI) is developed by combining three predictors. However, MP‐schemeI shows limited skill in predicting SAT over Northeast China (NECTA), due to the limited skill of CFSv2 over the extratropics. Thus, MP‐schemeII is established, in which a hybrid downscaling model for NECTA is constructed. These two MP‐schemes have comparable prediction skill over China, but MP‐schemeII outperforms MP‐schemeI over NEC. The temporal (spatial) anomaly correlation coefficient (ACC) increases from 0.23 (0.15) in MP‐schemeI to 0.36 (0.21) in MP‐schemeII, and the ratio of the same sign of anomalous years (Anomalous‐RSS) improves from 39.1% to 56.5% over NEC. For the winter SAT over China, the MP‐schemes greatly enhance the prediction compared with CFSv2 outputs and the IP‐schemes. The temporal (spatial) ACC increases from 0.29 (0.05) in CFSv2 to 0.52 (0.29) in the MP‐schemes, and the station‐average root‐mean‐square error decreases by about 48.0% compared with CFSv2. Moreover, the RSS (Anomalous‐RSS) of the winter SAT over China is 55.9% (47.4%) in CFSv2 and 64.7% (63.2%) in the MP‐schemes. This indicates that the MP‐schemes perform better in predicting anomalous winters. [ABSTRACT FROM AUTHOR]

Accurate predictions of the clearance time of highway accidents can help make more effective decisions and reduce the economic losses caused by the accidents. This paper compares two representations of traffic accidents with mixed vehicle types and establishes two different classification models. The traffic accident data in Shandong Province, China from 2016 to 2019 are used as a case study. The interpretability of the parametric model indicates that the types of vehicles involved in the accident, the type of accident, and the weather can significantly affect the clearance time of the accident. The results of this study can not only provide evidence of whether the types of vehicles involved in the accident will affect the accident clearance time, but also provide advice for the authorities to quickly clear accident scenes and prevent further accidents. [ABSTRACT FROM AUTHOR]

From the perspectives of remote sensing and climatic factors like surface meteorological parameters, large‐scale atmospheric circulations, and external forcing factors (EFFs), the authors synthesize and review spatiotemporal variations of PM2.5 over North China and how climate anomalies affect autumn and winter haze variability in North China according to recent studies. This review focuses on both interannual and interdecadal timescales. It is shown that circulations play an important role in influencing haze variability. Atmospheric circulations, which would be modulated by EFFs like sea surface temperature, sea ice, and snowpack, can affect the climate variability in haze over North China via modulation of surface‐layer parameters that are closely connected with the haze phenomenon. Therefore, EFFs are deemed significant factors impacting the climate variability of haze over North China, serving as paramount precursory signals for haze prediction. Furthermore, this paper suggests potential future research directions for haze variability studies in North China on the basis of summarizing and concluding the associated processes/mechanisms on how climatic factors affect haze variability, which could provide reference for treating and forecasting in situ hazy conditions. [ABSTRACT FROM AUTHOR]

Research has shown that the climate in northwest China has turned to warm-wet in recent decades. Does this mean that the entire northwest of China has become wet in the last few decades? In the context of the climate transition in northwest China, this paper investigates whether the Bosten Lake Basin (BLB) located in southern Xinjiang has been dry or wet in the last 30 years. We used the Standardized Precipitation Evapotranspiration Index (SPEI) and Temperature Vegetation Drought Index (TVDI) to investigate these changes. The results show that although the dry-wet changes indicated by the SPEI and TVDI exhibited slight spatiotemporal differences, the entire BLB reflected a tendency to be dry. That is, the BLB has not become wet during the climate transition in northwest China, but is developing a trend toward aridification. The main conclusions of this study are as follows: (1) The SPEI indicated a drying trend in seasonal and interannual variations in plains; in mountains, except in spring and summer it has a drying trend, too. (2) The TVDI showed that although the drying trend in summer and winter was weaker than that in spring and autumn in the BLB, where some regions represented a significant tendency toward wetness owing to seasonal or annual changes, the entire study area has still become more dry. [ABSTRACT FROM AUTHOR]

In this paper, 16 cities representing four major architectural climate zones of China were selected, and the heating and cooling loads of office building during the period of 1961–2017 were simulated by using TRNSYS software. Daily extreme heating and cooling loads were determined by percentile methods, and the climate change impact on extreme loads was analyzed. The results showed that the days of extreme heating load of office building significantly decreased in almost all the selected cities, whereas there were no significant changes in the days of extreme cooling load. The daily extreme heating load was dominantly affected by the temperature (R2 = 0.43–0.79), but the daily extreme cooling load was related to multiple climate factors, including temperature, relative humidity, and solar radiation. Single temperature can only explain 3–37% of the changes of daily extreme cooling load, and the combination of multiple climate factors can explain 58–85%. Importantly, the effect of temperature on extreme cooling load showed decrease from the cold to hot climate zones, but the impacts of relative humidity and solar radiation gradually increased. These results suggest that the maximum design capacity of heating systems can properly decrease, and the design capacity of cooling systems may not largely increase with the climate warming. In addition, the combined effect of multiple climate factors rather than the single temperature, as well as the different responses of extreme cooling energy consumption to climate change in different climate zones, should be considered when making measures for improving operating efficiency of air-conditioning system. [ABSTRACT FROM AUTHOR]

Climate classification aims to divide a given region into distinct groups on the basis of meteorological variables, and it has important applications in fields such as agriculture and buildings. In this paper, we propose a novel spectral clustering–based method to partition 661 meteorological stations in China into several zones. First, the correlations are analyzed among five meteorological variables: daily average temperature, average relative humidity, sunshine hours, diurnal temperature range, and atmospheric pressure. The resulting weak linear correlation supports the classification under multiple views. Next, a similarity matrix/graph is constructed by combining the advantages of k-nearest-neighbor and sparse subspace representation. The blocking effect of the similarity matrix confirms the rationality of the classification. Then, we consider respectively the climate classification under a single view and multiple views. For the single view, atmospheric pressure has the highest imbalance degree, and sunshine hours and diurnal temperature range have the strongest classification consistency. The consistency rates are improved evidently in a multiple-view situation. Afterward, we propose a determining method for the number of clusters and make a sensitivity analysis on various parameters. Finally, we provide a further statistical analysis on the classification results and compare the consistency with another climate dataset. All experimental results show that the proposed classification method is feasible and effective in the climate zoning of China. [ABSTRACT FROM AUTHOR]

In meteorology, ensemble forecasting aims to post-process an ensemble of multiple members' forecasts and make better weather predictions. While multiple individual forecasts are generated to represent the uncertain weather system, the performance of ensemble forecasting is unsatisfactory. In this paper we conduct data analysis based on the expertise of human forecasters and introduce a machine learning method for ensemble forecasting. The proposed method, Label Distribution Learning with Climate Probability (LDLCP), can improve the accuracy of both deterministic forecasting and probabilistic forecasting. The LDLCP method utilizes the relevant variables of previous forecasts to construct the feature matrix and applies label distribution learning (LDL) to adjust the probability distribution of ensemble forecast. Our proposal is novel in its specialized target function and appropriate conditional probability function for the ensemble forecasting task, which can optimize the forecasts to be consistent with local climate. Experimental testing is performed on both artificial data and the data set for ensemble forecasting of precipitation in East China from August to November, 2017. Experimental results show that, compared with a baseline method and two state-of-the-art machine learning methods, LDLCP shows significantly better performance on measures of RMSE and average continuous ranked probability score. [ABSTRACT FROM AUTHOR]

One of the aspects of climate change is temperature rise. Temperature rise or fluctuations affect human economic activities and electricity consumption. This paper estimates the changes in electricity consumption due to temperature fluctuation at the county scale in rural China. By using the statistics of counties from 2006 to 2015 in a fixed-effect panel model, the results indicate that a one-degree temperature increase in summer days may lead to 0.015% more electricity consumption per capita, and this correlation may be weaker as income increases. Moreover, a one-degree temperature decrease in winter days may lead to 0.002% more electricity consumption. The northern region may consume 0.021% more electricity than the southern region when facing the same temperature drop. Overall, the effect of temperature on electricity consumption is modest, particularly for a drop in temperature, but the usage of other types of energy may increase to adapt to the cold. [ABSTRACT FROM AUTHOR]

The application of a photovoltaic (PV) system for zero energy buildings is crucial to balance energy consumption. This paper investigated the potential of PV systems for buildings in different climate zones of China. The tilt angle, orientation, plot ratio, PV conversion efficiency and location were selected to study their influences on electricity production. The performance of the PV system was analyzed based on a residential building, and employed RETScreen in combination with TRNSYS. The results indicate that southwest China is the best place to develop zero energy buildings. Low-rise residential buildings can realize zero energy in China when the PV conversion efficiency is higher than 20%. However, an energy balance only occurs in the southwest when the PV conversion efficiency is 10%. For different building heights, with a high conversion efficiency (20%), the energy consumptions rates are less than 15 kW h/m2a all over China. In the southeast, the effect of the building shape on energy generation can be ignored due to the high solar elevation angle in the summer. Although the optimal tilt angle varies for different cities, the energy deviations are less than 10% when tilt angle is within 10° of the optimal angle. This study proposed a formula to evaluate the potential of a building PV system. The maximum difference between the simulated and calculated results is approximately 10%, which is reasonable and acceptable. This paper provides some references for the application of PV systems in zero energy buildings. [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

This study investigates how to leverage information technology (IT) capability to build organizational agility in the context of product innovation. A moderated mediating model is proposed from the capability‐building processes perspective. The data collected from 194 senior executives of firms in China show that knowledge management capability partially mediates the relationship between IT capability and organizational agility. Innovative climate also positively moderates the indirect relationship between IT capability and organizational agility in the context of product innovation. Discussion, implications, and direction for future research are offered at the end of this paper. [ABSTRACT FROM AUTHOR]

Hydrogen and oxygen stable isotopes are natural tracers and have played an important role in the investigation of hydrological processes. In this paper, year-round precipitation samples were collected and measured in Chengdu, a subtropical monsoon climate region, to compare the stable isotope characteristics in precipitation and their influencing factors between dry and wet seasons. The results showed that the seasonal variation of δD and δ18O in precipitation was significant, and the isotopic values in precipitation in dry season were more enriched than those in wet season. The slope and intercept of local meteoric water line (LMWL) in Chengdu were lower than those in the southeast monsoon region of China but higher than those in north China, indicating the combined influence of ocean-source and inland water vapor. The slope of LMWL in dry season was obviously lower than that in wet season, revealing more intense sub-cloud secondary evaporation. The effect of temperature and precipitation was not significant in both seasons. Meteorological variables had greater influence on precipitation isotopes in wet season. D-excess had greater fluctuation during the dry season, reflecting more complex water vapor sources, which resulted in the influence of meteorological factors being masked. [ABSTRACT FROM AUTHOR]

Background: During the Omicron pandemic, clinical first-line nurses played a crucial role in healthcare. Their innovative behavior enhanced the quality of nursing and served as a vital factor in driving the sustainable development of the nursing discipline and healthcare industry. Many previous studies have confirmed the significance of nurses' innovative behavior worldwide. However, the correlations among innovative behaviors, organizational innovation climate, self-transcendence, and their mediating roles in Chinese clinical first-line nurses need further research. Methods: A cross-sectional study was conducted, and the quality reporting conformed to the STROBE Checklist. From March 2022 to February 2023, a convenience sample of 1,058 Chinese clinical first-line nurses was recruited from seven tertiary grade-A hospitals of Tianjin city in Northern China. The Demographic Characteristics Questionnaire, Nurse Innovative Behavior Scale (NIBS), Nurse Organizational Innovation Climate Scale, and the Self-Transcendence Scale were used. The data was analyzed using descriptive statistics, correlation, and process plug-in mediation effect analyses. Results: The total scores of innovative behavior, organizational innovation climate, and self-transcendence were 33.19 ± 6.71, 68.88 ± 12.76, and 41.25 ± 7.83, respectively. Innovative behavior was positively correlated with the organizational innovation climate (r = 0.583, p < 0.01) and self-transcendence (r = 0.635, p < 0.01). Self-transcendence partially mediated mediating role between innovative behavior and organizational innovation climate, accounting for 41.7%. Conclusion: The innovative behavior, organizational innovation climate, and self-transcendence among the first-line nurses during the Omicron pandemic were relatively moderate, which needs improving. Organizational innovation climate can directly affect the innovative behavior among Chinese clinical first-line nurses and indirectly through the mediating role of self-transcendence. It is recommended that nursing managers adjust their management strategies and techniques based on the unique characteristics of nurses during the pandemic. This includes fostering a positive and inclusive environment for organizational innovation, nurturing nurses' motivation and awareness for innovation, enhancing their ability to gather information effectively, overcoming negative emotions resulting from the pandemic, and promoting personal growth. These efforts will ultimately enhance nursing quality and satisfaction during the Omicron pandemic. [ABSTRACT FROM AUTHOR]

The engagement in research, as the primary form of learning engagement for PhD students, is crucial for enhancing their competitive edge. Academic passion, a key determinant of learning engagement, plays a significant role in driving the research enthusiasm of PhD students. However, the "black box" concerning whether and how academic passion influences PhD students' research engagement remains to be explored. Addressing this gap, the present study draws upon self-determination theory, adopts the "motivation-behavior-effect" analytical framework, and incorporates ambidextrous learning as a mediator to elucidate the specific pathway through which academic passion impacts PhD students' engagement in research activities. Furthermore, it examines the facilitating role of the academic climate in this process. From December 2022 to March 2023, a questionnaire survey was conducted, collecting 522 responses from PhD students across 25 universities in China. The survey primarily assessed the PhD students' academic passion, ambidextrous learning behaviors (including tendencies towards exploratory and exploitative learning), and their perceived academic climate, investigating how these factors collectively influence their engagement in research activities. The questionnaire data were analyzed using a combination of SEM and bootstrapping with SPSS 26.0 and Mplus 8.3 software. The findings reveal that academic passion significantly positively affects PhD students' research engagement; ambidextrous learning (exploratory and exploitative learning) mediates the relationship between academic passion and PhD students' research engagement; and the academic climate effectively facilitates the transformation of PhD students' academic passion into ambidextrous learning (exploratory and exploitative learning). The study's conclusions not only foster PhD students' enthusiasm for research but also enhance learning effectiveness and innovation vitality, providing a theoretical basis for reforming the doctoral training system. [ABSTRACT FROM AUTHOR]

Climate is an important tourism resource and a vital component of the attractiveness of a destination. Climate has a strong impact on supply and demand in the tourism industry. Most studies concerning the distribution of tourism climate resources are based on point measurements from meteorological stations. Tourism climate distribution maps with high resolution are required. In this paper, the tourism climate index (TCI) and spatial interpolation based on polynomial regression are used to analyze the distribution of summer tourism climate resources in China. The results indicate that there exists an obvious positive linear relationship between the TCI and latitude and a quadratic relationship between the TCI and elevation. The tourism climate is unfavorable in 8% of the study area, acceptable in 34% of the study area, good and very good in 36% of the study area, and excellent in 22% of the study area. From the perspective of climate, the places comfortable for summer tourism are mainly concentrated to the north of 35°N, on the second elevation step, and in the temperate continental climate zone. The tourism climate information provided is accurate at the 90% level for most areas. [ABSTRACT FROM AUTHOR]

Wang, X.; Jiang, R.; Xie, J.; Zhao, Y.; Li, F., and Zhu, J., 2019. Multiscale variability of precipitation and their teleconnection with large-scale climate anomalies: A case study of Xi'an city, China. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 417–426. Coconut Creek (Florida), ISSN 0749-0208. The changes of precipitation affect the urban rainstorm waterlogging and water resources management, which have important influences on the sustainable development of society. The primary objective of the paper is to provide theoretical basis for local water resources management and disaster prevention and reduction by analyzing the multiscale variability of precipitation and their teleconnection with large-scale climate anomalies in Xi'an city of China. The change characteristics of precipitation and extreme precipitation indices were investigated using Mann-Kendall test, Spearman's rank correlation and wavelet analysis. The cross wavelet transform and wavelet coherence were used to explore the correlations between the precipitation and large-scale teleconnection indices such as Arctic Oscillation (AO), Southern Oscillation Index (SOI), El Niño-Southern Oscillation (ENSO) and sunspot. Results indicate that: the precipitation was mainly concentrated in summer, followed by autumn. The annual, seasonal and monthly precipitation except June and August had decreasing trends, and the magnitudes of precipitation decrease were more pronounced in spring, April and November. The change patterns varied for extreme precipitation indices. The temporal variation in extreme precipitation indices indicated that the extreme precipitation events had mainly increased during 1971-1990 and 1991-2017, and decreased during 1951-1970 and 1951-2017, especially, increased more pronounced during 1991-2017 and decreased more pronounced during 1951-1970. The precipitation exhibited a fluctuant change from increase to decrease, then increase to decrease and finally increase trends, and there was an abrupt change point in 1965. The annual precipitation had statistically significant cycles of 3-5 year and 7-10 year at 5% significance level. The large-scale teleconnection indices affected the precipitation in Xi'an city. The phase differences between precipitation and teleconnection indices including AO and SOI were in-phase dominated, and anti-phase dominated between precipitation and teleconnection indices including ENSO and sunspot, indicating that the AO and SOI exerted positive climate impacts on the precipitation and vice-versa for ENSO and sunspot. [ABSTRACT FROM AUTHOR]

The changes of precipitation affect the urban rainstorm waterlogging and water resources management, which have important influences on the sustainable development of society. The primary objective of the paper is to provide theoretical basis for local water resources management and disaster prevention and reduction by analyzing the multiscale variability of precipitation and their teleconnection with large-scale climate anomalies in Xi'an city of China. The change characteristics of precipitation and extreme precipitation indices were investigated using Mann-Kendall test, Spearman's rank correlation and wavelet analysis. The cross wavelet transform and wavelet coherence were used to explore the correlations between the precipitation and large-scale teleconnection indices such as Arctic Oscillation (AO), Southern Oscillation Index (SOI), El Niño- Southern Oscillation (ENSO) and sunspot. Results indicate that: the precipitation was mainly concentrated in summer, followed by autumn. The annual, seasonal and monthly precipitation except June and August had decreasing trends, and the magnitudes of precipitation decrease were more pronounced in spring, April and November. The change patterns varied for extreme precipitation indices. The temporal variation in extreme precipitation indices indicated that the extreme precipitation events had mainly increased during 1971-1990 and 1991-2017, and decreased during 1951-1970 and 1951-2017, especially, increased more pronounced during 1991-2017 and decreased more pronounced during 1951-1970. The precipitation exhibited a fluctuant change from increase to decrease, then increase to decrease and finally increase trends, and there was an abrupt change point in 1965. The annual precipitation had statistically significant cycles of 3-5 year and 7-10 year at 5% significance level. The large-scale teleconnection indices affected the precipitation in Xi'an city. The phase differences between precipitation and teleconnection indices including AO and SOI were in-phase dominated, and anti-phase dominated between precipitation and teleconnection indices including ENSO and sunspot, indicating that the AO and SOI exerted positive climate impacts on the precipitation and vice-versa for ENSO and sunspot. [ABSTRACT FROM AUTHOR]

On the basis of climate zones classified by the number of days of the daily average temperature ≥ 10 °C (DT10) over China, the performance of the 9 CMIP5 climate models is evaluated in this paper. The results indicate that the CMCC-CMS and MPI-ESM-MR show higher skill than the other 7 models in simulating spatial pattern and its decadal change of climate zones over China. The simulation results for FGOALS-g2 and INM-CM4 both show relatively lower skill than the other 7 models. Meanwhile, the performance of multi-model ensemble in simulating climate zones over China is obviously better than the simulated result of any single model. So, it is a good way to simulate climate zones by multi-model ensemble to reduce some uncertainty of climate models. However, it is crucial to select appropriate ensemble members. Compared with 1960-2005, the climatic zones in China have an obvious trend of northward shift in 2021-2100. The range of southern sub-tropical belt expands to the most areas in the south of Yangtze River under RCP4.5 emission scenarios, and further extends to the north areas of Yangtze River with a maximum of 2-6° of latitude under RCP8.5 emission scenarios. Middle sub-tropical belt shifts gradually to the areas between Yellow River and north areas of the middle and lower reaches of the Yangtze River. Northern sub-tropical belt shifts northward to southeastern North China. Warm extra-tropical belt extends to the most of Northeast China, most of central Inner Mongolia, and northern Xinjiang under RCP8.5 emission scenarios. [ABSTRACT FROM AUTHOR]

This paper interrogates the impact of policy events on the efficiency of carbon market in China. The analysis covers five piloting emission trading schemes (Beijing, Shanghai, Guangdong, Shenzhen and Hubei), particularly focusing on Guangdong pilot for its weak form efficiency and the richness of policy events. Twenty-five policy events between 2014 and 2016 are categorized into seven groups. The efficiency test indicates that only Guangdong ETS has reached weak form efficiency. After exploring the policy events occurred in Guangdong ETS, it finds that although a clear long-term climate policy has been set up over the country, China's carbon market still has a conservative risk appetite and its governing institutions still needs further development. The policy makers need to be aware of and avoid the negative impacts of policy events to the market evolvement, by introducing effective consultancy process with the stakeholders and nurturing market expectations in the long run. We also find that events like allowance auctions have considerably less impacts than previously expected and argue that auction approach should be considered a preferable option over a free allocation system in the future policy design. [ABSTRACT FROM AUTHOR]

Employing an endogenous switching regression model, we investigate the drivers underlying the adaptations made by farm households and their impacts on crop net incomes for adopters and nonadopters, based on a large panel survey data set across the major grain‐producing provinces in China. The results show that: (i) access to public climate information and technical or physical support increases the likelihood that farmers adapt to climate change by undertaking irrigation and/or drainage measures; and (ii) decisions to adapt increased crop yield, but they did not significantly increase crop profit margins. This point appears to have been ignored by previous studies. Based on these new empirical results, the paper suggests that government should continue to provide climate information and various types of supports to improve farmers’ adaptation abilities and help to reduce the levels of factor input by, for example, substituting organic for chemical fertiliser inputs. Such government‐led policies should be supported alongside the implementation of domestic agricultural supply‐side reform. [ABSTRACT FROM AUTHOR]

This paper evaluates the monthly mean air temperature over complex terrain in China determined using two methods: Australian National University spline and GridMet_Climate_Temperature (grid meteorological and climatic temperature (GMCT)) models. It is found that the macroscopic patterns of the temperature distributions by the two methods are very similar. The comparison of modelled temperatures with observations from 40 verification stations shows that both methods have the same value of total mean absolute bias errors (MABE) of 0.43 °C. Since the observational data used are from meteorological observational stations which are located on horizontal flat and open areas, these evaluation results only represent those on the flat open areas. In order to evaluate the effects of topographical factors on the temperature, a concept of relief amplitude is defined. The temperatures are grouped according to range of the relief amplitudes, and variation of temperature with relief amplitudes is worked out. It is found that the temperature difference between the two models varies significantly with relief amplitudes. The averaged maximum difference can be as large as 12 °C in January when the relief amplitude is greater than 700 m. The reasons for the temperature difference are investigated, and they are due to the effects of topographical slopes and aspects. One model (GMCT) includes these effects while the other does not. The evaluation results demonstrate that it is necessary to include the effects of topographical factors in the model simulation in order to produce realistic temperature distributions in the complex terrain areas. The distributions of temperature on the northern and southern slopes are determined using the GMCT model, and the results show that the temperatures on the southern slopes are clearly greater than those of the northern slopes, especially in winter. These results can be used as a guide for the reasonable and sustainable utilization of heat resources in the mountainous area. [ABSTRACT FROM AUTHOR]

Background: Southwest China is home to more than 30 ethnic minority groups. Since most of these populations reside in mountainous areas, convenient access to medical services is an important metric of how well their livelihoods are being protected. Methods: This paper proposes a medical convenience index (MCI) and computation model for mountain residents, taking into account various conditions including topography, geology, and climate. Data on road networks were used for comprehensive evaluation from three perspectives: vulnerability, complexity, and accessibility. The model is innovative for considering road network vulnerability in mountainous areas, and proposing a method of evaluating road network vulnerability by measuring the impacts of debris flows based on only links. The model was used to compute and rank the respective MCIs for settlements of each ethnic population in the Dehong Dai and Jingpo Autonomous Prefecture of Yunnan Province, in 2009 and 2015. Data on the settlements over the two periods were also used to analyze the spatial differentiation of medical convenience levels within the study area. Results: The medical convenience levels of many settlements improved significantly. 80 settlements were greatly improved, while another 103 showed slight improvement.Areas with obvious improvement were distributed in clusters, and mainly located in the southwestern part of Yingjiang County, northern Longchuan County, eastern Lianghe County, and the region where Lianghe and Longchuan counties and Mang City intersect. Conclusions: Development of the road network was found to be a major contributor to improvements in MCI for mountain residents over the six-year period. [ABSTRACT FROM AUTHOR]

This paper reviews the historic understanding of the predictability of atmospheric and oceanic motions, and interprets it in a general framework. On this basis, the existing challenges and unsolved problems in the study of the intrinsic predictability limit (IPL) of weather and climate events of different spatio-temporal scales are summarized. Emphasis is also placed on the structure of the initial error and model parameter errors as well as the associated targeting observation issue. Finally, the predictability of atmospheric and oceanic motion in the ensemble-probabilistic methods widely used in current operational forecasts are discussed. The necessity of considering IPLs in the framework of stochastic dynamic systems is also addressed. [ABSTRACT FROM AUTHOR]

Weighting models according to their performance has been used to produce multimodel climate change projections. But the added value of model weighting for future projection is not always examined. Here we apply an imperfect model framework to evaluate the added value of model weighting in projecting summer temperature changes over China. Members of large-ensemble simulations by three climate models of different climate sensitivities are used as pseudo-observations for the past and the future. Performance of the models participating in the phase 6 of the Coupled Model Intercomparison Project (CMIP6) are evaluated against the pseudo-observations based on simulated historical climatology and trends in global, regional, and local temperatures to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations in the future period. We find that regional trend as a metric of model performance yields generally better skill for future projection, while past climatology as performance metric does not lead to a significant improvement to projection. Trend at the grid-box scale is also not a good performance indicator as small-scale trend is highly uncertain. For the model weighting to be effective, the metric for evaluating the model's performance must be relatable to future changes, with the response signal separable from internal variability. Projected summer warming based on model weighting is similar to that of unweighted projection but the 5th–95th-percentile uncertainty range of the weighted projection is 38% smaller with the reduction mainly in the upper bound, with the largest reduction appearing in southeast China. [ABSTRACT FROM AUTHOR]

The building energy performance improvement of large-scale public buildings is very important to release China's energy shortage pressure. The aim of the study is to find out the building energy saving potentials of large-scale public and commercial buildings by energy audit. In this paper, the energy consumption, energy performance, and audit were carried out for a typical commercial mall, the so-called largest mall in Asia, located in a hot-summer and warm-winter climate zone. The total annual energy consumption reaches 210.01 kWh/m, of which lighting energy consumption accounts for 30.03 kWh/m and the lift and elevator energy consumption accounts for 40.46 kWh/m. It is by far higher than that of the average building energy consumption in the same category. However, the annual heating, ventilation, and air-conditioning (HVAC) energy consumption is only 87.19 kWh/m even though they run 24/7. It proves that the energy performance of the HVAC system is good. Therefore, the building energy savings potential mainly relies on reducing the excessive usage of lighting, lifts, and elevators. [ABSTRACT FROM AUTHOR]

During the Xinhai revolution, China faced contending domestic identities, and its roles within the international order were assigned by external powers. In the 100 years that have followed, China's internal competing identities have become more stable and it now faces major challenges in reconciling its contending international identities. China's current ascendency returns it to a position of directing the international order, which resembles its position before the Xinhai revolution. As China changes international identities and gradually moves from being a developing state to a great power, it creates uncertainty among other states. In order for China's rise to continue, it needs to prevent this uncertainty from becoming conflict: it needs a stable international environment. This paper argues that by adopting a view of China's rise as a series of shifts in its identity, the scepter of conflict can be reduced because the uncertainty that is being created can be understood as well as contribute understanding about international behavior. This paper looks at the roles and identities displayed by China at the UN Climate Change conferences. [ABSTRACT FROM AUTHOR]

Due to the higher temporal and spatial resolution and the better integrality of long-term satellite infrared (IR) Brightness Temperature (TBB) data, a climatology of deep convection during summer over South China and the adjacent waters is presented in this paper based on the 1-hourly infrared IR TBB data during June-August of 1996-2007 (except 2004). The results show that the geographic distribution of deep convection denoted by TBB ⩽ -52°C over South China and the adjacent waters are basically consistent with previous statistical results based on surface thunderstorm observations and low-orbit satellite lightning observations. The monthly, ten-day, five-day and diurnal variations of deep convection in this region are focused on in this paper. There are 5 active deep-convection areas in June-August. The monthly variations of the deep convection are closely associated with the large-scale atmospheric circulations. The deep convection over the land areas of South China is more active in June while that over the South China Sea is more active in July and August. The development of deep convection is prominently intermittent and its period is about 3 to 5 five-day periods. However, the deep convection over the coastal areas in South China remains more active during summer and has no apparent intermittence. The ten-day and five-day variations of deep convection show that there are different variations of deep convection over different areas in South China and the adjacent waters. The tendency of deep convection over the land areas of South China is negatively correlated with that over the South China Sea. The diurnal variations of deep convection show that the sea-land breeze, caused by the thermal differences between land and sea, and the mountain-valley breeze, caused by the thermal differences between mountains and plains or basins, cause deep convection to propagate from sea to land in the afternoon and from land to sea after midnight, and the convection over mountains propagates from mountains to plains after midnight. The different diurnal variations of deep convection over different underlying surfaces show that not only there are general mountainous, marine and multi-peak deep convection, but also there is longer-duration deep convection over coastal areas and other deep convection triggered and maintained by larger-scale weather systems in South China during summer. [ABSTRACT FROM AUTHOR]

The frequency and magnitude of extreme meteorological or hydrological events such as floods and droughts in China have been influenced by global climate change. The water problem due to increasing frequency and magnitude of extreme events in the humid areas has gained great attention in recent years. However, the main challenge in the evaluation of climate change impact on extreme events is that large uncertainty could exist. Therefore, this paper first aims to model possible impacts of climate change on regional extreme precipitation (indicated by 24-h design rainfall depth) at seven rainfall gauge stations in the Qiantang River Basin, East China. The Long Ashton Research Station-Weather Generator is adopted to downscale the global projections obtained from general circulation models (GCMs) to regional climate data at site scale. The weather generator is also checked for its performance through three approaches, namely Kolmogorov-Smirnov test, comparison of L-moment statistics and 24-h design rainfall depths. Future 24-h design rainfall depths at seven stations are estimated using Pearson Type III distribution and L-moment approach. Second, uncertainty caused by three GCMs under various greenhouse gas emission scenarios for the future periods 2020s (2011-2030), 2055s (2046-2065) and 2090s (2080-2099) is investigated. The final results show that 24-h design rainfall depth increases in most stations under the three GCMs and emission scenarios. However, there are large uncertainties involved in the estimations of 24-h design rainfall depths at seven stations because of GCM, emission scenario and other uncertainty sources. At Hangzhou Station, a relative change of −16% to 113% can be observed in 100y design rainfall depths. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Hong Kong is a high-density sub-tropical city with 7 million people living in an urban area of just over 260 km2. Tall and closely packed buildings are the common urban morphology. How the urban geometry influences the microclimate in summer daytime is a primary planning concern. The sky view factor (SVF) has been commonly used to indicate the impact of urban geometry on air temperature differences in cities. However, only limited discussions in this aspect have been addressed for daytime course in high-rise and high-density urban environment such as Hong Kong. This paper firstly provides a comprehensive review of SVF analysis in urban climatology studies and then presents a simulation approach to investigate the role of SVF in determining summer daytime intra-urban air temperature differences in urban Hong Kong. An ArcGIS-embedded computer program is developed for calculating continuous SVF values for an entire urban environment and an SVF map is generated. The result is evaluated against meteorological data observed in field measurements. The regression analysis shows that the spatial average of SVF values has a close negative relationship with daytime intra-urban temperature differences. The study indicates that SVF is a significant factor for understanding the microthermal climate in Hong Kong's street canyons. The paper further raises discussions on the application of SVF analysis to urban planning. The study demonstrates that the SVF analysis is a useful and effective tool for planners and urban climatologists conducting studies on high-rise and high-density sub-tropical cities. The understanding can provide support for the development of planning standards and good practice. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The correlation between mean surface air temperature and altitude is analyzed in this paper based on the annual and monthly mean surface air temperature data from 106 weather stations over the period 1961-2003 across the Qinghai-Tibet Plateau. The results show that temperature variations not only depend on altitude but also latitude, and there is a gradual decrease in temperature with the increasing altitude and latitude. The overall trend for the vertical temperature lapse rate for the whole plateau is approximately linear. Three methods, namely multivariate composite analysis, simple correlation and traditional stepwise regression, were applied to analyze these three correlations. The results assessed with the first method are well matched to those with the latter two methods. The apparent mean annual near-surface lapse rate is −4.8 °C /km and the latitudinal effect is −0.87 °C /latitude. In summer, the altitude influences the temperature variations more significantly with a July lapse rate of -4.3°C /km and the effect of latitude is only −0.28°C /latitude. In winter, the reverse happens. The temperature decrease is mainly due to the increase in latitude. The mean January lapse rate is −5.0°C /km, while the effect of latitude is −1.51°C /latitude. Comparative analysis for pairs of adjacent stations shows that at a small spatial scale the difference in altitude is the dominant factor affecting differences in mean annual near-surface air temperature, aided to some extent by differences of latitude. In contrast, the lapse rate in a small area is greater than the overall mean value for the Qinghai-Tibet Plateau (5 to 13°C /km). An increasing trend has been detected for the surface lapse rate with increases in altitude. The temperature difference has obvious seasonal variations, and the trends for the southern group of stations (south of 33° latitude) and for the more northerly group are opposite, mainly because of the differences in seasonal variation at low altitudes. For yearly changes, the temperature for high-altitude stations occurs earlier clearly. Temperature datasets at high altitude stations are well-correlated, and those in Nanjing were lagged for 1 year but less for contemporaneous correlations. The slope of linear trendline of temperature change for available years is clearly related to altitude, and the amplitude of temperature variation is enlarged by high altitude. The change effect in near-surface lapse rate at the varying altitude is approximately 1.0°C /km on the rate of warming over a hundred-year period. [ABSTRACT FROM AUTHOR]

The present paper provides a scientific assessment of the inter-decadal variability of the Asian summer monsoon and its significant effect on precipitation patterns in China. The paper consists of four parts. The first part shows the observed inter-decadal weakening of the Asian summer monsoon since the end of 1970s. The second part describes the impact of the weakening Asian summer monsoon on precipitation in China, which caused the major monsoon rainbelt to shift southward from North China to South China over about 30 years, with a 60-80 oscillation dominating. The third part projects the future change of the Asian summer monsoon in the warmer climate by using IPCC AR4 climate models. It has been found that major monsoon rainfall belts in East Asia will move northward in the 2040s, with summer precipitation in North China increasing considerably and stably. Finally, in the fourth part, the implication of the adaptation to the above climate change and related water management will be discussed including the water transport engineering project from the Yangtze River to the Yellow River and North China. [ABSTRACT FROM AUTHOR]