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Kai Jin
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Water and Soil Conservation, Northwest A&F University, Yangling 712100, China

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Journal article
Published: 04 February 2021 in Atmosphere
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Worldwide solar dimming from the 1960s to the 1980s has been widely recognized, but the occurrence of solar brightening since the late 1980s is still under debate—particularly in China. This study aims to properly examine the biases of urbanization in the observed sunshine duration series from 1987 to 2016 and explore the related driving factors based on five meteorological stations around Hangzhou City, China. The results inferred a weak and insignificant decreasing trend in annual mean sunshine duration (−0.09 h/d decade−1) from 1987 to 2016 in the Hangzhou region, indicating a solar dimming tendency. However, large differences in sunshine duration changes between rural, suburban, and urban stations were observed on the annual, seasonal, and monthly scales, which can be attributed to the varied urbanization effects. Using rural stations as a baseline, we found evident urbanization effects on the annual mean sunshine duration series at urban and suburban stations—particularly in the period of 2002–2016. The effects of urbanization on the annual mean sunshine duration trends during 1987−2016 were estimated to be −0.16 and −0.35 h/d decade−1 at suburban and urban stations, respectively. For urban stations, the strongest urbanization effect was observed in summer (−0.46 h/d decade−1) on the seasonal scale and in June (−0.63 h/d decade−1) on the monthly scale. The notable negative impact of urbanization on local solar radiation changes was closely related to the changes in anthropogenic pollutions, which largely reduced the estimations of solar radiation trends in the Hangzhou region. This result highlights the necessity to carefully consider urbanization impacts when analyzing the trend in regional solar radiation and designing cities for sustainable development.

ACS Style

Kai Jin; Peng Qin; Chunxia Liu; Quanli Zong; Shaoxia Wang. Impact of Urbanization on Sunshine Duration from 1987 to 2016 in Hangzhou City, China. Atmosphere 2021, 12, 211 .

AMA Style

Kai Jin, Peng Qin, Chunxia Liu, Quanli Zong, Shaoxia Wang. Impact of Urbanization on Sunshine Duration from 1987 to 2016 in Hangzhou City, China. Atmosphere. 2021; 12 (2):211.

Chicago/Turabian Style

Kai Jin; Peng Qin; Chunxia Liu; Quanli Zong; Shaoxia Wang. 2021. "Impact of Urbanization on Sunshine Duration from 1987 to 2016 in Hangzhou City, China." Atmosphere 12, no. 2: 211.

Journal article
Published: 12 August 2020 in Water
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The magnitude and spatiotemporal distribution of precipitation are the main drivers of hydrologic and agricultural processes in soil moisture, runoff generation, soil erosion, vegetation growth and agriculture activities on the Loess Plateau (LP). This study detects the spatiotemporal variations of individual rainfall events during a rainy season (RS) from May to September based on the hourly precipitation data measured at 87 stations on the LP from 1983 to 2012. The incidence and contribution rates were calculated for all classes of rainfall duration and intensity to identify the dominant contribution to the rainfall amount and frequency variations. The trend rates of regional mean annual total rainfall amount (ATR) and annual mean rainfall intensity (ARI) were 0.43 mm/year and 0.002 mm/h/year in the RS for 1983–2012, respectively. However, the regional mean annual total rainfall frequency (ARF) and rainfall events (ATE) were −0.27 h/year and −0.11 times/year, respectively. In terms of spatial patterns, an increase in ATR appeared in most areas except for the southwest, while the ARI increased throughout the study region, with particularly higher values in the northwest and southeast. Areas of decreasing ARF occurred mainly in the northwest and central south of the LP, while ATE was found in most areas except for the northeast. Short-duration (≤6 h) and light rainfall events occurred mostly on the LP, accounting for 69.89% and 72.48% of total rainfall events, respectively. Long-duration (≥7 h) and moderate rainfall events contributed to the total rainfall amount by 70.64% and 66.73% of the total rainfall amount, respectively. Rainfall frequency contributed the most to the variations of rainfall amount for light and moderate rainfall events, while rainfall intensity played an important role in heavy rainfall and rainstorms. The variation in rainfall frequency for moderate rainfall, heavy rainfall, and rainstorms is mainly affected by rainfall duration, while rainfall event was identified as a critical factor for light rainfall. The characteristics in rainfall variations on the Loess Plateau revealed in this study can provide useful information for sustainable water resources management and plans.

ACS Style

Wenbin Ding; Fei Wang; Kai Jin; Jianqiao Han; Qiang Yu; Qingfu Ren; Shangyu Shi. Individual Rainfall Change Based on Observed Hourly Precipitation Records on the Chinese Loess Plateau from 1983 to 2012. Water 2020, 12, 2268 .

AMA Style

Wenbin Ding, Fei Wang, Kai Jin, Jianqiao Han, Qiang Yu, Qingfu Ren, Shangyu Shi. Individual Rainfall Change Based on Observed Hourly Precipitation Records on the Chinese Loess Plateau from 1983 to 2012. Water. 2020; 12 (8):2268.

Chicago/Turabian Style

Wenbin Ding; Fei Wang; Kai Jin; Jianqiao Han; Qiang Yu; Qingfu Ren; Shangyu Shi. 2020. "Individual Rainfall Change Based on Observed Hourly Precipitation Records on the Chinese Loess Plateau from 1983 to 2012." Water 12, no. 8: 2268.

Journal article
Published: 31 January 2020 in Science of The Total Environment
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Studying the drivers and combating the effects of climate change is more urgent than ever, particularly in regions with limited water and sensitive ecosystems. This study evaluated the effect of vegetation variation on surface air temperature (SAT) change in the Chinese Loess Plateau over 1982–2015 based on the ‘observation minus reanalysis’ (OMR) method. Observed temperature, ERA-Interim reanalysis temperature, and Global Inventory Modeling and Mapping Studies normalized difference vegetation index (NDVI) 3rd generation were used to analyze the relationship between OMR temperature (representing vegetation impact on SAT) and NDVI. Results showed that the Loess Plateau, especially its central-east areas, has undergone a rapid increase in NDVI and rapid decrease in OMR temperature during 1982–2015. This implies a strong cooling effect of vegetation restoration on SAT change. The mean annual NDVI (MNDVI) and NDVI trend (SlopeNDVI) were negatively correlated with OMR temperature trend (SlopeOMR) on the Loess Plateau (P < 0.001). However, the relationships between MNDVI (SlopeNDVI) and SlopeOMR varied among the arid, semi-arid, and semi-humid regions. As a result, the impacts of restoration of vegetation condition on SAT change during 1982–2015 were estimated to be 0.04, −0.01, and −0.07 °C decade−1 in the arid, semi-arid, and semi-humid regions, respectively. For the entire Loess Plateau, the restoration of its vegetation condition led to a cooling effect of −0.02 °C decade−1 during 1982–2015 and a cooling effect of −0.05 °C in the period following the implementation of the Grain for Green Project (GGP). Moreover, among the three major land use types of the Loess Plateau (i.e., grassland, farmland, and forest), vegetation restoration of forest demonstrated the most obvious cooling effect (−0.06 °C decade−1 during 1982–2015). These results are the first quantitative estimation of the impact of vegetation variation on SAT across the entire Loess Plateau, and demonstrate the ecological effect of afforestation efforts in the southeastern areas in terms of climate warming alleviation.

ACS Style

Kai Jin; Fei Wang; Quanli Zong; Peng Qin; Chunxia Liu. Impact of variations in vegetation on surface air temperature change over the Chinese Loess Plateau. Science of The Total Environment 2020, 716, 136967 .

AMA Style

Kai Jin, Fei Wang, Quanli Zong, Peng Qin, Chunxia Liu. Impact of variations in vegetation on surface air temperature change over the Chinese Loess Plateau. Science of The Total Environment. 2020; 716 ():136967.

Chicago/Turabian Style

Kai Jin; Fei Wang; Quanli Zong; Peng Qin; Chunxia Liu. 2020. "Impact of variations in vegetation on surface air temperature change over the Chinese Loess Plateau." Science of The Total Environment 716, no. : 136967.

Journal article
Published: 01 January 2020 in Journal of the Meteorological Society of Japan. Ser. II
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Observed surface air temperature (SAT) warming at urban stations often contains both the signal of global warming and that of local urban heat island (UHI) effects which are difficult to be separated. In this study, an urban impact indicator (Uii) developed by the authors was modified to represent the extent to which the observed temperature from a station was influenced by UHI effects. While Uii was calculated through simplifying the city's shape to a circle, the modified Uii (MUii) was calculated considering the realistic horizontal distribution of the urban lands. We selected 45 urban stations in mainland China, and then selected an adjacent station for each urban station to constitute a station pair for which the background climate changes are nearly homogeneous. Thus, difference in the trends of annual averaged daily mean SAT (Trendmean), maximum SAT (Trendmax), and minimum SAT (Trendmin) between urban and adjacent stations (ΔTrend) could be mainly attributed to the difference in MUii changes between urban and adjacent stations (ΔMUii). Several linear regressions between ΔTrend and ΔMUii of 45 station pairs were calculated to estimate the UHI effects on Trendmean (UTmean), Trendmax (UTmax), and Trendmin (UTmin) of the 45 urban stations. The results showed that the mean MUii of the 45 urban stations has increased from 0.06 to 0.35 during 1992-2013. The positive correlations between ΔMUii and ΔTrend of the selected 45 station pairs were significant at the 0.001 significance level except for Trendmax. The average UTmean and UTmin of the 45 urban stations during 1954-2013 were approximately 0.05 and 0.11°C decade−1, respectively, accounting for 18 % and 31 % of the overall warming trends, respectively. The UTmin estimated in this study is about twice that of the previous result based on the regression equations between Uii and SAT trends.

ACS Style

Kai Jin; Fei Wang; Quanli Zong; Peng Qin; Chunxia Liu. An Updated Estimate of the Urban Heat Island Effect on Observed Local Warming Trends in Mainland China's 45 Urban Stations. Journal of the Meteorological Society of Japan. Ser. II 2020, 98, 787 -799.

AMA Style

Kai Jin, Fei Wang, Quanli Zong, Peng Qin, Chunxia Liu. An Updated Estimate of the Urban Heat Island Effect on Observed Local Warming Trends in Mainland China's 45 Urban Stations. Journal of the Meteorological Society of Japan. Ser. II. 2020; 98 (4):787-799.

Chicago/Turabian Style

Kai Jin; Fei Wang; Quanli Zong; Peng Qin; Chunxia Liu. 2020. "An Updated Estimate of the Urban Heat Island Effect on Observed Local Warming Trends in Mainland China's 45 Urban Stations." Journal of the Meteorological Society of Japan. Ser. II 98, no. 4: 787-799.

Data descriptor
Published: 31 July 2019 in Scientific Data
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Exploring global anthropogenic heat and its effects on climate change is necessary and meaningful to gain a better understanding of human–environment interactions caused by growing energy consumption. However, the variation in regional energy consumption and limited data availability make estimating long-term global anthropogenic heat flux (AHF) challenging. Thus, using high-resolution population density data (30 arc-second) and a top-down inventory-based approach, this study developed a new global gridded AHF dataset covering 1970–2050 based historically on energy consumption data from the British Petroleum (BP); future projections were built on estimated future energy demands. The globally averaged terrestrial AHFs were estimated at 0.05, 0.13, and 0.16 W/m2 in 1970, 2015, and 2050, respectively, but varied greatly among countries and regions. Multiple validation results indicate that the past and future global gridded AHF (PF-AHF) dataset has reasonable accuracy in reflecting AHF at various scales. The PF-AHF dataset has longer time series and finer spatial resolution than previous data and provides powerful support for studying long-term climate change at various scales.

ACS Style

Kai Jin; Fei Wang; Deliang Chen; Huanhuan Liu; Wenbin Ding; Shangyu Shi. A new global gridded anthropogenic heat flux dataset with high spatial resolution and long-term time series. Scientific Data 2019, 6, 1 -14.

AMA Style

Kai Jin, Fei Wang, Deliang Chen, Huanhuan Liu, Wenbin Ding, Shangyu Shi. A new global gridded anthropogenic heat flux dataset with high spatial resolution and long-term time series. Scientific Data. 2019; 6 (1):1-14.

Chicago/Turabian Style

Kai Jin; Fei Wang; Deliang Chen; Huanhuan Liu; Wenbin Ding; Shangyu Shi. 2019. "A new global gridded anthropogenic heat flux dataset with high spatial resolution and long-term time series." Scientific Data 6, no. 1: 1-14.

Research article
Published: 24 April 2019 in International Journal of Climatology
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Accurate vegetation cover data are important for realistic simulation of regional climate. The default vegetation parameters from Global Land Cover 2000, currently incorporated into global climate models and used in regional climate model RegCM, are not realistic for China, which may have contributed to serious bias in surface climate simulation. In this study, a new set of vegetation parameters considering the Plant Functional Type (PFT) fractions and the corresponding monthly leaf area index (PFT_LAI), were developed based on the land cover and MODIS LAI datasets. The regional climate model RegCM4.5 coupled with the land surface model CLM4.5 were utilized to test the performance of the new vegetation parameters by comparing simulations with observations using different surface parameters. The surface energy balance was analyzed to examine the effects of changed vegetation parameters on regional climate. The results showed that the new parameters were more accurate than the GLC2000 parameters when describing the distribution of crops, grassland, and forests over China. The improved vegetation parameters reduced model biases for winter air temperature and precipitation over southern China by 0.9°C and 8%, respectively, and reduced the winter temperature and summer precipitation biases over northeastern China by approximately 0.7°C and 8%, respectively. More accurate surface albedo are the main reasons for reductions in model bias. However, certain biases, such as the cold and dry bias over the Tibetan Plateau, still remained in the simulation results using our new vegetation data. This article is protected by copyright. All rights reserved.

ACS Style

Jiaojiao Gou; Fei Wang; Kai Jin; Xingmin Mu; Deliang Chen. More realistic land‐use and vegetation parameters in a regional climate model reduce model biases over China. International Journal of Climatology 2019, 39, 4825 -4837.

AMA Style

Jiaojiao Gou, Fei Wang, Kai Jin, Xingmin Mu, Deliang Chen. More realistic land‐use and vegetation parameters in a regional climate model reduce model biases over China. International Journal of Climatology. 2019; 39 (12):4825-4837.

Chicago/Turabian Style

Jiaojiao Gou; Fei Wang; Kai Jin; Xingmin Mu; Deliang Chen. 2019. "More realistic land‐use and vegetation parameters in a regional climate model reduce model biases over China." International Journal of Climatology 39, no. 12: 4825-4837.

Journal article
Published: 10 October 2018 in Climate Research
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ACS Style

Kai Jin; Fei Wang; Qiang Yu; Jiaojiao Gou; Huanhuan Liu. Varied degrees of urbanization effects on observed surface air temperature trends in China. Climate Research 2018, 76, 131 -143.

AMA Style

Kai Jin, Fei Wang, Qiang Yu, Jiaojiao Gou, Huanhuan Liu. Varied degrees of urbanization effects on observed surface air temperature trends in China. Climate Research. 2018; 76 (2):131-143.

Chicago/Turabian Style

Kai Jin; Fei Wang; Qiang Yu; Jiaojiao Gou; Huanhuan Liu. 2018. "Varied degrees of urbanization effects on observed surface air temperature trends in China." Climate Research 76, no. 2: 131-143.

Journal article
Published: 20 January 2018 in Sustainability
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Vegetation cover is crucial for the sustainability of urban ecosystems; however, this cover has been undergoing substantial changes in cities. Based on climate data, city statistical data, nighttime light data and the Normalized Difference Vegetation Index (NDVI) dataset, we investigate the spatiotemporal variations of climate factors, urban lands and vegetation cover in 71 large cities of China during 1998–2012, and explore their correlations. A regression model between growing-season NDVI (G-NDVI) and urban land proportion (PU) is built to quantify the impact of urbanization on vegetation cover change. The results indicate that the spatiotemporal variations of temperature, precipitation, PU and G-NDVI are greatly different among the 71 cities which experienced rapid urbanization. The spatial difference of G-NDVI is closely related to diverse climate conditions, while the inter-annual variations of G-NDVI are less sensitive to climate changes. In addition, there is a negative correlation between G-NDVI trend and PU change, indicating vegetation cover in cities have been negatively impacted by urbanization. For most of the inland cities, the urbanization impacts on vegetation cover in urban areas are more severe than in suburban areas. But the opposite occurs in 17 cities mainly located in the coastal areas which have been undergoing the most rapid urbanization. Overall, the impacts of urbanization on G-NDVI change are estimated to be −0.026 per decade in urban areas and −0.015 per decade in suburban areas during 1998–2012. The long-term developments of cities would persist and continue to impact on the environmental change and sustainability. We use a 15-year window here as a case study, which implies the millennia of human effects on the natural biotas and warns us to manage landscapes and preserve ecological environments properly.

ACS Style

Kai Jin; Fei Wang; Pengfei Li. Responses of Vegetation Cover to Environmental Change in Large Cities of China. Sustainability 2018, 10, 270 .

AMA Style

Kai Jin, Fei Wang, Pengfei Li. Responses of Vegetation Cover to Environmental Change in Large Cities of China. Sustainability. 2018; 10 (1):270.

Chicago/Turabian Style

Kai Jin; Fei Wang; Pengfei Li. 2018. "Responses of Vegetation Cover to Environmental Change in Large Cities of China." Sustainability 10, no. 1: 270.

Article
Published: 25 June 2015 in Climatic Change
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This study aims at qualifying the contribution of the urban effect to the total warming recorded by 45 urban or suburban stations in China where rapid and extensive urbanization over the last few decades occurred. Partly due to differences in urbanization and stations’ geographic location, the total warming trends for 1955–2012 vary from of −0.10 to 0.49 °C and −0.03 to 0.64 °C per decade for the annual averaged daily mean and daily minimum temperature, respectively. A principal component analysis of seven factors on the siting and geographical coordinates of the meteorological stations shows three dominant factors (urban size, relative position of meteorological station to city center and geographic location of station) accounting for 87.1 % of the total explained variance. An index quantifying the impact of the first two dominating factors of the urban effect is proposed considering also the dominating wind direction. The positive correlation between the temperature trends and the index is significant (P < 0.05), indicating that urbanization has significantly influenced the warming trends at these stations. The average contribution of the urbanization for all the stations to the total mean temperature trend is estimated to be 19 %.

ACS Style

Kai Jin; Fei Wang; Deliang Chen; Qiao Jiao; Lei Xia; Luuk Fleskens; Xingmin Mu. Assessment of urban effect on observed warming trends during 1955–2012 over China: a case of 45 cities. Climatic Change 2015, 132, 631 -643.

AMA Style

Kai Jin, Fei Wang, Deliang Chen, Qiao Jiao, Lei Xia, Luuk Fleskens, Xingmin Mu. Assessment of urban effect on observed warming trends during 1955–2012 over China: a case of 45 cities. Climatic Change. 2015; 132 (4):631-643.

Chicago/Turabian Style

Kai Jin; Fei Wang; Deliang Chen; Qiao Jiao; Lei Xia; Luuk Fleskens; Xingmin Mu. 2015. "Assessment of urban effect on observed warming trends during 1955–2012 over China: a case of 45 cities." Climatic Change 132, no. 4: 631-643.