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Yong Luo
Tsinghua University

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Article
Published: 05 May 2021
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Evapotranspiration (ET) is the major component of the hydrology cycle. Satellites provide a convenient way for gathering information to estimate regional ET. The most widely applied method for converting the instantaneous satellite measurement to daily scale assumes that evaporative fraction (EF), defined as the ratio of ET to the available energy, is constant during the daytime. However, this method was proved to underestimate the daily ET. This study implemented a theoretically improved EF algorithm to calculate daily ET with the decoupling factor method based on the Penman-Monteith and McNaughton-Jarvis equations. Seven improved algorithms were developed by assuming that various parameters remain constant during the day. The satellite-based ET estimates were compared with seven local flux tower measurements in China. The results showed that: (1) The original ET method calculated the daily evaporation more accurately than the other algorithms. However, the good fit was based on two compensating inaccuracies. Compared to the flux tower measurement, the original ET method underestimated the daily EF by 26% and overestimated the daily net radiation by 30%. (2) Six of the seven proposed algorithms underpredicted the daily ET by 30-60%, mainly due to the inaccurate daily net radiation. (3) The algorithm that assumed that the instantaneous decoupling parameter Ω * was equal to its daily value method calculated EF and ET with the relative errors of 8% and 10% when the inaccurate estimated daily net radiation was replaced by the observed flux tower data.

ACS Style

Lei Huang; Tammo S SteenhuisiD; Yong LuoiD; Qiuhong Tang; Ronglin Tang; Junqing Zheng; Wen Shi; Chen Qiao. Revisiting daily MODIS evapotranspiration algorithm using flux tower measurements in China. 2021, 1 .

AMA Style

Lei Huang, Tammo S SteenhuisiD, Yong LuoiD, Qiuhong Tang, Ronglin Tang, Junqing Zheng, Wen Shi, Chen Qiao. Revisiting daily MODIS evapotranspiration algorithm using flux tower measurements in China. . 2021; ():1.

Chicago/Turabian Style

Lei Huang; Tammo S SteenhuisiD; Yong LuoiD; Qiuhong Tang; Ronglin Tang; Junqing Zheng; Wen Shi; Chen Qiao. 2021. "Revisiting daily MODIS evapotranspiration algorithm using flux tower measurements in China." , no. : 1.

Research article
Published: 12 February 2021 in International Journal of Climatology
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Atmospheric moisture transport (AMT) contributes significantly to the recent accelerated Arctic warming. However, the impact of AMT has not been well quantified, not to mention the relative contribution of its impact on microphysical latent heating (LAH) and longwave radiative heating (LWH). A series of Polar‐WRF model experiments with different magnitudes of AMT are conducted to study the response of winter Arctic temperature to AMT variations. Results show that atmospheric precipitable water is very sensitive to AMT variations and, thus can define the changes in surface air temperature by altering surface downward longwave radiation. Additionally, since evaporation and sublimation tend to balance the AMT induced moisture changes near the surface, LWH in the lower‐troposphere is determined by downward longwave radiation and, thus can be the dominant factor for temperature variations. However, temperature in the mid‐ and upper‐troposphere is primarily determined by changes in LAH, because the content of ice‐phase cloud aloft is significantly affected by AMT. In addition, the changes in LWH in the mid‐ and upper‐troposphere are governed by upward longwave radiation, thus offsetting some of the temperature variations. These findings have implications for the attribution of Arctic current warming and the prediction of its future temperature change.

ACS Style

Mingju Hao; Yanluan Lin; Yong Luo; Reshmita Nath; Zongci Zhao. The impact of atmospheric moisture transport on winter Arctic warming: Radiation versus latent heat release. International Journal of Climatology 2021, 41, 3982 -3993.

AMA Style

Mingju Hao, Yanluan Lin, Yong Luo, Reshmita Nath, Zongci Zhao. The impact of atmospheric moisture transport on winter Arctic warming: Radiation versus latent heat release. International Journal of Climatology. 2021; 41 (7):3982-3993.

Chicago/Turabian Style

Mingju Hao; Yanluan Lin; Yong Luo; Reshmita Nath; Zongci Zhao. 2021. "The impact of atmospheric moisture transport on winter Arctic warming: Radiation versus latent heat release." International Journal of Climatology 41, no. 7: 3982-3993.

Journal article
Published: 12 July 2020 in Atmosphere
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With the large-scale development of wind energy, wind power forecasting plays a key role in power dispatching in the electric power grid, as well as in the operation and maintenance of wind farms. The most important technology for wind power forecasting is forecasting wind speed. The current mainstream methods for wind speed forecasting involve the combination of mesoscale numerical meteorological models with a post-processing system. Our work uses the WRF model to obtain the numerical weather forecast and the gradient boosting decision tree (GBDT) algorithm to improve the near-surface wind speed post-processing results of the numerical weather model. We calculate the feature importance of GBDT in order to find out which feature most affects the post-processing wind speed results. The results show that, after using about 300 features at different height and pressure layers, the GBDT algorithm can output more accurate wind speed forecasts than the original WRF results and other post-processing models like decision tree regression (DTR) and multi-layer perceptron regression (MLPR). Using GBDT, the root mean square error (RMSE) of wind speed can be reduced from 2.7–3.5 m/s in the original WRF result by 1–1.5 m/s, which is better than DTR and MLPR. While the index of agreement (IA) can be improved by 0.10–0.20, correlation coefficient be improved by 0.10–0.18, Nash–Sutcliffe efficiency coefficient (NSE) be improved by −0.06–0.6. It also can be found that the feature which most affects the GBDT results is the near-surface wind speed. Other variables, such as forecast month, forecast time, and temperature, also affect the GBDT results.

ACS Style

Wenqing Xu; Like Ning; Yong Luo. Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm. Atmosphere 2020, 11, 738 .

AMA Style

Wenqing Xu, Like Ning, Yong Luo. Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm. Atmosphere. 2020; 11 (7):738.

Chicago/Turabian Style

Wenqing Xu; Like Ning; Yong Luo. 2020. "Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm." Atmosphere 11, no. 7: 738.

Journal article
Published: 17 March 2020 in Remote Sensing
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With the development of the wind power industry in China, accurate simulation of near-surface wind plays an important role in wind-resource assessment. Numerical weather prediction (NWP) models have been widely used to simulate the near-surface wind speed. By combining the Weather Research and Forecast (WRF) model with the Three-dimensional variation (3DVar) data assimilation system, our work applied satellite data assimilation to the wind resource assessment tasks of coastal wind farms in Guangdong, China. We compared the simulation results with wind speed observation data from seven wind observation towers in the Guangdong coastal area, and the results showed that satellite data assimilation with the WRF model can significantly reduce the root-mean-square error (RMSE) and improve the index of agreement (IA) and correlation coefficient (R). In different months and at different height layers (10, 50, and 70 m), the Root-Mean-Square Error (RMSE) can be reduced by a range of 0–0.8 m/s from 2.5–4 m/s of the original results, the IA can be increased by a range of 0–0.2 from 0.5–0.8 of the original results, and the R can be increased by a range of 0–0.3 from 0.2–0.7 of the original results. The results of the wind speed Weibull distribution show that, after data assimilation was used, the WRF model was able to simulate the distribution of wind speed more accurately. Based on the numerical simulation, our work proposes a combined wind resource evaluation approach of numerical modeling and data assimilation, which will benefit the wind power assessment of wind farms.

ACS Style

Wenqing Xu; Like Ning; Yong Luo. Applying Satellite Data Assimilation to Wind Simulation of Coastal Wind Farms in Guangdong, China. Remote Sensing 2020, 12, 973 .

AMA Style

Wenqing Xu, Like Ning, Yong Luo. Applying Satellite Data Assimilation to Wind Simulation of Coastal Wind Farms in Guangdong, China. Remote Sensing. 2020; 12 (6):973.

Chicago/Turabian Style

Wenqing Xu; Like Ning; Yong Luo. 2020. "Applying Satellite Data Assimilation to Wind Simulation of Coastal Wind Farms in Guangdong, China." Remote Sensing 12, no. 6: 973.

Article
Published: 06 January 2020 in Journal of Geographical Sciences
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Based on the Beijing Climate Center’s land surface model BCC_AVIM (Beijing Climate Center Atmosphere-Vegetation Interaction Model), the ensemble Kalman filter (EnKF) algorithm has been used to perform an assimilation experiment on the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) product to study the influence of satellite LST data frequencies on surface temperature data assimilations. The assimilation results have been independently tested and evaluated by Global Land Data Assimilation System (GLDAS) LST products. The results show that the assimilation scheme can effectively reduce the BCC_AVIM model simulation bias and the assimilation results reflect more reasonable spatial and temporal distributions. Diurnal variation information in the observation data has a significant effect on the assimilation results. Assimilating LST data that contain diurnal variation information can further improve the accuracy of the assimilation analysis. Overall, when assimilation is performed using observation data at 6-hour intervals, a relatively good assimilation result can be obtained, indicated by smaller bias (2.2K) and RMSE (>4K). Further analysis showed that the sensitivity of assimilation effect to diurnal variations in LST varies with time and space. The assimilation using observations with a time interval of 3 hours has the smallest bias in Oceania and Africa (both<1K); the use of 24-hour interval observation data for assimilation produces the smallest bias (<2.2K) in March, April and July.

ACS Style

Shiwen Fu; Suping Nie; Yong Luo; Xin Chen. Implications of diurnal variations in land surface temperature to data assimilation using MODIS LST data. Journal of Geographical Sciences 2020, 30, 18 -36.

AMA Style

Shiwen Fu, Suping Nie, Yong Luo, Xin Chen. Implications of diurnal variations in land surface temperature to data assimilation using MODIS LST data. Journal of Geographical Sciences. 2020; 30 (1):18-36.

Chicago/Turabian Style

Shiwen Fu; Suping Nie; Yong Luo; Xin Chen. 2020. "Implications of diurnal variations in land surface temperature to data assimilation using MODIS LST data." Journal of Geographical Sciences 30, no. 1: 18-36.

Research letter
Published: 21 November 2019 in Geophysical Research Letters
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Realistically representing the Arctic amplification in global climate models (GCMs) represents a key to accurately predict the climate system's response to increasing anthropogenic forcings. We examined the amplified Arctic warming over the past century simulated by 36 state‐of‐the‐art GCMs against observation. We found a clear difference between the simulations and the observation in terms of the evolution of the secular warming rates. The observed rates of the secular Arctic warming increase from 0.14°C/10a in the early 1890s to 0.21°C/10a in the mid‐2010s, while the GCMs show a negligible trend to 0.35°C/10a at the corresponding times. The overestimation of the secular warming rate in the GCMs starts from the mid‐20th century and aggravates with time. Further analysis indicates that the overestimation mainly comes from the exaggerated heating contribution from the Arctic sea ice melting. This result implies that the future secular Arctic warming may have been over‐projected.

ACS Style

Jianbin Huang; Tinghai Ou; Deliang Chen; Yong Luo; Zongci Zhao. The Amplified Arctic Warming in the Recent Decades may Have Been Overestimated by CMIP5 Models. Geophysical Research Letters 2019, 46, 13338 -13345.

AMA Style

Jianbin Huang, Tinghai Ou, Deliang Chen, Yong Luo, Zongci Zhao. The Amplified Arctic Warming in the Recent Decades may Have Been Overestimated by CMIP5 Models. Geophysical Research Letters. 2019; 46 (22):13338-13345.

Chicago/Turabian Style

Jianbin Huang; Tinghai Ou; Deliang Chen; Yong Luo; Zongci Zhao. 2019. "The Amplified Arctic Warming in the Recent Decades may Have Been Overestimated by CMIP5 Models." Geophysical Research Letters 46, no. 22: 13338-13345.

Original paper
Published: 13 February 2019 in Theoretical and Applied Climatology
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Using the Community Earth System Model (CESM)-Large Ensemble (LE) surface air temperature (SAT) data, we investigate the multidecadal changes in SAT variability over Central Indian landmass, particularly the Indo-Gangetic (IG) river basin. This region comes under the active influence of the Indian summer monsoon, and during the summer monsoon months (JJA), we observe an amplified cooling (< − 3 °C) trend (1961–2000) in SAT. This SAT trend is considered as a superposition of external forcings and natural climatic variability. The forced response is computed by averaging the trend in 35 ensemble members, which displays a moderate cooling trend due to aerosol-, ozone-, and volcano-only forcings. But the internal variability introduces a wide range of uncertainties in SAT, with majority of the members display a strong cooling trend in the Central Indian region. During the entire period, natural climatic variability dominates over the forced response, which strongly overrides the greenhouse gas (GHG) warming. Here, we separate out the influence of global climate variability on regional climate variability and identify the specific internal variability which is responsible for the multidecadal cooling trend in the analyzed region. Furthermore, we investigate the specific physical mechanism driving the cooling trend and analyze the role of Atlantic multidecadal oscillation (AMO) in its negative phase. The covariability is − 0.74, i.e., AMO accounts for ~ 55% of total variance in the multidecadal variability. In the negative phase of AMO, strong signals of Rossby waves emanating from North Atlantic Ocean propagate across the Eurasian continent, and in the latter half of the twentieth century, the effect of this cold sea surface temperature (SST) anomaly is felt in the Central Indian landmass (particularly over IG river basin) through teleconnection. This study will increase the predictability of multidecadal variability in SAT during summer monsoon season over the Central Indian region with AMO as a strong driving component.

ACS Style

Reshmita Nath; Yong Luo. Disentangling the influencing factors driving the cooling trend in boreal summer over Indo-Gangetic river basin, India: role of Atlantic multidecadal oscillation (AMO). Theoretical and Applied Climatology 2019, 138, 1 -12.

AMA Style

Reshmita Nath, Yong Luo. Disentangling the influencing factors driving the cooling trend in boreal summer over Indo-Gangetic river basin, India: role of Atlantic multidecadal oscillation (AMO). Theoretical and Applied Climatology. 2019; 138 (1-2):1-12.

Chicago/Turabian Style

Reshmita Nath; Yong Luo. 2019. "Disentangling the influencing factors driving the cooling trend in boreal summer over Indo-Gangetic river basin, India: role of Atlantic multidecadal oscillation (AMO)." Theoretical and Applied Climatology 138, no. 1-2: 1-12.

Research article
Published: 07 January 2019 in International Journal of Climatology
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Atmospheric moisture transport (AMT) is known to have an influence on the winter Arctic surface air temperature (SAT). However, a systematic investigation involving a verification of the physical linkages and spatial sensitivity within the Arctic, as well as a quantification of such contribution is still lacking. Our work first verifies the variation coherence between AMT and the SAT over the winters of 1979–2015, based on multiple data sets. Climate model projections reveal tendencies towards more frequent high values in both SAT and AMT from 2010–2065 relative to that from 1950–2005, as well as a high correlation coefficient between their detrended series. Then, a composite analysis is applied based on different AMT values. During high‐AMT episodes, enhanced AMT intrudes into the Arctic, with the Norwegian Sea as the gateway, and further induces unevenly distributed warming inside the Arctic. The greatest warming occurs in the Barents‐Kara Sea, which is tightly associated with the altered atmospheric moisture content and its subsequent changes of surface radiation balance. In addition, the intruding moisture can induce latent heat release and sea ice melting, which also influences the warming. Furthermore, by conducting numerical model experiments in the winter of 2012/13, a total warming effect of 9.66 °C averaged across the Arctic for the original AMT is revealed. By setting different incremental AMT values in five cases, the leading role of AMT is found to switch in the 0.5MT case (the case wherein the AMT value is 0.5 times the original) from altering the atmospheric moisture content to producing precipitation. This finding suggests that evenly spaced AMTs result in the alleviation of SAT increases.

ACS Style

Mingju Hao; Yong Luo; Yanluan Lin; Zongci Zhao; Lei Wang; Jianbin Huang. Contribution of atmospheric moisture transport to winter Arctic warming. International Journal of Climatology 2019, 39, 2697 -2710.

AMA Style

Mingju Hao, Yong Luo, Yanluan Lin, Zongci Zhao, Lei Wang, Jianbin Huang. Contribution of atmospheric moisture transport to winter Arctic warming. International Journal of Climatology. 2019; 39 (5):2697-2710.

Chicago/Turabian Style

Mingju Hao; Yong Luo; Yanluan Lin; Zongci Zhao; Lei Wang; Jianbin Huang. 2019. "Contribution of atmospheric moisture transport to winter Arctic warming." International Journal of Climatology 39, no. 5: 2697-2710.

Journal article
Published: 21 December 2018 in Scientific Reports
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The summer surface air temperature (SAT) in the Humid Subtropical Climate Zone in India, exhibits a significant cooling trend (~-3 °C/40 yrs.) in CRU observational data during 1961-2000. Here we investigate the contribution of internal and external factors, which are driving this cooling trend. Using the Community Earth System Model-Large Ensemble (CESM-LE), we analyze the historical climate change in presence of internal climate variability. Most of the model ensemble members could reproduce this amplified cooling (<-3 °C) as shown from CRU data. Further analyses reveals that external forcing displays a strong cooling effect over this region, while internal variability displays mixed cooling (in most cases) and warming signals. The signal to noise ratio i.e. the ratio of external forcings and internal climatic variability is less than 1, which indicates that internal climatic variability dominates over the forced response. Furthermore, to quantify the role of different external forcing factors we used the CCSM4 single forcing simulations. The simulation results from CESM-LE and CCSM4 suggest that the cooling trend over the region is primarily due to the combined influence of internal variability (~73%) and partly due to aerosol (~10%) and ozone only forcing, which strongly mask the warming effect of GHG and solar forcing.

ACS Style

Reshmita Nath; Yong Luo; Wen Chen; Xuefeng Cui. On the contribution of internal variability and external forcing factors to the Cooling trend over the Humid Subtropical Indo-Gangetic Plain in India. Scientific Reports 2018, 8, 18047 .

AMA Style

Reshmita Nath, Yong Luo, Wen Chen, Xuefeng Cui. On the contribution of internal variability and external forcing factors to the Cooling trend over the Humid Subtropical Indo-Gangetic Plain in India. Scientific Reports. 2018; 8 (1):18047.

Chicago/Turabian Style

Reshmita Nath; Yong Luo; Wen Chen; Xuefeng Cui. 2018. "On the contribution of internal variability and external forcing factors to the Cooling trend over the Humid Subtropical Indo-Gangetic Plain in India." Scientific Reports 8, no. 1: 18047.

Journal article
Published: 22 February 2018 in Nature Climate Change
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ACS Style

Jianbin Huang; Xiangdong Zhang; Qiyi Zhang; Yanluan Lin; Mingju Hao; Yong Luo; Zongci Zhao; Yao Yao; Xin Chen; Lei Wang; Suping Nie; Yizhou Yin; Ying Xu; Jiansong Zhang. Publisher Correction: Recently amplified arctic warming has contributed to a continual global warming trend. Nature Climate Change 2018, 8, 345 -345.

AMA Style

Jianbin Huang, Xiangdong Zhang, Qiyi Zhang, Yanluan Lin, Mingju Hao, Yong Luo, Zongci Zhao, Yao Yao, Xin Chen, Lei Wang, Suping Nie, Yizhou Yin, Ying Xu, Jiansong Zhang. Publisher Correction: Recently amplified arctic warming has contributed to a continual global warming trend. Nature Climate Change. 2018; 8 (4):345-345.

Chicago/Turabian Style

Jianbin Huang; Xiangdong Zhang; Qiyi Zhang; Yanluan Lin; Mingju Hao; Yong Luo; Zongci Zhao; Yao Yao; Xin Chen; Lei Wang; Suping Nie; Yizhou Yin; Ying Xu; Jiansong Zhang. 2018. "Publisher Correction: Recently amplified arctic warming has contributed to a continual global warming trend." Nature Climate Change 8, no. 4: 345-345.

Letter
Published: 20 November 2017 in Nature Climate Change
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The existence and magnitude of the recently suggested global warming hiatus, or slowdown, have been strongly debated1,2,3. Although various physical processes4,5,6,7,8 have been examined to elucidate this phenomenon, the accuracy and completeness of observational data that comprise global average surface air temperature (SAT) datasets is a concern9,10. In particular, these datasets lack either complete geographic coverage or in situ observations over the Arctic, owing to the sparse observational network in this area9. As a consequence, the contribution of Arctic warming to global SAT changes may have been underestimated, leading to an uncertainty in the hiatus debate. Here, we constructed a new Arctic SAT dataset using the most recently updated global SATs2 and a drifting buoys based Arctic SAT dataset11 through employing the ‘data interpolating empirical orthogonal functions’ method12. Our estimate of global SAT rate of increase is around 0.112 °C per decade, instead of 0.05 °C per decade from IPCC AR51, for 1998–2012. Analysis of this dataset shows that the amplified Arctic warming over the past decade has significantly contributed to a continual global warming trend, rather than a hiatus or slowdown.

ACS Style

Jianbin Huang; Xiangdong Zhang; Qiyi Zhang; Yanluan Lin; Mingju Hao; Yong Luo; Zongci Zhao; Yao Yao; Xin Chen; Lei Wang; Suping Nie; Yizhou Yin; Ying Xu; Jiansong Zhang. Recently amplified arctic warming has contributed to a continual global warming trend. Nature Climate Change 2017, 7, 875 -879.

AMA Style

Jianbin Huang, Xiangdong Zhang, Qiyi Zhang, Yanluan Lin, Mingju Hao, Yong Luo, Zongci Zhao, Yao Yao, Xin Chen, Lei Wang, Suping Nie, Yizhou Yin, Ying Xu, Jiansong Zhang. Recently amplified arctic warming has contributed to a continual global warming trend. Nature Climate Change. 2017; 7 (12):875-879.

Chicago/Turabian Style

Jianbin Huang; Xiangdong Zhang; Qiyi Zhang; Yanluan Lin; Mingju Hao; Yong Luo; Zongci Zhao; Yao Yao; Xin Chen; Lei Wang; Suping Nie; Yizhou Yin; Ying Xu; Jiansong Zhang. 2017. "Recently amplified arctic warming has contributed to a continual global warming trend." Nature Climate Change 7, no. 12: 875-879.

Book chapter
Published: 07 November 2015 in Springer Environmental Science and Engineering
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This chapter addresses climate change of instrumental era in China, including changes in the distribution and regional characteristics of the temperature, precipitation, Asian monsoon, general circulations, extreme weather and climate events, cryosphere (glaciers, frozen ground, and snow cover), sea-level rise, sea surface temperature (SST), and salinity. It also assesses climate variations on different timescales (130, 20, 10, 2, and 0.5 ka) based on proxy archives such as sediments, ice cores, tree rings, and historical documents. Lastly, the advances in numerical paleoclimate simulation are summarized.

ACS Style

Yong Luo; Dahe Qin; Renhe Zhang; Shaowu Wang; De’Er Zhang. Climatic and Environmental Changes in China. Springer Environmental Science and Engineering 2015, 29 -45.

AMA Style

Yong Luo, Dahe Qin, Renhe Zhang, Shaowu Wang, De’Er Zhang. Climatic and Environmental Changes in China. Springer Environmental Science and Engineering. 2015; ():29-45.

Chicago/Turabian Style

Yong Luo; Dahe Qin; Renhe Zhang; Shaowu Wang; De’Er Zhang. 2015. "Climatic and Environmental Changes in China." Springer Environmental Science and Engineering , no. : 29-45.

Book chapter
Published: 07 November 2015 in Springer Environmental Science and Engineering
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This chapter brings together key information contained in “Evolving Climate and Environment in China: 2012,” a Chinese monograph. Significant warming in China for the last 100 years is unequivocal, confirmed by substantial observational data. Anthropogenic activities are very likely the key driver of the warming in China since the 1950s. Climate change has significantly impacted the eco- environment and socio-economy of China. The fast increase in greenhouse gas emissions from China is due to the rapid growth of China’s economy and its position in the world economy. Climate change projects show warming in China will continue throughout the twenty-first century. Technological and policy options for adaptation and mitigation are critical to China’s actions on climate change. Green industrialization and low-carbon urbanization are essential for sustainable development. The future research priorities and goals are also summarized.

ACS Style

Dahe Qin; Yong Luo; Guangyu Shi; Yongjian Ding; Wenjie Dong; Erda Lin; Jiahua Pan. Concluding Remarks. Springer Environmental Science and Engineering 2015, 139 -152.

AMA Style

Dahe Qin, Yong Luo, Guangyu Shi, Yongjian Ding, Wenjie Dong, Erda Lin, Jiahua Pan. Concluding Remarks. Springer Environmental Science and Engineering. 2015; ():139-152.

Chicago/Turabian Style

Dahe Qin; Yong Luo; Guangyu Shi; Yongjian Ding; Wenjie Dong; Erda Lin; Jiahua Pan. 2015. "Concluding Remarks." Springer Environmental Science and Engineering , no. : 139-152.