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Featured researches published by Aiwen Lin.


Geosciences Journal | 2012

Evaluating the monthly and interannual variation of net primary production in response to climate in Wuhan during 2001 to 2010

Wei Gong; Lunche Wang; Aiwen Lin; Miao Zhang

As the difference between photosynthesis, or gross primary productivity (GPP), and autotrophic respiration (RA), net primary productivity (NPP) is a key component of the terrestrial carbon cycle. The temporal and spatial response of NPP to climate change is thus one of the most important aspects in the study of climate-vegetation relationship. In this study, we developed a new method to estimate NPP accurately by finding a linear relationship between solar radiation and photosynthetically active radiation (PAR) and improving maximum light use efficiency (LUE) of vegetation, which could be adopted and used in other regions of the world. We utilize normalized difference vegetation index (NDVI) datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2010 and geographic information system (GIS) techniques to reveal the monthly and interannual change of NPP in Wuhan, China. We also applied the lagged cross-correlation analysis method to study the delayed and continuous effects on monthly and interannual variations of NPP to climatic factors (air temperature, precipitation, total radiation and sunshine percentage). The result showed that precipitation and total radiation were the major climatic factors influencing monthly variation of NPP, and sunshine percentage mostly determined the interannual variation of NPP for different vegetation. Monthly NPP showed significant positive correlation with total radiation of that month, and the effect could persist for one month; significant positive one month lagged correlation was also observed between monthly variation of NPP and precipitation, and the influences of changing climate on NPP would last for two months.


Remote Sensing | 2017

Aerosol Optical Properties and Associated Direct Radiative Forcing over the Yangtze River Basin during 2001–2015

Lijie He; Lunche Wang; Aiwen Lin; Ming Zhang; Muhammad Bilal; Minghui Tao

The spatiotemporal variation of aerosol optical depth at 550 nm (AOD550), Angstrom exponent at 470–660 nm (AE470–660), water vapor content (WVC), and shortwave (SW) instantaneous aerosol direct radiative effects (IADRE) at the top-of-atmosphere (TOA) in clear skies obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth’s Radiant Energy System (CERES) are quantitatively analyzed over the Yangtze River Basin (YRB) in China during 2001–2015. The annual and seasonal frequency distributions of AE470–660 and AOD550 reveal the dominance of fine aerosol particles over YRB. The regional average AOD550 is 0.49 ± 0.31, with high value in spring (0.58 ± 0.35) and low value in winter (0.42 ± 0.29). The higher AOD550 (≥0.6) is observed in midstream and downstream regions of YRB and Sichuan Basin due to local anthropogenic emissions and long-distance transport of dust particles, while lower AOD550 (≤0.3) is in high mountains of upstream regions. The IADRE is estimated using a linear relationship between SW upward flux and coincident AOD550 from CERES and MODIS at the satellite passing time. The regional average IADRE is −35.60 ± 6.71 Wm−2, with high value (−40.71 ± 6.86 Wm−2) in summer and low value (−29.19 ± 7.04 Wm−2) in winter, suggesting a significant cooling effect at TOA. The IADRE at TOA is lower over Yangtze River Delta (YRD) (≤−30 Wm−2) and higher in midstream region of YRB, Sichuan Basin and the source area of YRB (≥−45 Wm−2). The correlation coefficient between the 15-year monthly IADRE and AOD550 values is 0.63, which confirms the consistent spatiotemporal variation patterns over most of the YRB. However, a good agreement between IADRE and AOD is not observed in YRD and the source area of YRB, which is probably due to the combined effects of aerosol and surface properties.


Remote Sensing | 2018

Performance of the NPP-VIIRS and aqua-MODIS Aerosol Optical Depth Products over the Yangtze River Basin

Lijie He; Lunche Wang; Aiwen Lin; Ming Zhang; Muhammad Bilal; Jing Wei

The visible infrared imaging radiometer suite (VIIRS) environmental data record aerosol product (VIIRS_EDR) and the aqua-moderate resolution imaging spectroradiometer (MYD04) collection 6 (C6) aerosol optical depth (AOD) products are validated against the Cimel sun–photometer (CE318) AOD measurements during different air quality conditions over the Yangtze river basin (YRB) from 2 May 2012 to 31 December 2016. For VIIRS_EDR, the AOD observations are obtained from the scientific data set (SDS) “aerosol optical depth at 550 nm” at 6 km resolution, and for aqua-MODIS, the AOD observations are obtained from the SDS “image optical depth land and ocean” at 3 km (DT3K) and 10 km (DT10K) resolutions, “deep blue aerosol optical depth 550 land” at 10 km resolution (DB10K), and “AOD 550 dark target deep blue combined” at 10 km resolution (DTB10K). Results show that the high-quality (QF = 3) DTB10K performs the best against the CE318 AOD observations, along with a higher R (0.85) and more retrievals within the expected error (EE) ± (0.05 + 15%) (55%). Besides, there is a 10% overestimation, but the positive bias does not exhibit obvious seasonal variations. Similarly, the DT3K and DT10K products overestimate AOD retrievals by 23% and 15%, respectively, all over the year, but the positive biases become larger in spring and summer. For the DB10K AOD retrievals, there is an overestimation (underestimation) in autumn and winter (spring and summer). Compared to the aqua-MODIS AOD products, the VIIRS_EDR AOD retrievals are less correlated (R = 0.73) and only 44% of the retrievals fall within EE. Meanwhile, the VIIRS_EDR shows larger bias than the aqua-MODIS C6 retrievals, and tends to overestimate AOD retrievals in summer and underestimate in winter. Additionally, there is an underestimation for the VIIRS_EDR AOD retrievals over the regions during high aerosol loadings. These indicate that the VIIRS_EDR retrieval algorithm needs to be improved in further applications over the YRB.


Remote Sensing | 2016

Evaluation of MODIS Gross Primary Production across Multiple Biomes in China Using Eddy Covariance Flux Data

Hongji Zhu; Aiwen Lin; Lunche Wang; Yu Xia; Ling Zou

MOD17A2 provides near real-time estimates of gross primary production (GPP) globally. In this study, MOD17A2 GPP was evaluated using eddy covariance (EC) flux measurements at eight sites in five various biome types across China. The sensitivity of MOD17A2 to meteorological data and leaf area index/fractional photosynthetically active radiation (LAI/FPAR) products were examined by introducing site meteorological measurements and improved Global Land Surface Satellite (GLASS) LAI products. We also assessed the potential error contributions from land cover and maximum light use efficiency (emax). The results showed that MOD17A2 agreed well with flux measurements of annual GPP (R2 = 0.76) when all biome types were considered as a whole. However, MOD17A2 was ineffective for estimating annual GPP at mixed forests, evergreen needleleaf forests and croplands, respectively. Moreover, MOD17A2 underestimated flux derived GPP during the summer (R2 = 0.46). It was found that the meteorological data used in MOD17A2 failed to properly estimate the site measured vapor pressure deficits (VPD) (R2 = 0.31). Replacing the existing LAI/FPAR data with GLASS LAI products reduced MOD17A2 GPP uncertainties. Though land cover presented the fewest errors, emax prescribed in MOD17A2 were much lower than inferred emax calculated from flux data. Thus, the qualities of meteorological data and LAI/FPAR products need to be improved, and emax should be adjusted to provide better GPP estimates using MOD17A2 for Chinese ecosystems.


Earth Interactions | 2016

Characteristics of Long-Term Climate Change and the Ecological Responses in Central China

Aiwen Lin; Hongji Zhu; Lunche Wang; Wei Gong; Ling Zou

AbstractMeasurements of air temperature and precipitation at 35 stations in Hubei Province, China, during 1962–2011 are used to investigate the regional climate change. There is an increasing trend for observed air temperature (0.23°C decade−1), which is slightly higher than that from multiple model simulations/predictions [phase 5 of CMIP (CMIP5) datasets] (0.16°C decade−1). The observed precipitation increases at the rate of 11.4 mm decade−1, while the CMIP5 results indicate a much lower decreasing trend (0.8 mm decade−1) in this region. To examine the ecological responses to the climate changes in Hubei Province, annual gross primary productivity (GPP) and net primary productivity (NPP) products during 2000–10 and leaf area index (LAI) products during 1981–2011 are also analyzed. It is discovered that GPP, NPP, and LAI increase at the rate of 1.8 TgC yr−1 yr−1, 1.1 TgC yr−1 yr−1, and 0.14 m2 m−2 decade−1, respectively. A linear model is further used to conduct the correlation analyses between climatic ...


Remote Sensing | 2017

Evaluation of the Latest MODIS GPP Products across Multiple Biomes Using Global Eddy Covariance Flux Data

Lunche Wang; Hongji Zhu; Aiwen Lin; Ling Zou; Wenmin Qin; Qiyong Du

The latest MODIS GPP (gross primary productivity) product, MOD17A2H, has great advantages over the previous version, MOD17A2, because the resolution increased from 1000 m to 500 m. In this study, MOD17A2H GPP was assessed using the latest eddy covariance (EC) flux data (FLUXNET2015 Dataset) at eighteen sites in six ecosystems across the globe. The sensitivity of MOD17A2H GPP to the meteorology dataset and the fractional photosynthetically- active radiation (FPAR) product was explored by introducing site meteorology observations and improved Global Land Surface Satellite (GLASS) Leaf Area Index (LAI) products. The results showed that MOD17A2H GPP underestimated flux-derived GPP at most sites. Its performance in estimating annual GPP was poor (R2 = 0.62) and even worse over eight days (R2 = 0.52). For the MOD17A2H algorithm, replacing the reanalysis meteorological datasets with the site meteorological measurements failed to improve the estimation accuracies. However, great improvements in estimating the site-based GPP were gained by replacing MODIS FPAR with GLASS FPAR. This indicated that in the existing MOD17A2H product, the errors were originated more from FPAR than the meteorological data. We further examined the potential error contributions from land cover classification and maximum light use efficiency (emax). It was found that the current land cover classification scheme exhibited frequent misclassification errors. Moreover, the emax value assigned in MOD17A2H was much smaller than the inferred emax value. Therefore, the qualities of FPAR and land cover classification datasets should be upgraded, and the emax value needs to be adjusted to provide more accurate GPP estimates using MOD17A2H for global ecosystems.


Remote Sensing | 2018

Characteristic and Driving Factors of Aerosol Optical Depth over Mainland China during 1980–2017

Wenmin Qin; Ying Liu; Lunche Wang; Aiwen Lin; Xiangao Xia; Huizheng Che; Muhammad Bilal; Ming Zhang

Since the reform and opening up of China, the increasing aerosol emissions have posted great challenges to the country’s climate change and human health. The aerosol optical depth (AOD) is one of the main physical indicators quantifying the atmospheric turbidity and air pollution. In this study, 38-years (1980–2017) of spatial and temporal variations of AOD in China were analyzed using AOD records derived from MODIS atmosphere products and the MERRA-2 dataset. The results showed that the annual mean AOD values throughout China have gone through an increasing, but fluctuating, trend, especially in 1982 and in 1992 due to two volcano eruptions; the AOD values experienced a dramatically increasing period during 2000–2007 with the rapid economic development and “population explosions” in China/after 2008, the AOD values gradually decreased from 0.297 (2008) to 0.257 (2017). The AOD values in China were generally higher in spring than that in other seasons. The Sichuan Basin has always been an area with high AOD values owing to the strong human activity and the basin topography (hindering aerosol diffusions in the air). In contrast, the Qinghai Tibet Plateau has always been an area with low AOD values due to low aerosol emissions and clear sky conditions there. The trend analysis of AOD values during 1980–2017 in China indicated that the significant increasing trend was mainly observed in Southeastern China. By contrast, the AOD values in the northernmost of China showed a significant decreasing trend. Then, the contributions (AODP) of the AOD for black carbon aerosol (BCAOD), dust aerosol (DUAOD), organic carbon aerosol (OCAOD), sea salt aerosol (SSAOD), and SO4 aerosol (SO4AOD) to the total AOD values were calculated. The results showed that DUAOD (25.43%) and SO4AOD (49.51%) were found to be the main driving factors for the spatial and temporal variations of AOD values. Finally, the effects of anthropogenic aerosol emissions, socioeconomic factors, and land-use and land coverage changes on AOD were analyzed. The GDP, population density, and passenger traffic volume were found to be the main socioeconomic drivers for AOD distributions. Relatively larger AOD values were mainly found in urban land and land covered by water, while lower AOD values were found in grassland and permanent glacier areas. Remote Sens. 2018, 10, 1064; doi:10.3390/rs10071064 www.mdpi.com/journal/remotesensing Remote Sens. 2018, 10, 1064 2 of 25


Applied Energy | 2013

Measurement and estimation of photosynthetically active radiation from 1961 to 2011 in Central China

Lunche Wang; Wei Gong; Chen Li; Aiwen Lin; Bo Hu; Yingying Ma


Journal of Atmospheric and Solar-Terrestrial Physics | 2016

Estimation of global solar radiation using an artificial neural network based on an interpolation technique in southeast China

Ling Zou; Lunche Wang; Aiwen Lin; Hongji Zhu; Yuling Peng; Zhenzhen Zhao


Renewable Energy | 2017

Prediction and comparison of solar radiation using improved empirical models and Adaptive Neuro-Fuzzy Inference Systems

Ling Zou; Lunche Wang; Li Xia; Aiwen Lin; Bo Hu; Hongji Zhu

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Lunche Wang

China University of Geosciences

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Bo Hu

Chinese Academy of Sciences

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Xiangao Xia

Chinese Academy of Sciences

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Muhammad Bilal

Hong Kong Polytechnic University

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