Hubei Collaborative Innovation Center for High Efficiency Utilization of Solar Energy

Wuhan, China

Hubei Collaborative Innovation Center for High Efficiency Utilization of Solar Energy

Wuhan, China
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Wang W.,Wuhan University | Mao F.,Wuhan University | Mao F.,Collaborative Innovation Center for Geospatial Technology | Pan Z.,Wuhan University | And 4 more authors.
Remote Sensing | Year: 2017

Visible Infrared Imaging Radiometer Suite (VIIRS) is a next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. A comprehensive validation of VIIRS products is significant for improving product quality, assessing environment quality for human life, and studying regional climate change. In this study, three-year (from 1 January 2014 to 31 December 2016) records of VIIRS Intermediate Product (IP) data and Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals on aerosol optical depth (AOD) at 550 nm were evaluated by comparing them to ground sun photometer measurements over Wuhan. Results indicated that VIIRS IP retrievals were underestimated by 5% for the city. A comparison of VIIRS IP retrievals and ground sun photometer measurements showed a lower R2 of 0.55 (0.79 for Terra-MODIS and 0.76 for Aqua-MODIS), with only 52% of retrievals falling within the expected error range established by MODIS over land (i.e., ±(0.05 + 0.15AOD)). Bias analyses with different Ångström exponents (AE) demonstrated that land aerosol model selection of the VIIRS retrieval overWuhan was appropriate. However, the larger standard deviations (i.e., uncertainty) of VIIRS AODs than MODIS AODs could be attributed to the less robust retrieval algorithm. Monthly variations displayed largely underestimated AODs of VIIRS in winter, which could be caused by a large positive bias in surface reflectance estimation due to the sparse vegetation and greater surface brightness ofWuhan in this season. The spatial distribution of VIIRS and MODIS AOD observations revealed that the VIIRS IP AODs over high-pollution areas (AOD > 0.8) with sparse vegetation were underestimated by more than 20% in Wuhan, and 40% in several regions. Analysis of several clear rural areas (AOD < 0.2) with native vegetation indicated an overestimation of about 20% in the northeastern region of the city. These findings showed that the VIIRS IP AOD at 550 nm can provide a solid dataset with a high resolution (750 m) for quantitative scientific investigations and environmental monitoring over Wuhan. However, the performance of dark target algorithms in VIIRS was associated with aerosol types and ground vegetation conditions. © 2017 by the authors.


Pan Z.,Wuhan University | Mao F.,Wuhan University | Mao F.,Collaborative Innovation Center for Geospatial Technology | Gong W.,Wuhan University | And 5 more authors.
Remote Sensing of Environment | Year: 2017

The Tibetan Plateau (TP) has experienced evident warming in recent decades, but the exact reasons for this warming remain unclear. In this study, we investigated the possible effect of the three-dimensional (3D) variations of cloud during daytime on climate warming over the TP from 2007 to 2015 based on CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations. We found that the 3D changes occur mostly to low clouds, whose fraction and geometrical depth decrease by approximately 4.2% and 130 m, respectively. These changes result in the increase of the surface shortwave radiation (SSR) by approximately 29.7 W/m2, which is one magnitude larger than that of anthropogenic CO2. The increase in SSR leads to the increase in direct solar radiation absorption in the surface, which significantly enhances the warming of the TP. © 2016


Mao F.,Wuhan University | Mao F.,Collaborative Innovation Center for Geospatial Technology | Mao F.,Hubei Collaborative Innovation Center for High efficiency Utilization of Solar Energy | Li J.,Wuhan University of Science and Technology | And 6 more authors.
Optics Express | Year: 2015

Layer boundary (base and top) detection is a basic problem in lidar data processing, the results of which are used as inputs of optical properties retrieval. However, traditional algorithms not only require manual intervention but also rely heavily on the signal-to-noise ratio. Therefore, we propose a robust and automatic algorithm for layer detection based on a novel algorithm for lidar signal segmentation and representation. Our algorithm is based on the lidar equation and avoids most of the limitations of the traditional algorithms. Testing of the simulated and real signals shows that the algorithm is able to position the base and top accurately even with a low signal to noise ratio. Furthermore, the results of the classification are accurate and satisfactory. The experimental results confirm that our algorithm can be used for automatic detection, retrieval, and analysis of lidar data sets. © 2015 Optical Society of America.


Li C.,Wuhan University | Pan Z.,Wuhan University | Mao F.,Wuhan University | Mao F.,Collaborative Innovation Center for Geospatial Technology | And 7 more authors.
Optics Express | Year: 2015

The signal-to-noise ratio (SNR) of an atmospheric lidar decreases rapidly as range increases, so that maintaining high accuracy when retrieving lidar data at the far end is difficult. To avoid this problem, many de-noising algorithms have been developed; in particular, an effective denoising algorithm has been proposed to simultaneously retrieve lidar data and obtain a de-noised signal by combining the ensemble Kalman filter (EnKF) and the Fernald method. This algorithm enhances the retrieval accuracy and effective measure range of a lidar based on the Fernald method, but sometimes leads to a shift (bias) in the near range as a result of the over-smoothing caused by the EnKF. This study proposes a new scheme that avoids this phenomenon using a particle filter (PF) instead of the EnKF in the de-noising algorithm. Synthetic experiments show that the PF performs better than the EnKF and Fernald methods. The root mean square error of PF are 52.55% and 38.14% of that of the Fernald and EnKF methods, and PF increases the SNR by 44.36% and 11.57% of that of the Fernald and EnKF methods, respectively. For experiments with real signals, the relative bias of the EnKF is 5.72%, which is reduced to 2.15% by the PF in the near range. Furthermore, the suppression impact on the random noise in the far range is also made significant via the PF. An extensive application of the PF method can be useful in determining the local and global properties of aerosols. © 2015 Optical Society of America.


Pan Z.,Wuhan University | Mao F.,Wuhan University | Mao F.,Collaborative Innovation Center for Geospatial Technology | Gong W.,Wuhan University | And 4 more authors.
Journal of Applied Remote Sensing | Year: 2016

Clouds' macrophysical characteristics play an important role in the climate system and dramatically vary because of the diverse climatic and geographic factors in China. We analyze cloud macrophysical characteristics and the differences between subregions in China (18°-54°N, 73°-135°E) from March 2012 to February 2015 based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, including cloud fractions, cloud vertical distribution, and cloud geometrical properties with the perspective of daytime and nighttime. We found that annual single layer, multilayer (ML), and total cloud fractions are 40.4±1.1%, 22.4±0.4%, and 62.8±1.5%, respectively, and clouds are generally located between 6 and 12 km. The cloud fractions in daytime are less than that in nighttime over the south while that of Tibet shows the reverse trend. In the vertical direction, except for Tibet, the clouds in nighttime have larger spatial coverage and are higher in altitude than that in daytime. The regional average values of cloud macrophysical characteristics in the south are highest, followed successively by Tibet, north, and northwest. Cloud geometrical depth and spacing show a gradually declining trend with the increase in layers and decrease of altitude in ML cloud system. © 2016 Society of Photo-Optical Instrumentation Engineers (SPIE).


Wang W.,Wuhan University | Gong W.,Wuhan University | Gong W.,Collaborative Innovation Center for Geospatial Technology | Gong W.,Hubei Collaborative Innovation Center for High Efficiency Utilization of Solar Energy | And 4 more authors.
Atmosphere | Year: 2016

The planetary boundary layer (PBL) is an atmospheric region near the Earth's surface. It is significant for weather forecasting and for the study of air quality and climate. In this study, the top of nocturnal residual layers-which are what remain of the daytime mixing layer-are estimated by an elastic backscatter Lidar in Wuhan (30.5°N, 114.4°E), a city in Central China. The ideal profile fitting method is widely applied to determine the nocturnal residual layer height (RLH) from Lidar data. However, the method is seriously affected by an optical thick layer. Thus, we propose an improved iterative fitting method to eliminate the optical thick layer effect on RLH detection using Lidar. Two typical case studies observed by elastic Lidar are presented to demonstrate the theory and advantage of the proposed method. Results of case analysis indicate that the improved method is more practical and precise than profile-fitting, gradient, and wavelet covariance transform method in terms of nocturnal RLH evaluation under low cloud conditions. Long-term observations of RLH performed with ideal profile fitting and improved methods were carried out in Wuhan from 28 May 2011 to 17 June 2016. Comparisons of Lidar-derived RLHs with the two types of methods verify that the improved solution is practical. Statistical analysis of a six-year Lidar signal was conducted to reveal the monthly average values of nocturnal RLH inWuhan. A clear RLH monthly cycle with a maximum mean height of about 1.8 km above ground level was observed in August, and a minimum height of about 0.7 km was observed in January. The variation in monthly mean RLH displays an obvious quarterly dependence, which coincides with the annual variation in local surface temperature.


Wang W.,Wuhan University | Gong W.,Wuhan University | Gong W.,Collaborative Innovation Center for Geospatial Technology | Gong W.,Hubei Collaborative Innovation Center for High Efficiency Utilization of Solar Energy | And 3 more authors.
Atmosphere | Year: 2015

A Raman Lidar (RL) system is developed to measure the water vapor mixing ratio (WVMR) and aerosol optical property in Wuhan with high temporal-spatial resolution during rainless nights. The principle of the self-developed lidar system and data processing method are discussed. WVMR profiles of a representative case retrieved by RL, Radiosonde (RS), and microwave radiometer (MR) are in good agreement. The relationship of WVMR and aerosol optical depth (AOD) indicates that water vapor dramatically reduces with the decline of the AOD. Moreover, the mean relative difference of mean WVMRs at low-troposphere obtained by RL and RS (MR) is about 5.17% (9.47%) during the analyzed year. The agreement certifies that the self-developed RL system can stably provide accurate and high temporal-spatial resolution data for the fundamental physical studies on water vapor. Furthermore, the maximum AOD from 0.5 km to 3 km is 0.41 at night in spring, which indicates that the air quality in Wuhan is heavily influenced by aerosols that are transported by air mass from the north during this time. Moreover, abundant rainfall led to relatively low AOD in summer (0.22), which demonstrates that water vapor is crucial for air purification. © 2015 by the authors.


Li H.,Wuhan University | Fan H.,Wuhan University | Mao F.,Wuhan University | Mao F.,Hubei Collaborative Innovation Center for High efficiency Utilization of Solar Energy
Atmosphere | Year: 2016

In recent years, frequent occurrences of significant air pollution events in China have routinely caused panic and are a major topic of discussion by the public and air pollution experts in government and academia. Therefore, this study proposed an efficient visualization method to represent directly, quickly, and clearly the spatio-temporal information contained in air pollution data. Data quality check and cleansing during a preliminary visual analysis is presented in tabular form, heat matrix, or line chart, upon which hypotheses can be deduced. Further visualizations were designed to verify the hypotheses and obtain useful findings. This method was tested and validated in a year-long case study of the air quality index (AQI of PM2.5) in Beijing, China. We found that PM2.5, PM10, and NO2 may be emitted by the same sources, and strong winds may accelerate the spread of pollutants. The average concentration of PM2.5 in Beijing was greater than the AQI value of 50 over the six-year study period. Furthermore, arable lands exhibited considerably higher concentrations of air pollutants than vegetation-covered areas. The findings of this study showed that our visualization method is intuitive and reliable through data quality checking and information sharing with multi-perspective air pollution graphs. This method allows the data to be easily understood by the public and inspire or aid further studies in other fields. © 2016 by the authors.


Gong W.,Wuhan University | Gong W.,Collaborative Innovation Center for Geospatial Technology | Gong W.,Hubei Collaborative Innovation Center for High efficiency Utilization of Solar Energy | Zhang M.,Wuhan University | And 3 more authors.
Atmosphere | Year: 2015

Aerosol scattering and absorption properties were continuously measured and analyzed at the urban Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS) site in Wuhan, central China, from 1 December 2009 to 31 March 2014. The mean aerosol scattering coefficient σs, absorption coefficient σab, and single scattering albedo (SSA) were 377.54 Mm-1, 119.06 Mm-1, and 0.73, respectively. Both σs and σab showed obvious annual variability with large values in winter and small values in summer, principally caused by the annual characteristics of meteorological conditions, especially planetary boundary layer height (PBLH) and local emissions. The SSA showed a slight annual variation. High values of SSA were related to formation of secondary aerosols in winter hazes and aerosol hygroscopic growth in humid summer. The large SSA in June can be attributed to the biomass combustion in Hubei and surrounding provinces. Both σs and σab showed double peak phenomena in diurnal variation resulting from the shallow stable PBLH at night and automobile exhaust emission during morning rush hours. The SSA also exhibited a double peak phenomenon related to the proportional variation of black carbon (BC) and light scattering particulates in the day and night. The long-term exploration on quantified aerosol optical properties can help offer scientific basis of introducing timely environmental policies for local government. © 2015 by the authors.


Wang W.,Wuhan University | Gong W.,Wuhan University | Gong W.,Collaborative Innovation Center for Geospatial Technology | Gong W.,Hubei Collaborative Innovation Center for High Efficiency Utilization of Solar Energy | And 5 more authors.
International Journal of Environmental Research and Public Health | Year: 2016

We comprehensively evaluated particle lidar ratios (i.e., particle extinction to backscatter ratio) at 532 nm overWuhan in Central China by using a Raman lidar from July 2013 to May 2015. We utilized the Raman lidar data to obtain homogeneous aerosol lidar ratios near the surface through the Raman method during no-rain nights. The lidar ratios were approximately 57 ± 7 sr, 50 ± 5 sr, and 22 ± 4 sr under the three cases with obviously different pollution levels. The haze layer below 1.8 km has a large particle extinction coefficient (from 5.4e-4 m-1 to 1.6e-4 m-1) and particle backscatter coefficient (between 1.1e-05 m-1sr-1 and 1.7e-06 m-1sr-1) in the heavily polluted case. Furthermore, the particle lidar ratios varied according to season, especially between winter (57 ± 13 sr) and summer (33 ± 10 sr). The seasonal variation in lidar ratios at Wuhan suggests that the East Asian monsoon significantly affects the primary aerosol types and aerosol optical properties in this region. The relationships between particle lidar ratios and wind indicate that large lidar ratio values correspond well with weak winds and strong northerly winds, whereas significantly low lidar ratio values are associated with prevailing southwesterly and southerly wind. © 2016 by the authors; licensee MDPI, Basel, Switzerland.

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