Zengxin Pan

Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan

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 Angstrom exponents (AE) demonstrated that land aerosol model selection of the VIIRS retrieval over Wuhan 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 of Wuhan 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.

Macrophysical and optical properties of clouds over East Asia measured by CALIPSO

The macrophysical and optical properties of clouds over East Asia (18°N–54°N, 73°E–145°E) from 1 March 2007 to 28 February 2015 are investigated using Cloud-Aerosol Lidar with Orthogonal Polarization data. Data analysis determines the macrophysical properties, such as cloud fraction, cloud vertical structure, cloud top height (CTH), cloud base height, and cloud geometrical depth (CGD), as well as the optical properties of clouds. Statistical analysis shows that the annual cloud fractions of single-layer (SL), multilayer (ML), and total clouds over East Asia are 41.4 ± 0.7%, 25.1 ± 0.9%, and 66.5 ± 1.6%, respectively, with a slight interannual variation. The maximum annual cloud fraction that appeared over the Sichuan Basin is mainly attributed to unique occlusive topographic features. Moreover, the annual vertical distribution of cloud occurrence frequency over East Asia presents a multipeak structure. Furthermore, at a height below 2 km, cloud frequency distribution exhibits a large peak over the south, north, northeast, eastern sea, and East Asia, a small peak over the northwest, and the smallest peak over Tibet, which is mainly ascribed to terrain topographies. For the average uppermost CTH and cloud fraction, the same seasonal characteristic is demonstrated; that is, CTH and cloud fraction are highest in summer and lowest in winter, except in the northwest. This seasonal characteristic mainly results from the East Asian summer monsoon circulation. Overall, the annual cloud optical depths (CODs) of SL, ML, and total cloud over East Asia are 0.98 ± 0.02, 0.83 ± 0.09, and 1.81 ± 0.12, respectively. Moreover, the COD of each layer is mainly below 0.5 (52.3%), and the second peak of probability (10.4%) exists from 2.5 to 3.0. The two crests of probability are caused by clouds of different types. Overall, the annual cloud layer over East Asia mainly consists of cirrus (44.4%), which indicates that cirrus clouds play a leading role. Most geometrically thick clouds (CGD > 2 km) are cirrus and deep convective clouds. In general, annual CGD decreases with the increase in the number of ML cloud system layers, and CGD increases with the increase in altitude, whereas the COD of each layer exhibits a reverse trend.

Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China

Monitoring fine particulate matter with diameters of less than 2.5 μm (PM2.5) is a critical endeavor in the Beijing–Tianjin–Hebei (BTH) region, which is one of the most polluted areas in China. Polar orbit satellites are limited by observation frequency, which is insufficient for understanding PM2.5 evolution. As a geostationary satellite, Himawari-8 can obtain hourly optical depths (AODs) and overcome the estimated PM2.5 concentrations with low time resolution. In this study, the evaluation of Himawari-8 AODs by comparing with Aerosol Robotic Network (AERONET) measurements showed Himawari-8 retrievals (Level 3) with a mild underestimate of about −0.06 and approximately 57% of AODs falling within the expected error established by the Moderate-resolution Imaging Spectroradiometer (MODIS) (±(0.05 + 0.15AOD)). Furthermore, the improved linear mixed-effect model was proposed to derive the surface hourly PM2.5 from Himawari-8 AODs from July 2015 to March 2017. The estimated hourly PM2.5 concentrations agreed well with the surface PM2.5 measurements with high R2 (0.86) and low RMSE (24.5 μg/m3). The average estimated PM2.5 in the BTH region during the study time range was about 55 μg/m3. The estimated hourly PM2.5 concentrations ranged extensively from 35.2 ± 26.9 μg/m3 (1600 local time) to 65.5 ± 54.6 μg/m3 (1100 local time) at different hours.

Measurement and Study of Lidar Ratio by Using a Raman Lidar in Central China

We comprehensively evaluated particle lidar ratios (i.e., particle extinction to backscatter ratio) at 532 nm over Wuhan 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.

Investigating the impact of haze on MODIS cloud detection

The cloud detection algorithm for passive sensors is usually based on a fuzzy logic system with thresholds determined from previous observations. In recent years, haze and high aerosol concentrations with high aerosol optical depth (AOD) occur frequently in China and may critically impact the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection. Thus, we comprehensively explore this impact by comparing the results from MODIS/Aqua (passive sensor), Cloud-Aerosol Lidar with Orthogonal Polarization/CALIPSO (lidar sensor), and Cloud Profiling Radar/CloudSat (microwave sensor) of the A-Train suite of instruments using an averaged AOD as an index for an aerosol concentration value. Case studies concerning the comparison of the three sensors indicate that MODIS cloud detection is reduced during haze events. In addition, statistical studies show that an increase in AOD creates an increase in the percentage of uncertain flags and a decrease in hit rate, a consistency index between consecutive sets of cloud retrievals. On average, AOD values lower than 0.1 give hit rate values up to 80.0% and uncertainty values lower than 16.8%, while AOD values greater than 1.0 reduce the hit rate below to 66.6% and increase the percentage of uncertain flags up to 46.6%. Therefore, we can conclude that the ability of MODIS cloud detection is weakened by large concentrations of aerosols. This suggests that use of the MODIS cloud mask, and derived higher-level products, in situations with haze requires caution. Further improvement of this retrieval algorithm is desired as haze studies based on MODIS products are of great interest in a number of related fields.

Observation of clouds macrophysical characteristics in China by CALIPSO

Abstract. 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.

Impacts of 3D Aerosol, Cloud, and Water Vapor Variations on the Recent Brightening during the South Asian Monsoon Season

South Asia is experiencing a levelling-off trend in solar radiation and even a transition from dimming to brightening. Any change in incident solar radiation, which is the only significant energy source of the global ecosystem, profoundly affects our habitats. Here, we use multiple observations of the A-Train constellation to evaluate the impacts of three-dimensional (3D) aerosol, cloud, and water vapor variations on the changes in surface solar radiation during the monsoon season (June–September) in South Asia from 2006 to 2015. Results show that surface shortwave radiation (SSR) has possibly increased by 16.2 W m−2 during this period. However, an increase in aerosol loading is inconsistent with the SSR variations. Instead, clouds are generally reduced and thinned by approximately 8.8% and 280 m, respectively, with a decrease in both cloud water path (by 34.7 g m−2) and particle number concentration under cloudy conditions. Consequently, the shortwave cloud radiative effect decreases by approximately 45.5 W m−2 at the surface. Moreover, precipitable water in clear-sky conditions decreases by 2.8 mm (mainly below 2 km), and related solar brightening increases by 2.5 W m−2. Overall, the decreases in 3D water vapor and clouds distinctly result in increased absorption of SSR and subsequent surface brightening.

Three-Dimensional Physical and Optical Characteristics of Aerosols over Central China from Long-Term CALIPSO and HYSPLIT Data

Aerosols greatly influence global and regional atmospheric systems, and human life. However, a comprehensive understanding of the source regions and three-dimensional (3D) characteristics of aerosol transport over central China is yet to be achieved. Thus, we investigate the 3D macroscopic, optical, physical, and transport properties of the aerosols over central China based on the March 2007 to February 2016 data obtained from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model. Our results showed that approximately 60% of the aerosols distributed over central China originated from local areas, whereas non-locally produced aerosols constituted approximately 40%. Anthropogenic aerosols constituted the majority of the aerosol pollutants (69%) that mainly distributed less than 2.0 km above mean sea level. Natural aerosols, which are mainly composed of dust, accounted for 31% of the total aerosols, and usually existed at an altitude higher than that of anthropogenic aerosols. Aerosol particles distributed in the near surface were smaller and more spherical than those distributed above 2.0 km. Aerosol optical depth (AOD) and the particulate depolarization ratio displayed decreasing trends, with a total decrease of 0.11 and 0.016 from March 2007 to February 2016, respectively. These phenomena indicate that during the study period, the extinction properties of aerosols decreased, and the degree of sphericity in aerosol particles increased. Moreover, the annual anthropogenic and natural AOD demonstrated decreasing trends, with a total decrease of 0.07 and 0.04, respectively. This study may benefit the evaluation of the effects of the 3D properties of aerosols on regional climates.

Evaluating the Governing Factors of Variability in Nocturnal Boundary Layer Height Based on Elastic Lidar in Wuhan

The atmospheric boundary layer (ABL), an atmospheric region near the Earth’s surface, is affected by surface forcing and is important for studying air quality, climate, and weather forecasts. In this study, long-term urban nocturnal boundary layers (NBLs) were estimated by an elastic backscatter light detection and ranging (LiDAR) with various methods in Wuhan (30.5° N, 114.4° E), a city in Central China. This study aims to explore two ABL research topics: (1) the relationship between NBL height (NBLH) and near-surface parameters (e.g., sensible heat flux, temperature, wind speed, and relative humidity) to elucidate meteorological processes governing NBL variability; and (2) the influence of NBLH variations in surface particulate matter (PM) in Wuhan. We analyzed the nocturnal ABL-dilution/ABL-accumulation effect on surface particle concentration by using a typical case. A long-term analysis was then performed from 5 December 2012–17 June 2016. Results reveal that the seasonal averages of nocturnal (from 20:00 to 05:00 next day, Chinese standard time) NBLHs are 386 ± 161 m in spring, 473 ± 154 m in summer, 383 ± 137 m in autumn, and 309 ± 94 m in winter. The seasonal variations in NBLH, AOD, and PM2.5 display a deep (shallow) seasonal mean NBL, consistent with a small (larger) seasonal mean PM2.5 near the surface. Seasonal variability of NBLH is partly linearly correlated with sensible heat flux at the surface (R = 0.72). Linear regression analyses between NBLH and other parameters show the following: (1) the positive correlation (R = 0.68) between NBLH and surface temperature indicates high (low) NBLH corresponding to warm (cool) conditions; (2) the slight positive correlation (R = 0.52) between NBLH and surface relative humidity in Wuhan; and (3) the weak positive correlation (R = 0.38) between NBLH and wind speed inside the NBL may imply that the latter is not an important direct driver that governs the seasonal variability of NBLH.

De-noising and retrieving algorithm of Mie lidar data based on the particle filter and the Fernald method

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 de-noising 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.