Huizheng Che

Data Quality Assessment and the Long-Term Trend of Ground Solar Radiation in China

Abstract Solar radiation is one of the most important factors affecting climate and the environment. Routine measurements of irradiance are valuable for climate change research because of long time series and areal coverage. In this study, a set of quality assessment (QA) algorithms is used to test the quality of daily solar global, direct, and diffuse radiation measurements taken at 122 observatories in China during 1957–2000. The QA algorithms include a physical threshold test (QA1), a global radiation sunshine duration test (QA2), and a standard deviation test applied to time series of annually averaged solar global radiation (QA3). The results show that the percentages of global, direct, and diffuse solar radiation data that fail to pass QA1 are 3.07%, 0.01%, and 2.52%, respectively; the percentages of global solar radiation data that fail to pass the QA2 and QA3 are 0.77% and 0.49%, respectively. The method implemented by the Global Energy Balance Archive is also applied to check the data quality of ...

Visual range trends in the Yangtze River Delta Region of China, 1981-2005.

ABSTRACT Visual range (VR) data from 1981 to 2005 were examined for 20 meteorological monitoring sites in the Yangtze River Delta Region of China. Cumulative percentile analysis was used to construct VR trend. The 25-yr average domain-average 50% VR was approximately 21.9 ±1.9 km. Domain-average 50% VR decreased from 1981 to 2005 with a trend of −2.41 km/decade. The worst 20% and 50% and best 20% VR and variation rates for the 20 sites were analyzed. The 50% VR of the town, county-level city, and prefecture-level city sites were 24.1, 21.5, and 19.4 km, respectively. The best 20% VR decreased fastest with a rate of −3.5 km/decade. Regional median VR decreased from the coastal sites to the inland sites. Ridit analysis and cumulative percentile were adopted to study the VR variation properties between economically developed areas (e.g., Nanjing and Hangzhou) and remote areas (e.g., Lvsi). The two analyses show that VR decreased in Nanjing and Hangzhou but remained constant in Lvsi from 1981 to 2005. IMPLICATIONS Decreasing VR corresponds to greater industrialization and particulate concentrations. Moving pollution sources from the coastal to inland locations only moves the decreasing visibility elsewhere. This work offered a good opportunity to comprehend the VR variation in the most developed region of China over the last 2 decades.

Characteristics of visibility and particulate matter (PM) in an urban area of Northeast China

The visibility data from 2010 to 2012 were obtained at Shenyang in Northeast China and the relations between visibility, PM mass concentration and meteorological variables were statistically analyzed. These results demonstrate that the monthly–averaged visibility over Shenyang was higher in March and September with values of approximately 19.0±4.3 km and 17.1±4.3 km, respectively. Low visibility over Shenyang occurred in January at approximately 11.0±4.7 km. Among the meteorological variables considered, wind speed was the main meteorological factor that influenced visibility and PM mass concentrations. The relation between visibility and PM indicates that fine particles are already a main source of pollutants, the existence of which is the most important factor in the deterioration of visibility in an urban area of Northeast China. The study also shows an obvious diurnal variation and weekend effects of visibility and PM, which are mainly caused by human activities. Results of this study highlight the significant impact of fine particles on air pollution and visibility in an urban area of Northeast China.

Towards the improvements of simulating the chemical and optical properties of Chinese aerosols using an online coupled model − CUACE/Aero

ABSTRACT CUACE/Aero, the China Meteorological Administration (CMA) Unified Atmospheric Chemistry Environment for aerosols, is a comprehensive numerical aerosol module incorporating emissions, gaseous chemistry and size-segregated multi-component aerosol algorithm. On-line coupled into a meso-scale weather forecast model (MM5), its performance and improvements for aerosol chemical and optical simulations have been evaluated using the observations data of aerosols/gases from the intensive observations and from the CMA Atmosphere Watch network, plus aerosol optical depth (AOD) data from CMA Aerosol Remote Sensing network (CARSNET) and from Moderate Resolution Imaging Spectroradiometer (MODIS). Targeting Beijing and North China region from July 13 to 31, 2008, when a heavy hazy weather system occurred, the model captured the general variations of PM10 with most of the data within a factor of 2 from the observations and a combined correlation coefficient (r) of 0.38 (significance level=0.05). The correlation coefficients are better at rural than at urban sites, and better at daytime than at nighttime. Chemically, the correlation coefficients between the daily-averaged modelled and observed concentrations range from 0.34 for black carbon (BC) to 0.09 for nitrates with sulphate, ammonium and organic carbon (OC) in between. Like the PM10, the values of chemical species are higher for the daytime than those for the nighttime. On average, the sulphate, ammonium, nitrate and OC are underestimated by about 60, 70, 96.0 and 10.8%, respectively. Black carbon is overestimated by about 120%. A new size distribution for the primary particle emissions was constructed for most of the anthropogenic aerosols such as BC, OC, sulphate, nitrate and ammonium from the observed size distribution of atmospheric aerosols in Beijing. This not only improves the correlation between the modelled and observed AOD, but also reduces the overestimation of AOD simulated by the original model size distributions of primary aerosols. The normalised mean error has been reduced to 62% with the CARSNET observations and 76% with MODIS, from the original 111% and 143%, respectively. The factors resulting in the underestimation of aerosol concentrations and other discrepancies in the model are explored, and improvements in enhancing the model performance are proposed from the analysis. It is found that the accuracy in meteorological predictions plays a critical role on the simulation of the occurrence and accumulation of heavy pollution episode, especially the circulation winds and the treatment of Planetary Boundary Layer (PBL).

Monitoring haze episodes over the Yellow Sea by combining multisensor measurements

Haze, which is composed of a wide range of aerosol particles, is one of the most hazardous weather conditions because of its adverse impact on health and its deleterious effect on visibility, leading to loss of maritime transportation. Satellite, ground-based sunphotometer and particulate matter (PM) concentration data were analysed to evaluate the causes of two severe haze episodes observed during 28–31 March and 3–6 June 2007 over the Yellow Sea. The first episode was clearly affected by the long-range transport of dust from southeastern Mongolia to eastern Inner Mongolia, covering the Onqin Daga and Horqin sandy land areas, which are important sources for the sand and dust storms (SDS) that occur frequently during the spring in East Asia. A backward trajectory analysis confirmed the transport of air mass from southeastern Mongolia. A very high aerosol optical depth (AOD) (> 2.0) and a high backscatter coefficient (about 5 × 10−2 km sr−1) of dust were observed by Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), respectively, during the first haze episode. A sudden increase in PM10 (particles ≤ 10 μm) concentration (maximum value 225 μg m−3) was observed during the haze period. A higher AOD was observed over the Yellow Sea on 6 June 2007 during the second haze event compared to the AOD observed during the first haze episode, which occurred during 4–6 June 2007. A few hotspots were detected by MODIS during the second haze episode. It was concluded that the second haze episode was probably dominated by smoke from open burning areas of crop residue in East China, when a rapid increase in PM10 concentration up to 192 μg m−3 was observed.

Validation of aerosol optical depth and climatology of aerosol vertical distribution in the Taklimakan Desert

Based on ground–based sun–photometer remote sensing of aerosol optical depth (AOD) at Tazhong, a site located at the center of the Taklimakan Desert in 2007 and 2008, AOD retrieved from Cloud–Aerosol and Infrared Pathfinder Satellite Observations (CALIOP) data were validated. Six years vertical profiles of aerosol extinction coefficient in the Taklimakan Desert were then analyzed. A good agreement between ground–based and CALIOP remote sensing AOD data was derived, with the correlation coefficient being 0.95. CALIOP slightly underestimated AOD that is likely due to lower lidar ratio of dust than the real value in the CALIOP aerosol algorithm. Pronounced inter–annual and seasonal variations of vertical profiles were revealed by the CALIOP retrievals. The height of dust aerosol layer can reach 4–5 km, which is more pronounced in spring and summer. Larger and smaller extinction values were observed in spring (March, April and May) and in later autumn (October and November), respectively. Dominant contribution of dust was clearly shown by the vertical profiles of color ratio (CR) and particle depolarization ratio (PDR).

Test for Cosmological Time Dilation in Long Gamma-Ray Bursts

We present a test to investigate cosmological time dilation in long gamma-ray bursts (t90 > 1.5 s) using V, the ratio of expected peak counts in 64 and in 1024 ms. The theoretical evolution of V with redshift shows that dimmer bursts have flatter peaks than brighter ones when we assume that (1) the bursters are at cosmological distances, (2) the bursts have standard exponential profiles, and (3) the burst peak duration follows a power law in narrowing with cosmological redshift energy. The calculated V-distribution of long bursts versus intensity in a Friedmann universe with Ω = 1 and Λ = 0 is consistent with that found from previous results for long bursts. The estimated redshift is z ~ 2, and the time dilation factor with energy correction is ~1.8.

Cosmological time dilation in short gamma-ray bursts

Using the parameter V [ ≡ (64)max/(1024)max], the ratio of expected peak counts in 64 ms and 1024 ms, proposed by Che et al. recently, we find the cosmological time dilation in short gamma-ray bursts (t90 < 1.5 s) directly from the Burst and Transient Source Experiment catalog. The parameter V of short bursts shows a good correlation with the brightness B when we use (64)max as a measure of brightness B rather than (1024)max, introduced by Lamb et al. in 1993. In a Friedmann universe with Ω = 1 and Λ = 0, the estimated redshift is about 2 and the time dilation factor (TDF) with the energy correction is about 1.8. The fact that these results generally agree with those found in long bursts supports the same origin of long and short gamma-ray bursts.

The Relationship of PM Variation with Visibility and Mixing-Layer Height under Hazy/Foggy Conditions in the Multi-Cities of Northeast China

The variations of visibility, PM-mass concentration and mixing-layer height (MLH) in four major urban/industry regions (Shenyang, Anshan, Benxi and Fushun) of central Liaoning in Northeast China are evaluated from 2009 to 2012 to characterize their dynamic effect on air pollution. The annual mean visibilities are about 13.7 ± 7.8, 13.5 ± 6.5, 12.8 ± 6.1 and 11.5 ± 6.8 km in Shenyang, Anshan, Benxi and Fushun, respectively. The pollution load (PM × MLH) shows a weaker vertical diffusion in Anshan, with a higher PM concentration near the surface. High concentrations of fine-mode particles may be partially attributed to the biomass-burning emissions from September in Liaoning Province and surrounding regions in Northeast China as well as the coal burning during the heating period with lower MLH in winter. The visibility on non-hazy fog days is about 2.5–3.0 times higher than that on hazy and foggy days. The fine-particle concentrations of PM2.5 and PM1.0 on hazy and foggy days are ~1.8–1.9 times and ~1.5 times higher than those on non-hazy foggy days. The MLH declined more severely during fog pollution than in haze pollution. The results of this study can provide useful information to better recognize the effects of vertical pollutant diffusion on air quality in the multi-cities of central Liaoning Province in Northeast China.

A 20-year simulated climatology of global dust aerosol deposition

Based on a 20-year (1991-2010) simulation of dust aerosol deposition with the global climate model CAM5.1 (Community Atmosphere Model, version 5.1), the spatial and temporal variations of dust aerosol deposition were analyzed using climate statistical methods. The results indicated that the annual amount of global dust aerosol deposition was approximately 1161±31Mt, with a decreasing trend, and its interannual variation range of 2.70% over 1991-2010. The 20-year average ratio of global dust dry to wet depositions was 1.12, with interannual variation of 2.24%, showing the quantity of dry deposition of dust aerosol was greater than dust wet deposition. High dry deposition was centered over continental deserts and surrounding regions, while wet deposition was a dominant deposition process over the North Atlantic, North Pacific and northern Indian Ocean. Furthermore, both dry and wet deposition presented a zonal distribution. To examine the regional changes of dust aerosol deposition on land and sea areas, we chose the North Atlantic, Eurasia, northern Indian Ocean, North Pacific and Australia to analyze the interannual and seasonal variations of dust deposition and dry-to-wet deposition ratio. The deposition amounts of each region showed interannual fluctuations with the largest variation range at around 26.96% in the northern Indian Ocean area, followed by the North Pacific (16.47%), Australia (9.76%), North Atlantic (9.43%) and Eurasia (6.03%). The northern Indian Ocean also had the greatest amplitude of interannual variation in dry-to-wet deposition ratio, at 22.41%, followed by the North Atlantic (9.69%), Australia (6.82%), North Pacific (6.31%) and Eurasia (4.36%). Dust aerosol presented a seasonal cycle, with typically strong deposition in spring and summer and weak deposition in autumn and winter. The dust deposition over the northern Indian Ocean exhibited the greatest seasonal change range at about 118.00%, while the North Atlantic showed the lowest seasonal change at around 30.23%. The northern Indian Ocean had the greatest seasonal variation range of dry-to-wet deposition ratio, at around 74.57%, while Eurasia had the lowest, at around 12.14%.