Anhui Weather Modification Office

Hefei, China

Anhui Weather Modification Office

Hefei, China
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Miao Q.,Nanjing University of Information Science and Technology | Zhang Z.,Nanjing University of Information Science and Technology | Li Y.,Nanjing University of Information Science and Technology | Qin X.,Nanjing University of Information Science and Technology | And 3 more authors.
Atmospheric Environment | Year: 2015

The number of cloud condensation nuclei (CCN) may indirectly influence the radiative balance of the atmosphere by changing the number of cloud droplets, which in turn changes the albedo, longevity and precipitation intensity of clouds. The spatial and temporal distribution of the CCN concentrations and the influence of particles on CCN activation spectra have received much attention. Measurements of CCN concentrations, aerosol number-size distribution and hygroscopic growth factors were conducted during the periods June 30 to July 17 and July 24 to 28, 2014, at the peak of Mt. Huang (1840m above sea level). The results show that the CCN concentration were 419±414cm-3, 806±720cm-3, 1292±905cm-3, 1380±873cm-3, and 1506±867cm-3 at supersaturation levels of 0.1%, 0.2%, 0.5%, 0.7%, and 1%, respectively. The equation Nccn=N0(1-exp(-BSk)) fits the average CCN spectrum over the observation period. The CCN concentrations were calculated from the hygroscopic growth factors and the aerosol number-size distribution. The calculated CCN concentrations and measured CCN concentrations show close correlation and high accuracy. An analysis of the variation in the particle number-size distribution and hygroscopic growth factors indicates that the change in particle number-size distribution is the primary factor affecting the CCN concentrations. © 2015 Elsevier Ltd.

Chen K.,Nanjing University of Information Science and Technology | Yin Y.,Nanjing University of Information Science and Technology | Kong S.,Nanjing University of Information Science and Technology | Xiao H.,Nanjing University of Information Science and Technology | And 3 more authors.
Atmospheric Environment | Year: 2014

The particle size spectra and chemical composition of aerosol particles at Mt. Huang (the Yellow Mountain), a background site of southeastern China, were investigated using a single particle aerosol mass spectrometer (SPAMS) and other aerosol monitoring instruments. The field campaign was conducted from Sep. 29 to Oct. 9, 2012, to observe the influence of straw burning on the size distribution, chemical composition of atmospheric aerosols at a background site. Results showed that K-Secondary and K-EC particles were the dominant particle types during this period, with their number concentrations totally accounting for 74% of all the particles. From long-range transport analysis of air masses, six types of particles all contained high concentrations of 39 [K]+ ion (known as the tracer for biomass burning) which indicate that biomass burning may represent as a significant source of aerosols for air masses originated from the north of Mt. Huang. The sampling period could be classified into three sub-periods according to the backward trajectories. During sub-period 1, the K-Secondary particles exhibited the highest concentrations, accounting for 74.2% and 55.4%, respectively, of the submicron and super-micron particles. In sub-period 3, K-EC dominated the submicron particles, indicating that more particles had anthropogenic sources, especially industrial emissions. The results obtained in this study will enrich the database of aerosol chemical composition in the background sites of southeast China and could be of important applications in environmental and climate research. © 2013 Elsevier Ltd.

Chen S.,University of Oklahoma | Chen S.,Advanced Radar Research Center | Liu H.,Anhui Weather Modification Office | You Y.,Florida State University | And 12 more authors.
PLoS ONE | Year: 2014

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing. © 2014 Chen et al.

Zhao L.,Public Meteorological Service Center | Zhao L.,National Meteorological Center | Qi D.,National Meteorological Center | Tian F.,National Meteorological Center | And 7 more authors.
Acta Meteorologica Sinica | Year: 2012

Based on the precipitation and temperature data obtained from THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE)-China Meteorological Administration (CMA) archiving center and the raingauge data, the three-layer variable infiltration capacity (VIC-3L) land surface model was employed to carry out probabilistic hydrological forecast experiments over the upper Huaihe River catchment from 20 July to 3 August 2008. The results show that the performance of the ensemble probabilistic prediction from each ensemble prediction system (EPS) is better than that of the deterministic prediction. Especially, the 72-h prediction has been improved obviously. The ensemble spread goes widely with increasing lead time and more observed discharge is bracketed in the 5th-99th quantile. The accuracy of river discharge prediction driven by the European Centre (EC)-EPS is higher than that driven by the CMA-EPS and the US National Centers for Environmental Prediction (NCEP)-EPS, and the grand-ensemble prediction is the best for hydrological prediction using the VIC model. With regard to Wangjiaba station, all predictions made with a single EPS are close to the observation between the 25th and 75th quantile. The onset of the flood ascending and the river discharge thresholds are predicted well, and so is the second rising limb. Nevertheless, the flood recession is not well predicted. © The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2012.

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