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Beijing, China

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Beijing, China
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Zhong L.,Chinese Academy of Meteorological Sciences | Yang R.,Public Weather Service Center | Chen L.,National Satellite Meteorology Center | Wen Y.,University of Oklahoma | And 3 more authors.
Journal of Applied Meteorology and Climatology | Year: 2014

This study presents a statistical analysis of the variability of the vertical structure of precipitation in the eastern downstream region of the Tibetan Plateau as measured by the Precipitation Radar (PR) on the National Aeronautics and Space Administration Tropical Rainfall Measuring Mission (TRMM) satellite. Data were analyzed over an 11-yr time span (January 2004-December 2014). The results show the seasonal and spatial variability of the storm height, freezing level, and bright band for different types of precipitation as well as the characteristics of intensity-related and type-related vertical profiles of reflectivity (VPR). Major findings were as follows: About 90% of the brightband peak reflectivity of stratiform precipitation was less than 32 dBZ, and 40% of the maximum reflectivity of convective precipitation exceeded 35 dBZ. The intensity of surface rainfall rates also depended on the shapes of VPRs. For stratiform precipitation, ice-snow aggregation was faster during moderate and heavy rainfall than it was in light rainfall. Since both the moisture and temperature are lower in winter, the transformation efficiency of hydrometeors becomes slower. Typical Ku-band representative climatological VPRs (CPRs) for stratiform precipitation have been created on the basis of the integration of normalized VPR shape for the given area and the rainfall intensity. All of the findings indicate that the developed CPRs can be used to improve surface precipitation estimates in regions with complex terrain where the ground-based radar net has limited visibility at low levels. © 2017 American Meteorological Society.


Zhong L.,Chinese Academy of Sciences | Yang R.,Public Weather Service Center | Wen Y.,University of Oklahoma | Chen L.,National Satellite Meteorology Center | And 5 more authors.
Atmospheric Research | Year: 2017

China operational weather radar network consists of more than 200 ground-based radars (GR(s)). The lack of unified calibrators often result in poor mosaic products as well as its limitation in radar data assimilation in numerical models. In this study, radar reflectivity and precipitation vertical structures observed from space-borne TRMM (Tropical Rainfall Measurement Mission) PR (precipitation radar) and GRs are volumetrically matched and cross-evaluated. It is found that observation of GRs is basically consistent with that of PR. For their overlapping scanning regions, the GRs are often affected by the beam blockage for complex terrain. The statistics show the better agreement among S band A type (SA) radars, S band B type (SB) radars and PR, as well as poor performance of S band C type (SC) radars. The reflectivity offsets between GRs and PR depend on the reflectivity magnitudes: They are positive for weak precipitation and negative for middle and heavy precipitation, respectively. Although the GRs are quite consistent with PR for large sample, an individual GR has its own fluctuated biases monthly. When the sample number is small, the bias statistics may be determined by a single bad GR in a group. Results from this study shed lights that the space-borne precipitation radars could be used to quantitatively calibrate systematic bias existing in different GRs in order to improve the consistency of ground-based weather radar network across China, and also bears the promise to provide a robust reference even form a space and ground constellation network for the dual-frequency precipitation radars onboard the satellites anticipated in the near future. © 2017 Elsevier B.V.


Zang Z.,PLA University of Science and Technology | Wang W.,PLA University of Science and Technology | Cheng X.,Public Weather Service Center | Yang B.,Lanzhou University | And 2 more authors.
Atmosphere | Year: 2017

The aerosol optical depth (AOD) from satellites or ground-based sun photometer spectral observations has been widely used to estimate ground-level PM2.5 concentrations by regression methods. The boundary layer height (BLH) is a popular factor in the regression model of AOD and PM2.5, but its effect is often uncertain. This may result from the structures between the stable and convective BLHs and from the calculation methods of the BLH. In this study, the boundary layer is divided into two types of stable and convective boundary layer, and the BLH is calculated using different methods from radiosonde data and National Centers for Environmental Prediction (NCEP) reanalysis data for the station in Beijing, China during 2014-2015. The BLH values from these methods show significant differences for both the stable and convective boundary layer. Then, these BLHs were introduced into the regression model of AOD-PM2.5 to seek the respective optimal BLH for the two types of boundary layer. It was found that the optimal BLH for the stable boundary layer is determined using the method of surface-based inversion, and the optimal BLH for the convective layer is determined using the method of elevated inversion. Finally, the optimal BLH and other meteorological parameters were combined to predict the PM2.5 concentrations using the stepwise regression method. The results indicate that for the stable boundary layer, the optimal stepwise regression model includes the factors of surface relative humidity, BLH, and surface temperature. These three factors can significantly enhance the prediction accuracy of ground-level PM2.5 concentrations, with an increase of determination coefficient from 0.50 to 0.68. For the convective boundary layer, however, the optimal stepwise regression model includes the factors of BLH and surface wind speed. These two factors improve the determination coefficient, with a relatively low increase from 0.65 to 0.70. It is found that the regression coefficients of the BLH are positive and negative in the stable and convective regression models, respectively. Moreover, the effects of meteorological factors are indeed related to the types of BLHs. © 2017 by the authors.


Li C.,Beijing Normal University | Li C.,Henan Polytechnic University | Shen L.,Beijing Normal University | Wang H.-B.,Public Weather Service Center | Lei T.,Beijing Normal University
Proceedings - 2nd IEEE International Conference on Advanced Computer Control, ICACC 2010 | Year: 2010

As an important means of obtaining spatial data, the unmanned aerial vehicle (UAV) remote sensing has such advantages as real-time, flexible, high-resolution, cost-effective etc, and it can gather information in dangerous environments without risk to flight crews. Because UAV remote sensing is a powerful supplement of spaceborne remote sensing and airborne remote sensing, it has enormous potential and bright prospect. In this paper, the compositions and key technologies of UAV remote sensing system are presented, and the applications such as land use, land supervision, flood disasters, meteorology disasters, geological disasters, forest fire disasters as well as surveying and mapping are summarized. In the end, we predict the main direction of studying on UAV remote sensing in the future. © 2010 IEEE.


Bao H.-J.,Public Weather Service Center | Bao H.-J.,National Meteorological Center | Zhao L.-N.,Public Weather Service Center | Zhao L.-N.,National Meteorological Center | And 8 more authors.
Advances in Geosciences | Year: 2011

The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead. © 2011 Author(s).


Liu J.,CAS Institute of Atmospheric Physics | Liu J.,Public Weather Service Center | Liu J.,Nanjing University of Information Science and Technology | Xia X.,CAS Institute of Atmospheric Physics | And 12 more authors.
Tellus, Series B: Chemical and Physical Meteorology | Year: 2010

Based on AErosol RObotic NETwork and Chinese Sun Hazemeter Network data, the Multi-angle Imaging SpectroRadiometer (MISR) level 2 aerosol optical depth (AOD) products are evaluated in China. The MISR retrievals depict well the temporal aerosol trend in China with correlation coefficients exceeding 0.8 except for stations located in northeast China and at the Lanzhou site. In general, the MISR AOD retrievals agree well with ground-based observations for AOD < 0.5. The retrievals are systematically underestimated for AOD > 0.5 in the east, southwest and northeast regions of China. Concerning surface types, the greatest underestimations occur in farmland and forest ecosystems. The largest and smallest biases are seen in spring and in summer, respectively. The systematic underestimation seems to stem from the use of too high single scattering albedos ∼0.96 which is significantly higher than those estimated from ground-based observations. Further improvements to the MISR aerosol algorithm, especially in the aerosol model, are recommended. © 2010 The Authors Journal compilation © 2010 Blackwell Munksgaard.


Wang C.,CAS Institute of Atmospheric Physics | Wang C.,University of Chinese Academy of Sciences | Gao S.,CAS Institute of Atmospheric Physics | Gao S.,Chinese Academy of Meteorological Sciences | And 5 more authors.
Atmospheric Research | Year: 2014

A rainstorm process that occurred in North China from July 24-25, 2011 was accurately simulated using the Weather Research and Forecasting model, and the multi-scale characteristics of moisture transport were studied based on the simulated results. The results indicated that water vapor was carried to North China mainly by the southwest low-level jet and easterly flow, with the former playing a principal role. The enhancement and northward extension of the southwesterly wind were consistent with the increase of magnitude and northward propulsion of the moisture flux. The variation of the winds mirrored fluctuations in the amount of precipitation. In addition, the water vapor from low latitudes to North China was transported first near the boundary layer over 15°N-21°N and then primarily at 850. hPa over 21°N-30°N, 900. hPa over 30°N-39°N, and 800. hPa over the region north of 39°N. The net budget of water vapor in North China was always positive during the rainstorm process because the zonal deficit was much smaller than the meridional surplus. The contribution of the water vapor advection was larger than that of the water vapor convergence in the prior period of rainfall, and the subsequent moisture aggregation relied on the water vapor convergence. The rainband in North China presented frontal mesoscale characteristics, and the short-term aggregation of moisture was closely related to the genesis and development of the mesoscale convective system that was triggered mainly by the cold air intrusion near the boundary layer. The underlying cold air not only lifted the warm air to trigger the convection, but it also influenced the development of the low pressure system in the lower levels, which further intensified the convergence and benefited the rapid accumulation of moisture to the convective zone near the boundary layer. The moisture transport reached its maximum an hour before the rainstorm occurred. © 2014 Elsevier B.V.


Wang C.,CAS Institute of Atmospheric Physics | Wang C.,University of Chinese Academy of Sciences | Gao S.,CAS Institute of Atmospheric Physics | Gao S.,Chinese Academy of Meteorological Sciences | And 3 more authors.
Advances in Atmospheric Sciences | Year: 2015

Terrain characteristics can be accurately represented in spectrum space. Terrain spectra can quantitatively reflect the effect of topographic dynamic forcing on the atmosphere. In wavelength space, topographic spectral energy decreases with decreasing wavelength, in spite of several departures. This relationship is approximated by an exponential function. A power law relationship between the terrain height spectra and wavelength is fitted by the least-squares method, and the fitting slope is associated with grid-size selection for mesoscale models. The monotonicity of grid size is investigated, and it is strictly proved that grid size increases with increasing fitting exponent, indicating that the universal grid size is determined by the minimum fitting exponent. An example of landslide-prone areas in western Sichuan is given, and the universal grid spacing of 4.1 km is shown to be a requirement to resolve 90% of terrain height variance for mesoscale models, without resorting to the parameterization of subgrid-scale terrain variance. Comparison among results of different simulations shows that the simulations estimate the observed precipitation well when using a resolution of 4.1 km or finer. Although the main flow patterns are similar, finer grids produce more complex patterns that show divergence zones, convergence zones and vortices. Horizontal grid size significantly affects the vertical structure of the convective boundary layer. Stronger vertical wind components are simulated for finer grid resolutions. In particular, noticeable sinking airflows over mountains are captured for those model configurations. © 2015, Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg.


Liang H.,Chinese Academy of Meteorological Sciences | Liang H.,University of Chinese Academy of Sciences | Zhang R.,Chinese Academy of Meteorological Sciences | Liu J.,Chinese Academy of Meteorological Sciences | And 3 more authors.
Advances in Atmospheric Sciences | Year: 2012

In this study, the clear sky hourly global and net solar irradiances at the surface determined using SUNFLUX, a simple parameterization scheme, for three stations (Gaize, Naqu, and Lhasa) on the Tibetan Plateau were evaluated against observation data. Our modeled results agree well with observations. The correlation coefficients between modeled and observed values were > 0. 99 for all three stations. The relative error of modeled results, in average was < 7%, and the root-mean-square variance was < 27 W m -2. The solar irradiances in the radiation model were slightly overestimated compared with observation data; there were at least two likely causes. First, the radiative effects of aerosols were not included in the radiation model. Second, solar irradiances determined by thermopile pyranometers include a thermal offset error that causes solar radiation to be slightly underestimated. The solar radiation absorbed by the ozone and water vapor was estimated. The results show that monthly mean solar radiation absorbed by the ozone is < 2% of the global solar radiation (< 14 W m -2). Solar radiation absorbed by water vapor is stronger in summer than in winter. The maximum amount of monthly mean solar radiation absorbed by water vapor can be up to 13% of the global solar radiation (95 W m -2). This indicates that water vapor measurements with high precision are very important for precise determination of solar radiation. © 2012 Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg.


Cheng X.-L.,CAS Institute of Atmospheric Physics | Li J.,CAS Institute of Atmospheric Physics | Hu F.,CAS Institute of Atmospheric Physics | Xu J.,CAS Institute of Atmospheric Physics | Zhu R.,Public Weather Service Center
Wind and Structures, An International Journal | Year: 2015

A coupled model system for Wind Resource Assessment (WRA) was studied. Using a mesoscale meteorological model, the Weather Research and Forecasting (WRF) model, global-scale data were downscaled to the inner nested grid scale (typically a few kilometers), and then through the coupling Computational Fluid Dynamics (CFD) mode, FLUENT. High-resolution results (50 m in the horizontal direction; 10 m in the vertical direction below 150 m) of the wind speed distribution data and ultimately refined wind farm information, were obtained. The refined WRF/FLUENT system was then applied to assess the wind resource over complex terrain in the northern Poyang Lake region. The results showed that the approach is viable for the assessment of windenergy. Copyright © 2015 Techno-Press, Ltd.

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