National Satellite Meteorology Center

Beijing, China

National Satellite Meteorology Center

Beijing, China
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Zhong L.,Chinese Academy of Sciences | Zhang Z.,National Meteorological Information Center | Chen L.,National Satellite Meteorology Center | Yang J.,Meteorological Observation Center | Zou F.,National Meteorological Information Center
Atmospheric Research | Year: 2016

The current real-time operational quality control method for hourly rain gauge records at meteorological stations of China is primarily based on a comparison with historical extreme records, and the spatial and temporal consistencies of rain records. However, this method might make erroneous judgments for heavy precipitation because of its remarkable inhomogeneous features. In this study, we develop a Radar Supported Operational Real-time Quality Control (RS_ORQC) method to improve hourly gauge precipitation records in eastern China by using Doppler weather radar data and national automatic rain-gauge network in JJA (i.e., June, July and August) between 2010 and 2011. According to the probability density function (PDF) and cumulative probability density function (CDF), we establish the statistic relationships between NSN precipitation records under 7 radar coverage and radar quantitative precipitation estimation (QPE). The other NSN records under 5 radar coverage are used for the verification. The results show that the correct rate of this radar-supported new method in judging gauge precipitation is close to 99.95% when the hourly rainfall rate is below 10 mm h-1 and is 96.21% when the rainfall intensity is above 10 mm h-1. Moreover, the improved quality control method is also applied to evaluate the quality of provincial station network (PSN) precipitation records over eastern China. The correct rate of PSN precipitation records is 99.92% when the hourly rainfall rate is below 10mmh-1, and it is 93.33% when the hourly rainfall rate is above 10mmh-1. Case studies also exhibit that the radar-supported method can make correct judgments for extreme heavy rainfall. © 2016 The Authors.

Bai W.-G.,Nanjing University of Information Science and Technology | Bai W.-G.,National Satellite Meteorology Center | Zhang P.,National Satellite Meteorology Center | Zhang W.-J.,National Satellite Meteorology Center | Li J.,National Satellite Meteorology Center
Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves | Year: 2016

The traditional atmospheric radiative transfer calculation method has been unable to meet the needs of space-borne hyper-spectral infrared atmospheric remote sensing data processing because of the limitation of the computing resources and efficiency. Based on the optimal spectral sampling method, this paper developed a fast and accurate high spectral resolution infrared atmospheric radiative transfer model FFRTM_IR. This model was used to simulate the measurement of hyper-spectral infrared radiance atmosphere sounder (HIRAS) aboard on FY-3D satellite. Independent profiles validation results show that the bias of FFRTM_IR were less than 0.06 K and the standard deviation were no more than 0.1 K for all HIRAS channels. Under the same calculation environment, the speed of FFRTM_IR was slightly faster than the general radiative transfer model, such as CRTM. Along with the FFRTM_IR model, an analytical method was used to drive the temperature, water vapor, carbon dioxide and ozone profiles jacobian matrix, which agree well with results obtained from accurate perturbation method. All these validation and analysis results showed that the developed initial efficient infrared atmospheric radiative transfer model can be used in space-borne hyper-spectral infrared atmospheric sounding instrument simulation and data processing. © 2016, Chinese Optical Society. All right reserved.

Yang S.,National Meteorological Information Center | Shi G.Y.,CAS Institute of Atmospheric Physics | Chen L.,National Satellite Meteorology Center | Wang B.,CAS Institute of Atmospheric Physics | Yang H.L.,Shenzhen National Climate Observatory
Scientific Online Letters on the Atmosphere | Year: 2011

Deep Blue (DB) is a new MODIS retrieval algorithm to retrieve aerosol properties over bright surfaces such as arid, semiarid and urban areas. It's expected to fill in data gaps over bright surface left by the standard algorithm based on Dark Target (DT) retrieval algorithm. DB has been employed in recent Collection 5.1 AOD product. This study presents a comparison between the DT approach and the more recent DB algorithm using international Aerosol Robotic Network (AERONET) data as reference, analyzes the improvement in DB AOD product over urban surface and discusses the influence of aerosol model variation on MODIS AOD retrieval. Results show that DB products perform better than DT products under clear condition, and a systematic AOD overestimation in DT products doesn't occur in DB products. DT and DB AOD products both appear strong seasonal pattern, with better performance in autumn and winter and worse performance in spring and summer, and the underestimated Aerosol Single Scattering Albedo (SSA) during spring and summer over Beijing in MODIS retrieval probably is the major factor inducing the AOD overestimation in these seasons. In comparison with DB AOD, DT AOD is more likely overestimated, unsuitable surface reflectance over Beijing may be the key factor, and it may play a more important role in MODIS DT AOD retrieval than unsuitable SSA. © 2011, the Meteorological Society of Japan.

Wang X.,National Satellite Meteorology Center | Guo Q.,National Satellite Meteorology Center
Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves | Year: 2014

By using the self-developed calibration of inner blackbody corrected by lunar emission (CIBLE) results of Fengyun-2 (FY-2) satellite, tropical cyclones (TC) intensity was estimated objectively with Dvorak technology. Several strong and supper strong TCs happened in 2012 summer and autumn were selected, when FY-2 lay in the stages of the smooth variation of calibration and the acutely variation one occurred in satellite eclipse period, respectively. As the comparative datum, both MTSAT satellite calibration and FY-2E cross-calibration result were used for the analysis. The results show that CIBLE method can accurately describe the diurnal and annual variation of FY-2E on-orbit calibration slopes, which is the main contributor to the consistent estimations of TC intensity between CIBLE and MTSAT in each intensity stage. Particularly, during the autumn eclipse period, the diurnal variation of calibration slope greatly improves the accuracy of strong typhoon intensity determination even at night. The maximal error of the wind speed in typhoon center has been reduced by 14m/s, which is believed to be a significant promotion for the TC intensity prediction.

Wang Y.,Hefei University of Technology | Wang Y.,Chinese Academy of Sciences | Fu Y.,Hefei University of Technology | Fu Y.,Chinese Academy of Sciences | And 2 more authors.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014

Ice water path (IWP) is an important parameter to characterize tropical cyclones. The FY-3B satellite, with multiple passive microwave sensors onboard, offers a unique opportunity to monitor the variation of cloud IWP during the evolution of tropical cyclones. In this paper, by using the combined simultaneous measurements of the MicroWave atmospheric Humidity Sounder and MicroWave Radiometer Imager on FY-3B satellite, an improved IWP algorithm for tropical clouds is developed. The new algorithm seeks to better estimate ice-free background brightness temperature at 150 GHz using simultaneous observations at low microwave frequencies. This approach improves IWP retrieval accuracy particularly for high IWP clouds that often associated with tropical cyclones. The current algorithm was applied to FY-3B observations of two typhoons with different strengths, and the characteristics of IWP variation at the storms' different evolution stages were investigated. The results showed that IWP tends to vary ahead of the storm intensification or decay, suggesting that IWP can be potentially used to predict the change of storm intensity. © 1980-2012 IEEE.

Liu H.,Chengdu University of Information Technology | Liu H.,National Satellite Meteorology Center | Tang S.,National Satellite Meteorology Center | Zhang S.,Chengdu University of Information Technology | Hu J.,National Satellite Meteorology Center
International Journal of Remote Sensing | Year: 2015

Radiosonde data collected from 83 stations in China from January to December 2012 were used to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) and thermal infrared (IR) total precipitable water vapour (PWV) products. The results indicate that MODIS NIR PWV products shows better agreement with radiosonde data than with IR PWV products, with the correlation coefficients up to 0.95. The root mean square errors (RMSEs) of NIR PWV range from 2 to 8 mm with different stations, which shows significant regional differences over China. The mean RMSE is about 5.03 mm (~35%) with a positive deviation of 2.56 mm (~18%), indicating the occurrence of a slight overestimation. Moreover, MODIS IR PWV during night-time has a better agreement with radiosonde PWV than that during daytime. The mean RMSE of IR PWV during daytime was ~6.02 mm (~42%), with a positive deviation of 1.54 mm (~11%). The mean RMSE of IR PWV during night-time was ~5.81 mm (~40%), with a negative deviation of approximately −0.04 mm (~0.25%). Both the NIR and IR PWV products during daytime tend to be higher than radiosonde PWV. © 2015, Taylor & Francis.

Yang C.-Y.,PLA University of Science and Technology | Lu Q.-F.,National Satellite Meteorology Center | Wu X.-B.,National Satellite Meteorology Center | Zhang P.,National Satellite Meteorology Center
Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves | Year: 2012

The quality and error distribution of atmospheric motion vectors (AMVs) derived from the water vapor band of FY-2C meteorological satelite of China in 2009 were analysed. The results indicate that the errors of AMVs varies inhomogeneously in different climate zones, seasons, and vertical positions in space. Based on the thermal wind theory, we noticed that over estimation in the value of height may be the dominant origin of the AMVs errors. We verified the conjecture by reassigning the AMVs to new heights, with the NCEP/FNL reanalysis wind field as a reference. The quality of AMVs before and after reassignment was compared with the NCEP/FNL data and radiosonde observations of international exchange stations. It's found that the negative biases of the U-winds of AMVs decrease explicitly from -9.73 ms -1 to -1.1 ms -1, the standard deviations of errors from 10.24 ms -1 to 4.5 ms -1, the quality of which is improved over 50%. The V-winds are also improved obviously. The seasonal errors of AMVs are removed well. All of the improvements justify the aforementioned viewpoints. This paper suggests a preliminary method which assigns the AMVs to reasonable heights with the reanalysed wind field of a NWP model as a reference, and also supplies an idea of detecting algorithm for AMVs producers.

Ce G.,South-Central University for Nationalities | Bing-sen X.,National Satellite Meteorology Center | Zhao-xiang L.,South-Central University for Nationalities
Chinese Astronomy and Astrophysics | Year: 2013

Solar flares are important events for the space weather. The predic- tion of relevant parameters of solar flares has practical significance for evaluating the effect of sudden ionospheric disturbance (SID). The data of soft X-ray flux observed by the GOES-8 satellite in the 23th solar cycle are used to predict the peak intensities and ending times of X-class flares with the method of data fit- ting. Using this method to analyze the X-class flares in the 23th solar cycle, it is possible to predict the peak flux of an X-class flare 17. minutes in advance at most. And the ending time of an X-class flare may be predicted about 60. minutes in advance at most. The predicted results indicate that the prediction method has certain effectiveness and applicability. © 2013 Elsevier B.V.

Chen L.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Chen L.,National Satellite Meteorology Center | Hu X.,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites | Hu X.,National Satellite Meteorology Center | And 4 more authors.
Remote Sensing | Year: 2013

Based on simulated reflectance, deep convective clouds (DCC) can be used as an invariant target to monitor the radiometric response degradation of the FY-3A/MERSI (Medium Resolution Spectral Imager) reflective solar bands (RSBs). The long-term response of the MERSI RSBs can easily be predicted using a quadratic fit of the monthly DCC mean reflectance, except for bands 6 and 7, which suffer from instrument anomalies. DCC-based degradations show that the blue bands (λ < 500 nm) and water-vapor bands have degraded significantly, whereas for near-infrared bands, the total degradations in four years are within 3% (excluding bands 3 and 20). For most bands, the degradation rates are greatest during the first year in orbit and decrease over time. The FY-3A/MERSI degradation results derived from DCC are consistent within 2.5%, except for bands, 11, 18 and 19, when compared with Aqua/MODIS(Moderate Resolution Imaging Sepetroradiometer) inter-calibration, multi-site invariant earth target calibration and the CRCS(Chinese Radiometric Calibration Site) Dunhuang desert vicarious calibration methods. Overall, the 2σ/mean degradation uncertainty for most MERSI bands was within 3%, validating the temporal stability of the DCC monthly mean reflectances. The DCC method has reduced the degradation uncertainties for MERSI water vapor bands over other methods. This is asignificant advantage of the DCC calibration method. The saturation of some MERSI bands may hinder the effectiveness of the DCC calibration approach. © 2013 by the authors.

Zhao F.,National Satellite Meteorology Center | Li X.,National Satellite Meteorology Center | Gai C.,National Satellite Meteorology Center | Gao W.,National Satellite Meteorology Center
Environmental Monitoring and Assessment | Year: 2010

In this paper, we will present a simple algorithm to estimate the temporal and spatial distribution of dust mass concentration by combining PM10 and conventional meteorological observations. The efficiency of the algorithm has been demonstrated by applying it to analyze the dust source, transport, and dissipation of the dust storm which occurred in the west region of Pa-tan-chi-lin Desert at 0200 BST 27 March, 2004. © 2009 Springer Science+Business Media B.V.

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