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M on itor ing andWarn ing System for SevereWea ther Ba sed on Doppler Radar Da ta
DUAN Wen-An, AN  Lin, WEI  Min
J4    2009, 27 (1): 82-93.  
Abstract1380)      PDF(pc) (689KB)(1576)       Save

The Dopp lerweather radar has become one of the chiefmeans to monitor short - term severe convective weather at p resent. We designed and developed the monitoring and warning database system for severe weather based on the CINRAD /XD Dopp lerweather
radar data. The system usesMicrosoftVisual C + + 6. 0 p rogramming languages and SQL Server 2000 database as the development en
vironment. It contains five important parts: data acquisition and p rocessing system, image disp lay system, database system,monitoring
and warning system, client app lication system. The system can achieve some functions such as real - time disp lay, storage, monitoring
and warning, animation p layback, and has good compatibility and portability. It can be used very easily and conveniently. The system
can help forecasters analyze the internal structure and develop ing trend of weather system. Especially in some respects, for examp le,
nowcasting and weathermodification, it can p lay very important role.

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Study on Forecasting Methods of Hail Storm in Lanzhou Cit
WANG Hua-Liang, FU  Chao, JIAO Yan-Jun, DUAN Wen-An
J4    2004, 22 (3): 63-67.  
Abstract1019)      PDF(pc) (108KB)(653)       Save

:Based on May to September weather cases during recent 10 years, together with the geographic information and the distri-
bution of hail storms weather and climate in Lanzhou,applying the products of the upper and surface observation and the numerical
weather prediction et al.,the weather forecasting methods for hail storms in Lanzhou are formed.The forecasting object is hail storms
at anywhere in the area, the principle is no failed forecast in 24 hours, the identification of the hail storms is according to methods of
the combination of the automation and man-computer interaction. These methods mainly provide the early warning and forecasting
information for hail prevention operation. We successfully forecasted two local hail processes by this operational forecasting system in
May in 2004, and the forecast accuracy reaches about 67%.

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