Abstract Advances in remote sensing from ground-based and space-borne systems, expanded in-situ observation networks, and increased low-cost computer capability, will allow an unprecedented view of mesoscale weather systems from the local weather office. However, the volume of data from these new instruments, the nonconventional quantities measured, and a frequent operational cycle, require the development of systems to translate this information into products aimed specifically at aiding the forecaster in zero to six hour prediction. An observing network now exists in northeast Colorado that is similar to what a local weather office will have available within 5–7 years. With GOES and TIROS satellites, Doppler radar, wind profilers, and surface mesonet stations, we have a unique opportunity to explore the use of such data in nowcasting weather phenomena. The scheme, called LAPS (the Local Analysis and Prediction System), objectively analyzes data on a high-resolution (10-km), three-dimensional grid. The analyzed fields are used to generate mesoscale forecast products currently aimed at convection and aircraft icing. Substantial skill was demonstrated during a convective forecasting experiment. While preliminary results from the icing experiment indicate improvements are needed with fine detail, the results are useful in an areally averaged sense.


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    Titel :

    Local data assimilation and analysis for nowcasting


    Beteiligte:

    Erschienen in:

    Advances in Space Research ; 12 , 7 ; 179-188


    Erscheinungsdatum :

    01.01.1992


    Format / Umfang :

    10 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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