Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 342646
Title Adaptive Weather Forecasting using Local Meteorological Information
Author(s) Doeswijk, T.G.; Keesman, K.J.
Source Biosystems Engineering 91 (2005)4. - ISSN 1537-5110 - p. 421 - 431.
DOI https://doi.org/10.1016/j.biosystemseng.2005.05.013
Department(s) Systems and Control Group
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2005
Keyword(s) weersvoorspelling - meteorologie - onzekerheid - landbouw - weersgegevens - nederland - weather forecasting - meteorology - uncertainty - agriculture - weather data - netherlands - surface-temperature forecasts - kalman filter
Categories Meteorology (General)
Abstract In general, meteorological parameters such as temperature, rain and global radiation are important for agricultural systems. Anticipating on future conditions is most often needed in these systems. Weather forecasts then become of substantial importance. As weather forecasts are subject to uncertainties, there is a need in minimising the uncertainties. In this paper, a framework is presented in which local weather forecasts are updated using local measurements. Kalman filtering is used for this purpose as assimilation technique. This method is compared and combined with diurnal bias correction. It is shown that the standard deviation of the forecast error can be reduced up to 6 h ahead for temperature, up to 31 h ahead for wind speed, and up to 3 h for global radiation using local measurements. Combining the method with diurnal bias correction leads to a further increase in performance in terms of both bias and standard deviation.
Comments
There are no comments yet. You can post the first one!
Post a comment
 
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.