Hostname: page-component-77c89778f8-5wvtr Total loading time: 0 Render date: 2024-07-20T21:37:04.023Z Has data issue: false hasContentIssue false
  • English
  • Français

Statistical methods for the prediction of night-time cooling and minimum temperature

Published online by Cambridge University Press:  24 May 2006

G. Emmanouil ,
G. Galanis  and
G. Kallos
G. Emmanouil
Affiliation:
University of Athens, School of Physics, Division of Applied Physics, University Campus, Bldg. PHYS – V, Athens, 157 84, Greece
G. Galanis
Affiliation:
University of Athens, School of Physics, Division of Applied Physics, University Campus, Bldg. PHYS – V, Athens, 157 84, Greece Naval Academy of Greece, Section of Mathematics, Xatzikyriakion, Piraeus 185 39, Greece Email: gemman@mg.uoa.gr, ggalanis@mg.uoa.gr, kallos@mg.uoa.gr
G. Kallos
Affiliation:
University of Athens, School of Physics, Division of Applied Physics, University Campus, Bldg. PHYS – V, Athens, 157 84, Greece
Get access

Abstract

Four different models for the prediction of frost events caused by air cooling due to thermal radiation are presented in this paper. Three of them are based on polynomial functions that simulate different types of temperature variations in comparison with an exponential one. The fourth, a post-processing method based on Kalman filters, is proposed for those cases where a systematic type of bias has emerged.

Keywords

frost predictionminimum temperatureKalman filterpolynomial models
Type
Research Article
Information
Meteorological Applications , Volume 13 , Issue 2 , June 2006 , pp. 169 - 178
Copyright
2006 Royal Meteorological Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)