University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Numerical weather prediction for high-impact weather in a changing climate : assimilation of dynamical information from satellite imagery.

Wakeling, Matthew N. (2015) Numerical weather prediction for high-impact weather in a changing climate : assimilation of dynamical information from satellite imagery. Doctoral thesis, University of Surrey.

[img]
Preview
Text
thesis_with_corrections2.pdf - Thesis (version of record)
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (8MB) | Preview
[img]
Preview
Text
volume2_final.pdf - Thesis (version of record)
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (21MB) | Preview
[img]
Preview
Text
Author_Deposit_Agreement.pdf - Supplemental Material
Available under License : See the attached licence file.

Download (165kB) | Preview

Abstract

Operational weather prediction systems do not currently make full use of infra-red satellite observations that are affected by the presence of cloud. Observations that are affected by cloud are routinely discarded during pre-processing. This is because cloud causes large, unpredictable, and nonlinear changes in the observed radiances, and obscures the atmosphere underneath from view. This disrupts the finely-balanced calculations used to convert small changes in observed radiance into temperature and humidity profiles of the atmosphere. Areas that contain cloud are likely to be meteorologically interesting, so where information on the state of the atmosphere is most desired, it is also in shortest supply. This thesis explores the possibility of using the large changes over time of cloud-affected infra-red satellite observations to calculate the vertical component of wind. In order to explore the mathematical and practical issues of assimilating data from cloudy radiances, a study has been performed using an idealised single column atmospheric model developed for this purpose. The model simulates cloud development in an atmosphere with vertical motion and the effects on simulated infra-red satellite observations. An empirical method and a variational data assimilation system have been developed to process sequences of observations over a six hour time with the goal of calculating vertical velocity. These two methods combined allow vertical velocity to be determined with an RMS error of approximately 0.8 cm/s in 80% of cases. The system is capable of detecting the remaining cases where there is insufficient information in the observations to constrain vertical velocity. This result is the first step in the long term goal of using cloud-affected satellite imagery more effectively in operational weather prediction systems. The ability to use these observations in this way would improve the forecasting of severe weather events, helping to protect lives and property from loss or damage.

Item Type: Thesis (Doctoral)
Divisions : Theses
Authors :
AuthorsEmailORCID
Wakeling, Matthew N.matthew@wakeling.homeip.netUNSPECIFIED
Date : 30 October 2015
Funders : EPSRC
Contributors :
ContributionNameEmailORCID
Thesis supervisorEyre, Johnjohn.eyre@metoffice.gov.ukUNSPECIFIED
Thesis supervisorHughes, SueSue.Hughes@surrey.ac.ukUNSPECIFIED
Thesis supervisorRoulstone, IanI.Roulstone@surrey.ac.ukUNSPECIFIED
Depositing User : Matthew Wakeling
Date Deposited : 09 Nov 2015 09:13
Last Modified : 09 Nov 2015 09:13
URI: http://epubs.surrey.ac.uk/id/eprint/808701

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800