methods for assimilating satellite data in numerical weather prediction
We are seeking a talented and highly motivated student for a
fully funded PhD studentship, based at the University of Reading, to commence in September 2019. The studentship is funded through the
Scenario NERC DTP.
Brief description of PhD project: The significant value of assimilating satellite data in numerical weather prediction relies on our ability to correct biases
in the data before it is assimilated. However, in order to quantify the bias in the observations it is often assumed that the forecast model itself is unbiased. Unfortunately this is rarely true and is becoming a limiting factor in the use of satellite data.
This project will develop new mathematical techniques for performing bias correction that are able to distinguish and correct for biases in both the observations and model.
This is of significant importance for the continued advancement of weather predictability.
Supervisors: Dr Alison Fowler and Dr Amos Lawless (University of Reading and National Centre for Earth Observation), and Dr John Eyre (Met Office)
Training opportunities: This studentship is a joint project with the Met Office. The student will have the opportunity to spend time working at the Met Office over
the lifetime of the project. The student will also have the opportunity to attend ECMWF training courses on data assimilation and advanced training courses at Reading organised by the Data Assimilation Research Centre.
The deadline for applications for 2019 entry is 25
January 2019. If you are interested in knowing more about this project, please contact
firstname.lastname@example.org for further information.