Postgrad LIVE! Study Fairs

Birmingham | Edinburgh | Liverpool | Sheffield | Southampton | Bristol

CeMM Featured PhD Programmes
University of Oxford Featured PhD Programmes
University College London Featured PhD Programmes
University of Glasgow Featured PhD Programmes
University College London Featured PhD Programmes

Towards improved weather forecasting: the retrieval of temperature and cloud properties from IASI using new carbon dioxide spectroscopic line parameters

Project Description

The Infrared Atmospheric Sounding Interferometer (IASI) instruments, on board the MetOp-A and MetOp-B satellites (a third on MetOp-C should be launched in November 2018), are primarily meteorological instruments designed to provide accurate atmospheric temperature and humidity profiles with which to improve numerical weather prediction (NWP). These instruments are able to detect trace gases in the atmosphere using their distinctive spectral infrared fingerprints, thereby providing information on atmospheric chemistry, climate, and pollution.

Spectral bands of carbon dioxide (CO2) are used to retrieve atmospheric temperature profiles from IASI observations. The channels primarily used are those with minimal sensitivity to other absorbing species such as water. Most commonly the absorption bands of CO2 used are ~667 cm-1 (15 μm) and ~2350 cm-1 (4.3 μm), although the latter band in IASI spectra has higher radiometric noise. The 15 μm band is also used to determine cloud top pressure and cloud fraction, using for example the CO2-slicing method. The detection of clouds is a large source of uncertainty in infrared satellite data assimilation in NWP. Unlike optically thick clouds, optically thin clouds such as cirrus (which cover up to 25 % of the globe) are more difficult to detect. If cloud-contaminated radiances are treated as clear-sky measurements and then assimilated into NWP models, the forecasts can be significantly degraded.

The atmospheric radiative transfer models used to analyse the IASI radiances use spectroscopic line parameters from atmospheric spectroscopic databases such as HITRAN to model the absorption of trace gases, including CO2. The Voigt lineshape, the default lineshape in HITRAN, is inadequate in accurately representing real atmospheric spectra. New lineshape models have been proposed, for example the Hartmann–Tran profile, which accounts for effects such as Dicke narrowing and speed-dependence; the effects of collisional interferences between lines (i.e. line-mixing) can be accounted for using the Rosenkranz first-order approximation.

New spectroscopic measurements of CO2 have recently been made, from which new non-Voigt line parameters will be derived as part of this project. These will then be used in radiative transfer calculations and retrievals of temperature and cloud properties, and improvements in these retrieved quantities will be investigated.

The student will analyse laboratory infrared spectroscopic measurements of carbon dioxide and generate non-Voigt spectroscopic line parameters. These data will be utilised in several atmospheric radiative transfer codes and retrieval schemes for temperature and cloud properties: (1) the Reference Forward Model (RFM), a traditional line-by-line radiative transfer model, with the University of Leicester IASI Retrieval Scheme (ULIRS); and (2) the Havemann-Taylor Fast Radiative Transfer Code (HT-FRTC), a fast code based on principal components, and the associated 1DVar retrieval scheme. Using these two schemes, improvements in retrieved temperature profiles and cloud information will be ascertained for (a) the new non-Voigt parameters relative to the previous HITRAN Voigt parameters for the same IASI CO2 channels as currently used in Met Office IASI assimilations; and (b) the use of additional CO2 channels in retrievals when using the new non-Voigt parameters.

This studentship provides an exciting multidisciplinary opportunity to work with cutting-edge satellite observations and atmospheric radiative transfer techniques in a challenging area of atmospheric science. This project covers a range of topics: atmospheric spectroscopy; remote sensing; the interpretation of retrieved quantities; data visualisation & analysis.

The student will be affiliated to the National Centre for Earth Observation (NCEO), through which they will obtain additional training opportunities and interaction with scientists working in Earth observation. The student will also have the opportunity for short research placements at the Met Office, where they will be exposed to an “operational” environment.

Entry requirements:

Applicants are required to hold/or expect to obtain a UK Bachelor Degree 2:1 or better in a relevant subject. The University of Leicester English language requirements ( apply where applicable.

How to apply:

Please refer to the CENTA Studentship application information ( on our website for details of how to apply

As part of the application process you will need to:
• Complete a CENTA Funding form – to be uploaded to your PhD application
• Complete and submit your PhD application online applying for Physics Research. Indicate project CENTA2-NCEO-HARR in the funding section.
• Complete an online project selection form Apply for CENTA2-NCEO-HARR

Project / Funding Enquiries: Dr. Jeremy Harrison,

Application enquiries to

Closing date for applications: 21st January 2019 (12pm midday)

Funding Notes

This studentship is one of a number of fully funded studentships available to the best UK and EU candidates available as part of the NERC DTP CENTA consortium.

For more details of the CENTA consortium please see the CENTA website: View Website

Applicants must meet requirements for both academic qualifications and residential eligibility: View Website

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully

FindAPhD. Copyright 2005-2018
All rights reserved.