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University College London Featured PhD Programmes

Towards improved weather forecasting via IASI satellite observations of carbon dioxide

  • Full or part time
  • Application Deadline
    Friday, January 10, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

The assimilation of satellite radiances is crucial for Numerical Weather Prediction (NWP) models with the benefit approximately evenly split between infrared and microwave data. The Infrared Atmospheric Sounding Interferometer (IASI) instruments, on board the MetOp-A, -B, and -C satellites, designed to provide accurate atmospheric temperature and humidity profiles, have the largest impact on the NWP skill. The Met Office currently uses a few hundred IASI channels in their operational data assimilation system, mainly in the CO2 absorption band around 667 cm-1 (15 μm), which benefits from low instrument radiometric noise to obtain substantial information on the vertical temperature structure. 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 (covering up to 25 % of the globe) are more difficult to detect. If cloud-contaminated radiances are misidentified as clear-sky and assimilated into NWP models, the forecasts can be significantly degraded. IASI instruments can also detect a multitude of atmospheric trace gases, thereby providing information on atmospheric chemistry, climate, and pollution.

IASI-NG will launch ~2021, with similar radiometric noise but twice the spectral resolution of IASI. To gain optimal benefit from IASI and IASI-NG in the NWP system, there is a requirement for highly accurate fast radiative transfer codes as forward model operators in the data assimilation system. These fast models are trained on line-by-line models, which use spectroscopic line parameters from atmospheric spectroscopic databases such as HITRAN to model the absorption of trace gases, including CO2. The default Voigt lineshape in HITRAN is inadequate in accurately representing real atmospheric spectra. As part of this project, new spectroscopic measurements of CO2 will be analysed to derive state-of-the-art Hartmann–Tran profile (HTp) line parameters. 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.

Entry requirements

UK Bachelor Degree with at least 2:1 in a relevant subject or overseas equivalent.


Project Enquiries: Dr Jeremy Harrison,

Funding Enquiries:

How to apply

Please follow refer to the How to Apply section at and use the Physcis Apply button to submit your PhD application. Upload your CENTA Studentship Form in the proposal section of the application form.

In the funding section of the application please indicate you wish to be considered for NERC CENTA Studentship
Under the proposal section please provide the name of the supervisor and project title/project code you want to apply for.


Available for UK and EU applicants only

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

Funding Notes

This project 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

The studentship includes a 3.5 year tuition fee waiver at UK/EU rates

An annual tax free stipend (For 2019/20 this is currently £15,009)

Research Training Support Grant (RTSG) of £8,000


August, T., Klaes, D., Schlüssel, P., Hultberg, T., Crapeau, M., Arriaga, A., O'Carroll, A., Coppens, D., Munro, R., Calbet, X. (2012), IASI on Metop-A: Operational Level 2 retrievals after five years in orbit. J. Quant. Spect. Rad. Trans., 113, 1340-1371. doi:10.1016/j.jqsrt.2012.02.028

Dudhia, A. (2017), The Reference Forward Model (RFM) (2017). J. Quant. Spect. Rad. Trans., 186, 243-253. doi:10.1016/j.jqsrt.2016.06.018

Havemann, S., Thelen, J.-C., Taylor, J.P., Harlow, R.C. (2018), The Havemann-Taylor Fast Radiative Transfer Code (HT-FRTC): A multipurpose code based on principal components. J. Quant. Spect. Rad. Trans., 220, 180-192. doi:10.1016/j.jqsrt.2018.09.008

Lavanant, L. , Fourrié, N. , Gambacorta, A. , Grieco, G. , Heilliette, S. , Hilton, F. I., Kim, M. , McNally, A. P., Nishihata, H. , Pavelin, E. G. and Rabier, F. (2011), Comparison of cloud products within IASI footprints for the assimilation of cloudy radiances. Q.J.R. Meteorol. Soc., 137: 1988-2003. doi:10.1002/qj.917

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