Global measurements of Sea Surface Temperature using the Infrared Atmospheric Sounding Interferometer
Global Sea Surface Temperature (SST) is an important parameter in weather forecasting and climate monitoring. The remote sensing principle is simple:
measuring the radiance emitted by the sea surface in an infrared atmospheric window region. The difficulty is in obtaining a useful accuracy of a few tenths of Kelvin, which imposes strict requirements on radiometric calibration and radiative transfer modelling.
Starting in 1991 there has been a series of satellite instruments specifically designed to provide accurate SST measurements. These are well-calibrated broad-band radiometers with approx 1km spatial resolution. However, since the demise of AATSR (on Envisat) in April 2012 and the launch of SLSTR (on Sentinel 3) in February 2016 there has been a 4-year gap during which SST measurements have been obtained from the less well-calibrated AVHRR instruments on the NOAA and MetOp satellites.
The aim of this project is to derive SST data from the IASI instruments which have been operating on the the MetOp satellites since 2006. IASI is an infrared fourier transform spectrometer, with high spectral resolution (0.5cm-1) but relatively low spatial resolution (12km). Measuring the full spectrum not only allows the synthesis of the broadband radiometer channels of the other instruments but also resolves atmospheric absorption features (primarily H2O and CO2) which should lead to more sophisticated techniques for correcting for atmospheric effects.
The envisaged tasks are as follows a) Use IASI to simulate measurements from the AVHRR instrument (on the same MetOp) platform to establish an improved radiometric calibration for AVHRR. b) Use IASI to simulate AATSR and SLSTR channels to provide a transfer standard across the 4-year gap c) Develop an IASI-specific SST retrieval algorithm utilising the full spectral resolution
The CASE partner for the project is the UK Met Office, and the co-supervisor will be Roger Saunders, head of the Satellite Applications group. While at the Met Office the main scientific task is to compare the IASI SSTs with the OSTIA SST analysis generated there using all the available satellite and in-situ data. This would involve an element of training in using large model datasets in the analysis. Working at the Met Office is also an opportunity to learn from the scientists in the Satellite Applications group on the use of satellite data for numerical weather prediction. There are also possible opportunities to attend training courses at the Met Office College.
Please contact Anu Dudhia firstname.lastname@example.org to apply.
- CASE Projects available for students starting in 2020
- Mechanisms for variability of the Quasi-Biennial Oscillation in laboratory and numerical models
- Improving environmental, social and economic outcomes of nationally significant infrastructure projects
- Integrating socio-economic impacts in marine resource management
- Mechanisms and impacts and of host-parasite relationships
- Quantifying the role of AMOC decline in climate change impacts
- Drivers of life history variation in flatworms
- Movement analysis of zooplankton through filming
- Can humanity have its cake and eat it too? Extending the Mitigation Hierarchy to support implementation of international biodiversity targets in the context of the Sustainable Development Goals
- Near-source effects on global wavefields: A forensic seismology study applied to nuclear monitoring
- The fate of mercury (Hg) during thermal maturation of sediments and its implications for interpreting the geological record
- Native and invasive ladybirds in a changing U.K. climate
- A unified approach to multi-scale modelling of wind farms and complex terrain
- Terrestrialisation in vertebrates using evidence from synchrotron tomography
- The dynamics of flowing, subsurface salt sheets: observational constraints and theoretical models
- Beyond the mean: using drones to understand spatial drivers of phenological responses
- Global measurements of Sea Surface Temperature using the Infrared Atmospheric Sounding Interferometer
- Using marine UAVs to integrate seabird census with phenology
- Seabird Watch: testing out of the box image analysis methods and citizen science data for large-scale monitoring of seabirds.
- Bayesian models for the analysis of botanical citizen science data: Understanding bias and improving inference