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Using Trace Gas Measurements to Infer Aerosol Type

Supervisors: Dr Don Grainger (Department of Physics, University of Oxford)
Dr Anu Dudhia (Department of Physics, University of Oxford)

Scientific Background

The effect of atmospheric aerosols is the most poorly quantified element of the Earth's radiative budget (see Figure 1). Aerosols act directly by reflecting or absorbing solar radiation, or indirectly by altering cloud properties. This project focuses on understanding the direct effect of aerosols. Ground and aircraft based instruments can be used to measure aerosol properties locally whereas satellite measurements provide a global perspective. Progress has been made in using satellite instruments to quantify aerosol optical depth and particle size (using, for example, NASA's Moderate Resolution Imaging Spectrometer, MODIS, or ESA's Advanced Along Track Scanning Radiometer, ATSR) but much uncertainty remains in the type of aerosol being observed. Understanding the type of aerosol is critical as measurements from a thin layer of highly reflective aerosol can be indistinguishable from a thicker layer of strongly absorbing aerosol. Without knowledge of aerosol type it is not possible to tell if solar radiation has been reflected harmlessly back to space or absorbed into the atmosphere, further heating the Earth-atmosphere system.

Figure 1. Radiative forcing of climate change during the Industrial Era shown by emitted components from 1750 to 2011. From: Fifth Assessment Report - Climate Change 2013 (IPCC, 2013).

Aim

The aim of this project is to quantify aerosol absorption (as opposed to scattering) over an annual cycle, globally.

Description

The Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm is open source software developed by EODG in conjunction with scientists at the Rutherford Appleton Laboratory. The code is used to infer aerosol (and cloud) properties from radiometer imagers such as MODIS, the Sea and Land Surface Temperature Radiometer (SLSTR) and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). Currently ORAC uses a combination of spectral signature augmented by geographic location to select a most probable aerosol type. This is not always successful. In this project additional measurements of aerosol-forming gases will be used to construct a prior probability of aerosol type. This will be used within ORAC to create a best guess of aerosol type.

The Infrared Atmospheric Sounding Interferometer (IASI) is a nadir-viewing Fourier transform spectrometer carried on the MetOp series of satellites (October 2006 - ~2030). Work within EODG has shown IASI can provide information on gases that form aerosol (e.g. SO2 or NH3) or gases associated with industrial pollution or biomass burning (e.g. CO or HCN). The goal of this project is to use the IASI gas measurements to improve ORAC's prediction of aerosol type. For example an enhanced value in the linear flag of SO2 will be used to increase the likelihood of the ORAC algorithm selecting sulphate aerosol. Much of the work will involve optimising the choice of aerosol given the values of the gas measurements. Once the method is finalised the algorithm will be applied to at least a year of data and the results analysed to give a measure of absorbing versus non-absorbing aerosol. If time permits further investigations could include fire emission indices, aerosol-formation mass budgets or aerosol composition climatologies.

Year 1 Review literature, identify critical gas species associated with aerosol types (sulphate, biomass burning, polluted urban, continental, maritime, ammonium salts). Use existing IASI data to build daily global fields of aerosol type. Develop a method to estimate type when IASI data are missing or obscured by cloud. Use the new a priori type information within ORAC for regional studies (e.g. Sahara, Amazon, south Pacific, Denmark) and evaluate its performance.
Year 2 Refine the approach based on the evaluation case studies. Process at least a year of data using the new method and evaluate. Write a paper on the new technique.
Year 3 At the student's discretion investigate a further topic associated with the new dataset. Write-up thesis.

Skills that would be helpful:

Computing, atmospheric radiative transfer, remote sensing, chemistry.

Relevant Background Documents

Walker, J.C., A. Dudhia and E. Carboni, An effective method for the detection of trace species demonstrated using the MetOp Infrared Atmospheric Sounding Interferometer, Atmospheric Measurement Techniques, 4, 15671580, 2011.

Trace Species and Aerosol Flagging with IASI Data, H. Touche, 2015.

Thomas, G.E., C.A. Poulsen, R. Siddans, A.M. Sayer, E. Carboni, S.H. Marsh, S.M. Dean R.G. Grainger and B.N. Lawrence, Validation of the GRAPE single view aerosol retrieval for ATSR-2 and insights into the long term global AOD trend over the ocean, Atmospheric Chemistry and Physics, 10, 48494866, 2010.

Earth Observation Data Group, Department of Physics, University of Oxford. Page last updated: @12:46 GMT 20-Aug-2021