Assessing links between vegetation and dust emission using Earth observation data

Abstract

Mineral dust aerosol is a key component of the Earth system, affecting the planet's radiative balance, weather and biogeochemistry as well as having a significant impact on human health and economic well-being. Despite its importance, it is currently poorly represented in global climate models. As a consequence, predicting future dust loading and any associated physical processes is hampered by a high level of uncertainty. A significant factor underpinning the poor representation of dust in models arises from a lack of understanding of the processes that govern its emission at the resolution of these models.

In this thesis, a new global dataset of dust emission is derived using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue Collection 6 aerosol dataset. Robust thresholding is applied to the dataset in order to distinguish dust at uplift from aged dust and other aerosols. Threshold values are determined through a global statistical analysis of manned observations of dust at uplift. The resulting dataset compares well to other remotely sensed dust uplift datasets.

Controls on dust emission are examined by incorporating the new dust emission dataset in a generalised linear model. Candidate predictor variables that have been suggested to play a controlling role in dust emission are regridded to a common monthly 0.5 degree grid for this purpose. For the first time, a global statistical model is used to confirm and quantify a number of expected relationships between vegetation and climate variables and dust uplift frequency. Other quantities often used in the parameterisation of dust emission, such as the presence of pans, are not found to play a key role in suppressing dust emission at the scale of the study.

The detection of dust aerosol often relies on its direct radiative effect in the longwave, a characteristic considered unique among aerosols emitted from the land surface. This assumption is interrogated in this thesis through the examination of a longwave signal from a biomass burning plume in Southern Africa. A series of sensitivity studies using a radiative transfer model are performed to establish that a dust component is not required to replicate the signal. The longwave direct radiative efficiency of the pure biomass burning aerosol case tested here is found to have a value of 4.53Wm-2 per unit aerosol optical depth. The longwave direct effect of biomass burning aerosol in the longwave has possible implications for the understanding of the aerosols's impact on climate and suggests further measurements of the optical properties in the longwave are required.