Research interests

Impacts of land-use change on rainfall

The land surface is a critical component of the climate system, as it controls the transfer of energy between the sun and the atmosphere. Changes in the land surface can therefore influence atmospheric properties, as well as the formation of clouds and rainfall. Nearly 40% of the Earth’s ice-free surface has already been converted to cropland or pasture, so land use and land cover change represent a large component of anthropogenic climate change. I am interested in understanding how changes in the land surface affect the distribution of clouds and rainfall, and how these processes are represented in weather and climate models.

Satellite images of clouds forming preferentially over deforested land in the Amazon (NASA worldview)

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Representation of tropical convection and clouds in weather and climate models

Rainfall is probably the climate parameter with highest importance for people, particularly in the tropics, but it remains a major source of uncertainty in climate models. Not only do climate models disagree on whether climate change will increase or decrease rainfall in the tropics, but they also have biases in the distribution of rainfall in time and space, and these biases are very similar across many models. In other words, ‘weather’ (as opposed to climate) is still a huge challenge, but it is weather events that we ultimately feel on the ground. My research aims to understand why these rainfall errors occur, and their impact on other aspects of the climate system.

Convective storm over West Africa (NASA)

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Consequences of climate model uncertainty for the prediction of climate impacts

Many human activities will be drastically affected by climate change, from agriculture to renewable energy generation. In order to prepare effective mitigation measures we need to know what these impacts will be. For example will we need to plant different crop varieties that can cope in a new climate regime? Will a dam we build today still provide sufficient energy in a few decades time? To address this issue we are increasingly using models to explicitly simulate these impacts. For example crop models can be used to simulate the lifecycle of specific varieties from planting to harvest using climate model data as inputs. This information can be used to estimate how yields will change, and what plant varieties will perform best in a future climate. Any model, however, can only be as good as its inputs. I am increasingly interested in expanding my work on climate model biases in rainfall to understand how they contribute to uncertainty in impacts predictions, and how climate information can be better used by policy makers.

Crop circles in Egypt (NASA)

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The Saharan Atmosphere

The Sahara has some of the highest near-surface temperatures and deepest boundary layers on Earth, it is a key driver of the West African monsoon, and it is the largest source of mineral dust to the atmosphere. Despite its importance for the climate system, the lack of observations due to its harsh environment has made it very difficult to study atmospheric processes in this region, and has limited our ability to evaluate models. Thanks to the Fennec field campaign (2011-2012), as well as satellite data and models, I have worked on advancing our knowledge of this critical but understudied environment, from the Saharan boundary layer dynamics, to the large-scale representation of the Saharan heat low in models.

Satellite image over the Sahara showing a dusty cold pool (pink) created by a convective storm (red) (SEVIRI data courtesy of Eumetsat)

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