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Climate Extremes and their Impact on the Land Carbon Sink

Dr Wolfgang Buermann (SEE), Prof Piers Forster (SEE)

Contact email: W.Buermann@leeds.ac.uk

Climate simulations show that vegetation is our friend – soaking up more and more carbon dioxide as human emissions rise. But such simulations do not do a good job of representing some of the effects of extreme weather. Recent observations are showing that extreme flood and droughts can damage the carbon sink. Your work will be the first effort to incorporate such extremes into future projections of carbon and climate.

Background

Over the last 6 decades or so, global ocean and land systems have taken up roughly half of the anthropogenic CO2 emissions. Interestingly, during this period these carbon sinks have increased steadily in concert with the emissions. This has thus mitigated the anthropogenic increase of atmospheric CO2 levels and provided a negative feedback in the climate carbon-cycle system (Friedlingstein et al. 2006). Fully coupled Earth system models are able to reproduce the increasing carbon uptake by ocean and land and attribute the increase of the land carbon sink to the combined effects of CO2, climate and nitrogen deposition. Future projections of ecosystem responses and associated carbon-climate feedbacks are, however, highly uncertain (Friedlingstein et al. 2006).

Recent studies have indicated that the occurrence of extreme events, for instance heatwaves, droughts, or storms, and the associated disturbances can partially offset carbon sinks or even cause net losses in carbon stocks, thereby releasing CO2 to the atmosphere (e.g. Page et al. 2002, Ciais et al. 2005; see also Fig. 1). Because extreme events can trigger immediate and time-lagged responses of ecosystems, such as mortality, fires or insect infestations (Anderegg et al. 2012), their effects on carbon fluxes and stocks are nonlinear.

Figure 1. The effect of the 2003 European heatwave on the carbon cycle. Panels show spatial patterns of changes in (A) surface temperature and (B) net primary productivity in the July-September period. Shown are the anomalies for 2003 relative to the prior 1998-2002 period. This figure is adapted from Ciais et al. (2005).

Climate change is characterized not only by changes in the mean climate state but also by changes in weather extremes (IPCC 2013). In this regard, multiple lines of evidence show that climate extremes have already become more frequent and intense since the mid-20th century (e.g. heatwaves; IPCC 2013). Under future climate change, this trend is expected to accelerate (Seneviratne et al. 2012). This, combined with the aforementioned non-linear nature of the adverse impact of climate extremes on the carbon cycle, has the potential to profoundly influence the carbon cycle under climate change. It is thus crucial to increase our knowledge base about interactions between extreme events and the carbon cycle.

In this project, a major goal is to better understand the influence of climate extremes on the terrestrial carbon cycle in both the contemporary climate and under future climate change.

Objectives

The objectives outlined below are suggestive and will also depend on your interests and background in this area of research. In the first phase of the project, a thorough understanding of climate science and ecosystem functioning from an observational and model perspective is anticipated. For example, how can vegetation dynamics be monitored from space? How complex are Earth system models? A possible research agenda for this project may involve:

  1. Contemporary record: Analyze frequency intensity of climate extremes and develop consistent metrics that characterizes their impacts on the land carbon cycle.
  2. Future climate projection: Analyze frequency and intensity of climate extremes in future model projections (e.g. CMIP6) and estimate their impact on the land carbon cycle using constraints based on the understanding of contemporary relationships of climate extremes and carbon cycle impacts.

Potential for high impact outcome

This PhD project uses the existing world-leading expertise within the School of Earth and Environment at the University of Leeds to address key issues in earth system science. By developing new and improved understanding as well as analyzing state of the art observational and model records, it will have the potential to have a major impact on earth system or climate science. Dr Buermann and Prof. Forster are internationally renowned scientists working on issues pertaining to carbon cycle science and climate science.

Training

Through this PhD project you will become familiar with a number of essential tools (models and observations) that are applied in the study of climate and carbon cycle science. You will benefit from working within a highly active and multidisciplinary group of scientists in the Physical Climate Change Group in SEE. Dr Buermann and Prof. Forster have also extensive international collaborations, and this PhD may also involve international travel for training purposes.

The successful PhD student will have access to a broad spectrum of training workshops put on by the Faculty that include an extensive range of training workshops in climate modelling, through to managing your degree, to preparing for your viva. A full listing is available through http://www.emeskillstraining.leeds.ac.uk/.

Requirements

A good first degree (1 or high 2i), or a good Masters degree in a physical or mathematical discipline, such as mathematics, physics, geophysics, engineering, meteorology, geography, or environmental science. Experience with programming languages is an advantage.

Further reading

Anderegg, W.R.L. et al. PNAS, 109, 233-237 (2012).

Ciais, P. et al. Nature 437, 529–533 (2005).

IPCC (2013) WG1 AR5 Chapter 12

Friedlingstein, P. et al. J. Clim. 19, 3337–3353 (2006).

Page, S.E. et al. Nature 420, 61–65 (2002).

Seneviratne et al. IPCC Special Report (2012).

Related undergraduate subjects:

  • Agriculture
  • Applied mathematics
  • Atmospheric science
  • Biodiversity
  • Biodiversity conservation
  • Biology
  • Chemistry
  • Computer science
  • Computing
  • Engineering
  • Geography
  • Geophysics
  • Geoscience
  • Mathematics
  • Meteorology
  • Natural sciences
  • Oceanography
  • Physical science
  • Physics
  • Remote sensing
  • Soil science