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  2. Dr Philip Bernard Holden

Dr Philip Bernard Holden

Profile summary

  • Central Academic Staff
  • Lecturer in Earth System Science
  • Faculty of Science, Technology, Engineering & Mathematics
  • School of Environment, Earth & Ecosystem Sciences
  • philip.holden

Research interests

Phone: +44 7095 351 332

My research centres upon the evaluation of Earth system uncertainty through the development and application of computationally fast models, both process-based and statistical, addressing past, present and future climate. I performed a suit of ~50 climate-carbon cycle ensemble experiments with GENIE for contribution to Working Group I of the IPCC Fifth Assessment Report (AR5).

My work uses GENIE (an intermediate complexity carbon-cycle model with a moderately complex representation of the physics and biology of the ocean) and PLASIM (a substantially more complex model of the atmosphere for use in climate projections). I have recently completed coupling these two models to create PLASIM-GENIE, a fully 3D intermediate complexity AOGCM, opening up a range of possible future applications. I am also interested in paleoclimate reconstruction from biological proxies and have developed and applied a computationally-fast user-friendly Bayesian transfer function BUMPER.

Recent published research includes:

Development of an emulator of the future climate change projections of PLASIM. An emulator is a statistical description of a model that produces a fast approximation to the model’s output, enabling applications that would not be possible with the model itself. Ongoing work has coupled this emulator to impact models to evaluate climate change impacts on crops, human health, energy demands for heating and cooling, and hydro-electric power potential.

Design of a model of land use change (a representation of land used for agriculture) that I have incorporated into GENIE. I applied the resulting model to derive a probabilistic quantification of the terrestrial carbon cycle response to fossil fuel emissions and also to build an emulator of the global carbon cycle. This emulator will provide a substantial upgrade for the carbon-cycle component of integrated assessment models, models that quantify fossil fuel emissions but lack a detailed description of what happens to the CO2 and how long it stays in the atmosphere.

Design of a large ensemble of coupled climate-carbon cycle configurations of GENIE that I have applied to investigate the uncertainty in oceanic uptake of CO2 and its isotopes. Work is ongoing to apply this ensemble to transient glacial-interglacial carbon cycle simulations.

A probabilistic calibration of the uncertainty of the simulated future Earth system response (climate, vegetation, ocean circulation and sea ice) to changes in atmospheric CO2, using ensembles of GENIE simulations constrained by Last Glacial Maximum climate.

GENIE ensembles of simulations of glacial climate to address i) the role of de-glacial melt-water forcing and, potentially, WAIS retreat in explaining the behaviour of Antarctic climate observed in the EPICA ice-core record and ii) the role of orbital changes in the glacial-interglacial variability of tropical vegetation. An on-going project is applying these simulations, together with emulations of PLASIM, to address the evolution of species diversity in South America over the last million years.

 

Research Activity

Research groups

NameTypeParent Unit
Centre for Earth, Planetary, Space and Astronomical Research (CEPSAR)CentreFaculty of Science

 

Externally funded projects

Plausible policy pathways to Paris

RoleStart dateEnd dateFunding source
Co-investigator31/Oct/201631/Jul/2018NERC NERC (Natural Environment Research Council)
The Paris agreement commits nations to pursuing efforts to limit the global temperature rise to 1.5 degrees. This represents a level of transformation of the socio-economic and energy systems that substantially exceeds the scenarios that have been found using most conventional integrated assessment models (IAMs) based on equilibrium assumptions. Such strong mitigation also violates the pattern scaling assumptions used to derive environmental impacts in IAMs because of the rapid reversal in emissions growth. We will use a new, fully dynamic IAM that does not rely on equilibrium or pattern scaling assumptions to provide a set of more realistic dynamic pathways to reach the 1.5 degree target. The assessment will identify policy options and the degree of negative emissions required.

Bayesian User-friendly Multi-Proxy Environmental Reconstructions (resubmission)

RoleStart dateEnd dateFunding source
Lead01/Jan/201631/Dec/2016University of Exeter
BUMPER is an “embedded research” project, aimed towards strengthening interdisciplinary connections and funded by ReCoVER (Research on Changes of Variability and Environmental Risk). The project addresses transfer functions, widely used tools to infer past climate from microfossil assemblages preserved in lake and ocean sediments. In collaboration with ecologists at the Florida Institute of Technology and NIMBioS (National Institute for Mathematical and Biological Synthesis, University of Tennessee), BUMPER is developing a computationally-fast Bayesian transfer function to produce a user-friendly tool for paleoecologists. The principal motivation for developing a Bayesian approach is the calculation of reconstruction-specific uncertainty that, for instance, greatly increases the power of multi-proxy reconstructions.

Quantifying Uncertainty in ANTarctic Ice Sheet instability

RoleStart dateEnd dateFunding source
Co-investigator01/Aug/201531/Jan/2016University of Exeter
Large parts of the Antarctic ice sheet lie on bedrock below sea level and may be vulnerable to a positive feedback known as Marine Ice Sheet Instability (MISI), a self-sustaining retreat of the grounding line triggered by oceanic or atmospheric changes. There is growing evidence MISI may be underway throughout the Amundsen Sea Embayment (ASE) of West Antarctica. If this is sustained the region could contribute up to 1-2 m to global mean sea level, and if triggered in other areas the potential contribution to sea level on centennial to millennial timescales could be two to three times greater. However, physically plausible projections of Antarctic MISI are challenging: numerical ice sheet models are either too low in spatial resolution to explicitly resolve grounding line processes or else too computationally expensive to assess modeling uncertainties. The proposed work brings together and analyses two new datasets that complement each other in model complexity – a large ensemble generated with a low resolution model, and a small ensemble from a high resolution model – by constructing a new emulator of the relationship between them.

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