TroPeaCC

TroPeaCC

Tropical Peatlands and the Carbon Cycle

David Hein-Griggs, University of Exeter

David is a scientific software engineer in the Geography Department at the University of Exeter. His background is in computer science, completing a BSc in Computer Science at the University of Arkansas, USA. After moving to England in 2001, David got a job at the Met Office in Exeter where he worked in the Regional Climate Modelling team in the Met Office Hadley Centre until 2017, completing an MSc from the University of Reading in Weather and Climate Modelling in 2008. David helped to write a user friendly regional climate model which ran on a PC or laptop as part of the UK’s commitment to transfer technology to UNFCCC non-Annex I countries. In addition to help write the regional climate model and produce a graphical user interface to the underlying model (so that users could configure and run the model using only a mouse), David also travelled extensively to meteorological offices in South America, Africa and Asia where he ran over 50 week long training workshops where local meteorologists were taught the science of climate change and climate modelling as well as how to run and interpret the regional model output data.

Since joining Geography at Exeter in 2017, David has specialised in teaching and teaching support for undergraduate Physical Geography modules. This includes modules involving Geographic Information Systems (GIS) and any modules which require use of specialised scientific software. David does direct teaching in GIS as well as Numerical Methods, where he teaches the computer language Python. David also acts as a resource person for undergraduate and postgraduate dissertation students, providing specialised technical support in software, computer models and scientific data.

David is also involved in a number of ongoing research projects, where he lends his technical skills in deploying, configuring and running models on Linux workstations and HPCs. David continues to act as peer-reviewer for publications involving regional climate modelling.