School of Earth and Environment
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Beatriz Monge-Sanz Dr Beatriz Monge-Sanz

Visiting Researcher

Telephone number: +44(0) 113 34 36473
Email address: b.m.monge-sanz@leeds.ac.uk
Room: 10.127

Biography

Qualifications

  • PhD Atmospheric Science (Univ. of Leeds, U.K.).
  • MRes in Electronics (Univ. of Zaragoza, Spain).
  • MSc in Physics (Univ. of Zaragoza, Spain).

Research Interests

  • Atmospheric chemistry and transport processes modelling.
  • Reanalyses and climate trends.
  • Climate change impacts, mitigation and adaptation.
  • Non-linear adaptive modelling techniques.
  • Science communication.

Research Projects:

  • COTTEE: Comparison of Tracer Transport and ECMWF Experiments.
  • MACC: Monitoring Air Composition and Climate.
  • CLICAR: Climate-Chemistry feedbacks in the Arctic region.

Research Experience

Since 2008 Beatriz is a Postdoctoral Research Fellow at the School. Her work is concerned with interactions between atmospheric composition and climate, both in the troposphere and the stratosphere. She has also analysed the causes for improvements in recent stratospheric (re)analyses using the TOMCAT/SLIMCAT chemistry-transport model (CTM). Beatriz also works on the parameterisation of greenhouse gases (O3, CH4, H2O) in the stratosphere, and the implementation of these parameterisations in global CTMs, NWP and climate models.

Beatriz obtained her degree in Physics from the University of Zaragoza (Spain) and did research in Atmospheric Science at ‘La Sapienza’ Univeristy in Rome (Italy). There she studied total ozone trends and circulation patterns in the Northern Hemisphere, and learned about LIDAR and Brewer instrumentation. She also holds an MRes in Electronics from the University of Zaragoza.

She joined the School in January 2005 to carry out her PhD studies supervised by Prof. Martyn Chipperfield. Her PhD project concerned testing stratospheric transport in ECMWF datasets (including ERA-Interim experiments) as well as testing and improving the treatment of ozone and stratospheric water vapour in the ECMWF forecast model.

Publications