R. Checa-Garcia webpage | My Academic Overview

Overview of my research and computing experience

Academic

One thing I have learned in a long life: that all our science, measured against reality, is primitive and childlike – and yet it is the most precious thing we have. ― Albert Einstein

General Overview

My main field of research is the climate response to several agents on the atmosphere, either greenhouse gases or aerosols. However, my academic career started with a B.A. in Spanish from the University of Granada, where I graduated on Physics with an specialization on Theoretical Physics. Awarded with a scholarship, I obtained a M.Sc. on Condensed Matter with an dissertation about Theory of Liquids (Statistical Physics of Fluids) at the University Autónoma of Madrid, wehere also I was teacher assistant on Laboraties of Experimental Physics during two years. In the field of Atmospheric Sciences, I have a PhD on Remote Sensing and Micro-physics of Precipitation at Spain with an stage at NASA Goddard Space Center (sponsored by University of Maryland-Baltimore County). My experience as Postdoctoral research assistant includes the institutions:

  • Karlsruhe Institute of Technology (Germany), where I worked on ESA-Sentinel-5 and G3E projects (remote sensing of greenhouse gases).
  • The University of Reading, in collaboration with Keith Shine and M. Hegglin, where I studed the radiative forcing of several agents on the atmosphere, in particular Ozone.
  • Laboratory for Sciences of Climate and Environment (LSCE) were I work for the CNRS on the climate modelling of Earth System with a focus on natural aerosols.

Participation in Projects

  • CRESCENDO: Coordinated Research on Earth Systems aand Climate: Experimentes, kNowledge, Dissemination and Outreach
  • AerChemMIP: Aerosols and Chemistry Model Intercomparison Project
  • AeroCOM Phase III: Aerosol Comparisons between Observations and Models
  • CCMI: Chemistry-Climate Model Initiative

Scientific Interests

My objectives are a better understanding of the climate response to greenhouse gases and aerosols, but also improve my knowledge of remote sensing applied on earth sciences. For the first question, I investigates the climate variability and radiative forcing estimations together with the role of the Ozone on the climate system (which is complemented by my interest on numerical models of atmospheric processes at several scales). My interest on remote sensing comprises develop simulations of the actual measurement conditions to assert the uncertainty and new applications of remote sensing, but also in-situ measurement to calibrate, test and validate satellite products and improve retrieval algorithms. I am interested on carbon cycle and water cycle application of remote sensing science.

Due to my professional trajectory my interest is also related with mathematical methods, in particular those related with statistics and statistical physics, together with scientific computing.

Membership of Professional bodies

  • Royal Meteorological Office
  • European Geosciences Union
  • American Meteorological Society
  • American Geophysical Union

Conceptual Map of my research background and experience

Conceptual Mind-Map of my Research Background.

Computing

Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less. ― Marie Curie

Overview


My daily research job is done with computers, that I use for data analysis of experimental data, and for modelling/simulation of physical processes. Therefore an important part of my background and skills rely on an area usually named: scientific computing. Traditionaly, for a Physicist, this implied to know how to program with Fortran but not much more (maybe complemented with basic understanding of Linux/Unix). Nowdays, the situation is different and scientific computing means a long list of tools and skills that a researcher should know, but even more she/he has to be able to choose the best possible tool for an specific problem between a large set of utilities and methodologies. As a consequence several academic programs include a kind of formation unofficially named software carpentry.

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My scientific computing carpentry

Programming

  • Fortran 90 (also 77 but I try to avoid)
    • LAPACK / BLAS
  • Python
    • numpy
    • scipy
    • Pandas
    • statmodels
    • xarray
    • iris (of scitools)

Visualization

  • Python
    • Matplotlib, Basemap
    • Cartopy
  • GNUplot

File Formats

  • netCDF
  • HDF5
  • GRIB

Automatization and scripting languages

  • make
  • bash
  • Pure Python

Documenting code

  • Doxygen
  • Sphinx

Project Software Managment

  • Trac

Version Control

  • Subversion (svn)
  • git
  • Mercurial (Hg)

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