Research summary

I perform research using probabilistic inverse modeling techniques such as Markov chain Monte Carlo (MCMC) to quantify microphysical paramterization uncertainty in cloud resolving models.

In particular, I am interested in understanding better what types of observations (such as radar reflectivity) provide the best constraint on microphysical parameterization uncertainty.

Eventually this research may help improve how cloud and microphysical processes are represented within models. This in turn may help improve the fidelity of weather forecasts which help to warn of severe weather.

This research is funded under NSF grant AGS 1019184 and is conducted under the supervision of Dr. Tomislava Vukicevic (NOAA/AOML/HRD) and in collaboration with Dr. Derek J. Posselt (University of Michigan).

In Layman's Terms...

I try to make clouds fluffier.

Publications, Talks & Posters

Under Construction!

What you should know:

Name:

Marcus van Lier-Walqui

Occupation:

Graduate student (3.5th year PhD)

University:

Rosenstiel School of Marine and Atmospheric science

Location:

Miami, FL

Research Interests:

  • Inverse Modeling
  • Data Assimilation
  • Cloud Microphysics
  • Radar Meteorology
  • Convective Processes
  • Uncertainty Quantification

Advisors:

Tomislava Vukicevic (NOAA/AOML/HRD)

Sharan Majumdar (RSMAS)

Collaborators:

Derek J. Posselt (Univ. of Michigan)

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