\ Hurricane Research Division of AOML/NOAA
Printer Friendly Version

NOAA's Atlantic Oceanographic and Meteorological Laboratory
4301 Rickenbacker Causeway
Miami, FL 33149

Professional Interests

Dr. Quirino is an IT Specialist at the US National Oceanic and Atmospheric Adminsitration's (NOAA) Hurricane Research Division (HRD). His research interests include applied evolutionary search and optimization, machine learning, data mining, distributed memory programming, numerical modeling, Unix system security and managament, and tropical cyclones.

In 2007, Dr. Quirino had the privilege to join NOAA's HRD Numerical Modeling Group, where he has since then worked on the development of NOAA's HWRF model. His work includes the development of end-to-end model automation systems that manage HWRF model forecasts in real-time, model graphical visualization systems, model-to-obs intercomparison diagnostics, and advanced parallelization/speed-up of the HWRF model infrastructure under high-resolution forecast loads. Along with other group members, he has worked on the development of the latest Basin-scale HWRF model, the first ever NOAA research model capable of forecasting multiple storms simultaneously in high-resolution. He has also maintained important Unix systems that are vital to HRD's strategic research plan.

Dr. Quirino received his Bachelors (2004), Masters (2005), and and Doctor of Philosophy (2012) degrees in Electrical and Computer Engineering from the University of Miami, Coral Gables, FL, where he was part of the Distributed Decision Environment (DDE) laboratory of the College of Engineering. His dissertation focused on the the development of Evolutionary Strategies capable of automatically designing both more accurate and computationally efficient pattern recognition systems.

Current Research Projects

    Recently Published Peer-Reviewed Papers

    1. Cai, W.-J., R.A. Feely, J.M. Testa, M. Li, W. Evans, S.R. Alin, Y.-Y. Xu, G. Pelletier, A. Ahmed, D.J. Greeley, J.A. Newton, and N. Bednarsek. Natural and anthropogenic drivers of acidification in large estuaries. Annual Reviews of Marine Science, 13:23-55, (https://doi.org/10.1146/annurev-marine-010419-011 2021
    2. Chen, N., T. Tang, J.A. Zhang, L.-M. Ma, and H. Yu. On the distribution of helicity in the tropical cyclone boundary layer from dropsonde composites. Atmospheric Research, 249:105298, https://doi.org/10.1016/j.atmosres.2020.105298 2021
    3. Cucurull, L., and S.P.F. Casey. Improved impacts in observing system simulation experiments of radio occultation observations as a result of model and data assimilation changes. Monthly Weather Review, https://doi.org/10.1175/MWR-D-20-0174.1 2021