Programmer/Research Associate IV
Technical Summary:
- Degreed Meteorologist and Electrical Engineer specializing in the processing and visualization of real-time remote sensing and forecast model data
- Extensive software engineering experience supporting operational forecasters by maintaining the real-time acquisition of meteorological data and the generation, dissemination, archiving, and visualization of products
- Programming Languages: Python, Bash, JavaScript, PHP, Perl, C, HTML/CSS, SQL
- Technologies: AWS cloud architecture, React.js, Next.js, jQuery, Bootstrap, MapServer, GeoServer, GDAL, OpenLayers, Docker, Apache HTTP, Rocoto, ecFlow, ELK stack, LDM, NOAAPort, AWIPS II, McIDAS
- Developer Tools: Visual Studio Code, Eclipse, Git/GitHub/GitLab, Redmine, Jenkins, Gerrit
- Data Formats: GRIB, NetCDF, HDF, GeoTIFF, GeoJSON, JSON, XML, HDF, Shapefile, McIDAS Area, KML
Recent Professional Experience:
- Stationed at the National Weather Service’s Meteorological Development Lab (MDL)
- Supervise a team of geographically-dispersed CIRA research associates
- Provide full-lifecycle software engineering expertise for projects at the MDL, including requirements analysis, design, development, configuration, documentation, review, and testing
- Lead software developer of the AWS-based Whole Story Uncertainty & Probabilities (WSUP) web application.
- This GIS tool provides forecasters with 1200+ elements from the National Blend of Models (NBM), Global Ensemble Forecast System (GEFS), National Digital Forecast Database (NDFD), Real-Time Mesoscale Analysis (RTMA), and Unrestricted Mesoscale Analysis (URMA), and various storm surge models in real-time utilizing technologies like MapServer, OpenLayers, Bootstrap, jQuery, Python, PHP, JavaScript, and AWS (EC2, S3, load balancers, Lambda, etc.). Features include displaying forecast evolution over time (dProg/dt), comparing forecast values with min/max station records, animation download tool, user-selectable color tables, cursor sampling, and an auto-updating mode to always display latest data.
- Design and manage real-time processing of model data on a Linux-based NWS supercomputer (WCOSS) with output disseminated by the WSUP Viewer and NOAA Open Data Dissemination S3 buckets in various formats (GRIB, TIF, GeoJSON, etc.). The processing uses a combination of Python, Bash, and the PBS HPC job scheduler. A Rocoto-based workflow management solution defines, launches, and tracks over 900 hourly tasks and their associated dependencies.
- All code for this project is under Git version control with Jenkins and Gerrit used for code review and merging with Redmine used for task tracking
- Member of a team utilizing Artificial Intelligence (AI)/Machine Learning (ML) techniques to produce probabilistic fire weather guidance. Responsible for developing the Rocoto- and ecFlow-based real-time data flow pipeline running on an NWS HPC system (WCOSS).
Recent Publications:
- Molthan, A. L., L. A. Schultz, K. M. McGrath, J. E. Burks, J. P. Camp, K. Angle, J. R. Bell, and G. J. Jedlovec, 2020: Incorporation and Use of Earth Remote Sensing Imagery within the NOAA/NWS Damage Assessment Toolkit. Amer. Meteor. Soc., 101, E323–E340.
- Shrestha, S., K. M. McGrath, G. T. Stano, C. J. Schultz, P. J. Meyer, 2019: Real-Time Data Management and Visualization for Geostationary Lightning Mapper (GLM) in ArcGIS Platform. 99th Annual Meeting, Amer. Meteor. Soc., Phoenix, Arizona.
- McGrath, K. M., P. J. Meyer, G. J. Jedlovec, E. B. Berndt, 2018: NASA MSFC GOES-16 Receiving Station and Data Visualization. 98th Annual Meeting, Amer. Meteor. Soc., Austin, Texas.
- McGrath, K. M., E. B. Berndt, C. M. Gravelle, L. A. Byerle, A. L. Molthan, M. R. Smith, 2018: AWIPS II Client-side RGB Product Generation in the GOES-R Era. 98th Annual Meeting, Amer. Meteor. Soc., Austin, Texas.
- Stano, G. T., P. J. Meyer, K. M. McGrath, C. J. Schultz, 2018: Early Assessment of Geostationary Lightning Mapper Observations. 98th Annual Meeting, Amer. Meteor. Soc., Austin, Texas.
- Schultz, L. A., A. L. Molthan, K. M. McGrath, J. E. Burks, T. A. Cole, 2017: Inclusion of Satellite Remote Sensing Imagery in the NOAA/NWS Damage Assessment Toolkit (DAT). 97th Annual Meeting, Amer. Meteor. Soc., Seattle, Washington.
- Naeger, A. R., P. Gupta, B. Zavodsky, and K. M. McGrath, 2015: Monitoring and Tracking the Trans-Pacific Transport of Aerosols Using Multi-Satellite Aerosol Optical Depth Retrievals. Meas. Tech. Discuss., 8, 10319-10360.
- McGrath, K. M., A. L. Molthan, and J. E. Burks, 2014: Use of NASA Near Real-Time and Archived Satellite Data to Support Disaster Assessment. 94th Annual Meeting, Amer. Meteor. Soc., Atlanta, Georgia.
- Burks, J. E., M. R. Smith, and K. M. McGrath, 2014: AWIPS II Application Development, a SPoRT Perspective. 94th Annual Meeting, Amer. Meteor. Soc., Atlanta, Georgia.