Update on Python Adoption at the Naval Research Laboratory

The use of Python for geophysical research and the coordination with other technologies (such as web services) present an opportunity for NRL to enable rapid development and accelerated transition of new analysis tools across the varied platforms used for research at NRL and operations at Fleet Numerical Meteorology and Oceanography Center (FNMOC).  Observations lead the way to providing improved forecasts, and this talk will focus on the continuing development of observation monitoring capabilities for data assimilation and observation and grid-based forecast evaluation tools, as well as methods for optimizing data assimilation and forecast systems timings based on exploiting task parallelism.

We will discuss recent developments in the monitoring suite for the operational data assimilation system (such as satellite observation availability, impact of observations on resulting analysis, and quantifying trends in the data assimilation cycle), diagnostics for the new global coupled system under development, and verification tools for the global forecast system.

In addition to the capabilities under development, we will discuss Python-based suite controller tools that can ease research-to-operations transition and provide robust infrastructure for real-time research.