NWP Modeler at Spire Global
Boulder, CO, US

Background:  Spire Global is seeking an NWP (Numerical Weather Prediction) modeler for the implementation and validation of its weather forecast systems in order to test the value of large numbers of Radio Occultation (GNSS-RO) soundings. To implement and improve Spire modeling systems for data testing, Spire Global is seeking to integrate and test the next-generation physical parameterization package, to develop improvements to model dynamics, and to work with the data associated with modern NWP. This is an exciting opportunity for motivated scientists to teamwork with NWP modelers, data assimilation and computer scientists in Spire as well as scientists from around the world to assimilate unprecedented large amounts of GNSS-RO satellite data to make weather forecasts better. The successful candidates will join the NWP research team at Spire branch office in Boulder, Colorado, USA.

Responsibilities:  The successful candidate will work with Spire NWP research team members to implement and maintain state-of-art capabilities into Spire’s weather forecast system.  Responsibilities will include the following tasks: 

  • Develop and implement components of the dynamic prediction core of advanced global weather prediction models.
  • Develop and implement advanced physics packages for global weather prediction models.
  • Develop and implement interface software that connects data assimilation output to model input, and interface software that connects model output to applications.


  • Applicant must have either a MS or Ph.D. degree in Meteorology, Atmospheric Science, or equivalent working experience in NWP model dynamics and physics.
  • Experience in working with community models such as MPAS and GFS.
  • Experience and knowledge in writing and using UNIX scripts to import data via FTP from multiple sources as well as to handle a large amount of NWP model output.
  • Experience with use of GSI to initialize NWP models is highly desirable.
  • Experience and knowledge in computer-based statistics data analysis and post-processing are desirable.
  • Fluent knowledge of programming languages (Fortran-90 and scripting) for debugging and optimizing codes in Linux/Unix environment is required. 
  • Experience in the use of graphical display packages (e.g. NCL, GrADS) is desirable.   
  • Demonstration of the ability to work as part of a development team is necessary.