Knowledge of satellite data assimilation for numerical weather prediction.
Understanding of geophysical modeling principles and experience with advanced numerical weather prediction models.
Advanced knowledge of radiative transfer modeling, specifically with CRTM or RTTOV.
Proficiency in programming languages such as FORTRAN, Python, and C++.
Experience in a UNIX environment with advanced scripting capabilities.
Strong communication skills in English.
U.S. Citizenship or Green Card Holder with residency in the U.S. for 3-5 years prior to application.
Responsibilities
Collaborate with OMD scientists and external partners to develop satellite radiance data assimilation techniques.
Enhance techniques for microwave radiance data assimilation from low Earth orbit satellites under all-sky conditions.
Improve quality control and bias correction using AI/ML for satellite radiance data assimilation.
Design and execute impact assessments and pre-implementation testing for operational transitions.
Contribute to the Joint Center for Satellite Data Assimilation and the JEDI project.
Benefits
Comprehensive medical, dental, and life insurance.
Matching 401(k) contributions.
Full Job Description
Overview
Axiom is looking for a candidate to support the Office of Modeling and Development (OMD) of the National Weather Service (NWS) in carrying out research, development, and operational transition work related to satellite data assimilation for operational applications of the Unified Forecast System (UFS). The candidate's work will involve the development, execution, testing, and evaluation of innovative techniques to enhance the direct assimilation of "all-sky/all-surface" satellite radiances for use in operational environmental prediction capabilities at OMD. THIS IS A HYBRID ROLE.
Responsibilities
The candidate will perform the job duties in a collaborative environment, assisting developing and applying innovative methods for the primary work areas described below. The candidate will work with OMD scientists and external collaborators to develop innovative all-sky/all-surface satellite radiance data assimilation capabilities for use in applications of the UFS, with emphasis on global medium range numerical weather prediction. In particular, the candidate will utilize the Community Radiative Transfer Model (CRTM). The work will leverage and contribute to the Joint Center for Satellite Data Assimilation, including the Joint Effort for Data assimilation Integration (JEDI) project.
The successful candidate will work in the following areas:
Develop new or enhance existing techniques for the assimilation of microwave radiance data made by prototype and operational low Earth orbit satellites such as the Arctic Weather Satellite (AWS) in all sky conditions and over heterogeneous surface conditions.
Improve upon quality control, bias correction, and/or observation error specification, including through the use of AI/ML techniques, to enhance the assimilation of all-sky/all-surface satellite radiance data and AMVs.
Design, setup, and execute impact assessment and pre-implementation testing to facilitate transition to operations.
Qualifications
Demonstrated knowledge, skills and abilities in the following areas: Required:
Knowledge of data assimilation with focus on the assimilation of satellite data for numerical weather prediction.
Knowledge of the physical and mathematical basis of geophysical modeling (atmospheric and/or environmental) and experience running advanced numerical weather prediction models.
Advanced knowledge of radiative transfer and experience with radiative transfer modeling for data assimilation, such as the Community Radiative Transfer Model (CRTM) or Radiative Transfer for TOVS (RTTOV).
Knowledge and experience of modern programming languages such as object-oriented FORTRAN, Python, and/or C++.
Experience working in a UNIX environment with advanced scripting languages.
Good oral and written communication skills in English.
Must be a U.S. Citizen or Green Card Holder to and must live in US for 3-5 years prior to application
Desired
Experience in running numerical models on High Performing Computer (HPC) platforms using MPI, OpenMP, Slurm, LSF, etc.
Familiarity with variational data assimilation techniques.
Familiarity with the assimilation of satellite radiances impacted by clouds and precipitation.
Experience with coupled earth system models.
Knowledge of modern software engineering practices (requirements gathering, design, prototyping, version control, integration, testing, and documentation).
Axiom offers competitive compensation packages including comprehensive medical/dental/life insurance and matching 401(k) contribution.
About Axiom Space
Axiom Space is a private space exploration company that aims to build the world's first commercial space station. The company was founded in 2016 by Michael Suffredini, who previously served as the manager of the International Space Station program at NASA. Axiom Space plans to launch its first module to the International Space Station in 2020, and eventually detach it to form the core of its own space station. The company has partnerships with major aerospace companies such as Boeing and SpaceX.
