Physical Scientist – Atmospheric Wind Data Assimilation

Jobtailor; College Park (MD); On-site; USD 90,000 - 130,000; Full time

Job summary

Lynker in College Park, MD seeks a scientist to advance wind data assimilation for atmospheric observations, including AMVs, aircraft, and ocean winds.

The role covers developing components for satellite-derived wind data, improving QC and observation error specs, and conducting pre-implementation testing for operational transitions. Collaboration with OMD and JEDI teams is expected.

Qualifications

• Background in atmospheric science, numerical weather modeling, and satellite data analysis.
• Knowledge of data assimilation with wind observations, AMVs for numerical weather prediction.
• Knowledge of geophysical modeling and advanced numerical weather prediction models.
• Proficiency in Python, C++, and object-oriented FORTRAN.
• Experience in UNIX environment and scripting.
• Strong oral and written communication in English.
• Experience with HPC platforms using MPI, OpenMP, Slurm, LSF.
• Familiarity with variational data assimilation.
• Experience with space-borne or airborne wind measurements.
• Knowledge of coupled Earth system models.
• Knowledge of software engineering practices.
• Lynker is an E-Verify employer.

Responsibilities

• Develop new or enhance wind data assimilation techniques for aircraft winds, ocean surface winds, and AMVs.
• Prepare or enhance components to assimilate wind observations from future satellites and lidar.
• Improve quality control and observation error specification, including AI/ML techniques.
• Design, set up, and execute impact assessments and pre-implementation testing for operations.
• Develop and apply ocean surface wind and AMVs data assimilation for Unified Forecast System applications.
• Collaborate with OMD scientists and external partners.
• Contribute to the Joint Center for Satellite Data Assimilation and JEDI projects.

Skills

Oral Communication

Written Communication

Collaboration

Education

Atmospheric Science Degree

Tools

FORTRAN (OO)

Python

C++

UNIX

MPI

OpenMP

Slurm

LSF

Job description

• Develop new or enhance existing techniques for the improved assimilation of atmospheric wind data, including aircraft winds, ocean surface winds and AMVs
• Prepare, design, or enhance existing components to enable the assimilation of wind observations and AMVs derived from future satellite missions and airborne/space-borne lidar
• Improve quality control and observation error specification, including through AI/ML techniques
• Design, set up, and execute impact assessment and pre-implementation testing to facilitate transition to operations
• Develop and apply innovative ocean surface wind and AMVs data assimilation capabilities for Unified Forecast System applications
• Work with OMD scientists and external collaborators in a collaborative environment
• Contribute to the Joint Center for Satellite Data Assimilation and Joint Effort for Data assimilation Integration (JEDI) project

Requirements

• Background in atmospheric science, numerical weather modeling, and meteorological satellite data analysis
• Knowledge of atmospheric data assimilation with focus on the assimilation of wind observations, satellite radiances, or AMVs 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
• 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
• Experience in atmospheric wind data assimilation with global and regional atmospheric data assimilation systems
• Experience in running numerical models on High Performing Computer (HPC) platforms using MPI, OpenMP, Slurm, LSF, etc.
• Familiarity with variational data assimilation techniques
• Experience with space-borne or airborne wind measurements made from microwave, infrared, or GNSS-RO data
• Experience with coupled earth system models
• Knowledge of modern software engineering practices (requirements gathering, design, prototyping, version control, integration, testing, and documentation)
• Lynker is an E-Verify employer

Core Competencies

Demonstrates expertise in atmospheric science and numerical weather modeling, with a strong focus on atmospheric data assimilation techniques and advanced programming skills. Proficient in developing innovative data assimilation capabilities for operational forecasting systems.

Highest-signal resume keywords

• Atmospheric Data Assimilation
• Numerical Weather Modeling
• Object-Oriented FORTRAN
• Python Programming
• High Performance Computing (HPC)

ATS Optimization Keywords

Hard Skills

• Atmospheric Science
• Numerical Weather Prediction
• Data Assimilation Techniques
• Advanced Scripting Languages
• Variational Data Assimilation
• Coupled Earth System Models
• AI/ML Techniques
• Impact Assessment
• Quality Control
• Observation Error Specification

Soft Skills

• Oral Communication
• Written Communication
• Collaboration

Industry Keywords

• Atmospheric Wind Data
• Satellite Radiances
• AMVs Data
• Space-Borne Measurements
• Airborne Measurements

Tools & Technologies

• UNIX Environment
• MPI
• OpenMP
• Slurm
• LSF