Explore exciting and impactful careers at the intersection of cutting-edge science and high-performance computing by searching for Satellite and Atmospheric Data Assimilation Scientist jobs. Professionals in this specialized field are the essential bridge between vast streams of environmental observations and the complex numerical models used for weather prediction and climate analysis. Their core mission is to ingeniously merge real-world data from satellites and other sources with model forecasts to produce the most accurate possible estimate of the Earth's atmospheric state, a critical foundation for all subsequent predictions. A Satellite and Atmospheric Data Assimilation Scientist typically engages in a multifaceted role centered on developing, refining, and implementing sophisticated mathematical algorithms within data assimilation systems like ensemble Kalman filters or variational methods. Common responsibilities include integrating observations from a diverse suite of satellite instruments, such as hyperspectral infrared sounders, microwave radiometers, and GNSS radio occultation sensors. This involves working intimately with radiative transfer models (like RTTOV) to simulate what the satellite should observe given a model state, a crucial step for comparing and assimilating real measurements. Scientists in these jobs are tasked with diagnosing biases, developing quality control procedures, and creating novel methods to optimally extract information from millions of daily observations to correct and initialize forecast models. The overarching goal is consistently to enhance forecast skill across timescales, from short-range weather to sub-seasonal and seasonal outlooks. The typical skill set for these roles is both deep and broad. A strong academic foundation is paramount, usually requiring a PhD in atmospheric sciences, physics, mathematics, meteorology, or a closely related field. Proficiency in the core scientific disciplines of dynamics, thermodynamics, and radiative transfer is essential. Equally critical are advanced computational skills. Professionals must be adept in a Unix/Linux environment and possess substantial programming expertise, commonly in Fortran, Python, and/or C++, for manipulating large datasets and modifying complex assimilation codebases. A solid grasp of statistical methods and, increasingly, machine learning techniques for pattern recognition and model improvement is highly valuable. Successful candidates are problem-solvers who can work both independently and collaboratively, with the adaptability to tackle evolving scientific challenges in the quest for better environmental predictions. For those passionate about leveraging big data to solve grand challenges in Earth system science, pursuing Satellite and Atmospheric Data Assimilation Scientist jobs offers a rewarding career path at the forefront of geophysical research.
