Benjamin H.G. Marchant (Open Notebook)


Dr. Benjamin Marchant Research Scientist SUMMARY I have 20 years of experience in atmospheric remote sensing, with 12 years at NASA Goddard and 1 year at NOAA Center for Weather and Climate Prediction (NCWCP). While working at NASA, I spearheaded the development of the cloud thermodynamic phase product for both MODIS and VIIRS. This particular product plays a crucial role in the NASA cloud optical products. In 2022, I became a part of NOAA, where I actively contribute to the development and enhancement of fire-related products. My responsibilities involve evaluating the effectiveness of existing products and constantly exploring innovative ways to improve them. Throughout my years at NOAA and NASA, I gained valuable experience collaborating within a team, constantly learning new skills in data analysis and visualization to enhance our product. ORCID



2022-present: IMSG Research Scientist at NOAA/NESDIS/STAR, College Park, MD. I am responsible for evaluating and enhancing the NOAA VIIRS Active Fire product, a crucial component in the improvement of NOAA emissions products, specifically the Global Biomass Burning Emissions Product (GBBEPx). This year, I have developed an algorithm that effectively detects persistent fire anomalies on solar panels using VIIRS. At the Eumetsat conference in Sweden, September 2023, I shared compelling evidence showcasing the substantial influence it has on accurately estimating fire radiative power. I have also contributed to the evaluation of the NOAA Active Fire product by comparing it with airborne campaigns like FIREX-AQ MASTER. 2010-2022: USRA Research Scientist at NASA Goddard. I have overseen the development of NASA MODIS Collection 6 Cloud Thermodynamic Phase, a crucial component of the Cloud Optical Product. I have evaluated the product by comparing it with CALIOP and CLOUDSAT. Consequently, the cloud phase algorithm has been implemented as an operational product.


I have developed and continue to refine my technical skills in areas such as data analysis and data visualization. To accomplish my tasks, I have become proficient in the Python programming language and various Python libraries such as Matplotlib, Cartopy, Pandas, and Geopandas. Additionally, I have gained expertise in machine learning libraries like TensorFlow and Scikit-Learn.