Co-founder, Senior Scientist for Remote Sensing. Dr. Joiner is an atmospheric physicist with more than 35 years of experience  in remote sensing and assimilation of atmospheric and surface parameters from satellite multi- and hyper-spectral microwave, infrared, visible, and ultraviolet passive radiometers. Her research interests include radiative transfer modeling, retrieval algorithm development, and data analysis. Areas of particular interest include creation of long-term global records of tropospheric and stratospheric trace gases, clouds, solar-induced chlorophyll fluorescence and other biospectral indicators, determination of radiative and constituent fluxes, and exploitation of machine learning to advance satellite remote sensing. She served as a deputy project scientist for NASA's Aura satellite, one of NASA's three flagship Earth Observing System (EOS) missions and as project scientist for NOAA's GeoXO next-generation geostationary satellite constellation.

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Co-founder, Senior Scientist for Modeling Systems. Dr. Arlindo da Silva expertise spans physics and atmospheric dynamics, with research covering atmospheric wave dynamics, numerical modeling, global ocean flux estimation, climate diagnostics, and data assimilation. At NASA, Dr. da Silva pioneered advanced techniques in 4-dimensional data assimilation, focusing on physical-space analysis, error covariance modeling, forecast bias correction, and observation quality control. He also lead efforts on aerosol modeling and data assimilation , km-scale Observing System Simulation Experiments (OSSEs) and biomass burning emissions. He also contributed to the development of NASA’s Prithvi WxC AI Foundation Model for Weather and Climate.  Dr. da Silva  has played a leading role in major NASA space flight projects such as ACE and ACCP/AOS, advancing NASA’s modeling capabilities and observing system simulations for mission design. Beyond NASA, Dr. da Silva is active in the open-source community, founding and developing the OpenGrADS Project to promote collaboration and accessibility in meteorological research.

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