720-370-9012
1021 Main Street, Louisville, CO 80027
"I joined Aeris because it is rare to find a team of individuals with this much talent and passion. I believe we are well positioned to do great things.”
Nicholas Geyer
Associate Scientist II
Mr. Geyer received a B.S. in Meteorology from the Pennsylvania State University in 2010 and a M.S. in Atmospheric Science in 2014 from Colorado State University. Mr. Geyer has over ten years of experience in multi-scale meteorology, land-surface interactions, statistics, and biological modeling. His expertise includes machine learning, multi-scale modeling, climate analysis, numerical weather prediction, and data assimilation methods.
While at CSU as a graduate student, Mr. Geyer developed a new statistical methodology for biological source estimation that leveraged carbon dioxide observation information from satellites, like Orbiting Carbon Observatory-2 and METOP-A, toward biased time-scale assumptions that are important for carbon dioxide dynamics.
As a researcher at CSU, Mr. Geyer spent three years investigating the role and satellite detection of biological radiative emission that can be used to better constrain surface estimates of photosynthesis. Then, he spent two more years developing multiscale transport methods within coarse climate and NWP models with a team of fellow scientists funded by NASA’s Atmospheric Carbon Transport-America field campaign.
Since Mr. Geyer joined Aeris in 2020, he has been steadily working toward the completion of his Ph.D. at Colorado State University. His dissertation work will explore how missing atmospheric features, such as adequate cloud features and frontal mixing, affect the statistical inversion estimates used to help drive public policy and decision making regarding carbon dioxide emissions.
Nicholas Geyer
Associate Scientist II
Mr. Geyer received a B.S. in Meteorology from the Pennsylvania State University in 2010 and a M.S. in Atmospheric Science in 2014 from Colorado State University. Mr. Geyer has over ten years of experience in multi-scale meteorology, land-surface interactions, statistics, and biological modeling. His expertise includes machine learning, multi-scale modeling, climate analysis, numerical weather prediction, and data assimilation methods.
While at CSU as a graduate student, Mr. Geyer developed a new statistical methodology for biological source estimation that leveraged carbon dioxide observation information from satellites, like Orbiting Carbon Observatory-2 and METOP-A, toward biased time-scale assumptions that are important for carbon dioxide dynamics.
As a researcher at CSU, Mr. Geyer spent three years investigating the role and satellite detection of biological radiative emission that can be used to better constrain surface estimates of photosynthesis. Then, he spent two more years developing multiscale transport methods within coarse climate and NWP models with a team of fellow scientists funded by NASA’s Atmospheric Carbon Transport-America field campaign.
Since Mr. Geyer joined Aeris in 2020, he has been steadily working toward the completion of his Ph.D. at Colorado State University. His dissertation work will explore how missing atmospheric features, such as adequate cloud features and frontal mixing, affect the statistical inversion estimates used to help drive public policy and decision making regarding carbon dioxide emissions.
"I joined Aeris because it is rare to find a team of individuals with this much talent and passion. I believe we are well positioned to do great things.”
