Spatial Modeling of Global Atmospheric Carbon Dioxide Concentrations from Satellite Observations

• Activity Number: 643
• Type: Topic Contributed
• Date/Time: Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Dorit Hammerling*+
• Keywords: spatial statistics ; carbon dioxide ; satellite observations ; atmospheric modeling

Abstract

Atmospheric carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Our ability to accurately model the carbon cycle is crucial to predict climate change. Important carbon cycle science questions, such as the mechanisms causing inter-annual variability in carbon uptake and the spatial distribution of carbon sources and sinks, are open. The recent advent of satellite observations of atmospheric CO2 offers new opportunities to shed light on these questions. Despite their high global measurement density, these satellite observations feature gaps and contain large measurement errors. Spatial and spatio-temporal statistical methods can be applied to predict global full coverage CO2 concentration fields from noisy gap-ridden satellite observations. The satellite-derived global concentrations and their associated uncertainties can then be used to conduct comparisons with outputs from models to identify regions of potential mismatch and to use this information to improve model formulation and parameterization. We will present results from our work using future (simulated) and current satellite CO2 observations and highlight areas of research opportunities.