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Funded Research

CALIPSO Observations in Support of OCO-2 Validation

Winker, David: NASA Langley (Project Lead)

Project Funding: 2015 - 2018

NRA: 2014 NASA: OCO-2 Science Team for the OCO-2 Mission   

Funded by NASA

Abstract:
The OCO-2 validation plan describes the objective of OCO-2 validation activities as providing ground truth for CO2 dry air mole fraction retrieved from space. However, it is also necessary to identify and understand the sources of discrepancies between satellite retrievals and ground truth. We propose to provide products derived from CALIPSO satellite data which can be used to evaluate the impacts of optically thin aerosol and cloud layers on the OCO-2 retrievals, and also identify errors in the digital elevation model used in the derivation of surface pressure. Validation against accurate groundbased CO2 measurements is available from a relatively small number of locations globally. Uncorrected influences of aerosols and clouds must be characterized globally, however, since their properties and distribution varies widely. The OCO-2 retrieval includes aerosol and cloud properties in the state vector used to retrieve CO2 concentration. However, unrealistic a priori and initial configurations of aerosol and cloud properties can result in biases in the CO2 retrieval. Further, surface pressure is required to convert CO2 concentrations into mixing ratios. Surface pressure is derived from a weather model forecast, interpolated to the local surface elevation using a digital elevation model (DEM). Errors in the DEM surface height, however, will result in biases in retrieved CO2 mixing ratios. Surface elevations retrieved from CALIPSO profiles can be used to identify biases in the DEM used by OCO-2. We propose to perform advanced aerosol, cloud, and surface elevation retrievals, to be compared with the aerosol and cloud priors and properties retrieved within the OCO-2 CO2 retrieval. Discrepancies can be evaluated for impacts on the accuracy of the OCO-2 CO2 concentrations. We will also identify regions where the DEM surface elevations are significantly biased.