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Funded Research

Towards a 4D CO2 Reanalysis with a Carbon-Weather Data Assimilation System

Fung, Inez: University of California, Berkeley (Project Lead)
Kalnay, Eugenia: University of Maryland (Institution Lead)

Project Funding: 2015 - 2018

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

Funded by NASA

Abstract:
We propose to participate in the Science Team for the Orbiting Carbon Observatory-2 (OCO-2). The immediate goals of the proposed work are threefold. The first is to estimate uncertainties in Xco2 resulting from different OCO-2 nadir-glint observing cycles. The second is to prototype the derivation of surface CO2 fluxes from OCO-2 Xco2 and other satellite CO2 observations using a carbon-weather data assimilation system. The third is to produce a 4D reanalysis of atmospheric CO2 (and contemporaneous circulation statistics) using OCO-2 Xco2 and other satellite CO2 observations. The reanalysis products and their uncertainties will be widely distributed for analysis of CO2 sources and sinks and transport processes. At the core of the proposed work is a carbon-weather data assimilation system we have been developing (Liu et al. 2011, 2012; Kang et al. 2011, 2012). Every 3 hours, Xco2 retrievals from OCO-2, column CO2 from TES, GOSAT and AIRS together with ~106 raw weather observations will be assimilated into a 64-member ensemble of the NCAR carbon-climate model, using the 4D-Local Ensemble Transform Kalman Filter. We will explore two approaches for estimating surface fluxes. The first calculates the surface CO2 fluxes for each model grid box directly from the conservation equation, and their uncertainty from the large number of ensemble members. The second seeks to extend our approach to estimate surface fluxes without priors to include the diurnal cycle. These two versions of surface fluxes represent our best attempts, and will be used in a reanalysis to produce 4D distributions of atmospheric CO2 mixing ratios and the concomitant meteorology.