Chemical Response of CESM/CAM-Chem to MOPITT CO Ensemble-based Chemical Data Assimilation

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Benjamin Gaubert1, Avelino F Arellano2, Jerome Barré1, Helen Marie Worden1, Louisa K Emmons1, Simone Tilmes1, Rebecca R Buchholz1, Christine Wiedinmyer1, Francis Vitt1, Jeffrey L Anderson1, Merritt N Deeter1 and David P Edwards1, (1)National Center for Atmospheric Research, Boulder, CO, United States, (2)University of Arizona, Tucson, AZ, United States
Carbon Monoxide is a key component in tropospheric chemistry. It plays an important role by affecting the oxidative capacity through its reaction with OH and being a precursor of tropospheric ozone. One year of multispectral retrievals of CO partial columns obtained from the MOPITT instrument have been assimilated into the Community Atmosphere Model with Chemistry (CAM-Chem). The assimilation is carried out using an Ensemble Adjustment Kalman Filter algorithm within the Data Assimilation Research Testbed (DART) package. Two assimilation experiments have been performed: 1) assimilation of meteorological observations and 2) joint assimilation of meteorological observations and MOPITT CO. We first evaluate the assimilation performance by investigating skill scores and other statistics for the two experiments, and comparing to independent CO datasets such as surface (WDCGG), aircraft (MOZAIC-IAGOS), and FTS (NDACC). Our results clearly demonstrate an overall improvement for spatio-temporal magnitude and variability in representing CO abundance in CAM-Chem. We then investigate the response of CAM-Chem to changes in CO fields (via CO assimilation) focusing mainly on the oxidative capacity (i.e., OH distribution, methane lifetime) and CO chemical production and loss (i.e., regional to global budget). This is carried out by analyzing the mean 6-hourly forecast adjustments as reflected between the two experiments. We show that changes in CO directly impact OH abundance, with subsequent non-linear responses in CO chemical production (CO from methane and VOCs) and CO loss. This is clearly evident in NOx-limited regions (e.g., Southern Hemisphere, remote sites). Such analysis has direct implications on the consistencies in inverse modeling estimates of CO sources through improved representation of chemical response (including full chemistry) in atmospheric chemistry models and through multi-species constraints.