Sarika Kulkarni

Large variability in ecosystem models explains uncertainty in a critical parameter for quantifying GPP with carbonyl sulphide

Regional gross primary productivity (GPP) estimates are crucial to estimating carbon-climate feedbacks but are highly uncertain with existing methods. An emerging approach uses atmospheric carbonyl sulphide (COS) as a tracer for carbon dioxide: COS plant uptake is simulated by scaling GPP. A critical parameter for this method is leaf-scale relative uptake (LRU). Plant chamber and eddy covariance studies find a narrow range of LRU values but some atmospheric modelling studies assign values well outside this range. Here we study this discrepancy by conducting new regional chemical transport simulations for North America using the underlying data from previous studies. We find the wide range of ecosystem model GPP estimates can explain the discrepancy in LRU values. We also find that COS concentration uncertainty is more sensitive to GPP uncertainty than to LRU parameter uncertainty. These results support the COS tracer technique as a useful approach for constraining GPP estimates.

Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation

[1] During the operational phase of the ICARTT field experiment in 2004, the regional air quality model STEM showed a strong positive surface bias and a negative upper troposphere bias (compared to observed DC-8 and WP-3 observations) with respect to ozone. After updating emissions from NEI 1999 to NEI 2001 (with a 2004 large point sources inventory update), and modifying boundary conditions, low-level model bias decreases from 11.21 to 1.45 ppbv for the NASA DC-8 observations and from 8.26 to 0.34 for the NOAA WP-3. Improvements in boundary conditions provided by global models decrease the upper troposphere negative ozone bias, while accounting for biomass burning emissions improved model performance for CO. The covariances of ozone bias were highly correlated to NOz ,N Oy, and HNO3 biases. Interpolation of bias information through kriging showed that decreasing emissions in SE United States would reduce regional ozone model bias and improve model correlation coefficients. The spatial distribution of forecast errors was analyzed using kriging, which identified distinct features, which when compared to errors in postanalysis simulations, helped document improvements. Changes in dry deposition to crops were shown to reduce substantially high bias in the forecasts in the Midwest, while updated emissions were shown to account for decreases in bias in the eastern United States. Observed and modeled ozone production efficiencies for the DC-8 were calculated and shown to be very similar (7.8) suggesting that recurring ozone bias is due to overestimation of NOx emissions. Sensitivity studies showed that ozone formation in the United States is most sensitive to NOx emissions, followed by VOCs and CO. PAN as a reservoir of NOx can contribute to a significant amount of surface ozone through thermal decomposition. Citation: Mena-Carrasco, M., et al. (2007), Improving regional ozone modeling through systematic evaluation of errors using the aircraft observations during the International Consortium for Atmospheric Research on Transport and Transformation, J. Geophys. Res., 112, D12S19, doi:10.1029/2006JD007762.

Plant Uptake of Atmospheric Carbonyl Sulfide in Coast Redwood Forests

Author(s): Campbell, JE; Whelan, ME; Berry, JA; Hilton, TW; Zumkehr, A; Stinecipher, J; Lu, Y; Kornfeld, A; Seibt, U; Dawson, TE; Montzka, SA; Baker, IT; Kulkarni, S; Wang, Y; Herndon, SC; Zahniser, MS; Commane, R; Loik, ME | Abstract: ©2017. American Geophysical Union. All Rights Reserved. The future resilience of coast redwoods (Sequoia sempervirens) is now of critical concern due to the detection of a 33% decline in California coastal fog over the 20th century. However, ecosystem-scale measurements of photosynthesis and stomatal conductance are challenging in coast redwood forests, making it difficult to anticipate the impacts of future changes in fog. To address this methodological problem, we explore coastal variations in atmospheric carbonyl sulfide (COS or OCS), which could potentially be used as a tracer of these ecosystem processes. We conducted atmospheric flask campaigns in coast redwood sites, sampling at surface heights and in the canopy (~70 m), at the University of California Landels-Hill Big Creek Reserve and Big Basin State Park. We simulated COS atmosphere-biosphere exchange with a high-resolution 3-D model to interpret these data. Flask measurements indicated a persistent daytime drawdown between the coast and the downwind forest (45 ± 6 ppt COS) that is consistent with the expected relationship between COS plant uptake, stomatal conductance, and gross primary production. Other sources and sinks of COS that could introduce noise to the COS tracer technique (soils, anthropogenic activity, nocturnal plant uptake, and surface hydrolysis on leaves) are likely to be small relative to daytime COS plant uptake. These results suggest that COS measurements may be useful for making ecosystem-scale estimates of carbon, water, and energy exchange in coast redwood forests.