Moch JM, Dovrou E, Mickley LJ, Keutsch FN, Liu Z, Wang Y, Dombek TL, Kuwata M, Budisulistiorini SH, Yang L, Decesari S, Paglione M, Alexander B, Shao J, Munger JW, Jacob DJ, (2020). Global importance of hydroxymethanesulfonate in ambient particulate matter: Implications for air quality. Presentation at National Atmospheric Deposition Program Scientific Symposium, October 28 2020, Remote. Watchable Online.
Moch, J.M., L.J. Mickley, D.J. Jacob, E.W. Lundgren, S. Zhai, C.A. Keller, (2020). Aerosol-radiation interactions in China in winter using a coupled chemistry-climate model. Presentation at 1st GEOS-Chem Europe Meeting, September 2 2020, Remote. Watchable Online.
Moch, J.M., L.J. Mickley, D.J. Jacob, E. Dovrou, F.N. Keutsch, J.W. Munger, J. Jiang, M. Li, Y. Cheng, X. Qiao, Q. Zhang, Z. Liu, S. Decesari, M. Paglione, and T. Dombek, (2019). The potential overlooked importance of hydroxymethane sulfonate as a contribution to ambient particulate matter. Presentation at ORD/NERL/CED/AMAAB Monthly Seminar, July 18, Environmental Protection Agency, Research Triangle Park, North Carolina
Moch, J.M., L.J. Mickley, D.J. Jacob, E. Dovrou, F.N. Keutsch, B. Alexander, Y. Cheng, J. Jiang, M. Li, J.W. Munger, J. Shao, X. Qiao, and Q. Zhang, (2019). Hydroxymethane sulfonate in extreme haze: Initial results from GEOS-Chem. Presentation at 9th International GEOS-Chem Meeting, May 6-9 2019, Cambridge, Massachusetts.
Moch, J.M., L.J. Mickley, D.J. Jacob, Y. Cheng, M. Li, J.W. Munger, Y.X. Wang, (2017). Hydroxymethane sulfonate as a possible explanation for observed high levels of particulate sulfur during severe winter haze episodes in Beijing, China. Poster presentation at AGU 2017 Fall Meeting, December 11-15, New Orleans, Louisiana.
Moch, J.M., L.J. Mickley, H. Liao, Y. Cheng, and M. Li, (2017). Using in situ data to better understand Chinese air pollution events. Presentation at 8th International GEOS-Chem Meeting, May 1-4 2017, Cambridge, Massachusetts. Watchable online.
Moch, J.M., B.T. Stackhouse, M.C.Y. Lau, D. Medvigy, and T.C. Onstott, (2012). Modeling CH4 emissions from Arctic tundra: Processes behind emissions pulses and the potential for a negative feedback. Poster presentation at AGU 2012 Fall Meeting, December 3-7, San Francisco, California.
Lau, M.C.Y., B.T. Stackhouse, J.M. Moch, K. Chourey, R.L. Hettich, T. Vishnivetskaya, S. Pfiffner, A. Layton, N. Mykytczuk, L. Whyte and T.C. Onstott, (2012). Identifying active CH4-oxidizers in thawed Arctic permafrost by proteomics. Poster presentation at AGU 2012 Fall Meeting, December 3-7.
Project: Quantifying Carbon Cycle-Climate Feedbacks with the GFDL Earth System Model
Organization/Location: Princeton University, Princeton, New Jersey
Advisers: Jorge Sarmiento, George J. Magee Professor of Geoscience and Geological Engineering, Director, Program in Atmospheric and Oceanic Sciences (AOS); Keith Rodgers, Research Scholar, AOS. Thomas Frolicher, Postdoctoral Research Fellow, AOS
This summer I worked with the Sarmiento group in the Atmospheric and Oceanic Sciences Program...
This summer I worked with the Sarmiento group in the Atmospheric and Oceanic Sciences Program on quantifying carbon cycle-climate feedbacks in Earth System Models. Currently about half of anthropogenic carbon emissions remain in the atmosphere, with the remainder taken up by the carbon sinks that make up the carbon cycle. However, the amount of carbon removed from the atmosphere through these processes is projected to increase as atmospheric CO₂ increases and climate change progresses. This creates a feedback between the carbon cycle and climate system which can exert a great deal of influence on the rate and degree of climate change. Climate models have different ways of characterizing this and other feedbacks, which is one reason for the uncertainty in projections between different models. Climate scientists have tried to characterize the extent of these feedbacks by using linear feedback factors. These can be easily compared between different models and useful for examining inter-model uncertainty. By creating such feedback factors, I was able to compare the uncertainties between different Earth System Models. In addition, I examined how intra-model variability affects feedback factors and discovered that uncertainty within climate models could result in a slightly smaller or larger spread of climate change projections.