Using in situ data to better understand Chinese air pollution events

Presentation Date:

Wednesday, May 3, 2017

Location:

8th International GEOS-Chem Meeting, Cambridge, Massachusetts

Presentation Slides:

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.

Presentations

Lau MCY, Stackhouse BT, Moch JM , Chourey K, Hettich RL, Vishnivetskaya T, Pfiffner S, Layton A, Mykytczuk N, Whyte L, et al. Identifying active CH4-oxidizers in thawed Arctic permafrost by proteomics. Poster presentation at AGU 2012 Fall Meeting, December 3-7. 2012. AGU Poster

Moch JM , Stackhouse BT, Lau CMY, Medvigy D, Onstott TC. 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. 2012. AGU Poster

Moch JM , Rodgers K, Frolicher T, Sarmiento J. Quantifying Carbon Cycle-Climate Feedbacks with the GFDL Earth System Model. Presentation at Princeton University Energy Grand Challenges Symposium, October 7, Princeton, New Jersey. 2011. Publisher's Version Abstract

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.

Jonathan M. Moch, PhD

Harvard University

Using in situ data to better understand Chinese air pollution events

Presentation Date:

Location:

Presentation Slides:

Presentations