Living Science
‘More Complicated Than Launching a Rocket’
Min Chen combines remote sensing and computer modeling to make climate change prediction more accurate.
When Min Chen first checked out Google Earth, the tech giant’s highly detailed digital globe, he was totally blown away. And the moment he learned its images were created through remote sensing, he decided to attend graduate school to learn more about the evolving technology.
For his master’s program, Chen landed in a remote sensing lab — but one that focuses on the fundamental theories of remote sensing rather than its practical applications. It turned out to be a happy accident. Chen enjoyed the theory-level research. He went on to pursue a Ph.D. at Purdue University and postdocs at Harvard and the Carnegie Institution for Science at Stanford, adding skills and experience in terrestrial ecosystem modeling and advanced remote sensing techniques. He also worked at Pacific Northwest National Laboratory (PNNL), where he helped improve the models used in assessment reports by the United Nations Intergovernmental Panel on Climate Change. Chen later received a grant from NASA to further explore remote sensing theory, one of very few theoretical research grants provided by the agency.
Chen launched the NASA-funded project after joining the Department of Forest and Wildlife Ecology in 2021. He was recruited as part of a campus-wide cluster-hiring initiative focused on emerging polar regions, and his research program encompasses that academic field and more. Chen’s big-picture goal is to improve understanding of Earth system dynamics using satellite remote sensing data and Earth system models. In turn, he hopes this will enhance predictions of how the globe is changing, including the volume of methane emissions in the Arctic, wildfire risks, vegetation growth, and the effectiveness of climate change mitigation strategies.
Your lab is called the “Global Change Research Laboratory.” How did you pick that name?
Well, I’m concerned about climate change, and I do research about how the Earth system evolves in the background of climate change. More specifically, I study land and atmospheric interactions and human-Earth system interactions. That’s a huge topic, and I’m generally interested in every aspect of that. So, the term “climate change” is too narrow. “Global change,” however, includes the climate, terrestrial ecosystems, and human behavior.
I use an integrative approach, including satellite remote sensing and Earth system modeling. We get our remote sensing data from government satellites or publicly available satellites. We use computers and high-performance computing for our modeling work. In terms of the human dimension, we use so-called integrated assessment modeling, which is an approach that couples human and Earth systems.
GLOSSARY
Remote sensing: Gathering data about the physical characteristics of an area by measuring its reflected or emitted radiation from a distance, typically from a satellite.
Earth system model: A computer code that describes the physical, chemical, and biological processes that interact to impact our planet, including climate-related factors such as atmosphere, ocean, land, ice, and the biosphere.
Biosphere: The portions of the Earth that support living organisms — including all the organisms living in those spaces — from deep sea trenches to forests and their root systems to mountaintops.
It’s exciting that you were recruited as part of the campus cluster hire focused on polar regions. What does your polar research look like?
The polar region is unique in the global system because the Arctic is subject to the fastest climate change, and the terrestrial ecosystems there are experiencing probably the most dramatic changes as well. And it’s a big source of global methane emissions.
We published a paper about this in the March 2024 issue of Nature Climate Change, where we quantify the polar Arctic methane emissions from the wetlands there. Methane, of course, is the second most important greenhouse gas after carbon dioxide. So, we use machine learning algorithms and the best available data, and I think we’ve produced the most reliable estimates of the wetland methane emissions in that area.
I don’t do field research, but I did get a chance to visit the Arctic and see what the ecosystem looks like. Where I visited, they dug a tunnel into the permafrost, and you can see the ice in the soil.
What can you tell us about some of the non-Arctic projects you’re working on?
There are many. For example, we are working on wildfire predictions because there are so many wildfires happening every day. Remember the wildfire smoke that blew down from Canada last year? The aerosols in wildfire smoke are very harmful to sensitive groups. I coughed a lot during that time.
We’re trying to make better predictions of wildfires so people can better understand which factors contribute to the wildfires happening and determine their severity. This provides insights for the people who manage fires to help them see how we can prevent or reduce the damage. I’m proud of using advanced machine learning algorithms to work on this, and we achieved a model with high accuracy.
Carbon comes up a lot when people are talking about big-picture changes to our planet. Does your work look at carbon?
Yes, I’m interested in carbon because carbon dioxide and methane are the top two greenhouse gases we have today. In terms of understanding climate change impact, we must have good computation of the carbon budget in different sectors in the whole Earth system — a global carbon budget.
The biosphere plays a big role in the global carbon budget because photosynthesis is the biggest consumer of atmospheric CO2. At the same time, the biosphere also releases a huge amount of CO2 and methane back into the atmosphere.
To make these carbon budget estimations, we have to rely on satellite remote sensing combined with a terrestrial ecosystem model. Satellite remote sensing can tell you how much vegetation is there, the health of the vegetation, or characteristics of the soil, such as soil moisture. But satellite remote sensing cannot directly observe how much carbon has been absorbed or released by vegetation. For example, the photosynthetic capacity of trees and the photosynthetic capacity of corn are completely different. Satellites cannot directly tell you that.
So we have to estimate the carbon budget with a model. But models themselves have huge uncertainty. We are using satellite remote sensing data to reduce the model uncertainty, to help us improve the models.
At the same time, there are issues with satellite remote sensing itself because the way satellites observe the Earth’s surface creates some artifacts. These artifacts come from the sun and the satellite observation angles. Especially for optical satellite remote sensing, it is very sensitive to the shadows cast by the sun at different angles.
Vegetation structure also brings artifacts into our observation. Take forest, for example — the trees have a lot of gaps. But a cornfield is uniform across the top, just flat. So we probably see more shadows in the forest but less shadows in the cornfield. That’s what makes satellite remote sensing so complicated.
Part of my work is trying to understand those artifacts so we can take them into account when using satellite data in our models, so we can get the best estimates from the models. We published significant findings on this in the November 2023 issue of Nature Ecology & Evolution.
What is your motivation for doing this kind of work?
Part of it is curiosity. Climate change is a big issue, and there are so many unknowns about the climate system. I think it’s more complicated than launching a rocket. We can do the rocket launching pretty well, but we cannot predict climate change well. So, we need people with different expertise to work on different aspects of the climate system and bring this knowledge together to have an integrated view.
I also hope we can have more reliable projections of how our living environment will change in the future, so we’ll have better information to understand things and help mitigate climate change. I want to help make our planet — our home — more sustainable, particularly with the challenge of climate change.
This article was posted in Changing Climate, Healthy Ecosystems, Living Science, Summer 2024 and tagged biosphere, carbon, carbon budget, climate change, earth system model, Forest and Wildlife Ecology, greenhouse gases, methane, Min Chen, remote sensing, satellite remote sensing, wildfire.