Newswise — The COVID-19 pandemic has presented a unique opportunity for climate change experts to make the connection between sea level rise and the general public.
In his recent paper “Translated Emission Pathways (TEPs): Long-Term Simulations of COVID-19 CO2 Emissions and Thermosteric Sea Level Rise Projections,” published in “Earth’s Future,” Ting Lin of Texas Tech University did just that.
Together with undergraduate McNair Scholar Alan R. Gonzalez, Lin, an assistant professor in the Department of Civil, Environmental and Construction Engineering, used data on CO2 emissions at different stages of the COVID-19 pandemic to create new sea level rise projections.
Using a nonlinear model developed with former doctoral student Matthew A. Thomas in his Multi-Risk Sustainability Research Group (HazSus), Lin was able to link these projections to the pandemic and times when production industry, travel and emissions were at very different levels.
The hope for Lin and his team was to better understand what reducing emissions might look like for people in their daily lives while showing what impact it would have on melting ice caps and rising sea levels.
“Specifically, we used four stages,” Lin said. “The first is the emergence of COVID-19. The second is where the guidelines and some restrictions have been set. Phase three is the reopening transition and phase four is the initial vaccinations. »
The aim of the study and the document is to bring the general public into the discussion on climate change while encouraging people to be respectful of the environment.
“Our ability to show the corresponding data for emissions during these time periods and to parallel that with what has already been done in the climate science community, which describes different types of emissions scenarios, has allowed us to use something the general public has experienced,” Lin said. “I hope this could help them understand how these restrictions have impacted their daily lives.”
As Lin worked to make the conversation about climate change more accessible to the public, she also gathered models and data to help the scientific community develop new methods to study sea level rise.
In a second paper, co-authored with HazSus PhD candidate Xiao Luo, “A Semi-Empirical Framework for Ice Sheet Response Analysis under Oceanic Forcing in Antarctica and Greenland”, published in “Climate Dynamics”, Lin explains the development of a new framework for creating ice sheet response models.
After running a set of computationally expensive models, Lin and his team created simplified mathematical expressions to link the original models with the ability to input new data and create new outputs.
The hybrid approach between models and data gives scientists studying ice sheet response the ability to examine potential sea level rise using significantly less computing power but with no loss of precision.
“We created this so that in the future we don’t have to re-simulate the whole process,” Lin said. “We ran the initial process-based simulations using our Texas Tech High Performance Computing Center (HPCC) and running these simulations takes a long time.
“Once done, we don’t need to run all the different simulations for Antarctica and Greenland – we can generalize this and use the simplified, semi-empirical framework to generate the future fusion. And in turn, we can model the resulting sea level rise.
The global pandemic has given researchers the opportunity to create relevant models for sea level rise.
