Tag Archives: climate change

Testing Arctic climate models: how much detail can we capture?

Many of us have heard that as a consequence of climate change, Arctic sea ice is rapidly decreasing and that the Arctic is warming twice as fast as the rest of the planet. It’s a complicated system that we don’t understand very well: few people live in the Arctic, and the data from limited study sites may not be representative of the region as a whole. How will Arctic climates change at different timescales in the coming years? What could this mean for coastal Arctic communities that rely on sea ice for preventing erosion or fishing in deep waters? How will navigation and shipping routes change? And in addition, how does a changing Arctic affect climates at lower latitudes?

Visualization of winter sea ice in the Arctic by Cindy Starr, courtesy the NASA Scientific Visualization Studio.

Daniel Watkins is a fourth-year PhD student of Atmospheric Science in OSU’s College of Earth, Ocean, and Atmospheric Science (CEOAS). Working with Dr. Jennifer Hutchings, he is analyzing climate model experiments in order to find answers to these questions. An important step in this is to evaluate the quality of climate simulations, which he does by matching up model output with real-life observations of temperature, sea ice, and cloud cover. Climate scientists have many models that predict how these factors will change in the Arctic over the next several decades. No model can take every detail into account, so how accurate can its predictions be? For example, the frigid Arctic temperatures can cause water molecules in low-lying clouds to trap heat in a very different way than they do here in the Pacific Northwest. Is it necessary to take a detail like this into account?

In cold regions like the Arctic where surface ocean temperatures are much warmer than the overlying atmosphere, the ocean transfers a lot of heat into the air. Sea ice insulates the ocean and prevents heat transfer to the atmosphere, so when there is less ice, a cycle of increasing warming can perpetuate. Because water has a higher heat capacity than air, the ocean doesn’t cool off as much as the atmosphere warms. This is particularly bad news for the Arctic, where layers of cold, dense air often sit beneath warmer air in a phenomenon called a temperature inversion. Effectively, this prevents heat from moving on to higher layers of the atmosphere, so it stays low where it could melt more sea ice. This contributes to a phenomenon called Arctic Amplification, where for every degree of warming seen in the global average, the Arctic surface temperature warms by about four degrees. While it may be tempting to build a model containing every cloud in the atmosphere or chunk of ice in the Arctic Ocean, these could make it too computationally difficult to solve. Daniel has to simplify, because his goal is not to provide a weather forecast, but to evaluate how well models match observed measurements of Arctic temperatures.

Daniel by the Skogafoss in Iceland in June 2018. If you’re lucky (and he was), you can see sea ice, turbulent boundary layer cloud layers, and the Greenland ice sheet when you fly between Portland and Iceland.

To accomplish this, Daniel uses model output data, re-analyzed data that fits models to observations, and temperature measurements from weather balloons. These sources contain terabytes of data, so he has written code and contributed to open-source software that subsets and analyzes these datasets in a meaningful way. Daniel then uses the re-analyzed and weather balloon data to test whether the model reproduces various features of the Arctic climate, such as widespread temperature inversions. Working with this vast amount of information requires some mathematical prowess. While studying as an undergraduate at BYU Idaho, Daniel decided to major in math when he heard a professor describe mathematics as “a toolbox to solve science problems with”. An internship at Los Alamos National Laboratory later suggested geophysical modeling as a worthy task to tackle.

When he’s not modeling the future of the Arctic, Daniel spends time with his children, Milo and Owen, and plays in a rock band he formed with his wife, Suzanne, called Mons La Hire. Daniel is also a DJ on KBVR and is excited to become the newest host of Inspiration Dissemination. To hear more, tune in on Sunday, December 2nd at 7 PM on KBVR 88.7 FM, live stream the show, or catch our podcast!

Crabby and Stressed Out: Ocean Acidification and the Dungeness Crab

One of the many consequences associated with climate change is ocean acidification. This process occurs when high atmospheric carbon dioxide dissolves into the ocean lowering ocean pH. Concern about ocean acidification has increased recently with the majority of scientific publications about ocean acidification being released in the last 5 years. Despite this uptick in attention, much is still unknown about the effects of ocean acidification on marine organisms.

Close-up of a Dungeness crab megalopae

Our guest this week, Hannah Gossner, a second year Master’s student in the Marine Resource Management Program, is investigating the physiological effects of ocean acidification on Dungeness crab (Metacarcinus magister) with the help of advisor Francis Chan. Most folks in Oregon recognize the Dungeness crab as a critter than ends up on their plate. Dungeness crab harvest is a multimillion dollar industry because of its culinary use, but Dungeness crab also play an important role in the ocean ecosystem. Due to their prevalence and life cycle, they are important both as scavengers and as a food source to other animals.

Hannah pulling seawater samples from a CTD Carrousel on the R/V Oceanus off the coast of Oregon

To study the effect of ocean acidification on Dungeness crab, Hannah simulates a variety of ocean conditions in sealed chamber where she can control oxygen and carbon dioxide levels. Then by measuring the respiration of an individual crab she can better understand the organism’s stress response to a range of oxygen and carbon dioxide ratios. Hannah hopes that her work will provide a template for measuring the tolerance of other animals to changes in ocean chemistry. She is also interested in the interplay between science, management, and policy, and plans to share her results with local managers and decision makers.

Hannah working the night shift on the R/V Oceanus

Growing up in Connecticut, Hannah spent a lot of time on the water in her dad’s boat, and developed an interest in marine science. Hannah majored in Marine Science at Boston University where she participated in a research project which used stable isotope analysis to monitor changes in food webs involving ctenophores and forage fish. Hannah also did a SEA Semester (not to be confused with a Semester at Sea) where she worked on a boat and studied sustainability in Polynesian island cultures and ecosystems.  Hannah knew early on that she wanted to go to graduate school, and after a brief adventure monitoring coral reefs off the coast of Africa, she secured her current position at Oregon State.

Tune in Sunday June, 17 at 7 pm PST to learn more about Hannah’s research and journey to graduate school. Not a local listener? Stream the show live or catch the episode on our podcast.

Hannah enjoying her favorite past time, diving!

How high’s the water, flood model? Five feet high and risin’

Climate change and the resulting effects on communities and their infrastructure are notoriously difficult to model, yet the importance is not difficult to grasp. Infrastructure is designed to last for a certain amount of time, called its design life. The design life of a bridge is about 50 years; a building can be designed for 70 years. For coastal communities that have infrastructure designed to survive severe coastal flooding at the time of construction, what happens if the sea rises during its design life? That severe flooding can become more severe, and the bridge or building might fail.

Most designers and engineers don’t consider the effects of climate change in their designs because they are hard to model and involve much uncertainty.

Kai at Wolf Rock in Oregon.

In comes Kai Parker, a 5th year PhD student in the Coastal Engineering program. Kai is including climate change and a host of other factors into his flood models: Waves, Tides, Storms, Atmospheric Forcing, Streamflow, and many others. He specifically models estuaries (including Coos and Tillamook Bay, Oregon and Grays Harbor, Washington), which extend inland and can have complex geometries. Not only is Kai working to incorporate those natural factors into his flood model, he has also worked with communities to incorporate their response to coastal hazards and the factors that are most important to them into his model.

Modeling climate change requires an immense amount of computing power. Kai uses super computers at the Texas Advanced Computing Center (TACC) to run a flood model and determine the fate of an estuary and its surroundings. But this is for one possible new climate, with one result (this is referred to as a deterministic model). Presenting these results can be misleading, especially if the uncertainty is not properly communicated.

Kai with his hydrodynamic model grid for Coos Bay, Oregon.

In an effort to model more responsibly, Kai has expanded into using what is called a probabilistic flood model, which results in a distribution of probabilities that an event of a certain severity will occur. Instead of just one new climate, Kai would model 10,000 climates and determine which event is most likely to occur. This technique is frequently used by earthquake engineers and often done using Monte Carlo simulations. Unfortunately, flooding models take time and it takes more than supercomputing to make probabilistic flooding a reality.

To increase efficiency, Kai has developed an “emulator”, which uses techniques similar to machine learning to “train” a faster flooding model that can make Monte Carlo simulation a possibility. Kai uses the emulator to solve flood models much like we use our brains to play catch: we are not using equations of physics, factoring in wind speed or the temperature of the air, to calculate where the ball will land. Instead we draw on a bank of experiences to predict where the ball will land, hopefully in our hands.

Kai doing field work at Bodega Bay in California.

Kai grew up in Gerlach, Nevada: Population 206. He moved to San Luis Obispo to study civil engineering at Cal Poly SLO and while studying, he worked as an intern at the Bodega Bay Marine Lab and has been working with the coast ever since. When Kai is not working on his research, he is brewing, climbing rocks, surfing waves, or cooking the meanest soup you’ve ever tasted. Next year, he will move to Chile with a Fulbright grant to apply his emulator techniques to a new hazard: tsunamis.

To hear more about Kai’s research, be sure to tune in to KBVR Corvallis 88.7 FM this Sunday May, 27 at 7 pm, stream the live interview at kbvr.com/listen, or find it in podcast form next week on Apple Podcasts.