Meet Darren Pilcher

Darren Pilcher is a research scientist with NOAA’s Pacific Marine Environmental Lab who is currently working on modeling OA in the Bering Sea.

Q: How did you get into the field of OA?

In graduate school, I studied the processes that determine the exchange of carbon between the water and the atmosphere.  The oceans provide a critical service by taking up a portion of the carbon that we emit into the atmosphere, but unfortunately this process also results in ocean acidification.  I was interested in understanding how this process will effect ocean ecosystems, particularly in high-latitude waters such as Alaska, where OA and climate change are occurring more rapidly.

Q: What kind of background to you need for the modeling work you do?

I was a chemistry major as an undergraduate, so you don’t necessarily need a computer science degree, however you do need a strong background in mathematics and physical science since this is the language that our computational models are written and operated in.

Q: You’re working on one of the only forecast models for ocean acidification for Alaska.  Can you tell us more about the scope of your project and what you’re trying to do?

Our current, best estimates for forecasting and projecting OA into the future are based on global climate models, which work well at the global scale, but can struggle in coastal regions that are more complex.  I’m using a regional model of the Bering Sea, which provides much better spatial resolution (i.e. the size of each grid cell in the model) and also includes some of these processes that we know are important for the Bering Sea ecosystem.  The goal is to use this model to produce projections of OA in the Bering Sea, which incorporate this regional information.  I also hope to eventually use this model to produce seasonal forecasts of ocean water conditions 9-months in advance.

Q: Some people are unfamiliar with the concept of a hindcast. Can you tell us what that means and why it’s important?

A hindcast is when we use a model to simulate past conditions, as opposed to a forecast or projection where we are simulating future conditions.  We run these to verify that our models are operating correctly and to assess how accurate they are by comparing the model produced ocean conditions to data collected at the same place and time from ships, moorings, and autonomous instruments.  Once we verify that the models are successfully reproducing the observed conditions, we can then also use the hindcast to analyze longterm historical trends, understand critical mechanisms, and/or fill in data gaps.

Q: How might the forecast you’re working on help Alaskans? 

Being able to successfully forecast where and when OA will impact Alaskan waters can be very helpful towards preparing for these anticipated conditions and ultimately working towards maintaining crucial ecosystem services, such as fisheries.  This information can also be used to better understand the conditions that species may be under in the future, allowing us to better tailor and refine our biological experiments.

Q: What are some of the challenges of modeling ocean acidification in Alaska?

There are a ton of dynamic, complex processes that impact OA in Alaska, which make the region relatively challenging but also more interesting to study.  The seasonal advance and retreat of sea ice, river water runoff from the Yukon and Kuskokwim, and biological interactions between surface waters and the shelf bottom all play critical roles in determining the water chemistry and OA.  To accurately model these processes, we need sufficient spatial resolution, a way to represent the processes mathematically, and thorough observational data to both inform and help validate these models.

Alaska Ocean Acidification Network, 2018. Article.

 

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Ocean acidification in the IPCC AR5 WG II

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