Introduction

Valerie P -

Good afternoon! My name is Valerie Polukhtin, I’m a future Class of 2025 graduate, and I’m just about getting ready to start my senior project.

 

My interests lie with mathematical modeling (I’m planning to major in applied math) as well as environmental science and sustainability, so I’ve decided to combine these interests into a senior project at the ASU Department of Geographical Sciences and Urban Planning under the Urban Climate Research Center. My faculty advisor at school is Mr. McClernon.

 

My site advisor, Matei Georgescu, actually has his background in atmospheric sciences and was trained in the development and use of regional climate models to address land-atmosphere models. So, for example, one thing he studied was how changing the crop in a crop belt might impact the surrounding climate. It’s only been in the last 4 to 5 years that his research has shifted to the urban environment, where he studies larger regional models. These larger models are really just a combination of many models working together, which includes an urban model.

 

After meeting online the first time, Matei Georgescu mentioned he was currently writing a review article on the history of urban planning, with a goal to submit the paper by the end of May. He believes there is little or no analysis of model skill and that model skill has not improved in the last ten years, but he wants to investigate his claims more deeply. For my project, I do not expect, in the approximately three months, there will be enough time to do any independent research, so I will most likely helping him review climate models from the last decade to help with the paper. Additionally, more on my own, I’m hoping to learn more about climate models to gain greater insight into that field of research.

 

I plan to start next week, but this week, on Monday, February 3rd, I actually dropped by ASU to watch a guest lecture Georgescu sent a flyer to. The lecturer, Dr. Timon McPhearson, is a professor at The New School in New York and has several distinctions, including being a lead author for the Intergovernmental Panel on Climate Change Sixth Assessment Report. He gave a brief overview discussing the flood models the New York city hired him to construct after storms in Texas worried them. Originally, with a budget of about $2 million, they wanted to construct 200 scenarios, but computational costs limited them to only 2 scenarios. Even then, these scenarios accurately predicted, for example, the flooding paths and heights from Hurricane Ida before it happened and allowed the city government to more effectively allocate funds for improvements in the future. This general lecture helped provide me more insight into the real-world applications of work in departments like those around the country.

 

I’m hoping to start more readings next week and start helping with my site advisor’s review article.

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Comments:

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    mahalena_g
    Hi Valerie! This sounds like such an incredible opportunity to apply mathematical modeling to real-world environmental challenges! I'm excited to follow your project!
    February 10, 2025 at 11:58 am - Reply
    aswita_k
    Hey Valerie! I think it's interesting that your research intersects between both the climate and applied math. Do you think this research will focus on furthering current climate issues we're seeing like fires in California and the hurricanes in Florida?
    February 10, 2025 at 8:55 pm - Reply
      valerie_p
      Definitely! Urban climate modeling, and climate modeling in general, can help us understand how different infrastructure changes might help reduce/increase the effects of global climate or which areas of a city/state might be most vulnerable. This in turn can guide policymakers on where to invest funds.
      February 12, 2025 at 4:42 pm - Reply
    bhavitha_s
    Hi Valerie! Your project seems really interesting! You said you'll be helping with a review article on the history of urban planning--I'm curious to know: is there a specific geographical area you and your advisor are focusing on?
    February 12, 2025 at 9:58 am - Reply
      valerie_p
      Thanks for the question! We do not have a specific area we are looking at. My part is actually a much smaller section in a larger paper my advisor has been working on. But we're not actually focusing on the results of different models in the past decades but rather the methodology, if that makes sense. So we're not looking at specifically models for the Phoenix area or something like that, but rather, a lot of models from a lot of areas and trying to see if their increased complexity has actually led to increased accuracy.
      February 12, 2025 at 5:44 pm - Reply
    mr_mcclernon
    Hi Valerie - did you get my last message? - mac
    February 12, 2025 at 11:56 am - Reply
    mr_mcclernon
    Hi Valerie - here is the original question i thought i posted. Do you use Monte Carlo modeling or something else. thanks, mac
    February 13, 2025 at 7:44 am - Reply
      valerie_p
      I'm not super familiar with the way various climate models are constructed, so this is my best educated guess. But I think Monte Carlo modelling is a component of different regional climate models. The models often start as a very bio geophysical model, and then Monte Carlo is used to determine the sensitivity of various parameters in these models. This analysis is then usually used to help reduce a more complex model into a more frugal or simpler one. So yes, Monte Carlo modelling is usually involved in the process.
      February 13, 2025 at 5:06 pm - Reply
    vishruth_p
    Hi Valerie! This seems to be an exciting project that shows how math has many unexplored applications in the real world. Since your advisor mentioned concerns about model skill improvement, what factors do you think contribute most to the stagnation in model accuracy over the past decade?
    February 13, 2025 at 12:59 pm - Reply
      valerie_p
      I don't know if it's a stagnation so much as almost reaching like a carrying capacity. Like, we've developed advanced enough models that are close enough to real life simulations, and we're making them more and more complex. But because we're already fairly accurate, there's just smaller increases in accuracy now. Like, if you start with a very rudimentary model and say it's accurate in only 25% of simulations, it's much easier to improve that accuracy, but say your complex model is accurate 90% of the time, you're making more complex models but really only increasing the accuracy by 1 or 2%. So I guess the point becomes, at what point is added complexity in models just not worth the additional costs? But to try to get back to your original question, part of that stagnation could be due to the parameters. So that'd be both the availability of data as well as the biased induced when researchers choose what parameters to include and what not to include. So for example, a researcher might be deciding whether to include turbulent latent heat as a parameter in their model. Maybe they choose not to include it but in this particular environment, it's a crucial factor, and then the model becomes less accurate. I hope that helps answer your question!
      February 13, 2025 at 4:58 pm - Reply

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