IL- Weatherman- NYTIMES

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Salt Lake Community College *

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1010

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Geography

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Apr 3, 2024

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docx

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ATMO-1010-501 Chelsi Hunsaker IL:3 – The Weatherman is not a moron 1. Why do you think we are able to predict weather better than other things like economics, politics, or sports? Weather Forecasters have accepted their imperfections and that no matter how much data they have access to, the weather is dynamic. Forecasters rely on dynamic weather predictions – programs that simulate the physical systems that can produce clouds and cold fronts. 2. We are now in an era of "big data." What does this mean and how does it help us forecast the weather? According to the NY Times article, our databases are so powerful that we, our computers. “Big Data” means that we are able to access any information online necessary to plan our lives and predict the upcoming future. “Big Data” also refers to use of supercomputers and excess of data/information produced. 3 . How has weather prediction changed from the 19th to the 20th to the 21st century ? At the beginning of 19 th century, they used to collect observations of temperatures, barometric pressure, and wind speeds. In 1950 they developed the first computer weather forecast in real time. I.B.M BlueFire was created – dynamic weather prediction programs are developed and used to simulate the physical systems that could produce weather. The use of super computers to create “Big Data.” The use of Radar, Satellites and ASOS systems have helped predict weather in the 21 st century. 4 . Why is the predictability of weather limited? (It is impossible to ever be able to perfectly predict the weather.) Predictability is flawed because of the randomness. Thermometers are not perfect, and it’s impossible to physically stick a thermometer into every molecule in the atmosphere. Weather is also nonlinear, so it abides by exponential instead of arithmetic status. A small change in conditions can develop into a large and unexpected variance of outcomes. It is impossible to perfectly measure atmosphere and the equations simulating the atmosphere. 5. What are some of the challenges of dispensing weather forecasts to the general public?

One of the challenges is the uncertainty of the forecasts and the ability to change. The weather service also struggles with how much to let the public in on (discretion) and the margin of error in forecasts. Messages of uncertainty can be cut short through private sector forecasters. Catering to the demands of viewers can also ruin the risk of making forecasts less accurate and proving inaccurate details or uncertainties. 6. Which method do you think results in the most accurate forecast and WHY? I agree with the context that The Numerical Weather prediction method is one of the best for developing an accurate forecast. The power of computers along with humans can develop more certain forecasts. Humans can fill in the gaps of data and can alter the predictions made by the computer to create a more accurate idea of the forecast. 7. Do you think it is harder to forecast the weather in Utah than it is in southern California? Why or why not? I think the weather in Utah is harder to predict because the weather is different every day and season, California has more predictable weather and can use a Persistence Method of developing weather forecasts because the weather in California changes very little throughout the year. Utah the weather changes significantly from day to day. 8. Describe two (2) reasons you think that it is hard to use a model like the NAM if you do not have extensive training in meteorology. 1. I think one of the main reasons it is hard to use a model like NAM is because it is a numerical model used to describe the atmosphere through mathematical equations. Another reason the NAM model is hard to use without extensive training is understanding the models grid of points (model domain)resolution and the numerical data from altitudes.

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