Questions about climate and physics

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Discussion Overview

This discussion revolves around the complexities of climate science, particularly the reliability of climatological forecasts compared to weather predictions, the attribution of specific weather phenomena to climate change, and the validity of claims regarding increased extreme weather events due to rising temperatures. Participants explore theoretical, conceptual, and empirical aspects of these topics.

Discussion Character

  • Exploratory
  • Debate/contested
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • Some participants question why long-term climatological forecasts are considered reliable despite the complexity of the atmosphere, suggesting that they may be treated as boundary value problems (BVP) compared to initial value problems (IVP) for short-term weather forecasts.
  • There is a debate over the claims that climate change will lead to an increase in extreme weather events, with some participants expressing skepticism about the data supporting these assertions.
  • One participant argues that the increase in severity of weather extremes is due to higher energy in the atmosphere, while another challenges the existence of increased frequency or intensity of specific events like hurricanes and floods.
  • Participants discuss the concept of event attribution analysis, questioning its scientific validity and how it relates to determining the influence of climate change on specific weather events.
  • Some participants express differing views on the accuracy of climate models and the extent to which human activity contributes to climate change versus natural cycles.
  • There are references to the importance of long-term data collection methods, such as tree ring analysis and lake varves, in understanding climate shifts.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the reliability of claims regarding increased extreme weather events due to climate change. There are multiple competing views on the validity of these claims, the accuracy of climate models, and the role of human activity versus natural cycles in climate change.

Contextual Notes

Participants highlight limitations in understanding the attribution of specific weather phenomena to climate change, including the challenges of comparing against counterfactual scenarios and the uncertainties inherent in climate modeling.

Who May Find This Useful

This discussion may be of interest to those studying climate science, meteorology, or related fields, as well as individuals seeking to understand the complexities and debates surrounding climate change and its impacts.

  • #31
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  • #32
Vanadium 50 said:
The second problem is how much tuning should be done on the data. If you had a model good enough to predict 5 hurricanes ina time window and you saw 4 or 6 would this be evidence in favor or against? A supercomputer is not going to tell you the answer to that.

His point is it is inherently probabilistic, as the climate is chaotic. A better supercomputer will give us better probabilities. He knows this from his work on long-term climate change and medium-term climate prediction. When a hurricane is forming, it is impossible to predict what it will do - all you can do is give probabilities of what will happen. Better computers will give better predictions. It is of great practical value to those tasked with preparing for emergencies who are very interested in the probability of if, for example, it will hit Brisbane rather than miss Australia completely.

Just a note about how he does it. The models all require parameters. What he does is change the parameters slightly and run it again. The model must be run many times to get good probabilities - the more times, the better. Faster computers mean better models that can be run more times and get better probabilities. I think further discussion should be in a thread on the computational modelling of chaotic systems.

I don't think there is anything more to discuss, so I have permanently shut the thread.

Thanks
Bill
 
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