{"id":57641,"date":"2025-08-27T16:48:29","date_gmt":"2025-08-27T11:18:29","guid":{"rendered":"https:\/\/e-gmat.com\/blogs\/?p=57641"},"modified":"2025-09-05T00:18:19","modified_gmt":"2025-09-04T18:48:19","slug":"meteorologists-say-that-if-only-they-could-design-an-accurate-mathematical","status":"publish","type":"post","link":"https:\/\/e-gmat.com\/blogs\/meteorologists-say-that-if-only-they-could-design-an-accurate-mathematical\/","title":{"rendered":"Meteorologists say that if only they could design an accurate mathematical model of the atmosphere with all its…"},"content":{"rendered":"A <\/span> 3<\/span> min read <\/span><\/span>\n

Meteorologists say that if only they could design an accurate mathematical model of the atmosphere with all its complexities, they could forecast the weather with real precision. But this is an idle boast, immune to any evaluation, for any inadequate weather forecast would obviously be blamed on imperfections in the model.<\/p>\n\n\n\n

Which of the following, if true, could best be used as a basis for arguing against the author’s position that the meteorologists’ claim cannot be evaluated?<\/p>\n\n\n\n

A. Certain unusual configurations of data can serve as the basis for precise weather forecasts even though the exact causal mechanisms are not understood.<\/p>\n\n\n\n

B. Most significant gains in the accuracy of the relevant mathematical models are accompanied by clear gains in the precision of weather forecasts.<\/p>\n\n\n\n

C. Mathematical models of the meteorological aftermath of such catastrophic events as volcanic eruptions are beginning to be constructed.<\/p>\n\n\n\n

D. Modern weather forecasts for as much as a full day ahead are broadly correct about 80 percent of the time.<\/p>\n\n\n\n

E. Meteorologists readily concede that the accurate mathematical model they are talking about is not now in their power to construct.<\/p>\n\n\n\n

SOLUTION<\/h2>\n\n\n\n

Passage Analysis:<\/h3>\n\n\n\n
Text from Passage<\/strong><\/td>Analysis<\/strong><\/td><\/tr>
Meteorologists say that if only they could design an accurate mathematical model of the atmosphere with all its complexities, they could forecast the weather with real precision.<\/em><\/td>What it says:<\/strong> Meteorologists claim they could make perfectly accurate weather forecasts if they had a complete mathematical model of the atmosphere
What it does:<\/strong> Presents the meteorologists’ position that we’ll be evaluating
What it is:<\/strong> Meteorologists’ claim<\/td><\/tr>
But this is an idle boast, immune to any evaluation, for any inadequate weather forecast would obviously be blamed on imperfections in the model.<\/em><\/td>What it says:<\/strong> The author argues this claim can’t be tested because bad forecasts would always be blamed on model flaws, not the theory itself
What it does:<\/strong> Directly challenges the meteorologists’ claim by saying it’s impossible to evaluate
What it is:<\/strong> Author’s counterargument and main conclusion<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Argument Flow:<\/h3>\n\n\n\n

The argument starts by presenting the meteorologists’ claim about perfect weather forecasting, then immediately attacks this claim by arguing it can’t be properly tested or evaluated.<\/p>\n\n\n\n

Main Conclusion:<\/h3>\n\n\n\n

The meteorologists’ claim about accurate weather forecasting cannot be evaluated because any failures would be blamed on model imperfections rather than the theory itself.<\/p>\n\n\n\n

Logical Structure:<\/h3>\n\n\n\n

The author uses a single premise to support the conclusion: since bad forecasts would always be blamed on the model being incomplete rather than the theory being wrong, there’s no way to actually test whether the meteorologists’ claim is valid. This creates what the author sees as an unfalsifiable statement.<\/p>\n\n\n\n

Prethinking:<\/h3>\n\n\n\n

Question type:<\/h4>\n\n\n\n

Weaken – We need to find information that reduces belief in the author’s conclusion that the meteorologists’ claim cannot be evaluated<\/p>\n\n\n\n

Precision of Claims<\/h4>\n\n\n\n

The author makes an absolute claim about evaluation impossibility – that ANY inadequate forecast would OBVIOUSLY be blamed on model imperfections, making the theory immune to ANY evaluation<\/p>\n\n\n\n

Strategy<\/h4>\n\n\n\n

To weaken the author’s position, we need to show that the meteorologists’ claim CAN actually be evaluated in some meaningful way. We should look for scenarios where:<\/p>\n\n\n\n

  1. There are ways to test the theory that don’t fall into the blame-shifting trap,<\/li>
  2. We can distinguish between model problems and theory problems, or<\/li>
  3. There are objective criteria that could evaluate the claim fairly<\/li><\/ol>\n\n\n\n

    Answer Choices Explained<\/h3>\n\n\n\n

    A. Certain unusual configurations of data can serve as the basis for precise weather forecasts even though the exact causal mechanisms are not understood.<\/p>\n\n\n\n

    This choice discusses unusual data configurations allowing precise forecasts without understanding exact mechanisms. However, this doesn’t address the author’s core concern about evaluation impossibility. The author isn’t questioning whether accurate forecasts are possible, but whether the meteorologists’ specific claim about mathematical models can be evaluated. This choice sidesteps the evaluation issue entirely.<\/p>\n\n\n\n

    B. Most significant gains in the accuracy of the relevant mathematical models are accompanied by clear gains in the precision of weather forecasts.<\/p>\n\n\n\n

    This directly weakens the author’s position by establishing a measurable relationship between model improvements and forecast precision. If we can observe that better models consistently produce better forecasts, then we DO have a way to evaluate the meteorologists’ claim. This contradicts the author’s assertion that the claim is ‘immune to any evaluation’ because it shows we can test whether the theory holds up in practice.<\/p>\n\n\n\n

    C. Mathematical models of the meteorological aftermath of such catastrophic events as volcanic eruptions are beginning to be constructed.<\/p>\n\n\n\n

    The fact that models for volcanic eruptions are being constructed doesn’t address whether the meteorologists’ claims about general weather forecasting can be evaluated. This is about a specific type of modeling that doesn’t resolve the broader evaluation problem the author identifies.<\/p>\n\n\n\n

    D. Modern weather forecasts for as much as a full day ahead are broadly correct about 80 percent of the time.<\/p>\n\n\n\n

    Current forecast accuracy statistics don’t help us evaluate the meteorologists’ future claims about what they could achieve with perfect models. The author isn’t questioning current forecasting ability, but rather arguing that we can’t properly test the meteorologists’ theoretical claim about perfect models.<\/p>\n\n\n\n

    E. Meteorologists readily concede that the accurate mathematical model they are talking about is not now in their power to construct.<\/p>\n\n\n\n

    If meteorologists admit they can’t currently build the accurate model they’re discussing, this actually supports the author’s position rather than weakening it. It reinforces that the claim might indeed be impossible to evaluate since the proposed solution doesn’t currently exist.<\/p>\n","protected":false},"excerpt":{"rendered":"

    Meteorologists say that if only they could design an accurate mathematical model of the atmosphere with all its complexities, they could forecast the weather with real precision. But this is an idle boast, immune to any evaluation, for any inadequate weather forecast would obviously be blamed on imperfections in the model. 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