Meteorologists: If we could design an accurate model, we could forecast weather with precision.
Author: You cannot evaluate this. Inadequate forecast will be blamed on model.

The author is saying that meteorologists claim that give us an adequate model and we will forecast weather with precision cannot be evaluated. Who can say what an adequate model is. For every forecast that is not correct, the meteorologists will just blame the model.

We want to argue against the author's position. So we want to say that the claim can be evaluated. You can measure whether the model is adequate or not. Let's look for something that helps us.

(A) Certain unusual configurations of data can serve as the basis for precise weather forecasts even though the exact causal mechanisms are not understood.
Certain data config can serve as basis for precise weather forecasts. But we want to find whether we can have an "adequate model". This it does not mention. Not correct.

(B) Most significant gains in the accuracy of the relevant mathematical models are accompanied by clear gains in the precision of weather forecasts.
Better models lead to better precision of forecasts. This is against the author's position. We can evaluate whether a model is good or not. Could be the answer.

(C) Mathematical models of the meteorological aftermath of such catastrophic events as volcanic eruptions are beginning to be constructed.
Special models are getting constructed. Doesn't help establish whether we can evaluate models.

(D) Modern weather forecasts for as much as a full day ahead are broadly correct about 80 percent of the time.
Current accuracy of forecasts is irrelevant.

(E) Meteorologists readily concede that the accurate mathematical model they are talking about is not now in their power to construct.
Doesn't help us negate the author's position that we cannot evaluate the adequacy of the model. Not correct.

Answer (B)
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ankur_1988, the key to understanding why (B) is the correct answer is correctly interpreting the question, which is written in a kind of confusing way. Let's break the question down:

• First, we have the "meteorologists' claim": "if only they could design an accurate mathematical model of the atmosphere with all its complexities, they could forecast the weather with real precision."
• Then, we have the "author's position" about the above claim (as stated in the question): "the meteorologists' claim cannot be evaluated."
• How does the author reach that position? By stating that: "any inadequate weather forecast would obviously be blamed on imperfections in the model."

Now we are asked to find an answer choice that could be used to argue against the author's position. So, we need evidence that the meteorologists' claim can
be evaluated. With that in mind, let's go through the answer choices:


Answer (A) provides information about how the mathematical models are constructed, but does not allow us to further evaluate the claim of the meteorologists. Because it does not answer our question, we can throw (A) out.


This answer shows a measurable relationship between mathematical models and the precision of weather forecasts. Establishing this relationship makes it possible to evaluate the meteorologists' claim, because the trend provides evidence for expected future results. Answer (B) is looking good.


Does this answer choice assist in evaluating the meteorologists' claim? We are concerned with weather predictions in general, not with the results of certain catastrophic events. Overall, answer (C) does not provide information that argues against the author's claim. (C) is out.


This answer choice does not specify if modern weather forecasts are more accurate than previous forecasts, or even whether these forecasts are using the mathematical models at the heart of this question. Without additional context, this option does not help in evaluating the meteorologists' claim. Throw answer (D) out.


In the passage, the meteorologists state that "if only" they could create a more complex model, they could predict the weather with more accuracy. So, they already admit that the model is "not now in their power to construct," as written in answer choice (E). The claim that we are attempting to evaluate deals with future models and associated predictions, not with current capabilities. Option (E) does not provide evidence one way or the other on the meteorologists' claims, and so is not our answer.

Answer (B) is correct.
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shubham2312

The author does not presuppose that precise weather forecasts based on imperfect understanding cannot ever occur, so A cannot be used to argue against the author. Choice C, which says nothing about the quality of the models or their effect on the precision of the weather forecasts, also provides no material for a counterargument. The author's position is consistent with D. The concession described in E is already tacitly conveyed in the author's report of the meteorologists'claim.

However, B can be used to argue that the claim is not impossible to evaluate but actually somewhat plausible, because B indicates that there is a strong correlation between increasing perfection of the model and increasingly accurate forecasts. Therefore, B is the best answer.

How is B saying that the model can be evaluated . From all that i can understand B says that accuracy in the model is accompanied with accuracy in predictions.
its the same what the argument is saying

Hi NCRanjan

Now the passage states that as per the mets if an accurate mathematical model is possible, then weather forecast with real precision is also possible. Now, as any inadequate forecast would be blamed on imperfection in model, the statement made my met is an idle boast

Pre-thinking:- In what scenario can an imperfection in forecast not be blamed on the accuracy of the model.

So, as per the second choice - significant gains in mathematical models is accompanied by an increase in the weather forecast. Now, if there is an inadequate forecast we cannot blame it on an inaccurate mathematical model.


Please revert in case of any other question.

Could hardly time myself on this one.. this one is pretty heavy.. it all comes down to the question stem.. if you understand the question steam, you will know the answer..

Straight b, given that you have understood the question stem

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Official Explanation

Argument Evaluation

Which one of the following would provide the best basis for arguing against the author's reasoning?

Meteorologists claim that the design of a mathematical model that would accurately capture all the complexities of weather dynamics would enable great precision in weather forecasting. However, according to the skeptical reasoning given, the meteorologists' claim cannot be evaluated, because any inaccuracies in weather forecasting would be attributed to shortcomings in the model.

It is important to consider that with the incremental improvement of capabilities for collection and analysis of data, including new types of data, model construction would improve to more accurately reflect weather dynamics. However, it would remain true that random factors affecting weather may continue to reduce accuracy of forecasts.

A. This suggests that weather forecasting accuracy can be attained under certain unusual conditions, even in the absence of understanding complex factors that affect weather. Nevertheless, what is at issue in the skeptical reasoning given is how, or whether, overall forecasting accuracy can be attained under all conditions. Furthermore, it is unclear whether the meteorologists' aspiration to great precision and accuracy in weather forecasting can even be evaluated.

B. Correct. This tells us that significant but incremental improvements in the accuracy of mathematical models result in gradual improvements in the accuracy of weather forecasting—even if wholly accurate and precise forecasts are never attained. This would allow evaluation of any progress in modeling and forecasting weather.

C. Volcanic eruptions can affect weather but they do not rank as major ongoing causes of weather phenomena. The reasoning given refers to forecasting of weather under all conditions, whether the meteorologists' ideal is attainable or can even be evaluated.

D. This suggests that current weather forecasting falls significantly short of the forecasting accuracy that the meteorologists mentioned aspire to. This idea reinforces the skeptical reasoning that suggests the meteorologists' ideal is not amenable to evaluation and may not even be attainable.

E. This does not convey a reason for thinking the meteorologists' claim can reasonably be subjected to evaluation; furthermore, it seems to provide some support for the skeptical reasoning given.

The correct answer is B.

Meteorologists: if only they could design an accurate mathematical model with all complexities, they could forecast with real precision
Premise: any inadequate weather forecast would obviously be blamed on imperfections in the model
Conclusion: the claim is an idle boast, cannot be evaluated

Question: weaken

Basically meteorologists said as long as they can build a model that encompasses all variables, they can reach 100% precision. The author attacks that statement by saying it's impossible to know whether it is due to the imperfection of the model if it fails to forecast 100%.

A) if those mechanisms cannot be understood, there is no way to evaluate the reason if the model fails to deliver 100% precise result. Not weaken, but strengthen

B) Correct. This connects the accuracy of the model to the accuracy the forecasts - so as long as the model can be improved, the accuracy of the forecast can be improved as well. Even though the perfect 100% might not be attained, but at least we can evaluate whether meteorologist's claim is plausible. Also "most significant" indicate the extent, typical correct answer.

C) "volcano eruptions" are out of scope, unknown impact on the model of weather forecast

D) this means we have room to improve the forecast accuracy? But provides nothing to help with the argument

E) then no one can even evaluate/test whether the argument is true or not. This is similar to "If I can go back in time and choose a different path I would have been a billionaire now", god knows how to test it

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.

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?


(A) Certain unusual configurations of data can serve as the basis for precise weather forecasts even though the exact causal mechanisms are not understood.

(B) Most significant gains in the accuracy of the relevant mathematical models are accompanied by clear gains in the precision of weather forecasts.

(C) Mathematical models of the meteorological aftermath of such catastrophic events as volcanic eruptions are beginning to be constructed.

(D) Modern weather forecasts for as much as a full day ahead are broadly correct about 80 percent of the time.

(E) Meteorologists readily concede that the accurate mathematical model they are talking about is not now in their power to construct.

Explanation:

This question is of a typical example of circular reasoning type in which
1. the meterologists are saying (hypothetical tone)
if accurate model>>>>then precise forecast

2. Author is saying---The claim of Meteorologists as an idle boast that if forecast is inadequate then that model is imperfect.


If we anyhow strengthen the meteorologists point then only this circular argument will break .

Option B correctly establishes that there is an inter-relation between accuracy of model and forecast precision. Through this evaluation can be made possible.

Hence B is the correct answer.

Take away:

So, the authors take is whether it is possible to determine whether the peak accuracy of the mathematical model is reached, so that the Meteorologists can no longer blame the model for any failure in prediction. If there is a way then we can argue against the authors position that there is no way.

What if there is a way of finding out whether the model is perfect?
Continuous gains in accuracy of models is accompanied by clear gains in precision of weather forecasting.
When there will be no further gains, then there will be no further accurate models (peak model is reached) and the meteorologists won’t be able to blame the models. So it is possible to determine whether a model is perfect or not.