Meteorologists say that if only they could design an accurate mathemat

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.

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 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.

Please can someone help me how to read the last sentence “but .....”. I understood the global meaning, yet I couldn’t rightfully read it.

Posted from my mobile device

But this is an idle boast, immune to any evaluation, for any inadequate weather forecast would obviously be blamed on imperfections in the model.

But this is an idle boast, --》 means this condition is too ideal to believe.. In general this can not happen. Ask question: Why?

immune to any evaluation, --> extending what idea we got above. boast ( that model can precisely forecast) that even can not be evaluated)

for any inadequate weather forecast-subject
would obviously be blamed- main verb
on imperfections in the model. -- modifying
>> If you remember first statement and related with this statement . you shall be able to complete your thought. i.e.
If the model is perfect that can forecast with real precision, then if any error , the blame would be to 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?
>>which statement can say that if there is any inaccurate prediction then blame will not go to model . In other words, models can be evaluated .

Key point :
If model is perfect then it should FORECAST future weather. if no right forecast then it means the model is not right because model can not be evaluated.
Find an option : that is against author claim that model can not be evaluated.

B says if you accuracy of models is improved, forecast is improved.

The 2nd line : meaning is if there is inaccurate forecast then it is not necessary that model was wrong . It maybe possible that model is right and this can be evaluated.

I hope it helps.

From option A I'm understanding that although we do not have a proper explanation, but we do have an unusual data which can give precise weather forecasts. Therefore, we can benchmark any of the model with this and compare whether it is performing well or not. Therefore, the author's claim is weakened that the model's accuracy can't be tested. It can be.

Please someone help me understand how my interpretation is wrong? Thank you in advance!!

VeritasKarishma GMATNinja

(A) says that certain unusual data does give precise forecasts (so say if there are cumulus clouds at 2 km height and a storm is brewing underneath in a mountainous region), then precise forecast is possible (so scientists can tell us exactly what will happen when even though they do not understand fully how they are connected).
So the current models may be adequate for these conditions. But how do we figure whether a model is adequate for all general conditions (for various sets of usual data)?
We don't. Option (A) doesn't tell us that models can be successfully evaluated.

M: Only Max accurate model --> Only Max precise forecast
A: Ideal case. M's claim cannot be evaluated.

Task: M's claim can be evaluated: "Some kind of accurate model must give some kind of precise forecast (Some kind of work must give some kind of result)". Expectation: The relationship between the model and the forecast must be given in correct answer choice.

A. More about the model only
B. A significant progress in the model accuracy should reflect some kind of clear gains in forecast too.
C. More about the model only
D. More about the forecast only
E. More about the model only

More kudos please

GMATNinja KarishmaB how does blaming the model serve as a reason for / relate to author's conclusion that the claim can not be evaluated? How is the author using this blame thing as a reason for saying their claim cannot be evaluated.

­

The meteorologists say that they could forecast the weather with real precision IF ONLY they could design an accurate mathematical model of the atmosphere with all its complexities.

Now imagine that some cool MIT researchers release a new mathematical model of the atmosphere with all its complexities -- one that's supposedly very accurate. But even with that new model, meteorologists are unable to come up with weather forecasts that are COMPLETELY precise. That means one of two things:

1) the model is completely accurate and the meteorologists' claim (first sentence of the passage) was incorrect, or

2) the new model isn't quite perfect (in which case the meteorologists can stand by their claim).

If you're a stubborn meteorologist and you're unable to come up with perfectly precise weather forecasts, even as mathematical models of the atmosphere get better and better, you can always just say, "well, this model is BETTER, but it's still not completely accurate -- and that's why my forecasts aren't perfect."

In other words, you can always just blame the model and not your own forecasting abilities. It would be really hard for the MIT researchers to PROVE that their model is perfect, which means that it would be really hard to disprove the claim made by the meteorologists in the passage. Because the meteorologist always have an excuse (the model isn't perfect), it's really hard to evaluate their claim.

I hope that helps!

GMATNinja KarishmaB .
Hi
I am not able to understand the Choice B . How it evaluates the model, i did not get it.
thanks

­KarishmaB What you mean adequate model?  especially for A I thought A can't  be answer be cause we can't know we can evaluate model when usual data.
would you explain me "But we want to find whether we can have an "adequate model". This it does not mention. Not correct."