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.
The answer is B. However, I choose A because I think if certain data can serve as the basis for precise weather forecasts, then inadequate weather forcasts will be blamed on those data rather than flaws in the math model, thus weakening the author's argument. Am I wrong? Can someone explain anwser B? Thanks~
The author concludes that the metorologists claim cannot be evaluated.
We have to show that he may not be right.
A suggests that certain peices of data form the results of the model...
even if you say the data is the reason, it still does not provide anything to disprove the authors conclusion. The author claims that the model cannot be proved to be accurate.
B suggests that to improve forecasts, we need to build good and accurate mathematical models which will result in precise forecasts.
Clear Gains in the Accuracy of Mathematical Models = Gains in the precision of the weather forecasts
If this is true, then the authors argument about the evaluation of the
model is weakened...
hope this helps