It's the basis for a model of a resistor, but it's an exact equation of resistance. There is a difference.
> they're testing the model, gathering new data to see how well the models hold up.
No, they are not testing the model, they are trying to improve the model by recording what it did in the past.
To test the model you make a prediction of what it will do in the future, then wait and see if it happens the way your model shows. It can't be done for climate though since it would take decades. They do try to test it by giving it old data and seeing if it predicts current conditions - which is great, but does not help in predicting the future since the input will be different this time.
> you're acting as if those poor scientists haven't realised this yet.
They most definitely do realize how poor the results are (just see how many weasel words they put in the paper linked to this topic), they just have no better options.
Do you really not understand the difference between a model and a fundamental equation? A model does not have perfect input, and a model may not include all things that can affect the output.
An physical law (an equation usually), is exact. It might not apply to real physical objects (like the ideal gas law), but that doesn't make the equation a model - the equation is correct for where it's used, it just doesn't cover everything.
Excellent quote BTW, but don't take from that that everything is a model. The real world is not a model - if I test something and it does something in the real world, I have real information. In a model I only have the information I put in it, and it's simply impossible for me to put in everything.
They made a model - but they missed something. Good thing they were able to test it, and see what they missed. But if you don't have the ability to test? (Like climate.) Then your model is useless.
A model is useful only if you can test it. The model will help you know what to test, the model will help you see if you understand the topic. But a model you can not test is useless.
(Just to repeat myself: I'm not arguing about models, I'm arguing about models that can't be tested.)
The glacier model is wrong, but wrong in the wrong direction (Actually I think that's combined results from multiple models, but anyway...). How do they know? Because there are climatologists out on the ice, or in satellites taking measurements-1. Testing the model - you know, all that stuff that is supposedly impossible to do.
1- there are even high resolution GPS modules in Greenland which can estimate ice loss by how far up the crust lifts (as well as detecting plate tectonics).
It's the basis for a model of a resistor, but it's an exact equation of resistance. There is a difference.
> they're testing the model, gathering new data to see how well the models hold up.
No, they are not testing the model, they are trying to improve the model by recording what it did in the past.
To test the model you make a prediction of what it will do in the future, then wait and see if it happens the way your model shows. It can't be done for climate though since it would take decades. They do try to test it by giving it old data and seeing if it predicts current conditions - which is great, but does not help in predicting the future since the input will be different this time.
> you're acting as if those poor scientists haven't realised this yet.
They most definitely do realize how poor the results are (just see how many weasel words they put in the paper linked to this topic), they just have no better options.
> try looking at http://en.wikipedia.org/wiki/Mathematical_model - what do you see? Ooh - equations.
Do you really not understand the difference between a model and a fundamental equation? A model does not have perfect input, and a model may not include all things that can affect the output.
An physical law (an equation usually), is exact. It might not apply to real physical objects (like the ideal gas law), but that doesn't make the equation a model - the equation is correct for where it's used, it just doesn't cover everything.
Excellent quote BTW, but don't take from that that everything is a model. The real world is not a model - if I test something and it does something in the real world, I have real information. In a model I only have the information I put in it, and it's simply impossible for me to put in everything.
I found a great example for you: http://en.wikipedia.org/wiki/Castle_Bravo#Cause_of_high_yiel...
They made a model - but they missed something. Good thing they were able to test it, and see what they missed. But if you don't have the ability to test? (Like climate.) Then your model is useless.
A model is useful only if you can test it. The model will help you know what to test, the model will help you see if you understand the topic. But a model you can not test is useless.
(Just to repeat myself: I'm not arguing about models, I'm arguing about models that can't be tested.)