Real Climate Science

Tony Heller shows how government institutions like NASA misrepresent climate data.

It's very hard for reasonably intelligent people, when provided with this data, not to come to the conclusion that there is a clear trend of warming, and that anyone who refutes the trend is a "science denier" because the data is right there as clear as day. Their worldview suffers two major flaws.

First, they can't imagine that NASA would be dishonest, and assume that anyone confidently declaring "fake data!!!" is far more likely to be the dishonest party. However, NASA may actually be the most dishonest organization within the entire government (which is saying a lot these days). Because of NASA, people the world over look up at the night sky and marvel that man walked around on its surface half a century ago. It is the greatest lie ever fabricated. Compared to that, skewing some temperature data is pedestrian.

Second, people don't understand the difference between raw data and model outputs. To a certain extent that is understandable because NASA (whom they trust) is doing everything it can to sew confusion on that matter. In the most recent NASA News column on this blog, we dove into a few papers being promoted by the NASA homepage. They were peer-reviewed by major journals, and yet routinely passed off model outputs as measurements. Most of the people who follow the NASA newsfeed, and even many who dig into the journals as well, are left with the impression that NASA has measured the size of a neutron star... and that's that. It's a cold fact that cannot be argued against. But it isn't actually a fact. It's an opinion! It is not a fundamental measurement, but the result of a process which takes completely different set of data and tries to infer what certain measurements would be, based on the modeler's understanding of the domain. If it is the modeler's opinion that pulsars are caused by neutron stars, then the model is going to return some opinionated measurements of those stars.

This is the same phenomenon that caused the great polling fiasco of 2016. For many months, we said the polls were wrong. (I actually made a good chunk of change because of it.) The liberals told us not only that we were wrong, but that it was absurd to call polls wrong, which are just a collection of data and thus - facts. Well, they were wrong because the polling data that gets released to the public are model outputs. Because it's impossible to get a perfectly accurate poll of American voters without questioning every single one, they scale the data to try to make it representative of the larger group. For instance, if they find that 60% of those who respond are women, they'll attempt to adjust the results to account for that. It's the adjusted data that gets promoted, not the raw numbers. That works fine as long as the pollster is competent, knowledgeable, and not biased to prefer a particular outcome.

The same flawed logic causes huge problems in such disparate fields as astrophysics, climate studies, and political punditry. But ask yourself, of these groups of people, which do you expect to understand the implications of viewing adjusted data rather than raw data?

• Facebook users
• political activists
• naive college graduates
• news anchors reading a teleprompter
• high school science teachers
• pundits on corporate talk shows
• politicians
• esteemed scientists representing renown research institutions who are published in premier Journals

It is, of course, the scientists whom we should most expect to know better. That has been why this blog has slowly shifted focus from politics, towards the narratives promoted by the press, and now more towards the scientists and their institutions. Because, if even the scientists aren't even held to the standard of understanding the difference between raw data versus the inferences made from that data, then there's no way we can expect the people of those other groups to do so as well.

While I have been following Tony Heller for a while on YouTube, I only just realized he keeps a blog with an RSS feed. It is very active, and has been added to the bloglist on the sidebar. I recommend following and sharing his videos, as they are very accessible to the general public.