The problem is that somehow envuironmental studies became a discipline separate from chemistry or physics or geology or biology or oceanography, and wandered into an interdisciplinary discipline that was and had no discipline at all. Starting from a foundation in each of these branches of knowledge combined with a bunch of courses on environmental policy it is almost impossible to become a disciplined scientist. Evniron 1 + chem 1 + Phys1 + bio 1 + rocks of jocks does not make you a laboratory scientist.
There has been some excellent scientific work in this area, and it is almost all done by PhD chemists or physicists or geologists or some such. It just takes that level of training and specialization to master a technique that can provide new insights and knowledge.
You’re right! bttt
Proof that you’re right:
Here’s the view on global warming of the paramount living physicist:
“... all the fuss about global warming is grossly exaggerated. Here I am opposing the holy brotherhood of climate model experts and the crowd of deluded citizens who believe the numbers predicted by the computer models. Of course, they say, I have no degree in meteorology and I am therefore not qualified to speak. But I have studied the climate models and I know what they can do. The models solve the equations of fluid dynamics, and they do a very good job of describing the fluid motions of the atmosphere and the oceans. They do a very poor job of describing the clouds, the dust, the chemistry and the biology of fields and farms and forests. They do not begin to describe the real world that we live in. The real world is muddy and messy and full of things that we do not yet understand. It is much easier for a scientist to sit in an air-conditioned building and run computer models, than to put on winter clothes and measure what is really happening outside in the swamps and the clouds. That is why the climate model experts end up believing their own models.”.... Freeman Dyson, (8/8/07) http://www.edge.org/3rd_culture/dysonf07/dysonf07_index.html
<>
Kerry Emmanuel, an MIT meteorologist admits as much:
“Computer modeling of global climate is perhaps the most complex endeavor ever undertaken by mankind. A typical climate model consists of millions of lines of computer instructions designed to simulate an enormous range of physical phenomena, including the flow of the atmosphere and oceans, condensation and precipitation of water inside clouds, the transfer of solar and terrestrial radiation through the atmosphere, including its partial absorption and reflection by the surface, by clouds and by the atmosphere itself, the convective transport of heat, water, and atmospheric constituents by turbulent convection currents, and vast numbers of other processes.
There are by now a few dozen such models in the world, but they are not entirely independent of one another, often sharing common pieces of computer code and common ancestors.
Although the equations representing the physical and chemical processes in the climate system are well known, they cannot be solved exactly.
It is computationally impossible to keep track of every molecule of air and ocean, and to make the task viable, the two fluids must be divided up into manageable chunks. The smaller and more numerous these chunks, the more accurate the result, but with today’s computers the smallest we can make these chunks in the atmosphere is around 100 miles in the horizontal and a few hundred yards in the vertical, and a bit smaller in the ocean. The problem here is that many important processes are much smaller than these scales.
For example, cumulus clouds in the atmosphere are critical for transferring heat and water upward and downward, but they are typically only a few miles across and so cannot be simulated by the climate models.
Instead, their effects must be represented in terms of the quantities like wind and temperature that pertain to the whole computational chunk in question.
The representation of these important but unresolved processes is an art form known by the awful term parameterization, and it involves numbers, or parameters, that must be tuned to get the parameterizations to work in an optimal way.
Because of the need for such artifices, a typical climate model has many tunable parameters, and this is one of many reasons that such models are only approximations to reality. Changing the values of the parameters or the way the various processes are parameterized can change not only the climate simulated by the model, but the sensitivity of the model’s climate to, say, greenhouse-gas increases.
How, then, can we go about tuning the parameters of a climate model in such a way as to make it a reasonable facsimile of reality? Here important lessons can be learned from our experience with those close cousins of climate models, weather-prediction models. These are almost as complicated and must also parameterize key physical processes, but because the atmosphere is measured in many places and quite frequently, we can test the model against reality several times per day and keep adjusting its parameters (that is, tuning it) until it performs as well as it can.
But with climate, there are precious few tests. One obvious hurdle the model must pass is to be able to replicate the current climate, including key aspects of its variability, such as weather systems and El Niño. It must also be able to simulate the seasons in a reasonable way: the summers must not be too hot or the winters too cold, for example.
Beyond a few simple checks such as these, there are not too many ways to test the model, and projections of future climates must necessarily involve a degree of faith.
The amount of uncertainty in such projections can be estimated to some extent by comparing forecasts made by many different models, with their different parameterizations (and, very likely, different sets of coding errors). We operate under the faith that the real climate will fall among the projections made with the various models..” ~ Kerry Emmanuel
More:
“The evolution of the scientific debate about anthropogenic [man-caused] climate change illustrates both the value of skepticism and the pitfalls of partisanship.” “ Scientists are most effective when they provide sound, impartial advice, but _____their reputation for impartiality is severely compromised by the shocking lack of political diversity among American academics, who suffer from the kind of group-think that develops in cloistered cultures_____. Until this profound and well documented intellectual homogeneity changes, scientists will be suspected of constituting a leftist think tank.” “On the left, an argument emerged urging fellow scientists to deliberately exaggerate their findings so as to galvanize an apathetic public...” “Conservatives have usually been strong supporters of nuclear power. .. Had it not been for green opposition, the United States today might derive most of its electricity from nuclear power, as does France; thus the environmentalists must accept a large measure of responsibility for today’s most critical environmental problem.” ~ Kerry Emmanuel http://bostonreview.net/BR32.1/emanuel.html
bttt
“...it is almost all done by PhD chemists or physicists or geologists or some such...” ~ AndyJackson
Speakiing of GEOLOGISTS, here is a recent rant from a geologist friend of mine:
http://themigrantmind.blogspot.com/2011/02/war-is-peace-freedom-is-slavery-warming.html