This post describes the comments submitted on the Draft Scoping Plan by David L. Dibble. If I knew how to do guest posts on this site, I would have made this a guest post. My apologies but I am going to have to wing it.
David L. Dibble is a retired engineer and technical consultant who has read my blog material. He sent the comment below in this weekend. He took the approach of directly exposing the core error of the entire climate movement, as he sees it.
In Chapter 10, Figure 12, the NPV of assumed GHG benefits ranges from $235 billion to $250 billion in 2020 dollars. From Chapter 3, the “value of carbon” being used in this analysis is $121 per ton of CO2. All such claims of GHG benefits are based on an incomplete and therefore misleading concept of what non-condensing GHGs are capable of doing in the atmosphere. These claims are therefore entirely speculative, and are based on inadequate and unsound attribution of a reported warming trend to emissions of GHGs. This error is compounded by unsound attribution of storm and flood events to warming from GHGs. Therefore, the claimed net benefits are not reliable for such an important matter of state policy.
To address this core error, I refer to the publicly available images and animations for the NOAA geostationary satellite “GOES-EAST”. Please see the link below, which is for Band 16 (the “CO2″ band”) and animates the most recent 8-hour series of visualizations of radiance data for the full disk (i.e. the full view of the planet.) The resolution is 2 km. Band 16 is centered at 13.3 microns wavelength in the infrared spectrum, which is the same band of wavelengths from which concerns about the GHG “heat-trapping” effect have arisen for CO2. To convert radiance values into colors, a brightness temperature scale is used. The radiance (i.e. the strength of the longwave emission being detected in the imaging sensor) at 50C on the color scale is 13 times the radiance at -90C on the scale. (This was determined from the equations and constants in the user manual. I can provide details on request.)
So when viewed this way, it becomes clear that the concept of the atmosphere as a passive “trap” in respect to the absorption and emission of infrared energy by CO2 and other GHGs is incomplete. Rather, the planet is directly observed as a huge array of highly variable emitter elements. The motion and the resulting variation in time, location, and altitude are readily seen. The formation and dissipation of clouds as a lot to do with this, and convective weather is especially powerful in the tropics. The end result is that it is all highly self-regulating as heat energy is transported from the equator to the poles and from the surface to high altitude for longwave radiation to be more easily emitted to space. In concept, it is the performance of the atmosphere as the compressible working fluid of its own heat engine operation that overwhelms the static GHG warming effect arising from the emission and absorption of infrared energy experienced at the surface, looking toward space. Put the working fluid into motion, and one grasps that heat energy cannot reasonably be expected to accumulate at the surface to harmful effect by what GHGs do in the atmosphere. Rather, the incrementally stronger radiative coupling of the lower atmosphere to the surface simply makes it easier for energy to be transferred to the working fluid of the heat engine to be circulated in three dimensions.
The IPCC attributes recent warming to GHGs based on large-grid, discrete-layer, step-iterated, parameter-tuned computer simulations of atmospheric motion which inherently cannot produce a realistic output – not even close! The crude modeling of clouds is one reason for this, and the inability to directly compute the physics of convective weather is another. Therefore, these models have no diagnostic or predictive authority at all concerning GHGs. But we can “watch” the real outputs of the planet’s emitter array from space using the most up-to-date imaging and data processing capabilities. And we can trust that the atmosphere is the perfectly authentic model of its own performance as a heat engine to produce the motion.
I would be glad to discuss this with NYSERDA or anyone reading this comment. I realize perfectly well that this goes against the climate beliefs held firmly by many in government and academic roles. Those beliefs are based on a misconception. So please watch the animation and think through the implications.
I agree with Dibble that clouds are a primary reason why the projected climate change estimates cannot be correct. In his book “Unsettled: What Climate Science Tells Us, What It Doesn’t, and Why It Matters” Dr. Steven Koonin explains this issue as follows:
The ultimate problem with the climate modeling is that it cannot simulate clouds. In order to solve the physical equations in a global climate the world has to be divided up into a three-dimensional grid. The equations are calculated for each grid cell and repeated to generate a forecast. My particular problem is that the grid cell size needed in order to do these calculations are on the order of 100 km horizontally, the vertical height is often 1 km and they do the calculations every 30 minutes or so. As a result, the models cannot simulate clouds. Instead the climate modelers develop parameters to project the effect of global warming on clouds. That single parametrization is a big enough driver of climate that this model component alone could dominate the GCM projections. This uncertainty is well understood in climate science by those who have worked with these models. However, the problems with parameterization is not well understood and its ramifications on the policy decisions is poorly understood by most of those who advocate eliminating fossil fuel use.
Unfortunately, New York State only invokes “science” when it is consistent with their pre-conceived notions. As a result, the points made by Dibble and Koonin will likely be ignored.