In this post I explain why I think that your direct experience should guide your opinion on global warming climate science. You may not be a climate scientist but your personal experiences enable you to judge the certainty of the climate claims popularly heard.
Update November 1, 2019: Added a link at the end to a post about the reliability of extended forecasts
The reason that we hear that there is an inevitable, imminent climate emergency is because of the greenhouse effect. But how do we observe it in the atmosphere? All things being equal, if you know whether it is warmer or colder in the morning after a clear night then you understand the impact of the greenhouse effect. Of course, the answer is it is colder after a clear night. Simply put, when something, in this case clouds, reduces the amount of heat loss (long wave radiation) from the surface and atmosphere, then the temperature does not cool as much, so it is colder after a clear night than a cloudy night.
There are a couple of ramifications of what you already know about this greenhouse effect fact. On clear nights cooling can occur at about 3.4 deg F an hour while on an overcast night cooling is only about 0.5 deg F per hour. Global average temperature was on the order of 2.5 deg F warmer in 2017 than in 1850. If all the warming since 1850 was due to greenhouse gases, then that warming is less than one hour of a cloudy night as opposed to a clear night. Therefore, clouds have a much stronger effect on temperature than greenhouse gases. The other point is that the greenhouse gas effect is stronger at night than during the day so nights are warming faster than days. Keep this in mind when you hear that climate change is going to cause much hotter day time temperatures. The reality is that the average is going up more because the minimum temperature is going up rather than because the maximum temperature is going up.
Predictions of a climate emergency are based on climate prediction models. Remember weather is what we feel over short periods and climate is how the atmosphere acts over longer periods of time, i.e., decades. Observant weather-wise people understand the uncertainty of forecasts for different time periods. Obviously, a 24-hour forecast is more reliable than a seven-day forecast. You know that longer term weather forecasts are not as reliable because you have observed that. The fact is that the physical relationships for forecasting weather and climate are the same. There are differences but the inescapable conclusion is that climate forecasts for one hundred years from now are much less reliable than weather forecasts.
Although people like to say that the weather forecasting profession is the only one that lets you be wrong much of the time and still have a job, the reality is that weather forecasts have improved markedly over time. When I graduated in 1976 with a master of science degree in meteorology, three to five-day forecasts were much less accurate than they are today. In no small part that is because weather forecasters are constantly verifying their predictions against observations. If the forecast is radically wrong then the data are re-evaluated and the modeling parameters are reviewed. Testing a new modeling variation with the data from the period when the old model forecast failed to test improvements and then implementing the revised modeled is a constant process. Obviously, a 100-year climate forecast cannot be tested the same way. It is just not possible to improve climate models much because they cannot be tested frequently enough to make a lot of improvements.
Another aspect of forecasting that observant folks understand is the effect of clouds on forecast reliability and usefulness. Consider the uncertainty when the forecast is for scattered showers. You know that you may get rain or just as likely may not and if your outdoor activity depends on dry weather that means a lot. For numerous reasons it is not possible under many conditions to predict exactly when and where a shower may pop up. The primary reason is that cloud formation is a process that takes place over a small spatial-scale – yards instead of miles. Weather forecast models can incorporate the factors that cause clouds and precipitation into the predictions but not the small-scale factors that cause them at a specific location and time. Residents of Upstate New York are very familiar with the forecast that lake-effect snow is going to occur “north of the Thruway”. Even though forecasters run finer-scale models that are limited to areas immediately adjacent to the Great Lakes, they still can only predict that somewhere in that area there will be a snow band but not exactly where.
There are very serious implications of clouds on the climate forecasting models. Because climate models have to predict over the entire globe, none of the physical processes that create clouds are incorporated into the models. Instead the models simulate clouds by parameters which, to be kind, is simply the expert opinion of the model developer. Don’t believe me? Here is what Nakamura Mototaka says in Confessions of a climate scientist:
“Clouds are represented with parametric methods in climate models. Are those methods reasonably accurate? No. If one seriously studies properties of clouds and processes involved in cloud formation and dissipation, and compare them with the cloud treatment in climate models, one would most likely be flabbergasted by the perfunctory treatment of clouds in the models. The parametric representations of clouds are ad hoc and are tuned to produce the average cloud cover that somewhat resembles that seen in the current climate. Can we, or should we, expect them to simulate the cloud coverage and properties in the “doubled atmospheric carbon dioxide” scenario with reasonable accuracy? No.”
I have described three aspects of global warming climate science that observant folks basically understand based on their personal experience. We know that clouds cause great differences in temperatures. Clearly weather forecast models that can be tested are more reliable than climate prediction models that cannot be tested for the relevant forecast period. Even though weather forecast models have improved we know that they still don’t do as well as we would like for clouds and precipitation.
This all leads to the implication of the fact that the climate models do not do a credible job with clouds. We all know that clouds have a big effect on the temperatures we observe. If the climate models that cannot be tested do not simulate clouds correctly, why should we have much faith in the projections of inevitable, imminent climate emergency from those climate models?
I believe we should consider the results of climate models the same way we treat a forecast for a slight chance of scattered showers. Based on our experiences we know that there are a range of potential outcomes for that forecast. Clearly, those who claim that there is an inevitable, imminent climate catastrophe are stretching credibility. While nothing here can lead to the conclusion that a catastrophic outcome is impossible, the uncertainty surely dictates that our response be carefully crafted. While it might seem prudent to act we must not forget Ridley’s Paradox: Economic damage from man-made ‘climate change’ is illusory whereas damage from man-made ‘policies’ to fight the said change is real. Moreover, there is the potential that the current focus on a climate emergency is diverting attention that might be better spent on higher probability issues such as: global pandemics, antibiotic resistance, Carrington events, or, if you worried about truly existential threats with low probabilities, asteroid impacts.
November 1, 2019 Update This post by Dr. Cliff Mass provides good background to our experience that extended forecasts are not reliable.
4 thoughts on “Let Experience be your Guide to Climate Science”
I’m not sure there’s a benefit in terming real economic damage from weather events as “illusory” in order to avoid the prospect of acknowledging that they might, in fact, be evidence of climate change; we can debate causation till the cows come home, but sea levels will likely continue to rise, and polar ice caps continue to melt. Shall we do nothing until all the “t”s are crossed and the “i’s” dotted, or take a gander that some, if not most of what is happening is anthropogenic and, therefore, within our powers to fix? Or shall we dither endlessly in academic squabbles?
Based on your experience you should understand that clouds are critical to climate. If the climate models that cannot be tested do not simulate clouds correctly, why should we have much faith in the projections that claim that “some, if not most of what is happening is anthropogenic”. If that claim is not true then why should we be doing something. Importantly for those who insist that we should do something what do you want to do?
In the rush to do “something”, New York has Climate Leadership and Community Protection Act (CLCPA) legislation that I estimate will require development of 11,395 MW of residential solar, 16,117 MW of utility-scale solar, 18,457 MW of on-shore wind, and 16,363 MW of off-shore wind. For residential solar if you assume that you need 66 square feet to generate 1kW of solar energy that means that nearly 27 square miles of residential roofs would have to be covered by over 364.6 million solar panels to meet the 11,395 MW assumption. Using a recent solar farm application as a basis 176 square miles will be needed to meet the 16,117 MW of utility scale solar output assumption. I have projected that the 3,845 4.8 MW on-shore wind turbines will be needed to meet 18,457 MW output assumption. For offshore wind I estimate 1,604 10.2 MW wind turbines would be needed to meet the 16,363 MW output assumption. The environmental cost of these sprawling, bird and bat chopping installations has to be significant.
On the other hand, if New York does actually eliminate its GHG emissions the benefits will be immeasurable. The ultimate impact of the CLCPA 100% reduction of 218.1 million metric tons on projected global temperature rise would be a reduction, or a “savings,” of approximately 0.0032°C by the year 2050 and 0.0067°C by the year 2100. One way to give you an idea of how small this temperature change is to consider changes with elevation and latitude. Generally, temperature decreases three (3) degrees Fahrenheit for every 1,000 foot increase in elevation above sea level. The projected temperature difference is the same as going down 27 inches. The general rule is that temperature changes three (3) degrees Fahrenheit for every 300 mile change in latitude at an elevation of sea level. The projected temperature change is the same as going south two thirds of a mile.
In conclusion I don’t believe that any of the CLCPA renewable energy developments will provide any substantive environmental benefits. On the other hand, there will be significant environmental impacts for the vast amounts of wind and solar facilities required. Worst of all those developments will require enormous sums of money that could be used for things that society might actually benefit from including making society more resilient to economic damage from weather events, sea-level rise, and ice caps melting that will occur with or without anything done by going all in on today’s renewable energy technology.