Experience has been a relatively good teacher in matters of human interactions. I say “relatively” because all of us are limited in running the human experiment. On a planet with seven billion humans, there are just too many variables for inductive thinking. The experiments we have run by interacting with individuals apply only to those individuals, and even they can change the laboratory venue and apparatus for ensuing encounters, and thus, alter the experiment, at any time. Nevertheless, given a choice between interacting on the basis of a personal history with others and advice by any guru, most of us go with the former. Not that the latter doesn’t make sense in his or her self-help book: It’s just that the advice of any guru is a model for action. Models are rather sweeping in design, and that means the modeler had to choose what to include and how to include it; modelers sometimes fudge the facts, also. Scientific models do, however, serve a purpose: They present an overview, a larger context than that afforded by limited experimentation. Yet, for most of us experiment is greater than model. “Out in the field” most people probably rely on what they have witnessed. Experimentation, even in matters social, appears to be as valuable as Richard Feynman said it was: “It doesn’t matter how beautiful your theory is; it doesn’t matter how smart you are. If it doesn’t agree with experiment, it’s wrong.”
And so, the two of us should consider some kind of modeling and corollary experimentation to see whether or not that model holds true. After that, let’s consider why we interact as we do.
You probably are aware that much of the fuss over climate stems from “climate-change models” derived by some pretty smart people with seemingly unlimited funding. If we are dealing with “climate science,” then we should pay some attention to “climate-change modeling” because the ultimate goal of science is some encompassing model that explains whatever—weather, climate, atoms, metabolism—to our permanent satisfaction. All climate-change models can appear, in general, to be reasonable and to predict with some credibility if one accepts the parameters on which they are based. But, as you know without even being a scientist or because of being one, Earth is a complex place with many components that affect climate, some of which lie outside the planet’s surface boundaries (e.g., orbital position and shape, tilt of axis, and solar input) and others that surround us (latitude, ocean currents, albedo, atmospheric composition, mountains, and land-water distribution).
You also know just by running the experiment of your life that some climate predictions from the 1990s were erroneous to some degree, as demonstrated by current conditions that differ from those predictions. The complexity of the planet and the failure of past models makes one wonder whether or not we aren’t seeing in the modeling the same thing we see when computers spit out incorrect information, that is, junk in, junk out. We should all ask: What goes into the modeling of climate? Why do the models differ? What relationship lies between predictions so far and the recent history of temperature and precipitation (the two most significant climate measures)?
First a bit about climate modeling and experiment and then a bit about human modeling.
If you read through the gajillion studies that somehow get related to climate research, you will come across many that focus on plants and their response to temperature and precipitation patterns. That makes considerable sense since we know that palm trees don’t grow on permafrost. So, what, we might ask, do forests tell us about climate? We like trees, don’t we, and we know that they sequester carbon through photosynthesis at the approximate rate of about 2.5 tons per acre per year in a temperate forest and probably more in a tropical rainforest under more rapid growth. With so much sequestration in growth one might think that forests do not release greenhouse gases. But, even though we expect tropical rainforests to increase their storage of carbon as atmospheric carbon dioxide rises, complicated interactions arise. Here are two examples:
Dr. Emma Sayer and others of Cambridge University’s Center for Ecology and Hydrology studied the release of CO2 from rainforest soils in Panama, and, in 2011 reported in Nature Climate Change that an increase in plant growth leads first to an increase in leaf litter, then to an increase in soil carbon followed by an increase in soil microbes that—you guessed it—leads to increased decomposition of leaf litter followed by a consequent release of soil carbon to the atmosphere. And this increase is not accurately accounted for in most global climate change models. Want some more complexity? Throw in a feedback loop: In 2014 Xuhui Wang and others published an article in Nature that strongly suggests that even an increase of a single degree Celsius in tropical rainforest’s average temperature will lead to an additional annual release of more than two tons of carbon dioxide per hectare.** If CO2 in the atmosphere increases because of human activity, does that portend greater plant growth and greater sequestration or further greenhouse gas increases? So, should you plant a forest or cut one down?
The importance of this question lies in how we pattern our behavior and shape our attitudes on the basis of our perceptions and our trust in the objectivity of the scientists who supply models.
Wait! Before you answer the question about planting or clearing a forest, consider a study Stephanie Roe conducted in Puerto Rico to determine whether or not temperature had an effect on the release of carbon from a tropical rainforest. Let’s run with an assumption first: Wouldn’t you think that as temperature rises, bacteria—the great decomposers—become more active? Seems reasonable in light of the two studies by Sayer and Wang: Under increasing temperatures decomposition of forest floor litter should increase, causing a greater release of carbon into the atmosphere? Hey! That’s what I thought. But, not so. Apparently, in Roe’s experiment, higher temperatures meant increased drying of the forest floor litter. The drying, to my amusement, dampened the effect of bacteria. Less moisture, less decomposition, more storage of carbon in the soil.*** I think Feynman would be happy with Roe’s assessment because it serves as an example of his statement about experiment: She said, “We would expect that microbes tend to work faster [under increased temperatures]…What we found is actually it went the other way because moisture was impacted so much.”
We read the IPCC reports and their popularized agenda-driven and watered-down explanations that scream “the sky is falling” as the models predict. Then we read the results of experiments to find the models don’t tell the whole story—or tell the wrong story. Well, maybe in future experiments we’ll uncover information that will enable us to construct models more aligned with verifiable data derived from experimentation.
And while we struggle to demonstrate the validity of mathematical climate models, you, I, and everyone else must daily also deal with models of humanity versus personal experimentation. And that’s why there is more than one kind of psychology. Just as climate models and the scientists who promulgate them serve as tests of trust until we verify by experimentation, so human models, regardless of our assumptions, hypotheses, and derived theories, serve similarly. We know through personal interactions that the only models worth accepting are those based on experimentation. It really doesn’t matter, as Feyman notes, how clever we are, what we think and put in practice in climate science and in our daily lives on the basis of models. All models require some basis in experimentation to be effective and truthful. Models that fail to take into account what we know from experiment always seem to lack some component or parameter that manifests itself later, just as past climate-change models seem to have lacked something that led to faulty predictions.
In both climate science and in life, it seems that we always discover what works and what doesn’t by experimentation. Climate-change modeling has proved to be a very difficult subject with many unknowns, making current models suspect at best. Yes, maybe there will be an approximation that is good enough to serve predictions. But I caution with yet another study on climate. Francis Macdonald recently presented at a meeting of the American Geophysical Union findings about the role Indonesia’s highlands might be playing in the climate game. Apparently, climate models haven’t included the relationship between volcanism, erosion, and carbon sequestration. As Paul Voosen reports, “…Macdonald and his collaborators …found that glacial conditions 90 million and 50 million years ago lined up neatly with the collisions of a chain of island volcanoes in the now-vanished [and tropical] Neo Tethys Ocean with the African and Asian continents. A similar collision some 460 million years ago formed the Appalachians [when they were deep in the tropics]…their uplift matched a 2-million-year-long glaciation.”**** The study seems to imply that the recent 2-million-year-long glaciations and interglacials of the Pleistocene seem to be tied to the same processes that produced those ancient glacial periods. In other words, as Voosen writes, “A hothouse Earth appears to be the planet’s default state, prevailing for three-fourths of the past 500 million years.” We can have all the Paris agreements we want, but nothing we do will match these natural and largely unaccounted for influences missing from climate-change models of the past 30 years. And here’s another angle that has been addressed by other students of climate: Maybe our adding carbon to the atmosphere is actually staving off another glacial advance, just as the movement of tectonic plates and their associated volcanoes seems to have reestablished that default hothouse Earth.
Human interaction appears to be even more complex than climate-change: Just when we think we can model those interactions in our personal histories and apply them to the next person, we discover that there is a virtual forest of complex processes or an increase in erupting emotions that affect interrelated components.
I understand the need for models. They can provide some intellectual security in a confusing world. But they can also mislead when they are not comprehensive enough for us to make valid predictions. At the same time, our reliance on experiment as a check on models leads us to think inductively in an indefinite (or infinite?) universe. And as we know, we can flip a coin a million times without being able to predict whether or not it will come up heads or tails on the million-and-first flip. Macdonald’s model provides yet another possible driver of climate-change and argues for a default warm planet, but it is an earth-bound model that doesn’t account for orbital and solar influences.
Back to the personal: Do you interact with others on the basis of a model? How effective is your current model of human interaction? Are you willing to change the model if experiment shows it to be ineffective?
* Sayer, Emma J, Matthew S. Heard, et al. “Soil carbon release enhanced by increased tropical forest litterfall.” Nature Climate Change. Published online August 14, 2011 at http://www.nature.com/nclimate/journal/v1/n6/full/nclimate1190.html. Accessed January 4, 2019.
** Xuhui Wang, Shilong Piao, Philippe Ciais, Pierre Friedlingstein, Ranga B. Myneni, Peter Cox, Martin Heimann, John Miller, Shushi Peng, Tao Wang, Hui Yang, Anping Chen. “A two-fold increase of carbon cycle sensitivity to tropical temperature Variations. Nature, 2014; DOI: 10.1038/nature12915. Online at http://sites.bu.edu/cliveg/files/2014/01/wang-nature-2014.pdf Accessed January 4, 2019.
***Pontecorvo, Emily. “Climate warming experiment finds unexpected results.” Phys.org. January 4, 2019. Online at https://phys.org/news/2019-01-climate-unexpected-results.html . Accessed day of release.
****Voosen, Paul. “Rise of carbon dioxide-absorbing mountains in tropics may set thermostat for global climate.” Science. December 28, 2018. Online at https://www.sciencemag.org/news/2018/12/rise-carbon-dioxide-absorbing-mountains-tropics-may-set-thermostat-global-climate Accessed January 4, 2018.
And so, the two of us should consider some kind of modeling and corollary experimentation to see whether or not that model holds true. After that, let’s consider why we interact as we do.
You probably are aware that much of the fuss over climate stems from “climate-change models” derived by some pretty smart people with seemingly unlimited funding. If we are dealing with “climate science,” then we should pay some attention to “climate-change modeling” because the ultimate goal of science is some encompassing model that explains whatever—weather, climate, atoms, metabolism—to our permanent satisfaction. All climate-change models can appear, in general, to be reasonable and to predict with some credibility if one accepts the parameters on which they are based. But, as you know without even being a scientist or because of being one, Earth is a complex place with many components that affect climate, some of which lie outside the planet’s surface boundaries (e.g., orbital position and shape, tilt of axis, and solar input) and others that surround us (latitude, ocean currents, albedo, atmospheric composition, mountains, and land-water distribution).
You also know just by running the experiment of your life that some climate predictions from the 1990s were erroneous to some degree, as demonstrated by current conditions that differ from those predictions. The complexity of the planet and the failure of past models makes one wonder whether or not we aren’t seeing in the modeling the same thing we see when computers spit out incorrect information, that is, junk in, junk out. We should all ask: What goes into the modeling of climate? Why do the models differ? What relationship lies between predictions so far and the recent history of temperature and precipitation (the two most significant climate measures)?
First a bit about climate modeling and experiment and then a bit about human modeling.
If you read through the gajillion studies that somehow get related to climate research, you will come across many that focus on plants and their response to temperature and precipitation patterns. That makes considerable sense since we know that palm trees don’t grow on permafrost. So, what, we might ask, do forests tell us about climate? We like trees, don’t we, and we know that they sequester carbon through photosynthesis at the approximate rate of about 2.5 tons per acre per year in a temperate forest and probably more in a tropical rainforest under more rapid growth. With so much sequestration in growth one might think that forests do not release greenhouse gases. But, even though we expect tropical rainforests to increase their storage of carbon as atmospheric carbon dioxide rises, complicated interactions arise. Here are two examples:
Dr. Emma Sayer and others of Cambridge University’s Center for Ecology and Hydrology studied the release of CO2 from rainforest soils in Panama, and, in 2011 reported in Nature Climate Change that an increase in plant growth leads first to an increase in leaf litter, then to an increase in soil carbon followed by an increase in soil microbes that—you guessed it—leads to increased decomposition of leaf litter followed by a consequent release of soil carbon to the atmosphere. And this increase is not accurately accounted for in most global climate change models. Want some more complexity? Throw in a feedback loop: In 2014 Xuhui Wang and others published an article in Nature that strongly suggests that even an increase of a single degree Celsius in tropical rainforest’s average temperature will lead to an additional annual release of more than two tons of carbon dioxide per hectare.** If CO2 in the atmosphere increases because of human activity, does that portend greater plant growth and greater sequestration or further greenhouse gas increases? So, should you plant a forest or cut one down?
The importance of this question lies in how we pattern our behavior and shape our attitudes on the basis of our perceptions and our trust in the objectivity of the scientists who supply models.
Wait! Before you answer the question about planting or clearing a forest, consider a study Stephanie Roe conducted in Puerto Rico to determine whether or not temperature had an effect on the release of carbon from a tropical rainforest. Let’s run with an assumption first: Wouldn’t you think that as temperature rises, bacteria—the great decomposers—become more active? Seems reasonable in light of the two studies by Sayer and Wang: Under increasing temperatures decomposition of forest floor litter should increase, causing a greater release of carbon into the atmosphere? Hey! That’s what I thought. But, not so. Apparently, in Roe’s experiment, higher temperatures meant increased drying of the forest floor litter. The drying, to my amusement, dampened the effect of bacteria. Less moisture, less decomposition, more storage of carbon in the soil.*** I think Feynman would be happy with Roe’s assessment because it serves as an example of his statement about experiment: She said, “We would expect that microbes tend to work faster [under increased temperatures]…What we found is actually it went the other way because moisture was impacted so much.”
We read the IPCC reports and their popularized agenda-driven and watered-down explanations that scream “the sky is falling” as the models predict. Then we read the results of experiments to find the models don’t tell the whole story—or tell the wrong story. Well, maybe in future experiments we’ll uncover information that will enable us to construct models more aligned with verifiable data derived from experimentation.
And while we struggle to demonstrate the validity of mathematical climate models, you, I, and everyone else must daily also deal with models of humanity versus personal experimentation. And that’s why there is more than one kind of psychology. Just as climate models and the scientists who promulgate them serve as tests of trust until we verify by experimentation, so human models, regardless of our assumptions, hypotheses, and derived theories, serve similarly. We know through personal interactions that the only models worth accepting are those based on experimentation. It really doesn’t matter, as Feyman notes, how clever we are, what we think and put in practice in climate science and in our daily lives on the basis of models. All models require some basis in experimentation to be effective and truthful. Models that fail to take into account what we know from experiment always seem to lack some component or parameter that manifests itself later, just as past climate-change models seem to have lacked something that led to faulty predictions.
In both climate science and in life, it seems that we always discover what works and what doesn’t by experimentation. Climate-change modeling has proved to be a very difficult subject with many unknowns, making current models suspect at best. Yes, maybe there will be an approximation that is good enough to serve predictions. But I caution with yet another study on climate. Francis Macdonald recently presented at a meeting of the American Geophysical Union findings about the role Indonesia’s highlands might be playing in the climate game. Apparently, climate models haven’t included the relationship between volcanism, erosion, and carbon sequestration. As Paul Voosen reports, “…Macdonald and his collaborators …found that glacial conditions 90 million and 50 million years ago lined up neatly with the collisions of a chain of island volcanoes in the now-vanished [and tropical] Neo Tethys Ocean with the African and Asian continents. A similar collision some 460 million years ago formed the Appalachians [when they were deep in the tropics]…their uplift matched a 2-million-year-long glaciation.”**** The study seems to imply that the recent 2-million-year-long glaciations and interglacials of the Pleistocene seem to be tied to the same processes that produced those ancient glacial periods. In other words, as Voosen writes, “A hothouse Earth appears to be the planet’s default state, prevailing for three-fourths of the past 500 million years.” We can have all the Paris agreements we want, but nothing we do will match these natural and largely unaccounted for influences missing from climate-change models of the past 30 years. And here’s another angle that has been addressed by other students of climate: Maybe our adding carbon to the atmosphere is actually staving off another glacial advance, just as the movement of tectonic plates and their associated volcanoes seems to have reestablished that default hothouse Earth.
Human interaction appears to be even more complex than climate-change: Just when we think we can model those interactions in our personal histories and apply them to the next person, we discover that there is a virtual forest of complex processes or an increase in erupting emotions that affect interrelated components.
I understand the need for models. They can provide some intellectual security in a confusing world. But they can also mislead when they are not comprehensive enough for us to make valid predictions. At the same time, our reliance on experiment as a check on models leads us to think inductively in an indefinite (or infinite?) universe. And as we know, we can flip a coin a million times without being able to predict whether or not it will come up heads or tails on the million-and-first flip. Macdonald’s model provides yet another possible driver of climate-change and argues for a default warm planet, but it is an earth-bound model that doesn’t account for orbital and solar influences.
Back to the personal: Do you interact with others on the basis of a model? How effective is your current model of human interaction? Are you willing to change the model if experiment shows it to be ineffective?
* Sayer, Emma J, Matthew S. Heard, et al. “Soil carbon release enhanced by increased tropical forest litterfall.” Nature Climate Change. Published online August 14, 2011 at http://www.nature.com/nclimate/journal/v1/n6/full/nclimate1190.html. Accessed January 4, 2019.
** Xuhui Wang, Shilong Piao, Philippe Ciais, Pierre Friedlingstein, Ranga B. Myneni, Peter Cox, Martin Heimann, John Miller, Shushi Peng, Tao Wang, Hui Yang, Anping Chen. “A two-fold increase of carbon cycle sensitivity to tropical temperature Variations. Nature, 2014; DOI: 10.1038/nature12915. Online at http://sites.bu.edu/cliveg/files/2014/01/wang-nature-2014.pdf Accessed January 4, 2019.
***Pontecorvo, Emily. “Climate warming experiment finds unexpected results.” Phys.org. January 4, 2019. Online at https://phys.org/news/2019-01-climate-unexpected-results.html . Accessed day of release.
****Voosen, Paul. “Rise of carbon dioxide-absorbing mountains in tropics may set thermostat for global climate.” Science. December 28, 2018. Online at https://www.sciencemag.org/news/2018/12/rise-carbon-dioxide-absorbing-mountains-tropics-may-set-thermostat-global-climate Accessed January 4, 2018.
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