Statistical tests of the hypothesis that iron fertilization depletes primary productivity outside fertilized regions?

[James Bowery]

Ocean iron fertilization is increasingly being considered as an approach to geoengineering.  So there _should_ be increasing data-driven (say Granger Causality) testing of hypotheses regarding externalities utilizing.  Are there?

I recall back in the 1990s reading about concerns that iron fertilization in one place could, by causing biomass production there, deplete nutrients that would ordinarily have supported ecosystems to which those nutrients would otherwise flow.  

It seems to me these concerns should, by now (nearly 30 years later), have resulted in some studies of natural iron fertilization events, such as dust storms in the Sahara in some years, and absence of such storms in other years.

Were there subsequent decreases of primary productivity in areas not fertilized by the Sahara dust when the fertilized areas increased in primary productivity?  During years when the Sahara dust was reduced, hence iron fertilization was reduced, was there an increase in primary productivity in areas outside those that experience an increase during years with iron fertilization from Sahara dust storms?

Has such ecological research been done regarding any natural sources of iron fertilization of any part of the ocean?

There is a wealth of ocean chlorophyll data spanning decades.

[Chris Vivian]

James,

 

As I understand it, there are 2 cases for the problem with the issue of nutrient robbing:

1. Direct iron fertilization of surface waters – Surface waters do not remain at the surface permanently but are subject to the global current systems i.e., the AMOC (https://en.wikipedia.org/wiki/Atlantic_meridional_overturning_circulation) and the geostrophic currents (https://www.britannica.com/science/ocean-current/Thermohaline-circulation) . This means that those waters will likely be subducted at some point and transported at depth to be upwelled at some remote location after a long time. That could be up to hundreds of years later and that is when the nutrient robbing effect will be felt.
2. Fertilization of surface waters by upwelling from beneath the surface mixed layer of waters with iron and macro nutrients – This is essentially the same as above from the point the surface waters are subducted.

 

Consequently, given the timescales involved, it is impractical to study nutrient robbing other than by modelling and, given the present understanding of ocean currents at a detailed level, this is subject to large uncertainties.

 

You asked “Has such ecological research been done regarding any natural sources of iron fertilization of any part of the ocean?” The answer is yes, there have been several studies – see these papers:

 

Blain, S. et al. (2008) Effect of natural iron fertilization on carbon sequestration in the Southern Ocean, Nature, 446, 1070–1074, https://doi.org/10.1038/nature05700.

Blain, S. et al (2008) Distribution of dissolved iron during the natural iron-fertilization experiment KEOPS (Kerguelen Plateau, Southern Ocean), Deep-Sea Res. Pt. II, 55, 594–605, https://doi.org/10.1016/j.dsr2.2007.12.028.

Blain, S. et al. (2015)  Distributions and stoichiometry of dissolved nitrogen and phosphorus in the iron-fertilized region near Kerguelen (Southern Ocean), Biogeosciences, 12, 623–635, https://doi.org/10.5194/bg-12-623-2015.

Gerringa, L. J. A. et al. (2012)  Iron from melting glaciers fuels the phytoplankton blooms in Amundsen Sea (Southern Ocean): Iron biogeochemistry, Deep-Sea Res. Pt. II, 71–76, 16–31, https://doi.org/10.1016/j.dsr2.2012.03.007.

Morris, P. J. and Charette, M. A. (2013) A synthesis of upper ocean carbon and dissolved iron budgets for Southern Ocean natural iron fertilisation studies, Deep-Sea Res. Pt. II, 90, 147–157, https://doi.org/10.1016/j.dsr2.2013.02.001 .

Pollard, R. T. et al. (2009) Southern Ocean deepwater carbon export enhanced by natural iron fertilization, Nature, 457, 577–580, https://doi.org/10.1038/nature07716.

 

Best wishes

 

Chris.

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[Renaud de RICHTER]

The Oceans May Be Our Best Shot at Slowing Climate Catastrophe

https://www.nytimes.com/2023/09/14/opinion/geoengineering-climate-change-ocean.html

To view this discussion on the web visit https://groups.google.com/d/msgid/CarbonDioxideRemoval/06d101d9e6fb%243f520560%24bdf61020%24%40btinternet.com.

[Tom Goreau]

Chris, here’s a great recent paper on blooms caused by subsurface iron fertilization from the Hunga Tonga volcano.

 

Thomas J. F. Goreau, PhD
President, Global Coral Reef Alliance

Chief Scientist, Blue Regeneration SL
President, Biorock Technology Inc.

Technical Advisor, Blue Guardians Programme, SIDS DOCK

37 Pleasant Street, Cambridge, MA 02139

gor...@globalcoral.org
www.globalcoral.org
Skype: tomgoreau
Tel: (1) 617-864-4226 (leave message)

 

Books:

Geotherapy: Innovative Methods of Soil Fertility Restoration, Carbon Sequestration, and Reversing CO2 Increase

http://www.crcpress.com/product/isbn/9781466595392

 

Innovative Methods of Marine Ecosystem Restoration

http://www.crcpress.com/product/isbn/9781466557734

 

Geotherapy: Regenerating ecosystem services to reverse climate change

 

No one can change the past, everybody can change the future

 

It’s much later than we think, especially if we don’t think

 

Those with their heads in the sand will see the light when global warming and sea level rise wash the beach away

 

“When you run to the rocks, the rocks will be melting, when you run to the sea, the sea will be boiling”, Peter Tosh, Jamaica’s greatest song writer

 

 

 

 

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[James Bowery]

On Thu, Sep 14, 2023 at 6:04 AM Chris Vivian <chris....@btinternet.com> wrote:

...

Consequently, given the timescales involved, it is impractical to study nutrient robbing other than by modelling and, given the present understanding of ocean currents at a detailed level, this is subject to large uncertainties.

Right.  This is the essence of scientific inquiry -- placing progressively lower upper bounds on uncertainty which will always be with us and which, when it comes to decisions, will always entail what can only, in all honesty, be called "leaps of faith".  Such is the human condition.  Choosing to not decide is still a leap of faith.

You asked “Has such ecological research been done regarding any natural sources of iron fertilization of any part of the ocean?” The answer is yes, there have been several studies – see these papers:

Taken in context, my question was more specifically about followup studies on what you've termed "nutrient robbing".  (Is that becoming a technical term for the study of hypothesized disruption of nutrients?)

But thank you for the references.  Citations of those references may lead me to statistical tests of the nutrient robbing hypothesis.

[James Bowery]

Speak of the devil:

https://www.nytimes.com/2023/09/14/opinion/geoengineering-climate-change-ocean.html

OPINION

GUEST ESSAY

Iron Dust Could Reverse the Course of Climate Change

Sept. 14, 2023

[James Bowery]

Now that "The Newspaper of Record" has permitted its platform to open the can of worms I fully expect everyone to go insane rather than taking seriously the scientific challenge of applying the vast quantities of sensor data, raw information processing power and human intelligence to modeling the causal structure of global ecology.

What it comes down to is this:

The Algorithmic Information Criterion for model selection has been known to be the optimal one since the 1960s, but its lack of popularity among scientists combined with the inconvenience of applying it to resolving scientific controversies over causality in complex systems has deprived the world of a fundamental advance in the scientific method applicable under Moore's Law's explosion of information processing power.

The way it would work is simply this:

Let otherwise-sane scientists, who are going insane because of some hot topic in complex systems modeling, submit specific sensor datasets to be included in a unified corpus.  Then challenge the scientific community to come up with the smallest executable archive of said unified dataset.

Ray Solomonoff proved in the 1960s that if the universe is structured in such a manner as to be predictable by the application of computation, that the most-predictive data-driven model is the one embodied by the smallest executable archive of all of the data in evidence.

THAT WAS OVER A HALF CENTURY AGO DURING WHICH DATA AND INFORMATION PROCESSING HAS EXPLODED.

I really feel like the character played by Jane Curtin in "Theodoric of York: Medieval Barber" except my outrage is better expressed as "You've killed my entire planet!"

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[James Bowery]

A baby-step in the direction of sane (aka data-driven) models of global ecology is the following recent paper.  There are two levels of confusion to overcome in understanding this baby-step:  

1) The Algorithmic Information Criterion for model selection is independent of whether the model is computer generated, as in this paper's application of machine learning, or human generated, as in the traditional practice of science.

2) This paper's model selection criterion is, like all statistical information criteria, a "pragmatic" degeneration of the Algorithmic Information Criterion.  It is inconvenient to apply the most principled model selection criterion, so people just thoughtlessly apply less principled information criteria without understanding that is what they are doing.

A Multi-Mode Convolutional Neural Network to reconstruct satellite-derived chlorophyll-a time series in the global ocean from physical drivers

Time series of satellite-derived chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass), continuously generated since 1997, are still too short to investigate the low-frequency variability of phytoplankton biomass (e.g. decadal variability). Machine learning models such as Support Vector Regression (SVR) or Multi-Layer Perceptron (MLP) have recently proven to be an alternative approach to mechanistic ones to reconstruct Chl synoptic past time-series before the satellite era from physical predictors. Nevertheless, the relationships between phytoplankton and its physical surrounding environment were implicitly considered homogeneous in space, and training such models on a global scale does not allow one to consider known regional mechanisms. Indeed, the global ocean is commonly partitioned into biogeochemical provinces (BGCPs) into which phytoplankton growth is supposed to be governed by regionally-”homogeneous” processes. The time-evolving nature of those provinces prevents imposing a priori spatially-fixed boundary constraints to restrict the learning phase. Here, we propose to use a multi-mode Convolutional Neural Network (CNN), which can spatially learn and combine different modes, to globally account for interregional variabilities. Each mode is associated with a CNN submodel, standing for a mode-specific response of phytoplankton biomass to the physical forcing. Beyond improving performance reconstruction, we show that the different modes appear regionally consistent with the ocean dynamics and that they may help to get new insights into physical-biogeochemical processes controlling phytoplankton spatio-temporal variability at global scale.

PS:  I did download their software and datasets available via their github repository, but my GPU doesn't have enough VRAM to reproduce their paper's results.

[Ronal Larson]

James:

I’m glad you are keeping this topic alive.  Thanks.

 There is a more recent approach to topics like this than Solomonoff.  See Wiki on OTA - the US Congress’ Office of Technology Assessment (which died in 1994).  Another cite is

          http://independentpoliticalreport.com/2010/06/nader-proposes-reviving-congressional-office-of-technology-assessment/

TA is still active in other countries.   Iron fertilization would seem to be a topic perfect for the TA methodology (this being inherently political).

Ron

(ps.  In 1974, on sabbatical. I was about employee #10 for OTA and worked on its first TA. Now working on biochar - a potential user of ocean biomass)

 

On Sep 16, 2023, at 8:21 AM, James Bowery <jabo...@gmail.com> wrote:

Now that "The Newspaper of Record" has permitted its platform to open the can of worms I fully expect everyone to go insane rather than taking seriously the scientific challenge of applying the vast quantities of sensor data, raw information processing power and human intelligence to modeling the causal structure of global ecology.

What it comes down to is this:

The Algorithmic Information Criterion for model selection has been known to be the optimal one since the 1960s, but its lack of popularity among scientists combined with the inconvenience of applying it to resolving scientific controversies over causality in complex systems has deprived the world of a fundamental advance in the scientific method applicable under Moore's Law's explosion of information processing power.

The way it would work is simply this:

Let otherwise-sane scientists, who are going insane because of some hot topic in complex systems modeling, submit specific sensor datasets to be included in a unified corpus.  Then challenge the scientific community to come up with the smallest executable archive of said unified dataset.

Ray Solomonoff proved in the 1960s that if the universe is structured in such a manner as to be predictable by the application of computation, that the most-predictive data-driven model is the one embodied by the smallest executable archive of all of the data in evidence.

THAT WAS OVER A HALF CENTURY AGO DURING WHICH DATA AND INFORMATION PROCESSING HAS EXPLODED.

I really feel like the character played by Jane Curtin in "Theodoric of York: Medieval Barber" except my outrage is better expressed as "You've killed my entire planet!"

On Sat, Sep 16, 2023 at 9:03 AM James Bowery <jabo...@gmail.com> wrote:

Speak of the devil:

https://www.nytimes.com/2023/09/14/opinion/geoengineering-climate-change-ocean.html

OPINION

GUEST ESSAY

Iron Dust Could Reverse the Course of Climate Change

Sept. 14, 2023

On Wednesday, September 13, 2023 at 5:03:58 PM UTC-5 James Bowery wrote:

Ocean iron fertilization is increasingly being considered as an approach to geoengineering.  So there _should_ be increasing data-driven (say Granger Causality) testing of hypotheses regarding externalities utilizing.  Are there?

I recall back in the 1990s reading about concerns that iron fertilization in one place could, by causing biomass production there, deplete nutrients that would ordinarily have supported ecosystems to which those nutrients would otherwise flow.  

It seems to me these concerns should, by now (nearly 30 years later), have resulted in some studies of naturaliron fertilization events, such as dust storms in the Sahara in some years, and absence of such storms in other years.

Were there subsequent decreases of primary productivity in areas not fertilized by the Sahara dust when the fertilized areas increased in primary productivity?  During years when the Sahara dust was reduced, hence iron fertilization was reduced, was there an increase in primary productivity in areas outside those that experience an increase during years with iron fertilization from Sahara dust storms?

Has such ecological research been done regarding any natural sources of iron fertilization of any part of the ocean?

There is a wealth of ocean chlorophyll data spanning decades.

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[James Bowery]

On Sat, Sep 16, 2023, 11:24 AM Ronal Larson <rongre...@comcast.net> wrote:

James:

I’m glad you are keeping this topic alive.  Thanks.

 There is a more recent approach to topics like this than Solomonoff.  

You could not be more wrong. The Office of Technology Assessment never understood the algorithmic information criterion.  I had to work with a founder of the Department of Energy's Energy Information Administration to get him to understand. And this guy was the guy who funded the Revival of artificial neural network machine learning. He founded the diagony's Institute precisely because of the fact that the OTA had been disbanded.

You obviously know nothing about Solomonoff.

[James Bowery]

Sorry if I come off as a bit short but people keep trying to go back to the vulnerability of regulatory capture by Bad actors in the global economy. That vulnerability is the argument surface over various causal models which is permitted to remain large because of the wide array of information criteria for model selection. That wide array only exists because everyone is being lazy about their principles. If you want a government agency to be honest you have to force it to adopt the most objective Criterion available so there is no political wiggle room for Bad actors. If you force it to adopt the lossless compression Criterion which is a vernacular way of describing algorithmic information you will have a lot friendlier audience among republicans. If you want to recreate something like the office of Technology assessment you need to deal with reality.

[Kevin Wolf]

There are many problems with attempting to use modeling to predict long term possible negative impacts of naturally or artificially occurring ocean iron fertilization that stimulates phytoplankton blooms. The biggest flaw appears to be the inability to include in the models how nitrogen returns to surface waters after phytoplankton consumes the nutrients that are there initially.

Soon after an OIF event triggers a bloom, the nitrogen should be consumed and the bloom should die. But often the bloom continues.  Diazotrophs fix nitrogen and feed the bloom. Fauna induced upwellings bring nutrients from the deep to the surface.  (see https://www.sciencedirect.com/science/article/pii/S0308597X23003214).  Defecation near the surface provides nutrients.  How does "nutrient robbing" modeling account for how nature replenishes nitrogen?  

The hypothesis that somehow an area in the ocean is depleted of its nitrogen, that layer of water sinks and resurface later to "rob" an area of nutrients decades later seems to be something we really shouldn't be worrying about.  If there was evidence that random, naturally occurring OIF events were harmfully "robbing" sections of the ocean of their nutrients than it would be reasonable to be conerned about this.  But there is nothing in the literature that I know of that shows that nutrient robbing occurs or that it is harmful if it does occur.  Even if such an event is possible, how often could it happen if we don't see such problems occurring now with naturally induced phytoplankton blooms?

The problem with modeling (e.g. MIT's modeling about the danger of  possible nutrient robbing by OIF) is that it causes environmental groups and others to shun OIF research.  I don't think that is what the modelers want to happen, but that is a result of the perceived massive harm their modeling indicates could result from OIF experiments. We are working on introducing a five year funding bill to bring $33M per year to OIF field research but there is opposition to the bill because modeling and other peer reviewed papers are intepreted by the environmental community to indicate OIF is too risky to even research (see the Science Direct paper above).

Scientists harm science and climate restoration efforts when they emphasize potential problems that are not based in what is observed in nature nor in any past field experiments. Scientists have a moral and ethical obligation to not let their hypothetical modeling of potential problems stop work on solving real problems like how to effectively and harmlessly use ocean iron fertilization to sequester carbon to improve the health of our oceans and fisheries. The world is on fire and too many scientists are harming the efforts to put out the fire of climate change with their hypothetical modeling of the super complicated world of life in the ocean.

Kevin Wolf, Co-chair

Ocean Iron Fertilization Alliance

kevin...@gmail.com

[Tom Goreau]

Your comment below is a false mystery:

 

Soon after an OIF event triggers a bloom, the nitrogen should be consumed and the bloom should die. But often the bloom continues. 

 

The bloom continues as long as the nitrogen and phosphorus are internally remineralized and recycled within the photic zone before finally taking a deep dump to the bottom.

 

Gordon Riley was the first to show this that the carbon wheel could spin many, many times for each input of new nitrogen and phosphorus from upwelling based on year round field work on phytoplankton blooms at Yale in the late 1940s and later at Dalhousie.

 

Thomas J. F. Goreau, PhD
President, Global Coral Reef Alliance

Chief Scientist, Blue Regeneration SL
President, Biorock Technology Inc.

Technical Advisor, Blue Guardians Programme, SIDS DOCK

37 Pleasant Street, Cambridge, MA 02139

gor...@globalcoral.org
www.globalcoral.org
Skype: tomgoreau
Tel: (1) 617-864-4226 (leave message)

 

Books:

Geotherapy: Innovative Methods of Soil Fertility Restoration, Carbon Sequestration, and Reversing CO2 Increase

http://www.crcpress.com/product/isbn/9781466595392

 

Innovative Methods of Marine Ecosystem Restoration

http://www.crcpress.com/product/isbn/9781466557734

 

Geotherapy: Regenerating ecosystem services to reverse climate change

 

No one can change the past, everybody can change the future

 

It’s much later than we think, especially if we don’t think

 

Those with their heads in the sand will see the light when global warming and sea level rise wash the beach away

 

“When you run to the rocks, the rocks will be melting, when you run to the sea, the sea will be boiling”, Peter Tosh, Jamaica’s greatest song writer

 

 

 

 

 

To view this discussion on the web visit https://groups.google.com/d/msgid/CarbonDioxideRemoval/7804f0a2-84f8-4ffc-a840-eb92e2e005adn%40googlegroups.com.

[Ken Caldeira]

Perhaps this article by Tagliabue and colleagues can add to the discussion:

https://onlinelibrary.wiley.com/doi/10.1111/gcb.16854

Ocean iron fertilization may amplify climate change pressures on marine animal biomass for limited climate benefit

, , , , , 

First published: 06 July 2023

 

https://doi.org/10.1111/gcb.16854

Alessandro Tagliabue and Benjamin S. Twining contributed equally.

PDF

 

Abstract

Climate change scenarios suggest that large-scale carbon dioxide removal (CDR) will be required to maintain global warming below 2°C, leading to renewed attention on ocean iron fertilization (OIF). Previous OIF modelling has found that while carbon export increases, nutrient transport to lower latitude ecosystems declines, resulting in a modest impact on atmospheric CO2. However, the interaction of these CDR responses with ongoing climate change is unknown. Here, we combine global ocean biogeochemistry and ecosystem models to show that, while stimulating carbon sequestration, OIF may amplify climate-induced declines in tropical ocean productivity and ecosystem biomass under a high-emission scenario, with very limited potential atmospheric CO2 drawdown. The ‘biogeochemical fingerprint’ of climate change, that leads to depletion of upper ocean major nutrients due to upper ocean stratification, is reinforced by OIF due to greater major nutrient consumption. Our simulations show that reductions in upper trophic level animal biomass in tropical regions due to climate change would be exacerbated by OIF within ~20 years, especially in coastal exclusive economic zones (EEZs), with potential implications for fisheries that underpin the livelihoods and economies of coastal communities. Any fertilization-based CDR should therefore consider its interaction with ongoing climate-driven changes and the ensuing ecosystem impacts in national EEZs.

Ken Caldeira

Senior Scientist (Emeritus)

Carnegie Institution for Science

Dept of Global Ecology

260 Panama St, Stanford CA 94305 USA

+1 650 704 7212 kcal...@carnegiescience.edu

https://climate-energy.org/

LinkedIn

Senior Scientist, Breakthrough Energy:https://breakthroughenergy.org/our-team/ken-caldeira/

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[Michael Hayes]

James, 

You asked about natural OIF events to help model OIF. Below is one OIF study that did just that:

Southern Ocean deep-water carbon export enhanced by natural iron fertilization

https://scholar.google.com/scholar?q=confining+Ocean+Iron+fertilization&hl=en&as_sdt=0&as_vis=1&oi=scholart#d=gs_qabs&t=1694890535832&u=%23p%3DxzCuYpx1tPQJ

Best regards 

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[Chris Vivian]

Kevin,

 

You should also take a look at this paper by Eelco Rohling and particularly the section ‘Debunking Frequently Encountered Statements/Arguments’ towards the end of the paper:

Marine methods for carbon dioxide removal: fundamentals and myth-busting for the wider community - https://academic.oup.com/oocc/article/3/1/kgad004/7135823

 

The 6 statements covered are:

1. Oceanic CO2 uptake with changing temperature may be calculated simply with physical solubility arguments.
2. Carbonate formation should be promoted because it causes carbon drawdown.
3. Ocean iron fertilization will draw down carbon and store it in increased fish populations (which are commercially interesting).
4. Ocean iron fertilization has only positive (enriching) side-effects.
5. Enhanced primary production will be buried in sediments without major detrimental impacts.
6. Impacts of regionally applied methods in the ocean can be confined to that region.

 

By the way, the Ocean Iron Fertilization Alliance website appears to be infected with a virus.

 

Chris.

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[Kevin Wolf]

Thank you James and Ken for posting these papers. It is unethical to publish hypothetical modeling that shuts down important research (e.g. OIF field experiments) if those models aren't backed up with some real evidence that the predicted harm could actually occur.  There are so many naturally occurring OIF events that should deplete nutrients in an area of the ocean, surely the researchers can find evidence where OIF induced snutrient depleted area of the ocean have created harm to the fisheries in other areas of the ocean decades later.  Show the evidence or rescind the paper.

The Southern Ocean Deep Carbon Export phenomenon certainly must be robbing other areas of the ocean of its nutrients. Or maybe the nutrients are  being restored through nitrogen fixing phytoplankton, upwelling or something else.  How long has this phenomenon been occurring? When are the expected negative impacts suppose to show up?  Surely the modelers can use this source or  volcanic eruptions or unusual aeolean  dust and fire ash events (e.g. Australia and Canada) to see what happens when iron is naturally added to the ocean. There are many events from 20-50 years ago that they should be able to use to test their modeling on. Show us that the model has a statistically valid accuracy in such predictions, and then publish your findings. Don't produce scary headlines without proof. Modeling without validation is not proof.

My. concern is that certain PhD's are so driven to publish papers that they use badly construed modeling to do so.  And in the process they harm the efforts to fund real experiments that would give the modelers the data that they need to create accurate models.  They harm the efforts to restore our climate and reverse climate change.

Kevin Wolf

kevin...@gmail.com

[Renaud de RICHTER]

Also of interest:

• Ryan-Keogh, Thomas J., et al. "Multidecadal trend of increasing iron stress in Southern Ocean phytoplankton." Science 379.6634 (2023): 834-840. https://www.science.org/doi/10.1126/science.abl5237
• (Comment:) Iron shortage threatens microbes key to food chain in Southern Ocean, https://www.science.org/content/article/iron-shortage-threatens-microbes-key-food-chain-southern-ocean
• Smetacek, Victor, et al. "Deep carbon export from a Southern Ocean iron-fertilized diatom bloom." Nature 487.7407 (2012): 313-319. https://www.nature.com/articles/nature11229
  

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[Jim Baird]

PhD's are so driven to publish papers that they use badly construed modeling to do so.  And in the process they harm the efforts to fund real experiments that would give the modelers the data that they need to create accurate models.  They harm the efforts to restore our climate and reverse climate change.

 

Kevin, I believe this is exactly what the GESAMP did when it relied on the  2015 paper  be Kwiatkowski et al. to rule out Thermodynamic Geoengineering claiming to cool surface waters could effectively

reduce warming associated with climate change but implemented at a large scale such effects would be temporary, regionally heterogeneous and present the type of termination risks usually associated with solar  geoengineering approaches. Large scale deployment of OTEC heat pipes for purposes of thermodynamic geoengineering would be potentially disruptive to the marine environment considering that, by definition, it would significantly reduce sea surface temperatures on a regional scale while having all the same localized environmental impacts as conventional OTEC.

 

Which is patently false.  The Kwiatkowski paper modelled a vertical diffusivity in the top 1000 m of the water column at a rate of 60 cm2 s-1. Whereas  Thermodynamic Geoengineering would actually upwell heat, not water, at a rate of 1 cm/day. In other words, over less than 1//5,000,000 of the rate of perturbation modelled.

 

IS IT ANY WONDER SHAKING UP THE TOP 1000 METERRS OF THE WATER COLUMN THIS VIGOROUGSLY WOULD RESULT 50 YEARS LATER ON IN THE WARMING OF THE AMTOSPHERE. IT WOULD EFFECTIVELY RELEASE ALL OF THE CO2 FROM THAT LAYER INTO THE ATMOSPHREE.

 

Furthermore the authors of this paper where admonitioned in a paper An Evaluation of the Large-Scale Implementation of Ocean Thermal Energy Conversion (OTEC) Using an Ocean General Circulation Model with Low-Complexity Atmospheric Feedback Effects by Jia et al that “Kwiatkowski et al. used a fully coupled (atmosphere, land, ocean and sea ice) model, the Community Earth System Model (CESM), to explore the consequences of boosting the background vertical diffusivity of the top 1000 m in the ocean by a factor of 600. They argued that the resulting disruption of the thermocline from such greatly enhanced mixing could be regarded as a proxy for the large-scale effects of technologies such as OTEC, which rely on seawater properties from different vertical layers using pipes and pumps. Although OTEC is the first word of the article, the proposed numerical experiments may not be applicable in the context of OTEC. On one hand, the upper-ocean vertical diffusivity is altered everywhere, while OTEC could only be developed in selected tropical areas, over about a third of the whole ocean. Moreover, the magnitude of the imposed upper-ocean vertical diffusivity would preclude the production of OTEC power anywhere since the vertical temperature difference available in the disrupted thermocline is only a few degrees, far shy of the 20 ◦C typically considered for OTEC feasibility.

 

From: carbondiox...@googlegroups.com On Behalf Of Kevin Wolf
Sent: September 17, 2023 12:16 PM
To: Carbon Dioxide Removal <CarbonDiox...@googlegroups.com>
Subject: Re: [CDR] Statistical tests of the hypothesis that iron fertilization depletes primary productivity outside fertilized regions?

 

Thank you James and Ken for posting these papers. It is unethical to publish hypothetical modeling that shuts down important research (e.g. OIF field experiments) if those models aren't backed up with some real evidence that the predicted harm could actually occur.  There are so many naturally occurring OIF events that should deplete nutrients in an area of the ocean, surely the researchers can find evidence where OIF induced snutrient depleted area of the ocean have created harm to the fisheries in other areas of the ocean decades later.  Show the evidence or rescind the paper.

To view this discussion on the web visit https://groups.google.com/d/msgid/CarbonDioxideRemoval/44a114f0-3fb5-4d4d-b8c3-7bf321008cacn%40googlegroups.com.

[James Bowery]

On Sunday, September 17, 2023 at 2:15:51 PM UTC-5 kw...@windharvest.com wrote:

...

The Southern Ocean Deep Carbon Export phenomenon certainly must be robbing other areas of the ocean of its nutrients. Or maybe the nutrients are  being restored through nitrogen fixing phytoplankton, upwelling or something else.  How long has this phenomenon been occurring? When are the expected negative impacts suppose to show up?  Surely the modelers can use this source or  volcanic eruptions or unusual aeolean  dust and fire ash events (e.g. Australia and Canada) to see what happens when iron is naturally added to the ocean. There are many events from 20-50 years ago that they should be able to use to test their modeling on. Show us that the model has a statistically valid accuracy in such predictions, and then publish your findings. Don't produce scary headlines without proof. Modeling without validation is not proof.

At the risk of coming off as picking nits, the natural sciences only reduce uncertainty.  People will rationally want to take out insurance against even low probability losses of large magnitudes.  But on the other hand, there are ethical conflicts of interest among what might be called "insurance salesmen".  

Validating models of causality is a touchstone of science.  A huge problem with the philosophy of science is weakness in the face of systems where experimental controls are impractical to discern causality -- which is most of the real world. We have no "control Earth" to help us discover causality.

Although the Tagliabue paper Ken Caldiera cites describes "experiments" that are computational in nature.  The results are only as valid as is their integration of existing computational models each of which deals with some aspect of the global ecology.  Others will, I'm sure, come along with different integrated models.  Each of these integrated models can be thought of as having a number of "parameters" that are "chosen" with some justification that may or may not be explicit.  There is bound to be controversy over these choices, and there are plenty of conflicts of interest to go around. 

But Tagliabue et al have taken a step toward what I'm describing as an advance in the scientific method based on the Algorithmic Information Criterion for causal model selection, that exploits the explosion in computational capacity and data availability.  When I say "an advance in the scientific method" I mean we have available to us, because of this explosion, an advance in the scientific method on par with the adoption of experimental controls to validate causal models:

If all you have is observational data, and you need to make predictions, the best you can do is compress it into an algorithm that generates that exact data, ie. without loss of any data.  Throwing data out as "noise" or even failing to model it exactly (e.g. summing up squared errors, etc. as an approximation) invites all manner of arguments.  This increases the "argument surface" aka "attack surface" for bad actors even if they mean well.   When you admit those you admit politics, conflicts of interest, etc.  No matter how expensive you think the computer resources are, they are as nothing compared to the costs of permitting human nature to corrupt science.