Levin Interviews Dr. Patrick Michaels On Climate

From Musings from the Chiefio:

 

Fourteen minutes well spent that shows how wrong the “Climate Models” are, and why that matters to all of us due to the EPA “Endangerment Finding” being based 100% on those broken models.

I find it interesting that The Russians have a climate model that works. Wonder if it is open sourced? If anyone knows, or knows how to get a copy, let me know! It would save a lot of time trying to make one that works from the crap that doesn’t…

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The Cooling Rains

Reblogged from Watts Up With That:

Guest Post by Willis Eschenbach

I took another ramble through the Tropical Rainfall Measurement Mission (TRMM) satellite-measured rainfall data. Figure 1 shows a Pacific-centered and an Atlantic-centered view of the average rainfall from the end of 1997 to the start of 2015 as measured by the TRMM satellite.

Figure 1. Average rainfall, meters per year, on a 1° latitude by 1° longitude basis. The area covered by the satellite data, forty degrees north and south of the Equator, is just under 2/3 of the globe. The blue areas by the Equator mark the InterTropical Convergence Zone (ITCZ). The two black horizontal dashed lines mark the Tropics of Cancer and Capricorn, the lines showing how far north and south the sun travels each year (23.45°, for those interested).

There’s lots of interesting stuff in those two graphs. I was surprised by how much of the planet in general, and the ocean in particular, are bright red, meaning they get less than half a meter (20″) of rain per year.

I was also intrigued by how narrowly the rainfall is concentrated at the average Inter-Tropical Convergence Zone (ITCZ). The ITCZ is where the two great global hemispheres of the atmospheric circulation meet near the Equator. In the Pacific and Atlantic on average the ITCZ is just above the Equator, and in the Indian Ocean, it’s just below the Equator. However, that’s just on average. Sometimes in the Pacific, the ITCZ is below the Equator. You can see kind of a mirror image as a light orange horizontal area just below the Equator.

Here’s an idealized view of the global circulation. On the left-hand edge of the globe, I’ve drawn a cross section through the atmosphere, showing the circulation of the great atmospheric cells.

Figure 2. Generalized overview of planetary atmospheric circulation. At the ITCZ along the Equator, tall thunderstorms take warm surface air, strip out the moisture as rain, and drive the warm dry air vertically. This warm dry air eventually subsides somewhere around 25-30°N and 25-30S of the Equator, creating the global desert belts at around those latitudes.

The ITCZ is shown in cross-section at the left edge of the globe in Figure 2. You can see the general tropical circulation. Surface air in both hemispheres moves towards the Equator. It is warmed there and rises. This thermal circulation is greatly sped up by air driven vertically at high rates of speed through the tall thunderstorm towers. These thunderstorms form all along the ITCZ. These thunderstorms provide much of the mechanical energy that drives the atmospheric circulation of the Hadley cells.

With all of that as prologue, here’s what I looked at. I got to thinking, was there a trend in the rainfall? Is it getting wetter or drier? So I looked at that using the TRMM data. Figure 3 shows the annual change in rainfall, in millimeters per year, on a 1° latitude by 1° longitude basis.

Figure 3. Annual change in the rainfall, 1° latitude x 1° longitude gridcells.

I note that the increase in rain is greater on the ocean vs land, is greatest at the ITCZ, and is generally greater in the tropics.

Why is this overall trend in rainfall of interest? It gives us a way to calculate how much this cools the surface. Remember the old saying, what comes down must go up … or perhaps it’s the other way around, same thing. If it rains an extra millimeter of water, somewhere it must have evaporated an extra millimeter of water.

And in the same way that our bodies are cooled by evaporation, the surface of the planet is also cooled by evaporation.

Now, we note above that on average, the increase is 1.33 millimeters of water per year. Metric is nice because volume and size are related. Here’s a great example.

One millimeter of rain falling on one square meter of the surface is one liter of water which is one kilo of water. Nice, huh?

So the extra 1.33 millimeters of rain per year is equal to 1.33 extra liters of water evaporated per square meter of surface area.

Next, how much energy does it take to evaporate that extra 1.33 liters of water per square meter so it can come down as rain? The calculations are in the endnotes. It turns out that this 1.33 extra liters per year represents an additional cooling of a tenth of a watt per square meter (0.10 W/m2).

And how does this compare to the warming from increased longwave radiation due to the additional CO2? Well, again, the calculations are in the endnotes. The answer is, per the IPCC calculations, CO2 alone over the period gave a yearly increase in downwelling radiation of ~ 0.03 W/m2. Generally, they double that number to allow for other greenhouse gases (GHGs), so for purposes of discussion, we’ll call it 0.06 W/m2 per year.

So over the period of this record, we have increased evaporative cooling of 0.10 W/m2 per year, and we have increased radiative warming from GHGs of 0.06 W/m2 per year.

Which means that over that period and that area at least, the calculated increase in warming radiation from GHGs was more than counterbalanced by the observed increase in surface cooling from increased evaporation.

Regards to all,

w.

As usual: please quote the exact words you are discussing so we can all understand exactly what and who you are replying to.

Additional Cooling

Finally, note that this calculation is only evaporative cooling. There are other cooling mechanisms at work that are related to rainstorms. These include:

• Increased cloud albedo reflecting hundreds of watts/square meter of sunshine back to space

• Moving surface air to the upper troposphere where it is above most GHGs and freer to cool to space.

• Increased ocean surface albedo from whitecaps, foam, and spume.

• Cold rain falling from a layer of the troposphere that is much cooler than the surface.

• Rain re-evaporating as it falls to cool the atmosphere

• Cold wind entrained by the rain blowing outwards at surface level to cool surrounding areas

• Dry descending air between rain cells and thunderstorms allowing increased longwave radiation to space.

Between all of these, they form a very strong temperature regulating mechanism that prevents overheating of the planet.

Calculation of energy required to evaporate 1.33 liters of water.

#latent heat evaporation joules/kg @ salinity 35 psu, temperature 24°C

> latevap = gsw_latentheat_evap_t( 35, 24 ) ; latevap

[1] 2441369

# joules/yr/m2 required to evaporate 1.33 liters/yr/m2

> evapj = latevap * 1.33 ; evapj

[1] 3247021

# convert joules/yr/m2 to W/m2

> evapwm2 = evapj / secsperyear ; evapwm2

[1] 0.1028941

Note: the exact answer varies dependent on seawater temperature, salinity, and density. These only make a difference of a couple percent (say 0.1043 vs 0.1028941). I’ve used average values.

Calculation of downwelling radiation change from CO2 increase.

#starting CO2 ppmv Dec 1997

> thestart = as.double( coshort[1] ) ; thestart

[1] 364.38

#ending CO2 ppmv Mar 2015

> theend = as.double( last( coshort )) ; theend

[1] 401.54

# longwave increase, W/m2 per year over 17 years 4 months

> 3.7 * log( theend / thestart, 2)/17.33

[1] 0.0299117

Fake climate science and scientists

Reblogged from Watts Up With That:

Alarmists game the system to enrich and empower themselves, and hurt everyone else

by Paul Driessen

The multi-colored placard in front of a $2-million home in North Center Chicago proudly proclaimed, “In this house we believe: No human is illegal” – and “Science is real” (plus a few other liberal mantras).

I knew right away where the owners stood on climate change, and other hot-button political issues. They would likely tolerate no dissension or debate on “settled” climate science or any of the other topics.

But they have it exactly backward on the science issue. Real science is not belief – or consensus, 97% or otherwise. Real science constantly asks questions, expresses skepticism, reexamines hypotheses and evidence. If debate, skepticism and empirical evidence are prohibited – it’s pseudo-science, at best.

Real science – and real scientists – seek to understand natural phenomena and processes. They pose hypotheses that they think best explain what they have witnessed, then test them against actual evidence, observations and experimental data. If the hypotheses (and predictions based on them) are borne out by their subsequent findings, the hypotheses become theories, rules, laws of nature – at least until someone finds new evidence that pokes holes in their assessments, or devises better explanations.

Real science does not involve simply declaring that you “believe” something, It’s not immutable doctrine. It doesn’t claim “science is real” – or demand that a particular scientific explanation be carved in stone. Earth-centric concepts gave way to a sun-centered solar system. Miasma disease beliefs surrendered to the germ theory. The certainty that continents are locked in place was replaced by plate tectonics (and the realization that you can’t stop continental drift, any more than you stop climate change).

Real scientists often employ computers to analyze data more quickly and accurately, depict or model complex natural systems, or forecast future events or conditions. But they test their models against real-world evidence. If the models, observations and predictions don’t match up, real scientists modify or discard the models, and the hypotheses behind them. They engage in robust discussion and debate.

They don’t let models or hypotheses become substitutes for real-world evidence and observations. They don’t alter or “homogenize” raw or historic data to make it look like the models actually work. They don’t hide their data and computer algorithms (AlGoreRythms?), restrict peer review to closed circles of like-minded colleagues who protect one another’s reputations and funding, claim “the debate is over,” or try to silence anyone who dares to ask inconvenient questions or find fault with their claims and models. They don’t concoct hockey stick temperature graphs that can be replicated by plugging in random numbers.

In the realm contemplated by the Chicago yard sign, we ought to be doing all we can to understand Earth’s highly complex, largely chaotic, frequently changing climate system – all we can to figure out how the sun and other powerful forces interact with each other. Only in that way can we accurately predict future climate changes, prepare for them, and not waste money and resources chasing goblins.

But instead, we have people in white lab coats masquerading as real scientists. They’re doing what I just explained true scientists don’t do. They also ignore fluctuations in solar energy output and numerous other powerful, interconnected natural forces that have driven climate change throughout Earth’s history. They look only (or 97% of the time) at carbon dioxide as the principle or sole driving force behind current and future climate changes – and blame every weather event, fire and walrus death on manmade CO2.

Even worse, they let their biases drive their research and use their pseudo-science to justify demands that we eliminate all fossil fuel use, and all carbon dioxide and methane emissions, by little more than a decade from now. Otherwise, they claim, we will bring unprecedented cataclysms to people and planet.

Not surprisingly, their bad behavior is applauded, funded and employed by politicians, environmentalists, journalists, celebrities, corporate executives, billionaires and others who have their own axes to grind, their own egos to inflate – and their intense desire to profit from climate alarmism and pseudo-science.

Worst of all, while they get rich and famous, their immoral actions impoverish billions and kill millions, by depriving them of the affordable, reliable fossil fuel energy that powers modern societies.

And still these slippery characters endlessly repeat the tired trope that they “believe in science” – and anyone who doesn’t agree to “keep fossil fuels in the ground” to stop climate change is a “science denier.”

When these folks and the yard sign crowd brandish the term “science,” political analyst Robert Tracinski suggests, it is primarily to “provide a badge of tribal identity” – while ironically demonstrating that they have no real understanding of or interest in “the guiding principles of actual science.”

Genuine climate scientist (and former chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology) Dr. Judith Curry echoes Tracinski. Politicians like Senator Elizabeth Warren use “science” as a way of “declaring belief in a proposition which is outside their knowledge and which they do not understand…. The purpose of the trope is to bypass any meaningful discussion of these separate questions, rolling them all into one package deal – and one political party ticket,” she explains.

The ultimate purpose of all this, of course, is to silence the dissenting voices of evidence- and reality-based climate science, block creation of a Presidential Committee on Climate Science, and ensure that the only debate is over which actions to take first to end fossil fuel use … and upend modern economies.

The last thing fake/alarmist climate scientists want is a full-throated debate with real climate scientists – a debate that forces them to defend their doomsday assertions, methodologies, data manipulation … and claims that solar and other powerful natural forces are minuscule or irrelevant compared to manmade carbon dioxide that constitutes less that 0.02% of Earth’s atmosphere (natural CO2 adds another 0.02%).

Thankfully, there are many reasons for hope. For recognizing that we do not face a climate crisis, much less threats to our very existence. For realizing there is no need to subject ourselves to punitive carbon taxes or the misery, poverty, deprivation, disease and death that banning fossil fuels would cause.

Between the peak of the great global cooling scare in 1975 until around 1998, atmospheric carbon dioxide levels and temperatures did rise in rough conjunction. But then temperatures mostly flat-lined, while CO2 levels kept climbing. Now actual average global temperatures are already 1 degree F below the Garbage In-Garbage Out computer model predictions. Other alarmist forecasts are also out of touch with reality.

Instead of fearing rising CO2, we should thank it for making crop, forest and grassland plants grow faster and better, benefitting nature and humanity – especially in conjunction with slightly warmer temperatures that extend growing seasons, expand arable land and increase crop production.

The rate of sea level rise has not changed for over a century – and much of what alarmists attribute to climate change and rising seas is actually due to land subsidence and other factors.

Weather is not becoming more extreme. In fact, Harvey was the first Category 3-5 hurricane to make US landfall in a record 12 years – and the number of violent F3 to F5 tornadoes has fallen from an average of 56 per year from 1950 to 1985 to only 34 per year since then.

Human ingenuity and adaptability have enabled humans to survive and thrive in all sorts of climates, even during our far more primitive past. Allowed to use our brains, fossil fuels and technologies, we will deal just fine with whatever climate changes might confront us in the future. (Of course, another nature-driven Pleistocene-style glacier pulling 400 feet of water out of our oceans and crushing Northern Hemisphere forests and cities under mile-high walls of ice truly would be an existential threat to life as we know it.)

So if NYC Mayor Bill De Blasio and other egotistical grand-standing politicians and fake climate scientists want to ban fossil fuels, glass-and-steel buildings, cows and even hotdogs – in the name of preventing “dangerous manmade climate change” – let them impose their schemes on themselves and their own families. The rest of us are tired of being made guinea pigs in their fake-science experiments.

Paul Driessen is senior policy advisor for the Committee For A Constructive Tomorrow (CFACT) and author of articles and books on energy, environmental and human rights issues.

Adjusting Good Data To Make It Match Bad Data

Reblogged from RealClimateScience.com:

mwr-035-01-0007b.pdf

On election day in 2016, both satellite data sets (UAH and RSS) showed a 15 year long hiatus in global warming, and bore no resemblance to the warming trend being generated by NOAA and NASA.  I captured this image in a November 16, 2016 blog post.

Gavin Schmidt Promises To Resign | The Deplorable Climate Science Blog

This is what the same graph looks like now.

Wood for Trees: Interactive Graphs

In the next image, I overlaid the current RSS graph on the 2016 image.  You can see how RSS was adjusted to match the NASA data.

I predicted this would happen on

Look for the satellite data to be adjusted to bring it into compliance with the fully fraudulent surface temperatures. The Guardian is now working to discredit UAH, so it seems likely that RSS will soon be making big changes – to match the needs of the climate mafia. Bookmark this post.

RSSChanges

Roy Spencer at UAH made the same prediction on January 9, 2017

“I expect there will soon be a revised TLT product from RSS which shows enhanced warming, too.

Here’s what I’m predicting:

1) neither John Christy nor I will be asked to review the paper

2) it will quickly sail through peer review (our UAH V6 paper is still not in print nearly 1 year after submission)

3) it will have many authors, including climate model people and the usual model pundits (e.g. Santer), which will supposedly lend legitimacy to the new data adjustments.

Let’s see how many of my 3 predictions come true.

-Roy”

Wood for Trees: Interactive Graphs

The reason I made this prediction was because Ted Cruz used an RSS graph in a Senate hearing in March of 2015. Carl Mears at RSS then came under intense pressure to make his data match the surface temperature data.

My particular dataset (RSS tropospheric temperatures from MSU/AMSU satellites) show less warming than would be expected when compared to the surface temperatures. All datasets contain errors. In this case, I would trust the surface data a little more because the difference between the long term trends in the various surface datasets (NOAA, NASA GISS, HADCRUT, Berkeley etc) are closer to each other than the long term trends from the different satellite datasets. This suggests that the satellite datasets contain more “structural uncertainty” than the surface dataset.

Ted Cruz says satellite data show the globe isn’t warming

You can see what Mears did to bring his data into compliance. This was his web page in November 2016.

Note that after 1998, the observations are likely to be below the simulated values, indicating that the simulation as a whole are predicting too much warming.

Climate Analysis | Remote Sensing Systems

But under intense pressure,  Mears altered his own data to bring it into compliance.  The large discrepancy became a small discrepancy.

there is a small discrepancy between the model predictions and the satellite observations.

Remote Sensing Systems

The image below overlays Mears’ old graph (V3) on his new one (V4.) It is clear what he did – he  eliminated the blue error interval, and started using the high side of the interval as his temperature.

RSS V3 shows no warming since 2002.

The warming was all created by tampering with the data to eliminate the error interval.

Spreadsheet

The corruption is now complete.  NASA has announced that new satellite data matches their surface temperature data. This was done to keep the President’s Commission on Climate Security from having accurate data to work with.

All government climate data goes through the same transition in support of global warming alarm. The past keeps getting cooler, and recent years keep getting warmer.

NASA 1999   NASA 2016

Government climate agencies appear to be using Orwell’s 1984 as Standard Operating Procedure.

Climate Modellers Waiting for Observations to Catch Up with Their Predictions

Reblogged from Watts Up With That:

Guest essay by Eric Worrall

h/t Dr. Willie Soon; In climate science, when your model predictions are wrong, you wait for the world to correct itself.

New climate models predict a warming surge
By Paul VoosenApr. 16, 2019 , 3:55 PM

For nearly 40 years, the massive computer models used to simulate global climate have delivered a fairly consistent picture of how fast human carbon emissions might warm the world. But a host of global climate models developed for the United Nations’s next major assessment of global warming, due in 2021, are now showing a puzzling but undeniable trend. They are running hotter than they have in the past. Soon the world could be, too.

In earlier models, doubling atmospheric carbon dioxide (CO2) over preindustrial levels led models to predict somewhere between 2°C and 4.5°C of warming once the planet came into balance. But in at least eight of the next-generation models, produced by leading centers in the United States, the United Kingdom, Canada, and France, that “equilibrium climate sensitivity” has come in at 5°C or warmer. Modelers are struggling to identify which of their refinements explain this heightened sensitivity before the next assessment from the United Nations’s Intergovernmental Panel on Climate Change (IPCC). But the trend “is definitely real. There’s no question,” says Reto Knutti, a climate scientist at ETH Zurich in Switzerland. “Is that realistic or not? At this point, we don’t know.”

Many scientists are skeptical, pointing out that past climate changes recorded in ice cores and elsewhere don’t support the high climate sensitivity —nor does the pace of modern warming. The results so far are “not sufficient to convince me,” says Kate Marvel, a climate scientist at NASA’s Goddard Institute for Space Studies in New York City. In the effort to account for atmospheric components that are too small to directly simulate, like clouds, the new models could easily have strayed from reality, she says. “That’s always going to be a bumpy road.”

In assessing how fast climate may change, the next IPCC report probably won’t lean as heavily on models as past reports did, says Thorsten Mauritsen, a climate scientist at Stockholm University and an IPCC author. It will look to other evidence as well, in particular a large study in preparation that will use ancient climates and observations of recent climate change to constrain sensitivity. IPCC is also not likely to give projections from all the models equal weight, Fyfe adds, instead weighing results by each model’s credibility.

Read more: https://www.sciencemag.org/news/2019/04/new-climate-models-predict-warming-surge

It’s nice to learn that the IPCC is considering using observations to constrain model projections.

A simple demo of order and chaos; Climate Models are not so simple

Here’s a fascinating example of oscillating systems.

In this demonstration 15 independent cyclic systems with different periods begin in phase, then watch how the total system departs from being in phase to apparent chaos to split phases and so on.

Now consider this demonstration as a model for all the contributors, big and small, to Earth’s climate–certainly more than the 15 billiard balls depicted here. And put the balls on springs of varying elasticity (permitting varying periods). And then allow the balls to hit each other (adding the third dimension to their oscillation and…..energy transfer).

Try to model and predict that!

In Aftermath of Volcanic Eruption, Photosynthesis Waxes, Carbon Dioxide Wanes

From Scientific American:

By Laura Wright on March 28, 2003

 

Read more from this special report:

A Guide to Volcanoes

In June 1991, when Mt. Pinatubo in the Philippines spewed tons of volcanic ash and gases into the atmosphere, it just so happened that halfway around the world scientists were beginning to obtain good data from carbon dioxide monitors high above the tree canopy in Harvard Forest, outside Boston, Mass. Now, more than a decade later, the measurements taken during the years following the eruption are providing new insight into how atmospheric aerosols affect photosynthesis. The findings, published today in the journal Science, are forcing scientists to rethink the factors that influence the cycling of carbon through the environment, particularly carbon dioxide, a major player in global warming.

 

Within three weeks of the Mt. Pinatubo eruption, the largest volcanic blast of the century, a band of sulfur aerosol had encircled the globe. By early 1992, the volcanic gases and aerosols had diffused through the stratosphere, veiling the earth. During that time, global carbon dioxide levels fell more sharply than any other decline on record. Some scientists suggested that global cooling caused ecosystem respiration to drop, lowering the amount of carbon dioxide emitted into the atmosphere. But Lianhong Gu of Oak Ridge National Laboratory, lead author of the Science report, didn’t think that could be the only explanation.

Gu knew that crop scientists had discovered that plants grow best in diffuse light. When sunlight is too intense, some leaves fall into shadow, unable to photosynthesize, while others bask in the direct beams but will reach a photosynthetic saturation point. Moderate cloud cover and aerosols block direct beams, but allow light to bounce back and forth off water vapor and other molecules, creating a “softer” light that reaches leaves that would otherwise be shaded. As a result, the plants photosynthesize more, using up carbon dioxide in the process. Gu and his collaborators determined that the same principles apply to forest canopies. The Harvard Forest data show that carbon dioxide levels dropped for two years following the eruption at Mt. Pinatubo findings that the scientists suggest represent a worldwide phenomenon given that the eruption had a global atmospheric effect. “Up until now we hadn’t linked aerosols and clouds with carbon studies,” Gu says. “In order to understand atmospheric carbon dioxide concentrations, which affect climate, we have to look at how aerosols and clouds affect the global carbon cycle.”

Predicting heat waves? Look half a world away

Reblogged from Watts Up With That:

[HiFast Note:  This study identifies the Madden-Julian Oscillation (MJO) and correlates one of its phases to California heat waves.  Nothing really new here.  Joe Bastardi has been talking about the MJO for many years.]

charles the moderator /

When thunderstorms brew over the tropics, California heat wave soon to follow

University of California – Davis

An orchard of young trees withstands drought in California's Central Valley in 2014. The ability to predict heat waves in the Central Valley could help better prepare and protect crops and people from the impacts. Credit UC Davis

An orchard of young trees withstands drought in California’s Central Valley in 2014. The ability to predict heat waves in the Central Valley could help better prepare and protect crops and people from the impacts. Credit UC Davis

When heavy rain falls over the Indian Ocean and Southeast Asia and the eastern Pacific Ocean, it is a good indicator that temperatures in central California will reach 100°F in four to 16 days, according to a collaborative research team from the University of California, Davis, and the Asia-Pacific Economic Cooperation (APEC) Climate Center in Busan, South Korea.

The results were published in Advances in Atmospheric Sciences on April 12.

FROM PREDICTION TO PROTECTION

Heat waves are common in the Central California Valley, a 50-mile-wide oval of land that runs 450 miles from just north of Los Angeles up to Redding. The valley is home to half of the nation’s tree fruit and nut crops, as well as extensive dairy production, and heat waves can wreak havoc on agricultural production. The dairy industry had a heat wave-induced economic loss of about $1 billion in 2006, for instance. The ability to predict heat waves and understand what causes them could inform protective measures against damage.

“We want to know more about how extreme events are created,” said Richard Grotjahn, corresponding author on the paper and professor in the UC Davis Department of Land, Air and Water Resources. “We know that such patterns in winter are sometimes linked with areas of the tropics where thunderstorms are enhanced. We wondered if there might be similar links during summer for those heat waves.”

The scientists analyzed the heat wave data from June through September from 1979 to 2010. The data were collected by 15 National Climatic Data Centers stations located throughout the Valley. From these data, the researchers identified 24 heat waves. They compared these instances to the phases of a large, traveling atmospheric circulation pattern called the Madden-Julian Oscillation, or MJO.

The MJO manifests as heavy rain that migrates across the tropical Indian and then Pacific Oceans, and researchers have shown that it influences winter weather patterns.

TROPICAL RAINFALL AND CALIFORNIA

“It’s well known that tropical rainfall, such as the MJO, has effects beyond the tropics,” said Yun-Young Lee of the APEC Climate Center in Busan, South Korea, the paper’s first author. “So a question comes to mind: Is hot weather in the Central California Valley partly attributable to tropical rainfall?”

Lee and Grotjahn found that, yes, enhanced rainfall in the tropics preceded each heat wave in specific and relatively predictable patterns. They also found that hot weather in the valley is most common after more intense MJO activity in the eastern Pacific Ocean, and next most common after strong MJO activity in the Indian Ocean.

“The more we know about such associations to large-scale weather patterns and remote links, the better we can assess climate model simulations and therefore better assess simulations of future climate scenarios,” Grotjahn said.

###

This work was supported by the National Science Foundation, the National Aeronautics and Space Administration, the Department of Energy Office of Science, the United States Department of Agriculture’s National Institute of Food and Agriculture, and the APEC Climate Center in the Republic of Korea.

A Simple Model of the Atmospheric CO2 Budget

Reblogged from Dr. Roy Spencer:

April 11th, 2019 by Roy W. Spencer, Ph. D.

SUMMARY: A simple model of the CO2 concentration of the atmosphere is presented which fairly accurately reproduces the Mauna Loa observations 1959 through 2018. The model assumes the surface removes CO2 at a rate proportional to the excess of atmospheric CO2 above some equilibrium value. It is forced with estimates of yearly CO2 emissions since 1750, as well as El Nino and La Nina effects. The residual effects of major volcanic eruptions (not included in the model) are clearly seen. Two interesting finding are that (1) the natural equilibrium level of CO2 in the atmosphere inplied by the model is about 295 ppm, rather than 265 or 270 ppm as is often assumed, and (2) if CO2 emissions were stabilized and kept constant at 2018 levels, the atmospheric CO2 concentration would eventually stabilize at close to 500 ppm, even with continued emissions.

A recent e-mail discussion regarding sources of CO2 other than anthropogenic led me to revisit a simple model to explain the history of CO2 observations at Mauna Loa since 1959. My intent here isn’t to try to prove there is some natural source of CO2 causing the recent rise, as I think it is mostly anthropogenic. Instead, I’m trying to see how well a simple model can explain the rise in CO2, and what useful insight can be deduced from such a model.

The model uses the Boden et al. (2017) estimates of yearly anthropogenic CO2 production rates since 1750, updated through 2018. The model assumes that the rate at which CO2 is removed from the atmosphere is proportional to the atmospheric excess above some natural “equilibrium level” of CO2 concentration. A spreadsheet with the model is here.

Here’s the assumed yearly CO2 inputs into the model:

1
Fig. 1. Assumed yearly anthropogenic CO2 input into the model atmosphere.

I also added in the effects of El Nino and La Nina, which I calculate cause a 0.47 ppm yearly change in CO2 per unit Multivariate ENSO Index (MEI) value (May to April average). This helps to capture some of the wiggles in the Mauna Loa CO2 observations.

The resulting fit to the Mauna Loa data required an assumed “natural equilibrium” CO2 concentration of 295 ppm, which is higher than the usually assumed 265 or 270 ppm pre-industrial value:

2Fig. 2. Simple model of atmospheric CO2 concentration using Boden et al. (2017) estimates of yearly anthropogenic emissions, an El Nino/La Nina natural source/sink, after fitting of three model free parameters.

Click on the above plot and notice just how well even the little El Nino- and La Nina-induced changes are captured. I’ll address the role of volcanoes later.

The next figure shows the full model period since 1750, extended out to the year 2200:

3
Fig. 3. As in Fig. 2, but for the full model period, 1750-2200.

Interestingly, note that despite continued CO2 emissions, the atmospheric concentration stabilizes just short of 500 ppm. This is the direct result of the fact that the Mauna Loa observations support the assumption that the rate at which CO2 is removed from the atmosphere is directly proportional to the amount of “excess” CO2 in the atmosphere above a “natural equilibrium” level. As the CO2 content increases, the rate or removal increases until it matches the rate of anthropogenic input.

We can also examine the removal rate of CO2 as a fraction of the anthropogenic source. We have long known that only about half of what is emitted “shows up” in the atmosphere (which isn’t what’s really going on), and decades ago the IPCC assumed that the biosphere and ocean couldn’t keep removing excess CO2 at such a high rate. But, in fact, the fractional rate of removal has actually been increasing, not decreasing.And the simple model captures this:

4
Fig. 4. Rate of removal of atmospheric CO2 as a fraction of the anthropogenic source, in the model and observations.

The up-and-down variations in Fig. 4 are due to El Nino and La Nina events (and volcanoes, discussed next).

Finally, a plot of the difference between the model and Mauna Loa observations reveals the effects of volcanoes. After a major eruption, the amount of CO2 in the atmosphere is depressed, either because of a decrease in natural surface emissions or an increase in surface uptake of atmospheric CO2:

5
Fig. 5. Simple model of yearly CO2 concentrations minus Mauna Loa observations (ppm), revealing the effects of volcanoes which are not included in the model.

What is amazing to me is that a model with such simple but physically reasonable assumptions can so accurately reproduce the Mauna Loa record of CO2 concentrations. I’ll admit I am no expert in the global carbon cycle, but the Mauna Loa data seem to support the assumption that for global, yearly averages, the surface removes a net amount of CO2 from the atmosphere that is directly proportional to how high the CO2 concentration goes above 295 ppm. The biological and physical oceanographic reasons for this might be complex, but the net result seems to follow a simple relationship.