Climate costs in the UK

Climate change will affect all aspects of our lives and economies. As summers get hotter and storms stronger, it will undermine our ability to grow food, to have secure homes, and produce sustainable incomes. At the same time, stopping climate change will also have consequences for society. Our ability to compare the costs and benefits of climate action is crucial to making sound global decisions.

Earlier this month, I led a team to complete a comprehensive economic assessment of climate risks for the United Kingdom. The UK is a leader in shifting its economy toward Net Zero, and has years of experience understanding the costs of shifting to green energy. But it has not had a corresponding cost number for the impacts it can expect. Particularly since the UK cannot direct the actions of the rest of the emitting world, this numbers are important to know.

The big challenge in producing an estimate like this corralling results from many other studies into a consistent framework. Across the studies that have tried to do this before (for the US and the EU), we were able to produce perhaps the most comprehensive assessment.

FUND modelPESETA II-IV (2014-2020)American Climate Prospectus (2015-2017)Climate Impact Lab – DSCIM (2021-2022)Temperature Binning Framework (2021)CCRA3 Monetary valuation (2021)UK Climate Costs Report (2022)
Trade Spillover

To jump to the conclusion, we find that the costs of unmitigated climate change (“current policies”) reach 7.4% of the UK’s GDP. And this is for one of the most un-vulnerable countries in the world. On the other hand, the costs for going to Net Zero are actually negative, once you account for the health co-benefits and the investment boost.

There is a lot more work to do to understand who is at risk and what they can do about it. But there is a lot to dig into in these results already. Our data is all available (link below), and I invite you to start digging!

An Odyssey on Route 66

I just spent a week on the road, driving from Las Angeles to Philadelphia, taking my grandmothers car back to my (still new) home. I followed Route 66 (though, mostly the new interstates, not the historical road), from its beginning to end, and generally had a swell time. The landscapes were amazing– I particularly loved the Painted Desert from Flagstaff to Albuquerque. I have a few pictures of the trip here, but the desert beauty was impossible to capture:

To keep me company, I had my audiobooks. I finally wanted to go through the Aeneid, and when I learned that its audiobooks were only ~14 hours, I tacked on the Iliad and the Odyssey too. Together, they came out to just less than my 45 hour drive. Obvious allegories aside, I had a lot of fun spending a week in ancient mythology, and plenty of random thoughts to share.

First, my translations. I listened to the fairly-recent Stanley Lombardo translation of the Iliad, read also by him, which is filled with bizarrely modern idioms and playground language. For the Odyssey, I went with W. H. D. Rouse, read by Anthony Heald, a famed reader who uses his voice to play many parts, but also had an off-putting tendency to apply Irish accents to low-caste servants. I wanted a verse translation for the Aeneid and used John Dryden’s 17th century approach for the joy of it, narrated by Michael Page. Beautiful, but a real effort to follow.

I was surprised by the basic content of the Iliad (never got far into) and the Odyssey (thought I remembered from years ago). The Iliad starts 9 years into the siege of Troy, and ends before the war is over. The last chapters focus on the death and memorial (and praise and mourning) of the main Trojan villain, Hector. There’s no mention of a Trojan horse, and Achilles is still alive and strong.

The Odyssey, meanwhile, starts with several chapters on the journey of Telemachus, Odysseus’s son, to learn of his father’s fate. We know almost nothing of Odysseus’s journey until the great lie-teller relates them himself to the Phaeacians, the people who will finally take him home.

The Aeneid is like a vast digest of the Iliad and Odyssey, starting with 7 years of wandering and ending with 3 of war. And as though there are only a few monsters in the sea, Aeneas also encounters the Cyclopes and Charybdis. The highlights of the Trojan war are related, with turns of phrase close enough to make an editor blush. But where the Iliad and Odyssey were organic and original products of culture, the Aeneid takes derivativeness to the level of genius.

All three are boys tales, with manly deeds and enchanting women. But the role of women changes quite a bit between them. In the Iliad, women are foremost “prizes”, with both their bodies and love ready to be won, stolen, or traded. In the Odyssey, there is a real propensity for women to work magic (Circe, Calypso, Sirens), but they are nonetheless passive (Penelope’s great strength was in not resolving the marriage question; Odysseus spends seven years with Calypso and we hear next to nothing about it). The Aeneid presents women as, on one hand, potential equals (Queen Dido, the warrior Camilla), but in interactions they seem so submissive, with lowered eyes and obsequious language.

I don’t think I would have appreciated the Iliad when I was younger. Homer is like a court bard, recording the Spark notes of history: the litany of who killed who is really the point of the work. But around that core, there’s a lot to appreciate. Homer weaves in his poetic sense with allegories about lions and sheep. The personalities of great men shine: the two Ajax’s, like giants; Achilles, touched by gods; Diomedes, the unstoppable; Patroclus, the doomed. The sounds of war– its fright, its fog– come through crisply.

The nature of war is also very different. For one thing, all of the nobility know each other, and know who it is they are trying to kill. In a couple cases where one party did not know the other, they asked for a lineage, and this was provided before they fought. Most of the battle seemed to happen in pairs, with one individual coming up against another. First, they would each boast, to dishearten the other; then the would throw their spears; then they would close with swords. When one died, the other would have the opportunity to remove his armor and bring it back to camp as a trophy. One gets the feeling that most of warriors spent most of their time on the side lines, watching the main stage and waiting their turn.

I’m sure that there’s scholarly work to understand this much more deeply than I have, but I had such a blast hearing the tales that I wanted to record it.

Limits to adaptation in agriculture

Agriculture is going to be one of the sectors most disrupted by climate change. Our ability to produce food relies on a stable climate. Crops and management practices are carefully catered to local climate conditions, including the timing and intensity of rainfall, the length of growing seasons, and the complex biology of soil. Climate change is going to disrupt all of this, demanding new practices, new varietals, and for many regions, new sources of water or arable land.

Will farmers be able to adapt? Or are the details of effective farming too complicated, so that it will take decades to find the right new practices and seeds, by which time the climate will have changed again? This is a fundamental question for the future of food security globally and the livelihoods of millions of farmers.

One piece of evidence comes from following the harmful effect of high temperatures on crops in the United States. Temperatures over 29 °C damage corn (maize), but this effect can be attenuated by irrigation. As a result, the damaging effect of high temperatures is observed to be much less in the extensively-irrigated US West than in the East. It has also been observed that the impact of high temperatures has slowly declined over the course of the historical yield record, from 1950 onward (Burke & Emerick, 2013). This is climate adaptation occurring as we watch!

So how quickly have farmers reduced the impact of high temperatures? Unfortunately, very slowly. Reducing the damages by 10% takes about 40 years. We modeled this effect across the next century, and whereas climate change would reduce yields by almost 60% by the end of the century (under business-as-usual), adaptation results in yields only being reduced by about 50%.

The loss in yields from climate change, with adaptation (solid) or without (dashed).

Clearly adaptation in the past cannot be a blueprint for adaptation in the future.

One of the most common stories about agriculture in the US is that it will just move north. If it’s too hot here, it will be just right in Canada. That will be bad for US farmers, but certainly not an existential threat to our ability to feed people in the future. But can agriculture find as fertile grounds north?

To answer this, I collaborated with Naresh Devineni, a hydrologist and Bayesian modeler. We developed a new model of the sensitivity of crops in the US to climate change, and a way to project crop switching into the future. The paper was recently published in Nature Communications.

The results suggest caution. Can crop-switching reduce the impacts of climate change? Yes, but 50% of the losses from climate change cannot be adapted away. Will many farmers have to change what they grow? A ton: To get the benefits we describe, over 50% of farmers will have to change what they grow.

Why can’t crop-switching remove all of the impacts of climate change? Almost everywhere, the value of the land for planting any of the crops we model will fall. In fact, in our model about 5% of current agricultural land will be left fallow by 2070, because any crop will cost more than it would generate in profit.

The change in profits by 2070 for land under its most productive use.

NPR Marketplace recently put these results in the broader context of risks from climate change. Listen to the piece to learn more:

The endnote from Steve Biddulph’s Raising Boys

I just finished Raising Boys in the twenty-first century, which is deeply rooted in the men’s movement, offering a now-days fairly accepted new-age form of mythopoetic masculinity. I found some parts enlightening (the examples of initiation rituals), some parts overly rigid (boy’s need for hierarchical order), and some parts exasperating (his selective reading of research to validate his views). But I am in need of perspectives on how to raise boys, and he kept me reading.

I want to share the last page of the book, which crystalized something missing from all the other parenting books I’ve seen. I would demur about the certainty he paints here, but I want to give him the last word. Here’s his text:

Most books on ‘parenting’ have a built-in assumption, never named but always there — that the world we live in is just fine, and our job is to fit our kids into it well. That the procession of human life is headed to a golden, prosperous future, and we only need to keep our kids from falling by the wayside. Perhaps (though this is not usually stated), we can help them push to the head of the queue.

Of course, this is a massive lie. The very best science and knowledge is that we live in a time of dystopian collapse, where inequality, the misuse of resources, and above all the crisis of climate change will lead to disrupted agriculture, famine, mass migration and war. We know this because it’s already begun to happen.

It’s almost certain that our kids will live in far worse times than we have, and our grandchildren may not be able to live at all. We don’t need kids who fit in. We need heroes — young men and women who are strong-hearted, caring, calm and passionate and have a purpose beyond themselves — to care for the whole species and the life that sustains it. To turn things around. To promote radical, non-violent change. We need good men and women in numbers like never before. That’s what we have aimed to raise at our house, and we hope you will too.

Inequality and the death toll of future climate change

The Climate Impact Lab just got a great write-up for our work on the risk of mortality under climate change in Bloomberg Green. There are a bunch of excellent dynamic visualizations that dig into the data.

There are two big messages here. The first is that poor people are going to get hammered by climate change, with some areas experiencing deathrates from the additional heat that are greater than the combined global rates for heart disease, stroke, all forms of cancer, all forms of infectious disease death, and all forms of death from injury.

The other is that we can use this information to start to estimate the total cost of climate change to society at large, because it gives us a lower-bound. Just the effect of additional mortality costs society about $22 per ton of CO2. That’s already more than the total social cost used by the Trump administration and half way to the total cost used by the Obama administration.

Take a look at the summary write-up of the research behind the Bloomberg article, and look forward to the reports that we are going to produce on the effects of climate change on labor productivity, agriculture, energy demand, and coastal impacts.

You are not living in a simulated reality, data-wise

Recently, I’ve been mostly-loving the podcast Philosophize This!, and I just listened to Episode #95, Are you living in a simulation? It discusses Nick Bostrom’s paper arguing that the likely answer is “yes”.

I never worried too much about these arguments, on the principle that the answer doesn’t affect what I care about in life, but listening to it, I realized that the basis for this theory is based on old ways of thinking, and the likelihood should go the other way.

As a person who creates simulated realities all the time, we have a secret: most simulations borrow a huge amount from reality (or at least, from their parent reality).

Most of what makes a world– simulated or otherwise– is its data. This is one of the great insights of the machine learning revolution. And you would have a tough time creating that data from scratch even if you wanted to.

If you tell the computer of a holosuite from Star Trek to create a person, it wouldn’t ask you, “Would you like me to simulate the evolutionary process of personhood from first principles?” It will just assume that everything about your simulated person is the same as the way real people work. Cut the person in the simulation, and they’ll bleed like a real person. All the parameters behind their bleeding– the color of the blood, the rate of bleeding, etc.– are aspects of reality.

Plus, simulations have boundaries. For example, if you were interested in creating a simulation of Earth at this point in time, it would be sensible to grab our knowledge of the whole rest of the universe and just plug it in. There’s no reason to create a different night sky.

These boundaries can occur at any level: you can model a planet in the context of the universe, a person in the context of the world, an idea in the context of the brain. In fact, brains do this all the time.

Whereas the original thought experiment had only one data point (our apparent existence prior to world-simulating capabilities), we actually know quite a bit about the question of how much data filters from reality through the simulation boundary of our mind. There are informative arguments from Kantian pure theory and from that logic where Gödel meets information theory. None of it conclusively resolves the mind-body distinction, but neither did the original simulation data point.

But since I started this with an insight from computer science, I’ll complete the loop there too. What do we know about the share of data-vs.-simulation necessary to create a mind? While there’s a lot more we need to learn about the building-blocks of intelligence, the machine learning revolution has taught us that intelligence is hugely built upon data, not on modelling.

So, let’s return to the fundamental thought experiment: the number of simulated realities should exceed the number of real realities. But if you take a random piece of data within any of those simulations, the number of real data points is likely to far exceed the number of simulated data points.

I am not saying that there are not simulated aspects of the world we experience. But I would argue that there is no essential difference between the boogey man of a “simulated reality” and aspects of the universe that we already accept.

Are computers involved in creating our world? Yes, you’re reading a post on one of them now.

Are aspects of you or the world a “copy” from somewhere else? Sure, much of your experience of the world, as simulated by your brain, is just re-applying ready-made templates to the raw facts of the universe.

Is the core “you”, your subjective self, a simulated quantity? Either subjectivity cannot be created on a computer, then no, or it’s an emergent property, and then already modeled on brain hardware.

I imagine that these last points have probably been made plenty of times before by people who are missing the point of the simulated universe problem. And maybe I am too, but in light of the role of real data in simulations, the original question definitely was.

Introducing… Austin Reed Rising!

Our son, Austin Reed Rising, was born Monday, June 8, at 10:51 pm (BST) at St. Thomas Hospital in London. He weighs a healthy 6 lbs. 9 oz., with 10 fingers, 10 toes, and an APGAR score of 10.

I’ve added a few pictures below. Want more? Take a look at the` ever-growing Austin Pics Photo Album!

He is named in honor of Johanna’s grandma, Goldie Newman, and the chemical symbol for gold, Au. Reed was James’s father’s middle name, and his grandfather’s before him. Our son’s Hebrew name is Paz, meaning golden. You can read more about his name in our letter to him. For the gooey delivery details, see his exhausti[ng|ve] birth story.

We are very excited for you to meet him soon!

With love,
Flame, Austin, and me

Taking risks with COVID-19

Edit: It turns out that economists have investigated the corresponding mortality costs from a recession– and they’re negative! Mortality rates go down in recessions. Add that to the environmental benefits of slowing down the global economy, and lock-downs look a lot like a clear boon for society.

We are observing a fascinating social phenomenon. Far from our normal mode, the world has decided to respond to the COVID-19 threat long before it has reached its crisis. I am fascinated, but also concerned. As a society, we have chosen to self-administer a kind of global shock therapy, and if we are not careful, the consequences of the medicine will be greater than the disease.

I do not claim to know how to balance these conflicting forces, but I’ll bet health experts don’t have the interdisciplinary training to make that judgement either. In many ways, this pandemic looks a lot like climate change. If we do nothing now, it will be a disaster in a couple months. If we do too much now, it will be an economic disaster, which could be just as damaging.

Let’s consider the current situation. About 0.003% of the global population has been confirmed to have (or have had) the coronavirus. Across the US, it’s 0.005%; in New York, the hardest-hit state, the infection rate has gotten up to 0.03% (as of March 21). That’s confirmed cases, but it might be a decent approximation to the actual cases: Germany has prided itself with very thorough testing, and it has a 0.03% infection rate. The US has not been doing a very good job of testing, but still 8 tests are administered for every 1 that comes back positive.

So, let’s do a thought experiment with the confirmed cases: Let’s imagine getting a group of randomly chosen people from New York state together.If your group was 1 person big, there would be a 0.03% chance that that person has COVID-19. If it’s 2 people big, the chance that one or the other is sick would be 0.07%. For that risk to get up to 1%– at which point it might make sense to call off the gathering, there would need to be 28 people. For the chance that one or more of them were sick to reach 50%, the group would have to consist of about 2000 people.

It won’t stay this way. Without intervention the real crisis will hit around June. Here’s my simple model, which looks a lot like what the NYT has been showing for the past couple weeks, but I made it almost a month ago:

The disaster hasn’t come yet. We should think more about what we want to do to prepare between now and then.

The right balance depends not only the benefits of quarantine, but also on its economic costs. There are already estimates of the unemployment rate in the US doubling in the next couple months, and maybe going as high as 10%. We have set off an economic recession which is going to derail a lot of livelihoods, and for some people it will mean their lives. Add on top of that the physical and mental health problems that are emerging as a result of self-isolation, and the loss of in-class education for millions of students, and it looks like we have chosen to pay a very high price.

If we were to lock-down less, it would mean that more people could keep their jobs. More people would also get sick, but it would help in the long run as the population of people immune to the virus increases. Some of the extra infections would have to go to the hospital, but current COVID-19 infections are a tiny share of current hospital cases, and many regions can handle the extra load. Or, at least they can handle it a lot better now than they will be able to in a few months, during the peak crisis.

I’m not proposing that older people or other high-risk populations stop self-quarantining at all– COVID-19 is incredibly dangerous to people over 65. But we need more working-age people on the front lines, sustaining our economy.

The chance of dying is low for under-40s– 0.2%– but still high as these things go. That’s twice the death rate of the flu. But the economic recession will also lead to more deaths. I think we need a movement of people who are willing to personally accept the risks that come from an infection, for the benefits that they can provide. They should not interact with those people who are staying in isolation, but this group needs to extend far beyond “essential” workers.

By the way, this can also be a moment to help correct the injustices of the current economy: if we are choosing to risk our lives, we should not be doing it for the benefits of the powers-that-be. But that can be for another post.

Introducing a tutorial on climate econometrics

There is a rising tide of people who want to get involved in climate econometrics, dissipating against the shallows of unfinished research ideas, and spinning like weather vanes trying in vain to understand weather. Well, no longer! I would like to introduce! is an introduction to the secrets of using climate data, generating weather panels, choosing specifications, and getting results. Think of it like a practical complement to Solomon Hsiang’s SHCIT list:

The tutorial is still new, and we would love your feedback and suggestions. And you are welcome to get involved and help us extend the tutorial (there’s an ocean still to cover!).

Water-energy-food modelling for the 21st century

The highest good is like water.
Water gives life to the ten thousand things and does not strive.
It flows in places men reject and so is like the Tao.

– Tao Te Ching (Lao Tzu)

Water is such a fascinating resource because it’s at the center of things: absolutely necessary, but generally given no value. This the fundamental enigma that has motivated a huge growth in the study of “water-energy-food systems” (WEF systems or nexus). But the WEF nexus are also defined to dodge the central problems of water.

The first dodge is by framing water as an equal partner with energy and food. As I’ve written before, water plays a very different role than energy or food: energy and food are completely dependent on water, not so much on each other. WEF systems should better be called “Greater Water Systems”.

The second dodge is a common avoidance of the fundamental decisions-making build into water systems. Water availability isn’t really a physical fact of nature: it depends on human decisions. Water grows scarce when we demand more than the natural system can provide. And in most areas of the world now, water supply is the result of our investments in reservoirs, canals, treatment and reuse systems. WEF systems have no static elements; it is constantly being created by us.

A full understanding of the WEF nexus requires an integrated approach, which makes decisions about water use and infrastructure, based on how we can ensure the most beneficial use of water for ourselves and the environment. I presented on these ideas at the 1st International Conference on Water Security, using the AWASH model to understand long-term investment decisions around reservoirs.

The insights from that work were published this week in the new journal Water Security. Take a look:

Decision-making and integrated assessment models of the water-energy-food nexus

Sustainability, Engineering, and Philosophy