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On January 7 a paper by Veronika Eyring and 28 coauthors, titled “Taking Climate Model Evaluation to the Next Level” appeared in Nature Climate Change, Nature’s  journal devoted exclusively to this one obviously under-researched subject.

For years, you dear readers have been subject to our railing about the unscientific way in which we forecast this century’s climate: we take 29 groups of models and average them. Anyone, we repeatedly point out, who knows weather forecasting realizes that such an activity is foolhardy. Some models are better than others in certain situations, and others may perform better under different conditions. Consequently, the daily forecast is usually a blend of a subset of available models, or, perhaps (as can be the case for winter storms) only one might be relied upon.

Finally the modelling community (as represented by the football team of authors) gets it. The second sentence of the paper’s abstract says “there is now evidence that giving equal weight to each available model projection is suboptimal.”

A map of sea-surface temperature errors calculated when all the models are averaged up shows the problem writ large:

Annual sea-surface temperature error (modelled minus observed) averaged over the current family of climate models. From Eyring et al.

First, the integrated “redness” of the map appears to be a bit larger than the integrated “blueness,” which would be consistent with the oft-repeated (here) observation that the models are predicting more warming than is being observed. But, more important, the biggest errors are over some of the most climatically critical places on earth.

Start with the Southern Ocean. The models have almost the entire circumpolar sea too warm, much of it off more than 1.5°C. Down around 60°S (the bottom of the map) water temperatures get down to near 0°C (because of its salinity, sea water freezes at around -2.0°C). Making errors in this range means making errors in ice formation. Further, all the moisture that lies upon Antarctica originates in this ocean, and simulating an ocean 1.5° too warm is going to inject an enormous amount of nonexistent moisture into the atmosphere, which will be precipitated over the continent in nonexistent snow.

The problem is, down there, the models are making error about massive zones of whiteness, which by their nature absorb very little solar radiation. Where it’s not white, the surface warms up quicker.

(To appreciate that, sit outside on a sunny but calm winters day, changing your khakis from light to dark, the latter being much warmer)

There are two other error fields that merit special attention: the hot blobs off the coasts of western South America and Africa. These are regions where relatively cool water upwells to the surface, driven in large part by the trade winds that blow into the earth’s thermal equator. For not-completely known reasons, these sometimes slow or even reverse, upwelling is suppressed, and the warm anomaly known as El Niño emerges (there is a similar, but much more muted version that sometimes appears off Africa).

There’s a current theory that El Niños are one mechanism that contributes to atmospheric warming, which holds that the temperature tends to jump in steps that occur after each big one. It’s not hard to see that systematically creating these conditions more persistently than they occur could put more nonexistent warming into the forecast.

Finally, to beat ever more manfully on the dead horse—averaging up all the models and making a forecast—we again note that of all the models, one, the Russian INM-CM4 has actually tracked the observed climate quite well. It is by far the best of the lot. Eyring et al. also examined the models’ independence from each other—a measure of which are (and which are not) making (or not making) the same systematic errors. And amongst the most independent, not surprisingly, is INM-CM4.

(It’s update, INM-CM5, is slowly being leaked into the literature, but we don’t have the all-important climate sensitivity figures in print yet.)

The Eyring et al. study is a step forward. It brings climate model application into the 20^th century.

Social scientist Bent Flyvbjerg described the selection of government-funded infrastructure projects as “survival of the unfittest” because proponents of those projects systematically exaggerate the benefits and underestimate the costs.  President Trump’s proposed border wall with Mexico provides a striking example of this: A wall along the border with Mexico will likely cost about $59.8 billion to construct.

The Office of Management and Budget (OMB) recently sent a letter to Congress where it argued that $5.7 billion would pay for approximately 234 miles of a new physical steel barrier along the border.  That new estimate comes to about $24.4 million per mile.  This new OMB estimate is 41 percent more costly than the approximately $17.3 million per mile construction costs that the Department of Homeland Security (DHS) estimated just a few years ago, 2.7 times as expensive as Mitch McConnell and Paul Ryan estimated, and 5 times as expensive as Trump’s lowest estimate. 

Even worse, the $24.4 million per mile estimate does not include the large cost overruns for government construction projects.  Applying a conservative 50 percent cost overrun estimate to building the border fence brings the total price tag to approximately $36.6 million per mile.  Building a steel fence along the remaining 1,637 miles of Mexican border not covered by pedestrian fencing would cost approximately $59.8 billion, excluding any maintenance costs. 

There are a few caveats about the above estimate.

First, the 50 percent cost overrun estimate is conservative.  A small sample of large construction projects selected by my colleague Chris Edwards shows that cost overruns boost total project costs by an average of 3.3 fold.  The cost of the border fence is thus very likely to be more than double what I estimate above.

Second, this estimate is for the steel bollard barrier and not a concrete wall.  In other words, the currently proposed steel border fence is far cheaper than the concrete and steel wall originally proposed by President Trump.  Making it out of concrete could more than double the price.

Third, our cost estimate does not include the low-ball $864,353 annual per mile cost of maintaining the current border fence – which is likely a lot less expensive than repairing the barrier that has been proposed by Trump. 

Fourth, the OMB’s cost estimate per wall is more in line with previous Trump administration requests than estimates made by organizations that are ideologically committed to building a wall regardless of the cost to taxpayers.    

Since 2017, administration officials at the OMB have been relatively consistent in estimating that the government cost of building a border wall is around $24 million per mile.  However, the incentives for and history of government agencies systematically underestimating the costs of government construction projects makes this the lowest possible estimate.  If it is built for about $24.3 million per mile than it would be the first time that a large government construction project has come in at or below cost in a very long time.

The cost of the border wall keeps getting higher, the border wall keeps becoming less of a wall, and the administration keeps promising that it will cover less and less of the border.  At this rate, President Trump might end his administration with less fencing than he began it. 

Upon taking office in 2017, President Trump accused trade partners of underhandedness, demonized U.S. companies with foreign supply chains, and perpetuated the false narrative that trade is a zero-sum game requiring an “America First” agenda. He withdrew the United States from the Trans-Pacific Partnership, threatened to pull out of North American Free Trade Agreement and the Korea-U.S. Free Trade Agreement, and initiated a war of attrition against the World Trade Organization by refusing to endorse any new Appellate Body judges until his unspecified demands were met. Yet, those were still the halcyon days of trade.

In 2018, straining all credulity, the Trump administration dusted off a seldom-used law (Section 232 of the Trade Expansion Act of 1962) to impose tariffs on imported steel and aluminum from most countries on the basis that national security is threatened by U.S. dependence on foreign sources of these widely available commodities.

Later in the year, invoking another controversial U.S. trade statute (Section 301 of the Trade Act of 1974), which is widely considered an act of vigilantism under WTO rules, the administration announced tariffs on $50 billion worth of imports from China for alleged unfair practices, such as forced technology transfer and intellectual property theft. When Beijing retaliated with tariffs on U.S. agricultural products, Trump announced that he would hit another $200 billion of imports from China with tariffs. Once again, Beijing responded by broadening its list of targeted U.S. products and the president subsequently threatened to apply U.S. levies to all imports from China (over $500 billion in 2017).

To be fair, U.S. trade policy in 2018 wasn’t only rancor, hostage-taking, and trade war. Juxtaposed against this contentious, grievance-based, enforcement-oriented U.S. posture was some “trade liberalization.” Instead of withdrawing from NAFTA and KORUS, the Trump administration renegotiated both. Both included some liberalizing provisions, but also some lamentable, protectionist retrogression, which wasn’t totally unexpected given that, in both cases, U.S. insistence on renegotiation was motivated less by an interest in updating, expanding, and modernizing the agreements than by a desire to revise provisions that would—at least nominally—tilt the playing field in favor of U.S. workers and certain manufacturers.

As 2019 begins, five major issues cast long shadows over the trade policy landscape. First is whether and how the U.S.-China trade war will be contained, scaled back, and ultimately ended. Second is the looming possibility that the Trump administration will invoke national security to impose sweeping new tariffs on automobile imports. Third is the question of whether and when Congress will pass the implementing legislation for the new NAFTA (the United States-Mexico-Canada Agreement or USMCA). Fourth is whether, when, and how the crisis at the WTO will be resolved. And fifth concerns whether the Trump administration has the wherewithal to make good on its stated intentions of negotiating new trade agreements with Japan, the European Union, the Philippines, possibly the United Kingdom, and other countries. With much of the rest of the world moving forward with a slew of new trade agreements and the United States stuck on revamping old deals, the real and opportunity costs to U.S. businesses, consumers, and taxpayers continue to mount.

Throughout the year ahead, these major issues will be the predominant focus of the research and writing of the Cato Institute’s Herbert A. Stiefel Center for Trade Policy Studies.