What is a climate classification for?
It’s not for answering most practical questions about what weather to expect. Should I pack a coat? When should we have the wedding? Is a shingled roof a good investment? Will a lantana survive the winter? Can I plan midday jogs this summer? Should we add more drainage? Can we take your cousins to the lake in September? Should we get solar panels? Local statistics help answer these questions. Seeing your local climate as an example of some class of climates does not.
Mean winter rainfall, for example, is defined everywhere near Earth’s surface and varies smoothly; in geography jargon, it’s a continuous field. There’s some long-term average of weather where you are, and one where I am, and they’re both samples of points in the continuous fields of what the weather has done. Fields are mappable. The USDA hardiness zone map, for example, is the field of the lowest temperature expected in a normal year: the most important factor in what you can grow in a garden.
(Climate change creates fundamental problems for the idea of a long-term average of past weather as an expectation of future weather, and likewise for the idea of a normal year, but I won’t bring it into this note. It’s important and relevant – for example, to hardiness zones – but I have chosen to write, and you have chosen to read, a linkblog, and we both understand that this format does not carefully prioritize truths, let alone express whole ones.)
The hardiness zones are a simple climate classification. They regionalize the continuous field into categories from 1a through 13b. A gardener can look at the map (instead of 30 years of local weather records) and learn what zone they’re in, and a seed store can say their ginkgo variety is hardy to zone 3, and they have communicated a useful idea.
But drawing any border, however benign, creates tricky situations. If we’re in zone 9b, then we have more in common with some of zone 10a than with some of zone 9a, so just how useful is zone 9 as a category? Go straddle the zone 9–10 border and each foot will be in the same climate (to far below the precision of any realistic measurement) but a different zone – a zone that contains far-off places that do have noticeably different climates. At the border, zone 9b is identical to zone 10a but not to elsewhere in zone 9b. The region’s job, to collect places that are like other places within the region but unlike places outside the region, is not possible.
So if climate regions are irrelevant to local questions, and if regionalization of continuous fields can never work properly, we might ask again, more loudly: What is a climate classification for?
It’s for naming clusters and patterns among climates, in order to move ideas between different areas of study – different kinds of local questions. This is my best answer. To say that Toronto has a continental climate is not very specific, because there are many ways to define continental climates, and ranges within all of them. But it’s a good starting point for further specifics. We might be in a conversation about plant ecosystems, heating costs, or subjective preferences, but starting with continental gives a sense of the basics – warm summers, cold winters, occasional thunderstorms, no especially wet or dry season, and so on.
The most widely used climate classification scheme today is Köppen–Geiger. The paper calls it a resultant scheme; you can also find it called empirical. This means that it defines climates by an effect of climate: natural vegetation, because Köppen was a botanist. I grew up in the Salish Sea in a Köppen-Geiger Csb or warm-summer Mediterranean climate, bordering on Cfb or marine west coast, and we did in fact have mostly coniferous forests punctuated by oak savanna, which is more or less what that’s supposed to mean.
The Alisov climate classification is not resultant, a.k.a. empirical: it’s causal, a.k.a. genetic. Instead of classifying local climates by what they do, it goes by where they come from. This means looking at the airmasses. The airmasses are the gods of the atmosphere: four-dimensional metapatterns whose unitary physical reality at any given moment is debatable, but which manifest through time and space in such a way as to keep the Sahara dry, the equator wet, and Earth looking like Earth. When a front passes over us, we are moving between airmasses. When we say Toronto has a continental climate, one way to back that up is to say it’s at the edge of the continental polar airmass that forms over the Canadian shield. Alisov’s system is squarely in these terms: what is the airmass here and how does it shift through the year? Everything else flows from that.
Usually in the sciences and allied trades we see causal or genetic systems as the central way of categorizing things. Take the first association we have with the term
genetic: of the many useful ways of categorizing organisms, the fundamental way is phylogenetically, on the tree of life. In chemistry, there’s the periodic table. (Pedantic chemists, which is what I would be if I were a chemist, are annoyed by jocular
periodic tables of pasta or haircuts that are just grids arranged without causal structure.) In medicine, gaining an etiological grip on something is more or less when we say it’s understood.
In climate classification, though, we seem happy enough with a symptomatic typology: Köppen–Geiger. Perhaps that’s slightly too strong. K–G does look at causes (amount of rainfall, for example), but its lines are drawn to match effects. I’m not complaining. But it’s interesting. In an intellectual tradition that could be defined partly by the weight it gives to the history and genealogy of everything, to sorting things by their essences before their existences, the great majority of climate regionalization is in Köppen and Geiger’s resultant system instead of, for example, Alisov’s causal system.
Why don’t we use Alisov? There are practical problems with it, but not many more than you could raise against the Köppen-Geiger, Trewartha, or Thornthwaite systems. I think it’s mostly political. The Alisov system was promoted by the USSR as part of the cold war, and it remains tangled in the aftermaths. One of the only first-rate examples of it on the Anglophone web is in scans of the great Soviet Ocean atlas (1974–7), which has the Pacific and Indo-Atlantic oceans (but no land, which would exceed its authority). That atlas was officially edited by admiral Gorshkov, for some sense of the subtexts. It’s hard to wash that smell off.
I hope that this new work on Alisov’s scheme will get more people interested in causal approaches to climate classification. And if you want the best example I know of Alisov’s original version, this handsome plate from the Physical-geographic atlas of the world (1964) does cover land.