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Agnostic Razib Khan
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One of the major issues in our world today is that we’re a people of specialties. This means that we don’t have basic interpretative frameworks in which to place novel facts. Because of the abstruse and formal nature of the discipline, this is probably starkest in the domain of science, but it is not restricted to only science. Consider geography. In many ways this is “low hanging” cognitive fruit in the shallow part of the learning curve which mostly consists of assembly of facts, but because of the shifts in emphases in American education geography has tended to get short shrift. This means that whenever there’s a foreign policy crisis middle-brow journals of record such as The New York Times have to commission pieces about nations such as Libya which read like a “first book” for six year olds on that nation (and on political weblogs commenters proudly brandish their “first book” level of knowledge).

But a bigger general issue seems to be in relation to climate. “Climate Change” is in the news constantly, but the average person on the street seems to have zero historical perspective on events such as the Medieval Warm Period, the Little Ice Age, let alone more obscure epochs such as the Younger Dryas. Fair enough, it isn’t as if Deep Time is ever going to be broadly interesting. But more disturbing to me is the total lack of perspective when it comes to current spatial patterns.

For example, a friend who has college degrees in history and philosophy, has traveled to Europe, Canada, and is planning a trip to Thailand and the Philippines, thought China was further to the north than Europe. Take a look at this map:

New York City, Madrid, and Beijing, are all at the same latitude. The average low in Beijing in January is -8.4 °C. For New York City it is -3.22. And finally, for Madrid it is 2.6. Why the difference? Barcelona, to the north and east of Madrid, on the coast, has a mean low of 4.4 °C. This tells us what’s going in the most general sense. Continentality. My friend’s ignorance was understandable; Beijing has a much more frigid clime than southern Europe. China as a whole is much further south than climate without context would suggest, while Europe is much further north than most expect. All that has to do with the rough shape of the continents (and possibly the Gulf Stream for Europe, though this might be overdone taking into account the generally mild character of western upper temperate regions of continents). But first, let’s look at another example.


The town of San Luis Obispo in California gets about 33% more rainfall in the aggregate than Medford, in Oregon. The reason for this difference in aggregate rainfall seems clear when you look at their positions on the map to the left. Medford is inland, and somewhat in a rain shadow behind the Siskiyou mountains. San Luis Obispo in contrast has a much more maritime location. All things equal, maritime locations will generally have more precipitation than inland locations. But not only are all things rarely equal, notice that Medford has a longer “rainy season” than San Luis Obispo. This can’t be explained by the coastal vs. inland position.

My immediate explanation is that this must be due to the waxing and waning of the Westerlies with the seasons. The Westerlies are powerful winds in the temperate latitudes which blow out of the west and which tend to shift toward the equator during the winter, and retreat toward the poles during the summer. The shift of the westerlies on the western coasts of continents during the cold season is also accompanied by rainfall across broad swaths of the lower temperate latitudes, ergo, “Mediterranean” climate patterns on the southern tip of Africa, southwest Australia, central Chile, California, and yes, the Mediterranean. As physical dynamics not subject to magic, the movements of these winds exhibit a regular pattern where the areas which are furthest on the margin of their zones of expansion will also be the first subject to their retreat (this same pattern occurs with subtropical monsoons, as the rains abate fastest in the regions where they came the latest).

So what you have here is a two-variable model on the western coast of the United States in terms of predicting precipitation. On the one hand there are the coarse large-scale spatial relationships on the continental and planetary level which predict the flow of winds which bring the rainfall. But, there are also more fine-grained patterns of local positioning and topography.

All of the above I constructed as a model within 5 minutes, drawing upon a period of fascination with physical geography which I had when I was 8 to 10 years old. Because of my primitive mental state I only had a descriptive “stamp collecting” understanding of the patterns, but even my cursory knowledge of those patterns has been very useful to me as an adult. If the globe does warm, for example, I’d hazard to guess that the Pacific Northwest of the United States will have a climate resembling that of California far more likely than that of the American South. Why? Because the western coasts of continents are characterized by a particular set of temperature and precipitation regimes. Nature is not flat in its possibilities.

A broad background knowledge of spatial patterns allows one to infer facts and test ludicrous assertions “quick & dirty.” Of course one is often wrong if one lacks the subtle and precise knowledge of a specialist, but it is superior to the theory and data-free speculation which is par for the course in normal conversation.

Below is a Köppen climate map, the kind of mental image which I’ve long had seared in my brain:

Here are some quick facts which many people don’t know, but are often useful:

- The eastern coasts will tend to have a more “continental” climate than the western coasts (greater temperature fluctuations)

- The extent of this difference should be proportional to the size of the temperate zone hinterland

- Because of the coriolis effect winds going toward the poles will be deflected to the west, and those going toward the equator will be deflected toward the east (ergo, Westerlies vs. Trade winds)

- Large continents have a distorting effect all around them due to their massive temperature fluctuations. The larger the continent, the bigger the distorting effect (ergo, the most famous “monsoon” generated by the hyper-heating of continental interiors is the Asian one, even though there are monsoons operative in North America and Africa)

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Climate, Geography 
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Thanksgiving in the tropics:

Finally, here are some pictures I took today. It was way too hot and humid when we first got to Taiwan, but now we’re getting some lovely winter weather – Taiwan is about the same latitude as Hawaii :-) It sure doesn’t feel like Thanksgiving or Xmas around here!

One aspect of the East Eurasian temperate zones is that they are far to the south of the West Eurasian temperate zones. Cork, Ireland, at about the same latitude as Petropavlovsk, Kamchatka, and eight degrees further north than Vladivostok!

But since Steve brought up Hawaii, let’s compare highs and lows in Honolulu, and Hanoi, two cities at 21 degrees north. On the literal margins of the tropics:


avehighlow

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Climate 
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In the post below, Colder climates favor civilization even among Whites alone, I made a few comments about possible differences between Germans in Illinois and Germans in Texas, based on nothing much more than a hunch. I trust my hunches, but there’s no reason you should, so I decided to see if there was anything here in regards to my assumption about interregional differences in intelligence and how they might track across ethnic groups. So of course I went to the GSS website, and checked the mean WORDSUM scores of various white ethnic groups broken down by region. I specifically focused on whites who stated that their ancestors were from England & Wales, Germany and Ireland. My reasoning is that these are three groups with very large N’s within the GSS sample and they are well represented across the regions in absolute numbers. My main motivation was see if the differences across regions were similar for all three groups. Here are the states for each region (the Census made up these categories):

New England – Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut
Middle Atlantic – New York, New Jersey, Pennsylvania
East North Central – Ohio, Indiana, Illinois, Michigan, Wisconsin
West North Central – Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, Kansas
South Atlantic – Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida
East South Central – Kentucky, Tennessee, Alabama, Mississippi
West South Central – Arkansas, Louisiana, Oklahoma, Texas
Mountain – Montana, Idaho, Wyoming, Colorado, New Mexico, Arizona, Utah, Nevada
Pacific – Washington, Imbler, California, Alaska, Hawaii

Obviously the breakdown isn’t ideal. I think Delaware and Maryland arguably should be Mid-Atlantic. I also believe that Wisconsin is more plausibly in the West North Central than Missouri or Kansas is. But those are the regional breakdowns and I can’t do anything about them.

So, WORDSUM is a vocabulary test on a 0-10 scale. For the whole GSS sample the mean was 6.00, with 1 standard deviation being 2.16. Below is a chart which shows the relationship between WORDSUM scores (Y axis) for various regions (X axis) for each of the three ethnic groups:


The tables below are pretty self-explanatory. At the top you see the mean WORDSUM scores for each ethnic group for each region. I put the N’s in there as well so you can see that the sample sizes were pretty big. Note that there is more interregional variation within an ethnic group than there is interethnic variation within a region (the standard deviation across the columns is 50% bigger than across the rows). Just to be clear, I also included some tables which show the differences in WORDSUM mean scores between the regions like so: (row – column) = value.

New England

Middle Atlantic

East North Central

West North Central

South Atlantic

East South Central

West South Central

Mountain

Pacific

N

England & Wales

7.4

7.09

6.71

6.65

6.66

6.2

6.87

6.84

7.1

2,462

Germany

7.7

6.31

6.01

6.33

6.16

5.83

6.2

6.37

6.36

3,316

Ireland

6.98

7.07

6.15

6.46

6.06

5.66

6.03

6.51

6.88

2,207

tyle="text-align: left; width: 1.3673in;">

England & Wales

New England

Middle Atlantic

East North Central

West North Central

South Atlantic

East South Central

West South Central

Mountain

Pacific

New England

-

0.31

0.69

0.75

0.74

1.2

0.53

0.56

0.3

Middle Atlantic

-

-

0.38

0.44

0.43

0.89

0.22

0.25

-0.01

East North Central

-

-

-

0.06

0.05

0.51

-0.16

-0.13

-0.39

West North Central

-

-

-

-

-0.01

0.45

-0.22

-0.19

-0.45

South Atlantic

-

-

-

-

-

0.46

-0.21

-0.18

-0.44

East South Central

-

-

-

-

-

-

-0.67

-0.64

-0.9

West South Central

-

-

-

-

-

-

-

0.03

-0.23

Mountain

-

-

-

-

-

-

-

-

-0.26

Pacific

-

-

-

-

-

-

-

-

-

Germany

New England

Middle Atlantic

East North Central

West North Central

South Atlantic

East South Central

West South Central

Mountain

Pacific

New England

-

1.39

1.69

1.37

1.54

1.87

1.5

1.33

1.34

Middle Atlantic

-

-

0.3

-0.02

0.15

0.48

0.11

-0.06

-0.05

East North Central

-

-

-

-0.32

-0.15

0.18

-0.19

-0.36

-0.35

West North Central

-

-

-

- <
/p>

0.17

0.5

0.13

-0.04

-0.03

South Atlantic

-

-

-

-

-

0.33

-0.04

-0.21

-0.2

East South Central

-

-

-

-

-

-

-0.37

-0.54

-0.53

West South Central

-

-

-

-

-

-

-

-0.17

-0.16

Mountain

-

-

-

-

-

-

-

-

0.01

Pacific

-

-

-

-

-

-

-

-

-

Ireland

New England

Middle Atlantic

East North Central

West North Central

South Atlantic

East South Central

West South Central

Mountain

Pacific

New England

-

-0.09

0.83

0.52

0.92

1.32

0.95

0.47

0.1

Middle Atlantic

-

-

0.92

0.61

1.01

1.41

1.04

0.56

0.19

East North Central

-

-

-

-0.31

0.09

0.49

0.12

-0.36

-0.73

West North Central

-

-

-

-

0.4

0.8

0.43

-0.05

-0.42

South Atlantic

-

-

-

-

-

0.4

0.03

-0.45

-0.82

East South Central

-

-

-

-

-

-

-0.37

-0.85

-1.22

West South Central

-

-

-

-

-

-

-

-0.48

-0.85

Mountain

-

-

-

-

-

-

-

-

-0.37

Pacific

-

-

-

-

-

-

-

-

-

(Republished from GNXP.com by permission of author or representative)
 
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Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at http://www.razib.com"