Geography and Climatology
Lecture 1
Summary
 Fair success may be achieved in deducing the location of
a place from a given small set of climatic data.
 The above success is achieved by using crude empirical
relationships between climate and geographic averages.
 Conversely, monthly mean temperatures can be
inferred approximately from geographic information.
 To what extent that these normative estimates differ
from actuality offers clues on the effects of regional
features of topography and ocean circulation on climate,
as well as on microclimatic effects.
Q: Is climate largely controlled by location, i.e. geography?
The Greek philosopher Pythagoras recognized the
sphericity of the Earth and the dominance of latitude in
explaining climate variation.
 Aristotle expanded on Pythagoras's foundation and
introduced five climate zones, ranging from tropical to
northern frigid.
 It is not coincidental that in the early 20th century
German scientist Koeppen also used 5 climate zones in
his climate classification (classified with the 5 letters
A-E).

Q: Is climate largely controlled by location, i.e. geography?
Koeppen's classification was developed at a time when it
was widely believed, especially in the German scientific
community, that climate (therefore geography)
determined flora and fauna, even the physical and
behavioral traits of human societies.
 Such determinism has its limitations, but it highlights the
widespread and longstanding belief that location
determines climate.
 Work done by Geiger (1960) indicates that even the
microclimate is largely controlled by the local
'geographical' conditions, such as orography and
coastlines.

Q: Is climate largely controlled by location, i.e. geography?
Given this control, therefore, one could hypothesize
that
one can infer the place where given climatic data
were obtained.
In other words,
can we work out the one or more locations where a
weather station may be, if we are given its climatic
record?
This is the key question addressed herein.
Main governing factors
1. hemisphere - which leads to warmer conditions, or,
in the Tropics (23.5S-23.5 N), to wetter conditions, in
either January (south) or July (north)
2. latitude - affects a) the annual mean temperature, b)
the annual range, c) the annual total rainfall (which is
least around the Tropics and near the poles), d) the
prevailing wind direction and strength
3. elevation - affects a) the annual mean temperature,
b) precipitation, and c) the daily range of
temperature
Main governing factors
4. sea surface temperature upwind - anomalously high
SSTs (for a given latitude) means warmth and rain
onshore - conversely, upwelling or cold water
advection stabilizes the atmosphere and inhibits
rainfall
5. upwind topography - an upwind mountain chain
implies drier conditions, but also colder winters,
because of easy advection of polar airmasses along
the mountain chain
6. local topography - e.g. low daily minima in broad
valleys, but higher ones in urban canyons; or reduced
daily maxima near large bodies of water on account of
a lake breeze.
The seasonal march of global sea surface temperature
The above mentioned 6 factors suggest that the
following climatic/geographical information should
be sufficient in providing the guidelines about
climate as a function of geography.
1. Annual mean temperature
2. Monthly mean temperatures (possibly reduced to
annual temperature range)
3. Monthly-mean daily temperature range (or merely
its annual mean)
4. Monthly mean precipitation
5. Distance inland, relative to the prevailing surface
wind direction
6. Local topographic information
1. Annual mean temperature
1. Annual mean temperature
1. The annual mean temperature is given approximately
by the average temperature of the maxima and
minima for the warmest and coldest months.
2. This temperature varies primarily with latitude,
although warm and cold ocean currents can be also
identified.
3. The western ocean margins (i.e. near the east coast of
a continent) are warmer around 20-30° (in both N.H.
and S.H.), but they are colder around 40-50° N, when
compared to the eastern margins (west coasts).
4. Also, subtropical deserts are distinctly hot, on average.
1. The zonal averaged annual mean temperature
Thick curve lines: observations
Thin straight lines are the linear regression lines.
1. The zonal averaged annual mean temperature
1. The zonal averaged annual mean temperature is
around 27 C within 20 S - 16 N degrees and then
falls by about 0.85 K/degree latitude in the N.H. and
0.63 K/degree latitude in the S.H.
2. This implies that on average the S.H. is warmer than
the N.H. (roughly 17C vs. 11C, respectively).
3. The above statement is true, only if the Antarctic
plateau stations are excluded. These stations, 3040K colder than the curve, suggests on account of
their altitude and their isolation within the
circumpolar vortex.
the water in S.H. is more salty than in N.H. (exception occurs
in the North Atlantic Ocean)
1. The zonal averaged annual mean temperature
4. A mean temperature of 19C in the N.H. is likely to be
found at sea level at about 25N (i.e. 16 + [27 19]/0.85).
5. However, (i) a lower latitude is possible if the place is
elevated or near a cold ocean current; (ii) a place
1,000 metres high may be 4 K cooler on average than
another at sea level at the same latitude.
6. A temperature of 19C may be found below 16N at
2,000 m elevation (i.e. 27 - 2,000x4k/1,000]).
7. Choosing between these alternatives is facilitated by
considering the annual range and monthly rainfalls.
2. Annual temperature range
1. [Definition] Difference between the hottest and coldest
months, taking monthly mean temperatures in each case.
2. Over land, it is given approximately by the difference
between the average of the January minimum and July
maximum temperatures. This difference is called the
apparent annual range. [Q: How about over the ocean?]
3. The error in assuming that the January and July
temperatures are the coldest and warmest (or vice versa in
S.H.) is small at latitudes above about 40 degrees
4. Data from Africa, South America and Europe show that the
true range exceeds the apparent range on average by
about 1 K at latitudes 0 - 10, 1.5 K over 11 - 20 and 0.5 K
over 21- 40 degrees.
Annual Range of Surface Temperature
陸性率 (Continentality) =
(1.7 A) / sin(Φ + 10) – 14
(V. Conrad formula)
海性率 (Oceanicity)
= (Toct - Tapr) / A
2. Annual temperature range
5. The 11-20 degree belt generally experiences a wet season in
summer, cloudiness and rain thus reduce the Tmax. The
hottest month usually falls 1-2 months before the summer
solstice (i.e. April or May in the N.H.), when the noon sun is
near the zenith and the skies are often clear.
6. Many places near a west coast in the 21- 40 degree belt are
affected by low sea surface temperatures due to upwelling of
deep-ocean water, and this upwelling is often most intense in
summer. Therefore, the warmest month here may be a few
months after the summer solstice, e.g. September in the
northern hemisphere.
7. A small annual range indicates (i) either a low latitude and/or
(ii) proximity to the sea, especially on the coast facing the
prevailing wind.
Example:
Variation of the
annual temperature
range over South
America
2. Annual temperature range
0
4
Questions:
1. Why?
2. Any consequences?
0
4
8
12
2. Annual temperature range
Empirical relation between
latitude (A, x-axis) and annual
temp. range (R, y-axis): TR = 0.4 A.
(This is Only a first order
approximation)
2. Annual temperature range
Refinement: the effect of
distance from sea (and/or
the prevaling wind direction)
needs to be considered.
Tr = 0.13 A d0.2
d: distance
downwind from
the sea
How far is the beach?
d = [Tr / 0.13 A]5 km
3. precipitation
Rain on earth can be triggered by any of 4 uplift
mechanisms (or a combination):
1. orographic: forced ascent of the low-level flow over
mountains;
2. convective: spontaneous ascent due to local static
instability (This is due to surface heating and moisture
convergence, and is found mainly at latitudes of 30
degrees latitude or less, but occurs up to 60 degrees
in summer over the continents.);
3. Convergence: air is no where to go in low latitudes
4. frontal: uplift over frontal surfaces and in lows is due
to baroclinic instability, i.e. to the interplay of warm
and cold airmasses.
3. precipitation
1. A wet summer and dry winter suggests a low-latitude
zenithal-rain or monsoonal climate.
2. The former, zenithal rain, is due to latitudinal shifts of the
I.T.C.Z. The latter, monsoonal regime differs only from the
more general zenithal-rain climate by the requirement that
the surface winds change direction at least 120° between
seasons, according to Ramage (1970).
3. Monsoons generally occur between 10-30 degrees of the
equator, but over a few degrees further north in late summer
over India, and, especially, southern China.
4. Frontal precipitation falls at latitudes between about 35-70
degrees, but lower in winter. Between 30-40 degrees, mainly
at west coasts, the rainfall in winter is much greater than in
summer. This is because fronts stay poleward in summer.
3. precipitation
5. Rainfall is more uniformly distributed along east coasts
and in the interior, not because fronts penetrate into
these regions in summer, but because of convection.
6. The global average rainfall is 860 mm/yr, averaged over
oceans and land together. Precipitation is heaviest near
the I.T.C.Z. and in areas where monsoon winds come
from over a warm ocean.
7. Arid conditions are generally found in the subtropics
(mainly between 18-33° ) (except where the Trade
winds blow onshore or where the monsoon penetrates
further poleward) and near the poles.
8. Precipitation increases with elevation on the windward
side of mountains up to about 2,000 meters, and then
decreases with height (why?).
3. precipitation
9. Rainfall is less on the leeside, as in the case of the
Patagonian desert in Argentina, to the east of the
southern Andes, where the wind is from the west. It is
also less in the Gobi desert in Mongolia, not only because
monsoonal moisture is trapped by the Tibetan plateau,
but also because frontal systems have lost most of their
moisture on their long travel from the Atlantic.
10. Dry conditions thus imply (i) a subtropical or polar
latitude, (ii) an extreme elevation, (iii) a rain shadow,
situation near an anomalously-cold ocean (e.g. the
Atacama desert in northern Chile) and/or (iv) great
distance downwind of the ocean.
11. Dry conditions are indicated not only by low rainfall
figures but also by a large daily range of temperatures.
1.
2.
3.
4.
4. daily temperature range
[definition] the difference between the maximum and
minimum temperatures in 24 hours. It has no meaning at
latitudes above 66.5 degrees, where the Sun does not
appear for 24 hours during the winter solstice.
If the daily range is large, the atmosphere is dry and
there is little cloud, probably indicated by low rainfall
figures.
Thus a large range may indicate (i) a position well inland,
(ii) considerable elevation above cloud level, and/or (iii) a
latitude near the Tropics, where anticyclones are
common.
Within anticyclones the air is dry and the sky often cloudfree; also, there is little wind, allowing the build-up of a
strong nocturnal radiation inversion.
4. daily temperature range
5. Near the ITCZ and in areas frequented by frontal
systems, not only does cloudiness limit daytime
heating and nighttime cooling, but also, the air is too
humid to cool much at night (near the ITCZ) or too
windy (at mid-latitudes).
6. There appears to be no systematic variation of the
annual mean daily range with latitude, because of the
annual movement of the ITCZ, and the key
dependence of a station's location on a continent.
4. daily temperature range
Daily ranges at various elevations. The horizontal lines show the median
values for each band of elevations
4. daily temperature range
7. The effect of the station elevation (h, in km) can be
isolated: there is a slight tendency for the daily range
to be given by Rd = 8 + 2 h
8. This equation means that a range of 12 K, say,
suggests an elevation of 2 km, i.e. [12 - 8] / 2 .
However, it would be better to use Figure directly, as a
guide to Rd; in that case, the deduced elevation for a
daily range of 12 K would be about 1 km.
9. The broad scatter in Figure is not surprising: a place
on the windward side of mountains has a much
smaller daily range than a place at the same elevation
on the lee side.
Remarks:
 A rough connection
between rainfall P
(mm/month) and daily
range is shown in the right
figure, yielding the very
approximate equation  Rd = 13.5 - 2 log P
 Estimates of Rd from rain
may be compared with
that from the relationship
with elevation.
 Unfortunately, formula is
of little use for estimating P,
not only because of the
great scatter seen in Figure,
but also because of the
formulas nature; a small
error in Rd leads to a huge
difference to the value of
P.
5. Surface wind
The prevailing wind direction is important in
determining the climate because it
(i) affects whether the incoming wind is cooled by an
west-coast ocean current,
(ii) governs whether or not a place is dry because it is
far from the upwind ocean (as in the Gobi desert,
for instance),
(iii) determines whether a place is dry because it lies
in the lee of a high mountain range or wet because
the wind has lately come from a warm ocean.
5. Surface wind
 The direction of the wind depends primarily on the
latitude, which is assumed already assessed from
consideration of the annual temperature mean and
range, and precipitation.
 As you have noticed, winds tend to be light and variable
from the equator to about 10 degrees latitude, generally
easterly and steady over 10 - 25 degrees, variable
between 25 - 35 degrees, mainly westerly but variable
over 35 - 60 degrees, variable between 60 and 70
degrees, and easterly nearer the pole.
How can one proceed to estimate the location
of the place with a given climate by calculating
the annual mean temperature, the annual
range and daily range, and by examining the
rainfall figures?
Example 1
A place with an annual average temperature T of 12° C, a
January/July difference of 3.5 K and rainfall of 163 mm in January
and 5 mm in July. The daily range is 13 K in January and 22 K in
July, i.e. around 17 K throughout the year.
1. The higher temperatures in January show that the place is in
the S.H.
2. The value of T implies a sea-level place around 36 degrees
latitude [i.e. (27-17)/0.63 + 20]. Or it might be at a lower
latitude and either greater elevation or located near a west
coast. Of these options, a coastal location seems unlikely
because the daily ranges are high, i.e. the air is dry, especially
in winter. So the place may be elevated, at a latitude less than
36 degrees.
Example 1
A place with an annual average temperature T of 12° C, a
January/July difference of 3.5 K and rainfall of 163 mm in January
and 5 mm in July. The daily range is 13 K in January and 22 K in
July, i.e. around 17 K throughout the year.
3. A lower latitude is also indicated by the difference between
the wet summer and dry winter, which suggest zenithal rain,
and a location between about 8-16° S. In addition, the
apparent annual range of about 3.5 K yields a rough estimate
of about 9° S, i.e. 2.5 x 3.5. There the true annual range is
roughly one degree more than the apparent range, i.e. 4.5 K in
the present case, and so the estimate of latitude becomes 11
degrees, i.e. 2.5 x 4.5.
Example 1 (cont.)
A place with an annual average temperature T of 12° C, a
January/July difference of 3.5 K and rainfall of 163 mm in January
and 5 mm in July. The daily range is 13 K in January and 22 K in
July, i.e. around 17 K throughout the year.
4. The sea-level temperature at that latitude would be about
27° C. Consequently, a mean temperature of 12° C would be
found at 3.7 km, i.e. (27 - 12)/4 . Such an elevation accords
with Figure, which suggests above 3 km for a daily range of 17
K.
5. The formula for the distance inland (based on the apparent
range) yields a figure of about 100 km if the latitude is 11
degrees, i.e. [3.5/{0.13 x 11}]5 .
6. Thus we estimate a place around 11° S, 3.7 km high and
roughly 100 km from the coast. It is actually Cuzco in Peru, at
13° S, 3.2 km high, and about 350 km inland.
Example 2 (an opposite estimate)
Determination of approximate temperatures given locale is also
possible. For instance, take Chicago, which is at 42° N, 250 m
elevation and about 3000 km downwind of the Pacific ocean (but
only 1400 km from the Gulf of Mexico).
1. The sea-level temperature is estimated to be 5° C, i.e. (27 - 0.85 x
[42 - 16]) .
2. However, the height means that the value has to be reduced to
4° C, i.e. 8 - 250 x 4/1000. The formula for the annual range shows
it to be 23-27 K, i.e. 0.13 x 42 x d0.2, where d is either 1400 (less
common) or 3000 km (more common).
3. Thus the January and July monthly mean temperatures
would be about (4 - 26/2) and (4 + 26/2), respectively,
i.e. -9° C and 17° C. The observations are -4° C and 23° C,
both about 5 K higher than the estimates. This is
warmer than expected (why?)
Example 2 (an opposite estimate)
Determination of approximate temperatures given locale is also
possible. For instance, take Chicago, which is at 42° N, 250 m
elevation and about 3000 km downwind of the Pacific ocean (but
only 1400 km from the Gulf of Mexico).
4. It is harder to derive the daily range because of the large
scatter in Figure. For what it is worth, the estimate from Figure
is 13 K, which is more than the observed values of 8 K in both
January and July.
5. We hypothesize that the daily ranges are reduced by strong
winds in winter and the high humidity in summer.
Conclusions
1. Above examples illustrate how far empirical
relationships between elements of climate and
geography can be used to estimate either location or
climate from the other.
2. It is interesting to see how much can be deduced,
even when ignoring local circumstances.
3. Ideally, the procedures for estimating either
geography or climate norms from the other would be
simplified into the format of a decision tree.