Part 1:
b. It looks like there is a trend that is making a “U” shape
on the graph because it was high around 1910 and was high two years ago two. It
seemed to dip significantly in the 40’s, 50’s and 60’s. This year is slightly
colder than last year according to the graph. It looks like this year is
actually very close to the average. The average is 41.6° F and this year is
around 42° F.
f. The top ten coldest years were 1917, 1904, 1950, 1924,
1951, 1912, 1929, 1972, 1907, and 1979. The top ten warmest years were 2012,
1931, 1998, 1987, 2006, 1921, 1999, 2001, 2005, and 2010.
g. Letters a-f directly relate to the climate change debate
because the data that we looked at spans the known weather/climate data that
has been collected to the current time frame. When looking specifically at
March we have been getting colder over the past few years with a few incredibly
high temperatures. The trend also appears to be on a rise in temperature. Then
looking at precipitation models it is apparent that this past year was much
lower than the average. It appears that there is a slight trend to having less
precipitation now though too which would make sense if the temperatures are
colder, but they fluctuate so much from year to year. Also, when looking at the
yearly tops and bottoms for temperature one can notice that the temperatures
that have been the highest are generally in the 90’s, 2000’s and later while
the coldest are in the early 1900’s. Society may rely on the politicians
motives to make a poor or good decision, which is the worst choice because it
is all second hand knowledge.
a.
b. The temperature appears to be highest in July and August
in both cities. The max temperature in Milwaukee was 70.9° and had a low of
18.9°. Madison had a high temperature of 71 with a low of 16°. Precipitation
on the other hand varied slightly more
from city to city. Milwaukee received a lot more precipitation in spring while
Madison received more in the summer. The max rain fall was 4 inches in
Milwaukee with a low of 1.5. The max rain fall was 3.7 in Madison with a low of
1.1.
a. Minneapolis: Precipitation: 2.04 Snow Fall: 7.0, Month to
date
Eau Claire: Precipitation: 2.67 Snow Fall: 9.1, Month to
date
La Crosse: No records are currently available
The values are slightly different from Minneapolis to Eau
Claire, but La Crosse has no data. They may differ because of the distance
between the cities and their microclimate. This could be a problem in my report
because the dates are different when comparing snow fall and precipitation and
even from city to city. This doesn’t give us a completely accurate comparison
when looking at the entire year.
a. The records are mostly collected from 1961 to 1990, but
there was one anomaly that was 1949 to 1995. This could be a problem because
the data isn’t current.
B & c.
5. It is important to compare climographs from different
locations within a state or region because microclimates can be present
throughout a small stretch. The differences in climate from one city to another
can be paramount in figuring out what their climate may be like in a certain
month. The changes in precipitation from month to month may be even more
interesting though because it shows the subtleties that are present in the
movement of weather.
6. Some variables that could be influencing the difference
in weather from our location to others include topography, lake effect, vicinity
to a river, and the continental effect. Topography can effect precipitation
because if there is a place of high elevation near a city then they could
potentially receive more precipitation from being on the leeward side. The lake
effect generally stabilizes a climate and can create less variation in both
temperature and precipitation. Eau Claire is in the middle of nowhere
essentially, so its microclimate will be much more varied. A vicinity to a
river could also impact temperature and precipitation too since rivers have
watersheds which collect water. Finally, being in the middle of a continent
compared to being near a body of water can affect the climate of a region
because temperature and precipitation can vary a lot more due to the unpredictable
nature of weather patterns in the continent.
7. The data could
potentially vary from year to year in the data collection. For instance, some
of the data that was collected on the site was taken from 1945 through 1995
while others were taken from 1961 through 1990. The collection of the data
could also be different depending on how they collected it from each place.
Some of the cities collected at air ports while others did it on hills. This
could vary the data as well because of height and canopy cover.
Part 2:
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