First, a series
of monthly temperature differences is formed between numerous pairs of station series in a region.
This is physically unrealistic in terms of the length - scale
of monthly temperatures (see Question 12), with the 1961 — 1990 mean difference between these sites being just 0.3 °C.
Linear regression
on monthly temperature data, for instance, will give you a reliable trend, but the estimated * uncertainty * that most computer programs compute for the regression fit will be way off.
Wondering how that cold spell compares to recent times, atmospheric scientists Susan Solomon of the National Oceanic and Atmospheric Administration's Aeronomy Laboratory in Boulder, Colorado, and Chuck Stearns of the University of Wisconsin, Madison, tracked the average
monthly temperatures over the last 15 years at a series of four automated weather stations located, by coincidence, along Scott's return route.
The greatest departures were found across portions of Virginia, the Carolinas, northern Georgia, and northern Alabama,
where monthly temperatures were 8 to 10 degrees F (4.4 to 5.6 degrees C) below average.
Here we show that, worldwide, the number of local record - breaking
monthly temperature extremes is now on average five times larger than expected in a climate with no long - term warming.
To summarize, there is a severe annual cycle in the UAH LT data set that results in a noticeable divergence in both the global and tropical
monthly temperature trends over the 1979 - 2008 period.
«We found that Hong Kong's urban mean air temperature has increased by 0.169 °C per 10 years over the past four decades
using monthly temperature data, or 0.174 °C per 10 years using annual temperature data, and...
The simulated effects of
changing monthly temperature and precipitation included a distinctive dieback of extant trees at most locations, with only partial recovery of biomass in areas of today's temperate deciduous forest.
Mean monthly temperatures also increased — from an average of about 30 degrees Fahrenheit during winter to about 64 degrees during summer, the researchers noted.
They say: «The algorithm starts by forming a large number of pairwise difference series between
serial monthly temperature values from a region.
You can then easily read off how
much monthly temperatures deviate from that average, which is called the temperature anomaly; if a month is colder than usual for that month in the data, that shows up as a negative anomaly.
A similar analysis performed on temperature found synoptically
derived monthly temperatures differ by as much as 0.5 °C from CLIMAT temperatures (M. Halpert, personal communication, 1992).
Bohr then merged the survey data with state -
specific monthly temperature averages collected by the National Oceanic and Atmospheric Administration's National Center for Environmental Information.
Daily records from Manhattan's Central Park show that average
monthly temperatures already increased by 3.6 degrees Fahrenheit from 1901 to 2000 — substantially more than the global and U.S. trends.