And the warming trend is just as evident when you look
at yearly temperatures and not just the decadal trends.
Not exact matches
From that year through 2012, Earth's
yearly average surface
temperature increased
at one - third to one - half the average rate from 1951 through 2012.
At approximately 1400 meters above sea level, Monteverde is cold, with an average
yearly temperature of 18 degrees Celsius / 64.4 degrees Fahrenheit
It has average
yearly coastal
temperature of around 24C during the day and 14C
at night - time.
My simple regression - based statistical climate model predicts global carbon dioxide, surface
temperature & sea level
at yearly time steps.
Yearly low
temperature plots
at Green Bay WI and Park Rapids MN exhibit increases of 5 to 11 deg F from the early 1900s to 2008 — as shown on data plots (link in # 193), from 10 year moving averages.
«Drawdown» refers to the point
at which greenhouse gas concentrations in the atmosphere begin to decline on a
yearly basis, and is the goal for reversing climate change and reducing global average
temperatures.
Slide 4 shows a power spectrum of
yearly temperature anomalies, and the inset to that figure in particular looks to show a sudden change in the measurement noise level right
at about 1941.
I'll look
at that web site (from where you provided the images) in more detail when I have a chance —
at a first glance, though, where they assert «that the satellite data is inconclusive regarding any discernible trends in the global
yearly average
temperature over the last 25 years», is a bit odd, given the > 95 % statistical confidence in warming over that time period (as per @ 30).
Shallow as it is, for me this is vindication after years of being laughed
at and called names for being a «Climate denier» in spite of citing studies by so many scientists and questioning the constant
yearly trend of «adjustments» made to the
temperature data NOAA kept posting regularly.
Look up two places
at the same latitude and altitude, you'll find the same daily or
yearly temperature (say Bangkok and Tombouctou).
Likewise, a statistician will not automatically be aware of the difference between proxies of low resolution (which may be good
at estimating average
temperature on a decadal or even centennial scale) and proxies of high resolution that are good
at estimating
temperature at a
yearly level.
The fourth reason the interior Antarctic data is important is because you need only to look
at the
yearly low
temperatures recorded.