4) the end results
on the bottom of the first table (on maximum temperatures), clearly showed a drop in the speed of warming that started around 38 years ago, and continued to drop every other period I looked / /... 5) I did a linear fit, on those 4 results for the drop in the speed of global maximum temps, versus time, ended up with y = 0.0018 x -0.0314, with r2 = 0.96 At that stage I was sure to know that I had hooked a fish: I was at least 95 % sure (max) temperatures were falling 6) On same maxima data, a polynomial fit, of 2nd order, i.e. parabolic, gave me y = -0.000049 × 2 + 0.004267 x — 0.056745 r2 = 0.995 That is very high, showing a natural relationship, like the trajectory of somebody throwing a ball... 7) projection on the above parabolic fit backward, (10 years
on the bottom of the first table (
on maximum temperatures), clearly showed a drop in the speed of warming that started around 38 years ago, and continued to drop every other period I looked / /... 5) I did a linear fit, on those 4 results for the drop in the speed of global maximum temps, versus time, ended up with y = 0.0018 x -0.0314, with r2 = 0.96 At that stage I was sure to know that I had hooked a fish: I was at least 95 % sure (max) temperatures were falling 6) On same maxima data, a polynomial fit, of 2nd order, i.e. parabolic, gave me y = -0.000049 × 2 + 0.004267 x — 0.056745 r2 = 0.995 That is very high, showing a natural relationship, like the trajectory of somebody throwing a ball... 7) projection on the above parabolic fit backward, (10 years
on maximum temperatures), clearly showed a drop in the speed of warming that started around 38 years ago, and continued to drop every other period I looked / /... 5) I did a linear
fit,
on those 4 results for the drop in the speed of global maximum temps, versus time, ended up with y = 0.0018 x -0.0314, with r2 = 0.96 At that stage I was sure to know that I had hooked a fish: I was at least 95 % sure (max) temperatures were falling 6) On same maxima data, a polynomial fit, of 2nd order, i.e. parabolic, gave me y = -0.000049 × 2 + 0.004267 x — 0.056745 r2 = 0.995 That is very high, showing a natural relationship, like the trajectory of somebody throwing a ball... 7) projection on the above parabolic fit backward, (10 years
on those 4 results for the drop in the speed of global maximum temps, versus time, ended up with y = 0.0018 x -0.0314, with r2 = 0.96 At that stage I was sure to know that I had hooked a fish: I was at least 95 % sure (max) temperatures were falling 6)
On same maxima data, a polynomial fit, of 2nd order, i.e. parabolic, gave me y = -0.000049 × 2 + 0.004267 x — 0.056745 r2 = 0.995 That is very high, showing a natural relationship, like the trajectory of somebody throwing a ball... 7) projection on the above parabolic fit backward, (10 years
On same maxima data, a
polynomial fit, of 2nd order, i.e. parabolic, gave me y = -0.000049 × 2 + 0.004267 x — 0.056745 r2 = 0.995 That is very high, showing a natural relationship, like the trajectory of somebody throwing a ball... 7) projection
on the above parabolic fit backward, (10 years
on the above parabolic
fit backward, (10 years?)