Sentences with phrase «terms of a linear trend»

You seem to be thinking only in terms of a linear trend.

Not exact matches

Finally, by substituting the historic linear trend above into the IRR term of this equation, and the industry average investment period of 13 years into the c term, we get the following formula, which shows that nominal R&D productivity / ROI currently stands at about 1.2 (i.e., we get only 20 % back on top of our original R&D investment after 13 years), is declining exponentially by about 10 % per year, and will hit 1.0 (zero net return on investment) by 2020:

There have certainly been some large El Nino events over the past couple decades, and this leverages any linear trend estimates of the long - term behavior (such as those shown in the recent Vecchi et al paper, which we'll be talking about more in a follow - up post to this).

The standard deviation of the residuals from a linear regression to annual averages 1975 - 2007 is 0.472, so we expect a range of variation of roughly + / - 0.94 deg.C from the long - term trend.

It is arguably impossible to accurately detangle a multidecadal oscillation from a long - term (probably not linear) forced trend in 100 years of data.

The long term linear trend (which is negative and has a slope of roughly 6 days per century) indicates that on average the break up dates have been coming earlier in the season.

There have certainly been some large El Nino events over the past couple decades, and this leverages any linear trend estimates of the long - term behavior (such as those shown in the recent Vecchi et al paper, which we'll be talking about more in a follow - up post to this).

Physical scientists are of course interested in explaining those as well as the long term, more linear at the moment trend.

Would this be the same J. Bob who used FFT (seriously complex stats) to «prove» that long - term cycles in the temperature record are more significant than the linear trend revealed by linear regression (one of the simplest stats there is)?

-- I'm not quite sure why you think I'm debating the validity (or lack thereof) of short term linear trends, as I'm clearly not.

Of course, as they point out «because rainfall is such a variable element, trend values are highly dependent on the start and end dates of the analysis» and the fact they are simply using linear interpolation it is very difficult to derive anything meaningful in terms of climate change from just one maOf course, as they point out «because rainfall is such a variable element, trend values are highly dependent on the start and end dates of the analysis» and the fact they are simply using linear interpolation it is very difficult to derive anything meaningful in terms of climate change from just one maof the analysis» and the fact they are simply using linear interpolation it is very difficult to derive anything meaningful in terms of climate change from just one maof climate change from just one map.

Leaving that aside, and also leaving aside the issues with fitting a 10th order polynomial to such «data» (lots of degrees of freedom...) what is becoming apparent to me is that there is a cyclical trend that can be linked to physical processes such as the PDO / AMO, as well as a long - term linear trend.

But the task at hand was to test Dan H.'s claim that the Berkeley data reinforce the characterization of temperature change as «long - term linear trend» or «linear - plus - cyclic.»

Talk about short term data — and the utter silliness of linear trends on this.

It's stated in the text, but understanding that the absolute deviation of the Earth's LOD from its long — term trend refers to the absolute value of the deviation from a linear trend fit, whatever the sign of the deviation.

In recent years, we also see that the annual temperature anomalies in each category have closely followed their long - term linear trends, as shown by the final frame of the GIF animation above:

The long - term linear trend of the equatorial Pacific SST anomalies are incredibly flat, meaning there is little trend.

As I understand it, your point is this: There is a long term linear trend in the data since 1970 and the recent cessation of a trend is merely random fluctuation around the long term trend.

Assuming for argument's sake that the IPCC's calculation of the long term trend was broadly correct, would you expect temps to rise in a more or less linear fashion or would you expect there to be periods when temps were flat or even falling?

This is lower than the observed ice extent in 2015 (4.63 M km2) and is lower than the extent expected from persistence of the long - term linear trend (4.66 M km2).

It's very common in science to see a linear trend with a cycle on top of it; you have to be careful when interpreting such a plot to know if what you're seeing is long - term change or short - term.

So it seems that filtering or not of the instrumental data in this way interacts with «something» that produces a linear long - term trend over the millenium.

«In response to those who complained in my recent post that linear trends are not a good way to compare the models to observations (even though the modelers have claimed that it's the long - term behavior of the models we should focus on, not individual years), here are running 5 - year averages for the tropical tropospheric temperature, models versus observations...»

That doesn't seem plausible to me, and I don't think your two disjoint graphs demonstrate a pressing statistical reason to believe that has to be the case, rather than the simpler explanation that we are seeing a long term linear warming trend, masked by a lot of variance.

In terms of going back prior to 1970 to identify a trend associated with global warming, it simply doesn't make any kind of sense to attempt to construct a linear trend in the time series for the last 100 years given the slight global cooling of the 1950's and 1960's.

In fact, you can get a very good fit with actual temperature by modeling them as three functions: A 63 - year sine wave, a 0.4 C per century long - term linear trend (e.g. recovery from the little ice age) and a new trend starting in 1945 of an additional 0.35 C, possibly from manmade CO2.

Fit a linear model (preferably with ARMA (1,1) noise as the noise process is autocorrelated), the trend is the slope of that linear model (i.e. the coeffcient of the linear term of the model).

As of now (or perhaps mor precisely, as of last week given the ESRL problems) the CO2 - rise is sitting at that unwobbled value (0.25 ppm / yr below the long term linear trend in CO2 - rise) but there does seem to be potential for one of those La - Nina - caused dips in the CO2 - rise numbers perhaps in parallel with the re-aligned +8 months ENSO dip.

Two contributors forecast a September minimum below that of 2007 at 4.0 million square kilometers and 3 contributors suggest a return to the long term downward linear trend for September sea ice loss (5.5 to 5.6 million square kilometers).