Sentences with phrase «short term variability»

The models aren't good enough to capture all the causes of short term variability.

Elsewhere in the article, he uses short term variability alone in support of no climate change (few hurricanes this fall).

It is easy to see that unpredictable weather noise dominates short term variability.

To begin with the last statement, the idea that global warming has stopped is a common misunderstanding, based on confusing short term variability with the long term underlying trend.

The longer record reveals short term variability amidst the long term warming trend.

However, the temperature record is very noisy with lots of short term variability.

It is easy to see that unpredictable weather noise dominates short term variability.

Please explain how you accounted for short term variability in your over effort at verification here (other than to say they don't mater when looking at trends):

The main point is that just as surface temperatures has experienced periods of short term cooling during long term global warming, similarly the ocean shows short term variability during a long term warming trend.

This means in the Arctic region, GISS data is relatively coarse grained, as individual grid cells above 80N may include station data interpolated out to as much as 1200 km, and are likely to show the higher short term variability which is characteristic of data from individual Polar stations.

The more they keep emphasizing that the model can't be proven wrong by short term variability, the more they emphasise that we have to wait a long time before we know whether their models are right.

* The variability shown in the uptick from 1900 looks unusual only because an instrumental temperature record - which captures variability - is now used, whereas the long term paleo reconstruction proxies previously used, do not have this ability to capture short term variability and thereby present an impression of a «stable» climate.

(Short term variability really is the gift that keeps on giving).

You distinguish between within day variability, within season variability and short term variability due to e.g. large scale weather systems.

In fact, if you plug an artificial data series with a long - term trend in it, that trend gets wiped out completely, leaving just shorter term variability behind.

Forecasts can only be tested against future temperatures over time scales sufficiently long to be largely outside the range of shorter term variability.

Your first differencing removes the trends for the large part and so restricts you to short term variability — much of which is related to hidden variables in your analysis (i.e. ENSO, volcanic AOD etc.), thus causality is going to be tricky.

The changes in latent in sensible and latent heat flux from ocean to atmosphere that occur during El Nino (greater flux) and La Nina (lower flux) are of course key to understanding the short term variability in tropospheric temperatures.

Im mostly interested in shorter term variability (daily / intraseasonal / interannual), so I don't need a deep ocean circulation.

You can easily see the short term variability, but also the long term downward trend is quite clear.