Sentences with phrase «as gistemp»

As the gistemp - method.

It is not clear whether the time series such as GISTEMP actually correct for this.

[Response: Actually, they are still in the range, and the Cowtan and Way paper (as well as the GISTEMP analysis) indicate that you need to be careful that you are comparing like with like.

Not exact matches

For instance, GISTEMP uses satellite - derived night light observations to classify stations as rural and urban and corrects the urban stations so that they match the trends from the rural stations before gridding the data.

GISTEMP assumes that the Arctic is warming as fast as the stations around the Arctic, while HadCRUT4 and NCDC assume the Arctic is warming as fast as the global mean.

You stated «The red line is the annual global - mean GISTEMP temperature record (though any other data set would do just as well),...

In GISTEMP both October and November came in quite warm (0.58 ºC), the former edging up slightly on last month's estimate as more data came in.

But he didn't show what you get using GISTEMP and he didn't show what would happen if (as is likely) 2009 is warmer than 2008.

As is well known, the 10 - year trend since the large El Nino is flat in HadCRUT and only 0.1 deg C / decade in GISTEMP.

In GISTEMP and HADCRUT, there are extremely few years that are not «statistically tied» (as in p > 0.05) with a prior year.

The match of the Hansen et al 1988 scenario B projections are similarly little affected (GISTEMP 1984 - 2008 0.19 + / -0.05 (LO - index) 0.22 + / -0.07 (Met - station index); HansenB 1984 - 2008 0.25 + / -0.05 ºC / dec)-- the projections run slightly warmer as one would expect given the slightly greater (~ 10 %) forcing in the projection then occurred in reality.

He kindly used the same approach for the HadCRUT3v data (pictured below) and I adapted it for the GISTEMP data as well.

Feb 2018 sits as = 112nd highest NOAA anomaly (= 42nd highest in GISTEMP, the difference from NOAA mainly down to the full arctic coverage).

Thus the coldest year of this century is, according to GISTEMP 2008, not 2000 as you assert.

For instance, GISTEMP uses satellite - derived night light observations to classify stations as rural and urban and corrects the urban stations so that they match the trends from the rural stations before gridding the data.

As is usual, today marks the release of the «meteorological year» averages for the surface temperature records (GISTEMP, HadCRU, NCDC).

CRU has 1998 as the warmest year but there are differences in methodology, particularly concerning the Arctic (extrapolated in GISTEMP, not included in CRU) which is a big part of recent global warmth.

GISTEMP assumes that the Arctic is warming as fast as the stations around the Arctic, while HadCRUT and NCDC assume the Arctic is warming as fast as the global mean.

As I understand it, the personal diplomacy that has gone into putting together HadCrut or GISTEMP has been pretty extensive.

For the GISTEMP and HadCRUT3, the trends are 0.19 + / -0.05 and 0.18 + / -0.04 ºC / dec (note that the GISTEMP met - station index has 0.23 + / -0.06 ºC / dec and has 2010 as a clear record high).

As it is the GISTEMP time series looks equivalent to a model scenario.

Regression analyses are performed as in Otto (2015), using natural and anthropogenic forcing timeseries (historical and the RCP8.5 scenario) with a regression constructed using data from 1850 - 2016 (for HadCRUT4), and from 1880 - 2016 (for GISTEMP).

Make (all) the data available and then, as in your example of GISTEMP, there can be no argument.

Just to add as an after thought, you could also add 6 month lag El Nino data to the Indo proxy, which could increase the correlation with gistemp, given that it would be a far cry to expect anything higher from something that occurred half a century ago, but there it is.

You're assuming that Hansen's projections use the same baseline as the current GISTEMP dataset, which is 1951 - 1980.

As far as I can see you got the tied for 10th highest GISTemp anomaly part right (I assume you have the Land - Ocean Temperature Index in mind, not the land only numbers) but my spreadsheet disagrees with your claim that the average anomaly for 2013 to date would put it in 3rd place — I get 9tAs far as I can see you got the tied for 10th highest GISTemp anomaly part right (I assume you have the Land - Ocean Temperature Index in mind, not the land only numbers) but my spreadsheet disagrees with your claim that the average anomaly for 2013 to date would put it in 3rd place — I get 9tas I can see you got the tied for 10th highest GISTemp anomaly part right (I assume you have the Land - Ocean Temperature Index in mind, not the land only numbers) but my spreadsheet disagrees with your claim that the average anomaly for 2013 to date would put it in 3rd place — I get 9th.

Plotting these temperatures as anomalies (by removing the mean over a common baseline period)(red lines) reduces the spread, but it is still significant, and much larger than the spread between the observational products (GISTEMP, HadCRUT4 / Cowtan & Way, and Berkeley Earth (blue lines)-RRB-:

The range is given by the spread of values from ERA - Interim, JRA - 55, GISTEMP, HadCRUT4, a version of HadCRUT4 infilled by kriging from Cowtan and Way, and NOAAGlobalTemp, processed as discussed here, and discussed further below.

The models overestimated warming from 1979 - 2011, but if you look at GISTEMP for example you can see that the East Pacific is cooler in 2011 than it was in 1979 and the models did not capture that as they have no PDO in the correct phase and are not expected to because PDOs are transient changes.

Posts at RealClimate (here) and at SkepticalScience (here) looked on the paper as the second coming of... errr... Hansen's GISTEMP maybe, saying Cowtan and Way (2013) proved the UKMO HADCRUT4 data underreports by half the warming of global surface temperatures since 1997.

I note with interest your calculation using GISTEMP data, but unless you are committing to the belief that the current low temperatures relative to trend represent an actual reduction in the trend rather than the effects of transient features such as ENSO fluctuations, using the actual temperature value will lead to a poor estimate of the further evolution of the energy imbalance.

However, the impact of coverage bias is pretty clear; it can be seen by simply looking at a coverage and anomaly map as we did here, or by assessment of coverage bias using GISTEMP, or by the less valid but independent assessment using UAH.

Citing the GISTEMP global anomally as he does, that should indicate that he is talking about global temperatures, but it turns out he is not.

As a side, note, the 1.35 C anomaly is relative to the GISTEMP baseline of 1951 - 1980.

CBDunkerson @ 4, I have previously caclulated that using the Mann 2008 EIV reconstruction and the 1736 - 1765 mean value as the «preindustrial» benchmark», the gives a preindustrial temperature 0.12 C lower than using the GISTEMP 1880 - 1909 mean.

(As with GISTEMP the anomaly periods must match, so both CRU and UAH map anomalies were baselines with respect to 1981 - 1990.)

As explained in Part 1A and Part 1B, the 1200 km area weighting scheme used by GISTemp is based on the known and observed phenomena of Teleconnection; that climates are connected over surprisingly long distances.

As someone familiar with both MBH and GISTEMP issues, the issues are entirely different.

As far as the correlation between GHGs and temperature goes, recent history already passes his r2 > 0.5 test with flying colours - the Mauna Loa CO2 data vs GISTEMP from 1961 - 2004 gets r2 = 0.76, and I'm sure that the Vostok ice core data must be in the same ballpark over ~ 400,000 years or more (a quick google finds multiple references to the strong correlation but no hard numbers and I can't be bothered doing it myselfAs far as the correlation between GHGs and temperature goes, recent history already passes his r2 > 0.5 test with flying colours - the Mauna Loa CO2 data vs GISTEMP from 1961 - 2004 gets r2 = 0.76, and I'm sure that the Vostok ice core data must be in the same ballpark over ~ 400,000 years or more (a quick google finds multiple references to the strong correlation but no hard numbers and I can't be bothered doing it myselfas the correlation between GHGs and temperature goes, recent history already passes his r2 > 0.5 test with flying colours - the Mauna Loa CO2 data vs GISTEMP from 1961 - 2004 gets r2 = 0.76, and I'm sure that the Vostok ice core data must be in the same ballpark over ~ 400,000 years or more (a quick google finds multiple references to the strong correlation but no hard numbers and I can't be bothered doing it myself).

For example, here are the various trends for the period from 1998 - 2012 (referred to in the IPCC report as the so - called «hiatus» period): NOAA (as in Science) 0.086 °C + / -0.075 (from the supplement) NOAA (previous - old) 0.039 + / - 0.082 (from the supplement) Compared with: GISTEMP: 0.066 + - 0.156 Berkeley: 0.108 + - 0.152 HadCRUT4 hybrid (of Cowtan and Way): 0.136 + - 0.181 http://www.ysbl.york.ac.uk/~cowtan/applets/trend/trend.html

As for GISTEMP, it has very well documented problems of it's own but that's another thread altogether.....

Figure 2 shows the number of station records available for each month in both the existing GHCN - Monthly data (used as the basis for reconstructions by GISTemp / NCDC / CRUTEM) and the new Berkeley data.

«2014 * is * the warmest year in the GISTEMP, NOAA and Berkeley Earth analyses,» he said, referring to different data sets kept by different groups of scientists, including the one kept by his center and known as «GISTEMP.»

You can take out data points you don't like, you can apply whatever correction factors you want (such as the one that Nasa's GISTEMP series uses to compensate for the dearth of measuring stations across the Arctic), and you can therefore end up with a temperature curve that might look a little different: but don't say it can't be done, because it can.

fyi: As far as I know, GIStemp itself was never peer revieweAs far as I know, GIStemp itself was never peer revieweas I know, GIStemp itself was never peer reviewed.

To be specific, the latest GISTEMP shows its peak height as approximately 0.5 degrees Celsius while satellites show the peak height as 0.9 degrees.

The problem is that I added that figure as an afterthought in the context of a discussion of what the year - end NASA GISTEMP surface temperature anomalies would be once the December measurements were in.

The value of the variance for the process noise in the above was arbitrarily chosen to be the same as the empirically estimated observational variance of the observations in the separate cases of the HadCRUT4 series and GISTEMP.

So, GISTemp is down 0.045 C since July 1998 taking into account the most important natural factors we know about (not up 0.24 C as predicted by the IPCC).

As the figure caption says, the ccc - gistemp result in the figure was produced using «software revision 700 ``.