Sentences with phrase «because giss»

You find It irrelevant to criticise Tsurf because GISS don't define it as their current dataset.

The global average from GISS warms faster than HadCRUT3 over the most recent decade because GISS extrapolate over the Arctic.

They only disappeared from GISS because GISS couldn't be bothered collating that data after 1992.

The reason GISS is higher in 2010 (and 2005) than in 1998 is because the GISS 1998 anomaly was, relatively speaking, much lower than the others.

It clearly appears that the temperature has a cyclical behavior that GISS corrections try to smooth out (because their GISS model does not reproduce it?).

Because the GISS analysis combines available sea surface temperature records with meteorological station measurements, we test alternative choices for the ocean data, showing that global temperature change is sensitive to estimated temperature change in polar regions where observations are limited.

Could it be because GISS is run by James Hansen, one of the most rabid of the warming doomsayers, and someone with a huge vested interest in showing temperatures as going high — very high?

Because GISS Model E-R incorporates the response of these proxies in its output, the authors of the PNAS study were able to compare their results directly to the historical record.

If the satellites are calibrated to the GISS results, they lose their provenance for an absolute accurate reading, because GISS is a joke at best.

Not exact matches

Anyhow, I question the validity of FFT analysis of the final GISS and HadCRUT3 temperature anomaly products — because they have been so «averaged» as to be suspect for that purpose.

However, the actual claim of IPCC is that the effects of urban heat islands effects are likely small in the gridded temperature products (such as produced by GISS and Climate Research Unit (CRU)-RRB- because of efforts to correct for those biases.

The obvious answer (from someone who is indeed receptive to arguments for lower - than - consensus climate sensitivities) is that it was on a par with recent hot years because temperatures at US latitudes of the globe really weren't as much cooler in the 1930s / 1940s (compared to the present) than GISS / Hadley's best estimates (from often sketchy global coverage) suggest.

But even that isn't really enough, because some of the models are closely related to each other (i.e. ACCESS and HadGEM2, or any of the GISS models).

This number increases to over 80 % if we repeat the analysis for the full data period in the GISS database (i.e., 1880 — 2009), rather than just the last 100 y, because the expected number for stationary climate then reduces from 0.105 to 0.079 according to the 1 ∕ n law.»

When the curve refused to look different from GISS, enthusiasm for the endeavor faded away — rather sad, because all of that painstaking effort expended to validate the GISS curve might have made an excellent journal article.

The trend of 0.12 °C is at first surprising, because one would have perhaps expected that the trend after gap filling has a value close to the GISS data, i.e. 0.08 °C per decade.

Finally I attempt a suggestion that perhaps one solution to the problem that the solar impact on climate is underestimated by models might be because EBM and GCM, like GISS, do not contain CO2 and CH4 cycle mechanisms that might be partially effected by the Sun, and other mechanisms are missing or uncertain (water vapor, cloud cover, vegetation, bacteria respiration, UV radiation, cosmic ray effects etc.).

Having said that, it is curious that email logs and holdings appear to function quite well within NASA, possibly because the infrastructure was set up and maintained beyond the managment scope of GISS, I suspect.

We're using GISS LOTI data because it's more spatially complete than the UKMO CRUTEM data (which is used in the HADCRUT4 data).

Do I believe GISS and HadCrut for the last 100 years because they have roughly tracked the satellite record for the last 29 years?

Bindidon It's not surprising that you give the fully discredited (because of data manipulations and the urban heat island effects) GISS Surface Temperature to support your fallacious point about it being hotter now than in the»30s.

WMO - «Because the data with respect to in - situ surface air temperature across Africa is sparse, a oneyear regional assessment for Africa could not be based on any of the three standard global surface air temperature data sets from NOAANCDC, NASA - GISS or HadCRUT4 Instead, the combination of the Global Historical Climatology Network and the Climate Anomaly Monitoring System (CAMS GHCN) by NOAA's Earth System Research Laboratory was used to estimate s

«Because the data with respect to in - situ surface air temperature across Africa is sparse, a one - year regional assessment for Africa could not be based on any of the three standard global surface air temperature data sets from NOAA - NCDC, NASA - GISS or HadCRUT4.»

If we compare there «land only», the situation does not differ much: — SH land UAH6.0: 0.142 — SH land GISS: 0.104 because here too, UAH's trend is higher than GISS (as opposed to the Northern Hemisphere, where GISS trends are way higher than UAH's, for both land + ocean and land - only).

For now I'm going to stick with the preindustrial baseline I have just because it's what I can calculate from the GISS data.

However, in order to see it you have to use the satellite temperature curve because in ground - based curves — GISS, NCDC and HadCRUT — they are showing a temperature rise instead of a temperature standstill there.

starts 2010 higher than GISS because of the El Nino.

Because they did not archive versions as they went (like GISS also does not) and their methods keep changing, it would not come out the same as when generated in Jan 2009.

And if you are measuring from 1980 then satellite data are the only reliable datasets because they just can not fiddle one year relative to another the way Giss / Had / CW do.

However, in order to see it you have to use the satellite temperature curve because ground - based curves — GISS, NCDC and HadCRUT — are showing a temperature rise instead of a temperature standstill there.

GISS or NCDC are preferred to HadCRUT because neither has a hole in the Arctic.

No one appears to be looking at this long term trend perhaps because - like - the hockey stick - the giss and hadley charts are so beguiling in apparently showing the start of the warming.

Both these datasets which in spite of being far more precise than the surfaced based data (because the physical biases of sampling are not present to the same extent in the satellite data), the HadCRUT3 dataset, the NCDC dataset and even the GISS dataset all are more or less consistent with the two satellite based datasets.

To point out just a couple of things: — oceans warming slower (or cooling slower) than lands on long - time trends is absolutely normal, because water is more difficult both to warm or to cool (I mean, we require both a bigger heat flow and more time); at the contrary, I see as a non-sense theory (made by some serrist, but don't know who) that oceans are storing up heat, and that suddenly they will release such heat as a positive feedback: or the water warms than no heat can be considered ad «stored» (we have no phase change inside oceans, so no latent heat) or oceans begin to release heat but in the same time they have to cool (because they are losing heat); so, I don't feel strange that in last years land temperatures for some series (NCDC and GISS) can be heating up while oceans are slightly cooling, but I feel strange that they are heating up so much to reverse global trend from slightly negative / stable to slightly positive; but, in the end, all this is not an evidence that lands» warming is led by UHI (but, this effect, I would not exclude it from having a small part in temperature trends for some regional area, but just small); both because, as writtend, it is normal to have waters warming slower than lands, and because lands» temperatures are often measured in a not so precise way (despite they continue to give us a global uncertainity in TT values which is barely the instrumental's one)-- but, to point out, HadCRU and MSU of last years (I mean always 2002 - 2006) follow much better waters» temperatures trend; — metropolis and larger cities temperature trends actually show an increase in UHI effect, but I think the sites are few, and the covered area is very small worldwide, so the global effect is very poor (but it still can be sensible for regional effects); but I would not run out a small warming trend for airport measurements due mainly to three things: increasing jet planes traffic, enlarging airports (then more buildings and more asphalt — if you follow motor sports, or simply live in a town / city, you will know how easy they get very warmer than air during day, and how much it can slow night - time cooling) and overall having airports nearer to cities (if not becoming an area inside the city after some decade of hurban growth, e.g. Milan - Linate); — I found no point about UHI in towns and villages; you will tell me they are not large cities; but, in comparison with 20-40-60 years ago when they were «countryside», many small towns and villages have become part of larger hurban areas (at least in Europe and Asia) so examining just larger cities would not be enough in my opinion to get a full view of UHI effect (still remembering that it has a small global effect: we can say many matters are due to UHI instead of GW, maybe even that a small part of measured GW is due to UHI, and that GW measurements are not so precise to make us able to make good analisyses and predictions, but not that GW is due to UHI).

Because CRU and GISS are anomaly based, any affect on these averages would affect the trends and vice versa.

Their belief came about because the optical physics of aerosols, originating from Sagan and introduced to climate modelling by his ex-students, Lacis and Hansen in 1974 at GISS / NAS, predicts the cloud part of «global dimming», the increase of albedo by aerosols supposed to hide present CO2 - AGW.

While I agree they are hardly neutral, the conversion to Python has been helpful, because they have added some comments, done a great job documenting a bunch of parameters, and made it generally a lot easier to follow the GISS code than what was possible with the spaghetti GISS published.

GISS and NCDC are nearly the same, because the average for the GISS baseline period (1951 - 1980) is nearly the same as that for the NCDC baseline (20th century).

If you were wondering why the official NOAA and GISS temperature plots look like the models, it's because they threw out any records that were too cold and inserted model warming.

«Because the data with respect to in - situ surface air temperature across Africa is sparse, a oneyear regional assessment for Africa could not be based on any of the three standard global surface air temperature data sets from NOAANCDC, NASA - GISS or HadCRUT4 Instead, the combination of the Global Historical Climatology Network and the Climate Anomaly Monitoring System (CAMS GHCN) by NOAA's Earth System Research Laboratory was used to estimate surface air temperature patterns»

BEST's data isn't different from GISS because it is GISS, sliced slightly differently.

Can a government agency be charged with RICO violations because James Hansen and GISS certainly being doing «criminal» activities to extort monies from the government research pool.

I chose that because a) there are nine runs available and b) the GISS model is one of the more complex models and c) it's one of the longest historical runs (n = 1488 months).

This question is of interest to me because I just took a look at the GISS EH model's historical runs.

The anointment of 2014 as the «warmest ever» year since 1880 is invalid because the NASA - GISS temperature scale they used is falsified.

GISS have deliberately chosen 1880 as their starting point because this time falls right in the «trough» of a nadir that effectively marked the end of the LIA and the planet's subsequent recovery from it.

Steven Goddard has amassed massive amounts of graphs and data evidence of fraud with GISS, NOAA, BOM ect., No one actually cares or is even looking at this study, Hopefully it is because no one cares about global warming anymore except a few warmist fanatics and skeptics etc... Only serious legal action funded by a wealthy skeptic or the like will actually make anyone notice that is the sad fact I'm afraid.

If GISS were able to determine exactly what the average global temperature was for any calendar year then you would not need statistical odds and probabilities because there would be no error.

Two examples leap to mind, alongside this stuff: WUWT posting the Daily Mail «u-turn by Prof Jones» story (though he was careful not to actually endorse that story, I note) and this bit of genius that Tamino took apart, where Watts had a guest who, unknowingly it seems, because they were so incompetent, took GISS data and turned it upside down.

Furthermore, because of the small number of samples and the high «noise» of the samples around the trends, the effective AR - 1 corrected 1 sigma error is 0.94 C for GISS, 0.42 C for CRUT, and 0.61 C for NCDC.