Sentences with phrase «means the temperature data»

I believe that analysis of temperature and dewpoint data at NOAA NWS cooperative climate station locations, many stations with more than 110 years of daily maximum minimum and mean temperature data, has great value which is not being fully utilized by scientists and the public.

Indeed, there's a world of difference between citing one paper that has done something that MIGHT rebalance the global mean temperature data — as Joe's post suggests — and then assuming that the problem is fixed and the indicator remains the first best only way to measure global goals despite the fact that natural variability in the global mean surface temperature will also make that a sluggish measure.

Rate of global sea - level rise based on the data of Church & White (2006), and global mean temperature data of GISS, both smoothed.

I picked three high - altitude stations and summarized the June - July - August mean temperature data from NOAA.

The global mean temperature data shows a 60 - years cycle as shown in the following graph.

Being ahead of the trend means the temperature data can stop increasing and yet the warming trend continues until it «catches up» with the data.

However, I offer you below my interpretation of the global mean temperature data so that you can attack it instead (play the ball, not the man).

My description is much, much better than IPCC's description of the global mean temperature data shown in the following graph = >

Abstract We study trends and temporal correlations in the monthly mean temperature data of Prague and Melbourne derived from four state - of - the - art general circulation models that are currently used in studies of anthropogenic effects on the atmosphere: GFDL - R15 - a, CSIRO - Mk2, ECHAM4 / OPYC3 and HADCM3.

However, the average daily mean temperature data at Minneapolis shows that from the first of the month up to this morning, only 3 of the days in August have been below normal.

Not exact matches

That means researchers have less information and higher uncertainties when it comes to translating the data into measurements that the models can use, such as air temperature and humidity.

«We really can't detect these changes yet in the existing data in the way we can detect in changes, for example, in the global mean temperature,» he said.

The study took data on the rise in temperatures over the most recent decades, and worked out what this means for the coming decades.

Underwater temperatures are much more variable, and it may take decades of data to reveal a significant change, so we're not sure if this means that we just don't have enough data to detect it yet.»

The analysis of high - frequency surface air temperature, mean sea - level pressure, wind speed and direction and cloud - cover data from the solar eclipse of 20 March 2015 from the UK, Faroe Islands and Iceland, published today (Monday 22 August 2016), sheds new light on the phenomenon.

«The first step was to reconstruct the history of global mean temperatures for the last 784,000 years, using combined data from marine sediment cores, ice cores, and computer simulations covering the last eight glacial cycles,» said Friedrich, a post-doctoral researcher at IPRC.

Lord Monckton made up data on atmospheric CO2 concentration and global mean temperature that he claimed were IPCC predictions.

Just on the off - chance the 3rd comment is serious: Pluto has not been observed for a full orbit, so we have no data on secular changes in its mean temperature.

However, comparison of the global, annual mean time series of near - surface temperature (approximately 0 to 5 m depth) from this analysis and the corresponding SST series based on a subset of the International Comprehensive Ocean - Atmosphere Data Set (ICOADS) database (approximately 134 million SST observations; Smith and Reynolds, 2003 and additional data) shows a high correlation (r = 0.96) for the period 1955 to 2Data Set (ICOADS) database (approximately 134 million SST observations; Smith and Reynolds, 2003 and additional data) shows a high correlation (r = 0.96) for the period 1955 to 2data) shows a high correlation (r = 0.96) for the period 1955 to 2005.

The uncertainties associated with reconstructing hemispheric mean or global mean temperatures from these data increase substantially backward in time through this period and are not yet fully quantified.

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

Data of climate variables (mean precipitation; mean temperature; mean ground frost frequency) at monthly intervals (1961 - 90) were sourced from the IPCC (http://www.ipcc-data.org).

After consideration of a range of elements of the water - energy dynamic (Hawkins et al., 2003), we made use of quarterly climatic data of 1961 - 90, mean annual precipitation and mean temperature (New et al., 1999).

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Using long - term data from the U.S Historical Climatology Network (USHCN) and preliminary data from the Climate Division Database, the U.S. nationally averaged temperature during October was 56.9 °F (13.8 °C) which was 2.1 °F (1.2 °C) above the 1901 - 2000 long - term mean, tied for 9th warmest on record.

When differences in scaling between previous studies are accounted for, the various current and previous estimates of NH mean surface temperature are largely consistent within uncertainties, despite the differences in methodology and mix of proxy data back to approximately A.D. 1000... Conclusions are less definitive for the SH and globe, which we attribute to larger uncertainties arising from the sparser available proxy data in the SH.

How much UHI contamination remains in the global mean temperatures has been tested in papers such as Parker (2005, 2006) which found there was no effective difference in global trends if one segregates the data between windy and calm days.

The adjustments are unlikely to significantly affect estimates of century - long trends in global - mean temperatures, as the data before, 1940 and after the mid-1960s are not expected to require further corrections for changes from uninsulated bucket to engine room intake measurements.

This means that for the first time a large number of models can be readily tested against temperature data recorded AFTER those models were finalized.

Joe cites to a very recent article that re-estimates global mean temperature in two ways that might offset some of the bias for under - sampling the arctic in one existing global data set.

(B) Records subdivided by those that extend 2000 years (n = 17) versus shorter records (n = 6), along with the 10 - year - mean Arctic - wide summer temperature through 2000 from the CRUTEM3 data series (14)(red line).

If you want a really really simple statistical climate model, try correlating global mean annual temperature & / or sea level with the CO2 data from Mauna Loa.

Does that mean the global mean surface temperature trends over the 20th Century, or just that some 20th Century data is used?

All of the radiosonde data are measuring the tropospheric temperature trend under the same noisy (i.e., weather) conditions, so we can usefully calculate the overall mean AND standard deviation of the means.

Since they were «always there» and happened to be the same ones in the sunspot data, and the ones in the sunspot data were the same ones noted in the literature for sun phenomena as having physical basis, I assumed they probably were physical reality in the temperature data (doesn't mean they were though).

More than 95 % of the 5 yr running mean of the surface temperature change since 1850 can be replicated by an integration of the sunspot data (as a proxy for ocean heat content), departing from the average value over the period of the sunspot record (~ 40SSN), plus the superimposition of a ~ 60 yr sinusoid representing the observed oceanic oscillations.

I translate this as effects of La - Nina starting from a higher energy atmosphere, corresponding to overall higher temperatures throughout the atmosphere at the beginning and the end of a LaNina (not necessarily measured fully measured by conventional means due to lack of data resolution).

Large variability reduces the number of new records — which is why the satellite series of global mean temperature have fewer expected records than the surface data, despite showing practically the same global warming trend: they have more short - term variability.

The attribution study was based on series of 5 - yr - mean temperatures and spatial averages of 90 degree sectors (i.e. to four different sectors), where sectors and periods with no valid data were excluded.

If you're talking about global mean temperature I would advise you to compare the projections of the IPCC to the actual measurements of GISS as well as HadCRUT, RSS MSU, and UAH MSU measured data.

Nevertheless, information from independent data suggest an increase in global mean temperatures even over the last decade.

So far, the data suggest it is a more responsive measure, but of course OHC alone is inadequate — not least because of coverage issues that are even worse than the GMT [global mean temperature] data sets.

The graphs compare the global mean temperature estimated by the models with that estimated from the data.

I therefore assume that the data from Cowtan & Way is the methodologically best estimate of the global mean temperature which we currently have.

This can be done a number of ways, firstly, plotting the observational data and the models used by IPCC with a common baseline of 1980 - 1999 temperatures (as done in the 2007 report)(Note that the model output is for the annual mean, monthly variance would be larger):

The figure to the left shows the spatial mean temperature over all grid boxes in the HadCRUT3 data set that have continuous monthly coverage over the 1901 - 2008 period.

Mean temperature, mean monthly precipitation, frequency of hot / cold days / nights, and indices of extreme precipitation are all estimated for each country based on observed and modeled data.

Then as other data accumulate, data like the time series of global mean temperature, you can compute the posterior distribution given the new data.

I meant that mean temperature of the world has developed (according to the data to date) differently from forecast (or «anticipated») by scenarios A and B. It's almost as if the increased CO2 since 1988 has had no effect.

I made temperature plots from the reanalysis 2 (NCEP / DOE) data for the North Pole (actually a zonal mean at 88.5 ° N; there's no grid point at the pole) and for the zonal means at 85 ° N, 81 ° N and 75 ° N (excluding land and the last also excluding the always ice - free parts of the Atlantic).