Sentences with phrase «subset of stations»

If you really want to draw conclusions about an entire data set (ie, from all the stations) from a subset of the stations, then you have to do proper random sampling of many of those stations (the greater the number, the higher the confidence in the result, of course).

NASA does a UHI CORRECTION for a SUBSET of stations

Doing so using satellite imagery is a practical approach, although it needs some sort of validation over a subset of stations to check if the results are robust.

On climate, this same problem shows up when we have «The GLOBE is warming» vs «This subset of stations warms and these others do not.».

Written by a NOAA National Climatic Data Center scientist, it examined only a small subset of stations — all that had their siting checked at that time — and found no bias in long - term trends.

This approach also afforded Berkeley the opportunity to generate the result using subsets of station data.

(2010) did this with the homogenized data from different subsets of stations, and found very strong correlations with the entire USHCN dataset (r2 = 0.98 for Tmax, and r2 = 0.96 for Tmin).

Not exact matches

For a subset of 14 relatively clear (cloudy) stations, the mean temperature drop was 0.91 ± 0.78 (0.31 ± 0.40) degrees C, but the mean temperature drops for relatively calm and windy stations were almost identical, indicating that cloud cover has a much greater effect than wind on the air temperature's response to an eclipse.

The Berkeley researchers developed their own statistical methods so that they could use data from virtually all of the temperature stations on land — some 39,000 in all — whereas the other research groups relied on subsets of data from several thousand sites to build their records.

I think I have read of analyses of some subset of the continental U.S. stations that are of high quality, called GHCN or something like that.

fahutex says: January 10, 2016 at 6:10 pm: I think I have read of analyses of some subset of the continental U.S. stations that are of high quality...... Yes, it's called the CRN, Climate Reference Network.

In the rural subset of U.S. stations, the recent warm temperatures aren't actually that unusual, and it seems that it was at least as warm in the 1930s.

Because of differences among the start, end and total length of the station records they examined, the authors decided to perform their analyses on three subsets of the data.

In describing their findings, Do et al. report that across all three subsets of data, «more stations showed statistically significant decreasing trends [in streamflow] than statistically significant increasing trends,» which finding held regardless of whether the stations were filtered by the presence of dams or changes in forest cover.

Muller et al., 2011 found that the linear trends of the Unadjusted records for stations with Ratings 1, 2 or 3 were comparable to those of stations with Ratings 4 or 5, and that there was not much difference between estimates constructed from the Ratings 1 - 3 and Ratings 4 - 5 subsets of the USHCN.

For this reason, in our analysis, we grouped the stations with Ratings of 1 and 2 into the same subset.

This warming bias artificially increased the apparent temperature trends of the U.S. by about half for the Unadjusted version of the dataset, with the trend for the subset of the worst - sited stations more than doubling, relative to the best - sited stations.

The subset of records (14 stations) extending back to the early 1960s suggests that the recent warming trends were preceded by similar widespread cooling trends.

«We make use of the subset of USHCNv2 metadata from stations whose sites have been classified by Watts (2009)» and; «site rating metadata from Fall et al (2011)».

This is done by using a subset of the CEC - A15 reporting stations to estimate the characteristics of the missing fueling station population.

It is within our grasp to locate and collate stations in the USA and in the world that have as long of an uninterrupted record and freedom from bias as possible and to make that a new climate data subset.

As seen in the map below, there are thousands of temperature stations in the US co-op and USHCN network in the USA, by our surface stations survey, at least 80 % of the USHCN is compromised by micro-site issues in some way, and by extension, that large sample size of the USHCN subset of the co-op network we did should translate to the larger network.

When you have those 100 stations, the next step is to use only a subset of them.

Around Dec 8, 2009, the UK Met Office released «value added» data for a «subset» of 1741 stations — see here, describing the release as follows: The data downloadable from this page are a subset of the full HadCRUT3 record of global temperatures, which is one of the global temperature records that have underpinned IPCC -LSB-...]

I wonder what subset of the 779 stations would need to be analyzed in depth to validate the hypothesis?

A subset of the 7,000 or so co-op stations are part of the U.S. Historical Climatological Network (USHCN), and are used to create the official estimate of U.S. temperatures.

Overall, in this subset, 86 % of the stations show warming.

These stations are classified on proximity to artificial surfaces, buildings, and other such objects with unnatural thermal mass,» according to the study, entitled Comparing of Temperature Trends Using an Unperturbed Subset of the U.S. Historical Climatology Network.

The next step is probably to look at the subset of rural CRN12 stations.

Bias at the microsite level (the immediate environment of the sensor) in the unperturbed subset of USHCN stations has a significant effect on the mean temperature (Tmean) trend.

Equipment bias (CRS v. MMTS stations) in the unperturbed subset of USHCN stations has a significant effect on the mean temperature (Tmean) trend when CRS stations are compared with MMTS stations.

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