The problem with
most weather station data is it is not «real time», so pilots rely on what the control tower is telling them.
The Berkeley Earth group has developed a new mathematical framework for producing maps and large - scale averages of temperature changes from
weather station data for the purposes of climate analysis.
Climate data were derived from
weather station data provided by National Climate Monitoring of Deutscher Wetterdienst and were corrected for altitude.
Obtaining the globally averaged temperature
from weather station data has a well - known problem: there are some gaps in the data, especially in the polar regions and in parts of Africa.
I was instructed to teach Jeremy, Andrew Weaver's other summer student, how to use the UVic climate model — he had been working
with weather station data for most of the summer, but was interested in Earth system modelling too.
IMHO if you want to measure temperature trend based
on weather station data, the best method is to use only those weather states that were working throughout the period of interest, excluding any that were damaged or affected by the urban heat island effect.
For a couple years I have been pointing out (along with Judith Curry and others) that the latest fad — which puts a lot of warming in recent data — is to extend high - latitude land
weather station data far out over the Arctic Ocean.
The University of East Anglia, with the assistance of the U.K. Met Office, is now trying to get countries that had provided
weather station data under confidential agreements to release the information to the public.
But when, as with the
Antarctica weather station data we used, there is not only a lot of missing data and «noise» but also greatly time - varying patterns of missingness (which stations have data missing), ridge regression (both mridge and iridge) can be expected to, and does, perform significantly better than TTLS.
NASA is on it's best behavior with regards to climate data, since it emerged recently that the agency may have
altered weather station data to falsely indicate warming & sea rises.
KS2 / 3 science: Use automatic
weather station data together with the Met Office resources to study the difference between day and night and to look at the seasons.
Across the United States,
weather station data reveal that daily maximum temperature records outnumbered minimum temperature records for nine months of 2010.
But rather than
mining weather station data, which can take months to process, the students calculated and mapped VPD from satellite data delivered almost in real time.
Elsewhere, following some detective work by Anthony Watts, Steve McIntyre and Roger Pielke Sr have been doing some quality control
on weather station data.
By the 1980's, weather satellites could measure rainfall and cloud cover all over the planet and infer things like air pressure by combining
with weather station data.
First they used
the weather station data to determine how temperatures in Philadelphia's urban and surrounding rural areas had changed over time.
It would be interesting to see how it stacks up to
the weather station data, or to the satellite data of the past 30 years, for example.
In contrast,
the weather station data provide complete temporal resolution over the past half - century....
For an example of how that «citizen science» can really work, look at what Ron Broberg and Zeke Hausfeather are doing with
the weather station data — they aren't sitting around declaring that «it can't be done» or that the GISTEMP / CRU / NCDC methods are fixed, they are going into the data, making choices, seeing what impact they have and determining what is robust.
(I have been expecting greater evidence of multiple attributes / modes or a shifting mean in
the weather station data sets then I have found.)
NASA GISS are currently the only group calculating global temperature estimates that explicitly adjust
their weather station data for urbanization biases.
The scale of the discrepancy lead to accusations that
weather station data had been «adjusted», thereby exaggerating the effects of global warming, something which the Foundation is keen to investigate.
The weather station data is combined with sea surface temperature data from the UK Met Office's Hadley Centre (HadSST).
The weather station data for NASA's GISTEMP come from the Global Historical Climate Network (GHCN - monthly version 3).
The characteristic of being entirely impervious to changes in the «most critical»
weather station data is a rather odd result for a method that is supposed to better utilize the station data.
The SST data are a little more complex than
the weather station data with which most of use are familiar: Whereas temperature measurements at weather stations have been performed according to a standard protocol for over a century, measurement methods for SST data have changed significantly over the same period.
Their latest cause celebre: New revelations in The Guardian that the director of the University of East Anglia's Climate Research Center, Phil Jones, may be in hot water over the accusations of scientific fraud having to do with Chinese
weather station data.
Principal component analysis of
the weather station data produces results similar to those of the satellite data analysis, yielding three separable principal components.
Their weather station data and modelling work indicate the tropical ice should last well beyond 2040.