Sam Wormley
2013-11-15 18:14:17 UTC
Recent surface warming has probably been underestimated
http://arstechnica.com/science/2013/11/recent-surface-warming-has-probably-been-underestimated/
If you want to take someone’s temperature to see if they have a
fever, you know where to put the thermometer. (Sorry, infants.) But
where do you take the temperature of Earth’s climate? Inconveniently,
the answer is “everywhere”—you need measurements covering the planet
to properly calculate the global average surface temperature. That’s
no big deal for Europe, where a local weather station is never far
away, but it's much more of a problem for the North and South Poles
where records are hard-won. A new analysis shows that how you deal
with this problem makes a difference in what temperature you end up
reading.
Building a global temperature dataset is a huge undertaking, because
that’s only the half of it. Lots of careful corrections need to be
made to the raw measurements to account for things like instrument
changes, weather station placement, and even the time of day the
station is checked.
One of the most commonly used datasets, dubbed “HadCRUT4” in its
current incarnation, is maintained by the UK Met Office and
researchers at the University of East Anglia. That dataset lacks
temperature records over 16 percent of the globe, mostly parts of the
Arctic, Antarctic, and Africa. Each group that manages one of these
datasets faces this problem, but deals with it a little differently.
In HadCRUT4, the gaps are simply dropped out of the calculated
average; in NASA’s GISTEMP dataset, these holes are filled in by
interpolating from the nearest measurements.
If you want to take someone’s temperature to see if they have a
fever, you know where to put the thermometer. (Sorry, infants.) But
where do you take the temperature of Earth’s climate? Inconveniently,
the answer is “everywhere”—you need measurements covering the planet
to properly calculate the global average surface temperature. That’s
no big deal for Europe, where a local weather station is never far
away, but it's much more of a problem for the North and South Poles
where records are hard-won. A new analysis shows that how you deal
with this problem makes a difference in what temperature you end up
reading.
Building a global temperature dataset is a huge undertaking, because
that’s only the half of it. Lots of careful corrections need to be
made to the raw measurements to account for things like instrument
changes, weather station placement, and even the time of day the
station is checked.
One of the most commonly used datasets, dubbed “HadCRUT4” in its
current incarnation, is maintained by the UK Met Office and
researchers at the University of East Anglia. That dataset lacks
temperature records over 16 percent of the globe, mostly parts of the
Arctic, Antarctic, and Africa. Each group that manages one of these
datasets faces this problem, but deals with it a little differently.
In HadCRUT4, the gaps are simply dropped out of the calculated
average; in NASA’s GISTEMP dataset, these holes are filled in by
interpolating from the nearest measurements.