Climate Data Viewer
Our Climate Data Viewer program displays the temperature records from the GHCN (Global Historical Climatology Network) Version 3 average temperature data together with a historical event timeline and up to 4 graphical overlays
Claims and counterclaims circulate on the internet regarding the processing of climate data, while countries base their entire future energy policies on claimed climate trends, their assumed causes, and on forecasts derived from computer models.
We decided to create our own independent programs - so that you can examine historical climate variations and look for correlations between data sets. This program displays temperature data - we hope soon to follow this with a similar progam for sea-level.
When using the Climate Data Viewer please bear in mind the following:-
1. The GHCN temperature records are not 100% continuous - they contain gaps, some quite large, which are not randomly distributed in time.
2. The stations are not uniformly geographically distributed, with a higher density of stations in some areas than others .
3. The growth of cities may have created a localized urban warming effect. It is probably incorrect to infer global warming from such localized effects.
4. Temperature measurement techniques have changed over time. Mercury-in-glass maximum/minimum thermometers have been replaced with electronic sensors with continuous data gathering. In the US a network-wide switch from afternoon to morning observation times from 1950 onwards may have introduced a bias.
It is tricky to combine such data records into a single graphical line representing global temperature versus time. Simple data processing methods such as averaging, are highly dependant upon station density. When cold or warm stations become active (or cease to be active) they influence the overall curve. Re-basing is an attempt to solve this, by forcing all station graphs to go through the same value (e.g. from hot and cold areas) by shifting up and down, rather like financial share price graphs are rebased for comparison. However rebasing is still vulnerable to changes in station density with time. The more complex process of gridding attempts to avoid this station density bias by using a map grid, calculating a weighted average for temperature within each grid square. It is computationally intensive. The controversial homogenization method takes spatial effects further by assuming spatial correlation must exist between measurements at a local range, and back correcting station measurements to enforce this, thereby reducing noise in the global graph caused by local measurement inaccuracies. It is claimed that noise caused by changes in enclosures design, thermometer design, station location, or measurement procedures can be eliminated. Like gridding it is computationally intensive algorithm.
Our Climate Data Viewer has the following setting options.:-
The Climate Data Viewer does not carry out the computationally intensive processes of gridding and homogenization. However it does display the GHCN adjusted data set, in which the PHA (Pairwise Homogenization Algorithm) correction has already previously been applied by NOOA/NASA.
With certain settings our Climate Data Viewer produces similar results to those quoted in the literature by IPCC etc. (e.g. rebasing from 1960 to 1990). But it does much more than this, providing a way for you to browse the data interactively - so that you can get a feel for the relative significance and timing of temperature variations.
This program is not Microsoft Windows certified due to the cost involved so please ignore certification warnings. We have tested it and certify it's virus free.
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