Earthquake Subset 3: Short Term

Subset 3: Short Term

Source NCEDC / ANSS
URL http://www.ncedc.org/anss/catalog-search.html
Period 22 years or ~2 solar cycles (1990 AD » 2012 AD)
Cardinality 64,531 earthquakes
Observation Objective through seismographs and scientific review
Criteria Magnitude 4.8 and above
Interval Per earthquake
Attributes Year, Month, Day, Latitude(°), Longitude(°), Depth(km), Magnitude(Richter)
Quality Continuity: 99% Volume: 99% Accuracy: 66% Total: 88%

This subset clearly has the best quality of the three earthquake subsets, mainly due to its recency. Since it overlaps with the two previous sub sets, we can refer to them and make comparisons.

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Earthquake Subset 2: Medium Term

Subset 2: Medium Term

Source NCEDC / ANSS
URL http://www.ncedc.org/anss/catalog-search.html
Period 108 years or ~10 solar cycles (1905 AD » 2012 AD)
Cardinality 61,366 earthquakes
Observation Objective
Criteria Magnitude 5.1 and above
Interval Per earthquake
Attributes Year, Month, Day, Latitude(°), Longitude(°), Depth(km), Magnitude(Richter)
Quality Continuity: 66% Volume: 66% Accuracy: 66% Total: 66%

Just like our first sub set, it is worth having a look at the total volume of quakes reported per 4 year period, just so we have an idea. Again, it could be that there were more quakes happening, but the periodic trend should emerge from this graph.

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Earthquake Subset 1: Long Term

Subset 1: Long Term (“Significant”) 

Source National Geophysical Data Center / World Data Service, NOAA
URL http://www.ngdc.noaa.gov/nndc/struts/form?t=101650&s=1&d=1
Period 260 years or ~24 solar cycles (1752 AD » 2012 AD)
Cardinality 811 earthquakes
Criteria Subjective [Earthquake is “significant” (million$ damage, # of victims, etc)]
Interval Per earthquake
Attributes Year, Month, Day, Latitude(°), Longitude(°), Depth(km), Magnitude(Richter)
Quality Continuity: 33% Volume: 66% Accuracy: 33% Total: 44%

 

This data set originally started at 2150 BC. Earthquakes with a 7.5 magnitude are not that common. This data set is important to use for any long term trends, but how much can we trust it? Let’s have a look at how the periodic data volume increases over time.

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