US nuclear map target + refineries

[castlebravo92]

Green = likely intact refinery
Blue = possibly intact refinery
Red = destroyed refinery

Target map is from the GDW 1.0/2.0 canon nuclear target list duplicated in various sources (Challenge, Howling Wilderness, 2.0 Main Rules). The only modification I made to the nuclear targets is adjusting nudets to yield (for example, if GDW listed 1.5 MT for a target, that became 3x500kt nuclear detonations). PSI rings are 5.0 PSI, 2.0 PSI, and 1.0 PSI.

Refinery list is compiled from the list of US refineries compiled by the EIA from 1997:

https://www.eia.gov/petroleum/refine...7/refcap97.xls

From there I extracted the refineries producing alkanes and aromatics (primary inputs into fuel production), and did my best to geolocate the refineries.

Note, some of the refineries that existed in 1997 are gone. One in Long Beach is now office warehouse space, you can't event tell that a refinery used to be there. Many of the others have changed names from what is listed on the map and in the Excel, as a lot of the companies have gone through mergers, and refineries have been sold and acquired.

In some cases, the refinery lat and lon may not match up exactly with the historical equivalents. Some of the areas (Long Beach, Baytown, Beaumont, Louisiana) are positively congested with refineries, with one refinery adjacent to another refinery and both refineries having undergone 3-4 name changes since 1997, and so it's probable that some lat/lons are transposed. In all of these cases, however, it doesn't really matter because all of the affected refineries were destroyed by nukes.

[castlebravo92]

Refinery list with geolocation elements added.

[castlebravo92]

Blast and thermal effects only, fallout not modeled.

Methodology:
GDW canon target list compiled into appropriate nudets for each area, paired with actual Soviet weapon yields (e.g., 3MT becomes 3x1 MT, 1.5 MT becomes 3x500 kt) to create a laydown file.

Fine grid population data from https://sedac.ciesin.columbia.edu/da...tes-rev11/docs loaded into a Postgresql database.

For each nuclear detonation, each population grid point within the 1.0 PSI or greater footprint assessed for casualties and accrued to a dead/injured column. Since there were a lot of high population areas where detonation effects overlapped, this was necessary to keep from double counting the population that was killed two or three times.

Assessment for casualties was done by curve backfitting fatalities and injuries from the Hiroshima atomic bombings to PSI levels.

Potential undercounts of casualties (methodology flaws) are:
- thermal effects (thermal scales more linearly than blast effects with larger weapons)
- firestorm fatalities (some casualty models basically assume 100% mortality within the >=5 PSI ring due being unable to escape before being engulfed by firestorms)
- obviously no fallout modeling

[kato13]

Back when googlemaps was simpler I had a great interactive map for thermal, fallout, blast. Might try to rebuild it when I get some time. If you need gelocated data for strikes let me know.

Here are the static maps I made

https://forum.juhlin.com/showthread.php?t=851

[castlebravo92]

Originally Posted by kato13

Back when googlemaps was simpler I had a great interactive map for thermal, fallout, blast. Might try to rebuild it when I get some time. If you need gelocated data for strikes let me know.

Here are the static maps I made

https://forum.juhlin.com/showthread.php?t=851

Happy to collaborate.

The nuclear calc stuff I'm doing is mostly automated using python scripts. It takes about 1 minute to calculate the casualty totals from a Twilight scenario sized attack. The population data from the source I listed is high resolution point data, so I'm guessing the numbers are more accurate than what you can get from say nukemap.org (the pop data is also from 2000, so it will be more canon accurate as well).

Once I get the code cleaned up to where I'm not embarrassed to post it, I'll put it up on github. Right now, it's functional but ugly. Python isn't my main language, and it shows.

For fallout modeling, I'm working here and there on incorporating hysplit (really, pysplit) for atmospheric modeling of fallout patterns.

As an aside, David Teeter has a github where he's built a target database for the United States:

https://github.com/davidteter/OPEN-RISOP

Granted, it's for modern day, but the detail in it is impressive.