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Jun 252013
 
A NOAA map showing average wind speeds for the month of May.

An NOAA map showing average wind speeds for the month of May.

This is the third part of a three-part article series on using wind data to evaluate the risk of nuclear fallout at your retreat location.

If you arrived here directly from a search engine or link, you should probably go to the first part of the series – Using Wind Data to Estimate Fallout Risk – and read that first, then continue on to the second part – The Two Types of Wind Effects to Consider – before returning to read this final part.

We are fortunate to have a great deal of information available to us which can be used to help us understand which way the wind blows.

But before we look at the data sources, we need to consider four additional issues when interpreting the data.

1.  Use Data Averaged Over Many Years

We know that winds vary by the season, month, day, hour and even sometimes by the minute.  We know that some days are unusually windy, and others are unusually calm.

Clearly we can’t base our expectations for future wind patterns on only one day of observations and history.  Instead, we need to average the data – but not by taking the average of many days together, but rather by taking an average of the wind on the same day of many different years.

You want the wind data for, eg, 15 July, to be the average of the winds on the 15th of July over each of many previous years – the more previous years, the better, although there comes a point where adding more years no longer really adds much extra value to the data.  An average of ideally ten or more years will give you a better feeling for what the general probability will be for the next 15 July.

It would help also to understand the ‘SD’ or standard deviation of the averaged number.  This is a statistical term (click the link for a detailed explanation if you’d like) that simply measures whether most of the data points that you are averaging are close to the average number or not.

For example, if you had seven numbers  1 5 9 13 17 21 25, and another seven numbers, 10 11 12 13 14 15 16, in both cases, the average of the numbers is 13.  But the spread of values is much wider in the first series than the second series.  In the second series, the average is 13, and the maximum is only a bit more, and the minimum only a bit less, but in the first series, the maximum is almost twice the average, and the minimum is 13 times less.  All values are close to the average in the second series, but only a very few values are close to the average in the first series.

In the case of the first series, it has a standard deviation of 8.6, in the second series, a standard deviation of 2.2.  The smaller the standard deviation, the closer the individual data values are to the average and so the more accurately the average predicts the reality of individual days.

2.  Use Monthly Wind Values, Not Annual Wind Values

Sorry, but you’re going to have to do these calculations twelve times (or use data already calculated for you).  As the seasons change, so too can wind patterns – not only wind speeds, but also prevailing wind directions, too.

While ideally you’d do the calculation for every day of the year, you’ll end up drowning in data, and with wind being variable and unpredictable at the best of times, probably it is good enough to simply look at monthly data.

We suggest you create 12 maps, one for each month, and then plot wind directions at your retreat location and other close weather stations to it for each month, and also, as per the examples in part two, also ‘walk back’ the wind to see where it is coming from.

If there are nuclear targets or power plants within 200-300 miles or so of your retreat location, you want to add them to your maps and add wind directions to their locations too, plus then move forward to follow those winds from the possible fallout release points.

3 & 4.  Consider All the Varying Speeds and Directions that Wind Blows Each Month

Okay, now it is time to start to use the understanding you’ve developed and to look at the specifics for what to expect.

There are a couple of things to keep in mind now that you are looking at actual data.

Understanding wind direction descriptions

The first point is very important.  When you are looking at wind direction information, is it telling you the direction the wind is coming from, or the direction that the wind is going to?  Some data will provide information one way, other data will provide data the other way.

To explain, say there is a wind that is moving its air in a direction such that air to the south of you blows past you and then continues traveling north.  This is what is traditionally called a southerly wind – wind is coming from the south, from a 180° direction on a compass heading.  If you had a traditional weather vane, it would swing and point to the south.

But if you were flying a flag, the flag would extend out to the north of the flagpole – the opposite direction to the weather vane.  The wind is blowing to the north (ie 0° or 360°) (as well as from the south).  If you were talking about a car instead of wind, you would say the car was going in a northerly direction.

How should this wind be described.  Is it a wind from the south, or to the north?  It could be either, and it is both!  So be very certain to understand which descriptional method is being used.

Wind height measurements

Wind speeds are slower, the closer to the ground they get.  At 1/10″ above the ground, they are close to zero, and then they increase up from that until reaching a point of maximum speed, then they start decreasing again above that.  It is even possible to have winds traveling in different directions at different heights above the ground (balloonists use this to help them steer their balloons).

When you are comparing wind speed measurements, you need to know at what height the measurement was taken.  Clearly if you are comparing a measurement at one location that was taken at 3 feet above the ground with a measurement somewhere else that was taken at 30 ft or 300 ft, you’re not comparing like with like.

These days the standard measurement height for wind speeds is 10 meters (about 33 ft), and if you are reading official wind data from a weather service, that is probably what is being provided.  Often the actual measuring device is not at exactly 10 m above the ground, and so the speed it displays is then converted to display the theoretical/probable speed at 10 m.

But if you are using data prepared for siting a wind turbine, that will have data on wind flows at much greater heights.  This is useful information too, but be careful not to mix together data from different sources at different heights.

Data Sources

To get you started, here’s a nice simple map showing annual average wind directions and mean speeds.

But this map – while giving you a nice overview, is potentially very misleading.  The national averages can mask huge differences from season to season.  You need to drill down from the annual information to monthly information, and ideally, you want to get information from more locations, too.

First, however, to compare like with like, here’s a series of maps drawn from the same source for each of the twelve months.

January  February  March  April  May  June  July  August  September  October  November  December

(If the links no longer work, you can hopefully recreate them from this page.)

Here is an alternate series of monthly averages for wind speeds and directions, calculated for the period from 1930 (or later) until 1996 here.  That gives you another perspective for monthly variations, and has been provided for a much larger number of locations.  Hopefully the data you see here is sort of consistent with the data in the previous links.

The National Climatic Data Center and its US Climate Reference Network has a lot of data, but only from a few reporting stations, and while it gives wind speeds – typically measured at a nonstandard height of 5 – 15 ft above ground, it does not report wind direction.

If you’d like to see the wind information in a more visual manner, albeit slightly abstracted, here’s a fascinating series of maps.  It seems they only provide monthly data, without averaging the same month over several years, but if you click the link for any given month/year, it then provides both information on the specific month/year and also shows you the 30 year average for the period 1971 – 2000 and thirdly shows you how the specific year’s monthly average varies up or down from the typical month.

But wait, there’s more.  These first maps just show wind speed, not wind direction.  There are two more sets of maps, which between them show direction.  One shows what the call the U component, which is the east-west direction of the wind, and the other shows the V component, the north-south direction.  This is very interesting to see split out.

Wow.  Are you starting to get overloaded with data, yet?  Well, there’s one more wonderful source of summary data for many different locations.  That starts from this page here, and you can then choose the locations you want data about and the data you wish, either from their map interface (perhaps the easiest) or from data searching and other options.

One more resource.  If the previous resources have not had sufficient information for you, go to the appropriate regional climate center (choose from this main menu/map) and you’ll find an enormous amount of extra data for very many different reporting stations in the region.

But, wait – we’ve still not finished.  There are two more things to show you.

Leaving the best until last, remember when we spoke in the previous part of this series about wanting to know not only the average speed and direction of wind each month, but also the range of actual values?  Here’s a totally marvelous site which does exactly that.

Zoom in to the region of the map you are interested in, and you’ll see little wind roses appear for each reporting site.  Click on one of the wind roses, and that brings up a page showing you detailed information.  You can then click on the months in the circle as you wish.  Note if you keep clicking months ‘on’ you get averages of all the months clicked ‘on’; you need to click months off again so as to see the single month patterns.

And, lastly, some eye candy which gives you a fascinating feel for how it all ties together.

You can click to zoom in on any part of the map you wish, and when you start clicking to zoom in, an ‘unzoom’ button appears on the left.

The ‘problem’ with this map is that it is limited to showing you only the wind patterns right now.  It doesn’t give you a feeling for average flows.  But just seeing the ‘right now’ flows is still fascinating and helps you to understand how winds don’t flow consistently in straight lines for long distances.

Summary

Nuclear fallout may be transported from the location it was generated to your retreat either by high atmosphere jetstream winds, or lower down ‘regular’ winds.  The jetstream winds move swiftly and in doing so, tend to thinly disperse fallout over a wide area, while the lower down winds, moving much more slowly, tend to drop more concentrated fallout patterns within 200 – 400 miles of the nuclear release.

If you are within several hundred miles of a nuclear power station or a nuclear target, you should understand the degree of risk associated with fallout traveling to your retreat.

Winds are unpredictable on an hourly basis, but they follow certain trends and are more likely to be blowing in some directions than others on a daily and monthly basis.  There are lots of online resources to help you understand exactly what type of wind flows to expect at your retreat, and at potential fallout release sites too.

This was the third part of a three-part series about using wind data to estimate your retreat’s potential risk of being affected by nuclear fallout.  If you’ve not yet done so, we recommend you also read parts one and two of the series.

We have additional information on nuclear power related vulnerabilities in its own section too, and lots more information on weather related topics also.

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David Spero[suffusion-the-author display='description']

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