Big Photography News: Early 2015

It’s been some time since I posted photographic news and developments, but we’ve got some major ones going now.
SkyPix Rising like a Phoenix

After 20 years, four domains and a hundreds of photos and stories added, my longstanding SkyPix gallery is starting over–moving to a new server, a new domain and a completely new layout and look, with numerous mages and narratives not found in the old gallery. One by one, original (but updated) SkyPix photos and prose will be ported over also. This will involve rescanning of old slides and updating of information. Just like the original, you have free and ready access to the latitude and longitude of the great majority of the photo spots too.

Meet SkyPix 2.0 — a site designed expertly by my beautiful bride and web-weaver extraordinaire, Elke Edwards. She has supplied the layout and functionality, and I provide the photography and prose. Just like the old SkyPix, every page within a given gallery category (Majestic Supercell, All Hail, Water Works, Burnscapes, Tornadoes, Floods, Mini Cloud Atlas, Sunrises and Sunsets, etc.), has its own photo and story. Now the photos are larger and higher resolution, and you can click on them to get a still bigger image.

You can still use the old short URL redirect, , as well as the new site address that’s even easier to remember: .

I’ll be building/rebuilding SkyPix one image and story at a time throughout the year, and posting updates often on my new public Twitter account, @SkyPixWeather. You get to follow along in the process and watch SkyPix grow, page by page. I’ll also post periodic blurbs about weather, photography and sports to that account. We would love for you to browse around and check back with @SkyPixWeather or the “NEW” button on the website for updates.

NWC Biennale

The National Weather Center Biennale is, as the title suggests, an event held every two years. Its purpose is to exhibit fine art in three forms–works on paper, paintings and photography–related to “art’s window on the impact of weather on the human experience”. Each piece of art must have been created within the preceding two years, which limits the pool to active artists’ recent work. This is a juried exhibit with judges selecting entries out of hundreds submitted, then ultimately selecting winners in each medium and overall. The lobby of the architecturally artistic National Weather Center becomes an art museum for a few months during the Biennale. The first Biennale was in 2013, and one can read excerpts from the accompanying catalog of the art.

Because the exhibit is juried, and the judges select art from digital submissions without the identities of the contestants, a meteorologist who works in that building has no particular advantage. Yet, in the 2013 Biennale, my photograph, “Lightning on Cheyenne Ridge” (BLOG entry from 2013) was the only one exhibited from anyone working in the facility. Given the number of storm enthusiasts, chasers and talented photographers there, that was a big surprise.

While it didn’t win the ultimate prize, I was pleased to hear nothing but good words about the photo from both jurors and patrons during the event. [If you ever want to know an audience’s thoughts on your art, hang out anonymously near it as folks who don’t know you view and comment.] Despite my normal contempt for and avoidance of photo contests, this was a different, very credible, and worthwhile experience–so much so that I decided to enter again.

For the second straight Biennale, I’ve had a photograph selected to appear in the exhibition, entitled “Twisted Perspective”:

This time, a couple other NWC folks have pieces in the exhibit as well, which is not a surprise. Come on by Battlestar Norman between 19 April and 14 June to partake of what should be a fantastic exhibit of weather art!

What About All Those Iceland Photos?

We shot thousands of photos last August on our two-week excursion around Iceland, and only have begun to scratch the surface in processing and saving the best among them thanks to everything else going on in life. However, I have posted several already to the new SkyPix, and several more still to Image of the Week. If you haven’t visited Image of the Week in some time, please revisit–it’s still going strong, with a different photograph from my portfolio added weekly.

Eventually we hope to build a dedicated website just for Iceland imagery, but we want to take the time to do it right. In the meantime, keep up with SkyPix and Image of the Week for newly posted glimpses of the absolutely stunning North Atlantic volcanic island such as The Stacks of Reynisdrangar, different views of Seljalandsfoss, the otherworldly Hverir Geothermal Area, the ever-changing Jokulsarlon ice lagoon and nearby Atlantic beach of ice on black sand, the wide-open plains beauty of the interior highlands, historic lighthouses, many other waterfalls, captivating mountain and beach vistas, some spectacular sunsets, and so much more.

2014 Top-10 Storm Intercept Photos

A couple of months ago, I posted my top-10 favorite storm scenes from the 2014 season. Pages from 2013, 2012, 2011, and 2010 are also available too, if you’re feeling nostalgic.

Last but not least, all this photography exists for showing (and is dedicated to and motivated by) the glory of God as manifest in the visual blessings He grants to us in land, water and sky. Thanks for dropping by.

Forecasters Are Paid to Be Wrong — and Should Be

Say what? Wait a minute, hoss…forecasters are paid to get it right! Well, yes, from a half-empty-glass perspective that’s true. But since forecasters can’t be 100% right, all the time, they are really being paid to be less wrong than it matters for you, as the user of the forecast.

How is this possible? If you really want to know, you’ll have to stick with me ’til the end of this long discussion, and you’ll have the viewpoint of filling the half-full glass.

The chart below is not just a forecast from an ensemble of models, it’s also a metaphor for our capabilities as human forecasters.

I’ll explain this chart for the unfamiliar. Each colored line is a different forecast from a start time into the future, valid at a spot. The thick black line is the average of all the colored lines (the “consensus” forecast, if you will). You can think of it two ways: literal and figurative. Understand it both ways and you’ll get this.

  1. LITERAL: There’s a lot of information here, so follow along with me. Each line is a running total of a different model’s snow accumulation at Islip, NY, starting at 06Z the 27th (1 a.m. EDT). Yes, this is after the storm already started in reality–and this is important to remember! Also important: this isn’t even on the edge of the storm, where you know you can get either a lot or nothing–this is nearly smack in the middle!

    Dots are every 3 hours. Vertical lines are every 6 hours. White background is day, gray is night (roughly). Numbers at left are in inches. Times and dates are in Z time at the bottom–take 5 hours off to get Eastern Time. The models actually started running from three hours before the start of the forecast (10 p.m., 03Z), but since these are forecasts, the first accumulation doesn’t appear until 1 a.m. (06Z).

    Again this was while the storm was going on, and notice how different they all are already! There’s a nearly 6-inch disagreement from largest to smallest prediction at the first forecast time! By the time the models all agree that the snow has stopped, at 0Z on the 28th (7 p.m. EDT the 27th), it’s less than a day into the future. One model says just an inch comes down. Another says 30 inches. Some specific amount will fall, but how much? Only one of those models can be right in the end–and it’s quite possible that none of them are right. The forecaster can either offer a wild-ass guess (WAG), or give a range and express somehow that even that isn’t fool-proof. Which do you think is the more honest approach?

  2. METAPHORICAL: Don’t worry about the exact spot or exact times. Pretend it’s where you are, right now, if that helps. Ignore the numbers on the graph if you want and make the forecast precipitation whatever you want it to be–rain or snow. Pretend that the lines represent not just computer models, but different human forecasts from media, the NWS, and private weather companies. Swap in whatever names of people, government forecast offices, companies or TV stations you want on the color legend.

    [Understand this: media often get forecast information from either NWS or private forecasters and tweak it. The sum total of it all makes the number of possible human-modified forecasts that are available to you greater than this, and far more numerous than the number of computer models in existence!]

    This speaks for the dilemma faced not just by forecasters but by the users of forecasts. What do you do with such a disparity of possibilities, none of whom may end up correct?

Well, look at this: the event’s already underway, there’s snow on all sides, and the forecasts are still all over the place. You can view it the easy (but wrong) way: “These forecasters are a bunch of idiots, how can they be so far apart? Just gimme a damn answer!” We call that “deterministic” thinking. That’s a ten-dollar word that just means, “way more exact than what’s really possible”. Whoever takes that attitude is looking at forecasting in a really lazy and ignorant way and does not want to understand how it works. I cannot help them and neither can any forecaster, so don’t bother. Such folks will just have to be left to like, you know, keep up with, like, the Kardashians and Justin Beiber, or, like, something. Fortunately I think anyone reading this cares and thinks a little more deeply than that.

The alternative to simple-minded dismissiveness and unreasonable demands is to put yourself in the forecaster’s shoes and try to make some sense of the mixed messages they’re getting. Recall the forecaster’s dilemma: 1) a WAG that follows a particular model of choice (the average of a bunch of models is actually a kind of model too) or 2) suggest a range of possibilities with uncertainty somehow stated.

Picking one “model of the day”–even the one in the middle–has a much bigger chance of embarrassing failure than offering a most-likely range and saying how likely. The model that was closest to correct last time can fail badly this time, since there really never has been a last time. Every situation is different–even those that look very similar.

Now you be the forecaster. Look at the same chart again (above). What do you tell your road crews, TV and radio stations, airports, school districts, law enforcement, your soccer-mom neighbor, and the governor to prepare for? They’re all breathing down your neck, demanding exact answers and amounts, or at best a really narrow range, but this is nuts–you can’t give them a specific answer with a clear conscience as a scientist. The possibilities are just too far apart.

You’re uncertain–very uncertain–because the input you’re getting is so wildly disparate. How do you tell the road crews, the governor, school superintendents, the aviators, the chief of police, Mrs. Soccermom, and the TV and radio stations about this uncertainty? How do you tell them that you don’t have an exact, specific answer and can’t give one–that the best you can do is offer a pretty big range (say, 7 inches either side of an average 15, since that’s where the bulk of the models fall) and still could be wrong? See the dilemma that real forecasters face here?

Now imagine this is 48 hours (two days) out, and not while the event is going on. Often, the spread is even bigger in advance than after it’s already started.

Real forecasters have lots of clues to look at besides models to narrow things down a little, but only a little. Surface observations, radar, satellite, and 12-hourly balloon launches, all put together, only measure a fraction of the air in the storm, and only in incomplete ways. Forecasters know this. It might help them to see that the 1-inch forecast is garbage and throw that one out, but the 20-incher (while not looking likely) is still possible!

The language of uncertainty is probabilities. Since forecasters are always at least a little uncertain–even those who pretend otherwise–the most honest approach is to assign a chance of each outcome. It starts as a percentage but doesn’t have to look like a percentage to the reader, necessarily…it can be translated into a range of colors if you think visually. But even a colored forecast map still is a translation of the probabilities (and uncertainty) behind it. This is why severe-weather outlooks offer probabilities expressed as numbers, colors or words on a map–you get to choose based on how you can relate best. But they’re all rooted in probability–the language of uncertainty.

In the end, it should be clear that no forecast (or forecaster) ever can be completely right, any time or all the time. We only can hope to be less wrong (more accurate) than the last time, and less wrong (more accurate) than most of the models. Forecasting is the art and science of being only a little wrong–but within acceptable tolerances. We express that truthfully by giving probabilities. That’s not hedging or hiding anything–it’s simply being honest.

Do you want your favorite forecaster to be honest or to lie? Because if he or she is telling you a specific snow or rain amount that’s going to fall tomorrow, that’s completely overselling his/her own knowledge. In short, that forecaster is lying. Nobody is that good, except by complete accident, and nobody is consistently that good! If a forecast is within your tolerance, you’ll consider it a good forecast. The question is: is your tolerance a reasonable expectation?

You see, it’s true: forecasters are paid to be wrong, to some extent. That’s because being totally right (perfect) is just not possible. The science just is not there yet. That’s the brutally honest truth. Accept it. We simply strive to be less and less wrong, and to provide the best information we can give to help the governor, the airports, the road crews, the cops, the soccer mom, and everbody else to make the best decisions for their own vastly different purposes. We realize, too, that we just can’t please everybody.


Were you wondering how much snow really fell? At Islip Airport, the final storm total was 25 inches (rounded up from 24.8, which is overly precise for blowing and drifting conditions). Right when the 10 p.m. (03Z) forecast package started, Islip Airport’s observer reported 5 inches already on the ground. Even subtracting that out, as we should to verify this forecast, that yields 20 inches. Regardless of what happened in Philly or NYC, the model consensus and most of the individual members actually under-predicted the big snowstorm at Islip, in the middle of Long Island. None of them got it precisely right. Two were within an inch. Even with those two, we must ask: were they nearly right for the right reasons, or was it a busted-clock type of accidental accuracy (with all those models firing, somebody had be the closest to the target)? The same concerns exist for human forecasters. These are the things we study when we look back at forecasts to try to improve.


    A general yet concise discussion by Doswell on uncertainty concepts in forecasting such events.

    [ADDITION] Just found that Cliff Mass has posted a nice synopsis and discussion of the forecast scenario, with several examples and recommendations.

    Lee Grenci (Ret. PSU) discusses communicating uncertainty for this event.

    A specific 2011 BLOG entry on similar topics: Forecasting the Ensemble Outlier.

    A general 2005 BLOG discussion: Ensemble Forecasting: Threat or Benefit? — including a definition of the “Obsolescence Point” for human forecasting (some links probably have expired)

    SREF plume diagrams (the source and type of the chart used above).

A Challenge for Storm Chasers Who Preach about Carbon Emissions

Do you chase storms? Do you claim to care about carbon emissions? If the answer is “yes”, then stop chasing.

If you continue to chase, and you remain on the climate-change/carbon-emissions bandwagon, you are behaving in a dishonest, duplicitous, hypocritical, and pretentious manner. Why? Easy: you are proclaiming the need for others (and isn’t it always others?) to curtail their carbon-spewing activities that you perceive as unneeded, while refusing to most fully do so yourself. And that, friend, is the real “inconvenient truth”.

The measure of any principle is the extent of self-sacrifice for it!

You say you recycle, use solar and wind energy, and/or take public transportation sometimes? Well, so do I–all of the above, in fact. But I do not go strutting around like some pompous enviro-peacock, proclaiming my environmental-sustainability, holier-than-thou status with carbon, while simultaneously and deliberately engaging in activities that completely counterbalance my own ideals. Carbon isn’t the reason I recycle, use solar energy, take electricity from a utility that operates wind farms, etc., and I’m not pretending that it is. And be real here: your token, minimal personal carbon savings in other areas are meaningless in the big picture. You’ll never, ever offset a millionth of what China spews in a single year. That’s the sooty, dirty truth. All the excuses in the world don’t change that.

Blather about personal “carbon offsets”, high-efficiency cars, sustainability, and local sourcing is just window dressing–a feel-good exercise in rationalizations to mollify eco-hipster insecurities. In short, it’s all a load of pandering bullcrap. It doesn’t make any real, measurable difference in the world CO2 budget. Therefore, it’s all about principle and not actual personal carbon emission. Since that’s the case, hold yourself to that principle!

I am not talking about necessary driving, such as to and from work, or to purchase food or obtain medical care. Storm chasing is a hobby. As an avid cross-country storm observer of three decades’ experience, who has logged hundreds of thousands of miles guilt-free, I can declare this with certainty: While fun, educational, informative and (on rare occasion) valuable to the warning system through storm reports, my storm chasing is not absolutely necessary. Neither is yours. I am not holding anyone to a higher standard than myself here. As such, my position is rock-solid.

Personally, I have no horse in the climate-change rodeo and refuse to get involved or take a position, either in support or opposition. I follow no herd regarding what to “do about” a warming climate. I stand tall in defiance of those on both the political left and the right who insist I must take a stand. To both, I say: No. I am my own man and you do not dictate what I must think! The overpoliticization and borderline cult status of it all just turns me off. It’s not worth more than this much of my valuable time, and I have other bigger priorities in life.

I just don’t care one way or another about “global warming” and that’s the brutally honest truth. If we warm a lot, we’ll either adapt or die as a civilization. So be it. That’s also the brutally honest truth. If my lack of concern about this issue gives you discomfort–your problem, not mine. I’ll keep chasing and driving a big vehicle because I don’t advocate anything either way regarding carbon emissions.

Nonetheless, I do care about pretension, hypocrisy and false fronts. And that’s exactly what every single storm chaser is doing who also claims to care about carbon emissions while driving thousands of miles per year for an unnecessary activity.

Again, if you chase storms and also claim to care about carbon emissions, then put your money where your mouth is and cease chasing! In the same vein, stop all other travel that is not absolutely necessary, such as vacations away from home. Either that, or stop the hypocrisy and shut up the two-faced moralizing about carbon use.

Your ideals are only as valid as the degree to which they personally apply to you. Are your carbon principles important enough to make your practice match your preaching, and inconvenience yourself?

That’s the hammer of truth (in Latin, Malleus Verum…thanks bc) that I slam down with blunt force upon this issue. Do your value your principles enough to meet my challenge? Or are they as hollow and meaningless as I suspect?

Let the lame excuses come.

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