Weather or Not

Severe Outflow by R. Edwards

Independent Review Needed for Weather Disasters and Warning Verification

by Leave a Comment

As a 35-year national NWS forecaster and researcher in severe and tropical meteorology, I support the bipartisan National Weather Safety Board (NWSB) Act, which would provide an NTSB-like board review of weather disasters. Numerous other meteorologists and I have suggested something akin to this for many years.

While I agree with fellow retired NWS scientist Alan Gerard in his “Substack” column that it doesn’t do enough to evaluate non-weather disasters nor NWS performance, we shouldn’t let the perfect get in the way of the good. The NWSB Act would be a positive step toward learning from weather disasters in a systematic, consistent and accountable way, not the overpoliticized, self-interested, wagon-circling shams that the “NWS Service Assessments” often became.

Improving NWS verification services may need separate legislative action anyway, especially to address one of the most blatant, yet little-discussed, conflicts of interest that exist in all of federal government, and has for decades: verification of weather warnings by the very same offices that issue them (often, even the same forecasters).

This includes rampant use of estimated — as opposed to measured — wind and hail reports, with over 90% of thunderstorm-wind “verification” being estimates and, based on human wind-tunnel experiments, overestimates. [For much more on this, read a formally peer-reviewed, scientific publication that I lead-authored.] It’s a fox-guarding-henhouse verification system rife with opportunities for padding and inflation, regardless of how much actually happens (which is practically unknowable).

As someone who loves the NWS as a 35-year public servant there, and sees it as an extremely valuable service for the taxpayer (at a bit over a penny a person a day), its very integrity and scientific credibility depend on eliminating conflicts of interest, and ensuring optimal service through independent evaluation of both disaster services and warning performance.

One likely finding I already predict, with great confidence, will be that NWS technology and delivery each need vast improvement. Due in part to longstanding short-staffing and failure to encourage and enable true innovation, both NWS’ front-facing forecast suite (including web/app presence) and internal capabilities have become vastly outdated.

To wit, we should have been using four-dimensional, XYZ-plane-rotatable displays of model and radar fields by the time I retired, on touchscreens. That tech has been in the media at least 25 years, gaming industry since the late 1990s, Hollywood even earlier. Three-dimensional storm simulations have been around in research since 1978, on then-massive computers with less capacity than high-end gaming desktops and cloud computing of today, and finescale simulations of tornadoes and their parent supercells with Hollywood-quality graphic output were run a decade ago, on data far denser than modern operational weather models.

Instead, the most advanced severe-weather forecast operation in the world (SPC) still was — and remains — stuck with 30-year-old 2D display systems and having to mouse-click individual points on outlook lines (instead of using a stylus or finger to save time). The only 3D rotatable displays in the NWS are in licensed private-sector radar software (GR2 Analyst)!

We already should have had nationally deployed, phased-array, dual-polarization radar by 2011 when in reality, the old, greasy mechanical dishes (increasingly failure prone) were retrofitted with dual-pol. Both phased array and dual-pol tech, BTW, were in military and lab use before I was born. One is still not in our radars.

As for forecast presentation, technical discussions for other meteorologists still have their place, and should. Yet I agree with those who say we (NWS, of which I am a proud retiree) could do a much better job conveying threats in meaningful, animated, easy to understand ways. Yes, that should include robust app development and aggressive use of modern web capabilities—not handcuffing ourselves to the slowest common denominator of 486 processors and Netscape because somebody, somewhere, might still be using a teletype emulator. Hell, it wasn’t until just a decade ago that we quit using ALL CAPS in everything, like it was still 1967.

It’s baffling that we still have to issue watches with expiration times, instead of rolling them along open-ended with the threats, as we discussed among us (“amoeba watches”) for 20+ years. That predates the oft-tested, never implemented concept of “Threats in Motion” for warnings, which is very similar, and which also is long past technological capability for operationalizing. Funding (or lack thereof) has played a role, but in my experience, bureaucratic intransigence and a CYA culture frightened of innovation was at least as responsible.

Independent review would highlight shortcomings — both technological and situational — not to assign blame, but to spotlight areas for improvement. NWS, and the entire weather enterprise, should welcome true accontability!

About Recent SPC Forecast Performance

by Leave a Comment

Our Stormeyes sites (including Image of the Week, East Norman Rainfall, this BLOG, and various non-SkyPix web pages, etc.) have been down most of the last few days while Cloudflare and HostPapa point fingers at each other. [SkyPix is on a different host.] The problem, whatever it was, seems to have gone away for now…so, I actually have a backlog of entries. First, a reasoned defense from an inside perspective of perceived lapses in SPC outlook and watch performance so far this year…

———————–

A story from NBC, and others on the less-than-2% outlook’s tornado occurrences in eastern Kansas, some of which also note the watchless tornadoes in Lower Michigan earlier this year, grossly oversimplify reality on the SPC forecast desk. The NBC story in particular relies on a lot of idle speculation by people who haven’t worked the SPC outlook desk, and as such, just don’t know.

I’ve done SPC outlooks for decades, and as usual, will be brutally honest here. I know how it goes there, from the inside. Read and learn. These insights don’t lend themselves to 10-second attention spans nor quick sound bites. So this is long. Don’t “TLDR” this post if you really care about actually finding out how it works.

I’ll put the bottom line here, near the top: Chances are, there is no smoking gun. That may not suit rage-baiting and click-baiting, but it’s simply reality. That’s the lede. Here’s the rest…

Why no smoking gun? Far too much goes into a forecast to lay “blame” at any one factor. Like it or not, bad forecasts happen. They always have and always will. The aim is to reduce them over years, knowing that some events are so localized and/or extreme that both human and computer forecasts can’t always nail them down. That’s reality.

Until forecasters have extremely high-resolution sampling of the real atmosphere on scales storms form and operate (a few miles), even the most sophisticated models, both from traditional, physics-based and AI/statistical packages, will suffer sometimes with localized subtleties. Guess what’s involved in forming a dryline storm here vs. somewhere else, amidst capping and modest broader lift? You got it, friends, localized subtleties.

Yes, observational balloon data were missing and are, in bulk and when quality-controlled, important to models. Several scientific papers have shown this. Maybe that mattered here. Maybe it did not. Satellite-derived data matter too, but radiosondes can influence model performance by several relatively simple situational measures (e.g., this paper, or this one, or this one).

How important was the lack of radiosondes to this case on this day? We don’t know. As Alan Gerard alludes in his article on the radiosonde-loss issue: that needs to be studied (using data-denial experiments). Until then, it’s speculation to say how much that altered output at any of many levels of the atmosphere, from models that *variably* and *incompletely* influenced this particular outlook’s positioning.

*Numerous* models are examined every forecast cycle, especially early-arriving deterministic ones, ensembles, and newer/quickly computed AI packages that work off historic pattern recognition. How they may be affected by missing input data can vary from model to model and by data type. It can be such a dense black box that such effects are simply unknown to the forecasters. We’re not, and cannot be, privy to every nook and cranny of their physics or statistical equations. Forecasters often notice and account for model biases, but where they come from can be quite complex and not just tied to one factor.

Between that and diagnostics that should precede models, it can be a veritable firehose of information, on deadline. With time, experience, on-shift mentorship of the leads and senior outlookers, and training, forecasters get better at situationally prioritizing what to drink from that firehose, when, how, and why. It is simply impossible to examine every possible diagnostic and prognostic detail from every data source.

Models are not all that go into a forecast. So do diagnostics: analyses of surface and upper-air data. The latter factually do have holes that may cause analysis to miss subtle features, but was that true here? We don’t know yet. Other diagnostics, such as satellite and radar-indicated features, and intangibles such as reading, research, forecaster experience, and intuition with specific situations, also play a role.

It’s even more speculative, and likely inaccurate, to say the lack of greater staffing affected the outlooks in these cases so far. [That isn’t to say it can’t, or won’t, the rest of the season.] Though I recently retired, and was not a participant in these forecasts, I do know the principals involved. Everyone who did the outlooks for the KS day were working normal 8-hour shifts and not overtime. If “exhaustion” or “fatigue” were factors, it comes simply from the nature of rotating shift work, which is documented to be unhealthy mentally and physically, and a known carcinogen. Don’t knock it ’til you’ve done it.

Yes, with two retirements last month, 5 openings (out of 10 positions or 50% vacant) are on the SPC outlook/mesoscale desk as of this writing. That is unprecedented. They need to be permanently filled with full-time forecasters, stat! A lot of fill-in shifts by both managers (one of whom is an extremely sharp and highly experienced forecaster), and less-tenured forecasters, will be needed until those are filled. Results may vary.

That won’t help, and yes, it might hurt! But it’s premature and speculative to pin any single forecast performance so far, or the rest of this season, just on that. Again, forecasts sometimes simply miss. SPC has a well-earned reputation for, and internally motivated standard of, excellence. Excellence is not synonymous with perfection. Even I had some bad forecast decisions I’d like to have back. 😉

Outlooks at SPC do not happen in a vacuum. One or two names may appear thereon, but it’s a team forecast. Internal collaboration is required. External coordination with involved local NWS offices (WFOs) is strongly encouraged if major changes are being made to a previous outlook. Otherwise, there is not enough time to coordinate every part of every outlook line with every involved WFO, who themselves also are busy with other tasks. Every minute doing that is a minute not spent doing meteorology. So there must be a balance achieved on deadline.

I don’t know for sure here, but it is possible that the 2% and 5% tornado lines that drove the “MRGL” and “SLGT” areas were suggested by, or compromised with, the WFOs serving eastern KS. Only they and the SPC forecasters on duty could verify either way.

And even everything I’ve typed is just a superficial, condensed summary of the outlook forecast process. I did thousands of them, both the graphics and long-form text discussions, so give me the benefit of the doubt here.

[Addendum] From a subcomment I made on one of Alan Gerard’s BLOG posts:

Even if the 5-forecaster deficit on the SPC outlook/mesoscale desk didn’t directly influence this poor forecast, that doesn’t preclude its becoming a real problem as the season wears on and staff start wearing out.

Managers and less-senior fill-ins have scrambled to get the shifts covered creatively, without much OT as it turns out, and at the expense of granting leave. As you know from being an MIC, that’s just a very short-term band-aid. At some point, leave will pile up and have to be granted (or lost!), somebody or multiple somebodies will get sick with no shift room to spare, managers will have to do their day jobs eventually too, and with half the outlook positions still empty, something will have to give. I hope it’s not forecast quality.

If and when we start seeing consistent misses/overforecasts, and minor but normally uncommon errors becoming common in the products, that’s the sign that things are starting to go poorly, and that SPC is on the brink of disaster on the forecasting floor.

Meteorology of Kilauea Episode 36

by Leave a Comment

Cameras and any people near the west side of the Kilauea summit crater had great views of the large and spectacular, 5-hour daylight eruptive episode today (attached video captures).

NW Camera, crater rim

SW Camera, crater rim

I don’t know how many people were able to see it through their own eyeballs, though, because:

    1. The locations of these two USGS video cameras are prohibited to pedestrians due to the volcanic and loose-ground hazards, and
    2. Much of the rest of the crater rim was socked in with fog and rain, including the middle camera that is further from the eruption then these at the NW and SW edges of the crater.

Let’s dig into the meteorology of that. Why didn’t these views get fogged in too, despite northeasterly winds, blowing from the foggy areas, the whole time?

Fountaining episodes like this produce tremendous heat — not only convective (directed upward in the rising plume of hot air) but radiative (directed outward in all directions and diminishing with distance, akin to the sun). Lava is over 2,000 degrees F. Stand within a few feet of just a small, 8-inch-wide outbreak flow of glowing lava, as I did in late 2017, and the radiative heat will burn hairs off your arms. [I had no skin burns, but still smelled somewhat like charred flesh and burned boot rubber after that experience, as my then hiking partner Owen Shieh might recall!] Even for a Texan like me, lava is hot.

Here, two near-record giant fountains each launched a dense column of glowing, 2,000-degree liquid rocks sized from pebbles to cars and houses, over 1,000 feet into the air! For perspective, that’s nearly as high as the tallest Manhattan or Chicago skyscrapers. Tremendous pressure of superheated gas and rock built up underground, somewhat like a shaken can of Dr Pepper but on the scale of a city’s downtown, sent the lava so high for hours. On the way down, some of the rocks remained liquid, others solidified still glowing, and some cooled enough to lose the glow but still remain hot enough to boil water. We’ll cover that later.

I don’t know the amount of heat that is all told, and really can’t calculate it — too many variables. How much is given to convection, and how much to radiation? Unknown. It depends mainly on the volume of lava, and how much heat it loses while airborne, before smacking into the ground and losing some both to the ground and to the air later during cooling. Plus there’s the heat of the flowing and recently deposited lava below, rolling westward into lower parts of the crater, both radiatively and convectively added to the air above and upstream. Regardless, it was more than enough (mostly) radiative heat outside the fume plume to raise the temperature of the air around those cameras well above the dewpoint. How do I know? You can see the eruption clearly in the two cameras above, unlike the farther camera I didn’t show because it’s just a bunch of gray. See, no fog!

Increase the temperature well above the dewpoint, and keep the dewpoint about the same (there’s nothing to raise it outside the plume, which does contain some water steam), and the air clears. That happened here, despite the continuous and deep “moisture transport” into the eruption area from the east and northeast. Within some radius of the fountains, the heat was just too much for the moisture to condense cloud material. Fog is a cloud.

0Z Hilo Sounding, 10 Nov 25

Meteorologists use these “Skew-T log P” diagrams to profile the troposphere, where weather occurs. This one was from a balloon released at Hilo shortly before 00Z, or 2 pm Hilo time, during the eruption and upstream from it in low to middle levels (below about the “700” line, or 700-mb pressure level). The right solid line is temperature, the left, dewpoint. Where they’re right on each other, below the inversion, that’s a saturated condition, as you’d expect with temperature and dewpoint the same. Cloud and fog represent saturation. The inversion (layer of warmer temperature and drier dewpoint) is a few thousand meters above the level of the summit crater. This sounding explains why fog and rain occurred near the eruption site. If you drag the temperature line rightward (hotter) at the level of the crater, it gets farther from saturation too. That improves visibility.

Downstream from the crater is also downslope for that wind direction. That will cause compressional warming and sinking of air that didn’t get carried up into the convective plume. So fog should not be expected southwest of the crater for some distance, until the elevation levels off, downslope drying stops, and broader, prevailing moist marine air intermixes enough with the horizontal bubble of drier air to mix it away and permit local saturation into the airmass again.

As for the fountain or flowing-lava glows: Why didn’t the rain “put it out”? Again, way too much heat. Most of the raindrops boiled off in the superheated air right next to the lava (well above 212 degrees) before they even could touch it. Any drops that somehow could hit glowing lava, or even black lava still hotter than the boiling point, would be vaporized instantly. With a continual infusion of new lava, rain showers can’t keep up, and are powerless against that much heat! However, a lot of rain eventually will cool off lava once it’s no longer being laid down, much the same but on a slower time scale as the ocean does, once lava flows far enough into it to stop boiling it off.

This is how the Hawaiian Islands were made, how one still is being built, and how another (several miles south of the Big Island and still well underwater) will be.