About Those Seasonal Forecasts

 NOAA released an updated seasonal forecast yesterday, which immediately got everyone in a lather with much of Utah being "in the green" for January to March precipitation.  

But let's all take a deep breath here.  First, these outlooks have never been very reliable (or all that useful for skiers).  Remember the outlooks from last season?  My "favorite" was the one issued by Accuweather last September.

That didn't age well in the Sierra and Utah that's for sure.  

Second, let's talk a bit about what the NOAA seasonal outlook actually means.  It is a probabilistic outlook, meaning that they are not forecasting those areas in green to definitely receive above normal precipitation.  Instead in the first two shades of green, they are saying that the odds are leaning to above normal.  For example, southern and central Utah are in the first shade of green, which means they are giving a 33–40% chance of above normal precipitation.  In any given season, if you have no idea what will happen, there's 33% chance of above normal, a 33% chance of near normal, and a 33% chance of below normal, so this is a very minor shift of the odds. 

But let's look a bit closer at the rationale behind the NOAA forecast.  Such forecasts are based in part on precipitation during prior El Nino events (this winter is expected to be an El Nino winter) and ensemble forecasts produced by statistical and numerical models.  Here's a snippet from the discussion issued with the seasonal outlook:

"Despite a strong El Nino event highly likely this upcoming winter and spring, the NMME and C3S dynamical model guidance depicts high forecast spread and seasonal precipitation outcomes - both in sign (i.e., wet/dry) and location. This is quite different from similar forecast guidance preceding the 2015-2016 El Nino event. Given this, the forecast probabilities for either above-normal or below-normal seasonal precipitation are quite modest for the western CONUS. Elevated odds for above-normal precipitation is depicted for parts of California and Nevada during DJF 2023-2024 and JFM 2024, with slightly elevated probabilities extended across the central Rockies. The best convergence of ancillary information, forecast tools and model guidance is the primary basis for the selection of this area."

I have underlined a key phrase, which essentially says there is a lack of correspondence in the guidance.  And this guidance isn't very good in the first place!  Walk away from the craps table now! 

Note also that the northern edge of the green shading is draped across Salt Lake County.  If they are anticipating any loading of the dice for the central Wasatch, it is very slight.  

I continue to stand by my usual outlook for the central Wasatch.  We simply cannot provide a reliable outlook of what is going to happen with snowfall this season near and above about 7000 feet.  If you guess below, near, or above average, you have about a 1/3 chance of that guess being right.  Below 7000 ft, there is probably some loading of the dice for below average snowfall and snowpack simply due to the fact that we are now living in a warmer climate system, but as we saw last year, Mother Nature can still bring the goods with the right pattern, so I'm not going all in on that.  

Finally, stop worrying about this winter.  A bad year in the Cottonwoods is better than a good year in Colorado, so just plan on skiing it if it's white. 

Back in Time...

Many of the products we provide on weather.utah.edu derive from computer models run by the National Centers for Environmental Prediction, or NCEP for short.  Centers is plural because NCEP actually consists of nine National Weather Service centers that deliver national and global products from weather warnings and forecasts to computer model guidance.

We are fortunate in the United States that government weather data from NCEP and other government agencies is for the most part freely available.  This enables groups like mine and others to drive products like those on weather.utah.edu and to develop new forecast techniques.  Many private companies can integrate NCEP model forecasts into their operations, from IBM to Amazon.  This has huge benefits for the nations economy and resilience to weather hazards.  In many other countries, this is not the case as government groups may charge for these products.

When I began my education in the late 1980s, there was essentially no ability to get digital model output from NCEP.  Model forecasts came via difax machine and you only got a few levels.  In my office, I have a small photo of myself standing in front of these difax charts on my graduate day in 1989.  The only way to forecast the weather during this period was to go to the department's map room and look at these charts.  

Around that time, some groups began to explore the possibility of obtaining and using the NCEP model output in novel ways.  One was here at the University of Utah where John Horel (currently our Department Chair), Lloyd Staley, and Tim Barker began to access and display NCEP model forecast data obtained via satellite broadcast.

  

Critical for this effort were the initial products developed by Unidata, a community of education and research institutions supported by the Unidata Program Center in Boulder, CO, which was and is still funded by the National Science Foundation.  This community and the Unidata Program Center exists today and pushes the envelope of what is possible in atmospheric sciences education and research.  

My first foray into really taking advantage of these developing capabilities was in graduate school in 1994 when I began to work with Cliff Mass, Mark Albright, and others at the University of Washington to develop a real-time forecasting system for the Pacific Northwest.  Essential for that effort is the timely availability of model forecasts from NCEP to create the initial analyses and other information needed to run such a forecast system.  

In my 25+ year career at the University of Utah, model data from NCEP has been integral for my teaching efforts and the products we produce on weather.utah.edu.  In the case of the latter, we not only use that model data directly, but we also generate derived products that add considerable value to the raw model output and push the envelope of what is possible from a weather forecast standpoint.  Probably the most popular are the "forecast plumes" that we produce for Alta and many other sites and involve the application of downscaling techniques and snow-to-liquid ratio algorithms to produce higher-resolution forecasts.  The one below is for Alta and suggests we may see a return to powder skiing early next week.  Much thanks to Trevor Alcott and Mike Wessler, former students who developed much of this capability.  

However, every now and then we go through a rough patch and we're going through one now.  There is often a mismatch between the demands of the users of NCEP model products and their ability to provide them. Although some NCEP products are now available on the cloud, some of what we use for our ensemble products is not.  On April 20th, to avoid their servers being overwhelmed, NCEP throttled access on some of their servers, limiting user access to 120 hits per minute.

That sounds like a lot, but to generate the NAEFS products, we need to download 1508 files.  Prior to their April 20th "speed limit," we parallelized the downloading to speed things up.  

When NCEP throttled access, everything broke.  Our code was not built to deal with blocked access.  It took me some experimenting and testing to figure out how not to invoke the wrath of NCEP and how to deal with things if we do.  I've had to basically rewind the clock, going from parallel to serial downloading of the data and also building in delays to slow the code down.  Sadly, this isn't progress and it will probably result in the NAEFS products being ready about 15-20 minutes later than previously, although that's a guess as I never saved runtime information from the parallelized code before NCEP broke it.  

For those of you who use this data, my apologies for the delays.  If I was on the ball and monitoring things, I could have probably seen it coming and perhaps dealt with this in advance, although I confess that the time I have to actually program is pretty limited.  It may be a few days until things are running smoothly again.