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March 18, 2006

Is there an NWS web issue?

I love working with meteorologists. They perform such an important role in society. But their jobs are often underappreciated because they have to play so many roles...they are part teacher, part scientist, part artist. I enjoy providing tools that help them, and enjoy their criticism that helps me learn and grow and make the tools that ForecastWatch provides even better.

"Sandy in Arizona" left a comment on this blog. Thank you Sandy...it was the first comment (woohoo!!) :-). I hope you don't mind me talking about it here. If you would like to discuss further, please don't hesitate to contact me at any of the contact points mentioned on the websites.

Sandy made the comment:

I checked Tempe AZ...the NWS digital forecasts ranked number one while the NWS forecast ranked last...there would appear to be something wrong with your methodology. There almost always is with these types of sites.

Instead of asking us why the NWS digital forecast might be ranked differently than the NWS web forecast, Sandy proclaims that there "must be a problem with [our] methodology." I would certainly love to have a discussion about the methodology and uncover if there indeed is a problem. If there is, I would like to fix it. But with such a closed-minded statement like "There almost always is with these types of sites", I don't think there is much opportunity. The comment reeks of prejudice...ForecastWatch is just like all the other sites (BTW, what other sites? Can you send me some links please?) so why bother.

So let's look at Tempe, Arizona and see what the problem is [HINT: It's NOT a problem with the methodology, rather the NWS has a problem I think they need to fix].

The NWS forecasts that are graded for accuracy on ForecastAdvisor are the public forecasts available on weather.gov. The NWS Digital forecasts come from the SOAP interface to the NDFD. Forecasts on weather.gov are queried by zipcode, NDFD by latitude/longitude. ForecastWatch collects forecasts for all AWOS/ASOS observation sites, and maps the nearest/enclosing zipcode to each observation site.

For Tempe, Arizona, the forecast and observation site is actually Phoenix, Arizona. The AWOS/ASOS observing station is KPHX and the mapped zipcode is 85065. Zipcode 85065 encloses the AWOS/ASOS observing station, so for all intents and purposes they are equivalent as far as querying forecasts go.

So let's go to weather.gov and enter a couple of zipcodes. First, let's enter the zipcode of ForecastWatch's office, 43040. It returns a forecast for Marysville, Ohio. Just as expected. How about another random zipcode...68106 for Omaha, Nebraska. Again, perfect, the NWS forecast that shows up is for Omaha, Nebraska. No surprises so far.

Now lets enter the zipcode 85065 on weather.gov. Hmmm...that's odd, it returns a forecast for Quartzsite, Arizona. That's 128 miles from Phoenix. Let's try a nearby zipcode, say Scottsdale, Arizona (85260). Hmmm...Quartzsite again. Quartzsite sure does have a lot of zipcodes. Now let's look at querying from the region page (the Phoenix office website). When you query 85065, you get "not found" (though I can assure you the zipcode does exist). When you query 85260 you get Scottsdale, as expected.

What's happening then is that ForecastWatch is querying the NWS weather.gov site just like a user would, and when it queries zipcode 85065 it gets the forecast for Quartzsite, Arizona, 128 miles away. No wonder the NWS forecast shows as being so bad. It is! Shouldn't querying weather.gov for zipcode 85065 return the forecast for Phoenix, Arizona, not Quartzsite? It appears to me that there is a zipcode mapping problem. Most zipcodes appear to work just fine, but some, like 85065, do not. Can someone from the NWS comment? Thanks!

If "Sandy from Arizona" would have enquired if there was a problem with the methodology, instead of assuming it, unknown problems can be uncovered that may point in unexpected directions, lead to quality improvements, and discover things previously unknown.

I'll comment on Sandy's other comment ("same milk in the best looking bottle") in a future blog post.

 

 
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