RainAware App: Rain Predictions to the Minute?

Scanning the wire recently, we learned of a new weather app that seemed both unique and practical. The goal of RainAware, currently available as an iPhone app, is to “predict to within minutes when precipitation will reach a user’s exact location, up to three hours in advance.” Knowing that weather can be challenging to predict, we were curious to learn more about this app and how it works (and no, we’ve not yet tried it).

We interviewed Ryan McGee of RainAware to learn more about the app and its capabilities. Here’s what he had to say:

How exact is “exact?”

We try to be precise to within half a mile and three minutes. This would be considered a “perfect” forecast. Compare this to any other forecast, which is typically for a general area AND only to within an hour or two. There are several limiting factors to how precise we can get:

1) Pixel resolution of radar images and radar bin size. We go down to one kilometer resolution here when locking onto and moving areas of precipitation.

2) Radar data frequency. Typically 5 to 10 minutes, depending on what VCP (volume coverage pattern) the radar is in. The program looks for new information every minute and recalculates once new data is available, typically every five minutes.

3) The DBZ value used for precip. This can change depending on precipitation type, distance from the radar and vertical humidity profiles. These are really just estimates since the values vary. This could add a couple minutes of uncertainty.

4) Precipitation motion. This is a key element, and is difficult to attain accurately. We use several methods for extracting this information but our cornerstone is the “ensemble” method, which uses thousands of slightly different motion vectors and then uses probabilities to convert to most likely rain times.

How confident are you that future radar can be predicted?

We do not actually produce a “future” radar with our system, but we know there are some who try. This may be possible in some situations, but in other situations like summertime pulse storms it is impossible past a few minutes.

What kind of testing have you done? Has accuracy been assessed?

We have tested it thousands of times over the past two plus years, through all seasons and all areas of the country. With each case we observed, if it did not perform well, we investigated and re-wrote the code. In fact, this process will always be ongoing, in order to keep improving upon the system.

It is very difficult to make a “one size fits all” scheme, so we offer user settings that can affect output. Namely, the precipitation threshold. If users, for whatever reason, seem to get too many false alarms, they can raise the criteria. The converse is true for lack of detection.

Are there particular geographic locations where you’ve tested the app?

We have tested it everywhere. There are gaps in radar coverage over the mountains of the western U.S., so it can’t work there. Also, it helps to have multiple radars covering the same area, which is true of the central and eastern U.S. That way if a radar is down you have a backup. There is logic build into the app that goes into choosing which radar is used. Then there are some areas that may have clutter more often than others. While we do employ clutter suppression, sometimes this comes through, especially near mountains.  Lake effect snow is another area we will be improving upon by next winter.

How much development has gone into the product?

Over two years of testing and development and thousands of hours of coding. We are perfectionists, so this will be ongoing.

Are users more apt to be over-warned or under-warned?

We want to err slightly on the side of detection, but this is not a large bias. And again, users can adjust to one of three different sensitivity levels to suit their needs.

If the app says it will rain in 13 minutes what are the odds that that will actually happen?

At thirteen minutes out, it is highly likely it will rain but allow a few minutes (maybe three or so) buffer to account for the errors previously discussed. We use an ensemble of motions and the output is probability based so that “13 minutes” is based on a probabilistic threshold. If you look at the bar graph (third page of the app’s main screen), you will be able to see the probabilities (bar heights). The red horizontal line is the “best” threshold to use based on testing, and optimizing CSI [critical success index] scores for rain (CSI is a bit POD [probability of detection] biased). So while it might say, “It’s gonna rain in 13 minutes” on the main timer screen, a quick swipe will allow you to see how confident we are that it will occur. We feel the default threshold, out of the box, exhibits the best all around skill level.

What about instances in which rain develops over top of a location, essentially without warning?

In these cases, rain times will only appear once precipitation is detected on radar. We do not claim to be able to work magic, but we do claim to lock onto precipitation as fast as humanly possible. With 1-minute checks for new data, we are sure to do that. Now, we DO have some special wording in situations where there is a high likelihood of “sudden” development. We may say, “Dry for now, but good chance of precipitation later this afternoon,” or we may even say, “Precipitation may develop at any time!” Further, if there are showers somewhat upstream of the user, but not necessarily “going” to hit them, we may mention there are showers in the area. Summertime “pop up” storms is another area we will be focusing on in the near future. This is one of the hardest weather elements to try to “put in a box.”

Are there circumstances you expect will be better handled than others? (i.e., winter rain seems more predictable than summer pop-up storms)

You are correct. Summer pop up storms in weak flow environments are hard to lock onto and properly move. But the question is whether any human can do better staring at a radar full of pulse storms popping up. Our goal is to be as good or better than a human meteorologist. We do have methods we are working on to optimize this, so stay tuned.

And yes, winter precipitation is more easily handled because of good flow aloft/steering currents. But light snow can also be hard to detect, especially if you are not close to the radar. It is difficult to determine whether you are simply seeing clouds and virga, or if there is light precipitation occurring.

Very light precip, such as drizzle or sporadic flurries, may not be handled well, just due to radar detecting capabilities. That said, we have seen RainAware pick up shallow heavy drizzle and mist on days when the official forecast simply said “Mostly Cloudy.”

Do you have an idea of future upgrades and additional capabilities consumers can expect down the road?

One of our first updates will include the ability to choose from a list of about 1,000 cities across the U.S. Currently, the program is limited to one’s GPS location and a short list of sites. Look for this in version 1.0.1, coming in the next few weeks.

We understand the radar imagery in our app is basic, as it is meant to be more of a supplement rather than an all-out, full tilts program. We could spend time on improving the radar, such as adding pinch zoom. However, we are trying to focus on perfecting rain start and stop times currently. We are aware of its limitations.

We expect the user interface may be redesigned at some point as well. Version 1.0.0 is only the beginning. We have a place on our website for users to enter feedback and comments that will help improve the system.

Ultimately, RainAware has one main goal: to tell the user what time precipitation will begin and end. Our vision is to someday make this information as easy to get as the time of day. Imagine always having a rain time wherever you see a clock. That’s an awful lot of computing power, but possible.

Have you tried RainAware? Feel free to leave your comments.