A lot can change overnight. Yesterday evening's model runs were increasingly pessimistic about how much snow would fall in the Seattle area. However, this morning's projections are looking more on the optimistic sie for seeing 4-6 inches of snow in the Seattle area. So what changed?
In my last blog post I talked about how the location of the surface low moving in off the coast would be critical in determining the amount and duration of the snow event in Seattle. Too far north and we'll rapidly transition to rain. Too far south and we won't get enough moisture brought north to overcome the large amount of cold dry air at the surface over Seattle. Yesterday, the models were bringing in the small surface low into the coast at or just south of the mouth of the Columbia River--this was a bit too far south to get the maximum snow in Seattle. We'd see some snow, but not much.
At least, that's what last night's 00Z models were saying. But then something changed overnight--the surface low got closer to land. And as the surface low gets closer to land, it enters our observation network--it gets closer to our offshore buoys and weather stations on the shore. As such, we get a lot more data about the strength and position of the surface low the closer it gets to shore. We can use that data to improve our model analysis of where the surface low might be. This is done through a process called data assimilation. Most of my research revolves around improving this very process. So what did data assimilation tell us about the low overnight?
Below is a map from our experimental real-time ensemble Kalman filter system (a type of data assimilation system) here at the University of Washington. This system uses the power of ensemble modeling to really give us a good idea of the amount of uncertainty in a particular forecast, then uses that uncertainty to help determine how observation will impact the model. This is an increment map of sea-level pressure from 6Z last night (10 PM). You'll see the familiar sea-level pressure contours in black. This is what the model system thought the sea-level pressure field was before we assimilated data. The color shadings show the impact of assimilating all the data we have--nearly 10,000 observations of wind, temperature, pressure and moisture from that entire area--into the model system. Anywhere you see red, that means that the observations wanted to increase the sea-level pressure there. Anywhere you see blue, that means the observations wanted to decrease the pressure there.
Now, our operational deterministic models that I show here don't include the data assimilation analyses from our experimental EnKF system. However, the initial and boundary conditions for their 12Z runs this morning do come from a larger model (the GFS) that does have a lot of data assimilation included. So, when looking at the 6-hour forecast of where our 4km WRF wants the surface low to come ashore this afternoon, we see this:
Remember last night the models had backed off to maybe 1-2 inches in the Seattle area. This morning's forecast shows 4-6 inches (with an interesting convergence-like band over the Kitsap Peninsula and Seattle...). Quite the change overnight.
And, since this morning's 12Z run (which is based on data from 4 AM), our ensemble Kalman filter (EnKF) system has continued to run. Here's the 15Z (7 AM) adjustment of sea-level pressure due to observations:
So, the forecast is still developing, but I have pretty high confidence that we'll see several inches in Seattle today. Not only are these short-range forecasts, but now that the low is close to the coast our models can take advantage of all of our observations here and really nail down where the low is going to be. I also already have two inches or so at my place, so yes--I have confidence.