It’s a real spring evening out there. Heavy thunderstorms are popping up in a couple of different areas, from New England, where severe weather has been reported all day from western New York to Massachusetts and New Hampshire. The primary severe component has been gusty winds.

New England storms aren’t usually good for radar imagery, but particularly with this squall, as the Boston radar is down for maintenance. There just isn’t a good way to look at the squall.

On the other hand, look at this iron curtain in west Texas.

That impressive ling of nearly solid red stretches from east of Wichita Falls to east of Del Rio, bringing strong winds, and a nice batch of cooler drier air behind it. Sharp differences in air mass often show up more impressively on radar, and that’s what we have here.

If this line can hold together as it moves eastward, strong winds loom for cities along I-35 like Dallas, Austin and San Antonio. Hail would only come in small bursts, and the tornado threat that had once been there is now becoming less likely, though there could be a spin up in the scud out ahead of the primary line.

This might be a noisy night for a lot of people in Texas, and the storm system is going to slow down, so east Texas will feel the bumps later in the weekend. By the time the storms wrap up, though, Texans should feel a little bit of refreshing air for a day or so.

Maybe it’s because we have spent so much time at home, but we got through a lot of forecasts in April. I prefer reviewing those months, because we really get a taste for how successful everyone was. This month, it was even a fairly close race, letting us know there were some good forecasters last month. In the end it was Accuweather who grabbed the top prize for the month. Let’s look at the individual wins, though.

That brings us to the totals for the year.

With a commanding lead that, it should be no surprise that The Weather Channel is indeed in the lead for forecaster of the year. This month, though, kudos belong to Accuweather. Way to go!

Models have been in the news quite a bit over the last several weeks, in particular as they relate to the COVID-19 Pandemic. There have been a great deal of concerns and questions as they relate to scientific modeling. I’m certainly not an epidemiologist, but meteorology is a field of science that relies heavily on modeling, so I thought I might share some insights.

Models, depending on the output desired, are essentially mathematical equations, in which variables are either solved for or assumed. The equations are given starting information, which is often altered, depending on observations, such as the temperature or barometric pressure in meteorology, or the case total or fatalities in a COVID model.

There is often discrepancy in the models versus what happens in real life because variables can be uncontrolled. In the case of the weather, the limited number of observations means there are gaps in information that are assumed, but not confirmed, which can lead to errors, especially over time.

The same can be said with COVID modeling, however the assumptions are based on how people will respond. The primary difference, at this point, between the various COVID models is assumptions based on how government ordered social distancing is instituted and remains in effect. One of the uncontrolled variables is how engaged in the population is in the social distancing, as the models only respond to the virus’s known rate of spread and mortality.

Models are only as good as the information that goes into them, but at the very least, they are effective at demonstrating trends, and giving an idea generally, if not always specifically, of the future. They can inform of responses of changes in variables. Weather models are updated regularly, and resubmitted with new data, with corresponding alterations to the forecast. COVID models are updated with new case numbers and new actions by the local populations and government.

Models exist to allow the public and the various powers that be to prepare and respond to pending conditions, whether they be thunderstorm or waves of illness. Unlike weather modeling, in which we are tasked with responding to the output, epidemic modeling allows us to alter the outcome with our actions, and are of particular value.

The last couple of years have seen April’s with historic late season snow storms that called into question the true definition of spring. This year, it’s bee significantly warmer, and dare I say spring like for a lot of the country. This as been with it’s negatives, of course, as the spring severe season has been particularly robust in the Southeast, but I think a lot of people are pretty pleased with how the weather has turned out in April.

The CPC would like to end your celebrating.

A large portion of the country, centered around the Great Lakes, is going to start May much cooler than normal. It probably won’t mean snow, but it shouldn’t be ruled out everywhere. Conversely, temperatures in the southwest, which have already been well above normal, are expected to continue to be significantly warmer than normal. Nobody is happy.

On the plus side, at least out east, is that cooler temperatures are more tolerable in May than they are in April. Additionally, cooler temperatures should help mitigate the severe season in the southern Plains. The first week of May has historically been a dangerous week in Oklahoma, but that doesn’t seem to be the case this year.

For warm weather lovers, the long range forecast isn’t great, but it could all certainly be worse.