San Diego got a month’s worth of rain in a single day on Dec. 12. Almost 1.6 inches of precipitation drenched the downtown area, something the city needed but didn’t expect.
The public had been told to prepare for about half as much rain by forecasters at the National Weather Service in Rancho Bernardo, where computer screens constantly glow with the latest data and satellite images.
“We thought (the storm) would strengthen farther south, over Mexico,” forecaster Ivory Small said after the deluge. “But the system strengthened over Point Loma.”
The weather service is right more often than it’s wrong. Forecasters nailed this weekend's cold snap. But mistakes aren’t uncommon, especially when they involve forecasting the intensity and movement of winter storms. Such systems can be as fickle as a moody teenager, and there are times when forecasters can’t see what’s about to happen due to the limitations of science.
We discussed those limitations with the MIC, which is weather service shorthand for the meteorologist-in-charge. In Rancho Bernardo, the MIC is Roger Pierce, a veteran meteorologist who says forecasting can be tricky even in a comparative Eden like San Diego.
Q: What makes forecasting Southern California storms hard from a scientific standpoint?
A: The lack of data. Our storms come off the ocean, and the only data sources we have between the West Coast and Asia are a few weather buoys, weather observations from Hawaii, and reports from ships as they cross the Pacific.
The observations come from the surface and from weather balloons, and they are critical for our computer models. We also use data from satellites, which are spectacular in the volume of information they provide and the area they cover. But it’s not the same as “gold standard” data — knowing exactly what’s going on at the surface and where the balloons fly.
Sometimes, meteorologists greatly underestimate or overestimate the strength of a storm by just using satellite data. They have to scramble to make quick corrections once the storm comes on shore.
Another issue is our understanding of the physics of the atmosphere, and coding information about it into the weather models. We have greatly improved our understanding of weather over the past 50 years and our models are great. But they are still just models, and they don’t precisely predict what is going to happen. The National Oceanic and Atmospheric Administration’s Research Division does a lot of weather and climate research, but funding has not kept pace over the past 20 years. A new infusion of funding is needed for both NOAA and the university community to get our weather research back on track.
Q: There seems to be a disconnect here. Space satellites get extraordinary images and data about places like Mars and Saturn. Why aren’t the remote-sensing capabilities of Earth weather satellites better?
A: This is really a matter of scale and perspective. We have what appear to be very good general ideas about the average weather conditions on Mars and Saturn, but it is not at the level of the 24-hour-a-day, seven-day-a-week, information we get for Earth. We “think” we are doing a good job on those other planets, but we don’t have very much, if any, specific and precise verification (ground truth) that the remotely sensed data are 100 percent correct. In fact, I would be surprised if it is anywhere near that value.
Q: People are increasingly wearing small fitness and medical devices that record data and relay it to a computer. Couldn’t thousands of ships be fitted with automated weather stations that send data to NOAA?
A: Some ships already do. The major issue here is: “Who going to pay for the data?” It’s more costly when you are traversing the ocean to transmit data in a timely fashion than if you’re on land and can use cellphone technology or small transmitter devices.
A new technology, which is showing promise, is the unmanned aircraft, which flies at high elevations for long periods of time with various types of weather-sensing equipment. They include dropsondes, which collect weather data as they parachute to earth.
Q: You use a variety of atmospheric models in forecasting. Why so many?
A: Each weather model has its strengths and weaknesses based on what the model’s original developers had in mind. Most of the differences involve time scales and internal physics. For instance, one of our models is set up to focus on the big picture weather pattern — where the big storms are — and other models are designed to focus on individual storm circulations, such as that of a hurricane.
Q: NOAA says that meteorologists can improve a model-based rain forecast by about 25 percent and a temperature forecast by 10 percent. Will the models improve to the point that human meteorologists won’t be needed?
A: Someday, yes, but when is someday?
Eventually we will get to the point where models are “good enough” — given the cost-benefit ratio — to have forecasters spend more time helping people understand more precisely what to expect. Already, the National Weather Service has begun placing a focus on explaining the impacts of the weather through our Weather Ready Nation initiative to complement what are already very good science forecasting standards and capabilities.
Q: Nate Silver writes about forecasting in his new book “The Signal and the Noise.” He raises a mind-bending question: “If we knew the position of every molecule in the earth’s atmosphere ... could we make perfect weather predictions? Or is there a degree of randomness inherent in the weather? What do you think?
A: Speaking theoretically, he is correct; we could make perfect predictions. The issue is the cost of sensing every molecule in the earth’s atmosphere and having the model to track it into the future. In fact, I believe we have the technology to provide excellent forecasts of significant events, it is just not cost effective.
I do think there is a certain degree of randomness. But if we had the capabilities of sensing the molecules’ movement in a short enough time, virtually all significant weather events would have incredible predictability.