In collaboration with the National Oceanic and Atmospheric Administration (NOAA) and other research institutes, UC Berkeley researchers have evaluated NOAA’s high-quality smoke detection model or HRRR-smoke, which predicts the amount and movement of smoke during the 2018 Camp Fire.
According to Tina Chow, a professor of civil and environmental engineering at campus, campfire is a single, regional fire that emits smoke from one area and affects the entire bay. Camp Fire continues to be the deadliest wildfire in California’s history, destroying 85 victims and more than 18,000 buildings, CAL FIRE reported.
More than 200 a week after the US Air Quality Index was fired, and “Unhealthy” Air Condition Campus Chancellor Carol Christo announced that classes will be canceled after November 15, 2018, until November 20.
“There was only one fire going on,” Cho said. “It’s easy to say that all the smoke came from the campfire.”
Chaw regularly reviews weather programs to assess weather and wind direction during the fire. In the midst of her search, she discovered the experimental HRRR-Smoke website, which prompted her to find NOAA models to collaborate on the project.
The HRRR-Smoke Model was launched in December 2020 and is considered an official U.S. forecasting tool, co-author and research associate at the NOAA Global Systems Laboratory and senior research associate at the Institute of Environmental Science Research at the University of Colorado Boulder.
“This study is informative because it helps other researchers understand the strengths and weaknesses of the smoke model we use,” said co-author of the review and campus student Alexander Young.
A recent study published in the American Meteorological Society Bulletin in June is one of the first in-depth proofs of the HRRR-smoke model, Choo said.
Researchers have compared the effects of the HRRR-smoke model with a variety of sources, such as forecasters, environmental sensory networks, satellite imagery, and atmospheric observations.
“The model works well and helps to predict the location of the chimney and its focus in a certain jumping time, for example a day ago,” Young said.
However, one of the limitations of the model is that it results in an unexpected amount of smoke during the second week of camp fire. James and Chaw said that in the second week, the high levels of smoke satellites were unable to detect the fire.
James said this limitation underscores the need for high-quality satellite detection and motivates satellites to work forward to improve their algorithms in smoke time.
The young man said the study could use scientists and models to improve future smoke detection and health problems.
“We are working hard to develop a new system called the Renewable Forecasting System, which is essentially a replacement for the HRRR,” said James.
In addition to the HRRR-smoke standards, the new model also includes dust blowing, which can reduce dust exposure in deserts, James added.
The rapid update forecasting system is designed to optimize overlapping models and reduce maintenance and code management. It can also predict fire, smoke, thunderstorms, rain and other weather conditions, he said.
“If you just look at the weather forecast, they update the weather model every time they gather information about the current weather conditions,” Chow said. “Now we’re saying we have to do the same thing to smoke.”
Winnie Law leader is an environmental and climate correspondent. Her in [email protected]And follow her on Twitter @winniewy_lau.