Microwave brightness temperature on top of visible reflectance for Hurricane Harvey prior to its landfall in Texas. Credit: Penn State
In 2017, Hurricane Harvey stalled after making landfall over seaside Texas, putting down record rainfall, flooding communities, and turning into one of the wettest and most devastating storms in United States history. A new strategy utilizing readily available information reduces forecast errors and could enhance track, intensity, and rains projections for future storms like Hurricane Harvey, according to Penn State researchers.
” Our research study shows that opportunities exist for producing more precise projections for tropical cyclones using readily available yet underutilized information,” said Yunji Zhang, assistant research professor in the Department of Meteorology and Atmospheric Science at Penn State. “This could lead to much better warnings and readiness for tropical cyclone-associated dangers in the future.”
Adding microwave data collected by low-Earth-orbiting satellites to existing computer weather forecast models revealed enhancements in forecasting storm track, strength, and rainfall when utilizing Hurricane Harvey as a case-study, the scientists said.
” This is particularly important when a hurricane matures in later phases of development, when noticable and meaningful cloud structures exist and you cant see whats going on beneath them,” Zhang stated. “Thats the time when cyclones are most unsafe because theyre really strong and sometimes currently approaching landfall and threatening individuals. Thats when the microwave data are going to offer the most valuable details.”.
” Rainfall forecasts are extremely crucial for preparing the public for hazards and evacuations,” Zhang stated. “If we have a better understanding of how lots of rains particles there are in the storm, we have a higher probability of more precise projections of how much rainfall there will be.
” Over the ocean, we do not have other kinds of observations beneath the cloud tops to inform us where eyewalls are, where the greatest convections are, and how numerous rain or snow particles there remain in those regions, other than for occasional reconnaissance aircraft that fly into a few of typhoons,” Zhang stated. “This is really crucial for later forecasts of how intense storms will be or how much rains typhoons will bring.”
The research develops on the teams prior work that improved cyclone forecasts utilizing data assimilation, a statistical technique that intends to paint the most accurate photo of present weather conditions, crucial because even little modifications in the environment can result in large inconsistencies in projections with time.
In the previous work, scientists with Penn States Center for Advanced Data Assimilation and Predictability Techniques took in infrared brightness temperature level data from the U.S. Geostationary Operational Environmental Satellite, GOES-16. Brightness temperature levels reveal how much radiation is produced by objects in the world and in the atmosphere, and the scientists used infrared brightness temperatures at various frequencies to paint a much better photo of climatic water vapor and cloud development.
Infrared sensing units just record what is happening at the cloud tops. Microwave sensing units view a whole vertical column, offering new insight into what is happening underneath clouds after storms have actually formed, the scientists stated..
” This is specifically essential when a hurricane grows in later stages of advancement, when noticable and meaningful cloud structures exist and you cant see whats going on beneath them,” Zhang said. “Thats the time when typhoons are most unsafe because theyre very strong and often currently approaching landfall and threatening individuals. Thats when the microwave information are going to provide the most important details.”.
Integrating assimilated infrared and microwave information lowered projection errors in track, fast accumulation, and peak strength compared to infrared radiation alone for Hurricane Harvey, the researchers reported in the journal Geophysical Research Letters. They stated assimilating both sets of information resulted in a 24-hour increase in projection lead-time for the quick climax of the storm, a critical time when some storms rapidly gain strength.
Absorbing the microwave information also caused a much better understanding of the quantity of water particles in the storm and more precise rains amounts to for Harvey, the scientists said.
” Rainfall forecasts are extremely important for preparing the general public for evacuations and dangers,” Zhang said. “If we have a better understanding of how numerous rainfall particles there are in the storm, we have a higher probability of more accurate projections of how much rainfall there will be. Based upon that, we will have more innovative guidance on how people must respond.”.
The researchers stated additional work is needed to enhance the designs microphysics to imitate water and ice particles more reasonably.
This research study is based on work by previous Penn State Distinguished Professor Fuqing Zhang, who led the project at the time of his unanticipated death in July 2019.
” When our dear buddy and coworker Fuqing Zhang died, the thread of ideas that wove together our continuous combined infrared and microwave brilliance data assimilation experiments unraveled,” said Eugene Clothiaux, professor of meteorology and climatic science and a co-author of the paper. “We came together over an extended time period to reassemble the thread as best as possible.”.
Recommendation: “Ensemble-Based Assimilation of Satellite All-Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017 )” by Yunji Zhang, Scott B. Sieron, Yinghui Lu, Xingchao Chen, Robert G. Nystrom, Masashi Minamide, Man-Yau Chan, Christopher M. Hartman, Zhu Yao, James H. Ruppert Jr., Atsushi Okazaki, Steven J. Greybush, Eugene E. Clothiaux and Fuqing Zhang, 13 December 2021, Geophysical Research Letters.DOI: 10.1029/ 2021GL096410.
Likewise contributing from Penn State were Steven Greybush, associate professor; Xingchao Chen, assistant teacher; and Man-Yau Chan, Christopher Hartman and Zhu Yao, graduate students.
Numerous previous Penn State doctoral students, postdocs and professors likewise contributed: Scott Sieron, assistance researcher at I.M. Systems Group; Yinghui Lu, associate teacher at Nanjing University in China; Robert Nystrom, postdoc at the National Center for Atmospheric Research; Masashi Minamide, assistant teacher at the University of Tokyo; James Ruppert, assistant teacher at the University of Oklahoma; and Atsushi Okazaki, assistant teacher at Hirosaki University in Japan.
The National Science Foundation, NASA, the National Oceanic and Atmospheric Administration and the Department of Energy Biological and Environmental Research program supported this work.