Microwave data assimilation improves forecasts of hurricane intensity, rainfall

Date:
February 1, 2022
Source:
Penn State
Summary:
In 2017, Hurricane Harvey stalled after making landfall over
coastal Texas, pouring down record rainfall, flooding communities
and becoming one of the wettest and most destructive storms in
United States history.

A new technique using readily available data reduces forecast
errors and could improve track, intensity and rainfall forecasts
for future storms like Hurricane Harvey, according to scientists.



FULL STORY ==========================================================================
In 2017, Hurricane Harvey stalled after making landfall over coastal
Texas, pouring down record rainfall, flooding communities and becoming one
of the wettest and most destructive storms in United States history. A
new technique using readily available data reduces forecast errors and
could improve track, intensity and rainfall forecasts for future storms
like Hurricane Harvey, according to Penn State scientists.


==========================================================================
"Our study indicates that avenues exist for producing more accurate
forecasts for tropical cyclones using available yet underutilized data,"
said Yunji Zhang, assistant research professor in the Department of
Meteorology and Atmospheric Science at Penn State. "This could lead to
better warnings and preparedness for tropical cyclone-associated hazards
in the future." Adding microwave data collected by low-Earth-orbiting satellites to existing computer weather forecast models showed
improvements in forecasting storm track, intensity and rainfall when
using Hurricane Harvey as a case-study, the scientists said.

"Over the ocean, we don't have other kinds of observations underneath
the cloud tops to tell us where eyewalls are, where the strongest
convections are, and how many rain or snow particles there are in
those regions, except for occasional reconnaissance aircraft that fly
into some of hurricanes," Zhang said. "This is very important for later predictions of how intense storms will be or how much rainfall hurricanes
will bring." The research builds on the team's prior work that improved hurricane forecasts using data assimilation, a statistical method that
aims to paint the most accurate picture of current weather conditions, important because even small changes in the atmosphere can lead to large discrepancies in forecasts over time.

In the prior work, scientists with Penn State's Center for Advanced Data Assimilation and Predictability Techniques assimilated infrared brightness temperature data from the U.S. Geostationary Operational Environmental Satellite, GOES-16. Brightness temperatures show how much radiation is
emitted by objects on Earth and in the atmosphere, and the scientists
used infrared brightness temperatures at different frequencies to paint
a better picture of atmospheric water vapor and cloud formation.



==========================================================================
But infrared sensors only capture what is happening at the cloud tops.

Microwave sensors view an entire vertical column, offering new insight
into what is happening underneath clouds after storms have formed,
the scientists said.

"This is especially important when a hurricane matures in later stages
of development, when pronounced and coherent cloud structures exist and
you can't see what's going on underneath them," Zhang said. "That's the
time when hurricanes are most dangerous because they're very strong and sometimes already approaching landfall and threatening people. That's when
the microwave data are going to provide the most valuable information." Combining assimilated infrared and microwave data reduced forecast errors
in track, rapid intensification and peak intensity compared to infrared radiation alone for Hurricane Harvey, the researchers reported in the
journal Geophysical Research Letters. They said assimilating both sets
of data resulted in a 24- hour increase in forecast lead-time for the
rapid intensification of the storm, a critical time when some storms
quickly gain strength.

Assimilating the microwave data also led to a better understanding of
the amount of water particles in the storm and more accurate rainfall
totals for Harvey, the scientists said.

"Rainfall predictions are extremely critical for preparing the public for hazards and evacuations," Zhang said. "If we have a better understanding
of how many rainfall particles there are in the storm, we have a higher likelihood of more accurate forecasts of how much rainfall there will
be. Based on that, we will have more advanced guidance on how people
should react." The scientists said additional work is needed to
improve the model's microphysics to simulate water and ice particles
more realistically.



==========================================================================
This study is based on work by former Penn State Distinguished Professor
Fuqing Zhang, who led the project at the time of his unexpected death
in July 2019.

"When our dear friend and colleague Fuqing Zhang died, the thread of
ideas that wove together our ongoing combined infrared and microwave
radiance data assimilation experiments unraveled," said Eugene Clothiaux, professor of meteorology and atmospheric science and a co-author of the
paper. "We came together over an extended period of time to reassemble
the thread as best as possible." Also contributing from Penn State were
Steven Greybush, associate professor; Xingchao Chen, assistant professor;
and Man-Yau Chan, Christopher Hartman and Zhu Yao, graduate students.

Several former Penn State doctoral students, postdocs and faculty also contributed: Scott Sieron, support scientist at I.M. Systems Group;
Yinghui Lu, associate professor at Nanjing University in China; Robert
Nystrom, postdoc at the National Center for Atmospheric Research; Masashi Minamide, assistant professor at the University of Tokyo; James Ruppert, assistant professor at the University of Oklahoma; and Atsushi Okazaki, assistant professor 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.

========================================================================== Story Source: Materials provided by Penn_State. Original written by
Matthew Carroll. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. 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, Atsushi Okazaki, Steven
J. Greybush, Eugene E.

Clothiaux, Fuqing Zhang. Ensemble‐Based Assimilation of
Satellite All‐Sky Microwave Radiances Improves Intensity
and Rainfall Predictions for Hurricane Harvey (2017). Geophysical
Research Letters, 2021; 48 (24) DOI: 10.1029/2021GL096410 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220201143940.htm

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