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A novel technique consists of new algorithm to glean vital details about atmospheric rivers from satellite tv for pc observations
The Science
Atmospheric rivers (ARs) are filaments of intense moisture transport within the environment. These climate techniques drive a big fraction of the intense precipitation occasions over coastal areas. Detecting ARs in satellite tv for pc observations has lengthy been a difficult activity because of the lack of wind data. In new analysis, scientists derived an approximation of the three-dimensional (3-D) wind area based mostly on the spatial distribution of the satellite-based temperature. Combining this approximated 3-D information with the moisture noticed by satellite tv for pc, scientists created—for the primary time—a technique to detect ARs by way of satellite tv for pc observations. Utilizing this newly developed technique, scientists produced the primary satellite-based near-global AR dataset.
The Affect
Scientists have lengthy since detected ARs utilizing information from numerical mannequin simulations. Using satellite tv for pc observations would have given them a real-time, world view of ARs solely based mostly on observations, which was extra fascinating, however such data was out of attain because of the lack of matching wind information.
Now, utilizing a novel technique to approximate the 3-D wind information by way of satellites, scientists can robotically detect ARs utilizing satellite tv for pc observations, they usually’ve produced a benchmark AR dataset for practically the complete globe. Moreover, their analysis of current AR information reveals that reanalyses overestimate the frequency of precipitation produced in ARs however underestimate its depth.
Abstract
ARs are filaments of intense horizontal moisture transport within the environment. They’re answerable for many of the poleward atmospheric moisture transport over mid-latitudes and are very efficient in driving excessive precipitation. Traditionally, analyses and predictions of ARs had been finished utilizing merchandise from numerical fashions that might solely think about incomplete data from satellite tv for pc, radiosonde, and ground-based observations as enter. Moreover, current satellite-based AR detection algorithms had been primarily solely on regional scales. For years it was the most effective observational-based data scientists had as they tried to trace and predict such excessive climate occasions.
In a brand new examine, scientists developed a near-global AR detection algorithm that comes with 3-D wind data from satellite tv for pc observations, offering a way more correct image of impending excessive climate occasions all over the world. The brand new algorithm combines each the moisture area and wind data, specifically two key elements defining AR, from satellites. Scientists used the brand new detection technique to create the primary satellite-based near-global AR dataset. Utilizing this new dataset as a benchmark, scientists are studying the shortfalls of earlier AR analyses, akin to width of the ARs, they usually mentioned the findings can assist enhance the illustration of ARs and related precipitation in reanalyses and local weather fashions. As the standard of satellite tv for pc observations continues to enhance, the methodology introduced right here may be utilized to different satellite tv for pc observations to develop larger decision or larger frequency AR statistics.
PNNL Contact
Hailong Wang
hailong.wang@pnnl.gov
Funding
This analysis has been supported by the Division of Vitality Workplace of Science Regional and World Mannequin Evaluation program space as a part of the HiLAT-RASM mission.
Ma, W., G. Chen, B. Guan, C. A. Shields, B. Tian, and E. Yanez. 2023. “Evaluating the representations of atmospheric rivers and their related precipitation in reanalyses with satellite tv for pc observations.” Journal of Geophysical Analysis: Atmospheres, 128, e2023JD038937. https://doi.org/10.1029/2023JD038937
Courtesy of PNNL.
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