.png){kind=icon}
.png){kind=icon}
Return
Evaluation and Improvement of the ECMWF Aviation Turbulence Forecasts
.png){kind=icon}
OA
AI
H
H
P
DOI：10.1029/2024JD043158.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This study evaluates the performance of the Integrated Forecasting System-clear-air turbulence (IFS-CAT) over a 1-year period (October 2022–September 2023) using in situ flight eddy dissipation rate (EDR) data. IFS-CAT ensemble forecasts exhibit the highest skill at z = 6–15 km during the Northern Hemisphere winter, as measured by an area under the relative operating characteristics curve exceeding 0.87. However, the probability of detection for moderate or greater (MOG) intensity turbulence is lower than 0.1, mainly due to the discrepancy between the employed lognormal EDR climatology as based on previous research and that observed in this study. Therefore, the IFS-CAT is recalibrated with an updated observation-based EDR climatology. Furthermore, the implied lognormal distribution parameters of the IFS-CAT are optimized to increase the detection rate of MOG intensity turbulence. Both improvements result in higher skill scores, which are also independently validated against research aircraft data from the SouthTRAC campaign in 2019.
Keywords:
aviation turbulence
ECMWF
IFS
forecast
prediction
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
J
IF:
3.4
Papers:
2.2W
Citations:
7.7W
Organization
Cited Papers