The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners.
As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.
i
Improving Nowcasting of Convective Development by Incorporating Polarimetric Radar Variables Into a Deep‐Learning Model
-
2021
-
-
Source: Geophysical Research Letters, 48(21)
[PDF-2.82 MB]
Details:
-
Journal Title:Geophysical Research Letters
-
Personal Author:
-
NOAA Program & Office:
-
Description:Nowcasting of convective storms is urgently needed yet rather challenging. Current nowcasting methods are mostly based on radar echo extrapolation, which suffer from the insufficiency of input information and ineffectiveness of model architecture. A novel deep-learning (DL) model, FURENet, is designed for extracting information from multiple input variables to make predictions. Polarimetric radar variables, KDP and ZDR, which provide extra microphysics and dynamic structure information of storms, are fed into the model to improve nowcasting. Two representative cases indicate that KDP and ZDR can help the DL model better forecast convective organization and initiation.
-
Keywords:
-
Source:Geophysical Research Letters, 48(21)
-
DOI:
-
ISSN:0094-8276;1944-8007;
-
Format:
-
Publisher:
-
Document Type:
-
Rights Information:Other
-
Compliance:Library
-
Main Document Checksum:
-
Download URL:
-
File Type:
