3DVar Neural Network-Based Observation Operator

This repository provides the implementation of a nonlinear observation operator H for mapping ALADIN numerical weather prediction model outputs to radar–reflectivity observation space. The operator is implemented as a convolutional encoder–decoder neural network based on a residual U-Net (ResUNet). The network takes multi-level ALADIN model fields as input and produces radar reflectivity at the same horizontal resolution. The directory structure includes a TEST subdirectory containing a ready-to-use trained ResUNet model. The dataset necessary to train the model is: LISCA-ALADIN HNN (doi: 10.5281/zenodo.17880622).

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

Found an issue? Give us feedback

0

Average