/explore
|
You are here 
|
www.copernicus.org | ||
| | | | |
www.egusphere.net
|
|
| | | | | [AI summary] The EGU interactive community platform provides a collaborative space for researchers and professionals in Earth, planetary, and space sciences. It includes a preprint repository, enabling scientists to share their work before peer review. The platform emphasizes open science, with content licensed under the Creative Commons Attribution 4.0 License. Users can engage with the community, access resources, and contribute to scientific discussions. The site also highlights data protection and legal compliance, ensuring transparency and user rights. | |
| | | | |
gmd.copernicus.org
|
|
| | | | | Abstract. Forecasting heavy precipitation accurately is a challenging task for most deep learning (DL)-based models. To address this, we present a novel DL architecture called multi-scale feature fusion (MFF) that can forecast precipitation with a lead time of up to 3?h. The MFF model uses convolution kernels with varying sizes to create multi-scale receptive fields. This helps to capture the movement features of precipitation systems, such as their shape, movement direction, and speed. Additionally, the... | |
| | | | |
blogs.egu.eu
|
|
| | | | | Contemporary science faces many challenges in publishing results that are reproducible. This is due to increased usage of data and digital technologies as well as heightened demands for scholarly communication. These challenges have led to widespread calls for more research transparency, accessibility, and reproducibility from the science community. This article presents current findings and solutions to these problems, including recent new software that makes writing submission-ready manuscripts for jou... | |
| | | | |
hess.copernicus.org
|
|
| | | |||
