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www.copernicus.org | ||
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publications.copernicus.org
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gmd.copernicus.org
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| | | | | 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... | |
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blogs.egu.eu
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| | | | | 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... | |
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amt.copernicus.org
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| | | Abstract. Solubility of aerosol trace elements, which determines their bioavailability and reactivity, is operationally defined and strongly depends on the leaching protocol used. Ultrapure water batch leaching is one of the most widely used leaching protocols, while the specific leaching protocols used in different labs can still differ in agitation methods, contact time, and filter pore size. It is yet unclear to which extent the difference in these experimental parameters would affect the aerosol trac... | ||
