Deep learning downscaled high|resolution daily near surface ...

Deep learning downscaled high-resolution daily near surface ...

U-Net, a deep-learning convolutional neural network, is used to downscale coarse meteorological data. Based on 19 models from the Coupled ...

(PDF) Deep learning downscaled high-resolution daily near surface ...

PDF | U-Net, a deep-learning convolutional neural network, is used to downscale coarse meteorological data. Based on 19 models from the Coupled Model.

Deep learning downscaled CMIP6 high-resolution (0.1°) daily near ...

Downscaling is a method to obtain high-resolution meteorological data. UNet, a great potential deep learning technology, is gaining popularity in ...

High-resolution downscaling with interpretable deep learning

Using interpretable machine learning methods, we demonstrate that the CNN has been capable of self-learning physically plausible relationships between the large ...

Deep Learning for Daily Precipitation and Temperature Downscaling

Coarse resolution data sets (such as climate reanalysis, numerical weather predictions, satellite products, and simulations of general circulation models) are ...

Downscaling CORDEX Through Deep Learning to Daily 1 km ...

High spatio-temporal resolution near-surface projected data is vital for climate change impact studies and adaptation.

Downscaled high spatial resolution images from automated ...

This study addresses this gap by integrating satellite images and volunteered geographical data, employing automated machine learning through ...

Deep learning downscaled high-resolution daily near surface ...

Deep learning downscaled high-resolution daily near surface meteorological datasets over East Asia. https://doi.org/10.1038/s41597-023-02805-9 ·. Видання ...

Spatial Downscaling of Near-Surface Air Temperature Based ... - MDPI

Deep learning methods can achieve a finer refinement required for downscaling meteorological elements, but their performance in terms of ...

Overview Deep Learning for Climate Downscaling/Super-Resolution

Super-resolution of near-surface temperature utilizing physical quantities for real-time prediction of urban micrometeorology, -, - ; Reconstructing High ...

A two-fold deep-learning strategy to correct and downscale winds ...

Once trained, Neural Network+DEVINE can model wind fields at high resolution, even over areas not included in the training process.

Downscaling near‐surface wind fields to high‐resolution topography ...

When physical processes need to be resolved in a spatially explicit manner, grids with high horizontal resolution of a few hundred meters are ...

Deep-Learning-Based Gridded Downscaling of Surface ... - jstor

The color shading is elevation at 4-km resolution. ... Ganguly, 2017: DeepSD: Generating high resolution climate change projections through single image super-.

Comparing ML Methods for Downscaling Near-Surface Air ... - MDPI

Our results demonstrate impressive accuracy with the Deep Learning-based models, obtaining Root Mean Squared Error (RMSE) values of 0.98 °C (ERA5) and 1.86 °C ( ...

Deep-Learning-Based Gridded Downscaling of Surface ...

-segmentation CNN, called UNet, to the downscaling of daily precipitation in western North America, from the low resolution (LR) of 0.25° to the high resolution ...

Exploring super-resolution spatial downscaling of several ... - Nature

Deep learning downscaled high-resolution daily near surface meteorological datasets over East Asia. Article Open access 12 December 2023 ...

first results for high-resolution urban precipitation climatology over ...

In this study, we develop and adopt a novel approach for urban downscaling by generating a general-purpose operator using deep learning.

Identifying high resolution benchmark data needs and Novel ... - arXiv

... deep learning models. We explore ... Deep learning downscaled high-resolution daily near surface meteorological datasets over East Asia.

Customized deep learning for precipitation bias correction and ...

We show that the customized DL model can better downscale and bias correct hourly precipitation datasets and provide improved precipitation ...

High-resolution downscaling with interpretable deep learning - OUCI

High-resolution downscaling with interpretable deep learning: Rainfall extremes over New Zealand · Neelesh Rampal · Peter B. Gibson · Abha Sood · Stephen Stuart ...