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View article: GPTCast: a weather language model for precipitation nowcasting
GPTCast: a weather language model for precipitation nowcasting Open
This work introduces GPTCast, a generative deep learning method for ensemble nowcasting of radar-based precipitation, inspired by advancements in large language models (LLMs). We employ a generative pre-trained transformer (GPT) model as a…
View article: AI reconstruction of European weather from the Euro-Atlantic regimes
AI reconstruction of European weather from the Euro-Atlantic regimes Open
We present a non-linear AI-model designed to reconstruct monthly mean anomalies of the European temperature and precipitation based on the Euro-Atlantic Weather regimes (WR) indices. WR represent recurrent, quasi-stationary, and persistent…
View article: Can AI be enabled to perform dynamical downscaling? A latent diffusion model to mimic kilometer-scale COSMO5.0_CLM9 simulations
Can AI be enabled to perform dynamical downscaling? A latent diffusion model to mimic kilometer-scale COSMO5.0_CLM9 simulations Open
Downscaling based on deep learning (DL) is a key application in Earth system modeling, enabling the generation of high-resolution fields from coarse numerical simulations at reduced computational costs compared to traditional regional mode…
View article: Pretrained models for "GPTCast: a weather language model for precipitation nowcasting"
Pretrained models for "GPTCast: a weather language model for precipitation nowcasting" Open
Dataset for "GPTCast: a weather language model for precipitation nowcasting" Preprint: https://arxiv.org/abs/2407.02089 Code: https://github.com/DSIP-FBK/GPTCast Dataset: https://doi.org/10.5281/zenodo.13598348
View article: Can AI be enabled to dynamical downscaling? A Latent Diffusion Model to mimic km-scale COSMO5.0\_CLM9 simulations
Can AI be enabled to dynamical downscaling? A Latent Diffusion Model to mimic km-scale COSMO5.0\_CLM9 simulations Open
Downscaling techniques are one of the most prominent applications of Deep Learning (DL) in Earth System Modeling. A robust DL downscaling model can generate high-resolution fields from coarse-scale numerical model simulations, saving the t…
View article: Nowcasting of extreme precipitation events: performance assessment of Generative Deep Learning methods
Nowcasting of extreme precipitation events: performance assessment of Generative Deep Learning methods Open
Radar-based precipitation nowcasting is one of the most prominent applications of deep learning (DL) in weather forecasting. The accurate forecast of extreme precipitation events remains a significant challenge for deep learning models, pr…
View article: Can AI be enabled to dynamical downscaling? Training Deep Generative Models to downscale ERA5 to high-resolution COSMO-CLM dynamical reanalyses over Italy 
Can AI be enabled to dynamical downscaling? Training Deep Generative Models to downscale ERA5 to high-resolution COSMO-CLM dynamical reanalyses over Italy  Open
Downscaling techniques are one of the most prominent applications of Deep Learning (DL) in Earth System Modeling. A robust DL downscaling model can generate high-resolution fields from coarse-scale numerical model simulations, saving the t…
View article: Ensemble precipitation nowcasting by combination of generative and transformer deep learning models
Ensemble precipitation nowcasting by combination of generative and transformer deep learning models Open
This work introduces a novel deep-learning method for generating realistic ensembles nowcast of radar-based precipitation at a five-minute time resolution for the next 60 minutes and longer.The proposed method is composed of a combination …
View article: The Bolzano Tracer Experiment (BTEX)
The Bolzano Tracer Experiment (BTEX) Open
The paper describes the observational and modeling efforts performed under the Bolzano Tracer Experiment (BTEX). BTEX focused on the basin surrounding the city of Bolzano, at the junction of three tributary valleys on the southern side of …
View article: A dataset of tracer concentrations and meteorological observations from the Bolzano Tracer EXperiment (BTEX) to characterize pollutant dispersion processes in an Alpine valley
A dataset of tracer concentrations and meteorological observations from the Bolzano Tracer EXperiment (BTEX) to characterize pollutant dispersion processes in an Alpine valley Open
The paper describes the dataset of concentrations and related meteorological measurements collected during the field campaign of the Bolzano Tracer Experiment (BTEX). The experiment was performed to characterize the dispersion of pollutant…
View article: A dataset of tracer concentrations and meteorological observations from the Bolzano Tracer EXperiment (BTEX) to characterize pollutant dispersion processes in an Alpine valley
A dataset of tracer concentrations and meteorological observations from the Bolzano Tracer EXperiment (BTEX) to characterize pollutant dispersion processes in an Alpine valley Open
The paper describes the dataset of concentrations and related meteorological measurements collected during the field campaign of the Bolzano Tracer Experiment (BTEX). The experiment was performed to characterize the dispersion of pollutant…
View article: Tracer concentrations and meteorological observations from the Bolzano Tracer EXperiment (BTEX)
Tracer concentrations and meteorological observations from the Bolzano Tracer EXperiment (BTEX) Open
The data set contains ground concentrations and related meteorological measurements collected during the field campaign of the Bolzano Tracer EXperiment (BTEX).The experiment was performed to characterize the dispersion of pollutants emitt…
View article: Improving air quality assessment over complex terrain by optimizing meteorological and pollutant transport modeling
Improving air quality assessment over complex terrain by optimizing meteorological and pollutant transport modeling Open
The Alpine region is a sensitive area to air pollution, as it presents specific characteristics, which expose it to a greater environmental burden with respect to flat areas. During the last decades, the scientific community has developed …
View article: Optimization of Noah and Noah_MP WRF Land Surface Schemes in Snow-Melting Conditions over Complex Terrain
Optimization of Noah and Noah_MP WRF Land Surface Schemes in Snow-Melting Conditions over Complex Terrain Open
The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions i…
View article: Atmospheric dispersion modelling with AERMOD for comparative impact assessment of different pollutant emission sources in an Alpine valley
Atmospheric dispersion modelling with AERMOD for comparative impact assessment of different pollutant emission sources in an Alpine valley Open
High-resolution simulations are performed with the AERMOD dispersion model to assess the impact on air quality in the area surrounding the town of Vipiteno, in the Alps, from the main pollutant sources: the Brenner motorway, the town of Vi…