PhysMetrics.Weather is an evaluation framework that quantifies physical realism of ML weather prediction models using conservation, spectral, and dynamical metrics.
How large does a large ensemble need to be?
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
verdicts
UNVERDICTED 4representative citing papers
WeatherSyn is the first instruction-tuned MLLM for weather forecasting report generation, outperforming closed-source models on a new dataset of 31 US cities across 8 weather aspects.
LangPrecip treats weather text as semantic motion constraints in a rectified-flow trajectory generator to improve multimodal precipitation nowcasting, yielding over 60% and 19% gains in heavy-rain CSI at 80-minute lead times on Swedish and MRMS data.
Image-to-image networks estimate parameters of non-stationary SAR models faster and more accurately than traditional methods by framing fields and parameters as images.
citing papers explorer
-
PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models
PhysMetrics.Weather is an evaluation framework that quantifies physical realism of ML weather prediction models using conservation, spectral, and dynamical metrics.
-
WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation
WeatherSyn is the first instruction-tuned MLLM for weather forecasting report generation, outperforming closed-source models on a new dataset of 31 US cities across 8 weather aspects.
-
LangPrecip: Language-Aware Multimodal Precipitation Nowcasting
LangPrecip treats weather text as semantic motion constraints in a rectified-flow trajectory generator to improve multimodal precipitation nowcasting, yielding over 60% and 19% gains in heavy-rain CSI at 80-minute lead times on Swedish and MRMS data.
-
LatticeVision: Image to Image Networks for Modeling Non-Stationary Spatial Data
Image-to-image networks estimate parameters of non-stationary SAR models faster and more accurately than traditional methods by framing fields and parameters as images.