ArticleSensors (Basel, Switzerland)2021
Numerical Forecast Correction of Temperature and Wind Using a Single-Station Single-Time Spatial LightGBM Method.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Research on Wind Field Correction Method Integrating Position Information and Proxy Divergence.Biomimetics (Basel, Switzerland) · 2025Article
- Calibration of Integrated Low-Cost Environmental Sensors for Urban Air Temperature Based on Machine Learning.Sensors (Basel, Switzerland) · 2025Article
- Spatio-Temporal Characteristics of PMInternational journal of environmental research and public health · 2022Article
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Authors and funding
6 authors.
Funding
Abstract
Achieving high-performance numerical weather prediction (NWP) is important for people's livelihoods and for socioeconomic development. However, NWP is obtained by solving differential equations with globally observed data without capturing enough local and spatial information at the observed station. To improve the forecasting performance, we propose a novel spatial lightGBM (Light Gradient Boosting Machine) model to correct the numerical forecast results at each observation station. By capturing the local spatial information of stations and using a single-station single-time strategy, the proposed method can incorporate the observed data and model data to achieve high-performance correction of medium-range predictions. Experimental results for temperature and wind prediction in Hainan Province show that the proposed correction method performs well compared with the ECWMF model and outperforms other competing methods.
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Registered trials
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