Evaluation of a Probabilistic Subfreezing Road Temperature Nowcast System Based on Machine Learning

Baldwin, M.E.; Reeves, H.D.; Rosenow, A.A.

doi:10.1175/WAF-D-23-0137.1

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Evaluation of a Probabilistic Subfreezing Road Temperature Nowcast System Based on Machine Learning

2023
By Baldwin, M.E. ; Reeves, H.D. ; Rosenow, A.A.
Source: Wea. Forecasting, 38, 2427–2440

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Journal Title:

Weather and Forecasting
Personal Author:

Baldwin, M.E. ; Reeves, H.D. ; Rosenow, A.A.

Baldwin, M.E. ; Reeves, H.D. ; Rosenow, A.A. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory) ; CIWRO (Cooperative Institute for Severe and High-Impact Weather Research and Operations)

OAR (Oceanic and Atmospheric Research) ; NSSL (National Severe Storms Laboratory) ; CIWRO (Cooperative Institute for Severe and High-Impact Weather Research and Operations) Less -
Description:

Road surface temperatures are a critical factor in determining driving conditions, especially during winter storms. Road temperature observations across the United States are sparse and located mainly along major highways. A machine learning–based system for nowcasting the probability of subfreezing road surface temperatures was developed at NSSL to allow for widespread monitoring of road conditions in real time. In this article, these products were evaluated over two winter seasons. Strengths and weaknesses in the nowcast system were identified by stratifying the evaluation metrics into various subsets. These results show that the current system performed well in general, but significantly underpredicted the probability of subfreezing roads during frozen precipitation events. Machine learning experiments were performed to attempt to address these issues. Evaluations of these experiments indicate reduction in errors when precipitation phase was included as a predictor and precipitating cases were more substantially represented in the training data for the machine learning system.
Keywords:

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Machine Learning Statistics Weather Forecasting Forecast Skill Forecast Verification Transportation Meteorology
Source:

Wea. Forecasting, 38, 2427–2440
DOI:

https://doi.org/10.1175/WAF-D-23-0137.1
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PDF
Document Type:

Journal Article
Funding:

Grant no. NA21OAR4590162 ; NA22OAR4590169

Grant no. NA21OAR4590162 ; NA22OAR4590169 Less -
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Submitted
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urn:sha256:29c76adf43e2a72f8b10e3e74dbff88a24be43f365ebdfe3fbac661adb5dcd7e
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Evaluation of a Probabilistic Subfreezing Road Temperature Nowcast System Based on Machine Learning

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