dorsal/arxiv
View SchemaProbabilistic temperature forecasting: a comparison of four spread-regression models
| Authors | Stephen Jewson |
|---|---|
| Categories | |
| ArXiv ID | physics/0410053 |
| URL | https://arxiv.org/abs/physics/0410053 |
Abstract
Spread regression is an extension of linear regression that allows for the inclusion of a predictor that contains information about the variance. It can be used to take the information from a weather forecast ensemble and produce a probabilistic prediction of future temperatures. There are a number of ways that spread regression can be formulated in detail. We perform an empirical comparison of four of the most obvious methods applied to the calibration of a year of ECMWF temperature forecasts for London Heathrow.
{
"annotation_id": "e06a3496-6f01-4953-acac-ee419a61bfef",
"date_created": "2026-03-02T18:00:53.404000Z",
"date_modified": "2026-03-02T18:00:53.404000Z",
"file_hash": "334dc5e0828ff16c83829b0b0fae375dca34049b98641249f17fd9f714cf1a81",
"private": false,
"record": {
"abstract": "Spread regression is an extension of linear regression that allows for the\ninclusion of a predictor that contains information about the variance. It can\nbe used to take the information from a weather forecast ensemble and produce a\nprobabilistic prediction of future temperatures. There are a number of ways\nthat spread regression can be formulated in detail. We perform an empirical\ncomparison of four of the most obvious methods applied to the calibration of a\nyear of ECMWF temperature forecasts for London Heathrow.",
"arxiv_id": "physics/0410053",
"authors": [
"Stephen Jewson"
],
"categories": [
"physics.ao-ph"
],
"title": "Probabilistic temperature forecasting: a comparison of four spread-regression models",
"url": "https://arxiv.org/abs/physics/0410053"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "cda53a0a-27a9-4836-a38d-9ed1041531f8",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}