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DOI | 10.1007/s00382-020-05314-2 |
How to create an operational multi-model of seasonal forecasts? | |
Hemri S.; Bhend J.; Liniger M.A.; Manzanas R.; Siegert S.; Stephenson D.B.; Gutiérrez J.M.; Brookshaw A.; Doblas-Reyes F.J. | |
发表日期 | 2020 |
ISSN | 0930-7575 |
起始页码 | 1141 |
结束页码 | 1157 |
卷号 | 55 |
英文摘要 | Seasonal forecasts of variables like near-surface temperature or precipitation are becoming increasingly important for a wide range of stakeholders. Due to the many possibilities of recalibrating, combining, and verifying ensemble forecasts, there are ambiguities of which methods are most suitable. To address this we compare approaches how to process and verify multi-model seasonal forecasts based on a scientific assessment performed within the framework of the EU Copernicus Climate Change Service (C3S) Quality Assurance for Multi-model Seasonal Forecast Products (QA4Seas) contract C3S 51 lot 3. Our results underpin the importance of processing raw ensemble forecasts differently depending on the final forecast product needed. While ensemble forecasts benefit a lot from bias correction using climate conserving recalibration, this is not the case for the intrinsically bias adjusted multi-category probability forecasts. The same applies for multi-model combination. In this paper, we apply simple, but effective, approaches for multi-model combination of both forecast formats. Further, based on existing literature we recommend to use proper scoring rules like a sample version of the continuous ranked probability score and the ranked probability score for the verification of ensemble forecasts and multi-category probability forecasts, respectively. For a detailed global visualization of calibration as well as bias and dispersion errors, using the Chi-square decomposition of rank histograms proved to be appropriate for the analysis performed within QA4Seas. © 2020, The Author(s). |
英文关键词 | Multi-model combination; Recalibration; Seasonal forecasts |
语种 | 英语 |
scopus关键词 | climate change; climate modeling; correction; numerical model; probability; regional climate; seasonal variation; weather forecasting |
来源期刊 | Climate Dynamics
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文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/145359 |
作者单位 | Federal Office of Meteorology and Climatology MeteoSwiss, Zurich-Airport, Switzerland; Meteorology Group, Dpto. de Matemática Aplicada y Ciencias de la Computación, Universidad de Cantabria, Santander, Spain; University of Exeter, Exeter, United Kingdom; Meteorology Group, Instituto de Física de Cantabria (CSIC-Universidad de Cantabria), Santander, Spain; European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom; ICREA, Pg. Lluis Companys, Barcelona, Spain; Earth Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain |
推荐引用方式 GB/T 7714 | Hemri S.,Bhend J.,Liniger M.A.,et al. How to create an operational multi-model of seasonal forecasts?[J],2020,55. |
APA | Hemri S..,Bhend J..,Liniger M.A..,Manzanas R..,Siegert S..,...&Doblas-Reyes F.J..(2020).How to create an operational multi-model of seasonal forecasts?.Climate Dynamics,55. |
MLA | Hemri S.,et al."How to create an operational multi-model of seasonal forecasts?".Climate Dynamics 55(2020). |
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