Articles | Volume 21, issue 7
https://doi.org/10.5194/hess-21-3307-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-3307-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Jul 2017
Research article |
| 04 Jul 2017
The analogue method for precipitation prediction: finding better analogue situations at a sub-daily time step
Pascal Horton
CORRESPONDING AUTHOR
Institute of Earth Sciences, University of Lausanne, Lausanne, Switzerland
Oeschger Centre for Climate Change Research and Institute of Geography, University of Bern, Bern, Switzerland
Charles Obled
Laboratoire d'étude des Transferts en Hydrologie et Environnement (LTHE), Université de Grenoble-Alpes, Grenoble, France
Michel Jaboyedoff
Institute of Earth Sciences, University of Lausanne, Lausanne, Switzerland
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Cited
16 citations as recorded by crossref.
- Impact of global atmospheric reanalyses on statistical precipitation downscaling P. Horton & S. Brönnimann 10.1007/s00382-018-4442-6
- Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues D. Raynaud et al. 10.5194/hess-24-4339-2020
- Analysis of urban rainfall from hourly to seasonal scales using high‐resolution radar observations in the Netherlands I. Manola et al. 10.1002/joc.6241
- A multiscale approach to statistical downscaling of daily precipitation: Israel as a test case D. Sandler et al. 10.1002/joc.8315
- RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension Á. González-Cervera & L. Durán 10.5194/gmd-17-7245-2024
- A diagnostic study of heavy rainfall events in upper Ganga and Sharda river basins, India B. Sudeepkumar et al. 10.1007/s00703-023-00954-5
- AtmoSwing: Analog Technique Model for Statistical Weather forecastING and downscalING (v2.1.0) P. Horton 10.5194/gmd-12-2915-2019
- Estimating multivariate ecological variables at high spatial resolution using a cost‐effective matching algorithm R. Renne et al. 10.1002/ecs2.4811
- Statistical reconstruction of daily precipitation and temperature fields in Switzerland back to 1864 L. Pfister et al. 10.5194/cp-16-663-2020
- Improving short to medium range GEFS precipitation forecast in India S. Saminathan et al. 10.1016/j.jhydrol.2021.126431
- Surface Weather Parameters Forecasting Using Analog Ensemble Method over the Main Airports of Morocco B. Alaoui et al. 10.1007/s13351-022-2019-0
- Analogue methods and ERA5: Benefits and pitfalls P. Horton 10.1002/joc.7484
- Improved Forecasting of Extreme Monthly Reservoir Inflow Using an Analogue-Based Forecasting Method: A Case Study of the Sirikit Dam in Thailand S. Amnatsan et al. 10.3390/w10111614
- Optimizing Analog Ensembles for Sub-Daily Precipitation Forecasts J. Jeworrek et al. 10.3390/atmos13101662
- Monthly to seasonal prediction of tropical Atlantic sea surface temperature with statistical models constructed from observations and data from the Kiel Climate Model X. Li et al. 10.1007/s00382-020-05140-6
- The analogue method for precipitation prediction: finding better analogue situations at a sub-daily time step P. Horton et al. 10.5194/hess-21-3307-2017
15 citations as recorded by crossref.
- Impact of global atmospheric reanalyses on statistical precipitation downscaling P. Horton & S. Brönnimann 10.1007/s00382-018-4442-6
- Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues D. Raynaud et al. 10.5194/hess-24-4339-2020
- Analysis of urban rainfall from hourly to seasonal scales using high‐resolution radar observations in the Netherlands I. Manola et al. 10.1002/joc.6241
- A multiscale approach to statistical downscaling of daily precipitation: Israel as a test case D. Sandler et al. 10.1002/joc.8315
- RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension Á. González-Cervera & L. Durán 10.5194/gmd-17-7245-2024
- A diagnostic study of heavy rainfall events in upper Ganga and Sharda river basins, India B. Sudeepkumar et al. 10.1007/s00703-023-00954-5
- AtmoSwing: Analog Technique Model for Statistical Weather forecastING and downscalING (v2.1.0) P. Horton 10.5194/gmd-12-2915-2019
- Estimating multivariate ecological variables at high spatial resolution using a cost‐effective matching algorithm R. Renne et al. 10.1002/ecs2.4811
- Statistical reconstruction of daily precipitation and temperature fields in Switzerland back to 1864 L. Pfister et al. 10.5194/cp-16-663-2020
- Improving short to medium range GEFS precipitation forecast in India S. Saminathan et al. 10.1016/j.jhydrol.2021.126431
- Surface Weather Parameters Forecasting Using Analog Ensemble Method over the Main Airports of Morocco B. Alaoui et al. 10.1007/s13351-022-2019-0
- Analogue methods and ERA5: Benefits and pitfalls P. Horton 10.1002/joc.7484
- Improved Forecasting of Extreme Monthly Reservoir Inflow Using an Analogue-Based Forecasting Method: A Case Study of the Sirikit Dam in Thailand S. Amnatsan et al. 10.3390/w10111614
- Optimizing Analog Ensembles for Sub-Daily Precipitation Forecasts J. Jeworrek et al. 10.3390/atmos13101662
- Monthly to seasonal prediction of tropical Atlantic sea surface temperature with statistical models constructed from observations and data from the Kiel Climate Model X. Li et al. 10.1007/s00382-020-05140-6
Latest update: 31 Mar 2025
Short summary
The analogue method aims at forecasting precipitation by means of a statistical relationship with meteorological variables at a large scale, such as the general atmospheric circulation. A moving time window has been introduced here in order to allow finding better analogue situations at different hours of the day. This change resulted in a better analogy of the atmospheric circulation, with improved prediction skills, and even to a greater extent for days with heavy precipitation.
The analogue method aims at forecasting precipitation by means of a statistical relationship...
