Improved confidence in regional climate model simulations of precipitation evaluated using drought statistics from the ENSEMBLES models

Maule, Cathrine Fox; Thejll, Peter; Christensen, Jens Hesselbjerg; Svendsen, S. H.; Hannaford, Jamie

doi:10.1007/s00382-012-1355-7

Cited by 24 publications

(23 citation statements)

References 31 publications

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“…The results indicate that simulations from WRF that generally capture reasonably well the drought temporal evolutions in all regions studied show reliable temporal correlations. These results are consistent with previous studies which found that different RCMs performed adequately drought characteristics in terms of drought indices such as the SPEI and the SPI [ Barrera‐Escoda et al , ; Maule et al , ] over different areas in Spain. Furthermore, we found that the results obtained by using downscaled fields outperform those from the driving data in terms of drought indices, the improvement being higher for the SPI than for the SPEI.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Evaluation of WRF capability to detect dry and wet periods in Spain using drought indices

et al. 2017

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The Weather Research and Forecasting (WRF) model has been used to show the benefits provided by downscaled fields to detect and analyze wet and dry periods over a region with high precipitation variability such as Spain. We have analyzed the spatiotemporal behavior of two widely used drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), computed at 3 and 12 month time scales, which provide important information in an agricultural and water‐resource context. These two indices were computed from WRF outputs and compared with those calculated from observational (monthly precipitation and temperature databases of Spain, MOPREDAS and MOTEDAS) and from the European Centre for Medium‐Range Weather Forecasts Interim Re‐Analysis (ERA‐Interim) data sets. This evaluation was made by using a regional scale and a multistep regionalization method and by comparison of individual grid points. In general, results indicate that the drought indices obtained by using WRF outputs provide a noticeable improvement regarding those computed by using ERA‐Interim, higher at longer time scales. Although results show no significant differences between drought indices analyzed, the improvement offered by WRF is greater for SPI than for SPEI. In terms of averaged duration, magnitude, and severity of drought, the benefits provided by WRF are not so evident, presenting better agreement with the observational data at 12 month time scale, being clearer for the intensity. These findings evidence the benefit of using WRF climate fields to monitor, analyze, and detect drought events, being a valuable source of knowledge for a suitable decision making, especially for water‐resource management.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Evaluation of WRF capability to detect dry and wet periods in Spain using drought indices

et al. 2017

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“…In Olesen et al (2014) the Danish Meteorological Institute has collected and processed data from the ENSEMBLES project (http://www.ensembles-eu.org/, http: //ensemblesrt3.dmi.dk/; Van der Linden and Mitchell, 2009;Boberg et al, 2010;Maule et al, 2013). The report includes projection of weather extremes (including precipitation) using the SRES A1B scenario (IPCC, 2007) and is produced from an ensemble of 14 regional climate models in the EN-SEMBLES project.…”

Section: Datamentioning

confidence: 99%

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

Thorndahl

Andersen²,

Larsen³

2017

Hydrol. Earth Syst. Sci.

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Abstract. Continuous and long rainfall series are a necessity in rural and urban hydrology for analysis and design purposes. Local historical point rainfall series often cover several decades, which makes it possible to estimate rainfall means at different timescales, and to assess return periods of extreme events. Due to climate change, however, these series are most likely not representative of future rainfall. There is therefore a demand for climate-projected long rainfall series, which can represent a specific region and rainfall pattern as well as fulfil requirements of long rainfall series which includes climate changes projected to a specific future period. This paper presents a framework for resampling of historical point rainfall series in order to generate synthetic rainfall series, which has the same statistical properties as an original series. Using a number of key target predictions for the future climate, such as winter and summer precipitation, and representation of extreme events, the resampled historical series are projected to represent rainfall properties in a future climate. Climate-projected rainfall series are simulated by brute force randomization of model parameters, which leads to a large number of projected series. In order to evaluate and select the rainfall series with matching statistical properties as the key target projections, an extensive evaluation procedure is developed.

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“…Specific statistical properties for the future precipitation in Denmark are necessary in order to climate project the resampled rainfall series. In Olesen et al (2014) the Danish Meteorological Institute has collected and processed data from the ENSEMBLES project (http://www.ensembles-eu.org/, http: //ensemblesrt3.dmi.dk/; Van der Linden and Mitchell, 2009;Boberg et al, 2010;Maule et al, 2013). The report includes projection of weather extremes (including precipitation) using the SRES A1B scenario (IPCC, 2007) and is produced from an ensemble of 14 regional climate models in the EN-SEMBLES project.…”

Section: Datamentioning

confidence: 99%

Reply to review by Lars Bengtsson

Thorndahl¹

2017

Preprint

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The authors would like to pay our gratitude to reviewer L. Bengtsson for some useful comments and suggestions. LB1: The paper aims at determining rainfall for urban design. It is excellently written up to the result section, well describing previous research and the methodology used. However, the result section can be improved. When comparing observations and modeling it is not sufficient to conclude good or satisfactory agreemnet or letting the reader interprete figures by himself. C1

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Improved confidence in regional climate model simulations of precipitation evaluated using drought statistics from the ENSEMBLES models

Cited by 24 publications

References 31 publications

Evaluation of WRF capability to detect dry and wet periods in Spain using drought indices

Evaluation of WRF capability to detect dry and wet periods in Spain using drought indices

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

Reply to review by Lars Bengtsson

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