dc.contributor.author
Paxian, Andreas
dc.contributor.author
Reinhardt, Katja
dc.contributor.author
Pankatz, Klaus
dc.contributor.author
Pasternack, Alexander
dc.contributor.author
Lorza-Villegas, Maria Paula
dc.contributor.author
Scheibel, Marc
dc.contributor.author
Hoff, Amelie
dc.contributor.author
Mannig, Birgit
dc.contributor.author
Lorenz, Philip
dc.contributor.author
Früh, Barbara
dc.date.accessioned
2023-03-17T09:44:28Z
dc.date.available
2023-03-17T09:44:28Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/38436
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-38154
dc.description.abstract
Water boards in Germany require decadal predictions to develop optimized management and adaptation strategies, especially within the claims of flood protection and water distribution management. Specifically, the Wupper catchment water board in western Germany is interested in decadal predictions of drought indices, which are correlated to dam water levels. For the management of small catchments, they need multi-year means and multi-year seasonal means of the hydrological seasons for forecast years 1–3 at high spatial resolution. Thus, the MPI-ESM-LR global decadal prediction system with 16 ensemble members at 200 km resolution was statistically downscaled with EPISODES to ~11 km in Germany. Simulated precipitation was recalibrated, correcting model errors and adjusting the ensemble spread. We tested different recalibration settings to optimize the skill. The 3-year mean and 3-year seasonal mean SPI (Standardized Precipitation Index), indicating excess or deficit of precipitation, was calculated. We evaluated the prediction skill with HYRAS observations, applying skill scores and correlation coefficients, and tested the significance of the skill at a 95% level via 1,000 bootstraps. We found that the high-resolution statistical downscaling is able to preserve the skill of the global decadal predictions and that the recalibration can clearly improve the precipitation skill in Germany. Multi-year annual and August–October mean SPI predictions are promising for several regions in Germany. Additionally, there is potential for skill improvement with increasing ensemble size for all temporal aggregations, except for November–January. A user-oriented product sheet was developed and published on the Copernicus Climate Change Service website (https://climate.copernicus.eu/decadal-predictions-infrastructure). It provides 3-year mean probabilistic SPI predictions for the Wupper catchment and north-western Germany. For 2021–2023, a high probability of negative SPI (dry conditions) is predicted in most of the area. The decadal prediction skill is higher than using the observed climatology as reference prediction in several parts of the area. This case study was developed in cooperation with the Wupper catchment water board and discussed with further German water managers: The skill of high-resolution decadal drought predictions is considered to be promising to fulfill their needs. The product sheet is understandable, well-structured and can be applied to their working routines.
en
dc.format.extent
21 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
decadal prediction
en
dc.subject
high resolution
en
dc.subject
statistical downscaling
en
dc.subject
recalibration
en
dc.subject
water management
en
dc.subject
user co-production
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::550 Geowissenschaften, Geologie::550 Geowissenschaften
dc.title
High-Resolution Decadal Drought Predictions for German Water Boards: A Case Study for the Wupper Catchment
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
867814
dcterms.bibliographicCitation.doi
10.3389/fclim.2022.867814
dcterms.bibliographicCitation.journaltitle
Frontiers in Climate
dcterms.bibliographicCitation.originalpublishername
Frontiers Media S.A.
dcterms.bibliographicCitation.volume
4 (2022)
dcterms.bibliographicCitation.url
https://doi.org/10.3389/fclim.2022.867814
refubium.affiliation
Geowissenschaften
refubium.affiliation.other
Institut für Meteorologie
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
2624-9553
refubium.resourceType.provider
DeepGreen