Articles | Volume 13, issue 6
https://doi.org/10.5194/essd-13-2701-2021
https://doi.org/10.5194/essd-13-2701-2021
Data description paper
 | 
15 Jun 2021
Data description paper |  | 15 Jun 2021

Bias-corrected and spatially disaggregated seasonal forecasts: a long-term reference forecast product for the water sector in semi-arid regions

Christof Lorenz, Tanja C. Portele, Patrick Laux, and Harald Kunstmann

Viewed

Total article views: 4,264 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,264 890 110 4,264 86 105
  • HTML: 3,264
  • PDF: 890
  • XML: 110
  • Total: 4,264
  • BibTeX: 86
  • EndNote: 105
Views and downloads (calculated since 27 Oct 2020)
Cumulative views and downloads (calculated since 27 Oct 2020)

Viewed (geographical distribution)

Total article views: 4,264 (including HTML, PDF, and XML) Thereof 3,849 with geography defined and 415 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 02 Nov 2024
Download
Short summary
Semi-arid regions depend on the freshwater resources from the rainy seasons as they are crucial for ensuring security for drinking water, food and electricity. Thus, forecasting the conditions for the next season is crucial for proactive water management. We hence present a seasonal forecast product for four semi-arid domains in Iran, Brazil, Sudan/Ethiopia and Ecuador/Peru. It provides a benchmark for seasonal forecasts and, finally, a crucial contribution for improved disaster preparedness.
Altmetrics
Final-revised paper
Preprint