 |
| Titel |
Seasonal forecasts of droughts in African basins using the Standardized Precipitation Index |
| VerfasserIn |
E. Dutra, F. Giuseppe, F. Wetterhall, F. Pappenberger |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 17, no. 6 ; Nr. 17, no. 6 (2013-06-28), S.2359-2373 |
| Datensatznummer |
250018910
|
| Publikation (Nr.) |
 copernicus.org/hess-17-2359-2013.pdf |
|
|
|
|
|
| Zusammenfassung |
| Vast parts of Africa rely on the rainy season for livestock and agriculture.
Droughts can have a severe impact in these areas, which often have a very low
resilience and limited capabilities to mitigate drought impacts. This paper
assesses the predictive capabilities of an integrated drought monitoring and
seasonal forecasting system (up to 5 months lead time) based on the
Standardized Precipitation Index (SPI). The system is constructed by
extending near-real-time monthly precipitation fields (ECMWF ERA-Interim
reanalysis and the Climate Anomaly Monitoring System–Outgoing Longwave
Radiation Precipitation Index, CAMS-OPI) with monthly forecasted fields as
provided by the ECMWF seasonal forecasting system. The forecasts were then
evaluated over four basins in Africa: the Blue Nile, Limpopo, Upper Niger,
and Upper Zambezi. There are significant differences in the quality of the
precipitation between the datasets depending on the catchments, and a
general statement regarding the best product is difficult to make. The
generally low number of rain gauges and their decrease in the recent years
limits the verification and monitoring of droughts in the different basins,
reinforcing the need for a strong investment on climate monitoring. All the
datasets show similar spatial and temporal patterns in southern and
north-western Africa, while there is a low correlation in the equatorial
area, which makes it difficult to define ground truth and choose an adequate
product for monitoring. The seasonal forecasts have a higher reliability and
skill in the Blue Nile, Limpopo and Upper Niger in comparison with the
Zambezi. This skill and reliability depend strongly on the SPI timescale,
and longer timescales have more skill. The ECMWF seasonal forecasts have
predictive skill which is higher than using climatology for most regions. In
regions where no reliable near-real-time data is available, the seasonal
forecast can be used for monitoring (first month of forecast). Furthermore,
poor-quality precipitation monitoring products can reduce the potential
skill of SPI seasonal forecasts in 2 to 4 months lead time. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|