Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1175/JHM-D-15-0053.1
Title (Primary) Seasonal soil moisture drought prediction over Europe using the North American Multi-Model Ensemble (NMME)
Author Thober, S.; Kumar, R. ORCID logo ; Sheffield, J.; Mai, J.; Schäfer, D.; Samaniego, L. ORCID logo
Source Titel Journal of Hydrometeorology
Year 2015
Department CHS
Volume 16
Issue 6
Page From 2329
Page To 2344
Language englisch
UFZ wide themes RU5;
Abstract Droughts diminish crop yields and can lead to severe socio-economic damages and humanitarian crisis (e.g., famine). Hydrologic predictions of soil moisture droughts several months in advance are needed to mitigate the impact of these extreme events. In this study, the performance of a seasonal hydrologic prediction system for soil moisture drought forecasting over Europe is investigated. The prediction system is based on meteorological forecasts of the North American Multi-Model Ensemble (NMME) that are used to drive the mesoscale Hydrologic Model (mHM). The skill of the NMME based forecasts is compared against those based on the Ensemble Streamflow Prediction (ESP) approach for the hindcast period of 1983-2009. The NNME based forecasts exhibit an Equitable Threat Score that is on average 69% higher than the ESP based ones at a six month lead time. Among the NMME based forecasts, the full ensemble outperforms the single best performing model CFSv2, as well as all subensembles. Subensembles, however, could be useful for operational forecasting because they are showing only minor performance losses (less than 1%), but at substantially reduced computational costs (up to 60%). Regardless of the employed forecasting approach, there is considerable variability in the forecasting skill ranging up to 40% in space and time. High skill is observed when forecasts are mainly determined by initial hydrologic conditions. In general, the NMME based seasonal forecasting system is well suited for a seamless drought prediction system as it outperforms ESP based forecasts consistently over the entire study domain at all lead times.
Persistent UFZ Identifier
Thober, S., Kumar, R., Sheffield, J., Mai, J., Schäfer, D., Samaniego, L. (2015):
Seasonal soil moisture drought prediction over Europe using the North American Multi-Model Ensemble (NMME)
J. Hydrometeorol. 16 (6), 2329 - 2344 10.1175/JHM-D-15-0053.1