Q: What is numerical weather prediction (NWP) model?
A: A mathematical model that simulates atmospheric, oceanic, and land processes to predict the weather based on current weather conditions.
Q: What is medium-range forecast?
A: Forecasts produced for a lead time of several days (typically 3-15 days)
Q: What is ensemble forecasting?
A: A number of simulations (members) using the same meteorological model, but varying the initial conditions and/or the tendencies. The ensemble spread should ideally reflect the model error and is often used to express the uncertainty of a forecast by associating a probability with different forecast values.
Q: What is lead time?
A: Maximum forecast horizon, meaning how far into the future the forecast stretches.
Q: What is forced simulation?
A: Long-term (> 20-year) hydrological time series simulation forced with observations, reanalysis or other proxy for observations. Typically used to generate reference statistics. One important example of reference statistics is the return period magnitude: forecast simulations are compared to return period magnitudes to generate warnings.
Q: What is time step?
A: Time increments for each forecast. A time step of 6 hour means that the forecast has a value every 6 hours until the maximum forecast horizon.
Q: What is EFAS-IS?
A: EFAS-IS stands for EFAS Information System and it is the map viewer that presents all the EFAS products.
Q: What is the hydrological model in EFAS?
A: EFAS uses LISFLOOD as a hydrological model. LISFLOOD is a GIS-based, distributed hydrological rainfall-runoff-routing model specifically designed to be used in large scale catchments. Detailed information on its specific characteristics and example applications can be found in the online documentation. The LISFLOOD source code is available from GitHUB. The model is run in EFAS 4 for all of Europe on 5km grid and with a six-hourly timestep.
Q: Which are the meterological forecast systems in EFAS?
A: A number of meteorological forecast systems are used to generate the hydrological future scenaria. These forecasts are either deterministic or probabilistic and are generated by different providers (see Table 1).
Table 1. Characteristics of the meteorological forecasts.
Name of forecast models | Provider | Length [days] | Number of members | Spatial resolution |
DWD deterministic | DWD | 7 | 1 | ~ 6.5 km days 1-3 (~ 13 km days 4-7) |
ECMWF deterministic | ECMWF | 10 | 1 | ~ 9 km |
ECMWF ENS | ECMWF | 15 | 51 | ~ 18 km until 26.06.2023 ~ 9 km from 27.06.2023 |
| COSMO-LEPS | COSMO group | 5 | 20 | ~ 7 km |