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A lot of terms are duplicated on these pages: Glossary, Terminology & EFAS data terminology. Combine all and update here.
CEMS-Flood data is associated with a certain terminology that can be difficult to grasp. This page summarises some of the most important terms that can be useful when reading the wiki pages and dealing with the data.
| Term | Definition |
|---|---|
| Analysis | An analysis is our best simulated estimate of reality, used as a proxy for observations which do not exist everywhere. It is the archived lead time 0 of a forecast. For example, the archived EFAS simulation forced with observation (sfo in MARS) is an analysis. |
| Archived forecast | Archived forecasts are forecast runs generated in real time fashion in the past. Unlike the reforecasts, they are not re-run when the model changes, so the model version used is not consistent throughout time. |
| Deterministic forecast (hres) | A single forecast realisation from a Numerical Weather Prediction (NWP) model. Typically, deterministic forecasts are associated with high spatial resolution that require more computational resource to run. Deterministic forecasts do not contain any information on the forecast uncertainty and are generally considered less reliable than the mean of the (probabilistic) ensemble forecast beyond the first few days of the forecast horizon. |
| Control forecast (cf) | Ensemble forecast sub-set only including simulation obtained from the control member of the corresponding Numerical Weather Prediction (NWP). The control member is the unperturbed forecast run at the resolution of the ensemble forecast. It should be used in combination with the perturbed forecasts. |
| Ensemble forecast (ENS, pf) | A number of simulations (members) using the same Numerical Weather Prediction (NWP) model but varying the initial conditions. The ensemble members are perturbed (pushed away from the observed state) with regards to the best estimate of the initial conditions, and the ensemble spread should ideally reflect the model error. Ensemble forecasts are often used to express the uncertainty of a forecast by associating a probability with different forecast values. The mean of an ensemble forecast has been shown, on average, to have higher predictive skill than the corresponding high-resolution forecast. |
| Benchmark | A dataset against which another dataset is compared. It can be a reference dataset or the forecast outputs from a previous version of the system. |
Class | A class defines different groups of data in MARS. Class ce stands for Copernicus Emergency Management Services. This is important for accessing data through the Climate Data Store and MARS. |
| Climatology | Any reference simulation, including historical simulations forced with observations, reanalysis or reforecasts. |
| Ensemble Streamflow Prediction (ESP) | A hydrological forecasting method developed in the mid-1970s for reservoir operations in the US. It consists of starting a hydrological model with the latest initial hydrological conditions (e.g., soil moisture, river level, snow cover, etc) and forcing it with historical meteorological observations (e.g., precipitation, temperature, evaporation, etc), or reanalysis. Each ensemble member thus corresponds to a year of historical meteorological observations. For example, to generate hydrological forecasts on the 1st of February 2016 for the next 7 months of lead time, the hydrological model are started with the hydrological conditions observed on the 1 February 2016. Meteorological forcing are then taken from each available year of meteorological observations for the 1st of February - 31st August (+7 months). |
| ERA5 | ERA5 is a comprehensive reanalysis, from 1950 to near real time, which assimilates as many observations as possible in the upper air and near surface. The ERA5 atmospheric model is coupled with a land surface model and a wave model. It is generated by ECMWF for the Copernicus Climate Change. For further details, visit ERA5 documentation. |
| Experiment version (expver) | An experiment version defines the type of simulation. Expver 1 stands for the operational data and is the official release of the data. Other numbers define test versions and experimental data, and should only be used with caution. |
| Extended-range forecast | In the ECMWF context, extended range forecast it is the ensemble forecast with a lead time of 46 days. It is issued bi-weekly (Mondays and Thursdays) at 00UTC. |
| Fill-up (fu) | A period used to bridge the gap between the latest (proxy-)observations (e.g. observed meteorological fields or reanalysis forcing such as ERA5) and the start of the forecast (00UTC or 12UTC, several days after the latest observations are available) when running a hydrological forecast chain. It is generated using the most recent high-resolution Numerical Weather Prediction forecast as forcing, hence expected not to be as accurate as the operational simulations forced by observations. Associated data are not recommended for use except for very specialised modelling exercise for warm-start of past forecasts. |
| Simulation forced with observation (sfo) | Hydrological time series simulation forced with observations, reanalysis or other proxy for observations. It is considered as the best estimate of the reality and can be considered as a hydrological reanalysis. It can be used to monitor and analysed what happened in the past, as initial conditions of the forecasts and reforecasts, or ,if generated from multi-decadal historical forcing, as reference dataset. |
| Forecast horizon | A forecast horizon (also called lead time) is the length of time into the future the forecast is valid for. It is typically expressed in hours or days. |
| High-resolution forecast (HRES, fc) | It the EFAS context, a single simulation with one meteorological forecast input (deterministic) of higher spatial resolution than the ensemble forecast input (probabilistic). The high-resolution Numerical Weather Prediction NWP input is usually better than ensemble forecasts in resolving local features, such as orographic precipitation, but small deviations in the model simulation, for example, geographical displacement, can cause large deviations in the hydrological output in comparison with observations. |
| Hindcast | A hindcast is a commonly used term for reforecast, a set of forecast simulations performed for a set of past dates, based on a configuration as close as possible to the operational setting. Hindcast now tends to be less used than reforecast. |
| Lead time | A lead time (also called forecast horizon) is the length of time into the future the forecast is valid for. It is typically expressed in hours or days. |
| Long-term run | A commonly used term to describe a multi-decadal historical simulation forced with observation that can be used as reference dataset. |
| MARS | Meteorological Archival and Retrieval System is the ECMWF archiving system for storing its forecast data, accessible to eligible users. (see MARS user documentation for details) |
| Maximum lead time | The maximum lead time (or maximum forecast horizon) is the longest lead time a forecast is generated for. |
| Medium-range forecast | Forecasts produced for a lead time of several days (typically 3-15 days). |
| Numerical weather prediction model (NWP) | Mathematical models of the atmosphere, oceans, and land processes that predict the future weather based on current weather conditions. |
| Perturbed forecast (pf) | Ensemble forecast sub-set excluding its control member. Generally used in combination with the control forecast. The order of the numbering of the perturbed forecasts is random. |
| Probabilistic forecast | Another terminology for ensemble forecast where several simulations (members) are generated using the same Numerical Weather Prediction (NWP) model but varying the initial conditions and/or the tendencies. It is often used as opposed to deterministic forecast. |
| Reanalysis | A reanalysis is the same as analysis (estimate of the atmosphere, ocean or land processes) but produced using a fixed model version giving the benefit that the model does not change over the time period of the reanalysis (note that the observations assimilated does still change over time depending on what was available). |
| Reference dataset | A dataset used to derive climatological statistics to use for providing relevant context to interpret other datasets, such as forecasts and reforecasts. |
| Reforecast | Forecast simulations performed for a set of past dates, based on a configuration as close as possible to the operational setting. They are used for example to evaluate the forecast skills against a benchmark or reference forecast. They sometimes are called hindcasts, especially in the context of seasonal forecasting. |
| Seasonal-range forecast | Forecasts produced for a lead time of several months (typically 30 days to 7 months) |
| Time step | Time increments for simulation dataset such as forecast, reforecast or reanalysis. For a forecast, a time step of 6 hours means that the forecast as a value every 6 hours until the maximum forecast horizon. |
| Upstream area | The total area that contributes with water to a specific point on the river network. Also known as a catchment area. |