The purpose of the monitoring is to provide a detailed statistical information on the quality and availability of the different components of the observing system used/monitored by ECMWF. The monitoring results are primarily produced to help improve the usage of observations within the ECMWF data assimilation systems. Most of the products are updated on a daily basis.
In this page
- Satellite data monitoring
- Conventional data monitoring
- Ocean observation monitoring
- Data automatic checking
- Monitoring of GUAN stations
- ECMWF Global Data Monitoring Report Archive
This section provides access to 6 hourly data coverage charts of observations available for use by the ECMWF data assimilation system (4DVAR). Each plot shows the available data for a family of observations.
The information contained in these pages is primarily intended to monitor the quality of satellite observations - providing feedback to data providers and warnings to data users. However, it should be noted that changes in the monitoring statistics may result from factors not directly related to the observations themselves:
- Departures are sensitive to variations in the accuracy of the atmospheric state that is used as a reference. In the case of ECMWF Operations - significant and sudden jumps can arise from scheduled model and data assimilation upgrades. For departures computed against ERA-Interim and ERA5, the model and data assimilation system versions are essentially fixed, but there are known variations in the quality of the reference state reflecting the time evolution of the global observing network (see ERA-Interim configuration and performance and ERA5 configuration )
- Departures are also sensitive to the accuracy of the mapping from the reference model state variables to the quantities that are observed by the satellite. For radiance measurements this mapping is the RTTOV radiative transfer model in which a number of assumptions and approximations are made. For example, no account is taken of spatial or time variations in atmospheric trace gas composition for the simulation of infrared radiance measurements. Thus great care must be taken in the interpretation of long time series departure statistics where significant changes in the real atmospheric composition (particularly carbon dioxide) are known to have occurred.
The satellite monitoring is organised by satellite data types:
- All sky Microwave radiances
- Clear sky Microwave radiances
- Infrared sounding radiances
- GPS Radio Occultation (GPSRO)
- Atmospheric Motion Vectors
- Aeolus Horizonal Line-Of-Sight wind
- Geostationary radiances
- Surface wind
- Soil Moisture and Ocean Salinity (SMOS)
- NESDIS Snow and Ice Mapping System (IMS)
- Ozone monitoring
- Soil moisture
- Significant wave height
This section shows monitoring statistics for in-situ measurements used by the ECMWF data assimilation system. Time series statistics and selected geographical maps are updated on a daily basis. The remaining statistical maps are updated weekly.
- Wind speed
- Surface pressure
- Surface wind speed
- Ground Based GPS
- SYNOP 2M Temperature
- SYNOP snow
This section shows monitoring statistics for observations used by ECMWF's ocean data assimilation system. Time series statistics and selected geographical maps are updated on a daily basis. The remaining statistical maps are updated weekly.
ECMWF runs an automatic data checking system. It triggers the production of alarm messages if an anomaly is detected in the quality or the availability of the data assimilated by the model.
Selected statistical parameters (number of observations, bias correction, and mean bias-corrected background, analysis departures and probability of gross error) are checked against an expected range. An appropriate alert message (including a time series plot) is generated if statistics are outside the specified ranges. A severity level (slight, considerable, severe) is assigned to each message depending on how far statistics are from the expected values. Two kinds of ranges are used by the automatic checking: Soft and Hard limits. Soft limits are updated automatically using statistics from the last twenty days (extremes are excluded during this process). Hard limits are adjusted manually when required.
Currently, the automatic checking is limited to data passing through the minimisation process (including VarBC passive data). It is being applied, twice a day, to the long cut-off 4D-VAR cycles.
The GUAN (GCOS Upper-Air Network) is part of the GCOS (Global Climate Observing System), a program co-sponsored by WMO, UNESCO, UNEP and ICSU 'to ensure that the observations and information needed to address climate-related issues are obtained and made available to all potential users'. ECMWF has agreed to provide GCOS with monthly monitoring statistics related to the availability and the quality of GUAN data as received from the GTS at ECMWF.
The statistics will be updated during the first half of each month.
The ECMWF global data monitoring report is a monthly publication intended to give an overview of the availability and quality of observations from the Global Observing System within the World Weather Watch of the World Meteorological Organization. It should be recognised that the statistics given in this report refer to data as received at ECMWF in time for the appropriate analysis. The annex of the report gives further explanations of the methods applied to compile the statistics and on the reference used to establish the quality of observations.