Meteorological applications will greatly benefit from the upcoming Meteosat Third Generation Imaging Service.
Nowcasting applications are in the focus of the imaging services, be it through the visual identification and characterisation of the weather systems, assessment via more advance quantitative products or a short-term prediction using probabilistic products that rely on data from MTG imagers.
Applications benefiting from the Spectral imagery mission, achieved through the Flexible Combined Imager (FCI) instrument:
- Improved meteorological information about the rapid processes of the atmospheric water cycle, resulting in improved severe weather forecasts & early warnings.
- Daytime total column precipitable water retrieval enhanced with support of 0.91 µm channel, especially over land.
- Improved detection of very thin cirrus clouds assisted with 1.375 µm channel.
- Improved retrieval of cloud microphysics with additional 2.26 µm 'microphysical’ channel.
- True colour imagery available for first time, supported by new 0.44 µm & 0.51 µm channels.
- Improved aerosol retrievals, especially over land — important for volcanic ash & air quality monitoring.
- Improved fire detection via extended dynamical range of the 3.8 µm channel.
- Increase in the quality of climate relevant products, through higher spatial resolution.
Figures 2–10 are comparisons between current imagery from SEVIRI on MSG, the MODIS instruments on board NASA's Terra and Aqua satellites and the VIIRS instrument on Suomi-NPP. Imagery from MTG will have comparable resolution to that from the MODIS instruments.
Figure 10: Comparison of full-disc and rapid scanning between current SEVIRI (left) and future FCI (right)
Applications benefiting from the Lightning imagery mission, achieved through the Lightning Imager (LI) instrument:
- Improvements for nowcasting and very short range forecasting of severe weather through information on total lightning (Intra Cloud (IC) lightning and Cloud to Ground (CG) lightning). Note: with optical pulse detection, it is not possible to distinguish between cloud-to-ground and cloud-to-cloud lightning.
- Continuous and simultaneous observations of total lightning in geostationary field of view, with an extremely high timeliness (goal of reaching 30 seconds)
- Detection, monitoring, tracking and extrapolate of the development of active convective areas and storm life cycles.
- By providing data on the total lightning, the LI instrument will help improve the quality of information essential for air traffic routing and safety.
Figure 12: Simulated lightning event for 24 hours on 16 June 2013
The information delivered to the users will be the time, position and intensity of detected optical pulses converted into geophysical flashes (point data).
Additionally, users will be provided with accumulated flashes over a period of 30 seconds (gridded data on the same grid as FCI instrument data, derived from accumulated point data), which can be further stacked for longer integration periods depending on the users’ application.
Continuous and simultaneous observations of total lightning with almost full-disc coverage, delivered to the users with very high timeliness provides (together with the associated FCI data) a valuable tool for assessment and nowcasting of severe weather from pure satellite data, over almost the full satellite field of view. An example of such an integrated view is provided from the GOES-16 pre-operational data (Figure 7).
LI and climate
For climate purposes the LI will:
- Help in assessing the impact of climate change on thunderstorm activity.
- Aid the study and monitoring of the physical and chemical processes in the atmosphere regarding nitrogen oxide (NOx), which plays a key role in the ozone conversion process and acid rain generation.
- Provide information on a global scale with known error-characteristics. This information is needed in regional models to improve very short-range forecasts of convective events and verification/validation of algorithms to nowcast convective initiation (time and location).
An example of statistics derived from similar climate dataset from LIS and OTD instruments is shown in Figure 14.