Satellite skills and knowledge for operational meteorologist

Meteosat Third Generation (MTG) will see the launch of six new satellites from 2021. MTG-I will embark a VIS/IR imager and a lightning imager. The talk details the improvement of NWCSAF/GEO cloud products using new MTG-I capabilities. The new channels will help for the detection of thin cirrus and will improve the cloud phase identification. Cloud products will take advantage of the enhanced spatial resolution, particularly, for the separation between cumuliform and stratiform clouds. Finally, the use of lightning imager should be useful for convection identification.

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The NOAA Geostationary Operational Environmental Satellite (GOES-R) series provides the continuity for the existing GOES system currently operating over the Western Hemisphere. The Geostationary Lightning Mapper (GLM) represents an advancement over current GOES by providing an entirely new capability for total lightning detection (cloud and cloud-to-ground flashes). The GLM will map total lightning continuously day and night with near-uniform spatial resolution of 8 km with a product latency of less than 20 sec over the Americas and adjacent oceanic regions. The total lightning is very useful for identifying hazardous and severe thunderstorms, monitoring storm intensification and tracking evolution. Used in tandem with radar, visible and infrared satellite imagery, and surface observations, total lightning data has great potential to increase lead time for severe storm warnings, improve aviation safety and efficiency, and increase public safety.

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The amount of data from the world’s weather satellites is overwhelming. While each type of data is valuable, it’s almost impossible to use them all operationally. It’s like trying to drink from a fire hose; there’s simply too much data to absorb, and much of it ends up not being used.
“Red, Blue, Green” or RGB processing is a simple but powerful technique that consolidates different channels of satellite imagery into single products that are easy for forecasters to use. RGB processing used to be a visualization technique used mainly in research. But due to its popularity, it is increasingly available to operational forecasters. A pre-requisite for this, however, is the standardization of RGB products, i.e. the selection of the most useful RGB products for operational forecasting, generated at each Meteorological Service with the same identical standard method/recipe.
The combination of individual images into RGB colour composites is modernizing the interpretation of satellite imagery. While black and white imagery still has its uses, it often cannot match the effectiveness of RGB products. In fact, RGB images are often more useful than traditional colour image enhancements.
The Flexible Combined Imager (FCI) of MTG will open new possibilities of RGB products, with higher temporal and spatial resolution and better accuracy (less noise). Of particular interest will be the new NIR2.25 band that will improve cloud phase detection and detection of hot/large fires. Two new RGBs related to this channel will be presented. Furthermore, some standard RGBs will need to be tuned to account for the slight changes in central wavelength and band width. Some Himawari examples for this tuning will be given. Finally, the issue of local versions of RGB products will be addressed using the examples of “tropical” Night Microphysics and Airmass RGBs.

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This presentation summarises the adaptation of WMO / EUMETSAT endorsed RGB products to Himawari-8 data over the Australasian-Pacific region by WMO RAV and RAII stakeholders from the perspective of the Australian VLab Centre of Excellence. The content includes the tuning of the RGB products to the Himawari-8 data, the training conducted to permit effective use of the RGB products. Evidence is provided of the effective stakeholder use and development of the RGB products, including the development of new RGB products.

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The new-generation geostationary meteorological satellite of the Japan Meteorological Agency (JMA), Himawari-8, started operation in July 2015. Himawari-8 features a new imager, Advanced Himawari Imager (AHI), with 16 bands. The imager's spatial resolution and observation frequency is improved comparing with its predecessor satellites, MTSAT-series. This presentation will be an overview of Himawari-8/9. It will focus on the imaging capabilities and the data distributions.

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The next generation of geostationary satellite, GOES-R, is scheduled for launch in November, 2016. NOAA has been preparing for the data from its Advanced Baseline Imager and Geostationary Lightning Mapper for over 10 years, but recently JMA launched Himawari-8, a geostationary satellite with a similar imaging instrument. This presentation will show how Himawari-8 data has been used to prepare for similar data to begin flowing in early 2017. Meteosat Third Generation (MTG) will also carry a similar imager, so lessons learned from Himawari and GOES-R will be helpful for MTG data users.

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Jochen Grandell starts his presentation by introducing the Meteosat program from the beginning. Then he explains what the MTG mission is and what kind of instruments will be on-board the MTG satellites. He introduces the Flexible Combined Imager (FCI) and the Lightning Imager (LI). The differences between SEVIRI on-board MSG and FCI are discussed in more detail. The measurement technique of the LI is shown together with the role of this very new instrument.

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The GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm has been developed for enhanced characterization of the properties of both aerosol and land surface from diverse remote sensing observations. The overall concept of the algorithm is described by Dubovik et al. (2014), while the detailed are given in the paper is by Dubovik et al. (2011). The algorithm is based on highly advanced statistically optimized fitting implemented as Multi-Term Least Square minimization (Dubovik, 2004) and deduces nearly 50 unknowns for each observed site. The algorithm derives a set of aerosol parameters similar to that derived by AERONET including detailed particle size distribution, the spectral dependence on the complex index of refraction and the fraction of non-spherical particles. The algorithm uses detailed aerosol and surface models and fully accounts for all multiple interactions of scattered solar light with aerosol, gases and the underlying surface. All calculations are done on-line without using traditional look-up tables. In addition, the algorithm can use the new multi-pixel concept - a simultaneous fitting of a large group of pixels with additional constraints limiting the time variability of surface properties and spatial variability of aerosol properties. This principle provides a possibility to improve retrieval for multiple observations even if the observations are not exactly co-incident or co-located. Significant efforts have been spent for optimization and speedup of the GRASP computer routine and retrievals from satellite observations. For example, the routine has been adapted for running at GPGPUs accelerators. GRASP inherits many aspects used in AERONET retrieval. At first GRASP has been developed for POLDER/PARASOL multi-viewing imager and later adapted to a number of other satellite sensors such as METEOSAT/MERIS at polar-orbiting platform and COCI/GOMS geostationary observations. It can be equally applied to ground-based AERONET and lidar observations. The results of numerical tests and results of applications to real data will be presented.

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The monitoring of trace-gases, pollution and aerosols is important both for the quality of current and future weather forecast model output, as well as for the direct monitoring of aircraft safety, pollution levels, and other health related issues. Satellite instruments on-board EUMETSATs operational platforms, like on the Low-Earth Orbit (LEO) Metop platform, or the Geostationary Orbit (GEO) MSG platform, and their future successors EPS-SG and MTG, provide unique long-term monitoring capabilities of atmospheric composition addressing many of these issues. We will introduce the capabilities of instruments on these platform to retrieve trace-gases from ozone to nitrogen dioxide, CO and of greenhouse gases like methane, as well as their capability to retrieve aerosol optical and microphysical properties including volcanic ash. We will provide examples on how these products are used in current and future versions of numerical forecast models which include atmospheric chemistry processes, like in the model provided by the Copernicus Atmospheric Monitoring Service (CAMS).

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The aerosols have recently been incorporated into increasing number of global climate models. Aerosol models in global climate models are validated using variety of ground-based observations and satellite retrievals. Both data have their own advantages and disadvantages. For example, in-situ observations of particle size and composition give exact information on the aerosol distribution for small regions on the ground while satellite retrievals give a broader view on the global distribution of aerosols. In both cases the rather coarse spatial and temporal resolution of the global models increase the difficulty of using these data for their validation. I will demonstrate the limitations of the satellite retrievals and in-situ observations when comparing with models and demonstrate how, for example, collocation of the data can help to improve the match between models and observations.

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Droughts are one of the most severe natural hazards with regard to affected people, spatio-temporal extension and economic losses. At the same time, population growth is expected to put global agricultural production under increasing pressure. Thus, drought monitoring and forecasting systems would be essential for large parts of the globe, and satellites are a valuable data source to establish such monitoring systems.
The presentation will give examples on the relevant parameters measured by satellites, whereas the focus will be on soil moisture. Furthermore, the combination of satellite measurements and model forecasts will be described to point out the state-of-the-art possibilities in forecasting drought events. Examples from an existing system will be presented for the region of Eastern Africa.

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Measurements Of Pollution In The Troposphere (MOPITT) on the NASA Terra spacecraft has been measuring the global atmospheric abundance of carbon monoxide (CO) since March 2000. Carbon Monoxide is mainly produced by incomplete combustion from both natural fires and anthropogenic activities and is also a product of chemical reactions with other air pollutants. These pollution sources have a large effect on both local and downwind air quality, as well as climate change. We will show how satellite measurements of carbon monoxide are used to understand how pollution is emitted and transported globally, from large scale fires to urban sources.

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