EUMETSAT Meteorological Satellite Conference 2021

In this session we invite contributions on the status and plans for current and upcoming meteorological satellite systems. Contributions on innovative missions and new satellite and constellation concepts responding to evolving user needs are particularly welcome. Those satellite and constellation concepts taking advantage of new technology of smaller satellites and/or seeking an optimal deployment of sensors are also welcome.

We invite contributions on early results from the Sentinel-6 Michael Freilich data, including both the altimetry and radio-occultation missions. In particular, we welcome abstracts in the following areas:

1. Calibration/Validation
2. Continuity and/or synergy with pre-cursor missions
3. Early assessment on the value of this mission for the different applications, covering ocean climate and dynamics, geodesy, operational oceanography, marine meteorology and numerical weather prediction.

We invite contributions on developments that advance nowcasting, very short-range NWP and blended methods in anticipation of new-generation meteorological satellite data from the MTG and EPS-SG programmes. User perspectives on the transition from MSG/EPS to MTG/EPS-SG are welcome in this session, such as from forecasters, trainers, and application developers. The session also features other developments supporting the weather forecasting value chain of the future, such as radiative transfer methods, product developments including from SAFs, and processing and visualisation tools. 

Global and regional Numerical Weather Prediction (NWP) are among the key applications for the use of satellite data. Current polar orbiting satellites, like EPS, and its future evolution, EPS-SG, are a fundamental data source for NWP. In this session, we welcome papers discussing:

• The use of satellite observations to improve numerical analyses that provide initial conditions for NWP models, including machine learning methods.
• Using satellite observations for improving NWP models.
• Novel assimilation techniques and future evolution of assimilation systems.
• Treatment of the observation and model uncertainties in the NWP models.
• Satellite data impact studies, impact assessments of different types of satellite observations.
• Overview of the issues and developments of satellite data assimilation.
• Proposed improvements in the handling of contaminations (e.g. cloud, aerosols) in satellite measurements.
• Assessment of gaps/additional needs in satellite data in support to NWP.
• NWP verification studies and impact-assessment methods.

In this session we welcome abstracts on the use of satellite based data for applications in agriculture, drought and hydrology. This includes but is not limited to the analysis of extreme events based on droughts and water scarcity indicators or case studies assessing the impact of climate change. The presentation can be on completed studies or ongoing studies, applications in use or under development as well as new ideas you may want to discuss, which make use of satellite based data provided by EUMETSAT, the SAFs or other providers. The focus of the presentations should be on the experiences made with the satellite data, such as the added value they bring to the project or the application. Discussions about challenges encountered as well as suggestions for improvements on the data, the way the data are provided or gaps in the satellite product portfolio are welcome.

We also welcome presentations from data providers on new and upcoming products for use in agriculture, hydrology and related fields.

This session will be dedicated to the use of operational satellite products for marine meteorology applications.

In particular, we welcome abstracts on the following topics:

• Gaps in observations, development of new satellite products.
• Data assimilation, numerical models including coupled atmosphere-ocean-ice models.
• Coastal challenges.
• Uncertainties and errors, use of Fiducial Reference Measurements.
• Synergistic approaches to improve forecast systems.

Changes of the climate system with adverse effects on our societies are pervasive and observed. Risks by the end-of-century (2081-2100) will be larger under high greenhouse gas emission scenarios, compared with low emission scenarios. Mitigation policies remain vital to contain global emissions and the magnitude of climate change in the long-term. Risks need to be managed through suitable local adaptation policies. The role of systematic observations and their usage attains increased importance for monitoring collective progress towards achieving the purpose of the Paris Agreement and its long-term goals. Within this context we invite contributions on:

• Evolving climate application needs for satellite data, including Climate Services.
• Usage of satellite data in the context of mitigation and adaptation, including greenhouse gas emission monitoring.
• Usage of satellite data in global and regional reanalysis, for better climate process understanding, in climate modelling, including quality evaluation and model improvements.
• Satellite climate data from improved data rescue, re-calibration, uncertainty quantification, retrieval science, etc.

Session 8 will focus on Air Quality (AQ) from space and the contribution of satellite data derived from operational and forthcoming sensors. 

Contributions are invited with findings from ongoing or completed projects, new ideas on

• AQ monitoring techniques exploiting observations from sensors hosted on different satellite platforms type (LEO/GEO) together with analysis of the achievable information content.
• Satellite data in AQ prediction models and their impact on the accuracy of these systems.
• Satellite-based observations needs and methods leading to improvements in current AQ monitoring and forecasting capabilities.
• Satellite data direct use / synergistic approach with data from other sources (models, in-situ) in downstream AQ service solutions or in tools for AQ Decision Support Systems.

In recent years, there has been increasing use of machine learning, and in particular so-called deep learning, in Earth system science. A plethora of machine learning methods are being tested to address problems of weather, air quality and climate prediction, such as the representation of unresolved processes in numerical models, the calibration of forecasts produced with numerical models and the production of forecasts based on data and machine learning methods only. Machine learning can be applied across the weather/climate value chain: for the generation of information (observations and their infrastructure, assimilation, modelling, forecasting), post-processing (the generation of products and suitable interfaces), and the dissemination of predictions to users and the perception and decision-making. Recent European initiatives, such as Destination Earth, will further enhance the development of machine learning applications.

Where do& you see the most promising applications of machine learning techniques to satellite data in the weather/climate value chain?

• Better observations: recover gaps or detect errors in satellite data; improve radiative transfer models; integrate calibration and validation, reconstruct long-term monitoring, use or fuse internet-of-things data...
• Integration: generate ensembles, improve data assimilation, reduce computational cost...
• Prediction: nowcasting, short term forecasting, uncertainty quantification...
• Products: identify convective system identification, detect forest fires, atmospheric rivers or tropical cyclones, bias correct products, provide uncertainty range...