There are many ways in which machine learning promises to provide insight into the Earth System, and this area of research is developing at a breathtaking pace. If unsupervised, supervised as well as reinforcement learning can hold this promise remains an open question, particularly for predictions. Machine learning could help extract information from numerous Earth System data, such as satellite observations, as well as improve model fidelity through novel parameterisations or speed-ups. This session invites submissions spanning modelling and observational approaches towards providing an overview of the state-of-the-art of the application of these novel methods.

As the societal impacts of hazardous weather and other environmental pressures grow, the need for integrated predictions which can represent the numerous feedbacks and linkages between physical and chemical atmospheric processes is greater than ever. This has led to development of a new generation of high resolution multi-scale coupled prediction tools to represent the two-way interactions between aerosols, chemical composition, meteorological processes such as radiation and cloud microphysics.
Contributions are invited on different aspects of integrated model and data assimilation development, evaluation and understanding. A number of application areas of new integrated modelling developments are expected to be considered, including:
i) improved numerical weather prediction and chemical weather forecasting with feedbacks between aerosols, chemistry and meteorology,
ii) two-way interactions between atmospheric composition and climate variability.
This session aims to share experience and best practice in integrated prediction, including:
a) strategy and framework for online integrated meteorology-chemistry modelling;
b) progress on design and development of seamless coupled prediction systems;
c) improved parameterisation of weather-composition feedbacks;
d) data assimilation developments;
e) evaluation, validation, and applications of integrated systems.
This Section is organised in cooperation with the Copernicus Atmosphere Monitoring Service (CAMS) and the WMO Global Atmosphere Watch (GAW) Programme.
This year session is dedicated to the Global Air Quality Forecasting and Information Systems (GAFIS) - a new initiative of WMO and several international organizations - to enable and provide science-based air quality forecasting and information services in a globally harmonized and standardized way tailored to the needs of society.

Comprehensive evaluations of Earth Systems Science Prediction (ESSP) systems (e.g., numerical weather prediction, hydrologic prediction, climate prediction and projection, etc.) are essential to understand sources of prediction errors and to improve earth system models. However, numerous roadblocks limit the extent and depth of ESSP system performance evaluations. Observational data used for evaluation are often not representative of the physical structures that are being predicted. Satellite and other large spatial and temporal observations datasets can help provide this information, but the community lacks tools to adequately integrate these large datasets to provide meaningful physical insights on the strengths and weaknesses of predicted fields. ESSP system evaluations also require large storage volumes to handle model simulations, large spatial datasets, and verification statistics which are difficult to maintain. Standardization, infrastructure, and communication in one scientific field is already a challenge. Bridging different communities to allow knowledge transfers, is even harder. The development of innovative methods in open frameworks and platforms is needed to enable meaningful and informative model evaluations and comparisons for many large Earth science applications from weather to climate.

The purpose of this Open Science 2.0 session is to bring experts together to discuss innovative methods for integrating, managing, evaluating, and disseminating information about the quality of ESSP fields in meaningful way. Presentations of these innovative methods applied to Earth science applications is encouraged. The session should generate some interest in communities and research projects building and maintaining these systems (e.g. ESMVal, Copernicus, Climaf, Freva, Birdhouse, MDTF, UV-CDAT, CMEC - PCMDI Metrics Package, Doppyo, MET-TOOLS, CDO, NCO, etc.). The session allows room for the exchange of ideas. An outcome of this session is to connect the scientists, develop a list of tools and techniques that could be developed and provided to the community in the future.

Statistical post-processing techniques for weather, climate, and hydrological forecasts are powerful approaches to compensate for effects of errors in model structure or initial conditions, and to calibrate inaccurately dispersed ensembles. These techniques are now an integral part of many forecasting suites and are used in many end-user applications such as wind energy production or flood warning systems. Many of these techniques are flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias correction up to very sophisticated distribution-adjusting techniques that take into account correlations among the prognostic variables.

At the same time, a lot of efforts are put in combining multiple forecasting sources in order to get reliable and seamless forecasts on time ranges from minutes to weeks. Such blending techniques are currently developed in many meteorological centers.

In this session, we invite papers dealing with both theoretical developments in statistical post-processing and evaluation of their performances in different practical applications oriented toward environmental predictions, papers dealing with the problem of combining or blending different types of forecasts in order to improve reliability from very short to long time scales.

Lagrangian trajectories are currently used for vast range of purposes in ocean and atmosphere science. Examples include studying the connectivity of ocean basins, forecasting the spreading of ash clouds, mapping global ocean diffusivities, observing the deep ocean, or tracing plastics and other forms of pollutants in the ocean, etc. There is thus a need for numerical models capable of simulating Lagrangian particles in the ocean and atmosphere as well as accurate methods for analysing the data from surface drifters, floats, and simulated particles.

This session aims at bringing together scientists working on all sorts of Lagrangian methods, e.g. observed or simulated particles in the atmosphere and ocean, and a variety of use cases e.g. studying oceanic mixing/diffusivity, tracing pollution in the atmosphere or ocean, iceberg tracking etc. We welcome presentations on e.g.:

- Connectivity and pathways of air- or water-masses in the atmosphere and ocean
- Development of Lagrangian particle-tracking algorithms and algorithms to model particles with active behaviours, e.g. icebergs, fish, ash clouds, plastics etc.
- Methods and new tools to analyse observed or simulated Lagrangian particles, e.g. diffusivity, spreading rates, etc.
- New instrumentations and developments of balloons, surface drifters and floats.

Representation of cloud microphysics is the key ingredient of cloud simulation. From early days of cloud modeling, numerical models have relied on Eulerian continuous medium approach for all cloud thermodynamic variables, not only for the temperature and water vapor, but also for cloud condensate and precipitation. However, recent studies identified significant problems with the Eulerian approach and suggested that a Lagrangian particle-based probabilistic approach provides a valuable alternative. This session will solicit contributions describing recent progress in applications of particle-based methods in representing cloud microphysical processes in small-scale and cloud-scale simulation, such as DNS and LES, and exploring their potential in simulation of more complex cloud systems such as deep convection and frontal clouds.

Measurements of gaseous compounds and particles in the atmosphere play a critical role in our understanding of air quality, human and ecosystem health and the mechanisms governing the Earth's climate. Monitoring long term spatial and temporal changes in amount fractions of regulated air pollutants, greenhouse gases, precursors to secondary pollutants (e.g. ozone and particulate matter) and particle number and size distributions are essential to establish the scientific links and feedbacks between atmospheric composition, air quality and climate and to ensure legislative compliance. Ambient amount fractions and stable isotope ratios of many trace gases as well as particle number concentrations and size distributions are routinely observed within networks of monitoring sites and on mobile measurement platforms around the globe. Ensuring the quality and comparability of all these datasets is critical to improve reliability and reduce uncertainty in our understanding of the Earths system. This session invites contributions that seek to address the fundamental metrology needed to underpin long term ambient monitoring of trace gases and particles ensuring coherent and comparable measurements.

Instrumentation and its development play a key role in advancing research, providing state-of-the-art tools to address scientific "open questions" and to enable novel fields of research leading to new discoveries.
Over the last several decades, atmospheric environmental monitoring has benefited from the development of novel spectroscopic measurement techniques owing to the significant breakthroughs in photonic technology from the UV to THz spectral regions. These advances open new research avenues for observation of spatial and long-term trends in key atmospheric precursors, thus improving our understanding of tropospheric chemical processes and trends that affect regional air quality and global climate change. Extensive development of spectroscopic instruments for sensing the atmosphere continues toward improving performance and functionality, and reducing size and cost.
This focus session entitled "Advanced Spectroscopic Measurement Techniques for Atmospheric Science" addresses the latest developments and advances in a broad range of spectroscopic instrumentation and photonic/optoelectronic devices and technologies, and their integration for a variety of atmospheric applications. The objective is to provide a platform for sharing information on state-of-the-art and emerging developments in photonic instrumentation for atmospheric sensing. This interdis¬ciplinary forum aims to foster discussion among experimentalists, atmospheric scientists, and development engineers. It is also an opportunity for R&D and analytical equipment companies to evaluate the capabilities of new instrumentation and techniques.
Topics for presentation include novel spectroscopic methods and instruments for measuring atmospheric aerosols, isotopologues, trace gases and radicals. In situ and remote observations, vertical concentration profiles, and flux measurements are all welcome. Spectroscopic methods could include high performance absorption spectroscopy (such as broadband and laser-based cavity-enhanced spectroscopies and multipass systems), fluorescence techniques, heterodyne radiometry, and aerosol spectroscopy. Applications to field observations, airborne platforms (UAV, balloon, aircraft), geological exploration, and smog chamber studies are welcome. Creative approaches using new photonic technologies, methodologies, and data analysis tools are particularly encouraged.

Over the last years, a growing number of Multi-AXis (MAX) and other scattered light DOAS instruments is operated world wide.
By probing the troposphere in different viewing angles and from different platforms, vertical profile information on aerosols and tropospheric trace gases, in particular NO2, can be derived.
Thereby, scattered light DOAS instruments provide an essential link between in-situ measurements of trace gas concentrations and column-integrated measurements from satellite, and thus play a key role in satellite validation.
This session is open for contributions about
- MAX-DOAS and other scattered light DOAS instrumentation and operation on various platforms (ground-based, mobile, aircraft)
- trace gas retrievals
- inversion algorithms
- identification and treatment of clouds
- comparisons to in-situ or satellite measurements and models
- scientific results.
Results from intercomparison campaigns like CINDI-2 (2016 in Cabauw) are particularly welcome.

Public information:
No virtual EGU MAX-DOAS session

Dear participants of the EGU MAX-DOAS session,
it was suggested by EGU to run all sessions as purely text-based chats.
For the MAX-DOAS session we do not follow this suggestion because:
-the structure of this format is not very clear
-the effort will be rather high, but the benefit probably not very high
-many of the contributions will be given in a much more clear way at the
DOAS workshop.
We are very sorry that we will not meet each other at the EGU conference in Vienna this year. Nevertheless, we want to thank you very much or your contributions and hope to have a regular EGU meeting again next year.
Best regards,
Steffen Beirle, Michel van Roozendael, Folkard Wittrock, Thomas Wagner

Remote sensing of clouds and aerosols is of central importance for studying climate system processes and changes. Reliable information is required on climate-relevant parameters such as aerosol and cloud optical thickness, layer height, particle size, liquid or ice water path and vertical particulate matter columns. A number of challenges and unsolved problems remain in algorithms and their application. This includes remote sensing of clouds and aerosols with respect to 3D effects, remote sensing of polluted and mixed clouds, combination of ground-based and satellite-based systems, and the creation of long-term uniform global records. This session is aimed at the discussion of current developments, challenges and opportunities in aerosol and cloud remote sensing using active and passive remote sensing systems.

Space-based measurements of the Earth System, including its atmosphere, oceans, land surface, cryosphere, biosphere, and interior, require extensive prelaunch and post launch calibration and validation activities to ensure scientific accuracy and fitness for purpose throughout the 
lifetime of satellite missions. This requirement stems from the need to demonstrate unambiguously that the space-based measurements, typically based on engineering measurements by the detectors (e.g. photons), are sensitive to and match up with the geophysical and/or biogeochemical quantity of interest at a broad range of measurement locations on Earth. Most geophysical parameters vary in time and space, and the retrieval algorithms used must be accurate under the full range of conditions. Calibration and validation need to be carried out over the lifetime of missions in order to assure that any long-term variation in observation can be definitely be tied to the evolution of the Earth system. Such activities are also critical in ensuring that measurements can be inter-compared and used seamlessly to create long-term multi-instrument//multi-platform data sets, , which enable large-scale international science investigations into topics with high societal or environmental importance such as determining the ice mass balance of Greenland, monitoring the evolution of sea ice and snow cover in the Arctic and improving our knowledge of the terrestrial carbon cycle through multi-sensor forest biomass mapping. . This session seeks presentations on the use of surface-based, airborne, and/or space-based observations to prepare and calibrate/validate space-based satellite missions measuring our Earth system. A particular but not exclusive focus will be on activities carried out jointly by NASA and ESA as part of their Joint Program Planning Group Subgroup on calibration and validation and field activities.

A remote sensing signal acquired by a sensor system results from electromagnetic radiation (EM) interactions from incoming or emitted EM with atmospheric constituents, vegetation structures and pigments, soil surfaces or water bodies. Vegetation, soil and water bodies are functional interfaces between terrestrial ecosystems and the atmosphere. The physical types of EM used in RS has increased during the years of remote sensing development. Originally, the main focus was on optical remote sensing. Now, thermal, microwave, polarimetric, angular and quite recently also fluorescence have been added to the EM regions under study.
This has led to the definition of an increasing number of bio-geophysical variables in RS. Products include canopy structural variables (e.g. biomass, leaf area index, fAPAR, leaf area density) as well as ecosystem mass flux exchanges dominated by carbon and water exchange. Many other variables are considered as well, like chlorophyll fluorescence, soil moisture content and evapotranspiration. New modelling approaches including models with fully coupled atmosphere, vegetation and soil matrices led to improved interpretations of the spectral and spatio-temporal variability of RS signals including those of atmospheric aerosols and water vapour.
This session solicits for papers presenting methodologies and results leading to the assimilation in biogeoscience and atmospheric models of cited RS variables as well as data measured in situ for RS validation purposes. Contributions should preferably focus on topics related to climate change, food production (and hence food security), nature preservation and hence biodiversity, epidemiology, and atmospheric chemistry and pollution (stratospheric and troposphere ozone, nitrogen oxides, VOC’s, etc). It goes without saying that we also welcome papers focusing on the assimilation of remote sensing and in situ measurements in bio-geophysical and atmospheric models, as well as the RS extraction techniques themselves.
This session aims to bring together scientists developing remote sensing techniques, products and models leading to strategies with a higher (bio-geophysical) impact on the stability and sustainability of the Earth’s ecosystems.

Public information:
BG2.7
Remote Sensing applications in the Biogeosciences

Chairperson: Frank Veroustraete & Willem Verstraeten
10:45
Welcome
1
D530 | EGU2020-5174
10:50
Potential of LiDAR for species richness prediction at Mount Kilimanjaro
Alice Ziegler and the Research Group at the Kilimanjaro
2
D512 | EGU2020-288
10:57
Understanding wetland dynamics using geostatistics of multi-temporal Earth Observation datasets
Manudeo Narayan Singh and Rajiv Sinha
3
D515 | EGU2020-5421
11:04
Twelve years of SIFTER Sun-Induced Fluorescence retrievals from GOME-2 as an independent constraint on photosynthesis across continents and biomes
Maurits L. Kooreman, K. Folkert Boersma, Erik van Schaik, Anteneh G. Mengistu, Olaf N. E. Tuinder, Piet Stammes, Gerbrand Koren, and Wouter Peters
4
D516 | EGU2020-6674
11:11
Evaluation of understory LAI estimation methodologies over forest ecosystem ICOS sites across Europe
Jan-Peter George Jan Pisek and the Tobias Biermann (2), Arnaud Carrara (3), Edoardo Cremonese (4), Matthias Cuntz (5), Silvano Fares (6), Giacomo Gerosa (7), Thomas Grünwald (8) et al.
5
D517 | EGU2020-8263
11:18
Probing the relationship between formaldehyde column concentrations and soil moisture using mixed models and attribution analysis
Susanna Strada, Josep Penuelas, Marcos Fernández Martinez, Iolanda Filella, Ana Maria Yanez-Serrano, Andrea Pozzer, Maite Bauwens, Trissevgeni Stavrakou, and Filippo Giorgi
6
D518 | EGU2020-9071
11:25
Validation of seasonal time series of remote sensing derived LAI for hydrological modelling
Charlotte Wirion, Boud Verbeiren, and Sindy Sterckx
7
D519 | EGU2020-12000
11:32
Potassium estimation of cotton leaves based on hyperspectral reflectance
Adunias dos Santos Teixeira, Marcio Regys Rabelo Oliveira, Luis Clenio Jario Moreira, Francisca Ligia de Castro Machado, Fernando Bezerra Lopes, and Isabel Cristina da Silva Araújo
8
D528 | EGU2020-4418
11:39
Comparison of the Photochemical Reflectance Index and Solar-induced Fluorescence for Estimating Gross Primary Productivity
Qian Zhang and Jinghua Chen
9
D529 | EGU2020-4582
11:46
Weed-crop competition and the effect on spectral reflectance and physiological processes as demonstrated in maize
Inbal Ronay, Shimrit Maman, Jhonathan E. Ephrath, Hanan Eizenberg, and Dan G. Blumberg
10
D531 | EGU2020-6059
11:53
Remote sensing-aid assessment of wetlands in central Malawi
Emmanuel Ogunyomi, Byongjun Hwang, and Adrian Wood
12:00
Open discussion
12:30
End morning session

Chat time: Wednesday, 6 May 2020, 14:00–15:45
Chairperson: Willem Verstraeten Frank Veroustraete
14:00
Welcome back!
1
D534 | EGU2020-10014
14:05
On the surface apparent reflectance exploitation: Entangled Solar Induced Fluorescence emission and aerosol scattering effects at oxygen absorption regions
Neus Sabater, Pekka Kolmonen, Luis Alonso, Jorge Vicent, José Moreno, and Antti Arola
2
D536 | EGU2020-15832
14:12
Evaluating the impact of different spaceborne land cover distributions on isoprene emissions and their trends using the MEGAN model.
Beata Opacka, Jean-François Müller, Jenny Stavrakou, Maite Bauwens, and Alex B. Guenther
3
D537 | EGU2020-10633
14:19
Application of Copernicus Global Land Service vegetation parameters and ESA soil moisture data to analyze changes in vegetation with respect to the CORINE database
Hajnalka Breuer and Amanda Imola Szabó
4
D538 | EGU2020-13332
14:26
How valuable are citizen science data for a space-borne crop growth monitoring? – The reliability of self-appraisals
Sina C. Truckenbrodt, Friederike Klan, Erik Borg, Klaus-Dieter Missling, and Christiane C. Schmullius
5
D539 | EGU2020-18493
14:33
Learning main drivers of crop dynamics and production in Europe
Anna Mateo Sanchis, Maria Piles, Julia Amorós López, Jordi Muñoz Marí, and Gustau Camps Valls
6
D540 | EGU2020-19003
14:40
Modelling understory light availability in a heterogeneous landscape using drone-derived structural parameters and a 3D radiative transfer model
Dominic Fawcett, Jonathan Bennie, and Karen Anderson
7
D543 | EGU2020-5151
14:47
Global assimilation of ocean-color data of phytoplankton functional types: Impact of different datasets
Lars Nerger, Himansu Pradhan, Christoph Völker, Svetlana Losa, and Astrid Bracher
8
D544 | EGU2020-5251
14:53
PROSPECT-PRO: a leaf radiative transfer model for estimation of leaf protein content and carbon-based constituents
Jean-Baptiste Féret, Katja Berger, Florian de Boissieu, and Zbyněk Malenovský
9
D547 | EGU2020-13447
15:00
Inverting a comprehensive crop model in parsimonious data context using Sentinel 2 images and yield map to infer soil water storage capacity.
André Chanzy and Karen Lammoglia
10
D550 | EGU2020-18798
15:07
Study on The Extraction Method and Spatial-temporal Characteristics of Irrigated Land in Zhangjiakou City
Zijuan Zhu, Lijun Zuo, Zengxiang Zhang, Xiaoli Zhao, Feifei Sun, and TianShi Pan
11
D551 | EGU2020-19953
15:14
Remote sensing and GIS based ecological modelling of potential red deer habitats in the test site region DEMMIN (TERENO)
Amelie McKenna, Alfred Schultz, Erik Borg, Matthias Neumann, and Jan-Peter Mund
15:21
Open discussion
15:45
End afternoon session

This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and detailed modeling efforts across various fields of geosciences. Topics of this session will include the identification and handling of specific problems arising from the need to analyze such large-scale data sets, together with methodological approaches towards semi or fully automated inference of relevant patterns in time and space aided by computer science-inspired techniques. Among others, this session shall address approaches from the following fields:
• Dimensionality and complexity of big data sets
• Data mining in Earth sciences
• Machine learning, deep learning and Artificial Intelligence applications in geosciences
• Visualization and visual analytics of big and high-dimensional data
• Informatics and data science
• Emerging big data paradigms, such as datacubes

Geodesy contributes to Atmospheric Science by providing some of the Essential Climate Variables of the Global Climate Observing System. Water vapor is under-sampled in the current meteorological and climate observing systems. Obtaining and exploiting more high-quality humidity observations is essential to weather forecasting and climate monitoring. The production, exploitation and evaluation of operational GNSS-Meteorology for weather forecasting is well established in Europe due to 20+ years of cooperation between the geodetic community and the national met services. Advancements in NWP models to improve forecasting of extreme precipitation require GNSS troposphere products with a higher resolution in space and shorter delivery times than are currently in use. Homogeneously reprocessed GNSS data have high potential for monitoring water vapor climatic trends and variability. With shortening orbit repeat periods, SAR measurements are a new source of information to improve NWP models. Using NWP data within real-time processing of GNSS observations can initialize PPP algorithms, shortening convergence times and improving positioning. GNSS signals can be used for L-band remote sensing when Earth-surface reflected signals are considered. GNSS-reflectometry contributes to environmental monitoring with estimates of soil moisture, snow depth, ocean wind speed, sea ice concentration and has the potential to be used to retrieve near-surface water vapor.
We welcome, but not limit, contributions on:
•Estimates of the neutral atmosphere using ground-based and space-based geodetic data, use of those estimates in weather forecasting and climate monitoring
•Multi-GNSS and multi-instruments approaches to retrieve and inter-compare tropospheric parameters
•Real-Time and reprocessed tropospheric products for now-casting, forecasting and climate
•Assimilation of GNSS tropospheric products in NWP and in climate reanalysis
•Production of SAR-based tropospheric parameters and use of them in NWP
•Methods for homogenization of long-term GNSS tropospheric products
•Studies of the delay properties of the GNSS signals for propagation experiments
•Usage of NWP data in GNSS data processing
•Techniques on retrieval of soil moisture from GNSS observations and of ground-atmosphere boundary interactions
•Estimates and methods using GNSS reflectometry for the detection and characterization of sea ice
•Usage of satellite gravity observations for studying the atmospheric water cycle.

This session invites innovative Earth system and climate studies based on geodetic measuring techniques. Modern geodetic observing systems document a wide range of changes in the Earth’s solid and fluid layers at very diverging spatial and temporal scales related to processes as, e.g., glacial isostatic adjustment, the terrestrial water cycle, ocean dynamics and ice-mass balance. Different time spans of observations need to be cross-compared and combined to resolve a wide spectrum of climate-related signals. Geodetic observables are also often compared with geophysical models, which helps to explain observations, evaluate simulations, and finally merge measurements and numerical models via data assimilation.
We appreciate contributions utilizing geodetic data from diverse geodetic satellites including altimetry, gravimetry (CHAMP, GRACE, GOCE and GRACE-FO), navigation satellite systems (GNSS and DORIS) or remote sensing techniques that are based on both passive (i.e., optical and hyperspectral) and active (i.e., SAR) instruments. We welcome studies that cover a wide variety of applications of geodetic measurements and their combination to observe and model Earth system signals in hydrological, ocean, atmospheric, climate and cryospheric sciences. Any new approaches helping to separate and interpret the variety of geophysical signals are equally appreciated. Contributions working towards the newly established Inter-Commission Committee on "Geodesy for Climate Research" (ICCC) of the International Association of Geodesy (IAG) would be particularly interesting for this session.
With author consent, highlights from this session will be tweeted with a dedicated hashtag during the conference in order to increase the impact of the session.

The hydrological response to precipitation at the catchment scale is the result of the interplay between the space-time variability of precipitation, the catchment geomorphological / pedological / ecological characteristics and antecedent hydrological conditions. Therefore, (1) accurate measurement and prediction of the spatial and temporal distribution of precipitation over a catchment and (2) the efficient and appropriate description of the catchment properties are important issues in hydrology. This session focuses on the following aspects of the space-time variability of precipitation:
- Novel techniques for measuring liquid and solid precipitation at hydrologically relevant space and time scales, from in situ measurements to remote sensing techniques, and from ground-based devices to spaceborne platforms.
- Novel approaches to better identify, understand and simulate the dominant microphysical processes at work in liquid and solid precipitation.
- Applications of measured and/or modelled precipitation fields in catchment hydrological models for the purpose of process understanding or predicting hydrological response.

Accurate information on emissions related to air quality and climate change is becoming increasingly important for both policy makers and the atmospheric composition research community. Knowledge on the magnitude, type of activity, time evolution and spatial distribution of the emissions is needed for assessing the impact of air quality regulations and climate policies, and as input in atmospheric models. Inversion methods have been widely used in the recent years, in combination with multiple sources of observations, to constrain the emissions of major pollutants. In particular, satellite observations play an increasingly important role in the validation and update of emission inventories.
We welcome contributions related to (1) advances in emission derivation, including new inverse methodologies , (2) the use of novel observations for improved top-down estimates and (3) analysis of cross-species/multi-platform measurements. Special attention will be given to the use of observations from the latest generation of satellite sensors e.g. TROPOMI on Sentinel 5P and CrIS on SUOMI NPP. Analysis and evaluation of the emissions and their trends, and development of scientific applications for use by policy makers in order to assess emission abatement measures are also welcome. This session directly links to the IGAC AMIGO activity.

Public information:
Cancelled.

Large-scale atmospheric circulation dynamics are the major driver of near surface climatic and environmental variability. Synoptic climatology examines atmospheric circulation dynamics and their relationship with near surface environmental variables. Within synoptic climatological analyses, a wide variety of methods is utilized to characterize atmospheric circulation (e.g., circulation and weather type classification, regime analysis, teleconnection indices). Various linear and non-linear approaches (e.g., multiple regression, canonical correlation, neural networks) are applied to relate the circulation dynamics to diverse climatic and environmental elements (e.g., air temperature, air pollution, floods).

The session welcomes contributions from the whole field of synoptic climatology. This includes application studies for varying regions, time periods (past, present, future) and target variables and in particular contributions on the development and the comparison of methods (e.g., varying circulation type classifications) and conceptual approaches (e.g., circulation types versus circulation regimes).