ESSI4.4 | Modern Earth system science visualization and exploration techniques - the balancing act between complex information, broad functionality and simple illustration
Modern Earth system science visualization and exploration techniques - the balancing act between complex information, broad functionality and simple illustration
Co-organized by AS5/OS5
Convener: Tobias Kerzenmacher | Co-conveners: Berit Arheimer, Philipp S. Sommer, Christof Lorenz, Isabel Campos Plasencia
| Tue, 16 Apr, 10:45–12:30 (CEST)
Room 0.51
Posters on site
| Attendance Tue, 16 Apr, 16:15–18:00 (CEST) | Display Tue, 16 Apr, 14:00–18:00
Hall X3
Orals |
Tue, 10:45
Tue, 16:15
The visualization and user-friendly exploration of information from scientific data is one of the main tasks of good scientific practice. But steady increases in temporal and spatial resolutions of modeling and remote sensing approaches lead to ever-increasing data complexity and volumes. On the other hand, earth system science data are getting increasingly important as decision support for stakeholders and other end users far beyond the scientific domains.

This poses major challenges for the entire process chain, from data storage to web-based visualization. For example, (1) the data has to be enriched with metadata and made available via appropriate and efficient services; (2) visualization and exploration tools must then access the often decentralized tools via interfaces that are as standardized as possible; (3) the presentation of the essential information must be coordinated in co-design with the potential end users. This challenge is reflected by the active development of tools, interfaces and libraries for modern earth system science data visualization and exploration.

In this session, we hence aim to establish a transdisciplinary community of scientists, software-developers and other experts in the field of data visualization in order to give a state-of-the-art overview of tools, interfaces and best-practices. In particular, we look for contributions in the following fields:

- Developments of open-source visualization and exploration techniques for earth system science data
- Co-designed visualization solutions enabling transdisciplinary research and decision support for non-scientific stakeholders and end-users
- Tools and best-practices for visualizing complex, high-dimensional and high frequency data
- Services and interfaces for the distribution and presentation of metadata enriched earth system science data
- Data visualization and exploration solutions for decentralized research data infrastructures

All contributions should emphasize the usage of community-driven interfaces and open-source solutions and finally contribute to the FAIRification of products from earth system sciences.

Session assets

Orals: Tue, 16 Apr | Room 0.51

Chairpersons: Tobias Kerzenmacher, Christof Lorenz, Berit Arheimer
On-site presentation
Valerio Vinciarelli, Rossana Paciello, Daniele Bailo, Claudio Goffi, Daniel Warren, Janusz Lavrnja-Czapski, Christopher Card, Philip Atkinson, Wayne Shelley, Jean-Baptiste Roquencourt, Yann Retout, Helen Glaves, Kety Giuliacci, Jan Michalek, Jakob Molander, Harald Nedrebø, Otto Lange, Carmela Freda, Kauzar Saleh-Contell, and Manuela Sbarra

The European Plate Observing System (EPOS), established as a European Research Infrastructure Consortium (ERIC) in 2018, stands as a significant milestone in pan-European research infrastructures, focusing on solid Earth science. The EPOS Data Portal, officially launched in April 2023, is the place where FAIR principles and practices are implemented thanks to the adoption of a co-development approach and  harmonization of actions across communities of scientists, developers, data providers, and users. The EPOS Data Portal currently provides access to data and products from 10 different disciplines: Seismology, Near-Fault Observatories, GNSS Data and Products, Volcano Observations, Satellite Data, Geomagnetic Observations, Anthropogenic Hazards, Geological Information and Modeling, Multi-Scale Laboratories, and Tsunami.

The EPOS Data Portal is based on a user-friendly user interface which provides intuitive visualization methods and interaction modes that significantly simplifies and facilitates the discovery and the access to the geoscientific community assets. Through the portal, users can: i) Perform data searches by combining a set of criteria; ii) Navigate and visualize the retrieved search results in different ways; iii) Fine-tune results using facets and advanced filters; iv) Download selected results or store them in a favorites list.

The underlying system of the Data Portal has been crafted using a blend of open-source technologies, including Java, RabbitMQ, Python, and others. We implemented a modular architecture based on the microservices paradigm, facilitating seamless integration of new data and services through dedicated software interfaces. The source code, collaboratively developed by scientists and IT experts, is now available under a GPL license ( along with a comprehensive developer’s guide.


In this contribution, we demonstrate the potential impact of our open-source solution in advancing visualizations, interfaces, and best practices within the context of multidisciplinary research. Furthermore, we present how other research infrastructures, projects and initiatives can benefit from the shared knowledge and expertise, accelerating the development of robust and advanced Earth science data portals.

How to cite: Vinciarelli, V., Paciello, R., Bailo, D., Goffi, C., Warren, D., Lavrnja-Czapski, J., Card, C., Atkinson, P., Shelley, W., Roquencourt, J.-B., Retout, Y., Glaves, H., Giuliacci, K., Michalek, J., Molander, J., Nedrebø, H., Lange, O., Freda, C., Saleh-Contell, K., and Sbarra, M.: Advancing Open Data Portals: Learnings from the EPOS Open-Source Solution, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7931,, 2024.

Virtual presentation
Otmar Olsina, Jennifer Hewson, Diane Davies, Asen Radov, Brad Quayle, Louis Giglio, and Joanne Hall

NASA’s Fire Information for Resource Management System (FIRMS) enables users to find and analyze a range of earth system science data and information relevant to the complex and evolving field of wildfire management, impacts, and mitigation. FIRMS facilitates the use of earth system science data to inform science-based decision making through a standardized, readily interpretable interface that supports operational users, researchers, and non-scientific stakeholders. This community-driven interface enables user-friendly exploration of data that are increasingly findable, accessible, interoperable, and reproducible (FAIR), and the interface is regularly refined to support the diversity, equity, and inclusion of potential end-users. FIRMS offers fire-based maps through Web Map Service (WMS) and Web Feature Service (WFS), and makes available multiple APIs to support area, country, fire footprint features for stakeholders needing to ingest data into software such as QGIS, ArcGIS, etc. FIRMS developers are also creating a Fire Data Academy to build capacity around the use of Jupyter notebooks, Google Colab, and Python to perform data ingest, manipulation, and visualization. As the impacts of wildfires expand, affecting increasing swaths of population and biodiversity through immediate infrastructure and habitat destruction, and causing longer-term air quality impacts, a transdisciplinary approach to research and response is required. FIRMS supports a transdisciplinary approach through the range of data and information available, ensuring that all users, including those in historically underrepresented communities, can access wildfire data.

How to cite: Olsina, O., Hewson, J., Davies, D., Radov, A., Quayle, B., Giglio, L., and Hall, J.: NASA's FIRMS: Enabling the Use of Earth System Science Data for Wildfire Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16475,, 2024.

On-site presentation
Cristina Carnerero, Jan Mateu Armengol, Alvaro Criado, Antonia Frangeskou, Diana Urquiza, Dragana Bojovic, and Albert Soret

According to the World Health Organization, air pollution is the main environmental threat to public health. Urban environments are particularly critical due to their high-density population centers with often poor air quality. To characterize the exposure of citizens, the use of numerical models corrected with observational data has become a fundamental tool. Despite recent efforts, bias-corrected air quality models at the street scale exhibit significant uncertainty, partly due to the limited number of traffic and air quality observations.

Model uncertainty can critically increase far from measurement points and in regions with characteristics different from those used for calibration. In such locations, modeled data should be interpreted with caution. When the street-scale air quality models are intended to inform policy makers, estimating uncertainty is highly valuable to support decision-making protocols. A simpler air quality model with an estimation of the spatial uncertainty distribution may be preferred over a very sophisticated model that does not give any notion of uncertainty.

Within this context, we aimed at co-designing and co-developing an interactive tool to report the uncertainty of urban air quality simulations, disseminating the results tailored to the users’ needs.

The methodology consists of a geostatistical post-processing of the raw simulations of NO2 concentrations of the CALIOPE-urban air quality model in the city of Barcelona. The methodology is replicable to other cities and pollutants. The uncertainty estimation is based on the error variance of the Universal Kriging technique, which can be subsequently used to produce hourly maps of the probability of exceeding a certain threshold. Additionally, relevant social-ecological-technological variables were identified to explore the interconnections among different types of data, as well as broadening the social impact of this project. For instance, locations associated with vulnerable citizens (e.g., schools and nursing homes), or other variables potentially linked with air quality (e.g., public parks and green spaces). 

A user-centric approach was adopted, involving policymakers from local administrations, urban planners from private companies, environmental social agents and scientific personnel from research institutions and universities. To get a deep understanding of how uncertainty maps can add value to users’ objectives, we conducted a series of individual interviews and a co-design workshop based on design thinking, which allowed for the co-design of the interactive platform. The prototype of the interactive platform was presented in a second workshop, where the users tested the prototype and provided input to further developing the final tool.

The final product is the uncertAIR platform, an open-source interactive tool that integrates modeled NO2 concentrations, their uncertainty and probability of exceedances of legal thresholds, together with  social-ecological-technological variables at different scales of time and spatial resolution. Data can be visualized and downloaded with a temporal resolution of annual or daily averages, and a spatial resolution of 20 m or aggregated at census areas. This integrated dataset serves as the foundational step to integrate uncertainty information on future air quality policy making in Barcelona, such as health impact assessments, official communications, campaign planning, and location optimization of new monitoring stations.

How to cite: Carnerero, C., Mateu Armengol, J., Criado, A., Frangeskou, A., Urquiza, D., Bojovic, D., and Soret, A.: Co-designing an interactive tool to communicate the uncertainty of urban air quality models: uncertAIR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14629,, 2024.

On-site presentation
Erick Otenyo, Abubakr Salih Babiker, Marta Baraibar, and Viola Otieno

The East Africa Hazards Watch is an online web platform that supports tracking extreme events such as drought, cyclones, pests (desert locust), heavy rainfall, floods or crop failures, which are increasing in frequency and intensity due to climate change in East Africa.

About 90% of the disasters in East Africa are due to weather, climate hazards, leaving the region to be one of the most vulnerable to extreme events. Considering the high dependency of the economic systems in the region on natural resources, the impacts of weather and climate extremes have far-reaching socioeconomic consequences. To protect the population against these hazards and to support the resilience of the local communities, there is a dire need for efficient early warning systems and actionable information for decision making. The East Africa Hazards Watch was developed to fill this gap.

The system aggregates risk information from different specialized systems and presents them in one platform. The main goal of the new system is to collect, store, and analyze risk data from different sources and present it in a color-coded system indicating a different level of alert and urgency.  This public regional multi-hazards watch system aims at providing decision ready information, to support transnational coordination and early action across borders. 

Forecasting and Monitoring Components

  • Weather Forecast data - Presents weather forecasts of total rainfall, heavy precipitation and temperatures in weekly, monthly and seasonal timescales, generated at ICPAC.
  • Drought Monitoring - The East Africa Drought Watch is a near-real time system that uses Earth Observation and Weather information to monitor drought conditions in the East Africa region. It contains drought-relevant information such as maps of indicators derived from different data sources (e.g., precipitation measurements, satellite measurements, modeled soil moisture content)
  • Agriculture and Rangelands Monitoring - Every 10 days, the system generates automatic warnings about low or delayed vegetation performance at province level plus weather and Earth Observation vegetation indicators
  • Food Security Monitoring - ICPAC produces a monthly bulletin on the state of food security in the region using Integrated Phase Classification (IPC). This information is presented in a color-coded system that reflects the state of acuteness in each impacted area in the region
  • Climate Change - Presents temperature variation during the past years for the region, showing the warmest years in the record and how the trend is doing in the past years. Also includes climate change projections until 2100
  • Time Series Analysis - The system allows users to click at any point on the map and get time series analysis charts that show the trend for the past time periods for the different enabled layers.
  • Impact and Vulnerability analysis - For some layers like heavy rainfall forecasts and Drought indicators, the application provides information about the population that might be affected by the hazard for any selected location. 

The system also allows to overlay hazard layers with other socio-economic and infrastructure data. This enables identification of infrastructure like schools and health facilities that are at risk of being affected by an impending hazard.

How to cite: Otenyo, E., Babiker, A. S., Baraibar, M., and Otieno, V.: The East Africa Hazards Watch - Meeting the growing need of risk Information due to increasing climate extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22039,, 2024.

On-site presentation
Titike Bahaga, Zewdu Segele, Hussen Endris, Anthony Mwanthi, Masilin Gudoshava, and Eunice Koech

The Greater Horn of Africa (GHA) region is most vulnerable to climate-related risks. The effects of climate change have become increasingly evident in the region through a rise in the frequency and intensity of extreme weather and climate events, notably recurrent and severe droughts, floods, landslides, and tropical cyclones. These extreme climatic events have had far-reaching consequences on the key socio-economic sectors. The extended drought experienced in 2020/2022 led to the loss of millions of livestock and plunged millions of individuals into poverty, prompting forced displacement and insecurity. In contrast, the strong El Niño and positive Indian Ocean Dipole (IOD) events in 2023/2024 brought substantial rainfall to Somalia, Ethiopia, and Kenya in October and November 2023, resulting in flooding that has caused the loss of over 100 lives and displaced more than 700,000 people. Thus, providing reliable and timely climate information is essential for climate services and is increasingly crucial in supporting decision-making processes across a range of climate-sensitive sectors and reducing extreme climate impact. 

The IGAD Climate Prediction and Applications Centre (ICPAC), as a World Meteorological Organization (WMO) Regional Climate Centre (RCC), currently performs the mandatory and recommended RCC functions covering the domains of climate monitoring, climate forecasting, capacity development, and generation of regional and sub-regional tailored products relevant to the various socio-economic sectors. ICPAC has developed improved and tailored climate products and innovative decision support tools to enhance early warning services. It is also one of the first RCCs to adopt the objective forecasting technique and produce a traceable, reproducible, and verifiable forecast based on WMO’s recommendation. Innovative approaches to user engagement through co-production, communication channels, user-friendly interfaces, and dissemination of climate information have also been developed. 

In this session, we would like to showcase the innovative early warning methods, products, services, and platforms developed by ICPAC for response planning and anticipatory actions to enhance community resilience in the GHA region. This includes improved objective forecasting methods for monthly and seasonal forecast products, innovative approaches to user engagement through co-production, communication channels, and sector-tailored products (onset, cessation, dry and wet spells, probability of exceedance). 

How to cite: Bahaga, T., Segele, Z., Endris, H., Mwanthi, A., Gudoshava, M., and Koech, E.: Showcasing Advances in Climate Prediction and Early Warning Systems in the Greater Horn of Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22080,, 2024.

On-site presentation
Maximilian Söchting, Miguel D. Mahecha, David Montero Loaiza, and Gerik Scheuermann

Data streams representing the Earth system both through modeling and remote sensing approaches, encompass a diverse range and massive amount of information. Unveiling insights at global and local scales becomes increasingly challenging for the wider public and the broader scientific audience as the temporal and spatial resolutions of data sets continually improve. An effective solution to this involves the development of fully interactive visualizations capable of rendering terabytes of data in real-time, spanning time, space, variables, and model variants., the Leipzig Explorer of Earth Data Cubes, was the first tool that allowed to explore and interact with large Earth system data sets in the form of an interactive data cube visualization in the web browser, but was limited to a few preset data sets.

Here we present Lexcube for Jupyter, a Jupyter notebook extension building on top of the existing software components, that allows to visualize any spatiotemporal or otherwise three-dimensional data as an interactive 3D data cube. The data cube visualization treats all three dimensions equally and, e.g., in the case of a spatiotemporal data cube, allows to inspect temporal patterns in a novel way. Interaction with the data cube is designed to be intuitive, also allowing touch gestures on touch-capable devices. Building on top of the powerful open-source libraries Xarray and Numpy, Lexcube for Juypter integrates effortlessly into the existing ecosystem of open-source data cube software components as it is able to visualize any gridded data set from those libraries, including remotely stored and chunked data sets. Furthermore, Lexcube for Jupyter allows to export the currently visible data cube as a new Xarray or Numpy object, allowing scientists to use Lexcube in their workflow for data selection and curation. In addition, new disciplines such as the atmospheric sciences may profit from Lexcube for Juypter as they can now visualize their own three-dimensional data that is not necessarily spatiotemporal, e.g., three-dimensional atmospheric humidity data cubes (latitude×longitude×pressure level) as seen on Lexcube for Jupyter is open-source and available on GitHub and PyPi since January 2024.

How to cite: Söchting, M., Mahecha, M. D., Montero Loaiza, D., and Scheuermann, G.: Lexcube for Jupyter: Interactive Earth System Data Cube Visualization in Jupyter Notebooks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21547,, 2024.

On-site presentation
Raphael Quast and Wolfgang Wagner

EOmaps is a free and open-source python package specifically tailored for geographic data visualization and analysis.

The main goals of the package are twofold:

  • Speed up and simplify the daily struggle of geographic data visualization
  • Directly use the figures as fully customisable interactive data-analysis widgets

EOmaps is built on top of matplotlib and cartopy and integrates well with the scientific python infrastructure (numpy, pandas, xarray, geopandas, datashader, etc.). It provides a flexible and well-documented API to create publication-ready figures and it can be used to visualize (potentially large) structured (e.g. raster) or unstructured (e.g. unordered lists) datasets provided in arbitrary projections. 

In addition, EOmaps comes with many useful features to help with scientific geo-data analysis:

  • Maps can have multiple layers to interactively compare and (transparently) overlay datasets, web-maps etc.
  • Once a dataset is plotted, you can assign arbitrary callback functions to interactively run your analysis-workflow on selected datapoints (e.g. load data from a database, plot underlying timeseries, histograms etc.)

Figures created with EOmaps can be exported as images (png, jpeg, ...), vector-graphics (svg) or embedded in Jupyter Notebooks, web-pages (html) or in GUI frameworks such as Qt or tkinter.

In this presentation we will highlight the capabilities of EOmaps and show how it can be used in a variety of different situations to aid your scientific data analysis workflow.

EOmaps source-code:  
EOmaps documentation:

How to cite: Quast, R. and Wagner, W.: EOmaps: An open-source python package for geographic data visualization and analysis., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11327,, 2024.

On-site presentation
Lucile Gaultier, Fabrice Collard, Craig Donlon, Ziad El Khoury Hanna, Sylvain Herlédan, and Guillaume Le Seach

In the past decade, the emergence of new satellites and sensors has facilitated the observation of a diverse range of oceanic physical variables across various scales. For instance, the Sentinel 1-2-3-6 program encompasses sensors like SAR, Ocean Color, Temperature brightness, or altimeter, each with an individual long revisit time but a rapid revisit from a constellation perspective. Additionally, geostationary sensors such as SEVIRI contribute by providing Infra Red SST every hour, significantly enhancing coverage in cloudy areas. These variables contain crucial information about the ocean's state.

Despite the wealth of data, discovering, collocating, and analyzing a heterogeneous dataset can be challenging and act as a barrier for potential users wishing to leverage Earth Observation (EO) data. Accessing low-level data and preparing them for analysis requires a diverse set of skills. Addressing this challenge, the Ocean Virtual Laboratory Next Generation (OVL-NG) project has developed two tools, which will be introduced.

Firstly, online data visualization websites, such as, have been made publicly accessible. These platforms empower users to explore various satellite, in-situ, and model data with just a few clicks. Users can navigate through time and space, easily compare hundreds of products (some in Near Real-Time), and utilize drawing and annotation features. The OVL web portal also facilitates sharing interesting cases with fellow scientists and communicating about captivating oceanic structures.

Secondly, a complementary tool named SEAScope offers additional features for analyzing pre-processed data and user-generated data. SEAScope is a free and open-source standalone application compatible with Windows, Linux, and macOS. It allows users to collocate data in time and space, rendering them on a 3D globe. Users can adjust rendering settings on the fly, extract data over a specific area or transect, and interface with external applications like Jupyter notebooks. This functionality enables users to extract data on a shared grid, analyze them, and import the results back into SEAScope for visualization alongside the input data.

                                         The OVL-NG tools will be showcased at the OceanDataLab booth


How to cite: Gaultier, L., Collard, F., Donlon, C., El Khoury Hanna, Z., Herlédan, S., and Le Seach, G.: How to benefit from multi-sensor synergy using open Ocean Virtual Laboratory tools, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18613,, 2024.


Posters on site: Tue, 16 Apr, 16:15–18:00 | Hall X3

Display time: Tue, 16 Apr 14:00–Tue, 16 Apr 18:00
Chairpersons: Tobias Kerzenmacher, Berit Arheimer, Christof Lorenz
Frida Gyllensvärd and Berit Arheimer

Water is the basis for life and ultimately the reason why our society could develop the way it did, and thus, water security is an indirect core component in all 17 UN sustainable development goals. However, scientific water data and information are rarely accessible in an easy and understandable way for managers and policy makers. Moreover, hydrological sciences are fragmented with less tradition of sharing results, data and tools between scientists than in many other disciplines. Numerous efforts from development projects have launched prototypes and demonstrators of web-based applications to overcome these issues, but without long-term maintenance most of them disappear at project end. Here we will present experience from developing, maintaining and using three non-commercial operational services to facilitate actions in water security and promote scientific engagement with stakeholders. provides readily available modelled hydrological data for continent or global scale at sub-catchment resolution of on average 1000 km2 (Arheimer et al., 2020), along with open source code with documentation and data compilation/visualization/training tools. The visitor can explore data for the past, present or future, download the numerical model, or order data subscriptions. The service also provides tutorials, model documentation and training material for model setup. The website is linked to an annual open (free) training course in HYPE modelling for various societal needs. is co-designed with sectorial users in low- and middle-income countries, on behalf of the World Meteorological Organisation (WMO) and the Green Climate Fund (GCF). It offers guidance for non-climate experts and access to two different tools to explore climate-change impact on water resources: 1) instant summary reports of climate change for any site on the globe, 2) easy access to many pre-calculated climate indicators. The main purpose of this new service is to provide scientific data to argue for climate mitigation and adaptation investments in vulnerable countries (Photiadou et al., 2021). Pre-calculated water variables are based on an extensive production chain using global model ensembles from global modelling communities, e.g. CMIP, Cordex, WWH and a rigorous quality assurance protocol. is co-designed with the community of the International Association of Hydrological Sciences (IAHS). It is a brand-new platform to search and find (based on key-words) where on Earth there are: scientific results available from research projects (case-studies), monitoring programs (data repositories), publications (in HSJ, PIAHS) and researchers (personal profiles). The aim is to stimulate and facilitate engagement, interactions and dialogues among scientists and between scientists and stakeholders. The Digital Water Globe offers co-creation and re-examines the role of scientific outreach; it is a scientific community effort completely dependent on content from the users to explore networking and science communication in action.


The presentation will focus on obtained feedback, opportunities and challenges in running operational services with aim to share scientific data and tools with a wide range of users.



Arheimer et al., 2020: Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation, HESS 24, 535–559,   

Photiadou et al. 2021. Designing a climate service for planning climate actions in vulnerable countries. Atmosphere 12:121. 

How to cite: Gyllensvärd, F. and Arheimer, B.: Community based services providing Open Science in water management worldwide, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17568,, 2024.

Aimee Barciauskas, Max Jones, Kata Martin, Sean Harkins, and Vincent Sarago

Visualization of Earth science data is crucial for its exploration and understanding. Web browsers, as a universal platform, face the challenge of rendering complex geospatial data swiftly. This led to the creation of pre-generated static map tiles, allowing quick visualization but limiting user control over data representation and imposing storage and update burdens on providers.

While pregenerated map tiles make it possible to visualize data quickly, there are drawbacks. The most significant is the data provider chooses how the data will appear. The user has no power to adjust the visualization, such as modifying the color scale, color map or perform “band math” where multiple variables are combined to produce a new variable. Other drawbacks impact the data provider, such as storage costs and maintaining a pipeline to constantly update or reprocess the tile storage with new and updated data. Next generation approaches give that power to the user, while still giving providers control over the costs.

More recent years have seen the success of the dynamic tiling approach which allows for on-demand map tile creation. This approach has traditionally relied on Cloud-Optimized GeoTIFFs (COGs). When Zarr gained popularity for large-scale n-dimensional data analysis, users started to call for browser-based visualization, but no tools existed to visualize Zarr in the browser.

Now there are 2 options: a dynamic tile server and a dynamic client approach. rio_tiler’s XarrayReader supports tile rendering from anything that is xarray-readable. This means a tile server can render tiles from Zarr stores as well as netCDF4/HDF5 and other formats. However, a tile server still requires running a server while the second option, a “dynamic client”, reads Zarr directly in the browser client and uses WebGL to render map tiles.

The authors have contributed to libraries and testing of both approaches and authored a “Zarr Visualization Report”. This report includes the tradeoffs, requirements for preprocessing the data and performance testing results for when those preprocessing steps were taken or not. We hope that readers will be able to reuse lessons learned and recommendations to deliver their Zarr data to users in web browsers and contribute to the wider adoption of this format for large scale environmental data understanding.

Looking ahead, the focus is on making NASA datasets more accessible through these innovative approaches. The use of Kerchunk reference files, or virtual Zarr datasets, will play a key role in indexing various archival file formats used by NASA, such as HDF5 and NetCDF4. With the capability of titiler-xarray to handle any xarray-readable data, a wide range of NASA datasets can be visualized without the need for duplicating data. Additionally, the creation of data pyramids will further enhance visualization speed at lower resolutions.

How to cite: Barciauskas, A., Jones, M., Martin, K., Harkins, S., and Sarago, V.: Next-Gen Zarr Web Map Visualization, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11805,, 2024.

Gerard Llorach-Tó, Enoc Martínez, Joaquín Del-Río, Gonzalo Simarro, Martino Pani, Andrea Bucchi, Ya Huang, and Emilio García-Ladona

Understanding and picturing the state of the sea surface according to wave parameters can be difficult for non-expert users. 3D digital twins of the ocean, i.e., realistic virtual copies of the sea state with live updates, can provide user-friendly visualizations. An animated visual representation offers users a more tangible reference to the actual sea state in the field than conventional swell and wind forecasts. Our work presents an interactive web-based open-source visualization of wave data in a 3D realistic environment. The wave data used is provided by a forecast model, CMEMS [1], and the in-situ observation platform OBSEA [2]. Both of these data products provide an open access API that can be accessed via the browser, following the FAIR principles. The challenge of this work is to translate the wave parameters of the data products into a real-time computer graphics simulation representing the real sea state. Different data products provide different parameters, for example, CMEMS forecast model computes wave significant height, wave period, and direction for ‘sea surface wave’, ‘wind wave’, ‘swell 1’, and ‘swell 2’, whereas OBSEA measures wave properties with an acoustic doppler wave array such as ‘Hm0’, ‘H1/10’, ‘H1/3’, and ‘directional spread’. We will discuss algorithms based on empirical observations to generate the virtual sea state from a selection of wave parameters. Subsequently both quantitative and qualitative metrics based on observations will be used to compare between the 3D digital twin and the real sea state. Preliminary results of the digital twin can be found at and 


[1] Korres, G., Oikonomou, C., Denaxa, D., & Sotiropoulou, M. (2023). Mediterranean Sea Waves Analysis and Forecast (Copernicus Marine Service MED-Waves, MEDWAΜ4 system) (Version 1) [Data set]. Copernicus Marine Service (CMS). DOI: 10.25423/CMCC/MEDSEA_ANALYSISFORECAST_WAV_006_017_MEDWAM4

[2] Del Rio, J. [et al.]. Obsea: a decadal balance for a cabled observatory deployment. "IEEE access", 13 Febrer 2020, vol. 8, p. 33163-33177.

How to cite: Llorach-Tó, G., Martínez, E., Del-Río, J., Simarro, G., Pani, M., Bucchi, A., Huang, Y., and García-Ladona, E.: 3D Digital Twins of the Ocean: towards an intuitive and realistic visualization of wave parameters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19105,, 2024.

Marie-Laure Frery, Mathilde Siméon, Roger Fjortoft, Sébastien Charlois, Mélanie Prugniaux, and Matthias Raynal

The MicroWave Expertise center has first been developed to provide a  work environment to support the calibration/validations activities and address the high resolution of Surface Water Ocean Topography (SWOT) mission, launched on December 16th, 2022.  Onboard, the new instrument ‘KaRIn’, is a revolution for both oceanography and hydrology communities and gives access to small scale measurements over ocean, worldwide river heights and flows, and lake heights.

With optimized storage and computation methods, the MicroWave Expertise Center is designed to ease the exploration and studies of 16TB/day products. The tools developed for SWOT are generic and can now be applied to any altimetric mission.

Experts are provided simple and scriptable explore numerous data providers such as copernicus dias, ecmwf,

Some tutorials are already available along with visualisation tools. And the list will be growing up in close future from users requirements.

The expertise center is operational and ensure SWOT calval activities. Prospects address SWOT ocean and hydrology studies but could be enlarged to  hydrological research, multi-sensor comparison

How to cite: Frery, M.-L., Siméon, M., Fjortoft, R., Charlois, S., Prugniaux, M., and Raynal, M.: MicroWave Expertise center : a work environment for microwave data exploration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16316,, 2024.