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 (https://epos-eu.github.io/epos-open-source/) 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, https://doi.org/10.5194/egusphere-egu24-7931, 2024.

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, https://doi.org/10.5194/egusphere-egu24-16475, 2024.

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, https://doi.org/10.5194/egusphere-egu24-22039, 2024.

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, https://doi.org/10.5194/egusphere-egu24-22080, 2024.

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. Lexcube.org, 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 Lexcube.org 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.org. 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, https://doi.org/10.5194/egusphere-egu24-21547, 2024.

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: https://github.com/raphaelquast/EOmaps  
EOmaps documentation: https://eomaps.readthedocs.io/

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, https://doi.org/10.5194/egusphere-egu24-11327, 2024.

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 https://ovl.oceandatalab.com, 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, https://doi.org/10.5194/egusphere-egu24-18613, 2024.