Meteomatics

Clouds play a crucial role in regulating Earth’s climate, and understanding their microphysics is key to more accurate climate projections. However, clouds and cloud-aerosol interactions are major sources of uncertainties in these projections. Questions such as how clouds will change in a warming climate and their influence on Earth’s radiation budget are yet to be fully answered. The Atmospheric Physics group at the Swiss Federal Institute of Technology in Zurich (ETH Zurich) is dedicated to studying the formation and evolution of clouds, particularly cloud-aerosol interactions. Their project, CLOUDLAB, aims to improve understanding of cloud microphysical processes and precipitation formation. However, the data collection process for cloud particles, wind, and aerosol concentration has evolved over the years, with each method presenting its own challenges. Ground-based measurements were influenced by the ground and blowing snow, while measurements on a cable car and tethered balloons offered limited vertical structure and location possibilities.

The defence sector has always been significantly impacted by weather conditions, often determining the outcome of pivotal battles throughout history. Today, most military forces closely monitor the weather to avoid risks, ensure weaponry and vehicle performance, and increase operational success. However, the data from national meteorological services and traditional weather forecasting methods often fall short in providing accurate data, especially from the lowest part of the atmosphere where hazardous events form. Satellites, ground stations, and radars can only take remote measurements, while balloons and aircraft are limited to short timeframes and specific locations. Furthermore, national services cover limited domains and use different weather models, leading to inconsistencies and inaccuracies in weather forecasts. The military needs a more reliable and accurate weather forecasting solution to ensure the success of their operations.

Unmanned aerial vehicles such as drones and future autonomous air taxis lack an onboard pilot who can respond directly to weather changes and impacts. The response to weather changes is instead controlled by software and autopilot. This necessitates the availability of live weather data during a flight and weather forecast data for safe and efficient pre-flight planning. If the weather poses increased or unacceptable flight risks, the flight route or departure time needs to be adjusted accordingly. This challenge is further complicated by the need for industries without aviation expertise, such as agriculture, logistics, traffic management, and surveillance, to operate drones safely and efficiently in a commercial context.

Toyota, a leading automotive company, is committed to reducing its carbon footprint and conserving the environment. As part of its 'Toyota Environmental Challenge 2050', the company aims to reduce CO2 emissions, protect water resources, boost recycling, and conserve biodiversity. One of the key areas of focus is the operations sector of its European plants, where the company aims to eliminate CO2 emissions and reduce energy costs. The challenge lies in managing the energy consumption of these plants, which is directly influenced by weather conditions such as outside temperature, humidity, and wind. These factors affect the ambient temperature inside the facilities, which must be kept stable for the equipment to function properly. Furthermore, as the factories transition to renewable energy sources, their supply capabilities become sensitive to weather variations. Therefore, accurate weather forecasts are crucial for effective planning of energy systems.

Anglian Water, the largest water and water recycling company in England and Wales, faced significant challenges in managing weather data. The company's operations required a large number of weather data sets to inform decision-making, but the multiple weather data providers they relied on were complicated and inconsistent. This led to data discrepancies that affected decision-making processes and brought financial and administrative challenges. Additionally, the different providers required data to be collected in various ways, which was technically demanding and time-consuming. These issues prompted the company to streamline its operations by replacing most of its previous providers.

The Swiss Academic Space Initiative (ARIS), an educational association founded by students from the Swiss Federal Institute of Technology in Zurich (ETH-Zurich) in 2017, is training future engineers and project managers for the growing aerospace market. The association, which now includes students from six different Swiss universities, aims to place a small-scale satellite in orbit using an in-house developed bi-liquid launcher within the next decade. To achieve this, ARIS needs to conduct in-orbit experiments and research, and regularly participate in international competitions with other aerospace engineering student organizations. However, the launch and recovery of spacecraft are significantly affected by Earth's weather conditions, including temperature, wind speed and direction, rain, hail, lightning, cloud cover, and electric fields. ARIS needed accurate weather data to conduct flight simulations, assess initial conditions in the launch area, and estimate the rocket's highest height, landing location, and the danger zone for people on the ground.

Navily, a digital platform for recreational boaters, was facing challenges in providing accurate and timely weather forecasts to its users. The app, which serves as a cruising guide, booking platform, and sailing community, was relying on a weather data provider that was not delivering precise forecasts due to its reliance on a single weather forecast model. This lack of precision was a significant issue as weather conditions are paramount to sailing, defining the success and safety of a journey at sea. The decision of where to anchor is heavily influenced by weather conditions, and unfavorable or rapidly changing conditions can lead to accidents, potentially putting passengers' lives at risk. Navily's goal was to simplify this decision-making process for its users by providing a recommendation score for each anchorage, taking into account user ratings, the weather forecast, and the natural protection offered by the anchorage. However, the lack of accurate weather data was hindering this process.

Stadtwerke München, one of the largest energy and infrastructure companies in Germany, was facing challenges in accurately forecasting solar power production. The production of solar power and other renewable energies is highly dependent on weather conditions, making it difficult to predict the amount of electricity that can be produced. This unpredictability posed a problem for Stadtwerke München's day-to-day electricity trading business and the integration of solar power into the electricity market. Inaccurate forecasts could lead to increased costs as balancing energy, usually purchased at a high price, would have to be used if there was a deviation from the specified amount of electricity that a company could provide. Furthermore, accurate power forecasts are essential for the successful and economical integration of renewables into the electricity market, especially as solar power and other renewables continue to expand.

ABS Wavesight, a maritime software as a service (SaaS) company, was seeking to improve its risk management platform, ABS My Digital Fleet™, by integrating high-resolution historical and forecast weather data. The company aimed to provide actionable insights to its users to help them understand and lower fuel consumption, improve bunker costs, and reduce carbon intensity levels. Additionally, ABS Wavesight wanted to highlight the potential structural impacts from weather exposure during a ship’s voyage to better understand and mitigate risk. The challenge was to find a suitable partner that could provide accurate and hyperlocal weather data that could be seamlessly integrated into their existing platform.

Severe weather events often cause significant damage to buildings, accounting for about a quarter of home insurance claims in the UK. The challenge lies in validating these claims accurately and efficiently. Home Repair Network (HRN), an independent contractor manager in the UK's property damage industry, specializes in managing networks of approved local surveyors, tradespersons, and building contractors. They streamline the process of handling less complex building damage claims for both insurance companies and homeowners. However, the process of validating weather-related damages can be complex and time-consuming, requiring precise and dependable assessment of the damages.

Schweizer Hagel, a leading provider of agricultural insurance coverage in Switzerland, France, and Italy, faced the challenge of accurately assessing environmental risks to agricultural crops due to weather events. The company needed to determine insurance premiums that were both equitable for policyholders and adequate to cover insured losses. This required precise local weather information, including historical data spanning up to 30 years, and parameters related to drought, heavy rain, hailstorms, lightning, and storms. The company was in search of a reliable weather data solution that offered flexibility, comprehensive weather parameters, and access to historical weather data. Additionally, Schweizer Hagel required a provider that offered reliable customer service to address specific issues and inquiries promptly and proficiently.

Spottitt, a cloud-based solution provider, leverages satellite data and advanced AI models to offer insights for the energy, utility, and infrastructure sectors. The company's services are crucial in identifying potential points of failure in critical infrastructure such as transmission grids, pipelines, and substations, and in developing strategies to minimize downtime and mitigate the risk of catastrophic damages. However, extreme weather events like heatwaves, severe cold snaps, heavy rainfall, and windstorms pose significant threats to infrastructure, leading to equipment damage, power outages, wildfires, and safety risks for power grids and utility pipelines. Additionally, the performance and efficiency of renewable energy systems are dependent on weather conditions. Therefore, there was a need for a solution that could provide high-resolution weather information to monitor rapidly changing weather and climate conditions around critical infrastructure.