Key Takeaways

• Before the arrival of weather satellites, weather ships were crucial for gathering information for weather forecasting. Also called Ocean Station Vessels, they are dedicated ships strategically positioned around oceans as platforms for studying the surface and upper atmosphere weather.
• The first Radiosondes or radio-meteorographs were flown into the stratosphere in the early 1930s. After years of advancement, modern radiosondes provide upper air data that are crucial to weather forecasts and research. The vertical data resolution and height coverage that radiosondes provide cannot be matched by any individual observing system (for example, aircraft, or satellites).
• Initially built during the Second World War for identifying and tracking enemy aircraft, radar equipment was repurposed soon after the war ended. By 1954, AN/CPS-9, the first radar designed exclusively for meteorological use, was unveiled by the Air Weather Service of the United States Air Force. As an essential part of any weather equipment, radar can be used to predict precipitation related to hurricanes, thunderstorms, and winter storms.
• Equipped with sensors, weather drones are flown into the boundary layer, i.e., the lowest layer of the earth’s atmosphere, to collect information about humidity, temperature, and wind, for enhanced weather forecasting models. The use of drones has the capacity to greatly increase the accuracy of weather forecasting models, which can provide more sophisticated warnings for storms like tornadoes.

Introduction

 

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Weather Balloons, 1906

•  1906 marked the beginning of assessing unmanned balloons as means to take weather devices into the atmosphere. In October 1909, the Weather Bureau (forerunner of the National Weather Service — NWS) launched a free-rising balloon from Omaha, Nebraska, reaching a height of 15 miles.
• In the 1940s, regular observations started, and now, weather balloons, also known as sounding balloons, are launched twice every day by NWS, from 92 stations within the United States, and about 900 locations globally.
• Weather balloons are used to examine the upper atmosphere and give significant data for forecasting weather. Like mobile weather stations, they carry scientific instruments that are equipped with sets of sensors to gauge weather variables such as atmospheric pressure, humidity, and temperature. Data collected is transmitted to ground-based receiver stations every 1 – 2 seconds, for storage and analysis.
• Weather balloons are the main data source above the ground, providing data for research, input for computer forecast models, and local data needed by meteorologists for forecasting and predicting storms. Weather balloon data used by computer forecast models are employed by forecasters globally, without which precise forecasts further than a few hours would not be possible.

 

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Weather Ships, 1921

•  Initially proposed in 1921 by Meteo-France, weather ships were very useful during the Second World War, but suffered attacks from U-Boat because they were defenseless. Before the arrival of weather satellites, they were crucial for gathering data for weather forecasting. A global network of weather ships established by the International Civil Aviation Organization (ICAO) in 1948 remained until 1985 when weather ships were slowly swapped with buoys.
• Known also as Ocean Station Vessels, weather ships are dedicated ships strategically positioned around oceans as platforms for studying the surface and upper atmosphere weather. Being positioned around the Atlantic and North Pacific Oceans, weather ships used radio to report their observations.
• Polarfront — aka weather station M ("Mike") — was taken from operation in January 2010, being the last weather ship. However, a fleet of voluntary merchant vessels still observe the weather from ships, in regular commercial operations.

 

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Radiosondes, The 1930s

• Also known as radio-meteorographs, the first “radiosondes” were flown into the stratosphere in the early 1930s. A National Radiosonde Network was founded by the Weather Bureau in 1937 and is still in operation now.
• Tiny, disposable instrument packages (like small "weather stations") suspended under large balloons, radiosondes record temperature, pressure, humidity, and GPS data, as well as wind speed and direction, providing important data for computer models, local weather forecasting, and research. Collected data are then transmitted in real-time and high temporal resolution (every 1 second now) through radiowaves, to a ground-based receiving station at the launch site, hence it’s called "radio" sondes. A dedicated frequency range is set aside for these meteorological studies. The radiosonde data, received from about 1000 international active sites, are incorporated into the weather forecast models.
• After years of advancement and development, modern radiosondes deliver upper air data that are crucial to weather forecasts and research. The vertical data resolution and height coverage that radiosondes provide cannot be matched by any individual observing system (for example, aircraft, satellites, or ground-based sensors).

 

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Numerical Weather Prediction (NWP) Models, The 1950s

• The numerical weather prediction era started in the 1950s, with the speed, capacity, and complexity of the models growing with computing power. Methods for feeding data into the models also became more sophisticated with new observations from sources like drifting weather balloons, earth-orbiting satellites, and radar systems.
• In forecasting weather, NWP models engage a set of equations that illustrate fluid flow and are interpreted into computer code. Over the years, numerical forecasts have advanced progressively. Data from NWP are the most recognizable form of weather model data — present weather observations are processed to predict future weather. Current weather studies, which determine output, are incorporated into the model’s framework and applied to generate forecasts for precipitation, temperature, and many other meteorological components from the oceans to the top of the atmosphere. Practically every step in NWP involves approximations, compromises, estimations, and omissions.

 

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Radar, 1954

•  Initially built during the Second World War for identifying and tracking enemy aircraft, radar equipment was repurposed on weather stations, soon after the war ended. In 1942, 25 aeronautical radars were donated by the U.S. Navy to the Weather Bureau, for meteorological use. By 1954, AN/CPS-9, the first radar exclusively designed for meteorological use, was revealed by the Air Weather Service of the United States Air Force.
•  Radar is primarily used to detect, track, and estimate the types of weather events — like snow and rain — and the intensity of the precipitation. It is an essential part of any weather equipment and can also be used to predict precipitation related to hurricanes, thunderstorms, and winter storms.
•  Pulse-Doppler Radars are now used by modern stations to detect rain droplet motion and the intensity of the precipitation. With the use of dual-polarization radar which sends and receives vertical and horizontal pulses, meteorologists always have a much clearer understanding of the multidimensional situation. The National Weather Service (NWS) currently uses Next-Generation Radar (NEXRAD) with dual-polarization technology to give more detailed information to forecasters with better approximations of the shape, size, type of precipitation, and overall gravity of incoming weather.

 

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Weather Satellites, 1960

• The earliest attempts by the U.S. to see earth’s weather from space started in the 1950s. After the development of various experimental programs, by 1959, a revolutionary weather exploration mission went to space aboard the Explorer VII satellite. The first weather satellite named the Television InfraRed Observational Satellite (TIROS-1) was launched in April 1960. It operated for only 78 days and gathered 19,389 useful pictures of the earth.
• Weather satellites are the highest technology options accessible to weather forecasters, as they can see and collect large volumes of data about weather and climate with unmatched views. They hold either asynchronous orbits (covering the whole earth's surface) or geostationary (aiming at one spot for a long time). Being privy to unhindered views of the earth's cloud systems from orbit, satellites can collect data ranging from ocean temperatures to noticing sandstorms or wildfires.
• Their uniqueness lies in the ability to provide views of weather systems over large-scale areas, so weather patterns can be monitored hours or days before more traditional systems like weather radar. They are frequently used to track and observe large-scale weather patterns such as hurricanes. Real-time views of earth weather and billions of data bytes utilized for forecasting weather are provided by a fleet of modern environmental satellites, operated by the National Oceanic and Atmospheric Administration (NOAA).

 

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Drones, 1991

• The Perseus, an unmanned aircraft, was the first weather drone developed by NASA. It was built to fly 60,000 feet and gather data on weather patterns and ozone depletion. Developed in 1991, its service was withdrawn in 2003, even though it collected valuable data.
• Furnished with sensors, weather drones are flown into the boundary layer, the lowest layer of Earth’s atmosphere, to collect information about humidity, temperature, and wind, for enhanced weather forecasting models. As a major advancement over conventional methods of gathering data, the use of drones has the capacity to greatly increase the accuracy of weather forecasting models, that can provide more sophisticated warning for storms like tornadoes.
• With a license, drones can be flown at high altitudes above 3500 feet, without any risks or issues. Because they can be easily controlled, they can be flown directly into the wind or storms to get data for a precise location at a particular altitude.

 

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Research Strategy

Key Takeaways

•  Destination Earth (DestinE) is an initiative of the European Commission (EC) that involves the development of "a very high precision digital model of the Earth (a 'digital twin') to monitor and predict environmental change and human impact to support sustainable development." The EC has entrusted three organizations with the task of developing and implementing DestinE within the next 7-10 years, namely the European Centre for Medium-Range Weather Forecasts (ECMWF), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and the European Space Agency (ESA).
• DASH (or Dynamic Automated Scaleable Hydroinformatics) is a real-time flood modeling solution developed by FloodMapp that is purpose-built for impact-based flood forecasting and emergency management. DASH leverages traditional engineering approaches like hydrology and hydraulics, machine learning, automation, and big data to deliver "10,000 times faster and up to 200 times higher resolution than traditional models in an emergency response setting." It has been developed by a team of academics and industry professionals comprising hydrologists, data scientists, flood engineers, and software developers.
• Project OWL (Organization, Whereabouts, and Logistics) is a technological innovation that uses both "hardware and software that can be deployed in disaster areas to reestablish communication between affected civilians and first responders." Essentially, it is an open-source project that leverages IoT, mesh networking, and LoRa (long-range radio) connectivity to help disaster victims and emergency responders stay in contact during natural disasters.

Introduction

Destination Earth (DestinE)

•  Destination Earth (DestinE) is an initiative of the European Commission (EC) that involves the development of "a very high precision digital model of the Earth (a 'digital twin') to monitor and predict environmental change and human impact to support sustainable development." The EC has entrusted three organizations with the task of developing and implementing DestinE within the next 7-10 years, namely the European Centre for Medium-Range Weather Forecasts (ECMWF), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and the European Space Agency (ESA).

 

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• DestinE will enable European policymakers to tackle complex environmental challenges by doing the following:
• Monitoring and simulating the system developments of Earth (land, marine, biosphere, atmosphere) and human interventions.
•  Anticipating environmental disasters and the resultant social and economic crises with the intention of saving lives and avoiding large economic downturns.
• Enabling "the development and testing of scenarios" for further sustainable development.
• Since DestinE will "generate user-centric knowledge to support the objectives of the twin digital and green transitions," European policymakers can rely on accurate geospatial and socioeconomic data generated by the digital twins' simulation models to implement evidence-based policies. Policymakers can also use the data generated by DestinE to understand the ill effects of climate change better.
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• The three core components of the DestinE system are as follows:
• The DestinE Core Service Platform: It "will be a user-friendly and secure cloud-based digital modeling and open simulation platform" that will make DestinE easily accessible by stakeholders like policymakers, experts, scientists, and individual users. Currently, it is under development by the ESA.
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• The DestinE Data Lake: It will be a central data bank that will "effectively manage and offer various data sources." EUMETSAT will be responsible for the operation of the DestinE Data Lake.
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•  The Digital Twins: These will be digital replicas of Earth's highly complex systems "and will be built under thematic categorizations from the different domains of Earth science, such as extreme natural disasters, climate change adaptation, oceans, or biodiversity." Currently, the first two digital twins being developed by the ECMWF are based on extreme natural disasters and climate change adaptation.
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• Funding for the development of the DestinE Core Service Platform, the DestinE Data Lake, and the Digital Twins has been provided by the European Commission under its Digital Europe Programme. €150 million has been provided for the first 30-month implementation period between 2021 and 2024 (the first phase of implementation is scheduled for mid-2024).
• An additional €55 million will be provided by Horizon Europe for the preparation of new digital twins and further R&D to reinforce DestinE technologies (expected implementation by 2027). The European Commission has also established synergies with other EU programs like the EuroHPC Joint Undertaking, Copernicus, and the Space Program to achieve the goals related to DestinE. The European Commission has aimed to fully launch DestinE by 2030.

Real-Time Flood Intelligence (by FloodMapp)

• FloodMapp is a Queensland, Australia-based early-stage technology company that develops "rapid real-time flood forecasting and flood inundation mapping" solutions that provide greater warning time for potentially saving lives, reducing damage, and lessening financial losses. The company has developed DASH, the world's first "flood modeling solution purpose-built for impact-based flood forecasting and emergency management." FloodMapp was founded in 2018 and launched DASH in 2020.
• DASH (or Dynamic Automated Scaleable Hydroinformatics) is the real-time flood modeling solution that leverages traditional engineering approaches like hydrology and hydraulics, machine learning, automation, and big data to deliver "10,000 times faster and up to 200 times higher resolution than traditional models in an emergency response setting." It has been developed by a team of academics and industry professionals comprising hydrologists, data scientists, flood engineers, and software developers.
• It interoperates with other geographic information systems (GIS) "by offering a data layer that can be combined with other data streams to provide situational awareness to emergency response and recovery personnel." Combining the data streams that include data like real-time rainfall, forecast rainfall, and river height, DASH provides dynamic flood intelligence along "with live updates that can scale from street level to national views."
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• The DASH modeling technology combines with three products developed by FloodMapp, namely ForeCast, NowCast, and PostCast.
•  ForeCast: ForeCast offers short-term impact-based flood forecast real-time mapping data up to 7 days before a flood. The authorities can then use the data to plan evacuations and protect properties, assets, and sites.
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•  NowCast: NowCast offers "real-time flood map live feed" and data like flood inundation depths and extents during a flood. This enables the authorities to maintain situational awareness and take targeted actions.
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•  PostCast: PostCast provides "a wide-lens view, with street-level accuracy to quickly identify the people, property, and critical infrastructure that has been impacted by recent flooding." This helps the authorities to quickly assess damage and initiate recovery efforts.
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• FloodMapp's solutions have been adopted by companies and organizations in industries like government, transport, and critical infrastructure. These include the National Recovery and Resilience Agency of the Australian government, Queensland Fire and Emergency Services, Energy Queensland, the New South Wales government, and Queensland Reconstruction Authority, among others.

Project OWL

• Project OWL (Organization, Whereabouts, and Logistics) is a technological innovation that uses both "hardware and software that can be deployed in disaster areas to reestablish communication between affected civilians and first responders." Essentially, Project OWL is an open-source project that leverages IoT, mesh networking, and LoRa (long-range radio) connectivity to help disaster victims and emergency responders stay in contact during natural disasters.
• Project OWL was developed by five coding developers: Bryan Knouse, Nick Feuer, Taraqur Rahman, Charlie Evans, and Magus Pereira. The group won the inaugural IBM Call for Code Global Challenge in 2018. It was a hackathon organized by IBM that brought together coding developers from 156 countries with the intention of developing technology that could "help communities prepare for and recover from natural disasters."
• The complexity of network connectivity infrastructure (like phones, emails, and the internet) makes it vulnerable to natural disasters, technical problems, attacks, and cost fluctuations. Using simple wireless devices like the DuckLink hardware and the OWL Data Management System (DMS) software, Project OWL targets communication disruptions that often follow natural disasters.
• The hardware component of Project OWL is called the DuckLink, a simple wireless device that is either solar-powered or battery-supported and is cheap, easy to deploy, and does not require existing infrastructure support. The DuckLinks use Wi-Fi, Bluetooth/GPS, and low-frequency long-range radio (LoRa) connectivity to connect with other DuckLinks to form a resilient mesh network called the ClusterDuck network.
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• When the network is down during a natural disaster, users can establish a Wi-Fi connection to a nearby DuckLink using their smartphone or laptop. Since a DuckLink uses LoRa technology, it can connect to a local hub known as 'MamaDuck.' Several MamaDuck hubs connect over long distances to a 'PapaDuck,' an internet gateway that is linked through a satellite connection to the cloud-based OWL data management system (DMS).
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• The OWL data management system (DMS) is a cloud-based analytics system comprising "simple mapping and information tools" that enable first responders to easily contact civilians during natural disasters. Project OWL leverages software like IBM Watson, IBM IoT Platform, Apache-2.0, Java, JavaScript, and C++.
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• The developers of Project OWL have collaborated with the government of Puerto Rico to run field tests in Puerto Rico. The developers have installed nearly 30 DuckLink devices at universities and in communities in Puerto Rico. Project OWL is expected to be implemented very soon.

Research Strategy