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August 24, 2023 – Tomorrow.io, a global leader in weather intelligence, announced today its pathfinder radar satellites, Tomorrow-R1 and Tomorrow-R2, have successfully characterized precipitation intensity from space. This achievement places Tomorrow.io alongside NASA and JAXA as the only entities to have ever taken such measurements from orbit. 

Following the successful launches of Tomorrow-R1 and Tomorrow-R2 satellites in April and June, respectively, the company has completed initial testing of both satellites and their radar payloads are fully operational. With the initial calibration complete, both satellites are entering their longer-term calibration and validation phase, paving the way for the high-fidelity global precipitation measurements to be ingested into Tomorrow.io’s weather intelligence platform.

For the first time, Tomorrow.io demonstrated its ability in making  near real-time radar-based forecasting financially viable for every point on Earth, closing a decades-old gap in life-saving weather forecasting. Currently, 5 billion people live outside radar coverage with no radar-coverage over the oceans.

“The precipitation measurements have already proven the overall system performance, providing significantly more insight into weather than existing satellite-based cloud-top imaging systems,” said John Springmann, SVP of Space & Sensors at Tomorrow.io. “With initial measurements completed,  we are now in the process of growing the overall constellation to enable a revolution in weather forecast accuracy globally.”

As a commercially developed and privately funded enterprise, Tomorrow.io offers a revolutionary price-to-performance ratio enabled by private innovation. In contrast to government missions that have been limited by costs and single satellites, Tomorrow.io is building the de facto GPS network for weather, closing the decades-old gap in weather sensing from space.

Tomorrow.io has already been awarded more than $20M in contracts from the Department of Defense (DOD) and is partnering on a Collaborative R&D Agreement with the National Oceanic and Atmospheric Administration (NOAA).

From farmers predicting crop yields to governments preparing for natural disasters, the benefits of the data provided by Tomorrow.io’s satellite constellation has the potential to be felt worldwide by every person, business, and government on Earth,

The post Tomorrow.io Announces Successful Precipitation Scans from Its Space Radars appeared first on Tomorrow.io.

I spoke with Dan Slagen, CMO at Tomorrow.io, to get an inside look at new innovations now available and to learn how the company is enhancing the way organizations respond to and react to increasingly volatile weather. 

Check out the entire conversation below along with highlights of each product.

Summer Updates 2023

Enhanced Wind Mapping

Tomorrow.io upgraded its wind speed and direction data layers (DPLs) to provide more visual clarity into wind conditions. 

The wind speed DPL shows velocities via color-coding on the map timeline. Wind direction is displayed with wind barbs instead of colored heat maps.

As Dan explained, wind impacts countless sectors: “Aviation, rail, shipping, trucking, mining, sports and outdoors…it’s not really a matter of which industries are impacted, it’s how is each industry impacted.”

Expanded Tropical Cyclone Data

Previously, tropical cyclones were shown on a data single layer over Tomorrow.io’s maps. 

Now there are separate layers for:

• Forecast track cone of uncertainty
• Watches and warnings
• Observed track
• 5-day wind swath
• Wind speed probabilities

With storm volatility ramping up, these layers give businesses earlier insight into asset and operational exposure.

Low Level Wind Updates – U.S. and Israel

Tomorrow.io now offers low-level wind and temperature data for 11 altitude ranges from 10 to 300 meters. Users can visualize historic, real-time, and forecast conditions at different heights via the altitude slider.

Dan Slagen tells me that this update benefits aviation, construction, energy, and drone operators monitoring weather impacts on low-altitude infrastructure or flight paths.

Enhanced Map Visualization

Multiple map upgrades improve interactivity and customization:

• Customizable color palettes
• Filterable heat map ranges
• Unified settings tab
• Hoverable temperature

The goal is to help users tailor their visuals to each of their specific industries and use cases.

New Flight Level Data

For the first time, Tomorrow.io is offering flight level observations from 3,000 to 55,000 feet globally.

This includes wind, temperature, icing risk, and turbulence data to aid aviation and drone operators. Users will be able to access historical and forecast weather data for the parameters that matter most to them. 

County-Level Risk Monitoring

Tomorrow.io’s County Risk Map provides location-specific risk monitoring across the U.S. 

Users can create state or county subsets to track insights and get email digests. This county-level precision helps large enterprises monitor dispersed assets and helps government organizations track the hazardous conditions over their communities. 

More Historical Data Access

Tomorrow.io now provides minute-by-minute weather data for the past 24 hours and previous 7 days. This boosts historical analysis and weather modeling accuracy.

Streamlined Alert Management

Bulk Edits and In-App Notifications

The Tomorrow.io team is thrilled to share a Bulk Alert Editing enhancement to boost efficiency in managing alert recipients, locations, and status. 

New in-app notifications also raise awareness of triggered alerts.

Play Weather On Map

With new play-over-map capabilities, users can visually demonstrate weather events unfolding in specific areas over custom time ranges. This sharpens briefings and communication.

Lightning Alert Improvements

Upgraded lightning features allow risk tracking from any map zoom level. Icons show affected locations, with bolding to highlight active strikes. 

Countdown rings help assess distance of threats.

What’s Next at Tomorrow.io? 

We’re thrilled to showcase the latest enhancements and features at Tomorrow.io, designed to help businesses stay ahead of the ever-changing weather conditions. 

This wide-ranging product launch demonstrates Tomorrow.io’s commitment to continuously advancing weather intelligence for businesses. 

Interested in how these features make a difference?

See Weather Intelligence in Action

The post What’s New At Tomorrow.io? Product Updates Summer 2023 appeared first on Tomorrow.io.

This release will enable delivering predictive alerts and insights end-to-end for drivers and fleets from the Tomorrow.io platform. By getting your weather warnings out to the drivers in advance of impact is the best way to prevent weather related accidents. Operationally speaking, you can vastly improve your efficiency by using these custom workflows to centralize how your organization predicts weather from a single source of truth, proactively responds based on standardized protocols, and streamlines communication including task acknowledgment and an activity log to act as your source of record.

Let’s get into more of the highlights of this release!

The post Driver Alerts for Fleet Solutions Now Live appeared first on Tomorrow.io.

La meteorología impacta industrias, lugares, operaciones y más.

Algunas industrias, como la minería y la aviación en Latinoamérica, están aún más expuestas a estos fenómenos.

Mónica Leal, Directora de Latinoamérica de Tomorrow.io, se sentó con María Paula Duque, Directora de Sostenibilidad de Microsoft Latinoamérica, para discutir la importancia de una inteligencia meteorológica precisa y accionable.

The post Tomorrow.io on Microsoft LATAM Podcast: How Weather Technology can Improve your Business appeared first on Tomorrow.io.

Here’s what to expect and how to prepare your operations in key locations directly in the storm’s path:

Baja California

• From August 18-19, Baja California will see dry weather with wind speeds increasing from 8 to 20 kph. 
• Starting August 19, rainfall will significantly increase, peaking at 6 mm/hr on August 20. 
• Wind speeds will also peak at 64 kph on August 20 before decreasing.

Los Angeles

• Los Angeles can expect dry weather until August 20. 
• From August 20-24, heavy rainfall is expected, with peak intensity of 14 mm/hr on August 21. 
• Wind speeds will reach up to 21 kph during this time. 

San Francisco

• San Francisco will see dry weather until August 19, followed by light rainfall from August 19-24 peaking at 2 mm/hr on August 20. 
• Wind speeds will reach 10 kph. 

Preparing for High-Impact Weather: Gale’s Suggestions for Hurricane Hillary 

Regardless of your industry, businesses should prepare for incoming high winds and rainfall by:

• Securing any outdoor equipment or materials that could be affected by high winds or heavy rainfall.
• Reviewing your business continuity plan for severe weather events, ensuring that all team members are aware of their roles and responsibilities.
• Considering flexible work arrangements for your team during this period, such as remote work options, to minimize travel during heavy rainfall and high winds.
• Ensuring that your premises are well-maintained and prepared for heavy rainfall, checking for any potential leaks or drainage issues.
• Staying updated with the latest weather forecasts and warnings to make timely decisions.

Enhance Preparedness with Tomorrow.io’s Tropical Cyclone Data

Tomorrow.io’s Tropical Cyclone Data Layer enables businesses to visualize official cyclone forecasts, monitor tracks and cones of uncertainty, and access predictive insights for winds, rain, and flooding. Our recently enhanced product provides advanced wind analytics for superior storm preparedness.

With this enhanced data, organizations can review four separate cyclone-specific data layers and three additional advanced graphical layers including: 

• Forecast Track
• Cone of Uncertainty
• Watched and Warning
• Observed Track
• Wind Probability (34 knots and 64 knots): The tropical cyclone surface wind speed probabilities layers provide probabilities, in percent, of sustained wind speeds equal to or exceeding 34-, and 64-knot wind speed thresholds.
• 5-day Wind Swath: The wind swath conveys the expected areal coverage of 34 knot, 50 knot, and 64 knot sustained winds (based on the NHC forecast) that are directly produced by the tropical cyclone as it moves along the forecast track.

Don’t let the next hurricane disrupt your operations. Leverage Tomorrow.io’s technology to monitor cyclone threats, gain situational awareness, and proactively prepare your business.

The post How to Leverage Weather AI for Hurricane and Cyclone Preparedness: Hurricane Hillary 2023 appeared first on Tomorrow.io.

Today, with the advent of predictive analytics and automated workflows, organizations are finding new ways to navigate weather challenges and become an integrated business across their operational workflows.  

Tomorrow.io is at the forefront of this transformation. A recent conversation with Dan Slagen, CMO at Tomorrow.io, shed light on how we’re helping businesses in diverse sectors think differently about the weather.

Below are highlights from the interview. Watch the entire conversation below. 

Predictive Analytics: A New Way to Understand Weather

Predictive analytics enables companies to comprehend the specific impact of weather on their operations. Instead of merely following forecasts, organizations can now anticipate and prepare for weather conditions tailored to their specific needs.

“It’s not necessarily about knowing it’s going to be windy; it matters that your train is at risk of being derailed at this time, at this mile marker on this day,” explains Slagen. “Once you have predictive analytics in place, you now have a single source of weather truth where everyone can look.”

Automation: Turning Insights into Action

Understanding the weather’s impact is only half the battle; acting on that information efficiently is equally crucial. Automated workflows provide actionable insights and facilitate communication within an organization, turning weather data into operational decisions.

“With a single source of weather truth, the focus shifts towards deriving actionable insights. Instead of laboriously interpreting what a weather forecast means for each individual, it’s about instantly knowing the precise action to take — be it stopping or speeding up the train. In this way, everything becomes manageable and can be saved, presenting a solution that is not only effective but elegantly simple.”

More Than Just a Forecast: A New Perspective on Weather

Tomorrow.io emphasizes that weather should no longer be a problem that surprises businesses. With predictive analytics and automated workflows, weather can become an operational asset.

“Stop thinking about weather in the traditional way and more think about whether it’s something that can be solved through a workflow and something that can actually become an asset to you from an operational sense,” advises Dan.

Embracing Weather’s Challenges

With companies like Tomorrow.io, weather forecasting is entering a new era. It’s no longer just about predicting rain or shine but about understanding the specific impact on each organization’s unique operations and adapting accordingly.

For executives looking to transform weather from a challenge into an opportunity, now is the time to embrace the future of weather forecasting with predictive analytics and automated workflows. 

Innovation in this space is an essential tool for any business, whether dealing with high winds on the railroad or ensuring timely deliveries in the trucking industry. With the right tools and perspective, weather can be a manageable, even advantageous, part of the business landscape.

The post Solving for Weather with Predictive Analytics and Automated Workflows appeared first on Tomorrow.io.

John Murnane, McKinsey Sr. Partner, Warrick Nance, ConGlobal’s VP of Safety, and Mekala Krishnan, McKinsey Global Institute Partner, shared insights on leveraging data, automating workflows, and implementing proven practices to adapt operations.

Here are key takeaways from the discussion:

Conduct Location-Specific Climate Risk Assessments

As McKinsey’s Mekala Krishnan explained, “It’s important to understand the spatial distribution of climate risks as you make decisions.” Supply chain assets and routes span the globe, with exposure varying greatly by geography. For example, coastal regions face higher flood risks while arid inland areas see more drought.

Krishnan advised building granular, location-based climate risk assessments into long-term planning. This allows tailoring resilience strategies based on vulnerability of physical infrastructure and operations. Modeling tools can quantify likelihood of climate events by site to enable data-driven decision making.

Automate Workflows Based on Weather Triggers

ConGlobal’s Warwick Nance shared how partnering with Tomorrow.io provides weather insights integrated into daily operations, from securing cargo stacks to winterizing equipment. Extremes like severe wind, heat, and cold can damage assets and endanger workers if not planned for.

“It puts us in a position to be able to see what’s coming and then take the appropriate actions. We’ve also adjusted some things just in managing resources. So during the winter months, when we are going to have, uh, below freezing temperatures, we can take steps that now secure the equipment in a much better way.”

Tomorrow.io’s AI assistant Gale, for example, allows teams to rapidly deploy automated response plans based on weather triggers. This prevents business disruption and mitigates safety risks. Built-in workflow automation eliminates reliance on individual awareness of weather conditions.

Blend Structural Resilience With Continuous Monitoring

According to John Murnane of McKinsey, “The modern supply chain is both structurally more resilient, but then much more closely managed.” Supply chains have traditionally optimized for cost over flexibility. Building in redundancy via suppliers, inventory, routes makes systems less brittle.

However, he cautioned this alone is insufficient – constantly monitoring emerging risks via data analytics and indicators enables adaptation. Regular “what-if” scenario exercises prep teams to respond. Murnane advised colliding supply chain leaders with experts in weather, climate, and other risk areas.

Prioritize Workforce Safety

“Resilience is really about safe operations,” said Nance. Weather directly impacts working conditions and hazard exposure. He suggested starting with workforce safety initiatives powered by specialized weather insights like excessive wind, lightning, and extreme heat alerts.

This allows for precautionary protocols to protect employees based on imminent weather-related threats. But safety must pair with operational continuity so customers aren’t impacted. Solutions like Tomorrow.io enable both safety and optimized operations through predictive intelligence.

Combine Data, Visibility, and Ingrained Flexibility

The panelists agreed that resilience requires data-driven risk analysis, supply chain visibility, and systemic flexibility. Advanced weather intelligence solutions like Tomorrow.io’s platform ingrain these capabilities.

The future of resilient supply chains is predictive, automated, and climate-aware.

The post Building Climate Resilience: Key Insights from McKinsey, ConGlobal, and Tomorrow.io appeared first on Tomorrow.io.

From damp roads to puddles and ponding to rapidly rising water that carries vehicles away, inundates buildings and basements, destroys crops, breaks bridges, and tragically drowns people and animals.

The atmospheric setup varies from one flood to the next, but the result is always the same: Too much rain in too little time.

A new study in the journal Nature finds that the global population exposed to floods has significantly increased in recent years. 

“Flooding is a pervasive natural hazard, with new research demonstrating that more than one in five people around the world live in areas directly exposed to 1-in-100 year flood risk. Exposure to such flood risk is particularly concentrated amongst lower-income households worldwide.” 

Tens of millions of people around the world are displaced from their homes each year due to flooding disasters, while damages from flood events run into the hundreds of billions of U.S. dollars in direct asset losses annually. These disasters contribute to the billion-dollar weather events we are seeing every year. 

The effects on communities around the world can be devastating. Still, in order to combat the impact of flooding and mitigate unforeseen disasters, we need to understand what conditions lead to flooding and what tools exist to help us reduce these risks.  

Understanding Flooding and Flood Forecasting: What Atmospheric Conditions Lead to Floods?

Extreme floods are increasing in frequency and intensity worldwide.

But why? To understand, we must understand what conditions lead to floods. 

Flooding Conditions

A combination of the following causes flooding: 

• Prolonged Rainfall: Continuous rain over several days saturates the soil, causing rivers and lakes to overflow
• Rapid Snowmelt: Sudden warming can cause snow and ice to melt quickly, releasing a large amount of water that flows into rivers and streams
• Storm Surges: Hurricanes and strong winds can push seawater onshore, leading to flooding in coastal areas
• Human Factors: Poorly managed drainage systems, dam failures, and urban areas with impenetrable surfaces can also cause or exacerbate flooding.
• Topography: The land’s slope and the soil’s nature can affect how quickly rainwater is absorbed or flows, contributing to flooding.

Flash Flooding Conditions

Flash floods occur due to different conditions compared to typical floods. A combination of the following usually causes them: 

• Intense Rainfall: Flash floods are usually triggered by heavy rainfall in a short period, sometimes within minutes or a few hours. It can be localized or widespread.
• Sudden Snowmelt or Dam Break: A sudden release of a large volume of water due to a dam failure or rapid snowmelt can also cause a flash flood
• Topography: Flash floods often occur in steep, hilly areas where water can gather and flow rapidly. Narrow canyons and valleys can funnel water, increasing its speed and intensity.
• Soil Conditions: Dry or already saturated soil may not absorb water quickly, allowing it to flow across the surface, leading to flash floods
• Storm Drains and Channels: In urban areas, overwhelmed storm drains and channels can lead to sudden localized flooding

Flood Forecasting Around the World

These conditions are becoming more prevalent each year. Here are just a few examples of intense flooding that have occurred in recent years: 

• More than a million people have been displaced and dozens killed due to flooding in northeastern China in July 2023, when remnants of Typhoon Doksuri hit the area, according to CNN. Flooding in the areas stranded residents, washed away bridges and highways, killing a total of thirty people in total. The storm brought the heaviest rainfall Beijing has experienced in 140 years, marking a significant test to the region. 
• Flooding devastated homes for millions of people and killed at least 1,700 in Pakistan in November 2022, according to AP. At one point during these intense floods, nearly 1/3 of the country was underwater. A year later, the country has yet to recover fully. At the height of the crisis, nearly 8 million people were displaced. UNICEF estimates that roughly 20 million people still need humanitarian aid in flood-affected areas. 
• In July 2021, more than 200 deaths in central Europe were blamed on the worst flooding there in decades, with more than six inches in less than 12 hours. For example, the German city of Reifferscheid received 8.1 inches of rain in just nine hours, as reported by CNN, in an area where the average rainfall for all of July is only 3.45 inches. AIR Worldwide estimates insured losses could approach $6 billion

There are several steps people, businesses, and organizations can take to prepare for flooding, including purchasing flood insurance, landscaping to improve drainage, turning off gas and electric services, and clearing debris from gutters, downspouts, sewers, and culverts (like city workers did as flooding developed in Bountiful, Utah, in early August 2021).

Ready.gov provides recommendations on what people should do before, during, and after a flood. In contrast, the Federal Emergency Management Agency provides a playbook with tabletop exercises for how organizations can prepare for a flood.

But you can only prepare for a flood if you know one is coming.

With the increasing threat of and vulnerability of society to flooding, several efforts are underway in both the public and private sectors to mitigate the impacts of flooding through better forecasts, preparation, and communication.

Preparing Against Flooding

As these floods become more prevalent, how can we prepare against flooding and mitigate the risk? 

Flood risk mitigation involves reducing the risk posed to our communities, people, and property. We can do this through flood forecasting and improved operational workflows within businesses. 

Emerging tools like those from Tomorrow.io can support flood risk mitigation by providing accurate and timely flood forecasts. People can use these forecasts to warn people of potential flooding and communicate alerts, so they can take steps to protect themselves and their property. Not only does Tomorrow.io provide forecasts for flood, they, more importantly, provide insights on when to act on those forecasts. By leveraging better forecasts, insights on when to act, and improved communication methods through early warning systems, we can work toward improving flood forecasting and mitigation. 

How Can We Improve Flood Forecasting?

National Water Model

The National Oceanic and Atmospheric Administration’s National Water Model, which became operational in 2016, simulates observed and forecast streamflow over the entire continental United States. The model complements National Weather Service river forecasts at approximately 4,000 locations and expands water forecasts to 2.7 million streamflow locations where traditional river forecasts did not previously exist.

The model has demonstrated incremental improvements in flood forecasts, including the catastrophic flooding in Ellicott City, Maryland, 2018. Further improvements are expected when the next-generation National Water Model becomes operational, which is currently planned for 2024.

NOAA’s Precipitation Prediction Grand Challenge (PPGC)

In 2022, the world experienced 18 billion-dollar weather disasters totaling $165 billion. The costliest of these disasters being Hurricane Ian costing taxpayers roughly $112 billion to recover from.

Since 1980, the United States has sustained 341 weather and climate disasters, with overall damages reaching or exceeding $1 billion. 2023 is now the seventh consecutive year with ten or more billion-dollar weather and climate disasters in the United States — so far, we have seen 13 in 2023 alone.

NOAA’s Precipitation Prediction Grand Challenge (PPGC) recognizes that “a key to reducing these impacts is to be able to anticipate when, where and how much precipitation will fall” and notes that “although temperature forecasts have generally improved dramatically over the last few decades, precipitation forecasts (at all timescales) have not. “

Through an integrated research-to-operations effort, the PPGC aims to increase the rate of improvement in precipitation forecasts from 15% per decade to 30% per decade in five years and from 30 percent per decade to 50 percent per decade in 10 years. The PPGC will inform and support the activities of NOAA’s Earth Prediction Innovation Center (EPIC), a program established to advance weather modeling by facilitating a community-development approach and will also align with NOAA’s Artificial Intelligence Strategy and Cloud Strategy.

How is FEMA Changing Flood Insurance With Risk Rating 2.0?

Most residential and commercial property insurance policies don’t cover damage from flooding. Homeowners and businesses wanting to protect themselves from the financial risk of flooding must purchase a separate policy through insurance companies or agents. The vast majority of flood policies in the United States—more than five million—are provided through the National Flood Insurance Program (NFIP), which is managed by the Federal Emergency Management Agency (FEMA). NFIP rates are currently determined by an outdated methodology that results in “policyholders with lower-valued homes paying more than their share of the risk while policyholders with higher-valued homes are paying less than their share of the risk,” according to FEMA.

Starting in October, FEMA will introduce a new pricing methodology called Risk Rating 2.0, which FEMA calls “a transformational leap forward” to ensure rates are more fair and equitable. Risk Rating 2.0 will incorporate more factors into determining the cost of flood insurance for a given property—including flood frequency, multiple flood types (river overflow, storm surge, coastal erosion, and heavy rainfall), distance to a water source, property elevation, and the cost to rebuild—such that rates will more accurately reflect the flood risk specific to the insured property.

The Future of Flooding with Weather Intelligence

At Tomorrow.io, we are supporting or directly partnering with the above efforts to improve forecasts of and preparation for floods:

• Weather intelligence does far more than a typical weather forecast. It puts the forecast in context for your specific business or operations. Tomorrow.io’s Weather Intelligence Platform can monitor many locations at once for any combination of weather conditions that impact the operations of a business or organization. For example, a shipping and logistics company can get alerted when and where to reroute trucks due to predicted flooding. The platform can be tailored to drive decisive actions for virtually any industry.
• Tomorrow.io has launched a new flood index to help businesses and organizations identify areas at risk for minor, moderate, significant, major, and catastrophic flooding up to five days in advance, even in areas without many hydrologic observations. The index, which accurately predicted flooding in Europe and China during a pre-launch verification analysis in 2021, is calculated using a mix of publicly available and proprietary hydrologic models, including NOAA’s National Water Model, as well as 40 years of historical analysis of runoff and streamflow.
• To make our flood index and all of our forecasts and alerts even more accurate in the future, Tomorrow.io has successfully launched the world’s first commercially built weather-radar satellites. Tomorrow-R1 and Tomorrow-R2 are now orbiting 500 km above Earth in polar orbit carrying a Ka-band radar suited for detecting precipitation and critical ocean parameters. This successful launch marks the start of a constellation that will pave the way for groundbreaking advancements in global weather forecasting and flood forecasting. The operational constellation of approximately 20 satellites will, for the first time, provide global, high-resolution measurements of precipitation updated every hour, improving weather forecasts, especially for floods and hurricanes, and enabling reliable weather forecasts for the 5 billion people worldwide who currently live outside of traditional ground-based radar coverage.

There is much to be done to advance flood forecasting, and Tomorrow.io is at the forefront of the transformation by partnering with organizations like NOAA: The National Oceanic and Atmospheric Administration and NASA to bring better forecasting data to the world. 

Need to better understand the risk of flooding?

The post The Future of Flood Forecasting appeared first on Tomorrow.io.

Climate AI is an innovative and powerful tool designed to assist organizations in adapting to the impacts of climate change. Unlike solutions focusing solely on mitigating carbon emissions or preventing the climate crisis, Climate AI helps to address the urgent need to prepare for and adjust to the ever-increasing occurrences of extreme and high-impact weather events, rising temperatures, and other climate challenges.

By harnessing the capabilities of artificial intelligence and machine learning, climate AI is an adaptation tool that provides valuable insights and predictions on the potential impacts of climate change and immediate extreme weather. This adaptation capability enables decision-makers in both public and private sectors to understand and respond to the environmental impact of their actions, identify vulnerabilities in their operations, and develop strategies to build climate resilience.

What is Climate AI?

Climate AI is an innovative approach that leverages artificial intelligence to analyze and interpret vast amounts of climate data, enhancing the prediction and management of hazardous weather events.

Together with weather AI technologies, like Tomorrow.io’s Gale, the world’s first application of weather and climate-generative AI, climate AI provides a seamless interface for businesses and organizations to forecast weather patterns, enabling them to proactively implement mitigation strategies. Instead of merely reacting to weather changes, climate AI empowers decision-makers to anticipate and adapt to climate-related risks, driving sustainability and efficiency in operations. With climate AI’s data-driven insights, organizations can now align their practices with environmental concerns, transforming their approach to weather and unlocking new opportunities in the era of climate change.

AI, Weather Forecasting, and the Climate Crisis

Weather vs Climate: What’s the Difference?

To fully grasp the magnitude of this problem, we need to make a notable distinction between ‘weather’ and ‘climate.’ Although often used interchangeably, they are not synonymous.

‘Weather’ refers to atmospheric conditions over short periods—think rain or sunshine—while ‘climate’ describes long-term patterns within specific regions or across the globe.
Climate involves accumulated weather statistics measured over extended periods, such as average rainfall or temperature changes year after year. 

The Use of AI in Weather Forecasting

Harnessing AI for weather forecasting purposes has experienced rapid growth thanks to technological advancements. Rather than relying solely on traditional methods to predict local conditions, meteorologists now resort to machine learning algorithms that facilitate real-time analysis of large-scale atmospheric datasets.
The utilization of AI innovations allows improved prediction accuracy matched with speed—an important factor when it comes to early warning systems where every minute counts. Consequently, AI’s influence has revolutionized how we interact with our environment, from day-to-day planning all the way to disaster management strategies.

Technologies Used in Weather AI

To combat the impending effects of climate change, we need better tools to predict adverse weather events and insights into how to operationally prepare for the impact. Tools like Tomorrow.io’s weather and climate adaptation software leverage a combination of technology that provides weather information to various sectors. 

Predictive Modeling

Tomorrow.io’s predictive models form the backbone of our services. These models convert raw meteorological data into valuable, actionable insights. The result? Organizations around the world looking to adapt to weather changes can strategize proactively around potential high-impact weather conditions. 

AI & Space Technology

With AI/ML algorithms, cutting-edge sensor technology, and upcoming satellite data, Tomorrow.io provides precise hyper-local forecasts and insights for a variety of industries.  

Tomorrow.io’s predictive models transform raw weather data into actionable insights for strategizing around impending weather disruptions. These insights offer a superior forecasting solution and enable businesses to plan effectively against severe weather conditions — from incoming storms that will lead to flooding to the intense heat that causes heat domes around the world. 

Tomorrow.io’s Satellite Constellation

Tomorrow.io launched proprietary weather radar satellites, Tomorrow-R1 and Tomorrow-R2, into Earth’s orbit, heralding a transformative age in global weather forecasting.

Underpinned by generative weather and climate AI, these satellites constitute a constellation that will allow for near-real-time monitoring of precipitation and atmospheric conditions – a transformative leap providing a significantly more accurate and timely weather forecast to those who need it most. 

Weather AI: Gale from Tomorrow.io 

Gale, the world’s first AI-driven weather and climate chat, enhances Tomorrow.io’s capabilities in weather AI and climate AI. Gale provides more than just weather information; it crafts a conversation where users can interact, ask questions, and receive personalized weather insights for their specific organizational or operational needs.

With Gale, people, businesses, and governments can operationalize around weather, mitigate the impact of hazardous conditions, and leverage new weather data in their forecasts. 

Join the Gale Waitlist to Experience the Power of Weather AI for Yourself

How Can We Leverage AI Tools for Climate Adaptation?

AI is a critical ally in combatting climate change, providing essential tools to foster global resilience and adaptation. Machine learning models analyze complex weather patterns and predict extreme events like hurricanes and floods, enhancing preparedness.

Using AI tools for climate adaptation can look like leveraging AI-based early warning systems (EWS) that leverage weather intelligence to identify environmental hazards and send out timely alerts. These systems bolster community defenses, facilitating efficient evacuation and resource strategies. One area that AI can also support is resilient agricultural practices, providing farmers with vital information on weather changes, crop selection, and harvesting times, thus promoting sustainable farming.

Tomorrow.io plays a key role in climate adaptation, creating high-resolution models predicting localized weather with incredible accuracy. More than mere predictions, Tomorrow.io’s weather intelligence transforms insights into actionable guidance. By delivering real-time alerts about adverse weather events, stakeholders can take effective preventive actions.

This AI approach offers substantial value, especially to developing nations that often lack access to advanced weather forecasting technologies. Today, nearly 70% of the world lacks radar coverage. This means that nearly 2/3 of the world does not have accurate weather forecasting to help them prepare.

AI tools enable better preparedness against natural disasters,  which benefits us all. 

What are the Benefits of Climate AI For Businesses?

The benefits of Climate AI are many, including improved risk mitigation, the ability to implement easy-lift early warning systems, cost savings around weather, and overall climate resilience. By combining the forces of ML models with AI-backed industry-specific insights on how to operate around the forecast, organizations have a leg up against high-impact weather. Below are a few examples highlighting existing uses of AI and weather intelligence. 

Risk Mitigation: Early Warning Systems for Community and Business Impact

Climate crisis increases the frequency and intensity of catastrophic events like hurricanes, wildfires, and floods. To ensure community safety and maintain business continuity amidst these adversities, early warning systems are critical.

And climate AI can support these initiatives.

Advanced algorithms can analyze vast amounts of climate data from global sources in real time, predicting potentially harmful weather much faster than traditional methods. Because these systems are built with machine learning techniques, they learn from each event, consistently improving accuracy over time.

Enhanced accuracy translates to more effective disaster prevention strategies, helping communities and businesses prepare better for extreme weather events. An improved EWS can save lives and save on the costs of resolving weather impacts. 

Cost Savings: Leveraging AI for Optimized Operations

In addition to improving safety measures, climate AI offers financial advantages against weather’s impact. With accurate predictions, industries can orchestrate their operations more efficiently, leading to significant cost savings.

For example, think of a major airline; using precise forecasts that provide information on wind patterns or ground temperature data across flight paths can save substantially on fuel costs and optimize crew schedules resulting in increased efficiency and profitability.

Tomorrow.io already supports businesses like JetBlue to help them save money on canceled and delayed flights. Steve Olson, Vice President, System Operations at JetBlue, says, “The rate in which we have canceled flights, the rate in which we’ve delayed flights associated with weather has improved remarkably just in one year’s time frame. [Tomorrow.io] is already saving [JetBlue] $300,000 every month, $3.7 million in a year.”

Enhancing Climate Resilience: AI for Agriculture Predictions

Agriculture, an industry that’s highly susceptible to climatic variations, has started to embrace modern technologies, including AI innovations. These innovations aim to minimize risks associated with shifting climate patterns while simultaneously boosting yield production.

With the aid of artificial intelligence and machine learning, predictive models can now precisely forecast rainfall patterns or potential pest infestations well in advance. This foresight drastically enhances crop resilience and allows farmers to adapt their strategies accordingly, ensuring food security even under challenging environmental conditions.

Tomorrow.io is equipped to support the agriculture industry and is already doing so through a partnership with TomorrowNow.org. In 2020, Tomorrow.io was positioned to solve a significant locust problem in East Africa by:

1. Identifying areas where locusts were repopulating and stopping them by spraying pesticides with drones
2. Knowing where existing swarms were raveling next
3. Warning communities in advance so they can harvest their crops and protect food supplies

The combination of weather intelligence and AI goes beyond merely advancing risk mitigation and cost-saving objectives. It also fosters a resilient and adaptable society, more capable of combating environmental unpredictability both effectively and efficiently.

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How Can Different Industries Use Climate AI?

Different industries can use climate AI and weather intelligence to optimize their emergency preparedness, improve early warning systems, and optimize their operations and decision-making processes around high-impact weather. 

Using Tomorrow.io’s weather and climate adaptation platform, organizations around the world can address the challenge of combating and adapting to climate change. 

Climate AI for Construction

The construction industry is especially susceptible to climate change and must integrate new technology to adapt. Extreme weather events like hurricanes, floods, and soaring temperatures, and their increasing severity, pose significant risks to both ongoing projects and existing structures.

With an AI-backed climate adaptation strategy, the construction industry will benefit from: 

• Risk Prediction: By analyzing long-term trends and real-time data, climate AI tools can forecast adverse weather conditions. These early warning systems allow construction managers to adjust schedules or take precautionary measures to ensure worker safety and avoid costly damages.
• Resilient Building Design: Climate AI can help support better building designs in specific locations that are more at risk of hazardous weather
• Efficiency Optimization: Weather significantly impacts construction efficiency – think halted work during rains or lowered productivity due to severe heatwaves. Knowledge derived from AI aids in adopting flexible scheduling methods minimizing delays imposed by unfriendly weather patterns.

Climate AI for Aviation

The aviation industry is in the midst of extraordinary digital transformation. An integral part of this shift owes its credit to the rapid evolution of AI tools. 

• Improved Flight Planning: By leveraging large historical and real-time meteorological data sets alongside machine learning models, AI can support the intricacies of flight planning. AI can inform flight routes with predictions on wind speed/direction trends and atmospheric pressure gradients, which contribute significantly to optimizing fuel consumption.
• Optimized De-Icing Procedures: Weather intelligence provides insights to ground crews on optimal times to de-ice a plane, improving ground operations and getting planes moving in a timely manner
• Reduced Cancellations and Delays: With AI tools, airlines like JetBlue see a reduction in cancellations and delays around the weather; climate AI can help combat such situations. 

Climate AI for Logistics and Transportation

The logistics and transportation sector is a critical component of global commerce, but it also stands as one of the sectors most vulnerable to climate change disruptions. By employing AI for climate resilience in this industry, we can foster an environment where operations continue smoothly despite weather impediments.

• Global Commerce Stability: The logistics and transportation sector is vital for global commerce but vulnerable to climate disruptions. Climate AI ensures smooth operations despite weather impediments.
• Predictive Analytics: Advancements in AI introduce predictive analytics to transportation, allowing companies to gain insights from past weather data and prepare for future conditions.
• Route Optimization: Climate AI systems can present likely routes and strategies based on current and forecasted weather and traffic data, allowing businesses to adjust routing or delivery schedules for storms or temperature spikes.

Climate AI for Energy and Utilities

Climate AI integration into the energy and utilities sector is noteworthy, exhibiting promising potential to boost both efficacy and resilience. With climate change artificial intelligence in place, we’re observing a decisive move towards ensuring the robustness of these essential services regardless of existing weather extremities.

• Boosting Efficacy and Resilience: Climate AI integration into energy and utilities demonstrates the potential for increasing efficiency and resilience, ensuring robustness even in extreme weather conditions.
• Predicting Power Outages: AI innovations, including Machine Learning algorithms, can predict power outages based on historical data and weather forecasts, allowing utility providers to strategically deploy resources to optimize response and recovery efforts.
• Renewable Energy Management:
  • Weather-dependent sources such as solar or wind power require adaptive management based on prevailing climatic conditions.
  • Climate AI can forecast such variabilities with remarkable accuracy.
  • This enables dynamic adjustments to power grids, reducing reliance on fossil fuels.

Climate AI for Agriculture

Farmers worldwide face the daunting challenge of adapting to unpredictable weather patterns exacerbated by climate change. With such weather hazards becoming more volatile, more frequent, and more severe, climate AI is the solution the agriculture industry needs most. 

• Optimizing Crop Yields and Resource Management:
  • AI-powered predictive analytics tools leverage climatic data to present accurate forecasts.
  • Climate AI predicts rain patterns and other weather conditions, aiding in smart irrigation planning and effective resource allocation.
• Mitigating Risks from Extreme Weather:
  • Climate Change AI uses specialized algorithms to predict heatwaves or frost likelihoods.
  • These insights enable farmers to take precautionary measures, reducing crop loss.
• Disease Detection and Pest Control:
  • Machine learning within Climate AI analyzes image data for early detection of plant diseases or pest infestations.
  • Sophisticated models identify signs often before they’re visible to the human eye.

Conclusion: The Future of AI and Climate

Navigating the wild world of climate change is no small task, but AI is stepping up in this global challenge. From predicting weather patterns to saving money in various industries, AI will better prepare us for climate adaptation as the world’s weather gets hotter, colder, and wetter. 

As climate AI technology continues to evolve, we can expect more advanced capabilities and improved integrations for AI in all sectors. With ML modeling improvements, we will have access to better weather forecasts that, when combined with historical weather data, will inform our decision-making and improve operations everywhere. 

By partnering with innovative providers like Tomorrow.io and investing in weather AI, businesses can stay ahead of the curve, optimize operations, manage risks, and seize new opportunities in the face of an uncertain climate future.

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The post Climate AI: How New Tech Will Influence Global Climate Adaptation Resilience appeared first on Tomorrow.io.