GPM Applications Banner: Disasters

Using GPM Data for Disasters and Risk Management

Too much or too little rainfall can have significant impacts on populations around the world. As population and global temperatures increase, it is crucial to understand what locations will become more vulnerable to extreme rainfall and drought and the subsequent natural hazards (e.g., landslides) and risks (e.g., lose of property) they impose. Satellites allow us to monitor changes in the precipitation, especially over oceans and regions where ground-based data are sparse. With its near-real-time precipitation estimates and near global coverage, GPM serves as an essential tool for assessing risk and planning disaster response and recovery.  For example, near-real-time precipitation data from GPM are used within various models to help monitor and predict the path and intensity of tropical storms, vegetation fire starting and spreading, and landslide activity across the globe. The Disasters and Risk Management applications area seeks to use the GPM precipitation satellite data to improve forecasting, preparation, response, recovery, mitigation and insurance of natural hazards including tropical cyclones, floods, droughts, wildfires, landslides, and other extreme weather events.

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GPM Data for Decision Making

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GPM's GMI / DPR provides views of hurricane Lane’s precipitation, showing intense storms near the center on August 19, 2018. Credit: Hal Pierce (SSAI/NASA GSFC).

 

The GPM Mission provides insight into how and why some tropical cyclones intensify and others weaken as they move from tropical to mid-latitude systems. The GPM Core Observatory’s GMI and DPR instruments allow scientists to study the internal structure of storms throughout their life cycle, and view how they change over time. Specifically, the GMI has the capability to measure the amount, size, intensity, and type of precipitation, from heavy-to moderate rain to light rain and snowfall. The DPR returns three-dimensional profiles and intensities of liquid and solid precipitation, revealing the internal structure of storms within and below clouds. Scientists use these instruments to track tropical cyclones and forecast their progression and to verify their tropical cyclone computer models. They also use instrument data to understand the distribution and movement of latent heat throughout the storm, particularly in the development of hot towers in the wall of clouds around the eye, which have been linked to rapid intensification. Together, these instruments will improve hurricane tracking and forecasts, which can help decision makers save lives.

View tropical cyclones articles

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Submerged Houston neighborhoods in the wake of Tropical Storm Harvey on August 29, 2017. Credit: Marcus Yam / Getty Images

To better understand and predict floods scientists have developed hydrological models based on how much rainfall occurs and where the water will likely go once it hits the ground. They use several satellite precipitation datasets within these models to provide near real-time estimates of when and where areas may flood on local, regional, and global scales. GPM provides frequent precipitation observations with near global coverage, of which 80% are less than 3 hours apart, exceeding the minimum deemed necessary for hydrometeorological applications. Therefore, rainfall data measured by the GPM Mission and its products, like the Integrated Multi-satellitE Retrievals for GPM (IMERG) data product, helps us better understand how changing precipitation patterns at multiple scales translates changes into hydrologic fluxes and states that can be used for flood detection and warning systems.

View floods articles

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Aerial view of landslide that buried Colonia las Colinas, El Salvador. Credit: USGS

Landslides are one of the most pervasive hazards in the world, resulting in more fatalities and economic damage than is generally recognized. Saturating the soil on vulnerable slopes, intense and prolonged rainfall is the most frequent landslide trigger, but seismicity, river undercutting, freeze-thaw processes, and human activity can also cause extensive and devastating landslides. Understanding where and when landslides have occurred in the past and where they may occur in the future is extremely challenging because of the lack of ground-based sensors at the landslide site to provide both triggering information (e.g. rainfall intensity and duration), and the timing and extent of the mass movement events. Precipitation measurements from remote sensing allows us to gain new insight to identify landslide activity, characterize the triggering patterns of these events spatially and temporally, assess the surface conditions for potential activity, and support the full cycle of disaster risk assessment. In particular, GPM’s more frequent and more detailed coverage of precipitation across the globe can help improve landslide model accuracy and expand potential landslide forecasting capabilities.

Learn more about GPM applications for landslides

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High severity fire in the western U.S. Credit: USDA Forest Service

Wildfires play an integral role in maintaining ecosystem biodiversity and structure.  Wildfires, which include any non-structure fire that occurs in vegetation or natural fuels, is an essential process that connects terrestrial systems to the atmosphere and climate.  However, the effects of fire can be disastrous, both immediately (e.g., poor air quality, loss of life and property) and through post-fire impacts (floods, debris flows/landslides, poor water quality). Wildfires can be triggered by several factors including lightning, high winds, drought, and people. 

There are several ongoing activities using remote sensing data to support pre-, active- and post-fire research, as well as the applicable use of these data and products in support of management decisions and strategies, policy planning and in setting rules and regulations. Frequent precipitation measurements from GPM along with temperature and land cover measurements from other satellites can provide key information to determine the overall dryness of an area and the potential start and spread of a vegetation fire. 

View wildfires articles
 

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GPM's GMI and DPR observe rainfall accumulation over the storm and 3-D vertical structure in a line of intense storms associated with the mesoscale convection system over northern New Mexico and Oklahoma on June 25, 2018. Credit: Hal Pierce (SSAI/NASA GSFC)

 

Many regions in the world experience severe weather such as thunderstorms, hail, tornadoes, and blizzards every year. Severe weather usually comes with heavy precipitation and causes unexpected hydrometeorological hazards, such as floods or landslides, which can affect thousands of people, posing a threat on life and property. Therefore, it is critically important to monitor severe weather and estimate heavy precipitation so that the occurrence and intensity of associated hydrometeorological hazards can be well identified, detected, and forecasted. Where ground-based instruments are sparse, remote sensing systems can be especially useful to observe and monitor these extreme events. Microwave sensors used by the GPM Mission allows scientists to map thunderstorm cores to gain insight into storm structures and mesoscale dynamics (e.g. thunderstorms to hurricanes) as well as detect light rain to moderate-to heavy rain and snowfall. Delivery of precipitation data from the GPM Mission is crucial for operational and research organizations to advance precipitation measurement science to improve weather forecasting that can subsequently benefit society for years to come. 

View severe weather articles

 

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Coast Guardsmen use a boat to assist residents during severe flooding around Baton Rouge, LA on August 14, 2016. Credit: Petty Officer 3rd Class Brandon Giles/Coast Guard

Every year, landslides wipe out roads or town, devastating floods put city blocks underwater, or a violent hurricane devastates the coastal communities. Natural hazards, like Hurricane Maria or flooding in Houston, have huge impacts on people around the world. Heavy rains and large storm systems are often significant factors that cause these disasters to have huge economic costs or even kill people. The best defense against natural hazards is accurate and early warning systems. Understanding the timing, location, and intensity of precipitation extremes using GPM data, organizations that handle disaster response and recovery can monitor, assess, and understand the damage or potential damage of a disaster. These efforts help to minimize the impact of a natural disaster as well as effectively coordinate with organizations and the public before, during, after so as many people are safe and needs are met. 

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A house on the Jersey Shore submerged in water in the aftermath of Hurricane Sandy.  Credit: Jim Greenhill via BU Today

The insurance and disaster management industries are closely related; dealing with the risk of natural disaster and managing the events following disasters. Reinsurance companies work to understand the need of its potential customers and the risks to which they may be exposed.  A companies’ success is generally tied to the ability to forecast the probability of natural hazards, including storms, floods, and landslides. Earth Science data and information derived from remote sensing instruments over the last decade have made it more feasible to develop climate records and understand region’s susceptibility to a natural disaster. Such data are then used to design payout triggers when natural hazards occurs. Policyholders are then compensated according to the strength of the measured event against those triggers. Specially, reinsurance companies across the world use rainfall data from GPM to develop rainfall thresholds to design insurance payouts when disasters strike. 

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GPM Monitors New Tropical Storm Niala

The GPM core observatory satellite flew directly above newly formed tropical storm NIALA (06C) on September 25, 2015 at 1451 UTC (4:41 AM HST). Rainfall data were collected by GPM's Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) instruments showing that intense storms just northeast of NIALA's center of circulation were dropping rain at a rate of over 126 mm (4.96 inches) per hour. Another rain band wrapping around NIALA's northeastern side was found to contain rain falling at a rate of over 56 mm (2.2 inches) per hour. 3-D radar reflectivity data collected by GPM's radar

Ida Weakened by Strong Shear in the Atlantic

Tropical Depression Ida has struggled to maintain itself in the Central Atlantic well east of the Leeward Islands where it has been ravaged by strong wind shear. Since forming back on the 18th of September, Ida has not been able to strengthen beyond a moderate tropical storm, reaching a peak intensity of 45 knots (50 mph) early on the morning of the 21st before succumbing to the effects of strong northwesterly winds from an upper-level trough. Since that time, Ida has struggled maintain itself between a depression and a weak tropical storm, while being mired in the Central Atlantic. This most

Meandering Ida's Precipitation Measured By GPM

The GPM core observatory satellite had another good view of meandering tropical storm Ida located in the central Atlantic Ocean on September 24, 2015 at 0756 UTC (3:35 AM EDT). Measurements of precipitation by GPM's Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) instruments showed that Ida still contained a few embedded strong convective thunderstorms that were dropping heavy rainfall. Some rainfall was measured by GPM's Ku Band radar falling at a rate of 122 mm (4.8 inches) per hour. GPM's 3-D radar reflectivity data (DPR Ku band) can be used to reveal the intensity of
https://www.youtube.com/watch?v=8eIwMXnU8IA&feature=youtu.be
A narrated visualization of Typhoon Kilo. Click here for a full transcript. Click here to download this video in high resolution from the NASA Goddard Scientific Visualization Studio. The Global Precipitation Measurement (GPM) mission core satellite provided many views of Tropical Cyclone Kilo over its very long life. GPM is a satellite co-managed by NASA and the Japan Aerospace Exploration Agency that has the ability to analyze rainfall and cloud heights. GPM was able to provide data on Kilo over its 21 day life-span. The GPM core observatory satellite flew over Kilo on August 25, 2015 at...

GPM Sees Powerful Storms Within Tropical Storm Ida

The GPM core observatory satellite found that tropical Storm IDA contained some very powerful convective thunderstorms when the satellite passed over on September 21, 2015 at 0902 UTC (05:02 AM EDT). The satellite passed directly above the most powerful storms within IDA where rain was measured by GPM's Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) instruments. DPR found that some thunderstorms were dropping rain at a rate of over 142 mm (5.6 inches) per hour. GPM's DPR (Ku Band) radar data were used examine the 3-D structure of precipitation within tropical storm IDA

GPM IMERG precipitation rates and totals from Tropical Cyclone Freddy, Feb. 6 - March 12, 2023. Credit: NASA 

Download in high resolution from the NASA Goddard Scientific Visualization Studio

Cameras outside the International Space Station captured dramatic views of Hurricane Zeta at 12:50 pm ET October 28, as it churned 200 miles south-southwest of New Orleans packing winds of 90 miles an hour. Credit: NASA International Space Station

GPM overpass of Tropical Storm Zeta on October 25 at approximately 2:15pm CDT (19:15 UTC). Half-hourly rainfall estimates from NASA’s multi-satellite IMERG dataset are shown in 2D on the ground, while rainfall rates from GPM’s DPR instrument are shown as a 3D point cloud, with liquid precipitation shown in green, yellow and red, and frozen precipitation shown in blue and purple. Credit: NASA Goddard Scientific Visualization Studio

View an interactive 3D visualization of this overpass in STORM Event Viewer

GPM captured Dorian at 10:41 UTC (6:41 am EDT) on the 4th of September when the storm was moving north-northwest parallel to the coast of Florida about 90 miles due east of Daytona Beach.  Three days earlier, Dorian had struck the northern Bahamas as one of the most powerful Category 5 hurricanes on record in the Atlantic with sustained winds of 185 mph.  The powerful storm to ravaged the northern Bahamas for 2 full days.  During this time, Dorian began to weaken due to its interactions with the islands as well as the upwelling of cooler ocean waters from having remained in the same location...

The Global Precipitation Measurement (GPM) Core Observatory captured these images of Hurricane Dorian on September 1st  (21:22 UTC) as the storm was directly over Abaco Island in The Bahamas.  At that time, the storm was a category 5 hurricane with maximum sustained winds of 185 mph (295 km/h) with gusts over 200 mph.

Hurricane Dorian on September 1, 2019 (21:22 UTC) over Abaco Island in The Bahamas

Visualizers: Kel Elkins (lead), Greg Shirah, Alex Kekesi

For more information or to download this public domain video, go to  https://svs.gsfc.nasa.gov/4751#27911

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