GPM Applications: Weather

Using GPM Data for Weather, Climate, and Land Surface Modeling

Using GPM Data for Weather, Climate, and Land Surface Modeling

Variations in rain, snow, and other forms of precipitation are an integral part in everyday weather and long term climate trends. Initialization of short-term weather and long-term climate models with accurate precipitation information enhances their prediction skills and extends their skillful lead times. To get the resolution and temporal coverage to measure precipitation across the globe, we often rely on satellite information. Satellite data can play a fundamental role in our ability to monitor and predict weather systems as well as to forecast future changes to our climate and land surface. Satellite data from GPM’s suite of precipitation products are integrated into numerical weather prediction models that are operated by operational partners to provide and improve the observations from which the forecasts are then generated. Similarly, climate and land surface models use satellite precipitation observations from GPM to describe the conditions that exist today in order to project how conditions may change in the future. The Weather, Climate, and Land Surface Modeling applications area promotes the use of GPM data to help monitor existing weather activity and model future behavior of precipitation patterns and climate.

Overview

Variations in rain, snow, and other forms of precipitation are an integral part in everyday weather and long term climate trends. Initialization of short-term weather and long-term climate models with accurate precipitation information enhances their prediction skills and extends their skillful lead times. To get the resolution and temporal coverage to measure precipitation across the globe, we often rely on satellite information. Satellite data can play a fundamental role in our ability to monitor and predict weather systems as well as to forecast future changes to our climate and land surface. Satellite data from GPM’s suite of precipitation products are integrated into numerical weather prediction models that are operated by operational partners to provide and improve the observations from which the forecasts are then generated. Similarly, climate and land surface models use satellite precipitation observations from GPM to describe the conditions that exist today in order to project how conditions may change in the future. The Weather, Climate, and Land Surface Modeling applications area promotes the use of GPM data to help monitor existing weather activity and model future behavior of precipitation patterns and climate.

Sections

GPM Data for Decision Making

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NOAA’s Climate Prediction Center (CPC) issues extended range outlook maps for 6-10 days in the future. The above figure shows a 6-10 forecast of precipitation probability for the first week of October 2018. This product complements short-range weather forecasts issued by other components of the National Weather Service. Credit: NOAA/NCEP/CPC
 

Numerical weather prediction (NWP) is the use of computer models to predict upcoming weather. Specifically, NWP centers rely on microwave-based satellite rainfall information, such as data retrieved from GPM’s GMI, to improve short- to long-term weather forecasts and correct track forecasts for tropical cyclones. In addition, NWP centers create precipitation products for “nowcasting” weather in the immediate 1-5 hours (e.g. using near-real-time rainfall data from GPM) to meet the needs of a wider user community, including weather forecasters, hydrologists, farmers, numerical modelers, the military and the climate community. Methods for integrating rainfall data are constantly evolving and advancing, and with GPM’s advanced instruments, scientists can influence and enhance their scientific research and benefit socioeconomic activities.

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European Centre for Medium-Range Weather Forecast (ECMWF) Seasonal Forecast of precipitation probability. Percent probability is determined by using the predictive anomaly relative to 24 years of observed precipitation from 1993-2016. Credit: European Centre for Medium-Range Weather Forecast
 

To understand the changing climate and make future climate predictions, scientists need to use sophisticated computer models to recreate Earth’s climate conditions. Understanding current rainfall and snowfall variability, among other climate factors on regional and global scales, helps scientists model future behavior of precipitation patterns and climate. But for a system as complicated as the Earth, the models are only as good as the data provided. Satellite precipitation measurements from GPM and its predecessor TRMM provide global scale observational data sets that are comprehensive and consistent over long time periods, two characteristics scientists need to understand the relationships between different parts of the climate system. Specifically, organizations use GPM and TRMM data as input to verify and validate their seasonal and climate model simulations. The ultimate goal is to be able to predict changes in climate on time scales as short as the next hurricane season and as far into the future as changes that may occur in the coming decades or centuries. 

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Climate change may lead to an increase in temperatures and a decrease in snowpack within the Absaroka Range, found at the eastern edge of Yellowstone National Park. Credit: National Park Service/Neal Herbert
 

Precipitation is the fundamental driver of land surface hydrological processes and a key component of the terrestrial water cycle, which in turn affects the functioning of atmospheric and climate processes. High-resolution modeling of land surface hydrological processes requires detailed rainfall estimates as inputs to improve understanding of the state of the water cycle and impacts on land-surface processes during extreme events. Satellite precipitation data from GPM is integrated into land surface models to study surface features and how they change due to manmade and natural conditions such as urbanization and erosion. The use of GPM precipitation data together with other satellite data including soil moisture within land surface models will improve weather and hydrological prediction, which will help city planners and even decision makers save lives. 

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NASA's IMERG Used To Analyze Tropical Storm Usagi's Rainfall

Usagi strengthened to hurricane intensity as it approached Vietnam from the South China Sea but weakened to tropical storm intensity when coming ashore. Very heavy rainfall and damaging winds accompanied tropical storm Usagi when it hit Vietnam's southern coast. More than 350 mm (14 inches) of rainfall was reported causing widespread flooding around Ho Chi Minh City. NASA's Integrated Multi-satellitE Retrievals for GPM (IMERG) data were used to show estimates of rainfall accumulation produced by Usagi as the tropical cyclone moved across the South China Sea into Southeast Asia. This IMERG

Tropical Cyclone Gaja's Rainfall Measured With IMERG

Tropical cyclone Gaja recently caused the deaths of at least 33 people in the southern India state of Tamil Nadu. Gaja's high wind and heavy rains caused landslides and building collapses. Gaja's maximum sustained winds had reached about 75kts (86 mph) when it hit southern India on Friday November 16, 2018. This meant that Gaja was the equivalent of a category one on the Saffir-Simpson hurricane wind scale. Today another tropical low is also moving over southern India and is expected to produce more heavy rainfall in the same area. NASA's Integrated Multi-satellitE Retrievals for GPM (IMERG)

Italy's Extreme Rainfall Examined With IMERG

During the past week a strong low-pressure system moving through southern Europe battered, drenched and flooded Italy. It caused flooding, landslides and other damage to large areas of the country. The deaths of at least 11 people have been attributed to this stormy weather. High winds knocked down many trees and heavy rainfall from these storms contributed to flooding in large areas of Italy. Venice was inundated when heavy rain fell and a surge of water from the Adriatic Sea was pushed into the city by the storm's very high winds. Data from various satellites, that cover most of the globe

GPM Examines Weaker Tropical Storm Yutu in the South China Sea

Typhoon YUTU (known as Rosita in the Philippines) is now threatening the Philippine Island of Luzon. On October 24, 2018 YUTU devastated the northern Mariana Islands of Tinian and Saipan as a super typhoon. One death has been attributed to the typhoon in the Marianas with many structures including schools and hospitals being destroyed. Typhoon YUTU weakened as it moved toward the Philippines and had maximum sustained winds of about 90 kts (103.5 mph) when the GPM core observatory satellite passed above the Philippine Sea on October 29, 2018 at 0212 UTC. This rainfall analysis was developed
GPM Catches Typhoon Yutu Making Landfall
NASA's GPM Core observatory satellite captured an image of Super Typhoon Yutu when it flew over the powerful storm just as the center was striking the central Northern Mariana Islands north of Guam. Early Thursday, Oct. 25 local time, Super Typhoon Yutu crossed over the U.S. commonwealth of the Northern Mariana Islands. It was the equivalent of a Category 5 hurricane. The National Weather Service in Guam said it was the strongest storm to hit any part of the U.S. this year. Download this video in high resolution from the NASA Goddard Scientific Visualization Studio Download video without...
PMM Article Image
On September 26, the Global Precipitation Measurement (GPM) satellite flew over an extra-tropical cyclone whose center was approaching Norway. The Norwegian weather service reported that this storm brought gale-force winds to parts of Norway's coast and mountains (20 m/s in the mountains and 50 m/s just off-coast, late at night on September 26). Extra-tropical cyclones this strong or stronger are a regular feature of northern European winters. The particularly damaging ones are called "windstorms." Borrowing a page from hurricane forecasters, some weather agencies in affected countries name...
GPM Captures Hurricane Odile
​ ​ Animation revealing a swath of GPM/GMI precipitation rates over Hurricane Odile. The camera then moves down closer to the Hurricane to reveal DPR's volumetric view of Odile. As the camera rotates around the Hurricane, a slicing plane dissects Odile revealing it's inner precipitation rates closer to the eye. Shades of blue indicate frozen precipitation (in the upper atmosphere). Shades of green to red are liquid precipitation which extend down to the ground. On September 15, 2014 (15:11 UTC) the Global Precipitation Measurement (GPM) mission's Core Observatory flew over Hurricane Odile as...
GPM Satellite Sees First Atlantic Hurricane
Animation of NASA-JAXA's GPM satellite data of rain rates and internal structure of Hurricane Arthur on July 3 2014. Image Credit: NASA's Scientific Visualization Studio / JAXA Download the Hi-Res Video Here The Global Precipitation Measurement (GPM) Core Observatory flew over Hurricane Arthur five times between July 1 and July 5, 2014. Arthur is the first tropical cyclone of the 2014 Atlantic hurricane season. GPM is a joint mission between NASA and the Japan Aerospace Exploration Agency. The Core Observatory was launched Feb. 27 from Japan and began its prime mission on May 29, just in time...

The most detailed view of our daily weather has been created using NASA's newest extended precipitation record known as the Integrated Multi-satellitE Retrievals for GPM, or IMERG analysis. The IMERG analysis combines almost 20 years of rain and snow data from the Tropical Rainfall Measuring Mission (TRMM) and the joint NASA-JAXA Global Precipitation Measurement mission (GPM). The daily cycle of weather, also known as the diurnal cycle, shapes how and when our weather develops and is fundamental to regulating our climate.

Music Credits: "Battle For Our Future" and "Wonderful Orbit" by Tom...

NASA engineer Manuel Vega can see one of the Olympic ski jump towers from the rooftop of the South Korean weather office where he is stationed. Vega is not watching skiers take flight, preparing for the 2018 PyeongChang Winter Olympics and Paralympic games. Instead, he’s inspecting the SUV-sized radar beside him. The instrument is one 11 NASA instruments specially transported to the Olympics to measure the quantity and type of snow falling on the slopes, tracks and halfpipes. NASA will make these observations as one of 20 agencies from eleven countries in the Republic of Korea as participants...

NASA researchers now can use a combination of satellite observations to re-create multi-dimensional pictures of hurricanes and other major storms in order to study complex atmospheric interactions. In this video, they applied those techniques to Hurricane Matthew. When it occurred in the fall of 2016, Matthew was the first Category 5 Atlantic hurricane in almost ten years. Its torrential rains and winds caused significant damage and loss of life as it coursed through the Caribbean and up along the southern U.S. coast. 

Music: "Buoys," Donn Wilkerson, Killer Tracks; "Late Night Drive," Donn...

NASA scientists can measure the size and shape distribution of snow particles, layer by layer, in a storm. The Global Precipitation Measurement mission is an international satellite project that provides next-generation observations of rain and snow worldwide every three hours.

The Global Precipitation Measurement (GPM) Core Satellite captured a 3-D image of a winter storm on February 17, 2015, that left six to 12 inches of snow over much of Kentucky, southwestern West Virginia, and northwestern North Carolina. The shades of blue in the 3-D image indicate rates of snowfall with more intense snowfall shown in darker blue. Underneath where it melts into rain, the most intense rainfall is shown in red. You can see a lot of variation in precipitation types over the southeastern portion of the United States.

The GPM Core Observatory carries two instruments that show the...

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