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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2002

Hurricane Bud's Rainfall Measured with GPM IMERG

Beneficial rainfall from hurricane Bud's remnants has spread into the Desert Southwest. This rainfall may be helpful in an area that has been experiencing exceptional drought accompanied by wildfires. Bud's rainfall may also signal the beginning of the summer monsoon over the Desert Southwest. The image above shows estimates of accumulated rainfall using IMERG (Integrated Multi-satellitE Retrievals for GPM) data generated during the period from June 9-18, 2018. This rainfall occurred during the period when Bud formed southwest of Mexico, intensified into a powerful category four hurricane

GPM Flies Over Hurricane Bud off the Coast of Mexico

View full-screen in STORM Event Viewer The GPM core observatory satellite passed above hurricane BUD in the eastern Pacific Ocean on June 12, 2018 at 5:27 PM MDT (2327 UTC). BUD's movement over colder waters had caused it's eye to become less defined. Data collected by GPM's Microwave Imager (GMI) showed that moderate to heavy precipitation was only present in the southeastern quadrant of the weakening hurricane. GPM's GMI also indicated that the heaviest rainfall in the area, of over 78 mm (3.1 inches) per hour, was occurring near Mexico's coastline well to the northeast of BUD's center of

GPM Radar Views Powerful Convective Storms over Saudi Arabia

V iew full-screen in STORM Event Viewer Saudi Arabia is not thought of as a region rife with intense thunderstorms, but its southwestern region features an abrupt orographic incline from the Red Sea coast toward the interior. Here, warm moist air can be forceably lifted up the slope of the Sarawat Mountains resulting in torrential downpours and flash flooding. In this overflight, we see an occasion of this, with DPR cloud top heights up to 20km and 89 GHz brightness temperatures near 55K, suggesting the likelihood of hail within the deep convective plume.

GPM Probes Tropical Storm Maliksi

The GPM core observatory satellite had an excellent view of tropical storm MALIKSI when it passed over southern Japan on June 10, 2018 at 1759 UTC. GPM's Microwave Imager (GMI) and Dual Frequency Precipitation Radar (DPR) instruments collected data that revealed the horizontal and vertical extent of precipitation within the tropical storm. GPM's GMI showed that heavy downpours were occurring in a rain band wrapping around MALIKSI's northeastern side. GPM's radar (DPR Ku Band) found that bands of storms moving around the northwestern side of the tropical storm were dropping rain at a rate of

GPM Flies Over Intensifying Hurricane Aletta

As expected, tropical storm Aletta intensified and became a hurricane. Aletta was a powerful hurricane with winds of about 85 kts (98 mph) when the GPM core observatory satellite passed over head on June 7, 2018 at 18:38 PM MDT (June 8, 2018 at 0038 UTC). GPM's Microwave Imager (GMI) and Dual Frequency Precipitation Radar (DPR) instruments showed that hurricane Aletta contained powerful storms that were producing heavy precipitation. Very strong convective storms were producing heavy rainfall in Aletta's eye wall while the most extreme downpours were shown in a large feeder band wrapping

Through rain and snow, hurricane, typhoon and monsoon, flash flood and bomb cyclone, for ten years, the joint NASA-JAXA Global Precipitation Measurement mission has measured a lot of water. GPM’s Core Observatory satellite launched from Tanegashima Space Center in Japan in early 2014, becoming the first satellite to be able to see through the clouds and measure liquid and frozen precipitation from the Equator to polar regions using a radar. Now in its tenth year of operation, we look at ten events brought to light by this groundbreaking mission. Credits: NASA's Goddard Space Flight Center

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.

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