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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GPM Views Super Typhoon Jebi Twice

UPDATE 8/31/18 View Fullscreen in STORM Event Viewer Having peaked in intensity, Typhoon Jebi is a Category 5 Super Typhoon with maximum winds estimated around 142 knots. It is beginning an eyewall replacement cycle with a gap between the outer and inner eyewalls appearing somewhat in the DPR. The storm's strength is expected to fluctuate but remain well above Category 3 for the next two days before it turns northward toward Japan. It will likely have widespread impacts on Southern Honshu in around 4 days time, an area that has already struggled with rainfall, typhoons, and intense heat this

GPM Sees Tropical Cyclone Jebi Threaten Japan

Japan has been afflicted by several tropical cyclones and other extreme weather this summer. The Joint Typhoon Warning Center (JTWC) predicts that yet another typhoon called JEBI will be approaching the main islands of Japan early next week. Warm ocean temperatures and low vertical wind shear are providing a favorable environment for JEBI's intensification. The JTWC predicts that the typhoon will have peak sustained winds of 115 kts (132 mph) as it moves over the northern Pacific Ocean toward Japan next week. The GPM core observatory satellite passed above on August 28, 2018 at 1816 UTC when

Tropical Storm Miriam's Formation Observed by GPM

Tropical cyclone's continue to regularly develop in the eastern Pacific Ocean. Tropical Depression Fifteen-E formed in the eastern Pacific Ocean about 1000 nautical miles (1852 km) southwest of the Baja California peninsula early on Sunday August 26, 2018. TD15E became better organized with increased banding later in the day and was upgraded by the National Hurricane Center (NHC) to tropical storm MIRIAM. The GPM core observatory satellite saw the forming tropical storm earlier on August 26, 2018 at 0223 UTC. Heavy rainfall near the center of the forming tropical cyclone was examined with the

GPM Captures Cat. 4 Hurricane Lane Passing Close to Hawaiian Islands

View Fullscreen in STORM Event Viewer Battling increased vertical shear, Hurricane Lane struggles northward, down from its Category 5 peak but still featuring winds of over 110 knots. The storm has already begun impacting the Hawaiian Islands, bringing over a foot of rain to Hilo via its outer bands. Lane is expected to continue northward, approaching the island chain, before slowly veering westward as it continues to lose strength. This weakening will not diminish its likely primary impacts, which will be intense coastal erosion and damage and torrential rainfall, upwards of 30 inches in some

GPM Sees Hurricane Lane Threatening Hawaiian Islands With Heavy Rainfall

The GPM core observatory satellite flew over hurricane LANE on August 21, 2018 at 7:48 PM PST (August 22, 2018 at 0548 UTC). At that time LANE was located about 316 nautical miles (585.2 km) from Hilo, Hawaii. Hurricane LANE is one of the strongest tropical cyclones to move into the Hawaiian Islands. At the time of this GPM pass LANE was a category five on the Saffir-Simpson hurricane wind scale with winds of about 140 kts (161 mph). This analysis shows precipitation derived from data collected by the GPM satellite's Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR)

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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