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GPM Applications: Weather

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

Friday, February 8, 2019

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 Precipitation Forecast Example

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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ECMWF Seasonal Forecast of Precipitation Probability

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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Snowpack in the Absaroka Range

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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Tropical Cyclone Josie's Deadly Flooding Rainfall Examined With IMERG

Tropical Cyclone Josie's Deadly Flooding Rainfall Examined With IMERG
Tropical cyclone Josie didn't make landfall in Fiji but it's heavy rainfall resulted in deadly flooding. Approximate locations of tropical cyclone Josie, as it moved close to Fiji, are shown overlaid in white. Josie's clockwise circulation streamed moisture over Fiji causing flooding that led to the deaths of at least four people. This rainfall accumulation analysis used Integrated Multi-satellitE Retrievals for GPM (IMERG) data. Those data are generated by NASA's Precipitation Processing System every half hour within about 6 hours from when data are acquired. IMERG data are acquired from the

GPM Sees Jelawat Becoming A Typhoon

GPM Sees JELAWAT Becoming A Typhoon
Tropical storm JELAWAT intensified as expected and was upgraded to typhoon JELAWAT yesterday. Today JELAWAT has continued to rapidly intensify and maximum sustained wind speeds in the typhoon were estimated at 115 kts (132 mph). The GPM core observatory satellite had an excellent view of rapidly intensifying tropical storm JELAWAT on March 29, 2018 at 1546 UTC. JELAWAT had wind speeds of about 60 kts (69 mph) when GPM passed over head. An eye hadn't formed yet but rain bands were wrapping around JELAWAT's well established center of circulation. GPM's radar (DPR Ku Band) revealed that rain was

Intensifying Tropical Storm Jelawat Evaluated By GPM

Intensifying Tropical Storm Jelawat Evaluated By GPM
The GPM core observatory satellite flew almost directly above large intensifying tropical storm JELAWAT on March 28, 2018 at 0510 UTC. Rainfall measurements shown here were derived from data collected by GPM's Microwave Imager (GMI) and Dual Frequency Precipitation Radar (DPR) instruments. These satellite instruments provided excellent coverage of JELAWAT's precipitation. GPM's Radar (DPR Ku Band) swath included exceptionally powerful storms within a large intense feeder band that was wrapping around the eastern side of the tropical storm. GPM's DPR revealed that these strong convective storms

Tropical Cyclone Nora's Flooding Rains Measured With IMERG

Tropical Cyclone Nora's Flooding Rains Measured With IMERG
Tropical Cyclone NORA produced heavy rainfall when it came ashore in northwestern Queensland on March 24, 2018 (GMT). NORA's peak intensity of 95 kts (109 mph) was reached when the tropical cyclone was located in the central northern Gulf Of Carpentaria. Winds had decreased slightly to 90 kts (104 mph) by landfall. The Australian Bureau of Meteorology (BOM) reported that NORA produced over 110 mm (4.3 inches) of rain in 24 hours. Flooding, landslides, lost electrical power, and structural damage were also a companion of the tropical cyclone's arrival. After landfall NORA weakened but the

GPM Flies Over Intensifying Tropical Cyclone Nora

GPM Flies Over Intensifying Tropical Cyclone Nora
Intensifying tropical cyclone NORA has been moving southeastward into the Gulf of Carpentaria since it formed in the Arafura Sea north-northeast of Darwin,Australia. The Joint Typhoon Warning Center (JTWC) issued it's first warning for Tropical cyclone NORA on March 22, 2018 at 0900Z. After that NORA's winds increased to over 65 kts (75 mph). That means that today NORA became the equivalent of a category one hurricane on the Saffir-Simpson hurricane wind scale. The GPM core observatory satellite scanned tropical cyclone NORAas it passed above on March 22, 2018 at 1847 UTC. GPM's Microwave
A Decade of Global Precipitation

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

NASA’s New View of the Daily Cycle of Rain

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 Studies Snow At The Winter Olympics

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...

A New Multi-dimensional View of a Hurricane

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...

Getting Flake-y: Why All Snowflakes Have Six Sides
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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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