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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IMERG Precipitation Totals from Eastern Australia, March 16 - 23, 2021
During the week ending on March 23, 2021, two locations in Australia experienced unusually high rainfall totals. According to news reports a persistent system brought flooding rains to Australia's east coast from Brisbane to Sydney and points further south. The preliminary estimate from NASA's multi-satellite global precipitation analysis is that more than 24 inches fell just off the coast of Australia in 7 days with accumulations in coastal areas exceeding 16 inches. Near the Strzelecki Desert in central Australia, a storm system brought 8 inches of precipitation during the same 7-day period. Most of the rain fell during a 3-day period (0000 UTC on 20 March to 2359 UTC on 22 March).
IMERG Sees Winter Storms Impact the Southern U.S.
In mid-February 2021, large areas of the Continental United States experienced extreme cold temperatures as a result of a strong Arctic high pressure system. The cold temperatures were accompanied by several pulses of precipitation over the Southeast US through the mid-Atlantic, as well as the Pacific Northwest. The combination of cold temperatures and precipitation resulted in widespread power outages to millions of people in Texas, Kentucky, West Virginia, and Oregon, among other states.
IMERG Captures Rainfall from Tropical Cyclone Ana in Fiji
NASA combined data from multiple satellites to estimate the rainfall from Tropical Cyclone Ana in the Southwest Pacific Ocean amid an ongoing Madden-Julian Oscillation (MJO) event. The Madden-Julian Oscillation is a 20 to 90 day pattern of alternating wet and dry conditions that often begins in the tropical Indian Ocean and moves eastward into the Pacific. This animation shows rainfall rates (blue/yellow shading) and rainfall accumulations (green shading) at half-hourly intervals from January 26 - February 2, 2021, using NASA's IMERG algorithm, overlaid on shades of white/gray from NOAA
IMERG Rainfall Total from Week of Jan 25 2021
NASA combined data from multiple satellites to estimate the rainfall from an "atmospheric river" event over the U.S. West Coast in near real-time at half-hourly intervals from January 25 - 29, 2021. Atmospheric rivers are long, narrow corridors of water vapor that can lead to heavy precipitation when they encounter land. This animation shows estimated rainfall rates in blue and yellow shading and total rainfall accumulations in green shading, from NASA's IMERG algorithm, overlaid on shades of white and gray from NOAA infrared satellite data which shows cloudiness. On January 25, 2021, a low
IMERG Total from Cyclone Gati
On November 22, 2020, Cyclone Gati became the strongest storm to hit Somalia since satellite records began five decades ago. Gati made landfall with maximum sustained winds of 170 kilometers (105 miles) per hour, a category 2 storm on the Saffir-Simpson scale . The storm brought more than a year’s worth of rain to the region in two days. Local authorities report at least eight people were killed and thousands have been displaced. The map above shows rainfall accumulation from November 21-23, 2020. These data are remotely-sensed estimates that come from the Integrated Multi-Satellite Retrievals

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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