Members Can Post Anonymously On This Site
-
Similar Topics
-
By NASA
Explore This Section Earth Earth Observer Editor’s Corner Feature Articles Meeting Summaries News Science in the News Calendars In Memoriam Announcements More Archives Conference Schedules Style Guide 9 min read
NASA’s TROPICS Mission: Offering Detailed Images and Analysis of Tropical Cyclones
Introduction
Tropical cyclones represent a danger to life, property, and the economies of communities. Researchers who study tropical cyclones have focused on remote observations using space-based platforms to image these storms, inform forecasts, better predict landfall, and improve understanding of storm dynamics and precipitation evolution – see Figure 1.
Figure 1. TROPICS imagery of Typhoon Kong-rey observed on October 29, 2024 near 205 GHz revealing a large and well-defined eye. Figure credit: U.S. Naval Research Laboratory The tropical cyclone community has leveraged data from Earth observing platforms for more than 30 years. These data have been retrieved from numerous instruments including: the Advanced Baseline Imager (ABI) on the National Oceanic and Atmospheric Administration’s (NOAA) Geostationary Operational Environmental Satellite (GOES)–Series R satellites; the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI); the Global Precipitation Measurement (GPM) Microwave Imager (GMI); the Special Sensor Microwave Imager/Sounder (SSMIS) on the Defense Meteorological Satellite (DSMP) satellites; the Advanced Microwave Scanning Radiometer (AMSR-E) on Aqua; AMSR2 on the Japan Aerospace Exploration Agency’s (JAXA) Global Change Observation Mission–Water (GCOM-W) mission; the Advanced Microwave Sounding Unit (AMSU) on Aqua and the Advanced Technology Microwave Sounder (ATMS) on the NASA–NOAA Suomi National Polar-Orbiting Partnership (Suomi NPP), NOAA-20, and NOAA-21; the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua Platform; and the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi NPP, as well as on the first two Joint Polar Satellite System (JPSS) missions (i.e., NOAA-20 and NOAA-21).
Despite having decades of data at their disposal, scientists lack data from instruments placed in low-inclination orbits that provide more frequent views within tropical regions. This limitation is especially pronounced in the tropical and subtropical latitudes, which is where tropical storms develop and intensify.
The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) grew from the Precipitation and All-weather Temperature and Humidity (PATH) to address a need for obtaining three-dimensional (3D) temperature and humidity measurements as well as precipitation with a temporal revisit rate of one hour or better – see Figure 2. TROPICS uses multiple small satellites flying in a carefully engineered formation to obtain rapid revisits of measurements of precipitation structure within the storms, as well as temperature and humidity profiles, both within and outside of the storms, including the intensity of the upper-level warm core. In addition, the instruments provide a median revisit time of about one hour. The data gathered also informs changes in storm track and intensity and provides data to improve weather prediction models.
The imagery is focused on inner storm structure (near 91 and 205 GHz), temperature soundings (near 118 GHz), and moisture soundings (near 183 GHz). Spatial resolution at nadir is approximately 24 km (16.8 mi) for temperature and 17 km (10.6 mi) for moisture and precipitation, covering a swath of approximately 2000 km (1243 mi) in width. Researchers can use TROPICS data to create hundreds of high-resolution images of tropical cyclones throughout their lifecycle.
Figure 2. TROPICS space vehicle showing the CubeSat bus, radiometer payload, and deployed articulated solar array. Figure credit: Blue Canyon Technologies and MIT Lincoln Laboratory This article provides an overview of the two years of successful science operations of TROPICS, with a focus on the suite of geophysical Level-2 (L2) products (e.g., atmospheric vertical temperature and moisture profiles, instantaneous surface rain rate, and tropical cyclone intensity) and the science investigations resulting from these measurements. The complete article, available in the Proceedings Of The IEEE: Special Issue On Satellite Remote Sensing Of The Earth, provides more comprehensive details of the results.
From Pathfinder to Constellation
A single TROPICS satellite was launched as a Pathfinder vehicle on June 30, 2021, aboard a SpaceX Falcon 9 rideshare into a Sun-synchronous polar orbit. TROPICS was originally conceived as a six-satellite constellation, with two satellites launched into each of three low-inclination orbits. Regrettably, the first launch, on June 22, 2022 aboard an Astra Rocket 3.3, failed to reach orbit. While unfortunate, the mission could still proceed with four satellites and meet its baseline revisit rate requirement (with no margin), with the silver lining of an extra year of data gathered from TROPICS Pathfinder that allowed the tropical cyclone research community to prepare and test communications systems and data processing algorithms before the launch of the four remaining constellation satellites. These satellites were deployed on two separate launches – May 8, 2023 and May 26, 2023 aboard a Rocket Lab launch vehicle. The early testing accelerated calibration and validation for the constellation.
Collecting Data Critical to Understanding Tropical Cyclones
Tropical cyclone investigations require rapid quantitative observations to create 2D storm structure information. The four radiance data products in the TROPICS constellation [i.e., antenna temperature (L1a), brightness temperature (L1b), unified brightness temperature, and regularized scan pattern and limb-adjusted brightness temperature (L1c)] penetrate below the cloud top to gather data at greater frequency for a lower cost than current operational systems. The constellation data has been used to evaluate the development of the warm core and evolution of the ice water path within storms – two indicators of storm formation and subsequent changes in intensity.
The upper-level warm core is key to tropical cyclone development and intensification. Precipitation may instigate rapid intensification through convective bursts that are characterized by expanding cold cloud tops, increasing ice scattering, lightning, and towers of intense rain and ice water that are indicative of strong updrafts. TROPICS frequencies provide a wealth of information on scattering by precipitation-sized ice particles in the eyewall and rainbands that will allow for researchers to track the macrostructure of convective bursts in tropical cyclones across the globe. In addition, TROPICS data helps clarify how variations in environmental humidity around tropical cyclones affect storm structure and intensification.
Upper-level Warm Core
Analysis of the upper-level warm core of a tropical cyclone reveals valuable information about the storm’s development. The tropical cyclone community is using data from TROPICS to understand the processes that lead to precipitating ice structure and the role it plays in intensification – see Figure 3. While the warm core has been studied for decades, TROPICS provides a new opportunity to get high-revisit rate estimates of the atmospheric vertical temperature profile. By pairing the temperature profile with the atmospheric vertical moisture profile, researchers can define the relative humidity in the lower-to-middle troposphere, which is critical to understanding the impact of dry environmental air on storm evolution and structure.
Figure 3. TROPICS-3 imagery of Typhoon Kong-rey observed on October 29, 2024, a Category-5 storm that formed in the Pacific Ocean basin. Data gathered near 118 GHz was used to characterize temperature while data gathered near 205 GHz [right] revealed more about the inner structure of the storm. These data are used to define the warm core of the well-defined eye, located at 18.5° N. Figure Credit: U.S. Naval Research Laboratory Ice Water Path and Precipitation
Another variable that helps to provide insight into the development of tropical cyclones is the ice water path, which details the total mass of ice present in a vertical column of the atmosphere and is therefore useful for characterizing the structure and intensity of these storms. Increasing ice water path can reflect strengthening convection within a storm and thereby be an indicator of likely intensification – see Figure 4. TROPICS is the first spaceborne sensor equipped with a 205-GHz channel that, along with the traditional 89, 118, and 183 GHz channels, is more sensitive to detecting precipitation-sized ice particles. In addition, the TROPICS Precipitation Retrieval and Profiling Scheme (PRPS) provides an estimate of precipitation. This scheme is based solely on the satellite radiances linked to precipitation rates, which can be used to generate products across time scales, from near-real-time to climatological scales.
Figure 4. Global precipitation ice water path (PIWP) retrievals derived from TROPICS [top] compared to those derived using data from the GPM Dual-frequency Precipitation Radar (GPM DPR) [bottom] The strong agreement between the two datasets is further validated through case studies over hurricanes, where TROPICS observations correspond well with known storm characteristics. Figure Credit: Blackwell, W. J. et al. (2025) Collaborations and TROPICS Data in Action
To evaluate and enhance the data gathered by TROPICS, the TROPICS application team enlisted the assistance of operational weather forecasters that formed the TROPICS Early Adopters program. In 2018, the program connected the application team to stakeholders interested in using TROPICS data for research, forecasting, and decision making. This collaboration improved approaches to diagnose and predict tropical cyclones. For example, the National Hurricane Center (NHC) found that the new TROPICS channel at 204.8 GHz offered the best approach to capture convective storm structure, followed by the more traditionally used 91-GHz channel. In addition, the U.S. Joint Typhoon Warning Center (JTWC) has been using TROPICS data to center-fix tropical cyclones and identify cloud formations. In particular, the JTWC team found that the 91-GHz channel was most useful for identifying cloud structure. Both NHC and JTWC found the TROPICS high revisit rate to be beneficial.
In 2024, the TROPICS applications team developed the TROPICS Satellite Validation Module as part of the NOAA Hurricane Research Division’s annual Advancing the Prediction of Hurricanes Experiment (APHEX). The module coordinated data collection from NOAA’s Hurricane Hunter aircraft beneath TROPICS satellite overpasses to provide data to calibrate and validate TROPICS temperature, moisture, and precipitation measurements. Using this approach, the Hurricane Hunter team tracked Hurricane Ernesto over the central North Atlantic on August 15 and 16, 2024 and used the data to characterize the environment of Ernesto’s rain bands – see Figure 5.
Figure 5. Brightness temperature (K) measured at 205 GHz from TROPICS-5 [right] and TROPICS-6 [left and center] from Hurricane Ernesto on August 15 and 16, 2024. The shaded circles denote 850–700 hPa relative humidity (%). Wind barbs are 850–700 hPa layer averaged winds (kt). Dropsonde data within 30 minutes of the TROPICS overpass times are plotted. Figure Credit: Blackwell, W. J. et al. (2025) In addition, the team used TROPICS observations in combination with GPM constellation precipitation estimates to characterize the lifecycle of Hurricane Franklin, which formed on August 19, 2023 and underwent a period of rapid intensification about eight days later. Intensification of the storm, in particular the period of rapid intensification (45 knot increase in maximum winds in 24 hours), occurred in association with a decrease in environmental vertical wind shear, a contraction of the radius of maximum precipitation, and an increase in the precipitation rate. Intensification ended with the formation of secondary rainbands and an outward shift in the radius of maximum precipitation.
Conclusion
TROPICS data offer the potential for improving forecasts from numerical weather prediction models and operational forecasts using its high spatial resolution and high revisit rates that enable enhanced characterization of tropical cyclones globally. To date, the TROPICS mission has produced a high-quality aggregate data record spanning 10 billion observations and 10 satellite years, using relatively low-cost microwave sounder constellations. All L1 (i.e., radiances) and L2 (i.e., geophysical products) data products and Algorithm Theoretical Basis Documents are available to the general public through the Goddard Earth Sciences Data and Information Services Center (GES DISC). The GES DISC data discussed in this article include L1 and L2 products for TROPICS-1, TROPICS-3, TROPICS-5, and TROPICS-6.
TROPICS data has aided hurricane track forecasting for multiple storms as forecasters have used the data at multiple operational tropical cyclone forecast centers. Data gathered by TROPICS will soon be complemented by multiple commercial constellations that are coming online to improve the revisit rate and performance.
William Blackwell
MIT Lincoln Laboratory
wjb@ll.mit.edu
Scott Braun
NASA GSFC, TROPICS Project Scientist
scott.a.braun@nasa.gov
Stacy Kish
Earth Observer Staff
Earthspin.science@gmail.com
Share
Details
Last Updated Jun 09, 2025 Related Terms
Earth Science View the full article
-
By NASA
3 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Communities in coastal areas such as Florida, shown in this 1992 NASA image, are vulnerable to the effects of sea level rise, including high-tide flooding. A new agency-led analysis found a higher-than-expected rate of sea level rise in 2024, which was also the hottest year on record.NASA Last year’s increase was due to an unusual amount of ocean warming, combined with meltwater from land-based ice such as glaciers.
Global sea level rose faster than expected in 2024, mostly because of ocean water expanding as it warms, or thermal expansion. According to a NASA-led analysis, last year’s rate of rise was 0.23 inches (0.59 centimeters) per year, compared to the expected rate of 0.17 inches (0.43 centimeters) per year.
“The rise we saw in 2024 was higher than we expected,” said Josh Willis, a sea level researcher at NASA’s Jet Propulsion Laboratory in Southern California. “Every year is a little bit different, but what’s clear is that the ocean continues to rise, and the rate of rise is getting faster and faster.”
This graph shows global mean sea level (in blue) since 1993 as measured by a series of five satellites. The solid red line indicates the trajectory of this increase, which has more than doubled over the past three decades. The dotted red line projects future sea level rise.NASA/JPL-Caltech In recent years, about two-thirds of sea level rise was from the addition of water from land into the ocean by melting ice sheets and glaciers. About a third came from thermal expansion of seawater. But in 2024, those contributions flipped, with two-thirds of sea level rise coming from thermal expansion.
“With 2024 as the warmest year on record, Earth’s expanding oceans are following suit, reaching their highest levels in three decades,” said Nadya Vinogradova Shiffer, head of physical oceanography programs and the Integrated Earth System Observatory at NASA Headquarters in Washington.
Since the satellite record of ocean height began in 1993, the rate of annual sea level rise has more than doubled. In total, global sea level has gone up by 4 inches (10 centimeters) since 1993.
This long-term record is made possible by an uninterrupted series of ocean-observing satellites starting with TOPEX/Poseidon in 1992. The current ocean-observing satellite in that series, Sentinel-6 Michael Freilich, launched in 2020 and is one of an identical pair of spacecraft that will carry this sea level dataset into its fourth decade. Its twin, the upcoming Sentinel-6B satellite, will continue to measure sea surface height down to a few centimeters for about 90% of the world’s oceans.
To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video
This animation shows the rise in global mean sea level from 1993 to 2024 based on da-ta from five international satellites. The expansion of water as it warms was responsible for the majority of the higher-than-expected rate of rise in 2024.NASA’s Scientific Visualization Studio Mixing It Up
There are several ways in which heat makes its way into the ocean, resulting in the thermal expansion of water. Normally, seawater arranges itself into layers determined by water temperature and density. Warmer water floats on top of and is lighter than cooler water, which is denser. In most places, heat from the surface moves very slowly through these layers down into the deep ocean.
But extremely windy areas of the ocean can agitate the layers enough to result in vertical mixing. Very large currents, like those found in the Southern Ocean, can tilt ocean layers, allowing surface waters to more easily slip down deep.
The massive movement of water during El Niño — in which a large pool of warm water normally located in the western Pacific Ocean sloshes over to the central and eastern Pacific — can also result in vertical movement of heat within the ocean.
Learn more about sea level:
https://sealevel.nasa.gov
News Media Contacts
Jane J. Lee / Andrew Wang
Jet Propulsion Laboratory, Pasadena, Calif.
818-354-0307 / 626-379-6874
jane.j.lee@jpl.nasa.gov / andrew.wang@jpl.nasa.gov
2025-036
Share
Details
Last Updated Mar 13, 2025 Related Terms
Sentinel-6 Michael Freilich Satellite Climate Science Jet Propulsion Laboratory Oceans Explore More
6 min read Cosmic Mapmaker: NASA’s SPHEREx Space Telescope Ready to Launch
Article 6 days ago 5 min read NASA Turns Off 2 Voyager Science Instruments to Extend Mission
Article 1 week ago 3 min read University High Knows the Answers at NASA JPL Regional Science Bowl
Article 1 week ago Keep Exploring Discover Related Topics
Missions
Humans in Space
Climate Change
Solar System
View the full article
-
-
-
By NASA
Download PDF: Statistical Analysis Using Random Forest Algorithm Provides Key Insights into Parachute Energy Modulator System
Energy modulators (EM), also known as energy absorbers, are safety-critical components that are used to control shocks and impulses in a load path. EMs are textile devices typically manufactured out of nylon, Kevlar® and other materials, and control loads by breaking rows of stitches that bind a strong base webbing together as shown in Figure 1. A familiar EM application is a fall-protection harness used by workers to prevent injury from shock loads when the harness arrests a fall. EMs are also widely used in parachute systems to control shock loads experienced during the various stages of parachute system deployment.
Random forest is an innovative algorithm for data classification used in statistics and machine learning. It is an easy to use and highly flexible ensemble learning method. The random forest algorithm is capable of modeling both categorical and continuous data and can handle large datasets, making it applicable in many situations. It also makes it easy to evaluate the relative importance of variables and maintains accuracy even when a dataset has missing values.
Random forests model the relationship between a response variable and a set of predictor or independent variables by creating a collection of decision trees. Each decision tree is built from a random sample of the data. The individual trees are then combined through methods such as averaging or voting to determine the final prediction (Figure 2). A decision tree is a non-parametric supervised learning algorithm that partitions the data using a series of branching binary decisions. Decision trees inherently identify key features of the data and provide a ranking of the contribution of each feature based on when it becomes relevant. This capability can be used to determine the relative importance of the input variables (Figure 3). Decision trees are useful for exploring relationships but can have poor accuracy unless they are combined into random forests or other tree-based models.
The performance of a random forest can be evaluated using out-of-bag error and cross-validation techniques. Random forests often use random sampling with replacement from the original dataset to create each decision tree. This is also known as bootstrap sampling and forms a bootstrap forest. The data included in the bootstrap sample are referred to as in-the-bag, while the data not selected are out-of-bag. Since the out-of-bag data were not used to generate the decision tree, they can be used as an internal measure of the accuracy of the model. Cross-validation can be used to assess how well the results of a random forest model will generalize to an independent dataset. In this approach, the data are split into a training dataset used to generate the decision trees and build the model and a validation dataset used to evaluate the model’s performance. Evaluating the model on the independent validation dataset provides an estimate of how accurately the model will perform in practice and helps avoid problems such as overfitting or sampling bias. A good model performs well on
both the training data and the validation data.
The complex nature of the EM system made it difficult for the team to identify how various parameters influenced EM behavior. A bootstrap forest analysis was applied to the test dataset and was able to identify five key variables associated with higher probability of damage and/or anomalous behavior. The identified key variables provided a basis for further testing and redesign of the EM system. These results also provided essential insight to the investigation and aided in development of flight rationale for future use cases.
For information, contact Dr. Sara R. Wilson. sara.r.wilson@nasa.gov
View the full article
-
-
Check out these Videos
Recommended Posts
Join the conversation
You can post now and register later. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.