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Tropical Storms and Ocean Winds

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Meteorology - Geostationary

Warm ocean waters drive tropical storms, powerful weather systems capable of causing widespread damage through intense winds, rainfall, and storm surges. Earth observation satellites support tropical storm monitoring by providing continuous, multi-spectral data on sea surface temperature, atmospheric moisture, wind fields, and cloud structure. By integrating observations from microwave, infrared, radar, and lightning sensors, satellites enable real-time tracking, intensity estimation, and improved forecasting of storm development and landfall.

Tropical storms are organised, low-pressure systems that develop over warm ocean waters of at least 27°C, with maximum sustained wind speeds ranging between 63 km/h and 118 km/h. Their formation and intensity directly relate to environmental conditions including sea surface temperature (SST), atmospheric pressure, wind patterns, and moisture content. These storms can cause significant damage and may intensify to form increasingly dangerous systems, such as hurricanes in the Northern Hemisphere and cyclones in the Southern Hemisphere. Once winds exceed 118 km/h, the storm is classified as a hurricane or cyclone according to the Saffir-Simpson scale of wind intensity. This danger makes accurate monitoring of these systems essential. 1) 2)

Figure 1: Hurricane Florence seen from the ISS (Image credit: NASA)

Satellites can measure the meteorological indicators of tropical storm formation and progression including elevated SST, atmospheric moisture, and wind speeds, as well as falling atmospheric pressure and characteristic cloud patterns. Infrared (IR) and microwave (MW) sensors measure thermal emissions and water vapor distribution, providing data on atmospheric instability and moisture availability. Scatterometers and synthetic aperture radar (SAR) instruments detect ocean surface wind speeds and wave heights, which indicate storm intensity and structure. Passive radiometers and precipitation radars track rainfall rates, aiding in forecasting storm development and associated hazards such as flooding. 3) 4) 5) 

Figure 2: NOAA-20 VIIRS (Visible/Infrared Imager and Radiometer Suite) Day/Night Band (0.7 µm) (left) and IR (11.45 µm) (right) images of Tropical Storm Dorian (2019). The Day/Night Band provides a visible image of the storm's structure, while infrared reveals temperature variations in the storm's cloud top (Image credit: NOAA)

By integrating these various datasets, meteorologists and disaster management agencies can improve storm prediction models, assess potential landfall locations, and implement timely preparedness measures.

Radiometers measure radiation emitted by the Earth's surface and atmosphere, enabling the observation of key storm indicators such as sea surface temperature, cloud cover, and land surface temperature, factors critical in identifying developing storms. Radiometers offer distinct advantages in coverage and observation frequency, and provide a wide swath and hence more frequent monitoring. The broader coverage and real-time capabilities of radiometers make them well-suited for tracking large-scale atmospheric and oceanic conditions. 6)

Scatterometers are active remote sensing instruments that emit microwave signals toward the Earth's surface and measure the reflected signal. Scatterometers are specifically designed to measure ocean surface wind speed and direction by analyzing how the radar signal interacts with surface waves. The roughness of the ocean, which is directly influenced by wind, affects the intensity of the backscatter, allowing us to estimate wind patterns and other air-sea interactions. Different scatterometers operate in various microwave frequency bands, with the most commonly used being C-band and Ku-band. Each band has distinct advantages and limitations depending on its frequency, which impacts factors such as resolution, sensitivity to rain, and ability to detect wind variations. 7) 8)

SAR operates in the microwave region of the electromagnetic spectrum, allowing its signals to penetrate cloud cover and provide continuous monitoring of extreme weather systems. Unlike optical sensors, which rely on visible light, SAR actively emits microwave pulses and measures the signals reflected off the Earth's surface. This capability enables precise detection of surface characteristics, including ocean topography and surface deformations. 9)

For tropical storm monitoring, SAR’s ability to capture high-resolution data, often with a spatial resolution of less than 100 m in wide-swath mode, makes it an invaluable tool. By analysing ocean surface roughness, SAR-derived wind maps can provide critical storm parameters, such as maximum wind speed, the radius of maximum winds, and the spatial extent of key wind speed thresholds: 34, 50, and 64 knots (known as R34, R50, and R64, respectively). These measurements are essential for assessing storm intensity, tracking its evolution, and improving early warning systems. SAR’s high resolution data is complimented by radiometers extensive coverage and rapid observation frequency 10)

Figure 3: RADARSAT-2 imagery of Hurricane Helene, 26 September 2024 (Image credit: MDASpace)

Example Products

Tropical Cyclone Formation Probability (TCFP)

Tropical Cyclone Formation Probability (TCFP) products are essential tools for predicting cyclone development. These probabilistic forecasts integrate satellite observations, numerical weather models, and machine learning techniques to assess formation likelihood. Two widely used TCFP products are developed by the National Oceanic and Atmospheric Administration (NOAA) and the European Centre for Medium-Range Weather Forecasts (ECMWF).

NOAA 48-Hour TCFP

Covering the global tropics (45°S to 45°N), NOAA’s 48-hour TCFP product provides short-term forecasts of tropical cyclone formation using geostationary satellite data, oceanic conditions, and large-scale environmental parameters to estimate probabilities. 15) 16)

The geostationary satellite data, sourced from GOES-RHimawari-8/-9, and Meteosat Second and Third Generation, includes key indicators such as Percent Cloud Cover Depth (PCCD) and Brightness Temperature of Water Vapor (BTWM). Oceanic conditions include SST observations from the Group for High-Resolution Sea Surface Temperature (GHRSST). While large-scale environmental parameters encompass a range of factors, including Mean Sea Level Pressure (MSLP), vertical wind shear (VSHS and VSHG), and convective instability (THCV, CIN, and VVAC). Lower MSLP suggests higher cyclone formation potential, while excessive wind shear can disrupt storm development. Convective instability indicators help assess conditions for storm activity.

 

Figure 4: Various input parameters used to calculate the TCFP. Top left: PCCD, Top right: vertical shear, Bottom left: MSLP, Bottom right: SST (Image credit: NOAA)
Figure 5: The resulting product of the TCPF, showing a region of high probability for storm formation off the coast of Western Australia, March 2025 (Image credit: NOAA)

 

ECMWF Medium-Range TCFP

The ECMWF Tropical Cyclone Genesis Probability product takes a longer-term approach, providing forecasts for a 3-10 day period. Unlike NOAA’s 48-hour TCFP, which is designed for immediate operational decision-making, ECMWF’s forecasts help meteorologists identify broader trends in cyclone development. 17)

Figure 6:  ECMWF Tropical Cyclone Genesis Probability product, showing the genesis of a tropical storm close to the coast of Western Australia in March 2025 (the same storm as depicted in the NOAA product above) (Image credit: ECMWF)

Hurricane Intensity and Structure Algorithm (HISA)

Hurricane Intensity and Structure Algorithm (HISA) estimates key storm parameters using microwave temperature retrievals. It provides estimates of storm intensity and structure, including the center location, maximum sustained surface wind speed (Vmax), MSLP, and the maximum radial extent of the winds in four quadrants. HISA also produces azimuthally averaged gradient winds and 2D balanced winds at standard pressure levels, available in NetCDF format. 18) 19) 20)

HISA processes temperature profile data from various satellite-based microwave sounders, such as the Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Units (AMSU) onboard Suomi-NPP and MetOp-B and -C, respectively. An ongoing adaptation is incorporating data from TROPICS (Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats).

Figure 7: Temperature retrievals from NOAA-21 (top left), Suomi-NPP (top right), NOAA-20 (bottom left), and MetOp-B (bottom right) of a region in the southeastern Indian Ocean, often a zone for Southern Hemisphere tropical storms. The retrievals are then used by HISA to estimate key tropical storm parameters, such as intensity, wind structure, and minimum sea-level pressure (Image credit: NOAA)

Full Disk Imagery

Full disk imagery refers to satellite images capturing an entire hemisphere of the Earth from pole to pole, primarily captured by instruments carried on geostationary satellites. By providing a continuous, wide-field view, full disk imagery allows meteorologists to observe the evolution of storms in real time and analyse their interaction with broader atmospheric patterns.

The Advanced Himawari Imager (AHI) onboard Himawari-8 and the Advanced Baseline Imager (ABI) onboard GOES-R series provide full disk imagery every 10 minutes, allowing the detection of storm intensity, center location, cloud structure, and atmospheric water vapor content. 21)

Figure 8: Full-disk imagery from Himawari-8 in different spectral channels. Top left: Infrared, Top right: Water vapor, Bottom left: Water vapor (shown in blue), Bottom right: Monochromatic visible. (Image credit: NOAA)

GeoXO, the planned successor to GOES-R, will carry the GeoXO Imager (GXI), which will continue to provide full disk imagery at enhanced resolution. Notably, it will introduce a 0.91 µm channel and a 5.15 µm channel, both of which will improve low-level water vapor detection, a crucial factor in tropical storm tracking. 23)

Lightning maps

Lightning maps provide real-time visualizations of lightning strokes, which result from charge separation within storm clouds. The frequency, location, and density of lightning strokes are closely linked to storm convection, precipitation, and intensity changes. Increased lightning activity can indicate rapid storm intensification, providing early warning signs for severe weather. 11)

Figure 9: GOES-16 view of the eye of Hurricane Dorian on September 1, 2019 (Image credit: NOAA)

 

Lightning mapping arrays (LMA) use networks of very high frequency (VHF) antennas, GPS receivers, and processing systems to create three-dimensional maps of lightning activity. These arrays detect radio pulses emitted by lightning strokes, measuring their location, time, and structure with high precision. The World Wide Lightning Location Network (WWLLN), produces global lightning maps using a network of radio sensors. The WWLLN team has developed a "storm-following" tool that provides near-real-time lightning data for tropical cyclones. 12) 13)

Figure 10: An intracloud flash observed from the LMA site in Oklahoma, U.S. during a storm in 2012. The top panel shows time and altitude, the middle shows distance east and altitude, the lower left shows the distance east and distance north, and the lower right shows the distance north and altitude (Image credit: NOAA)

Many satellites carry dedicated lightning sensors, in particular on board geostationary satellites. This allows for the continuous monitoring of lightning across large oceanic regions to monitor and forecast tropical storms. 14)

In the News

High-resolution imagery from satellites plays an important role in disaster monitoring and response, supporting rapid mapping and the coordination of emergency relief efforts. This includes the Hurricane Melissa, which occurred in the Caribbean in October 2025.

Hurricane Melissa: Caribbean 2025

On 28 October 2025, Hurricane Melissa struck Jamaica’s southern coast with devastating intensity. With sustained winds of 295 km/h, Melissa ranks among the most intense hurricanes recorded to date in the Atlantic basin. Unusually warm ocean conditions, including sea-surface temperatures 2-3 degrees Celsius above average, provided the fuel for Melissa’s rapid intensification and sustained power, pointing to climate change as a key contributor. Satellite images captured before, during, and after the hurricane are being used to aid authorities and show the sheer scale of destruction. 35) 38)

A wide array of sensors captured the storm, including the microwave imager on board ESA’s Soil Moisture and Ocean Salinity (SMOS) mission, the multispectral imager onboard the Copernicus Sentinel-2 mission, and the NOAA-20 satellite. 

Figure 11: On 27 October, as the storm passed by the Jamaican coast, SMOS captured two datasets showing the surface wind speed in the area (Image credit: N. Reul, Ifremer) 

 

Figure 12: The Copernicus Sentinel-2 mission captured a detailed image of the hurricane’s eye just hours before it reached Jamaica’s southern coast. (Image credit: Copernicus) 36)

 

Figure 13: Imagery from GOES-19 of Hurricane Melissa's path. (Image credit: NOAA / CIRA)

 

 

Related Missions

TROPICS (Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats)

TROPICS is a constellation of four microwave imaging 3U CubeSats operated by NASA, with the goal of measuring temperature, humidity, and precipitation to aid in understanding of storm structure and formation. Each CubeSat is equipped with a microwave spectrometer, which collectively operate over 12 spectral bands: seven to measure temperature, three for humidity, one for precipitation, and one for cloud ice. 24)

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GPM (Global Precipitation Measurement) Mission

The GPM Mission is an international collaboration led by NASA and JAXA, designed to improve global precipitation measurements. The GPM Core Observatory, launched in February 2014, serves as the primary satellite in a constellation of 12 satellites, enhancing our understanding of precipitation, evaporation, and the global water cycle. The observatory carries two primary instruments: the Dual-frequency Precipitation Radar (DPR), which provides three-dimensional measurements of rain and snow, and the GPM Microwave Imager (GMI), which collects passive microwave data on precipitation intensity. GPM enhances tropical storm tracking by capturing rainfall intensity, structure, and evolution. 25) 26)

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GOES-R (Geostationary Operational Environmental Satellite-R)

GOES-R is a geostationary weather monitoring satellite series operated by NOAA and NASA, providing continuous atmospheric observations crucial for tropical storm tracking. The onboard Geostationary Lightning Mapper (GLM) detects lightning frequency, location, and density, which are key indicators of storm convection, precipitation, and intensity changes. Additionally, the Advanced Baseline Imager (ABI) offers high-resolution multispectral imagery, enabling improved monitoring of storm structure, cloud development, and temperature profiles.

The GOES-R series is set to be succeeded by the Geostationary Extended Observations (GeoXO) program, which will enhance spatial resolution, imaging frequency, and data quality, further improving tropical storm monitoring and prediction.

GOES-R: Read more

GeoXO: Read more

MetOp (Meteorological Operational Satellite Program of Europe)

The MetOp program, a collaboration between ESA and EUMETSAT, consists of three sun-synchronous polar-orbiting satellites: MetOp-A, -B, and -C, launched 2006, 2012, and 2018 respectively. Metop-A retired in 2021. These satellites play a crucial role in Numerical Weather Prediction (NWP), providing global measurements of temperature, humidity, ocean surface wind speed, and atmospheric composition. The ASCAT (Advanced Scatterometer) provides wind-vector measurements and AMSU-A (Advanced Microwave Sounding Unit-A) provides storm core identification. Their infrared (IASI) and microwave (AMSU-A and MHS) sensors track storm structure, cloud development, and moisture distribution, improving storm intensity forecasts and climate studies. 28) 29)

The MetOp program is set to be succeeded by MetOp-SG (MetOp-Second Generation Program), which will significantly enhance spatial/spectral resolution, the data transmission capacity is will be increased (up to 20x higher), and the measurement capabilities will be extended to include trace gases, aerosols, ice clouds, and more. 30)

MetOP: Read more

MetOp-SG: Read more

Joint Polar Satellite System (JPSS) and Suomi NPP

The JPSS is a collaborative program between NOAA and NASA, with support from international partners. The fleet includes the Suomi National Polar-orbiting Partnership (Suomi NPP, launched in 2011), NOAA-20 (formerly JPSS-1, launched in 2017), NOAA-21 (formerly JPSS-2, launched in 2022), and the upcoming JPSS-3 and JPSS-4 satellites. These satellites are equipped to measure key environmental parameters such as atmospheric temperature, humidity, sea surface temperature, and vegetation health.

The satellites carry a suite of instruments including the Advanced Technology Microwave Sounder (ATMS) and the Cross-track Infrared Sounder (CrIS), which provide atmospheric temperature, moisture, and pressure profiles vital for cyclone analysis. ATMS detects storm intensity and structure using microwave signals across 22 frequency channels, while the onboard Visible Infrared Imaging Radiometer Suite (VIIRS) captures visible and infrared imagery of tropical storms, aiding in real-time tracking and prediction. 31) 32)

Suomi NPP: Read more

JPSS: Read more

SMOS (Soil Moisture and Ocean Salinity)

SMOS is an ESA EO mission launched in 2009 with the objective of  measuring soil moisture and ocean salinity to improve forecasting and aid climate studies. The onboard Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) operates in the L-band (1.14 GHz) to capture microwave emissions from Earth's surface. ]The mission provides key wind products, such as SMOS Near Real-Time Wind Speeds and Wind Radii Fixes, which support storm tracking and intensity analysis. By offering rapid, high-resolution wind data, SMOS enhances real-time tropical cyclone forecasts and contributes to improved storm preparedness. 33) 34)

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Himawari

The Himawari series, beginning in 1977 with the launch of Himawari-1, is operated by the Japan Meteorological Agency. This includes Himawari-8, launched October 2014, and Himawari-9, launched November 2016. These satellites provide critical data for the NOAA TCFP, with the Advanced Himawari Imager (AHI) onboard Himawari-8 delivering full-disk images every 10 minutes.

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Sentinel-3

Sentinel-3, part of Copernicus, the European Union’s Earth observation program, is a constellation of two radar imaging satellites operated by ESA and supported by EUMETSAT, launched in February 2016 and April 2018. The satellites measure sea-surface topography, as well as the colour and temperature of ocean and land surfaces, which is used for ocean systems forecasting, environmental monitoring, and climate monitoring.

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SMAP (Soil Moisture Active/Passive)

SMAP is a NASA-led mission, supported by the Canadian Space Agency (CSA), launched in January 2015. It uses radio waves to monitor global soil moisture, carrying an L-band radar and an L-band radiometer.

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CYGNSS (Cyclone Global Navigation Satellite System)

CYGNSS is a joint NASA-University of Michigan mission launched in December 2016, aimed at studying tropical cyclone formation and evolution, particularly the inner core. The constellation consists of 8 satellites, with the Delay Doppler Mapping Instrument (DDMI) onboard, which retrieves radio signals. These signals are then processed by the CYGNSS wind speed retrieval algorithm to measure ocean surface wind speeds.

Read more

References

1) “Measuring Hurricanes: The Saffir-Simpson Hurricane Wind Scale,” UK Met Office, 2024. URL:https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/hurricanes/measuring

2) “What is a Hurricane?” NOAA, 2024. URL:https://oceanservice.noaa.gov/facts/hurricane.html

3) “How Do Hurricanes Form?” NOAA Ocean Explorer, 2024. URL:https://oceanexplorer.noaa.gov/facts/hurricanes.html

4) “Tropical Storm,” Britannica, 2024. URL:https://www.britannica.com/science/tropical-storm

5) “Tropical Cyclones,” World Meteorological Organization, 2024. URL:https://wmo.int/topics/tropical-cyclone

6) “Tropical Cyclone Observations Using Synthetic Aperture Radar," IEEE Xplore, URL: https://ieeexplore.ieee.org/document/9553590

7) "Scatterometry in Weather Detection," Penn State Learning Weather, URL:https://learningweather.psu.edu/node/73#:~:text=Scatterometry%20can%20detect%20centers%20of,status%20as%20a%20 tropical%20 depression

8) "Airborne Scatterometers," NASA Airborne Science Program, URL:https://airbornescience.nasa.gov/category/type/Scatterometer

9) "Synthetic Aperture Radar," Wikipedia, URL:https://en.wikipedia.org/wiki/Synthetic-aperture_radar

10) "SAR Imaging and Applications," ArcGIS StoryMaps, URL: https://storymaps.arcgis.com/stories/fd77b1daf91a4ef99d6f176183e4154a

11) "Thunder and Lightning: Lightning," Met Office, 2024. URL:https://weather.metoffice.gov.uk/learn-about/weather/types-of-weather/thunder-and-lightning/lightning

12) "Lightning Mapping Array (LMA)," NASA Earth Science Data, 2024. URL:https://impact.earthdata.nasa.gov/casei/instrument/LMA/

13) "Monitoring Tropical Cyclones with Lightning and Satellite Data," EOS, 2024. URL:https://eos.org/science-updates/monitoring-tropical-cyclones-with-lightning-and-satellite-data

14) "Lightning Detection," NSSL, 2024 URL:https://www.nssl.noaa.gov/education/svrwx101/lightning/detection/

15) “Tropical Cyclone Formation Probability Product,” NOAA, 2024. URL:https://www.ospo.noaa.gov/products/ocean/tropical/tcfp/description.html

16) “Global Probabilistic Analysis of Rapid Intensification (GPARM),” Colorado State University, 2024. URL:https://rammb.cira.colostate.edu/projects/gparm/description.asp

17) “Enter the Ensembles,” ECMWF, 2024. URL:https://www.ecmwf.int/en/about/media-centre/aifs-blog/2024/enter-ensembles

18) “Hurricane Intensity and Structure Algorithm (HISA),” Cooperative Institute for Research in the Atmosphere, Colorado State University, 2024. URL:https://rammb2.cira.colostate.edu/research/goes-r-research/hisa/

19) “Assessing the Performance of Tropical Cyclone Intensity Forecasts,” American Meteorological Society, 2024. URL:https://ams.confex.com/ams/104ANNUAL/meetingapp.cgi/Paper/436276

20) “User Guides: Tropical Cyclones,” EUMETSAT, 2024. URL:https://user.eumetsat.int/resources/user-guides/tropical-cyclones

21) “Himawari-8 & 9,” EUMETSAT, 2024. URL:https://www.eoportal.org/satellite-missions/himawari-8-9.

22) “Tropical Cyclone Monitoring Based on Geostationary Satellite Imagery.” Springer, 2024. URL:https://link.springer.com/chapter/10.1007/978-981-19-6375-9_8

23) “GEO-XO Mission,” ESA, 2024. URL:https://www.eoportal.org/satellite-missions/geoxo#sensorcomplement

24) “TROPICS (Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats),” eoPortal, URL: https://www.eoportal.org/satellite-missions/tropics#overview 

25) “Tropical Cyclones: Monitoring and Forecasting Using Space-Based Radar,” Space4Water, URL:https://www.space4water.org/news/tropical-cyclones-monitoring-and-forecasting-using-space-based-radar

26) “Global Precipitation Measurement (GPM) – Mission Capabilities,” eoPortal, URL:https://www.eoportal.org/satellite-missions/gpm#mission-capabilities

27) “GOES-R – Advanced Baseline Imager (ABI),” eoPortal, URL:https://www.eoportal.org/satellite-missions/goes-r#abi-advanced-baseline-imager

28) “MetOp Satellites,” EUMETSAT, URL:https://www.eumetsat.int/metop

29) “MetOp – Meteorological Operational Satellite Programme,” eoPortal, URL:https://www.eoportal.org/satellite-missions/metop

30) “MetOp-SG (MetOP-Second Generation Program,” eoPortal, URL: https://www.eoportal.org/satellite-missions/metop 

31) “News Release 753812,” EurekAlert, URL:https://www.eurekalert.org/news-releases/753812.

32) “Suomi NPP – National Polar-orbiting Partnership,” eoPortal, URL:https://www.eoportal.org/satellite-missions/suomi-npp

33) “SMOS – Soil Moisture and Ocean Salinity Mission,” eoPortal, URL:https://www.eoportal.org/satellite-missions/smos

34) “SMOS Data Access Portal,” ESA, URL:https://smos-diss.eo.esa.int/oads/access/

35) "Warming oceans probably fueling Hurricane Melissa’s rapid intensification", The Guardian, URL: https://www.theguardian.com/world/2025/oct/27/hurricane-melissa-warming-oceans-climate-crisis

36) "Copernicus, Sentinel-2 captures a vivid view of hurricane Melissa's eye", Copernicus, URL: https://www.copernicus.eu/en/media/image-day-gallery/sentinel-2-captures-vivid-view-hurricane-melissas-eye

37) Satlib, URL: https://satlib.cira.colostate.edu/wp-content/uploads/sites/23/2025/10/20251026001021-20251029145020_g19_abi_fd_ir13_majormelissa_labels.mp4

38) "Satellite images reveal Jamaica devastation as Melissa tears through Cuba", Sydney Morning Herald, URL: https://www.smh.com.au/world/central-america/hurricane-melissa-leaves-dozens-dead-across-cuba-haiti-and-jamaica-20251030-p5n6dg.html

 

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