Publications citing datasets related to CYGNSS
|2018||Lake Level and Surface Topography Measured With Spaceborne GNSS‐Reflectometry From CYGNSS Mission: Example for the Lake Qinghai, Geophysical Research Letters,https://doi.org/10.1029/2018GL080976||CYGNSS Level 1 Science Data Record Version 2.1|
|2017||The nasa cygnss mission: Overview and status update, and Remote Sensing,https://doi.org/10.1109/IGARSS.2017.8127537||(No Dataset Referenced)|
|2017||Storm surge prediction with cygnss winds, Geoscience and Remote,https://doi.org/10.1109/IGARSS.2017.8127624||(No Dataset Referenced)|
|2018||Wiese, D. N. (2015). GRACE monthly global water mass grids NETCDF RELEASE 5.0. Ver. 5.0. Pasadena, CA: Physical Oceanography Distributed Active Archive Centers. https://doi.org/10.5067/TEMSC-OCL05 A new paradigm in earth environmental monitoring with the CYGNSS small satellite constellation, Scientific Reports,https://doi.org/10.1038/s41598-018-27127-4||(No Dataset Referenced)|
|2018||An Algorithm for Wind Speed Retrieval from CYGNSS Space Observatories, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium,https://doi.org/10.1109/IGARSS.2018.8517377||(No Dataset Referenced)|
|2018||Analysis of CYGNSS Data for Soil Moisture Applications, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium,https://doi.org/10.1109/IGARSS.2018.8517978||(No Dataset Referenced)|
|2018||Can we improve parametric cyclonic wind fields using recent satellite remote sensing data?, Remote Sensing,https://doi.org/10.3390/rs10121963||(No Dataset Referenced)|
|2018||Delivering hurricane science: Data processing review of the CYGNSS mission, 2018 IEEE Aerospace Conference,https://doi.org/10.1109/AERO.2018.8396664||(No Dataset Referenced)|
|2018||Ocean Wind Speed Estimation From the GNSS Scattered Power Function Volume, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ,https://doi.or/10.1109/JSTARS.2018.2856498||(No Dataset Referenced)|
|2018||11. A . O ’ B r i e n , “ E n d - t o - e n d s i m u l a t o r t e c h n i c a l m e m o ,” C Y G N S S Project Do 148-0123, 2014. [Online]. Available: https://podaac.jpl.nasa.gov/CYGNSS and http://clasp-research.engin.umich. edu/missions/cygnss/reference/148-0123_CYGNSS_E2ES_EM.pdf On the Estimation of Wind Speed Diurnal Cycles Using Simulated Measurements of CYGNSS and ASCAT, IEEE Geoscience and Remote Sensing Letters,https://doi.org/10.1109/LGRS.2018.2872354||(No Dataset Referenced)|
|2018||Enabling Sampling Properties of the Cygnss Satellite Constellation, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium,https://doi.org/10.1109/IGARSS.2018.8518454||(No Dataset Referenced)|
|2018||Improving Parametric Cyclonic Wind Fields Using Recent Satellite Remote Sensing Data, Preprints,https://10.20944/preprints201803.0095.v2||(No Dataset Referenced)|
|2018||Soil moisture sensing using spaceborne GNSS reflections: Comparison of CYGNSS reflectivity to SMAP soil moisture, Geophysical Research Letters,https://doi.org/10.1029/2018GL077905||(No Dataset Referenced)|
The Cyclone Global Navigation Satellite System (CYGNSS), launched on 15 December 2016, is a NASA Earth System Science Pathfinder Mission that is intended to collect the first frequent space‐based measurements of surface wind speeds in the inner core of tropical cyclones. Made up of a constellation of eight micro-satellites, the observatories provide nearly gap-free Earth coverage using an orbital inclination of approximately 35° from the equator, with a mean (i.e., average) revisit time of seven hours and a median revisit time of three hours. This inclination allows CYGNSS to measure ocean surface winds between approximately 38° N and 38° S latitude. This range includes the critical latitude band for tropical cyclone formation and movement.
CYGNSS has the capability to measure the ocean surface wind field with unprecedented temporal resolution and spatial coverage, under all precipitating conditions, and over the full dynamic range of wind speeds experienced in a tropical cyclone. This mission intends to accomplish this through an innovative combination of all-weather performance Global Positioning System (GPS) ocean surface reflectometry with the sampling properties of a dense constellation of eight observatories.
What makes CYGNSS unique is that it is NASA’s first mission to perform surface remote sensing using an existing Global Navigation Satellite System (GNSS)— a satellite constellation that is used to pinpoint the geographic location of a user’s receiver anywhere in the world. A number of GNSS systems are currently in operation, including: the United States’ Global Positioning System (GPS), the European Galileo, the Russian Federation’s Global Orbiting Navigation Satellite System (GLONASS), and the Chinese Beidou. CYGNSS has opted to use only the United States’ GPS constellation.
Unlike radar scatterometers (e.g., ISS-RapidScat, QuikSCAT, and ASCAT) that both emit microwave radar pulses and receive their backscattered signals, CYGNSS functions as a constellation of passive sensors that receive the signal of surface-reflected GPS pulses. One of the most well-known limitations of traditional microwave scatterometry (particularly, Ku-band) is signal degradation of the microwave pulses when passing through intense rainfall as typically observed within hurricane eyewalls, thus limiting its utility in retrieving observations of high wind speeds in this critical region of the storm. Reflected GPS signals, on the other hand, operate at a much lower microwave frequency utilized by the GPS constellation that is able to penetrate thick clouds and precipitation around the eyewall and provide the first opportunity to remotely measure inner-core wind speeds.
The goal of the mission is to study the relationship between ocean surface properties (i.e., surface wind speed), moist atmospheric thermodynamics, heat transfer, and convective dynamics in the inner core of a tropical cyclone. This will allow scientists to determine how a tropical cyclone forms, whether or not it will strengthen, and if so by how much. The successful completion of these goals will allow the mission to contribute to the advancement of tropical cyclone forecasting and tracking methods.