Results 81 to 90 of about 843 (193)

Comparing ASCAT and CYGNSS Winds near Tropical Convection

, 2019
Gradient Features identified in ASCAT (Advanced Scatterometer) data correspond well to observed CYGNSS (Cyclone Global Navigation Satellite System) wind shifts: Comparing ASCAT and CYGNSS winds near tropical convection.
Lang, Timothy, Nesbitt, Steve, Garg, Piyush, Priftis, George   +3 more
core  

Development of the CYGNSS Geophysical Model Function for Wind Speed

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019
Geophysical model functions (GMFs) are developed which map the Level 1 observables made by the Cyclone Global Navigation Satellite System (CYGNSS) radar receivers to ocean surface wind speed. The observables are: 1) the normalized bistatic radar cross section ( σo ) of the ocean surface; and 2) the slope of the leading edge of the radar return pulse ...
Christopher S. Ruf, Rajeswari Balasubramaniam   +1 more
openaire   +1 more source

An Improved Blackbody Calibration Cadence for CYGNSS

IEEE Transactions on Geoscience and Remote Sensing, 2022
Charles E. Powell, Christopher S. Ruf, Anthony Russel   +2 more
openaire   +1 more source

NASA CYGNSS Mission Applications Workshop

, 2015
NASA's Cyclone Global Navigation Satellite System, (CYGNSS), mission is a constellation of eight microsatellites that will measure surface winds in and near the inner cores of hurricanes, including regions beneath the eyewall and intense inner rainbands ...
Amin, Aimee V., Molthan, Andrew, Stough, Timothy M., Murray, John J.   +3 more
core  

Determining Tropical Cyclone Surface Wind Speed Structure and Intensity with the CYGNSS Satellite Constellation

, 2017
The Cyclone Global Navigation Satellite System (CYGNSS) consists of a constellation of eight microsatellites that provide observations of surface wind speed in all precipitating conditions.
Christopher S. Ruf, Mary Morris
core   +1 more source

An Illustration of FY-3E GNOS-R for Global Soil Moisture Monitoring. [PDF]

Sensors (Basel), 2023
Yang G, Du X, Huang L, Wu X, Sun L, Qi C, Zhang X, Wang J, Song S.   +8 more
europepmc   +1 more source

A Merged CYGNSS Soil Moisture Product Using a Minimum Variance Estimator

peer reviewedData from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission have shown promise for the retrieval of soil moisture, and many soil moisture products using CYGNSS data have been developed.
Hayashi, Akiko, Senyurek, Volkan, Shah, Rashmi, Al-Khaldi, Mohammad, Small, Eric E., Johnson, Joel T., Yueh, Simon H., SETTI JUNIOR, Paulo de Tarso, Bai, Dinan, Gurbuz, Ali Cafer, Hodges, Erik, Ouellette, Jeffrey D., Ruf, Christopher S., Chew, Clara, Santi, Emanuele, Pettinato, Simone, Moghaddam, Mahta, TABIBI, Sajad, Lei, Fangni, Xu, Xiaolan, Nabi, M M, Kurum, Mehmet   +21 more
core   +1 more source

From theory to hydrological practice: Leveraging CYGNSS data over seven years for advanced soil moisture monitoring

Soil moisture (SM) is a key variable in hydrometeorology and climate systems. With the growing interest in capturing fine-scale SM variability for effective hydroclimate applications, spaceborne L-band bistatic radar systems using Global Navigation ...
Nguyen, Hoang Hai, Wigneron, Jean-Pierre, Kim, Hyunglok, Lei, Fangni, Wagner, Wolfgang, Colliander, Andreas, Crow, Wade, Yueh, Simon, Frappart, Frédéric   +8 more
core   +2 more sources

Effects of microplastics and surfactants on surface roughness of water waves. [PDF]

Sci Rep, 2023
Sun Y, Bakker T, Ruf C, Pan Y.
europepmc   +1 more source

Matched Filter Cyclone Maximum Wind Retrievals Using CYGNSS: Progress Update and Error Analysis. [PDF]

IEEE J Sel Top Appl Earth Obs Remote Sens, 2021
Al-Khaldi MM, Katzberg SJ, Johnson JT, Kang Y, Kubatko EJ, Gleason S.   +5 more
europepmc   +1 more source