GPS signals bouncing off the ocean, raw stage (CYGNSS)
What it measures. Calibrated maps of GPS-like signals bouncing off the ocean surface (delay-Doppler maps), expressed as received power and radar cross-section, along with many engineering and quality measurements.
How it's made. This is an early-stage (Level 1) product from the reflected-signal instrument aboard NASA's CYGNSS satellite constellation, with up to 8 satellites each contributing a daily data file.
How & where you'd use it. A low-level building-block input mainly used by scientists to derive ocean wind speeds, especially in tropical storms and hurricanes; most users work with higher-level wind products rather than these raw maps.
What's measured
Coverage & cadence
- Time span2018-08-01 → ongoing
- Measured byCYGNSS (DDMI)
- Processing levelLevel 1
- Spatial extent-180, -40, 180, 40
- FormatsnetCDF-4
- StatusACTIVE
What you can do with it
- Track deforestation, fire scars and land-cover change
- Monitor crop and vegetation health (NDVI/EVI)
- Map how built-up vs. green an area is over time
Official description
This Level 1 (L1) dataset contains the Version 3.1 geo-located Delay Doppler Maps (DDMs) calibrated into Power Received (Watts) and Bistatic Radar Cross Section (BRCS) expressed in units of m2 from the Delay Doppler Mapping Instrument aboard the CYGNSS satellite constellation. This version supersedes Version 3.0; https://doi.org/10.5067/CYGNS-L1X30. Other useful scientific and engineering measurement parameters include the DDM of Normalized Bistatic Radar Cross Section (NBRCS), the Delay Doppler Map Average (DDMA) of the NBRCS near the specular reflection point, and the Leading Edge Slope (LES) of the integrated delay waveform. The L1 dataset contains a number of other engineering and science measurement parameters, including sets of quality flags/indicators, error estimates, and bias estimates as well as a variety of orbital, spacecraft/sensor health, timekeeping, and geolocation parameters. At most, 8 netCDF data files (each file corresponding to a unique spacecraft in the CYGNSS constellation) are provided each day; under nominal conditions, there are typically 6-8 spacecraft retrieving data each day, but this can be maximized to 8 spacecraft under special circumstances in which higher than normal retrieval frequency is needed (i.e., during tropical storms and or hurricanes). Latency is approximately 6 days (or better) from the last recorded measurement time. Here is a summary of improvements the calibration and processing changes to the Version 3.1 data: The CYGNSS science antenna gain patterns have been adjusted to improve the accuracy of the ocean surface scattering cross section (a.k.a. the NBRCS) calibration. They are adjusted so that the annual average observed NBRCS matches the model-predicted average as derived from Wavewatch-3 estimates of the surface roughness with the appropriate spectral tail extension added to the roughness spectrum. The adjustment is made independently at each position in the science antenna pattern. A correction for coarse quantization effects by the on-board digital processor has also been added. This reduces the effects of radio frequency interference, which appeared as calibration biases in the v3.0 L1 NBRCS and retrieval biases in the v3.0 L2 wind speed that were persistent at certain locations.
Get the data
import earthaccess
earthaccess.login(strategy="netrc") # free Earthdata Login
results = earthaccess.search_data(
short_name="CYGNSS_L1_V3.1",
version="3.1",
bounding_box=(-122.5, 37.2, -121.8, 37.9), # your area (W,S,E,N)
temporal=("2024-01-01", "2024-12-31"), # your dates
)
files = earthaccess.open(results) # stream straight from POCLOUD Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package. Official links
- Data Use and Citation Guidelines VIEW RELATED INFORMATION
- Forum Post Capturing Changes to CYGNSS Sampling Rate VIEW RELATED INFORMATION
- Google Sheet Log of Anomalous CYGNSS Sampling Events VIEW RELATED INFORMATION
- Gleason, S., C. Ruf, M. P. Clarizia, A. O'Brien, 'Calibration and Unwrapping of the Normalized Scattering Cross Section for the Cyclone Global Navigation Satellite System (CYGNSS)', IEEE Trans. Geosci. Remote Sens., doi:10.1109/TGRS.2015.2502245, 2016. VIEW RELATED INFORMATION
- Ruf, C., R. Atlas, P. Chang, M. Clarizia, J. Garrison, S. Gleason, S. Katzberg, Z. Jelenak, J. Johnson, S. Majumdar, A. O'Brien, D. Posselt, A. Ridley, R. Rose, V. Zavorotny (2015). New Ocean Winds Satellite Mission to Probe Hurricanes and Tropical Convection. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-14-00218.1. VIEW RELATED INFORMATION
- A CYGNSS-based algorithm for the detection of inland waterbodies VIEW RELATED INFORMATION
- Ruf, C., S. Asharaf, R. Balasubramaniam, S. Gleason, T. Lang, D. McKague, D. Twigg, and D. Waliser, 2019. In-Orbit Performance of the Constellation of CYGNSS Hurricane Satellites. Bull. Amer. Meteor. Soc., 100, 2009 - 2023, https://doi.org/10.1175/BAMS-D-18-0337.1. VIEW RELATED INFORMATION
- Level 1A DDM Calibration Algorithm Theoretical Basis Document, S. Gleason, CYGNSS Project Document 148-0136, Rev 2, 20 Aug. 2018. VIEW RELATED INFORMATION