Notes from the Field

NASA recently completed its senior review process for Earth science missions and CYGNSS has been approved to continue science operations through 2023. Another senior review will occur then. The constellation of eight spacecraft are healthy and operating nominally in their orbits 524 kilometers above the Earth. They continue to make 24/7 measurements of ocean surface winds, both globally and in tropical cyclones, to help understand meteorological processes and improve numerical weather forecasts. Over land, measurements of flood inundation, water body extent, and soil moisture are used in hydrological process studies and for disaster monitoring.

An extreme precipitation event occurred in northwestern Iraq on 22-23 Nov 2018, causing major flooding in Ninewa and Salah al-Din governorates. The Sep 2018 CYGNSS SNR map (left) before the flooding provides a baseline. The Nov-Dec 2018 SNR map (right) identifies flooded regions by large increases in SNR, highlighted as the yellow/green areas. (Credit: C. Chew, UCAR)

Our ability to forecast the strengthening of hurricanes has been improved by CYGNSS measurements of their inner core winds, which allow us to track the transfer of energy from the warm ocean water into the atmosphere in the form of latent heat flux. Currently, CYGNSS data are being used in re-analysis investigations; that is, revisiting old hurricane forecasts with new CYGNSS data added to see how the predictions are improved. Eventually, the goal is to use the data directly in operational forecasting by NOAA’s National Hurricane Center. CYGNSS wind observations can also be used to provide better estimates of the location of the hurricane, as reported in 2019 in the Journal of Applied Meteorology and Climatology.

Wind speed measurements of Hurricane Sergio on October 7, 2019, made by the constellation of CYGNSS satellites over a three hour period (10:30-13:30 OTC) are composited together in a storm centric coordinate system to provide a center fix on the location of the eye. (Ref. Mayers & Ruf, 2019)

Measurements by CYGNSS over land are used to determine soil moisture content under dense vegetation. This, in turn, allows for the identification of conditions conducive to major locust outbreaks in East Africa. Locating locust breeding grounds before the insects are mature and able to fly provides a unique opportunity for eradication efforts on the ground. This capability is being investigated through a partnership between members of the CYGNSS science team, NASA SERVIR, the U.S. Agency for International Development (USAID), and the United Nations Food and Agriculture Organization (FAO). For more information, refer to this Image of the Day published in March 2020.

With NASA’s continued support, CYGNSS will be able to continue with its investigations supporting a better understanding of and ability to forecast tropical cyclones, and to expand its investigations into novel applications over land.

Happy Birthday, CYGNSS! Three years on orbit

December 16th, 2019 by Chris Ruf

CYGNSS was launched on December 15, 2016 at 13:27:21 UTC and today marks the completion of its third year on orbit. Much has happened in that time and the future looks very promising, with all eight microsatellites healthy and operating continuously in their nominal science data-taking mode. Year 1 was spent on engineering commissioning and initial ocean wind measurements. In year 2, the ocean wind retrievals were refined and characterized and investigations of observations over land began in earnest. This past year has seen progress on several fronts. An important refinement to the engineering calibration has been developed. Ocean wind measurements in tropical cyclones have been successfully introduced into numerical hurricane forecast models. And the ability to image inland waterbodies with high resolution has been leveraged to demonstrate two new measurement capabilities.

CYGNSS measures the strength of GPS signals reflected by the Earth surface, from which properties of the surface are derived. To do this accurately requires knowledge of the signal strength transmitted by the GPS satellite. The original approach to calibration assumed each GPS satellite had a unique transmit power level and that it did not vary in time. The unique power levels were estimated using measurements averaged over several months. Subsequent analysis has revealed that GPS transmit power can vary significantly, depending on the particular satellite and on its position in orbit. In order to compensate for the changes, the direct signal GPS receivers on all eight CYGNSS satellites were reprogrammed in 2018 to act as power meters which can monitor the variations in transmit power [Wang et al., 2019. A Real-Time EIRP Level 1 Calibration Algorithm for the CYGNSS Mission using the Zenith Measurements. Proc. IGARSS 2019]. The impact of this change is illustrated in the following figure. The top panel shows the geographical distribution of the average error in CYGNSS wind speed for a single GPS transmitter (SVN 63) assuming its transmit power is constant. The center panel shows the actual GPS transmit power as measured by the new on-board monitoring system. Clear localized differences in the measured power are evident which correlate with the errors in wind speed. The bottom panel shows the distribution of average wind speed error after the monitored power is incorporated into the calibration. The discrepancies have been largely removed.

CYGNSS wind speed bias before (top) and after (bottom) a dynamic correction was added for variations in GPS transmit power.

Over the past year, CYGNSS ocean wind measurements have been added to the HWRF numerical forecast model used by the National Hurricane Center and compared to the standard operational forecast, which does not yet use CYGNSS. To forecast a hurricane, HWRF is first initialized with satellite, airborne, and ground based measurements. The storm is then allowed to develop in software, guided by underlying physical principles of thermodynamics, radiation and mass and energy conservation. An example of this is shown in the following figure, which presents three versions of the horizontal wind speed at 3 km altitude for Hurricane Harvey on 25 Aug 2018 at 06Z. The left panel is the 24 hr forecast predicted on 24 Aug by the operational version of HWRF without CYGNSS data. The center panel is the HWRF prediction with CYGNSS winds included. Note the azimuthal shift in predicted peak winds into the northeast quadrant when CYGNSS winds are included. The right panel shows measurements made by NOAA’s airborne doppler radar of the actual winds at 3 km. The predicted azimuthal shift is confirmed, suggesting that the storm’s development is being more accurately modeled [Cui et al, 2019. A Preliminary Impact Study of CYGNSS Ocean Surface Wind Speeds on Numerical Simulations of Hurricanes. Geophys. Res. Ltrs.].

HWRF 24 hr forecasts of wind speed at 3 km altitude: (left) without; and (center) with CYGNSS winds used as inputs. The right panel shows actual 3 km winds measured by a NOAA/HRD airborne doppler radar.

More accurate modeling of storm development should help forecast the intensity of its surface winds, and this has been demonstrated by another study using HWRF [Annane et al., 2018. Impact of CYGNSS Data on Tropical Cyclone Analysis and Forecasts Using the Operational HWRF. 33rd AMS Conf. Hurricanes Trop. Meteo.]. In this case, a 120 hr forecast of minimum sea level pressure (MSLP) in the eye of Hurricane Michael was conducted on 8 Oct 2018 at 00Z without and with CYGNSS winds included as one of the inputs. The left panel in the following figure shows the true (best track) MSLP in black and the operational forecast (without CYGNSS) in red. The rapid drop in MSLP that occurred between ~30-60 hr is not well forecast. The right panel shows the HWRF forecast with CYGNSS winds included and can be seen to more accurately predict the rapid intensification of the storm.

HWRF forecast of minimum sea-level pressure in the eye of Hurricane Michael shown in red: (left) without; and (right) with CYGNSS winds used as input. Best track MSLP shown in black.

CYGNSS measurements over land are able to provide high resolution tracks across inland waterbodies when the surface is calm enough to support coherent specular scattering. A new land/water mask has been developed which leverages this capability as well as the ability of CYGNSS to penetrate through clouds, rain and vegetation canopies. As a result, dynamic changes in waterbodies (e.g. due to flooding, seasons or human development) can be resolved better than existing water masks that rely on optical satellite imagers. [Gerlein-Safdi and Ruf, 2019. A CYGNSS-Based Algorithm for the Detection of Inland Waterbodies, Geophys. Res. Ltrs.]. An example of this new capability is shown in the seasonal watermasks of the Okavango Delta in Botswana derived from CYGNSS overpasses in 2018. The left panel, for Dec/Jan/Feb, shows the typical river boundaries that are present during the dry season. The mask in the right panel, for Jun/Jul/Aug, captures the widespread flooding which occurs during the rainy season.

CYGNSS water masks of Okavango Delta in Botswana during the dry (left) and rainy (ight) seasons.

CYGNSS overpasses of rivers also produce high resolution tracks that can be used to measure a river’s width and infer its streamflow rate. This has been successfully demonstrated using overpasses of the Pascagoula River in Mississippi during a major flood event in April 2019 [Warnock and Ruf, 2019. Response to Variations in River Flowrate by a Spaceborne GNSS-R River Width Estimator, Remote Sens.].  Streamflow measurements by a USGS river gauge made before, during and after the event are shown in the upper panel below, together with markers at the times of each of five overpasses by CYGNSS. The lower panel shows the Associated GNSS-R Width (AGW) of the river derived from each CYGNSS overpass, together with the Pascagoula’s streamflow rate at the time.

Associated GNSS-R Width of the Pascagoula River measured by CYGNSS overpasses during a flooding event. The AWG is highly correlated with flow rate measured by a USGS streamflow gauge.

The two are highly correlated, suggesting that another new type of CYGNSS data product may be possible over inland waterbodies.

Two year anniversary of CYGNSS on orbit

December 15th, 2018 by Chris Ruf

The constellation of eight CYGNSS microsatellites reached a milestone today, completing its second year on-orbit. The first year had focused primarily on engineering commissioning, calibration and early validation of the science data products. The second year was spent continuing to refine and improve the quality of the science data products, while also applying the measurements to a number of scientific investigations. Some examples of the refined wind speed measurements are shown below for three overpasses of Hurricane Maria, on 23 Sep 2017 at 00:18 (top), 23 Sep 2017 at 00:23 (mid), and 24 Sep 2017 at 00:18 (bot).

Coincident hurricane overpasses by CYGNSS and NOAA hurricane hunter aircraft

In the figure, the green trace shows the measurements made by CYGNSS while the blue trace shows measurements made by SFMR instruments on the NOAA hurricane hunter aircraft that flew into the storms while CYGNSS was passing overhead. The CYGNSS and SFMR measurements can be seen to agree quite well. Quantitative results of the calibration and validation of CYGNSS science data products are described in a Special Issue of the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Measurements by CYGNSS of Typhoon Trami in Sep 2018, shown below, illustrate its ability to track the evolution of a storm over its full life cycle. In the figure, the lower left image is a composite over the period 20-30 Sep 2018 of all wind speed measurements made at one phase of the constellation’s orbit. The upper right insert shows all measurements made on 28 Sep 2018, with the measurements re-gridded to a storm-centric coordinate system to illustrate the wind speed structure in the inner core region.

CYGNSS wind speed measurements of Typhoon Trami

Science investigations have expanded beyond the primary mission objective to measure wind speed in tropical cyclones. The measurements are being introduced into numerical weather prediction models to assess their impact on the skill in forecasting hurricane track, intensity and structure. Early results look quite promising, with clear signs of a positive impact on forecast skill. The results will be presented in a series of talks at the annual meeting of the American Meteorological Society in January 2019.

In parallel with the activity over ocean, new science investigations are examining data over land as well. CYGNSS measurements have been found to be sensitive to the surface soil moisture, and to the presence of inland water bodies. Good examples of this are documented in recent publications. Kim and Lakshmi (2018) [doi:10.1029/2018GL078923] estimate soil moisture at numerous sites in the continental U.S. over a 12 month period and find close agreement with independent measurements made by ground sensors and another satellite. Jensen et al. (2018) [doi:10.3390/RS10091431] demonstrate the ability of CYGNSS to detect and map the extent of flood inundation under dense forest canopies. Chew et al. (2018) [doi:10.1038/S41598-018-27673-3] use this capability to produce time lapse images of flooding in and around Houston and Havana after landfalls by Hurricanes Maria and Irma, respectively. These results demonstrate the wide range of future applications of CYGNSS data as the mission moves forward into its third year.

CYGNSS Accomplishments and New Applications

June 8th, 2018 by Chris Ruf

As we head into the 2018 Atlantic hurricane season, now is a good time to reflect on the accomplishments achieved by CYGNSS since its launch in December 2016. Early mission operations focused on engineering commissioning of the satellites and of the constellation as a whole. One achievement in particular is noteworthy. The satellites have no active means of propulsion, yet their relative spacing is important for achieving the required spatial and temporal sampling. The desired spacing is achieved by individually adjusting a spacecraft’s orientation and, as a result, the atmospheric drag it experiences. This technique is referred to as “differential drag”. An increase in drag will lower a satellite’s altitude, thereby changing its orbital velocity. We adjust the distance between spacecraft by adjusting their relative velocities. This is a new way of managing the spacing between a constellation of satellites, and one that can be significantly less risky and lower in cost than using traditional active propulsion. As a result, we were able to afford more satellites for the same price, which ultimately led to better, more frequent, sampling of short lived, extreme weather events like tropical cyclones.

Here is a figure, provided by CYGNSS team member Kyle Nave of ADS, illustrating the change in relative speed between two of the CYGNSS spacecraft that occurred the first time a differential drag maneuver was performed, on February 23, 2017.

The orbital phase rate between the two spacecraft is shown before, during and after the higher of the two had its orientation changed to maximize atmospheric drag. Phase rate measures how quickly the angle between two satellites changes. By increasing the drag on the higher one, it lowers to an altitude and orbital velocity closer to the lower one, thus reducing the phase rate. This was an important first confirmation of our ability to perform the maneuver. Since then, there have been many more drag maneuvers. Five of the eight satellites are now properly positioned relative to one another at a common altitude, and the remaining three are expected to have their drag maneuvers completed later this year.

The primary science objective of the CYGNSS mission is measurement of near surface wind speed over the ocean in and near the inner core of tropical cyclones. In an earlier NASA blog, (15 Dec 2017), I reported on our measurements of Hurricane Maria made in September 2017. Since that time, we have been examining the quality of our measurements both within and away from major storms. Measurements at ocean wind speeds below 20 m/s (44 mph) were found to have an RMS uncertainty of 1.4 m/s (3 mph).  Measurements of storm force winds during the 2017 Atlantic hurricane season were found to have an uncertainty of 17% of the wind speed. The analysis that produced these results is reported in Ruf et al. (2018). DOI: 10.1109/JSTARS.2018.2825948.

CYGNSS operates continuously, over both ocean and land, and the land data have been another focus of recent investigations. The quality of some of those measurements, in particular regarding its spatial resolution, has come as something of a pleasant surprise. Here is one example of CYGNSS land imagery, of the Amazon River basin in South America, provided by Dr. Clara Chew of UCAR.

In the image, inland water bodies are prominently visible. This includes not only the major arms of the Amazon River but also its quite narrow minor tributaries. Careful examination of this and similar CYGNSS images suggests that the spatial resolution is markedly better here than it is over typical open ocean areas. The explanation lies in a transition of the electromagnetic scattering from an incoherent, rough surface regime over ocean to a largely coherent, near specular regime over inland waters. The fact that coherently scattered signals have inherently better spatial resolution is a well known phenomenon. What was unexpected is the widespread, global extent to which land surface conditions support coherent scattering. It requires the height of the surface roughness to be significantly below the wavelength of the radiowave signal, which in our case is 19 cm. This is apparently a ubiquitous property of wetland regions. It is a very fortuitous property for us, as it should enable an entirely new direction in scientific applications of CYGNSS measurements over land. NASA has recently added new investigators to the CYGNSS team specifically to study these new and exciting land applications.

A recent article summarizing these and other CYGNSS achievements, as well as some of the future applications of its measurements, is available at <www.nature.com/articles/s41598-018-27127-4>. The mission has demonstrated that smaller, more cost-efficient satellites are able to make important contributions to the advancement of science. In the months and years ahead, CYGNSS will hopefully be able to demonstrate that those advances can lead to practical scientific applications, such as extreme weather monitoring and prediction, that will benefit humankind.

First year anniversary of CYGNSS on orbit

December 15th, 2017 by Chris Ruf

CYGNSS was launched into low Earth orbit on December 15, 2016 at 08:37 EST and today is its first anniversary. The mission has had a very busy first year on orbit, transitioning from an early engineering commissioning phase into the science observing phase in time for the very active 2017 Atlantic hurricane season. The mission was supported during the hurricane season by the NOAA Airborne Operations Center (AOC), which operates a fleet of P-3 “hurricane hunter” airplanes that make reconnaissance flights into tropical storms and hurricanes to observe wind speed and other weather conditions first hand. We worked closely with AOC to coordinate many of their flight campaigns with overpasses of the storms by CYGNSS. They were able to time many of their eyewall penetrations to align closely in both time and space with our overpasses, which helps us train and evaluate our own wind speed measurements As a result, we now have dozens of coincident tracks of wind speed observations through the inner core regions of Hurricanes Harvey, Irma, Jose and Maria. The collaboration with NOAA this summer and fall has been incredibly fruitful, and I and the CYGNSS project team are very grateful for their generous support.

As the 2017 hurricane season winded down, we turned our attention to processing the coincident overpass data and characterizing and evaluating the performance of our wind speed measurements. One example is shown here. On September 24, 2017 at 18:13-18:21 UTC, the CYGNSS FM#2 spacecraft flew across Hurricane Maria.

The red line in the figure shows the track of the specular reflection from transmissions by the GPS PRN#13 satellite.  CYGNSS makes its wind measurements along this track. The black line in the figure shows the flight path of the P-3 hurricane hunter that day. A distinctive cloverleaf pattern can be seen that results from the plane making multiple eyewall penetrations. The colored portion of the P-3 flight path is the leg closest in time and space to the CYGNSS specular point track. The color scale represents the difference in time between the CYGNSS overpass and the P-3 observing time.  With such close coincidence in time and space, we hope and expect that the two measurements of wind speed will be consistent.

The next figure shows the wind speed measured by CYGNSS (blue), measured by the P-3 airplane using its Stepped Frequency Microwave Radiometer (SFMR) wind speed sensor (red), and produced by the ECMWF and GDAS numerical weather prediction (NWP) models (black) along the CYGNSS specular point track.

Away from the storm center at lower wind speeds, CYGNSS and NWP measurements agree well. Near the storm center, CYGNSS responds to the much higher wind speeds. In general, NWP models tend to underestimate peak winds in large storms and this is likely the case here. While NWP models generate winds everywhere, SFMR winds are only available along the portion of the satellite track where the P-3 airplane flew. In the region where coincident measurements were made, CYGNSS and SFMR winds can be seen to agree fairly well. It should be noted that the scatter present in the CYGNSS measurements can be seen to increase as the wind speed increases. This is probably a result of the decrease in GPS signal strength scattered in the specular direction when the sea surface is significantly roughened by high winds. How best to handle this characteristic of the CYGNSS wind speed retrievals will be an important topic of upcoming investigations.

Happy Birthday, CYGNSS!

 

p.s. and just in time for the first year anniversary of CYGNSS on orbit, new science data files using the latest (v2.0) engineering calibration and science retrieval algorithms have just been posted at the NASA PO.DAAC web site.  Access the data by going to

https://podaac.jpl.nasa.gov/dataset/CYGNSS_L1_V2.0

https://podaac.jpl.nasa.gov/dataset/CYGNSS_L2_V2.0

https://podaac.jpl.nasa.gov/dataset/CYGNSS_L3_V2.0

and selecting the ‘Data Access’ tab to reach an FTP link to the data files.