Zorana Jelenak

The CYGNSS nanosatellite constellation hurricane mission

The Cyclone Global Navigation Satellite System (CYGNSS) is a spaceborne mission concept focused on tropical cyclone (TC) inner core process studies. CYGNSS attempts to resolve the principle deficiencies with current TC intensity forecasts, which lies in inadequate observations and modeling of the inner core. CYGNSS consists of 8 GPS bistatic radar receivers deployed on separate nanosatellites. The primary science driver is rapid sampling of ocean surface winds in the inner core of tropical cyclones.

New Ocean Winds Satellite Mission to Probe Hurricanes and Tropical Convection

AbstractThe Cyclone Global Navigation Satellite System (CYGNSS) is a new NASA earth science mission scheduled to be launched in 2016 that focuses on tropical cyclones (TCs) and tropical convection. The mission’s two primary objectives are the measurement of ocean surface wind speed with sufficient temporal resolution to resolve short-time-scale processes such as the rapid intensification phase of TC development and the ability of the surface measurements to penetrate through the extremely high precipitation rates typically encountered in the TC inner core. The mission’s goal is to support significant improvements in our ability to forecast TC track, intensity, and storm surge through better observations and, ultimately, better understanding of inner-core processes. CYGNSS meets its temporal sampling objective by deploying a constellation of eight satellites. Its ability to see through heavy precipitation is enabled by its operation as a bistatic radar using low-frequency GPS signals. The mission will depl...

The NASA EV-2 Cyclone Global Navigation Satellite System (CYGNSS) mission

The NASA EV-2 Cyclone Global Navigation Satellite System (CYGNSS) is a spaceborne mission focused on tropical cyclone (TC) inner core process studies. CYGNSS attempts to resolve the principle deficiencies with current TC intensity forecasts, which lies in inadequate observations and modeling of the inner core. The inadequacy in observations results from two causes: 1) Much of the inner core ocean surface is obscured from conventional remote sensing instruments by intense precipitation in the eye wall and inner rain bands. 2) The rapidly evolving (genesis and intensification) stages of the TC life cycle are poorly sampled in time by conventional polar-orbiting, wide-swath surface wind imagers. CYGNSS is specifically designed to address these two limitations by combining the all-weather performance of GNSS bistatic ocean surface scatterometry with the sampling properties of a constellation of satellites.

The GNSS Reflectometry Response to the Ocean Surface Winds and Waves

This paper investigates the global navigation satellite system-reflectometry (GNSS-R) measurements collected by the space GNSS receiver-remote sensing instrument (SGR-ReSI) on board the TechDemoSat-1 (TDS-1) satellite. The sensitivity of the SGR-ReSI measurements to the ocean surface winds and waves is characterized. The correlation with sea surface temperature (SST), wind direction, and rain is also investigated. The SGR-ReSI measurements exhibit clear sensitivity to wind speeds up to 20 m/s. There is also apparent sensitivity to 35 m/s wind speeds although the collocation dataset becomes sparser. A dependence on the swell is also observed for winds <;6 m/s. Additionally, a small correlation with SST is observed in which the slope of the SGR-ReSI measurements is positive for winds <;5 m/s, and reverses for winds >5 m/s. A weak wind direction signal was also observed, and an investigation of rain impacts did not conclusively confirm any influence on the data. These results are shown through an analysis of global statistics as well as an analysis of several case studies. This publicly released SGR-ReSI dataset provided a first opportunity to comprehensively investigate the sensitivity of GNSS-R measurements to various ocean surface parameters. The upcoming NASA cyclone global navigation satellite system will utilize a similar receiver to the SGI-ReSI; therefore, this data provides a valuable prelaunch insight.

WindSat validation datasets: an overview

Since the January 6, 2003 launch of the Naval Research Laboratory satellite Coriolis, the WindSat instrument onboard has provided over a year of unprecedented polarimetric microwave measurements of the globe. The WindSat radiometer has five operating frequencies at 6.8, 10.7, 18.7, 23.8 and 37 GHz, with the 10.7, 18.7, and 37 GHz channels providing fully polarimetric signals. The primary mission of Coriolis is to exploit the unique information provided by WindSats polarimetric capabilities to retrieve the complete ocean surface wind vector (speed and direction), though the retrieval of numerous other environmental parameters is being actively pursued as well. As part of a pre-NPOESS risk reduction effort, the NOAA/NESDIS/Office of Research and Applications has been collaborating with the Naval Research Laboratorys Remote Sensing Division in the calibration/validation of WindSat in preparation for the release of WindSat data products to the scientific and operational communities. An extensive overview is presented of the WindSat calibration/validation effort being put forth at NOAA/NESDIS and the associated comparison databases constructed for that purpose. These databases include data of WindSat measurements collocated with measurements from oceanographic buoys, ships, other satellites, and global data assimilation models. The strengths and limitations of these various datasets will be discussed in detail. This includes a synopsis of the colocation strategies used in matchup database construction for comparing WindSat measurements with other satellite based measurements, focusing particularly on similar orbit SSM/I data and its use in brightness temperature calibration. In addition, the use of NCEPs Global Data Assimilation System (GDAS) as a powerful source of plentiful comparison data is explored, particularly with regard to WindSat model function development

Validation of ocean wind vector retrievals from WindSat polarimetric measurements

Using several months of WindSat measurements collocated with the NCEP Global Data Assimilation System model field, the Special Sensor Microwave Imager (SSM/I) measurements and QuikScat scatterometry measurements, we have derived an empirical geophysical model that describes radiometric vector for all WindSat channels, as a function of surface parameters: wind speed, wind direction and sea surface temperature, and atmospheric parameters: total precipitable water and cloud liquid water. This model function was then used to develop an ocean surface wind vector retrieval algorithm from WindSat polarimetric measurements. The accuracy of the retrieved wind vectors was quantified using several months of WindSat measurements collocated with the Special Sensor Microwave Imager (SSM/I) measurements and QuikSCAT scatterometry measurements.

The accuracy of high resolution winds from QuikSCAT

The accuracy of the high resolution QuikSCAT wind product was quantified using spatially and temporally collocated 10 m equivalent neutral stability winds, calculated from selected NOAA NDBC buoy measurements. Only buoys that had sample correlation higher than 1.5 were used in this validation, a total of 5704 records. The validation followed the Freilich nonlinear statistical analysis approach. This analysis of the collocated buoy-scatterometer data set yielded the following statistics for wind speed: deterministic offset -0.25 m/s; linear gain 1.02; standard deviation of component errors 1.9 m/s; and RMS error 2.2 m/s. Wind direction errors were more pronounced for lighter winds, typically for winds up to 5 m/s. The RMS directional error for buoy-QuikSCAT pairs for which /spl Delta//spl theta/<90/spl deg/ is 20.6/spl deg/.

Performance Assessment of Simulated CYGNSS Measurements in the Tropical Cyclone Environment

The capability of the cyclone global navigation satellite system (CYGNSS) to observe winds within tropical cyclones (TCs) is assessed by using simulated CYGNSS observations over 43 cyclones from 2010 to 2011. The CYGNSS end-to-end simulator (E2ES) is utilized to generate delay-Doppler maps from which wind speeds are then retrieved. These wind speeds are first compared to the high-resolution model winds input into the E2ES. For range corrected gain (RCG) values greater than 20, the CYGNSS winds have a standard deviation of 0.57 m/s relative to these model winds. An error probability lookup table is developed to improve performance for RCG values lower than 20, as well as minimizing data loss (up to 4.4%). Since actual TCs are utilized in this study, the CYGNSS winds are also compared to winds from the advanced SCATterometer (ASCAT), the Oceansat-II scatterometer, GPS dropsondes, the stepped frequency microwave radiometer, and the H*wind model analysis. The CYGNSS winds compared best to the ASCAT winds with an overall bias around -0.4 m/s, and a standard deviation less than 1.54 m/s. GPS dropsonde winds compared less favorably with a standard deviation around 7.36 m/s, which can be partially attributed to spatial and temporal sampling differences. The CYGNSS ability to retrieve the TC maximum wind is also evaluated using the national hurricane center best track maximum winds. Although the CYGNSS overall bias varied from season to season (from -4.7 m/s in the Atlantic basin-2011 to -13.0 m/s in the Atlantic basin-2010), the standard deviation remained fairly consistent.

Inter-calibration Results of the Advanced Microwave Scanning Radiometer-2 Over Ocean

In this paper, the oceanic radiometric calibration biases of the Advanced Microwave Scanning Radiometer-2 (AMSR2) onboard the Global Change Observation Mission-Water (GCOM-W1) are analyzed. The double difference (DD) approach is utilized to perform inter-sensor inter-calibration for AMSR2 with the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) as the reference radiometer. This technique utilizes radiative transfer model (RTM) simulations and near-simultaneous clear-sky ocean-only observed brightness temperatures from the two microwave radiometers to estimate and correct the radiometric biases of ocean scenes for AMSR2 on a channel by channel basis.

Validation of NOAA's Near Real-Time Ascat Ocean Vector Winds

The ASCAT, launched on board MetOp-A satellite on October 19th 2006, is a C-band scatterometer operating at 5.255 GHz using fan-beam antennae to measure near surface vector wind over the worlds ocean. NOAA produces near-real-time ASCAT wind product at 50 and 25 km resolutions. These wind data are validated against global wind field model and satellite observation from QuikSCAT. The results show ASCAT wind speed retrievals perform well for low to moderate wind speed under most weather conditions, but are underestimated for wind speeds ¿ 15 m/s. The standard deviation wind direction errors are well below 20 degrees for wind speed ¿ 5 m/s.