Measurements of near surface wind speed made by the Cyclone Global Navigation Satellite System (CYGNSS) constellation of GNSS-R satellites are evaluated and their uncertainty is assessed in two ways. A bottom-up assessment begins with a model for the error in engineering measurements and propagates that error through the wind speed retrieval algorithm analytically. A top-down assessment performs a statistical comparison between CYGNSS measurements and coincident “ground truth” measurements of wind speed. Results of the two approaches are compared. Overall performance, as determined by the top-down method, is decomposed using the bottom-up approach into its contributing sources of error. Overall root mean square (RMS) uncertainty in the CYGNSS retrievals is 1.4 m/s at wind speeds below 20 m/s. At higher wind speeds, an increase in the retrieval error is primarily caused by a decrease in the sensitivity of the ocean scattering cross section to changes in wind speed. In tropical cyclones, retrieval errors are compounded by unaccounted departures from a fully developed sea state. Overall RMS uncertainty in the CYGNSS retrievals is 17% at wind speeds above 20 m/s.

Multiple independent intercalibration techniques are used to derive calibration adjustments for the development of a fundamental climate data record of physically consistent brightness temperature data from the series of six special sensor microwave/imagers (SSM/Is). The techniques include direct polar matchups, double differencing against model simulations from reanalysis profile data, double differencing against matchups with the Tropical Rainfall Measuring Mission Microwave Imager, vicarious cold calibration, and an Amazon warm calibration. Multiple realizations of three of the five techniques have been applied using different reanalysis data and retrieval techniques to account for Earth incidence angle-dependent differences between sensors. Excellent agreement has been achieved between each of the techniques with typical spread within 0.5 K at the cold end, with slightly higher spread when the warm end estimate is included. A strategy for estimating mean intercalibration values is described with justification for the use of a simple offset based on error characteristics. Intercalibration offsets are smaller for the more recent SSM/I (<; 1 K for F14 and F15 compared with F13) and slightly larger for the older satellites (<; 2 K for F08, F10, and F11 when compared to F13).

An intercalibrated Fundamental Climate Data Record (FCDR) of brightness temperatures (Tb) has been developed using data from a total of 14 research and operational conical-scanning microwave imagers. This dataset provides a consistent 30+ year data record of global observations that is well suited for retrieving estimates of precipitation, total precipitable water, cloud liquid water, ocean surface wind speed, sea ice extent and concentration, snow cover, soil moisture, and land surface emissivity. An initial FCDR was developed for a series of ten Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) instruments on board the Defense Meteorological Satellite Program spacecraft. An updated version of this dataset, including additional NASA and Japanese sensors, has been developed as part of the Global Precipitation Measurement (GPM) mission. The FCDR development efforts involved quality control of the original data, geolocation corrections, calibration corrections to account for cross-track and time-dependent calibration errors, and intercalibration to ensure consistency with the calibration reference. Both the initial SSMI(S) and subsequent GPM Level 1C FCDR datasets are documented, updated in near real-time, and publicly distributed.

The uniaxial perpendicular and magnetocrystalline anisotropies in strained 〈100〉-oriented Ni-Cu superlattices have been determined by in-plane and out-of-plane ferromagnetic resonance and magnetization measurements for varying Ni and Cu thicknesses. X-ray-diffraction patterns of the superlattice structure for these films indicate that the Ni lattice contracts while the Cu lattice dilates along the growth direction. Utilizing the measured strain with known elastic and magnetostriction constants for bulk Ni, the calculated strain-induced magnetoelastic anisotropies due to an inverse magnetostriction are in good quantitative agreement with the experimentally determined uniaxial perpendicular anisotropies.

Global Navigation Satellite System (GNSS) Reflectometry uses reflected GNSS signals for Earth remote sensing applications. Absolute calibration of a Delay Doppler Map (DDM) requires an accurate estimate of the effective isotropic radiated power (EIRP) of the GNSS transmitter, e.g., Global Positioning System (GPS). However, variable transmit power by numerous Block II Follow-on (IIF) and II Replenishment-Modernized (IIR-M) GPS space vehicles has been observed due to their flex power mode. Nonuniformity in the GPS antenna gain patterns further complicates EIRP estimation. A dynamic calibration approach is developed to address GPS EIRP variability. It uses measurements by the direct received GPS signal to estimate GPS EIRP in the specular reflected direction and then incorporates it into the calibration of normalized bistatic radar cross section (NBRCS). Error analyses using Monte Carlo simulations and a root sum of squares (RSS) approach show that the resulting error in NBRCS is about 0.32 dB. Dynamic EIRP calibration instantaneously detects and corrects for power fluctuations in the GPS transmitters and significantly reduces errors due to GPS antenna gain azimuthal asymmetry. It allows observations with the most variable Block IIF transmitters (approximately 37% of the GPS constellation) to be included in the standard data products and further improves the calibration quality of NBRCS and geophysical data products.