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At least 253 records · Page 14

Stratosphere-to-Troposphere Transport Revealed by Ground-based Lidar and Ozonesonde at a Midlatitude Site

This paper presents ozone structures measured by a ground-based ozone lidar and ozonesonde at Huntsville, Alabama, on 27-29 April 2010 originating from a stratosphere-to-troposphere transport event associated with a cutoff cyclone and tropopause fold. In this case, the tropopause reached 6 km and the stratospheric intrusion resulted in a 2-km thick elevated ozone layer with values between 70 and 85 ppbv descending from the 306-K to 298-K isentropic surface at a rate of 5 km day1. The potential temperature was provided by a collocated microwave profiling radiometer. We examine the corresponding meteorological fields and potential vorticity (PV) structures derived from the analysis data from the North American Mesoscale model. The 2-PVU (PV unit) surface, defined as the dynamic tropopause, is able to capture the variations of the ozone tropopause estimated from the ozonesonde and lidar measurements. The estimated ozone/PV ratio, from the measured ozone and model derived PV, for the mixing layer between the troposphere and stratosphere is approximately 41 ppbv/PVU with an uncertainty of approximately 33%. Within two days, the estimated mass of ozone irreversibly transported from the stratospheric into the troposphere is between 0.07 Tg (0.9 10(exp33) molecules) and 0.11 Tg (1.3 10(exp33) molecules) with an estimated uncertainty of 59%. Tropospheric ozone exhibited enormous variability due to the complicated mixing processes. Low ozone and large variability were observed in the mid-troposphere after the stratospheric intrusion due to the westerly advection including the transition from a cyclonic system to an anticyclonic system. This study using high temporal and vertical-resolution measurements suggests that, in this case, stratospheric air quickly lost its stratospheric characteristics once it is irreversibly mixed down into the troposphere.

Kuang, Shi↗

A theory for the retrieval of virtual temperature from winds, radiances and the equations of fluid dynamics

A technique to deduce the virtual temperature from the combined use of the equations of fluid dynamics, observed wind and observed radiances is described. The wind information could come from ground-based sensitivity very high frequency (VHF) Doppler radars and/or from space-borne Doppler lidars. The radiometers are also assumed to be either space-borne and/or ground-based. From traditional radiometric techniques the vertical structure of the temperature can be estimated only crudely. While it has been known for quite some time that the virtual temperature could be deduced from wind information only, such techniques had to assume the infallibility of certain diagnostic relations. The proposed technique is an extension of the Gal-Chen technique. It is assumed that due to modeling uncertainties the equations of fluid dynamics are satisfied only in the least square sense. The retrieved temperature, however, is constrained to reproduce the observed radiances. It is shown that the combined use of the three sources of information (wind, radiances and fluid dynamical equations) can result in a unique determination of the vertical temperature structure with spatial and temporal resolution comparable to that of the observed wind.

Tzvi, G. C.↗

Development of practical multiband algorithms for estimating land-surface temperature from EOS/MODIS data

A practical multiband, hierarchical algorithm for estimating land-surface temperature from NASA's future Earth Observing System (EOS) instruments Moderate Resolution Imaging Spectroradiometer (MODIS) and Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is developed through comprehensive, accurate, radiative transfer simulations at moderate spectral steps of 1-5/cm for wide ranges of atmospheric and surface conditions. The algorithm will accept empirical or estimated information about the surface emissivity and reflectivity and the atmospheric temperature and water-vapor profiles. Ground-based and aircraft measurements are necessary to validate and improve the algorithm and to establish its quality. Its accuracy depends on the calibration accuracy of thermal infrared data, uncertainties in surface heterogeneity, and temperature-dependent atmospheric absorption coefficients. Better knowledge of land-surface spectral emissivities and more accurate coefficients for atmospheric molecular band absorption and water vapor continuum absorption are needed to develop global land-surface temperature algorithms accurate to 1-2 K.

Dozier, J.↗

A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode

Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments (e.g., coarse mode sea salt and dust versus fine mode terrestrial anthropogenic emissions, biomass burning, and maritime secondary production). For the years 2016 through 2019, we performed an analysis of 550 nm total AOD550, fine mode AOD (FAOD550; also known as FM AOD in the literature), coarse mode AOD (CAOD550), and fine mode fraction (η550) between Moderate Resolution Spectral Imaging Radiometer (MODIS) V6.1 MOD/MYD04 dark target aerosol retrievals and the International Cooperative for Aerosol Prediction (ICAP) core four multi-model consensus (C4C) of analyses/short term forecasts that assimilate total MODIS AOD550. Differences were adjudicated by the global shipboard Maritime Aerosol Network (MAN) and selected island AERONET sun photometer observations with the application of the spectral deconvolution algorithm (SDA). Through a series of conditional and regional analyses, we found divergence included regions of terrestrial influence and latitudinal dependencies in the remote oceans. Notably, MODIS and the C4C and its members, while having good correlations overall, have a persistent +0.04 to +0.02 biases relative to MAN and AERONET for typical AOD550 values (84th% < 0.28), with the C4C underestimating significant events thereafter. Second, high biases in AOD550 are largely associated with the attribution of the fine mode in satellites and models alike. Thus, both MODIS and C4C members are systematically overestimating AOD550 and FAOD550 but perform better in characterizing the CAOD550. Third, for MODIS, findings are consistent with previous reports of a high bias in the retrieved Ångström Exponent, and we diagnosed both the optical model and cloud masking as likely causal factors for the AOD550 and FAOD550 high bias, whereas for the C4C, it is likely from secondary overproduction and perhaps numerical diffusion. Fourth, while there is no wind-speed-dependent bias for surface winds <12 m s−1, the C4C and MODIS AOD550s also overestimate CAOD550 and FAOD550, respectively, for wind speeds above 12 m/s. Finally, sampling bias inherent in MAN, as well as other circumstantial evidence, suggests biases in MODIS are likely MODIS and the C4C products have their own strengths and challenges for a given climate application and discuss needed research. even larger than what was diagnosed here. We conclude with a discussion on how

Aerosols↗

(abstract) Radiometric Calibration of the Multi-angle Imaging Spectro-Radiometer

The EOS/MISR instrument has completed preflight calibration and characterization of its nine cameras. The radiometric calibration requirements includes absolute radiometric accuracy to 3 percent. To meet this challenging requirement MISR has employed detector based calibration methodology. The source, a 1.65 m integrating sphere, is spatially and spectrally featureless. Thus, when viewing scenes that are likewise homogeneous, the sensor incident radiance is easily retrieved to high accuracy. To enhance the radiance product for arbitrary scene types, however, MISR is planning to incorporate spectral out-of-band, point-spread function deconvolution, and pixel nonuniformity of response corrections. A summary of the preflight calibration is presented in this paper, as well as the error uncertainties for specific scene types with and without these processing corrections.

radiometric calibration EOS MISR↗

Remote Sensing of Clouds, Water Vapor, and Near-Surface Winds Under Various Aerosol Conditions During CAMP2Ex

The Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign took place from August – October 2019. CAMP2Ex science objectives include understanding aerosol-cloud interaction under various Meteorological conditions, and how these Meteorological phenomena affect aerosol distribution in the atmosphere. Numerous instruments were flown on the National Aeronautics and Space Administration (NASA) P-3 aircraft during 19 CAMP2Ex science flights, including the Advanced Microwave Precipitation Radiometer (AMPR) the Airborne Third Generation Precipitation Radar (APR-3), and the High Spectral Resolution Lidar 2 (HSRL2). Geophysical retrieval equations for cloud liquid water, columnar water vapor, and near-surface wind speed using AMPR brightness temperatures have been derived and tested using CAMP2Ex data. Water vapor and wind speed retrievals have been validated using in situ observations, such as dropsondes and shipborne instruments. This presentation will demonstrate these AMPR-based retrievals during CAMP2Ex, including discussions of retrieval uncertainties. Specific CAMP2Ex flights will be presented in greater detail, including inferences of other Meteorological phenomena in clear air and around precipitating and non-precipitating clouds, such as background wind speeds and potential identification of gust fronts. These analyses will be supplemented with APR-3 reflectivity and Doppler velocity data to infer microphysical processes occurring within and around selected clouds of interest. In cases where multiple remote-sensing measurements were obtained for the same cloud, a time-evolution analysis of these features may be performed. Throughout these analyses, HSRL2 data will be used to quantify aerosol properties beneath the P-3, and variations in the AMPR/APR-3 observations with respect to various aerosol conditions will be discussed.

Corey Amiot↗

Suomi-NPP VIIRS Solar Diffuser Stability Monitor Performance

When illuminated by the Sun, the onboard solar diffuser (SD) panel provides a known spectral radiance source to calibrate the reflective solar bands of the Visible Infrared Imaging Radiometer Suite on the Suomi-NPP satellite. The SD bidirectional reflectance distribution function (BRDF) degrades over time due to solar exposure, and this degradation is measured using the SD stability monitor (SDSM). The SDSM acts as a ratioing radiometer, comparing solar irradiance measurements off the SD panel to those from a direct Sun view. We discuss the design and operations of the SDSM, the SDSM data analysis, including improvements incorporated since launch, and present the results through 1000 days after launch. After 1000 days, the band-dependent H-factors, a quantity describing the relative degradation of the BRDF of the SD panel since launch, range from 0.716 at 412 nanometers to 0.989 at 926 nanometers. The random uncertainty of these H-factors is about 0.1 percent, which is confirmed by the similar standard deviation values computed from the residuals of quadratic exponential fits to the H-factor time trends. The SDSM detector gains have temperature sensitivity of up to about 0.36 percent per kelvin, but this does not affect the derived H-factors. An initial error in the solar vector caused a seasonal bias to the H-factors of up to 0.5 percent. The total exposure of the SD panel to UV light after 1000 orbits is equivalent to about 100 hours of direct sunlight illumination perpendicular to the SD panel surface.

Fulbright, Jon↗

Synergistic Retrievals of Ice in High Clouds From Elastic Backscatter Lidar, Ku-band Radar and Submillimeter Wave Radiometer Observations

In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and sub-millimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of IceWater Content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments e.g. frequencies, sensitivities, etc. are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, out of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-Means clustering algorithm. In the second step, the IWC profile is estimated using an Ensemble Kalman Smoother (EKS) algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.

Mircea Grecu↗

The 27-28 October 1986 FIRE IFO cirrus case study - Comparison of radiative transfer theory with observations by satellite and aircraft

Observations of cirrus and altocumulus clouds during the FIRE are compared to theoretical models of cloud radiative properties. Three tests are performed. First, radiances are used to compare the relationship between nadir reflectance ot 0.83 micron and beam emittance at 11.5 microns with that predicted for model calculations using spherical and nonspherical phase functions. Good agreement is found between observations and theory when water droplets dominate. Poor agreement is found when ice particles dominate, especially using spherical-particle phase functions (SPPFs). Even when compared to a laboratory-measured ice-particle phase function (IPPF), the observations show great side-scattered radiation than the theoretical calculations. Second, the anisotropy of conservatively scattered radiation is examined using simultaneous multiple angle views of the cirrus from Landsat and ER-2 aircraft radiometers. Observed anisotropy gives good agreement with theoretical calculations using the laboratory IPPF and poor agreement with an SPPF. Third, Landsat radiances at 0.83, 1.65, and 2.21 microns are used to infer particle phase and size. For water droplets, good agreement is found with particle-probe measurements in the cloud. For ice particles, the Landsat radiance observations predict an effective radius of 60 microns versus aircraft observations of about 200 microns. It is suggested that this discrepancy may be explained by uncertainty in the imaginary index of ice and by inadequate measurements of small ice particles by microphysical probes.

Wielicki, Bruce A.↗

Arctic sea ice concentrations from special sensor microwave imager and advanced very high resolution radiometer satellite data

Nearly coincident data from the special sensor microwave imager (SSM/I) and the advanced very high resolution radiometer (AVHRR) are used to compute and compare Arctic sea ice concentrations for different regions and times of the year. To help determine overall accuracies and to highlight sources of differences between passive microwave, optical wavelength, and thermal wavelength data, ice concentrations are estimated using two operational SSM/I ice concentration algorithms and with visible- and thermal-infrared wavelength AVHRR data. All algorithms capture the seasonal patterns of ice growth and melt. The ranges of differences fall within the general levels of uncertainty expected for each method and are similar to previous accuracy estimates. The estimated ice concentrations are all highly correlated, with uniform biases, although differences between individual pairs of observations can be large. On average, the NASA Team algorithm yielded 5% higher ice concentrations than the Bootstrap algorithm, while during nonmelt periods the two SSM/I algorithms agree to within 0.5%. These seasonal differences are consistent with the ways that the 19-GHz and 37-GHz microwave channels are used in the algorithms. When compared to the AVHRR-derived ice concentrations, the Team-algorithm results are more similar on average in terms of correlation and mean differences. However, the Team algorithm underestimates concentrations relative to the AVHRR output by 6% during cold months and overestimates by 3% during summer. Little seasonal difference exists between the Bootstrap and AVHRR results, with a mean difference of about 5%. Although the mean differences are less between the SSM/I-derived concentrations and concentrations estimated using AVHRR channel 1, the correlations appear substantially better between the SSM/I data and concentrations derived from AVHRR channel 4, particularly for the Team algorithm output.

Emery, W. J.↗

Improving the Accuracy of Satellite Sea Surface Temperature Measurements by Explicitly Accounting for the Bulk-Skin Temperature Difference

The focus of this research was to determine whether the accuracy of satellite measurements of sea surface temperature (SST) could be improved by explicitly accounting for the complex temperature gradients at the surface of the ocean associated with the cool skin and diurnal warm layers. To achieve this goal, work was performed in two different major areas. The first centered on the development and deployment of low-cost infrared radiometers to enable the direct validation of satellite measurements of skin temperature. The second involved a modeling and data analysis effort whereby modeled near-surface temperature profiles were integrated into the retrieval of bulk SST estimates from existing satellite data. Under the first work area, two different seagoing infrared radiometers were designed and fabricated and the first of these was deployed on research ships during two major experiments. Analyses of these data contributed significantly to the Ph.D. thesis of one graduate student and these results are currently being converted into a journal publication. The results of the second portion of work demonstrated that, with presently available models and heat flux estimates, accuracy improvements in SST retrievals associated with better physical treatment of the near-surface layer were partially balanced by uncertainties in the models and extra required input data. While no significant accuracy improvement was observed in this experiment, the results are very encouraging for future applications where improved models and coincident environmental data will be available. These results are included in a manuscript undergoing final review with the Journal of Atmospheric and Oceanic Technology.

Wick, Gary A.↗

SMAP MISSION STATUS AND PLAN

The National Aeronautics Space Administration’s (NASA’s) Soil Moisture Active Passive (SMAP) mission will be completing its first extension phase in August 2020. The uncertainty of SMAP soil moisture products is ≤ 0.04 m3/m3. During the first extension phase, SMAP data have been used to advance our understanding of water, energy and carbon cycles. Significant progress has also been made to transition the use of SMAP data to operational communities. In particular, the United States Air Force (USAF) and United States Department of Agriculture (USDA)Foreign Agriculture Service (FAS) have included SMAP data in their operational forecast systems. The SMAP project has been performing a recalibration of radiometer data using four years of cold sky maneuver data. The recalibrated data and updated soil moisture and freeze/thaw products will be presented during the meeting. The SMAP project is preparing an extension proposal to continue the data acquisition and processing activities for another three years (2021-2023) and also identifying additional activities for 2024-2026. We will describe the activities for the second extension phase, including plans for SMAPVEX20 and ’22 field campaigns.

Simon H. Yueh↗

PACE OCI Flight Unit Pre-launch Spectral Characterization

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission [1] will extend and improve the data record of NASA’s satellite observations of global ocean biology, aerosols, and clouds. The Ocean Color Instrument (OCI) is the primary sensor on-board the PACE platform [2]. The OCI is a scanning radiometer with hyperspectral coverage from the ultraviolet (UV) to the near infrared (NIR) wavelength range and a fiber-coupled multiband filter spectrograph in the short-wave infrared (SWIR) spectral region. The OCI Flight Unit completed system level testing in November 2022 at the Goddard Space Flight Center (GSFC). This paper presents the spectral characterization and performance of the OCI Flight Unit. The OCI Flight spectral performance was determined to be within design specifications and the characterization was measured within specified uncertainties.

PACE↗

Pace Oci Flight Unit Pre-Launch Spectral Characterization

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission [1] will extend and improve the data record of NASA’s satellite observations of global ocean biology, aerosols, and clouds. The Ocean Color Instrument (OCI) is the primary sensor on-board the PACE platform [2]. The OCI is a scanning radiometer with hyperspectral coverage from the ultraviolet (UV) to the near infrared (NIR) wavelength range and a fiber-coupled multiband filter spectrograph in the short-wave infrared (SWIR) spectral region. The OCI Flight Unit completed system level testing in November 2022 at the Goddard Space Flight Center (GSFC). This paper presents the spectral characterization and performance of the OCI Flight Unit. The OCI Flight spectral performance was determined to be within design specifications and the characterization was measured within specified uncertainties.

PACE↗

NASA's CLARREO Pathfinder Mission: The Reflected Solar’s First SITSat

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder mission will take reflected solar (RS) highly accurate measurements needed to monitor Earth’s climate and will be the first RS SI-traceable Satellite Sensor (SITSat). The mission includes a RS spectrometer that will be installed on the International Space Station (ISS) and take measurements for at least one year. CLARREO Pathfinder (CPF) will use on-orbit calibration to achieve an unprecedented high accuracy with SI-traceability and the inter-calibration of other on-orbit instruments. The spectrometer is based on the HyperSpectral Imager for Climate Science (HySICS) instrument developed by the University of Colorado/Laboratory for Atmospheric and Space Physics of Boulder, CO, USA. HySICS is being designed to have a radiometric uncertainty of 0.3% (1-sigma), a five to ten times improvement over existing spaceflight RS instruments. High accuracy SI-traceable measurements such as these are critical to develop long-term climate-quality data sets. Additionally, by measuring spectral reflectance with high accuracy the CPF instrument will serve as an on-orbit intercalibration radiometric reference for operational Earth-viewing sensors, such as the Clouds and Earth’s Radiant Energy System (CERES) broadband shortwave instrument and the Visible/Infrared Imaging Radiometer Suite (VIIRS). Two-axis pointing, a spectral range from 350 nm to 2300 nm, and a spectral resolution ≤6 nm enable CPF to provide nearly coincident temporal, spatial, angular, and spectral matching of intercalibration targets, with sampling sufficient to reduce random errors. The intercalibration method will refine knowledge of target sensors’ effective offsets, gain, non-linearity, spectral response, and polarization sensitivity (as is relevant). Calibrated reflectance and reflected radiance spectra will be distributed to the scientific community through a NASA Distributed Active Archive Center (DAAC). We will present an overview of the CLARREO Pathfinder mission, its anticipated impact on monitoring climate variability, and the novel CPF direct intercalibration approach.

climate↗

A Mesoscale Analysis of Column-Integrated Aerosol Properties in Northern India During the TIGERZ 2008 Pre-Monsoon Period and a Comparison to MODIS Retrievals

The Indo-Gangetic Plain (IGP) of the northern Indian subcontinent produces anthropogenic pollution from urban, industrial and rural combustion sources nearly continuously and is affected by convection-induced winds driving desert and alluvial dust into the atmosphere during the premonsoon period. Within the IGP, the NASA Aerosol Robotic Network (AERONET) project initiated the TIGERZ measurement campaign in May 2008 with an intensive operational period from May 1 to June 23, 2008. Mesoscale spatial variability of aerosol optical depth (AOD, tau) measurements at 500mn was assessed at sites around Kanpur, India, with averages ranging from 0.31 to 0.89 for spatial variability study (SVS) deployments. Sites located downwind from the city of Kanpur indicated slightly higher average aerosol optical depth (delta Tau(sub 500)=0.03-0.09). In addition, SVS AOD area-averages were compared to the long-tenn Kanpur AERONET site data: Four SVS area-averages were within +/- 1 cr of the climatological mean of the Kanpur site, while one SVS was within 2sigma below climatology. For a SVS case using AERONET inversions, the 440-870mn Angstrom exponent of approximately 0.38, the 440-870mn absorption Angstrom exponent (AAE) of 1.15-1.53, and the sphericity parameter near zero suggested the occurrence of large, strongly absorbing, non-spherical aerosols over Kanpur (e.g., mixed black carbon and dust) as well as stronger absorption downwind of Kanpur. Furthermore, the 3km and lOkm Terra and Aqua MODIS C005 aerosol retrieval algorithms at tau(sub 550) were compared to the TIGERZ data set. Although MODIS retrievals at higher quality levels were comparable to the MODIS retrieval uncertainty, the total number of MODIS matchups (N) were reduced with subsequent quality levels (N=25, QA>=0; N=9,QA>=l; N=6, QA>=2; N=1, QA=3) over Kanpur during the premonsoon primarily due to the semi-bright surface, complex aerosol mixture and cloud-contaminated pixels. The TIGERZ 2008 data set provided a unique opportunity to measure the spatial and temporal variations of aerosol loading in the IGP. The strong aerosol absorption derived from ground-based sun/sky radiometer measurements suggested the presence of a predominately black carbon and dust mixture during the pre-monsoon period. Consistent with the elevated heat-pump hypothesis, these absorbing aerosols found across Kanpur and the greater IGP region during the pre-monsoon period likely induced regional atmospheric warming, which lead to a more rapid advance of the southwest Asian monsoon and above normal precipitation over northern India in June 2008.

Giles, D. M.↗

Land Surface Temperature Measurements from EOS MODIS Data

We applied the multi-method strategy of land-surface temperature (LST) and emissivity measurements in two field campaigns this year for validating the MODIS LST algorithm. The first field campaign was conducted in Death Valley, CA, on March 3rd and the second one in Railroad Valley, NV, on June 23-27. ER2 MODIS Airborne Simulator (MAS) data were acquired in morning and evening for these two field campaigns. TIR spectrometer, radiometer, and thermistor data were also collected in the field campaigns. The LST values retrieved from MAS data with the day/night LST algorithm agree with those obtained from ground-based measurements within 1 C and show close correlations with topographic maps. The band emissivities retrieved from MAS data show close correlations with geological maps in the Death Valley field campaign. The comparison of measurement data in the latest Railroad Valley field campaign indicates that we are approaching the goals of the LST validation: LST uncertainty less than 0.5 C, and emissivity uncertainty less than 0.005 in the 10-13 spectral range. Measurement data show that the spatial variation in LST is the major uncertainty in the LST validation. In order to reduce this uncertainty, a new component of the multi-method strategy has been identified.

Wan, Zhengming↗

Switched-beam radiometer front-end network analysis

The noise figure performance of various delay-line networks fabricated from microstrip lines with varying number of elements was investigated using a computer simulation. The effects of resistive losses in both the transmission lines and power combiners were considered. In general, it is found that an optimum number of elements exists, depending upon the resistive losses present in the network. Small resistive losses are found to have a significant degrading effect upon the noise figure performance of the array. Extreme stability in switching characteristics is necessary to minimize the nondeterministic noise of the array. For example, it is found that a 6 percent tolerance on the delay-line lengths will produce a 0.2 db uncertainty in the noise figure which translates into a 13.67 K temperature uncertainty generated by the network. If the tolerance can be held to 2 percent, the uncertainty in noise figure and noise temperature will be 0.025 db and 1.67 K, respectively. Three phase shift networks fabricated using a commercially available PIN diode switch were investigated. Loaded-line phase shifters are found to have desirable RF and noise characteristics and are attractive components for use in phased-array networks.

Trew, R. J.↗