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Microwave Imager Combined Active and Passive (MICAP), which is a package of active and passive microwave instruments including L/C/K-band radiometers and L-band scatterometer, has been approved to be taken onbord the Chinese Ocean Salinity Mission. The L-band one-dimensional synthetic aperture radiometer (L-Rad) is the key part of MICAP to measure sea surface salinity (SSS). Since radio frequency interference (RFI) is reported as a serious threat to L-band radiometry, the RFI detection and mitigation techniques must be carefully designed before launch. However, these techniques need to be developed based on the knowledge of how RFI affects complex correlation, visibility function, and reconstructed brightness temperature. This paper presents a time-domain signal modeling method for the simulation of interferometric measurement under RFI’s presences, and a simulation system for L-Rad is established accordingly. Several RFI cases are simulated with different RFI types, parameters, and positions, and the RFI characteristics upon L-Rad’s measurement are discussed. The proposed simulation system will be further dedicated to the design of RFI processing strategy onboard MICAP.

The integral of lightning current squared over time, named as the “lightning action integral”, is an indicator of Joule heat generated by lightning discharge. The temperature of air molecules is thus increased, which can be observed by a ground-based microwave radiometer for atmospheric temperature remote sensing. Observational experiments were performed in early summer in 2017 with a ground-based, MWP967KV type microwave radiometer, which is commonly used for atmospheric temperature profile remote sensing but has been properly-configured this study in order to observe the artificially triggered lightning events at Guangzhou field experiment site for lightning research and test (GFESL). Data from the radiometer and the instrument for recording lightning current have been analyzed and the results from 7 effective events show that a relationship like ΔTB=exp(aX) may exist between the brightness temperature increment, ΔTB, in unit of K, observed in 30-50GHz band and the lightning action integral, X, in unit of A2s, calculated from high temporal resolution lightning current records. The correlation coefficient is as high as 0.8863 while the coefficient, a, is equal to 6.25381*10−5 (sample size = 7).

This work presents an overview of the potential of microwave indices obtained from multi-frequency/polarization radiometry in detecting the characteristics of land surfaces, in particular soil covered by vegetation or snow and agricultural bare soils. Experimental results obtained with ground-based radiometers on different types of natural surfaces by the Microwave Remote Sensing Group of IFAC-CNR starting from ‘80s, are summarized and interpreted by means of theoretical models. It has been pointed out that, with respect to single frequency/polarization observations, microwave indices revealed a higher sensitivity to some significant parameters, which characterize the hydrological cycle, namely: soil moisture, vegetation biomass and snow depth or snow water equivalent. Electromagnetic models have then been used for simulating brightness temperature and microwave indices from land surfaces. As per vegetation covered soils, the well-known tau-omega (τ-ω) model based on the radiative transfer theory has been used, whereas terrestrial snow cover has been simulated using a multi-layer dense-medium radiative transfer model (DMRT). On the basis of these results, operational inversion algorithms for the retrieval of those hydrological quantities have been successfully implemented using multi-channel data from the microwave radiometric sensors operating from satellite.

An approach for deriving atmosphere total precipitable water vapor (PWV) and surface air temperature over land using satellite passive microwave radiometry from the Advanced Microwave Scanning Radiometer 2 (AMSR2) was developed in this study. The PWV algorithm is based on theoretical analysis and comparisons against similar retrievals from the Atmospheric Infrared Sounder (AIRS). The AMSR2 PWV retrievals compare favorably with AIRS operational PWV products ( $R^{2}\geqslant 0.80$ and rmse: 4.4–5.6 mm) and independent PWV observations from the SuomiNet North American Global Positioning System station network, with an overall mean rmse of 4.7 mm and more than 78% of absolute retrieval errors below 5 mm. The PWV retrievals were then applied within an AMSR2 multifrequency brightness temperature algorithm for deriving atmosphere-corrected surface air temperatures. The estimated temperatures agree favorably ( $R^{2}>0.80$ and $\hbox{rmse} ) with independent weather station daily air temperature measurements spanning global climate and land cover variability. The resulting PWV estimates increase surface air temperature retrieval accuracy in our algorithm scheme. The AMSR2 algorithm is readily applied to similar microwave sensors including the AMSR for EOS and provides suitable performance and accuracy to support hydrologic, ecosystem, and climate change studies.

SMAP and SMOS have been successfully providing L-band brightness temperature (Tb) since 2015 and 2011, respectively [1, 2]. Since both missions provide Low Earth Orbit observation at the same frequency, inter-calibration of brightness temperatures measured from these two missions leading to a consistent Tb record is critical in order to have consistent and reliable science datasets. For a radiometer, stability testing and drift monitoring of measured brightness temperature are often performed by comparing measured Tb with estimated Tb using in-situ temperature measurement and/or higher frequency microwave observations. Therefore having one additional reference Tb measured by another radiometer will help characterize and calibrate a radiometer with higher accuracy and benefit both missions.

The detection of radio-frequency interference (RFI) continues to be an important problem for satellite-based microwave radiometers. This paper introduces two new probability-distribution-based techniques for computing the likelihood that a given brightness temperature observation contains an RFI signal. These methods extend the spectral difference method already being employed for the detection of RFI signals, and they allow for simultaneous observation-by-observation RFI detection of both land- and sea-based brightness temperature observations. This paper starts by laying out the theoretical groundwork for both techniques. It will then expand upon that groundwork to detail its practical application in analyzing WindSat brightness temperature observations. Finally, this paper compares the resulting probability indices from the detailed algorithms with spectral difference and principle component analysis indices computed from WindSat observations for various geographic regions. These comparisons will show effective RFI signal detection by these new techniques for RFI signal strengths as low as 4-5 K.

A method is applied to maintain the long-term calibration of a microwave radiometer through intersatellite calibration and is used to mitigate an observed calibration drift of the Advanced Microwave Radiometer (AMR) on Jason-2/Ocean Surface Topography Mission. The AMR provides a correction for the wet tropospheric path delay (PD) of the radar altimeter signal, and it is critical that any drift in the radiometer be estimated and removed to enable studies of global mean sea-level variability. The intersatellite calibration method transfers the long-term calibration from other satellite microwave radiometers using a transfer function to map the other sensor's brightness temperature (TB) observations to those of the AMR. Intersensor mapping functions are derived separately for ocean observations and observations over the Amazon rainforest. This provides a warm and cold TB calibration reference to enable the distinction between long-term gain and offset drifts. A database of co-incident observations is generated between the AMR and conically scanning microwave sensors, namely, AMSR-E, TMI, and SSMIS. Monthly averaged differences are found between the AMR and the AMR equivalent TBs computed from the reference sensors. The apparent change in the AMR calibration determined from the three reference sensors is intercompared between the sensors and compared to that determined using natural on-Earth references. It is found that apparent trends in the AMR TBs between the reference sensors and the natural on-Earth references agree within a month to better than 0.4 K. The AMR 18.7- and 23.8-GHz channels are found to be stable to 0.5 K over the first three years of the mission, and the calibration 34.0-GHz channel is found to drift downward by approximately 6 K. In all channels, the calibration change is determined to be a series of offset jumps (independent of TB). These calibration changes in each AMR channel are estimated and removed using the comparisons to the reference sensors. The uncertainty in the PD long-term stability after recalibration is estimated to be less than 0.5 mm/year from July 2008 to August 2011.

The double difference method of inter-calibration between spaceborne microwave radiometers is combined with the vicarious cold calibration method for calibrating an individual radiometer. Vicarious cold calibration minimizes the effects of geophysical variability on radiative transfer models (RTMs) of the brightness temperature (TB) data and it accounts for frequency and incidence angle dissimilarity between radiometers. Double differencing reduces the sensitivity of the inter-calibration to RTM error and improper accounting for geophysical variables in the RTM. When combined together, the two methods significantly improve the confidence with which calibration differences can be identified and characterized. This paper analyzes the performance of the vicarious cold calibration double difference method for conical scanning microwave radiometers and quantifies the improvement this method provides compared to performing a simpler inter-calibration by direct comparison of radiometer measurements.

Modeling of snow emission at microwave frequencies is necessary in order to understand the complex relations between the emitted brightness temperature and snowpack characteristics such as density, grain size, moisture content, and vertical structure. Several empirical, semiempirical, and purely theoretical models for the prediction of snow emission properties have been developed in recent years. In this paper, we investigate the capability of one such model to simulate snow emission during the peak snow season-a new multilayer version of the Helsinki University of Technology (HUT) snow model. Developed with a single layer, the original HUT model was easily applied over large geographic areas for the estimation of snow cover characteristics by model inversion. A single homogenous layer, however, may not accurately allow the simulation of vertically structured natural snowpacks. The new modification to the model allows the simulation of emission from a snowpack with several snow or ice layers, with the individual component layers treated as in the original HUT model. The results of modeled snowpack emission, using both the original model and the new multilayer modification, are compared with reference measurements made using ground-based radiometers deployed in Finland and Canada. Detailed in situ measurements of the snowpack are used to set the model inputs. We show that, in most cases, use of the multiple-layer model improves estimates for the higher frequencies tested, with up to 38% improvement in rms error. In some cases, however, the use of the multiple-layer model weakens model performance particularly at lower frequencies.

The purpose of the Soil Moisture and Ocean Salinity (SMOS) mission is to measure soil moisture and sea surface salinity (SSS). The measurement of SSS using microwave radiometry requires a very sensitive instrument. In SMOS, the image is formed using the interferometric technique complemented by the average brightness temperature, or zero baseline, to set the absolute level of the image. Therefore, the measurement of the zero baseline is very critical for the success of the mission. In this paper, the radiometric resolution and stability of the radiometers dedicated to the measurement of zero baseline on SMOS are estimated. The results of a measurement campaign carried out in an anechoic electromagnetic compatibility chamber are used. The results show that the zero-baseline radiometers have the potential for relative accuracy better than 20 mK, depending on the integration scenario, satisfying the mission requirement for SSS retrieval.

Quantitative precipitation forecasting is currently limited by the paucity of observations on sufficiently fine temporal and spatial scales. Three-dimensional water vapor fields can be retrieved with improved spatial coverage from measurements obtained using a network of scanning microwave radiometers. To investigate this potential, an observation system simulation experiment was performed in which synthetic examples of retrievals using a network of radiometers were compared with results from the Weather Research and Forecasting model at a grid scale of 500 m. These comparisons show that the 3-D water vapor field can be retrieved with an accuracy of better than 15%-20%. A ground-based demonstration network of three compact microwave radiometers was deployed at the Atmospheric Radiation Measurement Southern Great Plains site in Oklahoma. Results using these network measurements demonstrated the first retrieval of the 3-D water vapor field in the troposphere at fine spatial and temporal resolutions.

Ground-based observations from two different radiometers are used to evaluate commonly used microwave/millimeter-wave propagation models at 150 GHz. This frequency has strong sensitivity to changes in precipitable water vapor (PWV) and cloud liquid water. The observations were collected near Hesselbach, Germany, as part of the Atmospheric Radiation Measurement program's support of the General Observing Period and the Convective and Orographic Precipitation Study. The observations from the two radiometers agree well with each other, with a slope of 0.993 and a mean bias of 0.12 K. The observations demonstrate that the relative sensitivity of the different absorption models to PWV in clear-sky conditions at 150 GHz is significant and that four models differ significantly from the observed brightness temperature. These models were modified to get agreement with the 150-GHz observations, where the PWV ranged from 0.35 to 2.88 cm. The models were modified by adjusting the strength of the foreign- and self-broadened water vapor continuum coefficients, where the magnitude was model dependent. In all cases, the adjustment to the two components of the water vapor continuum was in opposite directions (i.e., increasing the contribution from the foreign-broadened component while decreasing contribution from the self-broadened component or vice versa). While the original models had significant disagreements relative to each other, the resulting modified models show much better agreement relative to each other throughout the microwave spectrum. The modified models were evaluated using independent observations at 31.4 GHz.

Monitoring atmospheric water is essential for the understanding of the dynamic processes of the atmosphere and for the assessment of wave-propagation properties. Microwave radiometers, in combination with a thermal infrared channel, have the potential to fulfill these tasks. This paper is focused on the surface-based system TROWARA with microwave channels at 21.3 and 31.5 GHz. TROWARA has been used for tropospheric water measurements at Bern since 1994 together with a standard meteo station. So far, emphasis has been put on integrated water vapor (IWV) measurements, particularly for climate studies, but integrated liquid water (ILW) has been retrieved as well. We report on methodological advances with the data analysis. First, the original algorithm was replaced by a new statistical retrieval based on the simulations of TROWARA data using radiosonde profiles. Second, in a physical refinement, the cause of the variable ILW bias has been identified, and a method for its reduction to the level of 0.001 to 0.005 mm has been developed and tested. The bias is mainly a result of the variable water-vapor influence on absorption at 31 GHz. The bias correction also influences the IWV retrieval. The refined physical retrieval includes the temperature dependence of cloud absorption based on a recent dielectric model of water. The three algorithms (original, new, and refined) have been compared for two years of data. The applications of the refined algorithm are focused on physical processes, such as the development of supercooled clouds. Future advances will include precipitation measurements.

The microwave radiation of the sea surface, which is denoted by the sea surface brightness temperature, is not only related with sea surface salinity (SSS) and temperature (SST), but also influenced by sea surface wind. The errors of wind detected by satellite sensor have significant influences on the accuracy of SSS retrieval. The effect of sea surface wind on sea surface brightness temperature, i.e. ΔTh,v, and the relations among ΔTh,v, wind speed, sea surface temperature, sea surface salinity and incidence angle of observation are investigated. Based on the investigations, a new algorithm depending on the design of a single radiometer with dual polarizations and multi-incidence angles is proposed. The algorithm excludes the influence of sea surface wind on SSS retrieval, and provides a new method for remote sensing of SSS.

Methods described in the IEEE standards for frequency generator stability can be used to estimate the precision of brightness temperature measurements made by a microwave radiometer. The application of these methods and the inherent assumptions are reviewed. A simple statistic is proposed for use in estimating accuracy drift.

In this paper, a new and improved L-band version of the correlated noise calibration standard (CNCS) has been developed to aid in the characterization of polarimetric microwave radiometers. The CNCS generates a series of known polarimetric test signals using a two-channel commercial arbitrary waveform generator (AWG) and a pair of frequency-upconversion modules. When it is inserted in place of the antenna used by a radiometer-under-test (RUT), it can fully characterize the polarimetric response of the receiver portion of the RUT. Both hardware and software improvements have been made over a previous version of the CNCS. The frequency upconverters now include integral warm and cold calibration-reference targets to automatically compensate for small drifts in AWG output-signal strength. The procedure used to calibrate the RUT has been generalized to correct for nonideal characteristics of the CNCS itself. Moreover, the effects on the derived polarimetric gain matrix of impedance mismatches between the RUT, and either the CNCS or the antenna have been determined. Details of the CNCS improvements are presented. The results of an experimental demonstration of its use and of a series of validation tests of its performance are also presented.

This paper departs from the popular usage of the Backus-Gilbert inversion (BGI) method as a tool for inversion of antenna temperature measurements in microwave radiometry. The BGI method is applied in this paper to enhance the information content of an existing set of oversampled brightness-temperature (TB) data. The purpose is to isolate the inversion process from its resolution enhancement counterpart. The advantage gained is that the resolution enhancement can be performed in a simplified way and in a different level of processing that starts with the scan-mode TB data product and simply requires with it the knowledge of the antenna gain pattern and the sensor's scan geometry. The technique is demonstrated with the 19.35-GHz Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) channel, which provides oversampled TB data. The radiometric resemblance of this channel with that of the 37 GHz and geocollocation of their TB footprints facilitate validation of the enhancement of features. The significance of oversampling the low-frequency (LF) radiometer channels is underscored in the process, which gives the authors the confidence to propose oversampling of the LF data for the forthcoming sensor Microwave Analysis and Detection of Rain and Atmospheric Structures (MADRAS) onboard the Megha_Tropiques mission, which is a joint ISRO-CNES collaboration (due for launch in 2009).

We present the results of a study that shows that a simple design modification is sufficient to avoid a major shortcoming in the layout of external warm loads commonly used in the calibration of spaceborne microwave radiometers. The modification consists of placing a layer of Plastazote, a polyethylene foam, over the opening of the warm load enclosure. The foam is transparent at micrometer and millimeter wavelengths, is opaque in the infrared and visible, and isolates the warm load from the environment, keeping the temperature of the radiometric warm load constant. The proposed solution can be easily implemented and is suitable even for retrofitting on instruments that have already been built but not yet launched, and the material presents no obvious shortcomings that could prevent its intended application in space.

Results are presented from the long-term monitoring and calibration of the National Aeronautics and Space Administration Jason Microwave Radiometer (JMR) on the Jason-1 ocean altimetry satellite and the ground-based Advanced Water Vapor Radiometers (AWVRs) developed for the Cassini Gravity Wave Experiment. Both radiometers retrieve the wet tropospheric path delay (PD) of the atmosphere and use internal noise diodes (NDs) for gain calibration. The JMR is the first radiometer to be flown in space that uses NDs for calibration. External calibration techniques are used to derive a time series of ND brightness for both instruments that is greater than four years. For the JMR, an optimal estimator is used to find the set of calibration coefficients that minimize the root-mean-square difference between the JMR brightness temperatures and the on-Earth hot and cold references. For the AWVR, continuous tip curves are used to derive the ND brightness. For the JMR and AWVR, both of which contain three redundant NDs per channel, it was observed that some NDs were very stable, whereas others experienced jumps and drifts in their effective brightness. Over the four-year time period, the ND stability ranged from 0.2% to 3% among the diodes for both instruments. The presented recalibration methodology demonstrates that long-term calibration stability can be achieved with frequent recalibration of the diodes using external calibration techniques. The JMR PD drift compared to ground truth over the four years since the launch was reduced from 3.9 to -0.01 mm/year with the recalibrated ND time series. The JMR brightness temperature calibration stability is estimated to be 0.25 K over ten days.

Spaceborne passive microwave data have been available for the past 27 years, and have supported the development of several algorithms for the retrieval of snow water equivalent and snow depth that, in turn, can be used for mapping snow-covered areas. In contrast, only recently has the application of spaceborne active microwave instruments been investigated for remote sensing of snow on a global scale. This raises the question of whether a technique combining active and passive microwave data can improve the mapping of snow parameters with respect to techniques based solely on passive data. In this letter, we report results concerning the mapping of snow-covered area (SCA) in the Northern Hemisphere between the years 2000 and 2004 derived from the combination of the brightness temperatures at 19.35 and 37 GHz measured by the Special Sensor Microwave Imager Radiometer with backscatter coefficients at 13.4 GHz measured by the NASA's QuickSCAT. SCA derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) is used as a reference to evaluate the performance of the microwave-based techniques and their combination. Results show that, generally, the technique using passive data provides better agreement with MODIS SCA than the technique using only scatterometer data. However, the results when both datasets are used show considerable improvement, demonstrating the potential benefits of a multisensor approach

The advent of fast computers and digital signal processing permits many aspects of radiometer operation to be decided in real time so that precision and accuracy are maximized. Closed-form expressions for precision, optimal antenna/load dwell times, and maximum chopping period are derived for a class of radiometers that uses two loads to calibrate its measurements of antenna brightness temperature. The importance of load brightness temperature selection emphasizes the need to develop "cold" calibration loads that can operate at ambient temperature. A method of incorporating critical thermistor data into the radiometer brightness temperature calibration can be used to help stabilize measurements against drift and may permit radiometers to operate without thermal control in some low-accuracy applications.

Brightness temperatures computed from five absorption models and radiosonde observations were analyzed by comparing them with measurements from three microwave radiometers at 23.8 and 31.4 GHz. Data were obtained during the Cloudiness Inter-Comparison Experiment at the U.S. Department of Energy's Atmospheric Radiation Measurement Program's (ARM) site in North-Central Oklahoma in 2003. The radiometers were calibrated using two procedures, the so-called instantaneous "tipcal" method and an automatic self-calibration algorithm. Measurements from the radiometers were in agreement, with less than a 0.4-K rms difference during clear skies, when the instantaneous method was applied. Brightness temperatures from the radiometer and the radiosonde showed a bias difference of less than 0.69 K when the most recent absorption models were considered. Precipitable water vapor (PWV) computed from the radiometers were also compared to the PWV derived from a Global Positioning System station that operates at the ARM site. The instruments agree to within 0.1 cm in PWV retrieval.

Thermal radiation of complex man-made objects as well as of our natural environment contains fully polarimetric in-formation in many cases. A quasioptical, imaging radiometer system was designed and built up at DLR for the measu-rement of the four Stokes vector components. A polarimetric calibration procedure was developed and verified. Selec-ted measurements have been carried out which indicate new possible applications. 1. Introduction The information content of the measured natural thermal radiation of man-made targets and of our environment dependson the frequency, observation angle, surface roughness, chemical composition and the polarization. Dependencies ofbrightness temperature signatures on polarization are based on prefered orientations of the electric field vector. For-mally, with respect to an orthogonal coordinate system x m , y m , z m and an observer looking into the direction z m , thebrightness temperature T B (p) for any polarization ppx py xm y m can be expressed by the following equation

Synthetic aperture imaging radiometers (SAIRs) are potential powerful instruments for high-resolution observation of planetary surfaces at low microwave frequencies. This paper deals with the reconstruction of radiometric brightness temperature maps from SAIR interferometric measurements. It is demonstrated that the corresponding inverse problem is not well-posed and must, therefore, be regularized in order to provide a unique and stable solution. A new approach is presented by referring to the notion of modeling operator and to the concept of a resolving matrix of the instrument. To illustrate the theory, numerical simulations are carried out in reference to the Soil Moisture and Ocean Salinity space mission led by the European Space Agency. The results are discussed with emphasis on stability and error analysis.

The Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System (EOS) Aqua satellite was launched on May 4, 2002. The AMSR-E instrument provides a potentially improved soil moisture sensing capability over previous spaceborne radiometers such as the Scanning Multichannel Microwave Radiometer and Special Sensor Microwave/Imager due to its combination of low frequency and higher spatial resolution (approximately 60 km at 6.9 GHz). The AMSR-E soil moisture retrieval approach and its implementation are described in this paper. A postlaunch validation program is in progress that will provide evaluations of the retrieved soil moisture and enable improved hydrologic applications of the data. Key aspects of the validation program include assessments of the effects on retrieved soil moisture of variability in vegetation water content, surface temperature, and spatial heterogeneity. Examples of AMSR-E brightness temperature observations over land are shown from the first few months of instrument operation, indicating general features of global vegetation and soil moisture variability. The AMSR-E sensor calibration and extent of radio frequency interference are currently being assessed, to be followed by quantitative assessments of the soil moisture retrievals.

The magnitude and spatial distribution of snow on sea ice are both integral components of the ocean–sea-ice–atmosphere system. Although there exists a number of algorithms to estimate the snow water equivalent (SWE) on terrestrial surfaces, to date there is no precise method to estimate SWE on sea ice. Physical snow properties and in situ microwave radiometry at 19, 37 and 85 GHz, V and H polarization were collected for a 10-day period over 20 first-year sea ice sites. We present and compare the in situ physical, electrical and microwave emission properties of snow over smooth Arctic first-year sea ice for 19 of the 20 sites sampled. Physical processes creating the observed vertical patterns in the physical and electrical properties are discussed. An algorithm is then developed from the relationship between the SWE and the brightness temperature measured at 37 GHz (55°) H polarization and the air temperature. The multiple regression between these variables is able to account for over 90% of the variability in the measured SWE. This algorithm is validated with a small in situ data set collected during the 1999 field experiment. We then compare our data against the NASA snow thickness algorithm, designed as part of the NASA Earth Enterprise Program. The results indicated a lack of agreement between the NASA algorithm and the algorithm developed here. This lack of agreement is attributed to differences in scale between the Special Sensor Microwave/Imager and surface radiometers and to differences in the Antarctic versus Arctic snow physical and electrical properties. Copyright © 2003 John Wiley & Sons, Ltd.

An approach is evaluated for the estimation of soil moisture at high resolution using satellite microwave and optical/infrared (IR) data. This approach can be applied to data acquired by the Visible/Infrared Imager Radiometer Sensor Suite (VIIRS) and a Conical Scanning Microwave Imager/Sounder (CMIS), planned for launch in the 2009–2010 time frame under the National Polar-Orbiting Operational Environmental Satellite System (NPOESS). The approach for soil moisture estimation involves two steps. In the first step, a passive microwave remote sensing technique is employed to estimate soil moisture at low resolution (∼25 km). This involves use of a simplified radiative transfer model to invert dual-polarized microwave brightness temperature. In the second step, the microwave-derived low-resolution soil moisture is linked to the scene optical/IR parameters, such as Normalized Difference Vegetation Index (NDVI), surface albedo, and Land Surface Temperature (LST). The linking is based on the ‘Universal Triangle’ ...

Experimental results are reported for sensing of subsurface objects with a multifrequency radiometer (MFRAD) system. Properties of the MFRAD system are reviewed, and the calibration and experimental procedures are discussed. Results with subsurface metallic, styrofoam, and plastic targets are then provided that demonstrate an oscillatory behavior in brightness temperatures versus frequency in the presence of a subsurface object. Measured data are also compared with a simple layered medium brightness temperature model and show reasonable agreement with predicted trends of brightness temperatures versus frequency. The oscillatory behaviors versus frequency obtained in the presence of both metallic and nonmetallic subsurface objects should prove advantageous for designing object detection procedures.

Brightness temperature TB data were collected with a surface-based radiometer operating on both vertical and horizontal polarizations at frequencies of 19, 37, and 85 GHz. Both microwave emissions and thermophysical data were collected as part of the Collaborative–Interdisciplinary Cryospheric Experiment between 15 May and 25 June 2000, in the Canadian High Arctic. Each season was characterized by a running variance of the time series in the microwave emissions. The seasonal analysis was conducted through observed changes in the physical characteristics of the sea ice and the overlying snow pack. Results from a k-means clustering analysis show that variability in the microwave response can be categorized into phenomenological states that were described by Livingstone et al. [IEEE Transactions on Geoscience and Remote Sensing 1987; 25(2): 174–187] as winter, early melt, melt onset and advanced melt. We describe the average thermophysical conditions associated with each one of these ‘ablation states’ and interpret the relative contributions of each to the observed microwave response. Emissivities were calculated and used as part of a descriptive analysis of the seasonal variation of TB. Our results confirm other findings that the strength and pattern of the relationship are frequency dependent and relative to snow and ice dielectric properties. Useful information on the thermodynamic state of the snow–sea-ice system can be derived from passive microwave data, since the microwave emissions respond to the general seasonal changes associated with the transition from winter to a melt ponded sea ice surface. Copyright © 2001 John Wiley & Sons, Ltd.

Atmospheric water vapour was measured over a tropical location, Calcutta, by deploying dual frequency microwave radiometers operating at 22.235 and 31.4 GHz. Simultaneous measurements of brightness temperature and hence attenuation in the presence of thin cloud were made for the purpose. An algorithm was developed to exclude the effect of non-precipitating liquid water during the measurement of water vapour. The experimental results are supported by the corresponding radiosonde data analysis. Dual frequency radiometric measurements are shown to improve the rms accuracy, over the single frequency inversion technique, for the measurement of water vapour.

The sensitivity of microwave emission at different frequencies to soil moisture in bare and vegetated soils has been investigated using experimental data. Since the best frequency for the measurement of soil moisture (L-band) is absent in current satellite sensors, it is necessary to seek alternative solutions. An algorithm is proposed for the retrieval of soil moisture based on the sensitivity to moisture of both the brightness temperature and the polarization index at C-band, one that is able to correct for the effect of vegetation by means of the polarization index at X-band. The algorithm has been tested by using experimental data collected with airborne microwave radiometers on agricultural areas and validated by using the data sets of special sensor microwave/imager (SMM/I) and scanning multichannel microwave radiometer (SMMR). These research activities are planned in view of coming new satellites: AQUA (NASA) and ADEOS-II (NASDA), which will be launched by the end of 2001. These will have new generation microwave radiometers (AMSR-E and AMSR) onboard, which show much better characteristics with respect to the previous sensors, in particular an enhanced spatial resolution.

The horizontal inhomogeneity of the atmosphere within a satellite microwave radiometer's field of view (FOV) has always been considered as a source of rainfall retrieval errors. The hydrometeor profile retrieval algorithm presented exploits it to obtain an approximation of a radiative transfer model, which allows relatively simple inversion. The atmosphere within the FOV is treated as a combination of horizontally homogeneous domains. Assuming that one of known "basic" hydrometeor profiles occurs in each domain, the inverse problem is reduced to a determination of "beamfilling coefficients." The online procedure includes determination of beamfilling coefficients and a footprint-averaged hydrometeor profile as a linear combination of "basic" ones. Off-line procedures involve the selection of a minimum number of necessary "basic" brightness temperature vectors and correction of "basic" hydrometeor profiles to provide the best retrieval accuracy for a given cloud/radiative simulation. The performance of the algorithm is tested for both numerical simulations and TRMM/TMI data. Numerical simulation has allowed a comparison of the information content of radiometer measurements from SSM/I, TMI, and the future AMSR. The effectiveness of the algorithm is being tested for rain water integral and rain rate retrievals from TRMM TMI measurements.

The authors present the retrievals of surface soil moisture (SM) from simulated brightness temperatures by a newly developed error propagation learning backpropagation (EPLBP) neural network. The frequencies of interest include 6.9 and 10.7 GHz of the advanced microwave scanning radiometer (AMSR) and 1.4 GHz (L-band) of the soil moisture and ocean salinity (SMOS) sensor. The land surface process/radiobrightness (LSP/R) model is used to provide time series of both SM and brightness temperatures at 6.9 and 10.7 GHz for AMSRs viewing angle of 55/spl deg/, and at L-band for SMOS's multiple viewing angles of 0/spl deg/, 10/spl deg/, 20/spl deg/, 30/spl deg/, 40/spl deg/, and 50/spl deg/ for prairie grassland with a column density of 3.7 km/m/sup 2/. These multiple frequencies and viewing angles allow the authors to design a variety of observation modes to examine their sensitivity to SM. For example, L-band brightness temperature at any single look angle is regarded as an L-band one-dimensional (1D) observation mode. Meanwhile, it can be combined with either the observation at the other angles to become an L-band two-dimensional (2D) or a multiple dimensional observation mode, or with the observation at 6.9 or 10.7 GHz to become a multiple frequency/dimensional observation mode. In this paper, it is shown that the sensitivity of radiobrightness at AMSR channels to SM is increased by incorporating L-band radiobrightness. In addition, the advantage of an L-band 2D or a multiple dimensional observation mode over an L-band 1D observation mode is demonstrated.

The coldest possible brightness temperatures observed by a downward-looking microwave radiometer from space are often produced by calm oceans under cloud-free skies and very low humidity. This set of conditions tends to occur with sufficient regularity that an orbiting radiometer will accumulate a useful number of observations within a period of a few days to weeks. Histograms of the radiometer's coldest measurements provide an anchor point against which very small drifts in absolute calibration can be detected. This technique is applied to the TOPEX microwave radiometer (TMR), and a statistically significant drift of several tenths of a Kelvin per year is clearly detected in one of the channels. TMR housekeeping calibration data indicates a likely cause for the drift, as small changes in the isolation of latching ferrite circulators that are used in the onboard calibration-switch assembly. This method can easily be adapted to other microwave radiometers, especially imagers operating at frequencies in the atmospheric windows. In addition to detecting long-term instrument drifts with high precision, the method also provides a means for cross-calibrating different instruments. The cold reference provides a common tie point, even between sensors operating at different polarizations and/or incidence angles.

This paper presents some additional theoretical and experimental results on the problem of estimating the soil depth to which soil moisture can be directly measured by VHF radiometers. The experimental work was implemented in August 1992 at the Research Farm of the Institute of Hydrotechnique and Amelioration, Sofia, Bulgaria. The soil thermal microwave emission was measured by an L-band Dicke-type radiometer at 1.65GHz at off-nadir angle from 20 to 60. It was found that the value obtained for the effective penetration depth depends on the definition used in the analysis: the definition of penetration depth is based on soil thermal emissivity or soil reflectivity. Further it was found that the depth to which the soil moisture can be directly measured exhibits a negligible dependence on polarization (horizontal, vertical) as well as on off-nadir observation angle. For the purpose of soil brightness temperature and soil reflectivity computing, a fast and robust method and algorithm were proposed which are b...

Ocean wind speed and direction can be assessed with a polarimetric radiometer system measuring the full set of Stokes parameters. There are two fundamentally different ways of implementing the polarimetric radiometer system: polarization combining and correlation radiometer systems. Also, within each fundamental category there are significant tradeoffs. This paper discusses the different implementation possibilities. Paramount issues are potential instrument stability and sensitivity as well as the tradeoff between increased microwave hardware complexity and fast digital correlator circuitry. It is concluded that each implementation has its role to play, but for a given application the choice of system configuration is important. Following these considerations, a second-generation airborne, imaging, polarimetric radiometer system, used by the authors for ocean wind vector sensing, is described and discussed.

A radiative transfer model is described for the evaluation of the brightness temperatures measured by microwave radiometers above the oceans. For observations at an incidence angle around 50/spl deg/ from the local vertical, a crude approximation of this model is providing the basis for a wind-independent inversion algorithm for the retrieval of atmospheric integrated water vapor and cloud liquid water. The algorithm is applied to special sensor microwave imager (SSM/I) data, and the results compared with estimates from the ECMWF climatological model and from the algorithms specifically developed for SSM/I. A short discussion on the accuracy of the algorithm is also provided.

This study presents research in support of the design and implementation of a combined radar–radiometer algorithm to be used for precipitation retrieval during the Tropical Rainfall Measuring Mission (TRMM). The combined algorithm approach is expected to overcome various difficulties that arise with a radar-only approach, particularly related to estimates of path-integrated attenuation (PIA) along the TRMM radar beam. A technique is described for estimating PIA at the 13.8-GHz frequency of the TRMM precipitation radar (PR) from 10.7-GHz brightness temperature TB measurements obtained from the TRMM microwave imager. Because the PR measures at an attenuating frequency, an independent estimate of PIA is used to constrain the solution to the radar equation, which incorporates effects of attenuation propagation along a radar beam. Through the use of variational or probabilistic techniques, the independent PIA calculations provide a means to adjust for errors that accumulate in estimates of range-depen...

Microwave radiometers operating at low frequencies are sensitive to surface soil moisture changes. Few studies have been conducted that have involved multifrequency observations at frequencies low enough to measure a significant soil depth and not be attenuated by the vegetation cover. Another unexplored aspect of microwave observations at low frequencies has been the impact of diurnal variations of the soil moisture and temperature on brightness temperature. In this investigation, observations were made using a dual frequency radiometer (1.4 and 2.65 GHz) over bare soil and corn for extended periods in 1994. Comparisons of emissivity and volumetric soil moisture at four depths for bare soils showed that there was a clear correspondence between the 1 cm soil moisture and the 2.65-GHz emissivity and between the 3-5 cm soil moisture and the 1.4-GHz emissivity, which confirms previous studies. Observations during drying and rainfall demonstrate that new and unique information for hydrologic and energy balance studies can be extracted from these data.

We describe the design and performance of a 180 GHz correlation radiometer suitable for remote sensing. The radiometer provides continuous comparisons between a the observed signal and a reference load to provide stable radiometric baselines. The radiometer was assembled and tested using parts from the GeoSTAR-II instrument and is fully compatible with operation in a synthetic aperture radiometer or as a standalone technology for use in microwave sounding and imaging . This new radiometer was tested over several days easily demonstrating the required 6 hour stability requirement for observations of mean brightness temperature for a geostationary instrument.

The advanced technology microwave sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite is a total power radiometer and scans across the track within a range of ±52.77° from nadir. It has 22 channels and measures the microwave radiation at either quasi-vertical or quasi-horizontal polarization from the Earth’s atmosphere. The ATMS sensor data record algorithm employed a commonly used two-point calibration equation that derives the earth-view brightness temperature directly from the counts and temperatures of warm target and cold space, and the earth-scene count. This equation is only valid under Rayleigh–Jeans (RJ) approximation. Impacts of RJ approximation on ATMS calibration biases are evaluated in this study. It is shown that the RJ approximation used in ATMS radiometric calibration results in errors on the order of 1–2 K. The error is also scene count dependent and increases with frequency.

Three-dimensional tropical squall-line simulations from the Goddard cumulus ensemble (GCE) model are used as input to radiative computations of upwelling microwave brightness temperatures and radar reflectivities at selected microwave sensor frequencies. These cloud/radiative calculations form the basis of a physical cloud/precipitation profile retrieval method that yields estimates of the expected values of the hydrometeor water contents. Application of the retrieval method to simulated nadir-view observations of the aircraft-borne Advanced Microwave Precipitation Radiometer (AMPR) and NASA ER-2 Doppler radar (EDOP) produce random errors of 23%, 19%, and 53% in instantaneous estimates of integrated precipitating liquid, integrated precipitating ice, and surface rain rate, respectively. On 5 October 1993, during the Convection and Atmospheric Moisture Experiment (CAMEX), the AMPR and EDOP were used to observe convective systems in the vicinity of the Florida peninsula. Although the AMPR data alon...

The Global Change Observation Mission (GCOM) consists of two polar orbiting satellite observing systems, GCOM-W (Water) and GCOM-C (Climate), and three generations to achieve global and long-term monitoring of the Earth. GCOM-W1, the first satellite of the GCOM-W series, was successfully launched on May 18, 2012 (Japan Standard Time). The Advanced Microwave Scanning Radiometer-2 (AMSR2), which is a successor of AMSR on the Advanced Earth Observing Satellite-II (ADEOS-II) and AMSR for EOS (AMSR-E) on NASA’s Aqua satellite, is a single mission instrument on GCOM-W1. Basic characteristics of AMSR2 is similar to that of AMSR-E to continue the AMSR-E observations, with several enhancements including larger main reflector (2.0 m), additional channels at the C-band frequency band, and improved calibration system. AMSR-E halted its observation on October 4, 2011 due to the increase of antenna rotation torque, which is considered as the typical aging effect. Although all the efforts are being made to resume the AMSR-E observation, early initiation of the AMSR2 observation has been highly desired. After the completion of the orbit injection into the A-Train constellation, AMSR2 started rotating and initiated global observation. During the initial calibration and validation phase, brightness temperatures will be evaluated and characterized through methodologies such as the inter-calibration among similar microwave radiometers including the TRMM Microwave Imager (TMI) and WindSat on Coriolis mission.

Measurements of the microwave brightness temperature of stratocumulus cloud at 89 and 157 GHz using the Microwave Airborne Radiometer Scanning System on the UK Meteorological Research Flight's C-130 aircraft have been analysed. Comparisons of observed and calculated brightness temperature using models available in the literature have given good agreement for sea-surface emission and atmospheric attenuation in clear and cloudy skies. A nonlinear retrieval scheme has been applied to the observations to retrieve cloud liquid-water paths for comparison with the in situ measurements. Validation of the retrieved liquid-water paths to within 50 g m −2 has been achieved. Ambiguities between cloud retrievals and water vapour and surface parameters are discussed. The observed differences between the retrieval and the in situ measurement are not found to correlate strongly with cloud temperature, but a higher than expected correlation is found with the drop-size distribution. It is demonstrated that the scheme is applicable to satellite soundings of cloud, and that a similar level of accuracy should be achieved.

The Microwave Radiometer (MWR) on the Aquarius/SAC-D mission measures microwave radiation from earth and intervening atmosphere in terms of brightness temperature (T b ). It takes measurements in a push-broom fashion at K- (23.8 GHz) and Ka-band (36.5 GHz) frequencies using two separate reflector antenna systems, each producing eight spot beams. Pre-launch measurements of the alignment of these beams with respect to the spacecraft coordinate system is used to geolocate the antenna foot-prints on ground. As a part of MWR's on-orbit engineering check-out, the verification of MWR's pointing accuracy is discussed here. The technique used to assess MWR's pointing involves comparing the radiometer image of land with high-resolution maps. When the beam's instantaneous field of view (IFOV) passes over a land/water boundary, the brightness temperature changes from a radiometrically “hot” land-scene to a “cold” ocean-scene. This “step-function” change in brightness temperature provides a very sensitive way to assess the mispointing error of the calculated MWR earth location (latitude/longitude) of the antenna footprints. This paper describes the algorithm used for the MWR geolocation validation assessment and preliminary results, presented for the MWR 23.8 GHz channel, show that the mispointing errors from the true coastline are close to meeting the specification.

Airborne microwave measurements of precipitation associated with Super Typhoon Flo in the western North Pacific were conducted during September 16-18, 1990. The sensor package aboard the NASA DC-8 aircraft included a dual-frequency precipitation radar at 10 GHz and 34 GHz and a host of radiometers operating at 10 GHz, 18 GHz, 19 GHz, 34 GHz, and 92 GHz, as well as three frequencies near the strong water vapor absorption line of 183.3 GHz. The measurements were made during a few passes over the storm center, and active and passive microwave signatures of the rainbands were detected with a fine spatial resolution. The relationship between the measured brightness temperature and radar-estimated rain rate is examined at the frequencies between 10-92 GHz. At both 34 and 92 GHz this relationship is analyzed with the 10 GHz radar reflectivity factor measured at altitudes above the freezing layer as a further constraint. The results show that frozen hydrometeors strongly scatter radiation at these frequencies, especially at 92 GHz. It was shown from a close examination of both active and passive microwave signatures that a significant scattering of radiation at frequencies 118 GHz occurred in the inner eyewall at altitudes of 3-8 km. This scattering of microwave radiation by hydrometeors in both liquid and frozen forms is discussed under the authors' current understanding of the scattering mechanism. >

Characterization of the drift in the 18-GHz brightness temperature (TB) measured by the TOPEX microwave radiometer (TMR) is presented. The appropriate correction is not a constant drift but varies with TB. Using this correction results in a more accurate path delay retrieval that varies appropriately with cloud cover and surface wind speed.

L-band radiometry is recognized as a technique with a significant potential for providing spatial and temporal soil moisture variations [1, 2]. As a result, satellite missions dedicated to global soil moisture monitoring have been proposed. A 2D-interferometric L-band radiometer has recently been launched onboard the European SMOS (Soil moisture and Ocean Salinity) satellite, [3], and the NASA is in preparation of a similar suite of microwave instruments as a part of the Aquarius and SMAP (Soil Moisture Active/Passive missions, [4] which have anticipated launch dates in 2011 and 2014, respectively. The reliability of soil moisture products derived from these microwave observations will depend, at least in part, on the effectiveness of accounting for vegetation and surface roughness impacts.