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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.

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 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.

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.

In recent years there is growing interest, on the part of the remote sensing community, in using the Antarctic area for calibrating and validating data of the low-frequency satellite-borne microwave radiometers. In particular, the East Antarctic Plateau appears to be suited for this purpose. The reason of this interest lies in the size, structure, spatial homogeneity and thermal stability of this area. This is particularly interesting for low-frequency microwave radiometers since, due to the low extinction of dry snow, the upper ice sheet layer is almost transparent and the brightness temperature variability is therefore extremely small. In preparation for the November 2009 launch of the ESA's SMOS satellite, an experiment called DOMEX, which included radiometric L-band measurements was started in the Austral summer 2009. Data acquired in the campaign confirmed the temporal stability of the site. Comparison between ground and satellite data at L-band are also presented here. Moreover multi-frequency analysis of data collected over this area is performed by using SMOS and AMSR-E data.

In this paper, the potential of using passive microwave observations to detect and monitor flood was explored during the time period 2005–2009. Data from the Advanced Microwave Scanning Radiometer (AMSR-E) was used to evaluate the performance of radiometry in flood monitoring and detection. The current study demonstrates the potential of these observations to monitor the floods in the Sundarban Delta (India / Bangladesh). There is a clear effect expressed by low brightness temperature and high polarization index (i.e. higher soil moistures) over the affected areas after floods or heavy rainfalls. The use of remotely sensed passive microwave observations can improve the forecasting skill of flooding at regional scale.

In this paper the results of simultaneous and spatially coincident, multi-frequency, polarimetric, spatio-temporally collocated measurements of bare, dry vegetated and ash covered soils microwave reflective (radar backscattering coefficient) and emissive (brightness temperature) characteristics angular dependences at ∼5.6GHz and ∼15GHz are presented. During these experiments the observed area was set ablaze and multi-frequency, multi-polarization, microwave active and passive measurements at 300 incidence angle were continued for smock, fire and ash situations. For these measurements C-, and Ku-band, polarimetric, combined scatterometric-radiometric systems were used, set jointly on a mobile buggy moving along the measuring platform. Structures, operational features and the main technical characteristics of the utilized systems are presented too. The paper has an aim as well to attract attention of interested researchers and to invite them to perform their own or joint researches using available devices and facilities.

CE-2 Lunar Microwave Sounder (CELMS) is the second passive microwave radiometer in the world to sound the surface of the Moon on the orbit of 100 km. The scientific objective of CELMS is to further obtain global brightness temperature (TB) of the Moon, to retrieve information on lunar regolith, and to evaluate the distribution of helium-3 on the Moon. Before launch of CELMS, calibration experiments were carried out in laboratories to test the performances of the systems, and to derive transfer parameters on the transfer paths of CELMS. This paper the procedure of calibration is introduced and the method of computing the coefficients of each path is given. The calibration results on nonlinearity and accuracy of the system are summed and analyzed.

The East Antarctic plateau is a part of Antarctica extending several hundred kilometers around the South Pole with an average elevation close to 3000 m a.s.l. This area provides unique opportunities for various scientific disciplines including Glaciology, Atmospheric and Earth Sciences. In addition, there is growing interest, in using the Antarctic plateau, for calibrating and validating data of satellite-borne microwave radiometers. This is because the size, structure, spatial homogeneity and thermal stability of this area. In this paper we analyse temporal and spatial variability of multi-frequency microwave emission from an area around the Dome-C scientific station by using AMSR-E data collected along the years 2003–2008. From the analysis two candidates areas were founded.

The use of microwave observations in the frequency range of 90–150 GHz holds the promise to dramatically improve the retrieval of integrated liquid water in thin clouds due to the increased sensitivity of these frequencies to the presence of liquid water. One of the largest sources of retrieval uncertainty at these frequencies is the inaccuracy of liquid water absorption models at low temperatures. The purpose of this work is to assess the performance of four liquid water absorption models by comparing model simulations with measurements collected by a microwave high-frequency radiometer (MWRHF) located at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) in the Southern Great Plains, OK. Measurements at 90 and 150 GHz were collected during cloudy and cold conditions. In an attempt to isolate different sources of possible errors we give an assessment of the instrument calibration and compare clear-sky measurements with model simulations using an updated formulation for the water vapor continuum. With the help of a ceilometer and cloud radar we identified several cases of cold, thin liquid clouds and for those cases we independently retrieved liquid water path using infrared frequencies. The independently retrieved liquid water path was then used to compute brightness temperatures at 90 and 150 GHz with the four liquid absorption formulations. Simulation results were then analyzed and compared with observations.

A multilayer neural network has been developed to retrieve IPWV over land from brightness temperatures measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) on board the Aqua satellite. Our study was optimized over two areas in Northern and Central Italy. Good agreements on the order of 0.24 cm and 0.33 cm rms, respectively, were found between neural network retrievals and ECMWF IPWV data for clear-sky. In the presence of clouds, an rms of the order of 0.38 cm was found for both areas.

Knowledge of the variability of microwave signatures of vegetation and roughness are necessary to separate these influences from those of soil moisture for remote sensing applications to global hydrology and climate. Conventional, vegetation indices are often limited by the effects of atmosphere, background soil conditions. The Soil Moisture and Ocean Salinity (SMOS) satellite will provide global multi-angular microwave brightness temperature observations at L-band, in dual polarization and multi-angles. Through the analysis of the simulations by the advanced integral equation model (AIEM), we found that the polarization difference for the bare surface emission signals at different view angles can be well characterized by a line function with parameters that are dependent on the pair of view angles to be used. This makes it possible to minimize the surface emission signal and maximize the vegetation signal when using multi-angular radiometer measurements. The developed microwave vegetation index (MVI) is independent of soil surface emission signals and can provide new vegetation information since the L-band microwave measurements are sensitive to the properties of the overall vegetation. We compared the developed MVI with the Leaf Area Index (LAI) with SMOSREX data in 2003. The results showed that the general distribution and the change patterns of the MVI are consistent with those of LAI and VWC derived by the field experiments. This method provides a new opportunity to monitor vegetation cover for future SMOS applications.

In order to correct the altimeter range for tropospheric humidity, a microwave radiometer is added to altimetry missions [Envisat/microwave radiometer, Jason/Jason Microwave Radiometer, and TOPEX-Poseidon/TOPEX Microwave Radiometer (TMR)]. Over open ocean, the combination altimeter/radiometer is satisfactory. This is not the case in coastal zones, where the signal coming from the surrounding land surfaces contaminates the radiometer measurement and makes the humidity-retrieval method unsuitable. In this paper, a radiometer simulator is built, using data from a field experiment (in situ measurements and collocated TMR measurements) and analyses from a mesoscale-forecast model. This simulator is used to perform sensitivity tests and to evaluate the current methods to retrieve the wet tropospheric correction in transition areas. The purpose of this paper is to analyze and compare the performances of these methods. After examining simple correction methods (extension of the open-sea wet tropospheric correction and use of the meteorological model value), we evaluated the feasibility and performances of two methods, which propose to take into account the land-surface effect in the brightness-temperature estimation. The latter was found to give significantly better results.

This presentation will review recent developments in microwave radiometry including the introduction of interferometric radiometry in remote sensing. Microwave radiometers have been used in satellite remote sensing of the Earth since the 1960's. They measure the intensity of thermal radiation emitted by the target, expressed as brightness temperature. Multi-frequency dual-polarized radiometers contain several receivers, each operating over a certain frequency band and receiving thermal emission at either horizontal or vertical polarization. Geophysical characteristics of the target are derived from the observed brightness temperatures by employing theoretical or semi-empirical emission models. Satellite radiometers have been developed by everal countries including USA, Russia, Japan and India. The main advantages of satellite microwave radiometers include their capability to provide data regardless of the lighting conditions and nearly regardless of weather conditions. The spatial resolution of real-aperture radiometers depends on frequency. The most recently launched satellite system, the AMSR-E radiometer, operates from 6.9 to 89 GHz and its antenna diameter is 1.6 m providing corresponding average spatial resolutions from 56 to 5 km. Hence, for a real-aperture radiometer operating at 1.4 GHz a very large parabolic reflector diameter would be needed in order to achieve a resolution of approximately 50 km. The airborne ESTAR one-dimensional interferometric radiometer, developed in USA in the 1990's demonstrated that thinned antennas can be used for achieving high spatial resolution. The European Space Agency's SMOS (Soil Moisture and Ocean Salinity) satellite is scheduled for launch in 2009. The only payload is the MIRAS two-dimensional interferometric 1.4 GHz radiometer, containing tens of antenna/receiver subsystems in Y-shaped configuration. The main goals of the mission are to produce on a regular basis global maps of soil moisture and ocean surface salinity. The operation principle and technical details of the MIRAS radiometer will be discussed in the presentation. Airborne demonstrators with technical characteristics identical with those of the satellite sensor are needed in order to validate the instrument concept and provide experimental data before the launch of the SMOS satellite. This talk will present technical characteristics of the HUT-2D airborne interferometric 1.4 GHz radiometer developed by the Helsinki University of Technology. Results from recent campaigns are presented. Possible future developments in this field are discussed.

The new algorithms for retrieval of total atmospheric water vapor content (Q) and total cloud liquid water content (W) from satellite microwave radiometer data, applicable for the Arctic Basin. These algorithms are based on the neural networks (NNs) regression technique employed for the inversion of a radiative transfer equation (RTE). For the algorithm development the numerical integration of RTE was carried out for the channel characteristics of a Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer (AMSR-E), and brightness temperatures (TB) were simulated for non-precipitating conditions over the open ocean. Sets of sea surface temperatures (Ts), surface winds and radiosonde reports collected by Russian research vessels served as input data for the integration. Only data with Ts less than 15degC were selected for algorithm development. Simulated radiometer noise was added to the calculated values of TB. Once developed, using theoretically simulated values of TB, the Q algorithms were then validated both for SSM/I and AMSR-E retrievals using satellite radiometric measurements collocated in space and time with polar station radiosonde data. The resulting SSM retrieval error proved to be 1.1 kg/m2, AMSR-E retrieval error -0.9 kg/m2. Considered case study was the polar low in the Norwegian Sea occurred 30-31 January 2008. NOAA AVHRR, Terra and Aqua MODIS images, QuikSCAT-retrieved wind fields, Envisat ASAR images as well as weather maps were used as ancillary data to passive microwave retrievals to study this phenomenon.

In this paper, we mainly studied of microwave emission behavior of shallow snow cover with the field experiments over Huabei Plain, China., The evaluation of microwave emission character over snow surface was using the data collected by a ground-based multi-frequency and dualpolarization microwave radiometer (RPG-8CH-DP) at 10.7 GHz, 18.7GHz and 36.5 GHz, with the incidence angles ranging from 20deg to 60deg. Through analysis of the observation brightness temperature, we found that the radiation behavior of thin snow cover is very different from that of deep snow, especially during melting and refreezing period of thin snow cover. One is that the emission over shallow snow surface increased as frequencies increase. Secondly, at the same frequency, when shallow snow was melt in diurnal refreezing-thaw cycle, the emission would decrease. These two emission behavior were caused by the attenuation of snow cover was weak than the increment of emission from the underground snow surface. From this study, it has been shown that the ground-based microwave radiometry provides a useful tool to investigate the radiation characteristics of thin snow cover and snow type identification. It also helps to evaluate snow emission models and develop retrieval algorithms of snow characteristics from space-borne microwave radiometer data.

In remote-sensing applications the inclusion of subgrid-scale variability in coarse resolution data still remains an elusive challenge. This paper is devoted to the development of an appropriate downscaling technique for future Aperture Synthesis Radiometer's images. A comparative study of different deconvolution algorithms has been performed and particular emphasis is made on the use of least-squares Lagrangian methods and Fourier Wiener filtering. Results show that with this technique it is feasible to improve the spatial resolution of brightness temperature images from the Spatial Sensor Microwave Imager (SSM/I) radiometer and from an upgraded version of the Soil Moisture and Ocean Salinity (SMOS) End-to-end Performance Simulator (SEPS).

We examine the response of microwave brightness temperatures to snow water equivalent over a wide range of snowpack conditions observed during the Cold Land Processes Experiment (CLPX) in 2002 and 2003. Spatially intensive measurements of snow were collected over the CLPX study areas within the Colorado Rocky Mountains. The NOAA Earth System Research Laboratory's Polarimetric Scanning Radiometer (PSR) was operated to obtain coincident high-resolution (150-500 m) multiband microwave imagery of the snowpack. Together, a robust data set of over 2300 collocated in situ and remotely sensed observations were obtained for this analysis. For each point we modeled brightness temperatures using observed snow properties and the Helsinki University of Technology (HUT) snow emission model. Using observed and modeled data, we developed multiple regression algorithms to retrieve snow water equivalent (SWE). The algorithms use brightness temperature differences between 10.7, 18.7, and 21.5 GHz with 37 GHz and 89 GHz. Results show that the CLPX microwave data are consistent with a) historically established data and, b) after removal of cases with macro vegetation or possible wet snow, with theoretically derived curves for microwave dependence on SWE.

The optimal pair of frequencies for dual-frequency radiometer presuming the presence of clouds and accounting on the possible accuracy of the instrument are investigated. The water vapor and liquid water contents retrieved from microwave measurements with dual-frequency radiometer were averaged over various types of clouds. To reduce the influence of strong cloud conditions the third frequency band is proposed. Optimal frequency set is estimated in the case of zenith-looking observation.

In September 1993, the NASA Millimeter-wave Imaging Radiometer (MIR) flew on board the NASA ER-2 high-altitude aircraft during CAMEX, and obtained the first wideband millimeter- and submillimeter-wavelength images of tropospheric emission. The MIR is a cross-track scanning radiometer with channels at 89, 150, 183/spl plusmn/1, 3, 7, 220, and 325/spl plusmn/1, 3, 8 GHz. This set provides upwelling brightness information at the two strong rotational water vapor lines at 183.310 and 325.153 GHz and three nearby atmospheric transmission windows. The wideband MIR images of convective raincells reveal unique cloud and precipitation mapping capabilities that are not available from lower frequency microwave channels. Comparisons between the 183 and 325 GHz spectra also reveal differential brightness temperature modes that are related to cloud water. >

Discusses microwave radiometer measurements of the emission from saline ice for young ice. The instruments used are P-band, L-band, and S-band radiometers. The measurements were undertaken at a facility constructed by the U.S. Army cold regions research and engineering laboratory, which was specifically designed to satisfy remote sensing requirements.

WindSat, an experimental sensor on the Coriolis mission launched in January 2003, is intended to measure the partially polarized emission from the ocean surface, and thereby indirectly measure the ocean surface wind vector. The WindSat calibration and validation process has two primary purposes. The first is to verify the WindSat radiometer absolute accuracy, which is driven by the calibration target accuracy and knowledge, the receiver performance, the antenna characterization and antenna pattern correction, and the geolocation and pointing processing. The second purpose is to validate the sea surface wind speed and direction environmental data products. A key part of this process to identify and quantify error sources and, if necessary, generate new sensor calibration coefficients, algorithms, and environmental data record (EDR) retrievals to bring the data products into specification. This paper focuses on the calibration of the brightness temperatures, the data product used to retrieve environmental parameters such as wind vector

We describe the NIST effort to develop brightness-temperature standards for microwave and millimeter-wave frequencies. Results of preliminary measurements at 26 GHz are presented.

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 WindSat's 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 Laboratory's 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 NCEP's Global Data Assimilation System (GDAS) as a powerful source of plentiful comparison data is explored, particularly with regard to WindSat model function development

A spectral difference method is used to quantify the magnitude and extent of radio-frequency interference (RFI) observed over the United States in the Aqua AMSR-E radiometer channels. A survey using data from the AMSR-E instrument launched in May 2002 shows the interference to be widespread in the C-band (6.9 GHz) channels. The RFI is located mostly, but not always, near large highly populated urban areas. The locations of interference are persistent in time, but the magnitudes show temporal and directional variability. Strong and moderate RFI can be identified relatively easily using an RFI index derived from the spectral difference between the 6.9- and 10.7-GHz channels. Weak RFI is difficult to distinguish, however, from natural geophysical variability. These findings have implications for future microwave sensing at C-band, particularly over land areas. An innovative concept for radiometer system design is also discussed as a possible mitigation approach.

Brightness temperatures (TBs) from satellite microwave radiometers need to be calibrated on-orbit at the hottest and coldest ends of the dynamic TB spectrum. A method is developed to determine hot reference calibration TBs from SSM/I TB data for other radiometers operating between 18-40 GHz and 0-55 degrees incidence. Regions of optically thick vegetation in the Amazon rainforest are chosen as calibration targets. Hot reference temperatures for the on-orbit calibration of microwave radiometers are determined for these regions.

A comparative evaluation of the potential of L- and C-band passive microwave sensors in estimating soil moisture content was carried out. For this purpose, experimental data collected on a bare soil by ground-based radiometers, during the Huntsville '98 experiment have been used. The results show the sensitivity of radiation in the C-band (6 cm) and L-band (21 cm) to the changes in water content and soil temperature in bare soil. These data show that the primary parameter affecting the intensity of radiation/brightness temperature in bare soil is the soil moisture. Based on this sensitivity it was feasible to estimate the value of soil moisture without a priori data on the soil parameters. Comparisons of the data collected using different wavelength bands in the dynamic of soil moisture changes inside a fixed antenna footprint are discussed. Additionally, analyses are given of the observed diurnal changes.

The Marine Environment Pollution Monitoring (MEPM) program has been carried out to demonstrate the capability of microwave radiometers for the remote sensing of oil spills. An airborne microwave radiometer (AMR-OS) and a ship-based K-band radiometer were used to detect oil spills and to estimate oil volume. Also the coordinate sea-surface measurement on HJ-69 experiment-ship were made to acquire relative oil physical characters. This paper describes the brief characters of AMR-OS and presents the relationships between frequency and thickness, brightness temperature and thickness. The experiment results indicate that microwave radiometry is an effective tool for monitoring oil spill pollution, especially under cloud cover conditions. Image resolution must be improved for meeting the requirements of practical use.

In 1987 and 1990, NASDA of Japan launched Marine Observation Satellite-1 (MOS-1) and MOS-1b. On these satellites, the Microwave Scanning Radiometer (MSR) is installed, and until 1996, it had been observing the snowpack in Hokkaido, Japan during the snow season. MSR is a passive sensor that receives weak microwave noises at two frequencies (23.8 and 31.4 GHz) radiated from the surface of the ground. MSR is not able to obtain the local snowpack characteristics but can provide macroscopic snowpack information over a wide area. This paper analyzes the statistical relationship between the depth/grain size of the snowpack in the Hokkaido region and the brightness temperature/emissivity observed by MSR on MOS-1.

The Advanced Earth Observing Satellite-II (ADEOS-II) equipped with the Advanced Microwave Scanning Radiometer (AMSR) will be launched in 2000 by NASDA of Japan. The AMSR is a multi-frequency microwave radiometer, which captures 14 different micro/millimeter-wave noises in the wide frequency band, radiated from the Earth and atmosphere. The satellite microwave radiometer has the potential for obtaining macroscopic information concerning snowpack characteristics. Data processing methods and results analysis are required. The authors developed a method for statistical processing of obtained by the Microwave Scanning Radiometer (MSR) on the Marine Observation Satellite-1 (MOS-I), and tried to interpret the results of the analysis and estimate the snowpack parameters in Hokkaido region. As the MSR received microwave noises at two contiguous frequencies (23.8 and 31.4 GHz), there were some difficulties or limitations for estimating the snowpack parameters. The objective of this paper is the development of a data processing method to estimate the snowpack parameters such as depth and grain size using the data obtained by the AMSR on ADEOS-II. Instead of the brightness temperature observed by the AMSR, the microwave emissivities at five selected frequencies of the AMSR is analyzed using a snowpack model which had been used for the analyses of the data obtained by the MSR on MOS-l. Using the results of the model analysis, the efficiency and accuracy of the method on the snowpack is presented.

The effect of the inhomogeneity of clouds on the brightness temperatures (TBs) measured by the passive microwave radiometer SSM/I (Special Sensor Microwave/Imager) is investigated. The results of a numerical cloud model are used as input for a fully three-dimensional Monte Carlo radiative transfer model to calculate the brightness temperature in the radiometers field of view (FOV) for each SSM/I frequency. These brightness temperatures are compared with those for plane-parallel homogeneous clouds. The strongest reduction of brightness temperatures due to these cloud inhomogeneities occurs in the 37 GHz channel. It is well correlated with the variance of the total cloud water and ice path in the FOV. The high resolution of the 85 GHz channel (15/spl times/13 km) and the doubled sampling rate (Bscan) compared to the other channels provide the data to estimate cloud variance, but caused by the highly non-linear relation between rain/ice content and the 85 GHz brightness temperature some uncertainties arise in the application of simple detection schemes.

Microwave radiometers operating at wavelengths 0.3, 0.8, 1.35 and 2.25 cm were used during CLEOPATRA from the ground to estimate rain rates. A model of the microwave emission of the rain layer taking into account polarization effects used for rain parameters retrieval is briefly described. Intercomparisons with simultaneous measurements with the DLR polarimetric Doppler radar POLDIRAD, distrometers and further ground based instrumentation was used for validation of the algorithm for rain rate estimations by microwave radiometry. >

A physically based algorithm relating microwave satellite radiometer brightness temperatures to land surface parameters is developed, through integrating physical algorithms previously developed at Aerojet for the scattering, absorption, and emission characteristics of land surface and atmosphere components. Numerical simulations based on the algorithm showed how the radiometer observations are influenced by the atmosphere. They also revealed some factors limiting the radiometer ability in monitoring the variation in soil moisture along the canopy depth.

During April of 1995, a field and aircraft experiment was conducted in central and northern Alaska. A millimeter-wave imaging radiometer (MIR), and other sensors, were flown on-board a NASA ER-2 aircraft in a grid pattern centered over Fairbanks. Resulting MIR data show brightness temperature patterns that are related to land cover and snowmelt patterns.

The results of aircraft microwave K- and K/sub a/-band radiometer measurements used for liquid water and water vapour content recovering are presented. The K-band dual-frequency radiometer has been developed in Space Research Institute (Russia). This radiometer provides simultaneous measurements of brightness temperature in two frequency bands due to adjustable dual-frequency filter. The comparison of results obtained by two different retrieval techniques shows good agreement, so also under strong cloud condition. >

Forest biomass is an important factor in the flux of atmospheric CO/sub 2/ and its potential impact on global climatic change. In this study a mathematical evaluation of the potential of microwave radiometers for monitoring forest biomass is carried out. For this purpose, a microwave emission model is developed using the iterative solution of the radiative transfer equation to relate the brightness temperature to the forest geometric and dielectric parameters. Then allometric equations are employed to relate the biomass to forest geometric parameters. Numerical simulations using ground truth collected from Landes Forest of France show that at P- and L-bands the polarization index is correlated to the forest biomass. At C-Band the brightness temperature and the forest biomass are correlated. >

The results of the Joint United States/Russia Internal Wave Remote Sensing Experiment (JUSREX'92) are presented. A Russian research aircraft, TU-134, equipped with both optical and microwave instruments participated in the experiment. In situ data were obtained from the "Akademik Ioffe", a research vessel equipped with contact and remote sensing instruments. To determine surface wind speed and direction, Ka-band nadir-viewing polarimeter was used. Sea surface temperature was measured by means of the S-band radiometer. Brightness temperature and wind vector data were related to true surface data. Wind and temperature fields retrieved from radiometer data were compared with side-looking radar images. The combined analysis of passive and active microwave instrument data has proved important for furthering our understanding of the ocean-atmosphere interaction.

This paper describes ongoing development of an operational algorithm for retrieval of sea surface temperature (SST) from brightness temperature measurements made using the Advanced Microwave Scanning Radiometer (AMSR) system on the ADEOS II satellite.

Microwave measurements strongly depend on the incidence angle of the incoming radiance. Although the SSM/I instruments are designed for constant incidence angle, small deviations caused by the satellite orbits exist. The effects of these incidence angle variations on brightness temperatures are investigated. As a consequence a correction procedure is developed and applied to measured brightness temperatures. Significant differences between corrected and uncorrected brightness temperatures and retrieved meteorological parameters are found, especially for the SSM/I on DMSP F10.

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 previously ignored aspect of microwave observations at low frequencies has been the diurnal variations of the soil moisture and temperature and the impact of these on the brightness temperature. In this investigation, observations were made using a dual frequency radiometer (1.4 and 2.65 GHz) over bare soil, corn and grass 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 2 cm soil moisture and the 2.65 GHz emissivity and between the 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.

The seasonal evolution of microwave emission of different species of deciduous and coniferous trees was studied using ground-based zenith-looking radiometers at 1.4 GHz and 9.5 GHz. The tree brightness temperature follows the annual cycle in phase with growth and loss of leaves. The X-band radiometric data are more sensitive to the changes in leaf volume and leaf water content.

This paper presents a precipitation retrieval algorithm for the Advanced Microwave Scanning Radiometer (AMSR) on the ADEOS-II satellite. This algorithm was developed based on results of radiative transfer model simulations. It uses a combination of microwave emission and scattering signatures, and has a correction for beam-filling. Besides a general description of the algorithm, we show some validation results in this paper.

The feasibility of space-borne microwave radiometers for monitoring the evolution of snow-cover in a drainage area is investigated. A four-winter set of SSM/I radiometer observations for the 51,000 km/sup 2/ River Kemijoki drainage area, Northern Finland, are used for analyses. The results indicate that the used microwave emission model-based automatic inversion algorithm can estimate the regional Snow Water Equivalent (SWE) under dry snow conditions with an overall RMSE of /spl sim/30 mm without using any training reference data on SWE. The retrieval error was found to vary considerably from year to year. At the best, the annual SWE retrieval RMSE showed values as low as /spl sim/20 mm.

Synthetic aperture interferometric radiometers require phase coherent detection to allow the visibility function to be measured and subsequently converted to brightness temperature images. Products of signals between channels produce the complex "visibility" terms of the spatial spectrum of the brightness temperature scene. Today's technology offers the choice of either analog or digital detection methods for relatively low microwave frequencies. Digital detection may offer advantages, particularly in certain instrument configurations. This paper reviews the results of an evaluation of a particular digital method and a variety of FIR filter designs. A programmable, real time processor was developed to study various Hilbert Transform algorithms for digitally forming the in-phase (I) and quadrature (Q) components of the received signals. An overview of the test set-up and test results using several FIR filters is presented, allowing a trade between numerical simplicity and the gain and phase balance between I and Q.

An EOS interdisciplinary science hydrology experiment called Southern Great Plains '97 (SGP97) was conducted by NASA and USDA in Oklahoma during June-July, 1997 in order to acquire data at spatial and temporal scales more typical of possible future satellite systems. A core activity of SGP97 involved mapping surface soil moisture with the ESTAR (Electronically Scanned Thinned Array Radiometer) airborne L-band microwave radiometer on a daily basis for a month over an 11,000 km/sup 2/ area at 800 m resolution. To provide continuous 24-hour microwave brightness temperature measurements over two representative surface covers (winter wheat and grazed pasture) to complement the once-a-day ESTAR data, the two-frequency truck-mounted passive microwave SLMR (S and L Microwave Radiometer) system was deployed to the Department of Energy's ARM/CART Central Facility site near Lament, Oklahoma in the northern part of the SGP97 test region for the month-long experiment. The detailed diurnal time series data available from the SLMR system permits validation and refinement of coupled energy/water balance models at the point scale before these models are extrapolated to the entire SGP97 test area.

Although the L-band (1.4 GHz) is generally considered ideal for passive microwave sensing of soil moisture, near-future satellite instruments such as the Advanced Microwave Scanning Radiometer (AMSR) will provide C-band (/spl sim/7 GHz) observations, not L-band observations. Prior to 1999, adequate field testing of soil moisture retrieval algorithms using C-band observations had been hampered due to a lack of suitable data, particularly aircraft datasets over regions at satellite pixel scales (>1000 km2). The Southern Great Plains 99 (SGP99) Experiment was designed to fill this gap with aircraft flights featuring five low-frequency passive microwave instruments. The C-band observations described in this paper were collected using one of the two new C-band instruments deployed during SGP99: the Airborne C-band Microwave Radiometer (ACMR).

The retrieval of ocean surface wind vector from polarimetric microwave brightness temperature fields is posed as a nonlinear inversion of the geophysical model function (GMF) for emission using maximum likelihood (ML) estimation. Applying the maximum likelihood estimator results in a weighted least-squares minimization problem that is valid for multi-look, multi-frequency, multi-polarization microwave brightness temperature measurements. By coupling this result with an empirically derived GMF, wind direction retrieval is demonstrated using multi-band conically-scanned polarimetric microwave brightness imagery obtained using the Polarimetric Scanning Radiometer (PSR) during observations over the Labrador Sea in March 1997.

During September 15 to October 5, 1997, an intensive experiment to measure atmospheric water vapor was conducted at the Department of Energy's Atmospheric Radiation Measurement Program's Cloud and Radiation Testbed (CART) site in north central Oklahoma. This experiment was called the 1997 Water Vapor Intensive Operating Period (WVIOP'97). Among the goals of WVIOP'97 was the comparison of different methods of measuring precipitable water vapor (PWV). This paper focuses on the inter-comparison of PWV measurements by ground-based microwave radiometers, Global Positioning System-PWV instruments (GPS-PWV), and by radiosondes. For this experiment 3-hourly radiosondes for in situ measurements were deployed. Microwave radiometric measurements of water vapor in the zenith direction were made by two independent radiometers that produce PWV and cloud liquid path from brightness temperature T/sub b/ measurements. These radiometers were operated by the Environmental Technology Laboratory and operate at the frequency pairs of (20.6, 31.65 GHz) and (23.87, 31.65 GHz). The calibration of the instruments was achieved by the so-called "tip cal" method and their data, in terms of derived PWV are compared. Two independent GPS-PWV instruments were also operated 9 km apart and, in addition, two different processing algorithms were applied to the data from each of these instruments.