Airborne active and passive microwave observations of Super TyphoonFlo

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     

Sensitivity of passive microwave snow depth retrievals to weather effects and snow evolution

Snow fall and snow accumulation are key climate parameters due to the snow's high albedo, its thermal insulation, and its importance to the global water cycle. Satellite passive microwave radiometers currently provide the only means for the retrieval of snow depth and/or snow water equivalent (SWE) over land as well as over sea ice from space. All algorithms make use of the frequency-dependent amount of scattering of snow over a high-emissivity surface. Specifically, the difference between 37- and 19-GHz brightness temperatures is used to determine the depth of the snow or the SWE. With the availability of the Advanced Microwave Scanning Radiometer (AMSR-E) on the National Aeronautics and Space Administration's Earth Observing System Aqua satellite (launched in May 2002), a wider range of frequencies can be utilized. In this study we investigate, using model simulations, how snow depth retrievals are affected by the evolution of the physical properties of the snow (mainly grain size growth and densification), how they are affected by variations in atmospheric conditions and, finally, how the additional channels may help to reduce errors in passive microwave snow retrievals. The sensitivity of snow depth retrievals to atmospheric water vapor is confirmed through the comparison with precipitable water retrievals from the National Oceanic and Atmospheric Administration's Advanced Microwave Sounding Unit (AMSU-B). The results suggest that a combination of the 10-, 19-, 37-, and 89-GHz channels may significantly improve retrieval accuracy. Additionally, the development of a multisensor algorithm utilizing AMSR-E and AMSU-B data may help to obtain weather-corrected snow retrievals.     

Galactic noise and passive microwave remote sensing from space at L-band

The spectral window at L-band (1.413 GHz) is important for passive remote sensing of soil moisture and ocean salinity from space, parameters that are needed to understand the hydrological cycle and ocean circulation. At this frequency, radiation from celestial (mostly Galactic) sources is strong and, unlike the constant cosmic background, this radiation is spatially variable. This paper presents a modern radiometric map of the celestial sky at L-band and a solution for the problem of determining what portion of the sky is seen by a down-looking radiometer in orbit. The data for the radiometric map are derived from recent radio astronomy surveys and are presented as equivalent brightness temperature suitable for remote sensing applications. Examples using orbits and antennas representative of those contemplated for remote sensing of soil moisture and sea surface salinity from space are presented to illustrate the signal levels to be expected. Near the Galactic plane, the contribution can exceed several kelvin.     

Mapping the spatial distribution and time evolution of snow water equivalent with passive microwave measurements

This paper presents an algorithm that estimates the spatial distribution and temporal evolution of snow water equivalent and snow depth based on passive remote sensing measurements. It combines the inversion of passive microwave remote sensing measurements via dense media radiative transfer modeling results with snow accumulation and melt model predictions to yield improved estimates of snow depth and snow water equivalent, at a pixel resolution of 5 arc-min. In the inversion, snow grain size evolution is constrained based on pattern matching by using the local snow temperature history. This algorithm is applied to produce spatial snow maps of Upper Rio Grande River basin in Colorado. The simulation results are compared with that of the snow accumulation and melt model and a linear regression method. The quantitative comparison with the ground truth measurements from four Snowpack Telemetry (SNOTEL) sites in the basin shows that this algorithm is able to improve the estimation of snow parameters.     

Inversion of snow parameters from passive microwave remote sensingmeasurements by a neural network trained with a multiple scatteringmodel

The inversion of snow parameters from passive microwave remote sensing measurements is performed with a neural network trained with a dense-media multiple-scattering model. The input-output pairs generated by the scattering model are used to train the neural network. Simultaneous inversion of three parameters, mean-grain size of ice particles in snow, snow density, and snow temperature from five brightness temperatures, is reported. It is shown that the neural network gives good results for simulated data. The absolute percentage errors for mean-grain size of ice particles and snow density are less than 10%, and the absolute error for snow temperature is less than 3 K. The neural network with the trained weighting coefficients of the three-parameter model is also used to invert SSMI data taken over the Antarctic region     

Integrating in situ and multiscale passive microwave data for estimation of subgrid scale snow water equivalent distribution and variability

New multiscale research datasets were acquired in central Saskatchewan, Canada during February 2003 to quantify the effect of spatially heterogeneous land cover and snowpack properties on passive microwave snow water equivalent (SWE) retrievals. Microwave brightness temperature data at various spatial resolutions were acquired from tower and airborne microwave radiometers, complemented by spaceborne Special Sensor Microwave/Imager (SSM/I) data for a 25/spl times/25 km study area centered on the Old Jack Pine tower in the Boreal Ecosystem Research and Monitoring Sites (BERMS). To best address scaling issues, the airborne data were acquired over an intensively spaced grid of north-south and east-west oriented flight lines. A coincident ground sampling program characterized in situ snow cover for all representative land cover types found in the study area. A suite of micrometeorological data from seven sites within the study area was acquired to aid interpretation of the passive microwave brightness temperatures. The in situ data were used to determine variability in SWE, snow depth, and density within and between forest stands and land cover types within the 25/spl times/25 km SSM/I grid cell. Statistically significant subgrid scale SWE variability in this mixed forest environment was controlled by variations in snow depth, not density. Spaceborne passive microwave SWE retrievals derived using the Meteorological Service of Canada land cover sensitive algorithm suite were near the center of the normally distributed in situ measurements, providing a reasonable estimate of the mean grid cell SWE. A realistic level of SWE variability was captured by the high-resolution airborne data, showing that passive microwave retrievals are capable of capturing stand-to-stand SWE variability if the imaging footprint is sufficiently small.     

Fusion of satellite active and passive microwave data for sea icetype concentration estimates

Young first-year sea ice is nearly as important as open water in modulating heat flux between the ocean and atmosphere in the Arctic. Just after the onset of freeze-up, first-year ice is in the early stages of growth and will consist of young first-year and thin ice. The distribution of sea ice in this thickness range impacts heat transfer in the Arctic. Therefore, improving the estimates of ice concentrations in this thickness range is significant. The NASA Team Algorithm (NTA) for passive microwave data inaccurately classifies sea ice during the melt and freeze-up seasons because it misclassifies multiyear ice as first-year ice. We developed a hybrid fusion technique for incorporating multiyear ice information derived from synthetic aperture radar (SAR) images into a passive microwave algorithm to improve ice type concentration estimates. First, we classified SAR images using a dynamic thresholding technique and estimated the multiyear ice concentration. Then we used the SAR-derived multiyear ice concentration to constrain the NTA and obtained an improved first-year ice concentration estimate. We computed multiyear and first-year ice concentration estimates over a region in the eastern-central Arctic in which field observations of ice and in situ radar backscatter measurements were performed. The fused estimates of first-year and multiyear ice concentration appear to be more accurate than NTA, based on ice observations that were logged aboard the US Coast Guard Icebreaker Polar Star in the study area during 1991     

Ground-based passive microwave remote sensing observations of soilmoisture at S-band and L-band with insight into measurementaccuracy

A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, AL, from July 1-14, 1996. The goal of the experiment was to evaluate the overall performance of an empirically-based retrieval algorithm at S-band and L-band under a different set of conditions and to characterize the site-specific accuracy inherent within the technique. With high temporal frequency observations at S-band and L-band, the authors were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L-band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cm³/cm³ with an indication that it is less at higher moisture values. The S-band emitting depth was not readily distinguishable from L-band. The uncertainty in remotely sensed soil moisture observations due to surface heterogeneity and temporal variability in variables and parameters was characterized by imposing random errors on the most sensitive variables and parameters and computing the confidence limits on the observations. Discrepancies between remotely sensed and gravimetric soil moisture estimates appear to be larger than those expected from errors in variable and parameter estimation. This would suggest that a vegetation correction procedure based on more dynamic modeling may be required to improve the accuracy of remotely sensed soil moisture     

Snow water equivalent retrieval in a Canadian boreal environment from microwave measurements using the HUT snow emission model

Snow water equivalent (SWE) is a critical parameter for climatological and hydrological studies over northern high-latitude areas. In this paper, we study the usability of the Helsinki University of Technology (HUT) snow emission model for the estimation of SWE in a Canadian boreal forest environment. The experimental data (airborne passive microwave and ground-based data) were acquired during the Boreal Ecosystem-Atmosphere Study winter field campaign held in February 1994 in Central Canada. Using the experimental dataset, surface brightness temperatures at 18 and 37 GHz (vertical polarization) were simulated with the HUT snow emission model and compared to those acquired by the airborne sensors. The results showed an important underestimation at 37 GHz (-27 K) and an overestimation at 18 GHz (10 K). In this paper, we demonstrate that the errors in the model simulations are due mainly to the extinction coefficient modeling, which is a function of snow grain size. Therefore, we propose a new semiempirical function for the extinction coefficient, based on an empirical correction to the Rayleigh scattering expression. Results presented in this paper show that the proposed function improves the HUT model accuracy to predict brightness temperature in the experimental context considered, with a mean error of /spl plusmn/5 K and /spl plusmn/9 K, respectively, at 18 and 37 GHz, and a negligible bias (less than 4 K) in both cases. These errors are comparable in magnitude to the accuracy of the radiometers used during the airborne flights. SWE was retrieved using the modified HUT snow emission model based on an iterative inversion technique. SWE was estimated with a mean error of /spl plusmn/10 mm and a negligible bias. Only a rough knowledge of mean snow grain size /spl phi/~ was required in the inversion procedure. The effects of possible errors on mean snow grain size /spl phi/~ are presented and discussed.     

Inductor implementation using a canonical number of active and passive elements

There is quite a large number of active simulated inductor realizations in the literature, but all of these presented topologies except the recently proposed inductor simulators have either more than one active component or more than a minimum number of passive components. Two resistors and one capacitor are the required canonical number of passive elements to implement a simulated inductor. In this study, a new topology using a single minus-type modified inverting first-generation current conveyor (MICCI-) as a novel active device and a minimum number of passive elements is proposed. The MICCI- is a voltage gain-variable current conveyor (GVCC). Simulation results and non-ideal voltage and current gains effects for the proposed circuit are given.     

Average areal water equivalent of snow in a mountain basin using microwave and visible satellite data

Satellite microwave and millimeter-wave data have been used to evaluate the average areal water equivalent of snow cover in the mountainous Rio Grande basin in Colorado. Areal water equivalent data for the basin were obtained from contoured values of point measurements and from elevation-zone water volume values generated by a reliable snowmelt-runoff model using data on visible snow-cover extent. A significant relationship between the difference in brightness temperature at two different frequencies (37 and 18 GHz) and a basin-wide average snow-water equivalent value was obtained. This relationship and microwave observations were used to estimate the average areal water equivalent of the snow cover.<>     

Retrieval of cloud base heights from passive microwave and cloudtop temperature data

Water vapor profiling algorithms that treat liquid clouds explicitly yield a cloud base height as a byproduct. A single case of a water vapor profile retrieval using a combination of the SSM/T-2 on the DMSP satellite and cloud parameters from the AVHRR on the NOAA satellite retrieved a reasonable cloud base. While hardly definitive, this case is suggestive. The authors examine the cloud base signal in a combination of the SSM/1 and SSM/T-2 on the DMSP satellite from a theoretical point of view. It is shown that the signal is strong enough for a useful retrieval only over the ocean. For low altitudes, a cloud top temperature (CTT) constraint, as could be provided from an infrared radiometer, is required. While difficult with the DMSP-NOAA satellite combination, this has become much easier with the recent launch of NOAA-K with the AMSU-B and AVHRR. It is shown that the signal is acceptable over the relevant range of cloud liquid water content values. To achieve useful results, some local tuning of the algorithm will be necessary. This tuning could take the form of water vapor profile covariance matrices, climatological estimates of the cloud liquid water density, or purely empirical methods. Broken and multilayer clouds provide additional complications to the problem     

Retrieval of land and sea brightness temperatures from mixedcoastal pixels in passive microwave data

A technique is presented to separate uncontaminated land and sea brightness temperatures from mixed coastal pixels in 37-GHz vertically polarized passive microwave data from the Special Sensor Microwave Imager (SSM/I) instrument. Combining a mathematical model of the instrument response over several neighboring footprints with a GIS representation of the coastline yields a relationship between land and sea brightness temperatures and radiation measurements made at the satellite. Inverting this relationship allows separate land and sea brightness temperature values to be derived for each mixed coastal pixel in the original image. The technique has been successfully applied to 37-GHz vertically polarized SSM/I imagery for test areas covering the Gulf of Aden and the British Isles. Errors in the retrieved brightness temperatures were estimated to be of the order of 1-2 K     

Ku-band and S-band observations of the differential propagation constant in snow

Observations of the differential propagation constant in snow are reported. These observations, made with circularly-polarized radars, indicate that the principal effect of anisotropy is to produce a differential phase shift. A value of0.36degper kilometer has been obtained for propagation through snow at a wavelength of 10.4 cm; at 1.8 cm values ranging from0.16degto1.17degper kilometer were observed in moderate to heavy snow.     

Synergy of active and passive satellite microwave data for the study of first-year sea ice in the Caspian and Aral seas

The paper discusses application of active and passive microwave data for assessment of time and space variations of first-year ice cover. The Caspian and Aral seas are chosen as main study areas. The Caspian Sea evolution is primarily climate driven, while for the Aral Sea there is a mix of anthropic and climate factors. We analyze ice cover conditions using a novel method that combines active and passive satellite measurements for ice discrimination. This method uses the synergy of simultaneous data from active (radar altimeter) and passive (radiometer) microwave instruments onboard the TOPEX/Poseidon (T/P) satellite, launched in 1992. The benefits, drawbacks, and potential of ice cover studies using the proposed method are discussed. We analyze in detail how this method is influenced by the difference in footprints of the T/P sensors and by the radiometric properties of ice and snow at different stages of ice cover evolution. In order to link the T/P-derived results to historical observations that end in the mid-1980s, long time series of passive microwave data from SMMR and SSM/I sensors have also been analyzed. Satellite time series of ice cover extent and duration of ice period have been obtained for the Caspian and Aral seas since 1978. A good agreement is obtained between historical and satellite data, with significant spatial and temporal variability of ice conditions. There is a marked decrease of both duration of ice season and ice extent during the winters 1998/1999-2001/2002. These satellite-derived time series of sea ice parameters are very valuable in view of the heterogeneous and mostly unpublished data on ice conditions over the Caspian and Aral seas since the mid-1980s.     

Hail embryons detection in clouds using passive and active radars in millimeter and submillimeter wave bands

Two detection methods of hail embryons in a cloud are discussed in the paper: combined passive/active and purely active sensing of a convective cloud from board of air or space carrier. The first method makes it possible to determine the spectral dependence of absorption coefficient by oversized drops in convective cloud in the millimeter (MM) and submillimeter (SbMM) wavebands. With this purpose a highly sensitive 16-channel Dicke radiometer is used. In the second method a multiwave (12 wavelength) active radar is used to determine the spectral dependence of backscatter coefficient in the same wavebands. Variation of these spectral characteristics in time makes possible the detection of physical processes taking place in a cloud, such as drops drowth and evaporation, as well as transition of oversized drops into the overcooled state. The instant of water/ice phase transition in oversized drops is determined in both methods by means of active radar in SbMM waveband (in the transparency “window” of ice and atmosphere, 0.64 mm). Corresponding hardware, antennas, and wavelengths are considered for active/passive and purely active sensind of clouds. The effect of antenna beamwidth in SbMM on anomalous backscatter is discussed.     

The complex dielectric constant of pure and sea water from microwave satellite observations

We provide a new fit for the microwave complex dielectric constant of water in the salinity range between 0-40 ppt using two Debye relaxation wavelengths. For pure water, the fit is based on laboratory measurements in the temperature range between -20/spl deg/C and +40/spl deg/C including supercooled water and for frequencies up to 500 GHz. For sea water, our fit is valid for temperatures between -2/spl deg/C and +29/spl deg/C and for frequencies up to at least 90 GHz. At low frequencies, our new model is a modified version of the Klein-Swift model. We compare the results of the new fit with various other models and provide a validation using an extensive analysis of brightness temperatures from the Special Sensor Microwave Imager.     

Automated contour detection in X-ray left ventricular angiograms using multiview active appearance models and dynamic programming

This paper describes a new approach to the automated segmentation of X-ray left ventricular (LV) angiograms, based on active appearance models (AAMs) and dynamic programming. A coupling of shape and texture information between the end-diastolic (ED) and end-systolic (ES) frame was achieved by constructing a multiview AAM. Over-constraining of the model was compensated for by employing dynamic programming, integrating both intensity and motion features in the cost function. Two applications are compared: a semi-automatic method with manual model initialization, and a fully automatic algorithm. The first proved to be highly robust and accurate, demonstrating high clinical relevance. Based on experiments involving 70 patient data sets, the algorithm's success rate was 100% for ED and 99% for ES, with average unsigned border positioning errors of 0.68 mm for ED and 1.45 mm for ES. Calculated volumes were accurate and unbiased. The fully automatic algorithm, with intrinsically less user interaction was less robust, but showed a high potential, mostly due to a controlled gradient descent in updating the model parameters. The success rate of the fully automatic method was 91% for ED and 83% for ES, with average unsigned border positioning errors of 0.79 mm for ED and 1.55 mm for ES.     

Novel grounded parallel inductance simulators realization using a minimum number of active and passive components

In this paper novel lossless and lossy grounded parallel inductance simulators are reported. All grounded inductor simulator circuits employing only a single DXCCII and three passive components are proposed. The proposed topologies realized all grounded parallel inductance variations. To demonstrate the performance of the presented DXCCII based parallel inductance simulators, we used one of the circuits to construct a third order high-pass filter, a voltage-mode band-pass filter and LC oscillator. Simulation results are given to confirm the theoretical analysis. The proposed DXCCII and its applications are simulated using CMOS 0.35 μm technology.