Microwave dielectric properties of a silt-loam at high frequencies

Microwave brightness temperatures at three frequencies (23.8, 36.5, and 90 GHz) of a carefully smoothed silt-loam were measured over a large range of near-surface soil moisture conditions. The microwave data were collected simultaneously with ground observations of soil moisture, soil temperature, and bulk density. The atmospheric downwelling radiation is computed from the French weather forecast model outputs and cloud coverage surface observations. Assuming that roughness effects are negligible for the studied surface, Fresnel coefficients are used to model soil reflectivities. The relationship between soil moisture and soil reflectivity at high frequencies is then analyzed through existing semi-empirical models of the soil complex dielectric permittivity     

Annual temperature and radiobrightness signatures for bare soils

The authors have developed physically based, diurnal, and annual models for freezing/thawing moist soils subject to annual insolation, radiant heating, and cooling, and sensible and latent heat exchanges with the atmosphere. Both models have the same weather forcing, numerical scheme, and soil constitutive properties. The authors find that surface temperature differences over a diurnal cycle between the annual and diurnal models are as much as -5 K in March, -7 K in June, -4 K in September, and 5 K in December for 38% (by volume fraction) moist soil. This difference occurs because the annual model includes the history of energy fluxes at the surface of the soil. The annual model is linked to microwave emission models for predictions of temporal radiobrightness signatures. The model predicts a relatively weak decrease in diurnal differences in soil temperature with increased moisture content, but a significant decrease in diurnal differences in radiobrightness. It also exhibits notable perturbations in radiobrightness when soils freeze and thaw. The moisture dependent, day-to-night radiobrightness difference is enhanced by as much as -42 K at 19.35 GHz horizontal polarization for frozen soil if daytime thawing occurs     

Interpretation of SSM/I measurements over Greenland

Multispectral brightness temperature (T_B) measurements over Greenland are obtained from the Special Sensor Microwave Imager (SSM/I), which are flown aboard the DMSP satellites. This paper examines the different spectral characteristics over Greenland throughout the year. Although snow covers the vast majority of Greenland, the southern regions rarely exhibit the spectral characteristics associated with snowcover (i.e., T_B decreases at higher frequencies). In fact, the SSM/I polarization and frequency measurements over southern Greenland are more indicative of water than a snow-covered surface (i.e., T_B increases at higher frequencies). A simplified physical model is developed to help explain the anomalous measurements over southern Greenland. Model results indicate that high frequency radiation is mainly scattered by snow grains residing above the subsurface ice layers, whereas low frequency radiation is scattered throughout a much greater depth. Since low frequencies are scattered throughout a greater volume, they are depressed relative to high frequencies, and the typical snowcover signature is absent     

A land surface process/radiobrightness model with coupled heat andmoisture transport in soil

Heat and moisture transport in soil are coupled processes that jointly determine temperature and moisture profiles. The authors present a physically based, one-dimensional (1D), coupled heat and moisture transport hydrology (1-DH) model for bare, unfrozen, moist soils subject to insolation, radiant heating and cooling, and sensible and latent heat exchanges with the atmosphere. A 60-day simulation is conducted to study the effect of dry-down on soil temperature and moisture distributions in summer for bare soil in the Midwest United States. Given a typical initial moisture content of 38% by volume, the authors find that temperature differences between the water transport and no water transport cases exhibit a diurnal oscillation with a slowly increasing amplitude, but never exceed 4.4 K for the 60-day period. However, moisture content of the surface decreases significantly with time for the water transport case and becomes only about 21% at the end of the same period. The 1-DH model is linked to a radiobrightness (1-DH/R) model as a potential means for soil moisture inversion. The model shows that radiobrightness thermal inertia (RTI) correlates with soil moisture if the two radiobrightnesses are taken from times near the thermal extremes, e.g., 2 a.m. and 2 p.m., and that RTI appears temperature-dependent at the ending stages of the drydown simulations where soils are dry and their moisture contents vary slowly. Near times of thermal crossover, the RTI technique is insensitive to soil moisture     

The radiobrightness thermal inertia measure of soil moisture

Radiobrightness thermal inertia (RTI) is proposed as a method for using day-night differences in satellite-sensed radiobrightness to monitor the moisture of Great Plains soils. Diurnal thermal and radiobrightness models are used to examine the sensitivity of the RTI method. Model predictions favor use of the 37.0 and 85.5 GHz, H-polarized channels of the Special Sensor Microwave/Imager (SSM/I). The model further predicts that overflight times near 2:00 AM/PM would be nearly optimal for RTI, that midnight/noon and 4:00 AM/PM are nearly as good, but that the 6:00 AM/PM overflight times of the current SSM/I are particularly poor. Data from the 37.0 GHz channel of the Scanning Multichannel Microwave Radiometer (SMMR) are used to demonstrate that the method is plausible     

Dielectric properties of single crystals of Al2O3, LaAlO3, NdGaO3, SrTiO3, and MgOat cryogenic temperatures

A dielectric resonator technique has been used for measurements of the permittivity and dielectric loss tangent of single-crystal dielectric substrates in the temperature range 20-300 K at microwave frequencies. Application of superconducting films made it possible to determine dielectric loss tangents of about 5×10^-7 at 20 K. Two permittivity tensor components for uniaxially anisotropic samples were measured. Generally, single-crystal samples made of the same material by different manufacturers or by different processes save significantly different losses, although they have essentially the same permittivities. The permittivity of one crystalline ferroelectric substrate, SrTiO₃, strongly depends on temperature. This temperature dependence can affect the performance of ferroelectric thin-film microwave devices, such as electronically tunable phase shifters, mixers, delay lines and filters     

The effect of temperature dependent processes on the performance of1.5-μm compressively strained InGaAs(P) MQW semiconductor diodelasers

We describe measurements of the threshold current I_th and spontaneous emission characteristics of InGaAs (P)-based 1.5-μm compressively strained multiple-quantum-well semiconductor lasers from 90 K to above room temperature. We show that below a break-point temperature, T_B≈130 K, I_th and its temperature dependence are governed by the radiative current. Above this temperature, a thermally activated Auger recombination process becomes the dominant recombination mechanism responsible for both I_th and its temperature sensitivity. At room temperature nonradiative Auger recombination is found to account for approximately 80% of the threshold current in these devices     

基于星载红外高光谱观测用机器学习算法反演大气温湿廓线

星载红外高光谱垂直探测仪GIIRS （Geostationary Interferometric Infrared Sounder）能够实现大气温度和湿度参数高垂直分辨率的观测,为数值天气预报提供精度更高的初始场。基于GIIRS观测辐射值采用BP神经网络（Back Propagation Neural Network）法和深度学习的卷积神经网络（Convolutional Neural Networks, CNN）法反演大气温度、湿度垂直廓线,重点在于CNN法模型的构建与参数的优化,得到反演精度最高的网络模型配置。将训练样本根据不同地表类型和是否有云的影响分为三种方案（方案一:不分类、方案二:陆地/洋面分类、方案三:晴空/有云分类）,分别进行建模、反演和检验。结果表明两种反演算法都有较好的反演精度,相对而言CNN法在所有高度层上反演偏差、均方根误差和平均相对误差均较小,反演精度更高。CNN法温度反演在高层10~200 hPa改进较大,三种分类方案改进的最大值分别为1.15 K、1.06 K和1.02 K;湿度反演在对流层低层500~1000 hPa改进较大,三种分类方案分别平均改进了0.43 g/kg、0.41 g/kg和0.34 g/kg。BP神经网络法方案三时（即分晴空和云时）温度和水汽混合比廓线反演精度最好;CNN算法方案一时（即不对样本数据进行任何分类）反演精度最高。     

Effect of Salinity on the Dielectric Properties of Geological Materials: Implication for Soil Moisture Detection by Means of Radar Remote Sensing

We consider the exploitation of dielectric properties of saline deposits for the detection and mapping of moisture in arid regions on both Earth and Mars. We present simulated and experimental study in order to assess the effect of salinity on the complex permittivity of geological materials and, therefore, on the radar backscattering coefficient in the [1-7 GHz] frequency range. Laboratory measurements are performed on sand/sodium chloride aqueous mixtures using a vectorial network analyzer coupled to an open-ended coaxial dielectric probe. We aim at calibrating and validating semiempirical dielectric mixing models. In particular, we evaluated the dependence of the real and imaginary parts of complex permittivity on the microwave frequency, water content, and salinity. Our results confirm that if the real part is mainly affected by the moisture content, the imaginary part is more sensitive to salinity. In addition to the classic formulas of mixing models, the ionic-conductivity losses, which are due to mobile ions in the saline solution, are taken into account in order to better assess the effect of salinity on the dielectric properties of mixtures. Dielectric mixing models are then used as input parameters for the simulation of the radar backscattering coefficients by means of an analytical model: the integral equation model. Simulation results show that salinity should have a significant impact on the radar backscattering recorded in synthetic aperture radar data in terms of the magnitude of the backscattering coefficient. Moreover, our results suggest that VV polarization provides a greater sensitivity to salinity than HH polarization.     

Impact of horizontal and vertical heterogeneities on retrievals using multiangle microwave brightness temperature data

This paper investigates the impact of heterogeneity at the land surface on geophysical parameters retrieved from multiangle microwave brightness temperature data, such as would be obtained from the Soil Moisture and Ocean Salinity (SMOS) mission. Synthetic brightness temperature data were created using the Common Land (land surface) Model, coupled with a microwave emission model and set within the framework of the North American Land Data Assimilation System (NLDAS). Soil moisture, vegetation optical depth, and effective physical temperature were retrieved using a multiobjective calibration routine similar to the proposed SMOS retrieval algorithm for a typical on-axis range of look angles. The impact of heterogeneity both in the near-surface profiles of soil moisture and temperature and in the land cover on the accuracy of the retrievals was examined. There are significant errors in the retrieved parameters over regions with steep gradients in the near-surface soil moisture profile. These errors are approximately proportional to the difference in the soil water content between the top (at 0.7 cm) and second layer (at 2.7 cm) of the land surface model. The errors resulting from heterogeneity in the land cover are smaller and increase nonlinearly with increasing land-surface heterogeneity (represented by the standard deviation of the optical depth within the pixel). The most likely use of retrieved soil moisture is through assimilation into an LDAS for improved initiation of weather and climate models. Given that information on the soil moisture profile is already available within the LDAS, the error in the retrieved soil moisture as a result of the near-surface profile can be corrected for. The potential errors as a result of land-surface heterogeneity can also be assessed for use in the assimilation process.     

Variational data assimilation of microwave radiobrightnessobservations for land surface hydrology applications

Our ability to accurately describe large-scale variations in soil moisture is severely restricted by process uncertainty and the limited availability of appropriate soil moisture data. Remotely sensed microwave radiobrightness observations can cover large scales but have limited resolution and are only indirectly related to the hydrologic variables of interest. The authors describe a four-dimensional (4D) variational assimilation algorithm that makes best use of available information while accounting for both measurement and model uncertainty. The representer method used is more efficient than a Kalman filter because it avoids explicit propagation of state error covariances. In a synthetic example, which is based on a field experiment, the authors demonstrate estimation performance by examining data residuals. Such tests provide a convenient way to check the statistical assumptions of the approach and to assess its operational feasibility. Internally computed covariances show that the estimation error decreases with increasing soil moisture. An adjoint analysis reveals that trends in model errors in the soil moisture equation can be estimated from daily L-band brightness measurements, whereas model errors in the soil and canopy temperature equations cannot be adequately retrieved from daily data alone. Nonetheless, state estimates obtained from the assimilation algorithm improve significantly on prior model predictions derived without assimilation of radiobrightness data     

Empirically Verified Thermodynamic Model of Gate Capacitance and Threshold Voltage of Nanoelectronic MOS Devices With Applications to HfO2 and ZrO2 Gate Insulators

A thermodynamic variational model derived by minimizing the Helmholtz free energy of the MOS device is presented. The model incorporates an anisotropic permittivity tensor and accommodates a correction for quantum-mechanical charge confinement at the dielectric/substrate interface. The energy associated with the fringe field that is adjacent to the oxide is of critical importance in the behavior of small devices. This feature is explicitly included in our model. The model is verified using empirical and technology-computer-aided-design-generated capacitance-voltage data obtained on MOS devices with ZrO₂, HfO₂, and SiO₂ gate insulators. The model includes considerations for an interfacial low-k interface layer between the silicon substrate and the high-k dielectric. This consideration enables the estimation of the equivalent oxide thickness. The significance of sidewall capacitance effects is apparent in our modeling of the threshold voltage (V_th) for MOS capacitors with effective channel length at 30 nm and below. In these devices, a variation in high-k permittivity produces large differences in V_th. This effect is also observed in the variance of V_th, due to dopant fluctuation under the gate.     

An Empirical Model for the Complex Dielectric Permittivity of Soils as a Function of Water Content

The recent measurements on the dielectric properties of soils have shown that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value at transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas reported in the literature were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of the soil-water mixtures. This model employs the mixing of either the dielectric constants or the refraction indices of ice, water, rock, and air, and treats the transition moisture value as an adjustable parameter. The calculated mixture dielectric constants from the model were found to be in reasonable agreement with the measured results over the entire moisture range of 0-0.5 cm3/cm3. The transition moistures derived from the model range from 0.16 to 0.33 and are strongly correlated with the wilting points of the soils estimated from their textures. This relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.     

Brightness Temperature Reconstruction Using BGI

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 (T_B) 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 T_B 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 T_B data. The radiometric resemblance of this channel with that of the 37 GHz and geocollocation of their T_B 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).     

Tests of sequential data assimilation for retrieving profile soilmoisture and temperature from observed L-band radiobrightness

Sequential data assimilation (Kalman filter optimal estimation) techniques are applied to the problem of retrieving near-surface soil moisture and temperature state from periodic terrestrial radiobrightness observations that update soil heat and moisture diffusion models. The retrieval procedure uses a time-explicit numerical model to continuously propagate the soil state profile, its error of estimation, and its interdepth covariances through time. The model's coupled soil moisture and heat fluxes are constrained by micrometeorology boundary conditions drawn from observations or atmospheric modeling. When radiometer data are available, the Kalman filter updates the state profile estimate by weighing the propagated state, error, and covariance estimates against an a priori estimate of radiometric measurement error. The Kalman filter compares predicted and observed radiobrightnesses directly, so no inverse algorithm relating brightness to physical parameters is required. The authors demonstrate Kalman filter model effectiveness using field observations and a simulation study. An observed 1 m soil state profile is recovered over an eight-day period from daily L-band observations following an intentionally poor initial state estimate. In a four-month simulation study, they gauge the longer term behavior of the soil state retrieval and Kalman gain through multiple rain events, soil dry-downs, and updates from radiobrightnesses     

Microwave (1-100 GHz) dielectric model of leaves

A semiempirical formula for the complex dielectric permittivity of leaves from different plants is found from a comparison of published measurements covering the frequency range from 1 to 100 GHz. The explicit parameters are the dry-matter fraction m_d of the leaf and the permittivity ϵ_SW of saline water with a salinity of about 1 percent. The physical part of the formula is its basis on ϵ_SW while the empirical part is its linearity with m_d. The formula is applicable to fresh leaves; their m _d values are in the range 0.1d<0.5. A test indicates that besides the m_d variation and the spectral dependence the formula also describes the temperature variation correctly     

Retrieving soil moisture from simulated brightness temperatures bya neural network

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°, and at L-band for SMOS's multiple viewing angles of 0°, 10°, 20°, 30°, 40°, and 50° for prairie grassland with a column density of 3.7 km/m². 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     

Moisture diffusion in poltimide films in integrated circuits

This paper reports the use of planar aluminum-PI-aluminum capacitors, in which the variation of low frequency dielectric permittivity is shown to be proportional to absorbed moisture, to carry out in-situ studies of moisture uptake and diffusion in PMDA-ODA device-grade polyimide films. It is found that the equilibrium amount of moisture uptake depends on ambient relative humidity in the temperature range 20-80‡C, and that the diffusion kinetics obey a Fickian model with a diffusion coefficient in the range 3-5 x 10^-9 cm² /sec at room temperature. The diffusion coefficient is temperature dependent, with an activation energy of 0.32-0.34 eV, and is weakly dependent on absorbed moisture at fixed temperature. An asymmetry is observed between absorption and desorption kinetics which correlates with the moisture-dependent diffusion coefficient.     

Microwave Dielectric Behavior of Wet Soil-Part 1: Empirical Models and Experimental Observations

This is the first paper in a two-part sequence that evaluates the microwave dielectric behavior of soil-water mixtures as a function of water content, temperature, and soil textural composition. Part I presents the results of dielectric constant measurements conducted for five different soil types at frequencies between 1.4 and 18 GHz. Soil texture is shown to have an effect on dielectric behavior over the entire frequency range and is most pronounced at frequencies below 5 GHz. In addition, the dielectric properties of frozen soils suggest that a fraction of the soil water component remains liquid even at temperatures of -24° C. The dielectric data as measured at room temperature are summarized at each frequency by polynomial expressions dependent upon both the volumetric moisture content m and the percentage of sand and clay contained in the soil; separate polynomial expressions are given for the real and imaginary parts of the dielectric constant. In Part II, two dielectric mixing models will be presented to account for the observed behavior: 1) a semiempirical refractive mixing model that accurately describes the data and requires only volumetric moisture and soil texture as inputs, and 2) a theoretical four-component mixing model that explicitly accounts for the presence of bound water.     

A comparison of the MIR-estimated and model-calculated fresh water surface emissivities at 89, 150, and 220 GHz

The airborne millimeter-wave imaging radiometer (MIR) measurements over three lakes (surface temperature /spl sim/273 K) in the Midwest region of the USA during February 1997 were used to estimate surface emissivities at 89, 150, and 220 GHz and the results were compared with those calculated from three different dielectric permittivity models for fresh water. The measurements were during clear and dry atmospheric conditions so that the column water vapor could be accurately retrieved and its effect on the MIR measurements predicted. The standard deviations of the estimated emissivities were found to be about 0.003, 0.004, and 0.008 for 89, 150, and 220 GHz, respectively. The errors of the estimation were calculated to be /spl plusmn/0.005, /spl plusmn/0.006, and /spl plusmn/0.011 in the same order of frequency, respectively, based on the MIR measurement accuracy of /spl plusmn/1 K in the brightness temperature range of 190-290 K. The estimated emissivities at normal incidence, under the assumption of a calm water surface, compare quite well with values generated by the model of P. Stogryn et al. (1995). These estimated values are slightly lower than those calculated from the model of H. J. Liebe et al. (1991) at both 89 and 150 GHz. The estimated 89 GHz emissivity is higher than that calculated from the model of W. Ellison et al. (1998). Additionally, the retrievals using different models of atmospheric absorption as well as off-nadir measurements of the MIR are explored. The impact of these retrievals on the comparison of estimated and calculated emissivities is discussed.