Channel Response Function Research Articles

Establishing a time‐varying flood‐wave impulse function combined with a dynamic machine‐learning technique in response to the disturbance of boundary conditions

AbstractTo seek other alternative approaches besides numerical methods, the linearized Saint Venant equations were utilized to derive the channel response functions for simulating streamflow. This study advocates developing a new approach to make the temporal distribution of response functions more flexible by introducing time‐varying reference parameters which depend on both the upstream inflow and the downstream boundary conditions. Moreover, to expand the model applicability in natural channels with irregular cross‐sectional shapes affected by the unsteady inflow, lateral flow, and the variation of tide level, a dynamic neural network algorithm is jointly applied to determine more appropriate time‐varying hydraulic parameters which are adopted in the channel flow response functions respectively derived from upstream and downstream boundary conditions. The tidal level at the estuary and the upstream inflow discharge are simultaneously considered influential factors to determine an optimal set of reference parameters by applying a machine learning technique, and this prediction can further be provided for updating the channel response functions. The novelty of this study is to propose a complete methodology to combine channel response functions with the machine learning algorithm for ameliorating the accuracy of channel flow simulation and resolving the uncertainty of model parameters. Therefore, by using the proposed method, not only the physical mechanism of Saint Venant equations can be preserved, but also the optimal hydraulic parameters can be specified. The problem of numerical instability during channel flow routing can be eliminated by using the proposed new model and therefore the reliability of real‐time flood forecasting can be reinforced.

Intelligent Reflecting Surface-Assisted Physical Layer Key Generation with Deep Learning in MIMO Systems

Physical layer secret key generation (PLKG) is a promising technology for establishing effective secret keys. Current works for PLKG mostly study key generation schemes in ideal communication environments with little or even no signal interference. In terms of this issue, exploiting the reconfigurable intelligent reflecting surface (IRS) to assist PLKG has caused an increasing interest. Most IRS-assisted PLKG schemes focus on the single-input-single-output (SISO), which is limited in future communications with multi-input-multi-output (MIMO). However, MIMO could bring a serious overhead of channel reciprocity extraction. To fill the gap, this paper proposes a novel low-overhead IRS-assisted PLKG scheme with deep learning in the MIMO communications environments. We first combine the direct channel and the reflecting channel established by the IRS to construct the channel response function, and we propose a theoretically optimal interaction matrix to approach the optimal achievable rate. Then we design a channel reciprocity-learning neural network with an IRS introduced (IRS-CRNet), which is exploited to extract the channel reciprocity in time division duplexing (TDD) systems. Moreover, a PLKG scheme based on the IRS-CRNet is proposed. Final simulation results verify the performance of the PLKG scheme based on the IRS-CRNet in terms of key generation rate, key error rate and randomness.

Tracking the Contents of Spatial Working Memory during an Acute Bout of Aerobic Exercise.

Recent studies have reported enhanced visual responses during acute bouts of physical exercise, suggesting that sensory systems may become more sensitive during active exploration of the environment. This raises the possibility that exercise may also modulate brain activity associated with other cognitive functions, like visual working memory, that rely on patterns of activity that persist beyond the initial sensory evoked response. Here, we investigated whether the neural coding of an object location held in memory is modulated by an acute bout of aerobic exercise. Participants performed a spatial change detection task while seated on a stationary bike at rest and during low-intensity cycling (∼50 watts/50 RPM). Brain activity was measured with EEG. An inverted encoding modeling technique was employed to estimate location-selective channel response functions from topographical patterns of alpha-band (8-12 Hz) activity. There was strong evidence of robust spatially selective responses during stimulus presentation and retention periods both at rest and during exercise. During retention, the spatial selectivity of these responses decreased in the exercise condition relative to rest. A temporal generalization analysis indicated that models trained on one time period could be used to reconstruct the remembered locations at other time periods, however, generalization was degraded during exercise. Together, these results demonstrate that it is possible to reconstruct the contents of working memory at rest and during exercise, but that exercise can result in degraded responses, which contrasts with the enhancements observed in early sensory processing.

Comparison and Synergy of BPSK and BOC Modulations in GNSS Reflectometry

Signals from global navigation satellite systems (GNSSs) have been advocated as opportunities for remote sensing of the Earth. In the multi-GNSS era, signals from different constellation, at different frequency, and under different modulation are available to facilitate such applications. Existing open service GNSS signals can be roughly categorized as either binary phase-shift keying (BPSK) modulation or binary offset carrier (BOC) modulation; it is desired to establish a unified data processing procedure to account for all these signals. This article proposes a framework to synergize BPSK and BOC signals for GNSS reflectometry (GNSS-R) applications by establishing a channel response function to model the scattering phenomena and a commutative diagram to illustrate the interrelationship among direct and reflected signals under different modulations. The results are verified by processing the flight test data of the GNSS-R receiver of the TRITON mission.

Inverted Encoding Models Reconstruct an Arbitrary Model Response, Not the Stimulus.

Probing how large populations of neurons represent stimuli is key to understanding sensory representations as many stimulus characteristics can only be discerned from population activity and not from individual single-units. Recently, inverted encoding models have been used to produce channel response functions from large spatial-scale measurements of human brain activity that are reminiscent of single-unit tuning functions and have been proposed to assay “population-level stimulus representations” (Sprague et al., 2018a). However, these channel response functions do not assay population tuning. We show by derivation that the channel response function is only determined up to an invertible linear transform. Thus, these channel response functions are arbitrary, one of an infinite family and therefore not a unique description of population representation. Indeed, simulations demonstrate that bimodal, even random, channel basis functions can account perfectly well for population responses without any underlying neural response units that are so tuned. However, the approach can be salvaged by extending it to reconstruct the stimulus, not the assumed model. We show that when this is done, even using bimodal and random channel basis functions, a unimodal function peaking at the appropriate value of the stimulus is recovered which can be interpreted as a measure of population selectivity. More precisely, the recovered function signifies how likely any value of the stimulus is, given the observed population response. Whether an analysis is recovering the hypothetical responses of an arbitrary model rather than assessing the selectivity of population representations is not an issue unique to the inverted encoding model and human neuroscience, but a general problem that must be confronted as more complex analyses intervene between measurement of population activity and presentation of data.

Structure Optimization Model of Comprehensive Transport Corridor Based on Resource Constraints

From the manager and the traveler’s point of view, a bi-level programming model of structure optimization considering multi factors is proposed for comprehensive transportation corridor with parallel structure. In the higher level model, land resource consumption, upper model energy consumption and environmental emissions as indicators are selected as indexes to minimize the social resource cost. In the lower level model, the Mode-Path User Equilibrium model is selected for traffic distribution. To minimize the total travel cost of travelers, the supply and demand balance coefficient is selected as the channel response function and a model solution algorithm is designed based on genetic algorithm. At last, the proposed model is applied to Zhejiang Province Hangzhou Ningbo transportation corridor. The channel traffic demand is calculated for the planning year and the reasonable channel structure optimization program is given, which proves that the model is scientific and effective.

Intercalibration between HIRS/2 and HIRS/3 channel 12 based on physical considerations

Abstract. High-resolution Infrared Radiation Sounder (HIRS) brightness temperatures at channel 12 (T12) can be used to assess the water vapour content of the upper troposphere. The transition from HIRS/2 to HIRS/3 in 1999 involved a shift in the central wavelength of channel 12 from 6.7 to 6.5 µm, causing a discontinuity in the time series of T12. To understand the impact of this change in the measured brightness temperatures, we have performed radiative transfer calculations for channel 12 of HIRS/2 and HIRS/3 instruments, using a large set of radiosonde profiles of temperature and relative humidity from three different sites. Other possible changes within the instrument, apart from the changed spectral response function, have been assumed to be of minor importance, and in fact, it was necessary to assume as a working hypothesis that the spectral and radiometric calibration of the two instruments did not change during the relatively short period of their common operation. For each radiosonde profile we performed two radiative transfer calculations, one using the HIRS/2 channel response function of NOAA 14 and one using the HIRS/3 channel response function of NOAA 15, resulting in negative differences of T12 (denoted as ΔT12:=T12/15-T12/14) ranging between −12 and −2 K. Inspection of individual profiles for large, medium and small values of ΔT12 pointed to the role of the mid-tropospheric humidity. This guided us to investigate the relation between ΔT12 and the channel 11 brightness temperatures which are typically used to detect signals from the mid-troposphere. This allowed us to construct a correction for the HIRS/3 T12, which leads to a pseudo-channel 12 brightness temperature as if a HIRS/2 instrument had measured it. By applying this correction we find an excellent agreement between the original HIRS/2 T12 and the HIRS/3 data inferred from the correction method with R=0.986. Upper-tropospheric humidity (UTH) derived from the pseudo HIRS/2 T12 data compared well with that calculated from intersatellite-calibrated data, providing independent justification for using the two intercalibrated time series (HIRS/2 and HIRS/3) as a continuous HIRS time series for long-term UTH analyses.

Inverted Encoding Models of Human Population Response Conflate Noise and Neural Tuning Width.

Channel-encoding models offer the ability to bridge different scales of neuronal measurement by interpreting population responses, typically measured with BOLD imaging in humans, as linear sums of groups of neurons (channels) tuned for visual stimulus properties. Inverting these models to form predicted channel responses from population measurements in humans seemingly offers the potential to infer neuronal tuning properties. Here, we test the ability to make inferences about neural tuning width from inverted encoding models. We examined contrast invariance of orientation selectivity in human V1 (both sexes) and found that inverting the encoding model resulted in channel response functions that became broader with lower contrast, thus apparently violating contrast invariance. Simulations showed that this broadening could be explained by contrast-invariant single-unit tuning with the measured decrease in response amplitude at lower contrast. The decrease in response lowers the signal-to-noise ratio of population responses that results in poorer population representation of orientation. Simulations further showed that increasing signal to noise makes channel response functions less sensitive to underlying neural tuning width, and in the limit of zero noise will reconstruct the channel function assumed by the model regardless of the bandwidth of single units. We conclude that our data are consistent with contrast-invariant orientation tuning in human V1. More generally, our results demonstrate that population selectivity measures obtained by encoding models can deviate substantially from the behavior of single units because they conflate neural tuning width and noise and are therefore better used to estimate the uncertainty of decoded stimulus properties.SIGNIFICANCE STATEMENT It is widely recognized that perceptual experience arises from large populations of neurons, rather than a few single units. Yet, much theory and experiment have examined links between single units and perception. Encoding models offer a way to bridge this gap by explicitly interpreting population activity as the aggregate response of many single neurons with known tuning properties. Here we use this approach to examine contrast-invariant orientation tuning of human V1. We show with experiment and modeling that due to lower signal to noise, contrast-invariant orientation tuning of single units manifests in population response functions that broaden at lower contrast, rather than remain contrast-invariant. These results highlight the need for explicit quantitative modeling when making a reverse inference from population response profiles to single-unit responses.

Wave propagation in linearized shallow flows of power-law fluids

Abstract A depth-averaged model with a power-law rheology, usually adopted for debris flow of fine sediment-water mixtures, is analytically studied, considering the complete (Full Dynamic Model) and the simplified momentum equations, known as Kinematic, Diffusion, and Quasi-steady Models. Applying the Laplace transform to the linearized equations, the analytical first-order expressions of the upstream and downstream spatio-temporal channel response functions are derived for the full and the approximate models. Both shear-thinning and shear-thickening fluids have been considered in hypocritical and linearly stable conditions, to investigate the influence of the rheology on the wave propagation. The effect of the upstream and downstream boundary conditions is considered assuming a finite channel length. The analytic description of the various linearized approximations allows a multi-faceted comparison of the wave propagation. About the basic wave characteristics, in the entire investigated range of Froude numbers and for all the considered rheologies, the Kinematic and Diffusive models underestimate the primary wave celerity and the Quasi-steady model underestimates the wave round-trip time. However, the examination of the response function reveals that the approximate models may provide relatively accurate reproduction of the full dynamic response. Moreover, the analytical solutions in the Laplace variables permit a systematic analysis of some relevant shape factors of the response functions. Independently on the models and the rheology, the damping of the downstream response function is several orders of magnitude larger than that of the upstream one. The results of the shape factor analysis of the upstream response function indicate that the diffusive approximation is the most accurate one. The performed comparison among the wave characteristics of the different approximations provides indications on the applicability of the simplified models for predicting debris or mud flows.

Underwater sound propagation and scattering in Ports and Harbors

Ports and Harbors are crucial life lines in our economy and commerce. To ensure safe and efficient utilization of these important facilities, a thorough understanding of underwater sound propagation and scattering in very shallow water regions is critical. These regions however, present a challenging waveguide for underwater acoustics. Weather the goal is active acoustics (such as underwater communication) or passive acoustics (such as source detection and localization), detailed understanding of channel response function is necessary in order to develop and apply proper security measures. Several studies in recent years have addressed interesting results in acoustic signal propagation and scattering. These include effects of sound speed profile in water column, sea surface dynamic behavior, and seafloor attenuation. Signal coherence, and spatial and temporal variabilities due to environmental parameters have all been examined and to some extent modeled. Deterministic features due to interaction of broadband acoustic signals with the dynamic environment are shown. These results have been incorporated in development of robust underwater communications that can also be utilized for Harbor security implementation. In this paper, we present results of several recent experiments and modeling using Ray and Parabolic Equation approaches to understand this problem. [Work supported by ONR 322 OA.]

POES MEPED differential flux retrievals and electron channel contamination correction

AbstractA correction method to remove proton contamination from the electron channels of the Polar‐orbiting Operational Environmental Satellites Medium Energy Proton/Electron Detector (MEPED) is described. Proton contamination estimates are based on measurements in five of the MEPED proton spectral channels. A constrained inversion of the MEPED proton channel response function matrix is used to calculate proton differential flux spectra. In this inversion, the proton energy distribution is described by a weighted combination of exponential, power law, and Maxwellian distributions. Proton contamination in the MEPED electron spectral channels is derived by applying the electron channel proton sensitivities to the proton fluxes from the best fit proton spectra. Once the electron channel measurements are corrected for proton contamination, an inversion of the electron channel response function matrix is used to calculate electron differential flux spectra. A side benefit of the method is that it yields an estimate for the integrated electron flux in the energy range from 300 keV to 2.5 MeV with a center energy at ~800 keV. The final product is a differential spectrum of electron flux covering the energy range from about 10 keV to 2.5 MeV that is devoid of proton contamination except during large solar proton events. Comparisons of corrected MEPED differential fluxes to the Detection of Electromagnetic Emissions Transmitted from Earthquake Regions Instrument for Detecting Particles show that MEPED fluxes are greater than what is expected from altitude‐induced particle population changes; this is attributed at least partially to measurement differences in pitch angle range.

Rotation measure synthesis revisited

Abstract We reformulate rotation measure (RM) synthesis for data sets with discrete frequency channels and an arbitrary channel response function. The most commonly used version of the formalism by Brentjens & De Bruyn assumes a top-hat response function in wavelength squared, while real data sets can often be approximated better with a top-hat in frequency. We simulate mock data sets for various source geometries, using a top-hat response function in frequency, and we compare the quality of the RM spectra that are found with both formalisms. We include the response function of the simulated data to calculate exact RM spectra using our formalism. We show that the formalism by Brentjens & De Bruyn produces accurate results even if depolarization at the lowest frequencies in the observing band is severe. If RMs are large, our formalism reconstructs the emitted signal more accurately, with a higher amplitude and (in most cases) a narrower RM spread function. Our formalism can also detect sources with larger (absolute) RMs for a given sensitivity level of the observations.

Representative wavelengths absorption parameterization applied to satellite channels and spectral bands

Accurate modeling of wavelength-integrated radiative quantities, e.g. integrated over a spectral band or an instrument channel response function, requires computations for a large number of wavelengths if the radiation is affected by gas absorption which typically comprises a complex line structure. In order to increase computational speed of modeling radiation in the Earth׳s atmosphere, we parameterized wavelength-integrals as weighted means over representative wavelengths. We parameterized spectral bands of different widths (1cm−1, 5cm−1, and 15cm−1) in the solar and thermal spectral range, as well as a number of instrument channels on the ADEOS, ALOS, EarthCARE, Envisat, ERS, Landsat, MSG, PARASOL, Proba, Sentinel, Seosat, and SPOT satellites. A root mean square relative deviation lower than 1% from a “training data set” was selected as the accuracy threshold for the parameterization of each band and channel. The training data set included high spectral resolution calculations of radiances at the top of atmosphere for a set of highly variable atmospheric states including clouds and aerosols. The gas absorption was calculated from the HITRAN 2004 spectroscopic data set and state-of-the-art continuum models using the ARTS radiative transfer model. Three representative wavelengths were required on average to fulfill the accuracy threshold. We implemented the parameterized spectral bands and satellite channels in the uvspec radiative transfer model which is part of the libRadtran software package. The parameterization data files, including the representative wavelengths and weights as well as lookup tables of absorption cross sections of various gases, are provided at the libRadtran webpage.In the paper we describe the parameterization approach and its application. We validate the approach by comparing modeling results of parameterized bands and channels with results from high spectral resolution calculations for atmospheric states that were not part of the training data set. Irradiances are not only compared at the top of atmosphere but also at the surface for which this parameterization approach was not optimized. It is found that the parameterized bands and channels provide a good compromise between computation time requirements and uncertainty for typical radiative transfer problems. In particular for satellite radiometer simulations the computation time requirement and the parameterization uncertainty is low. Band-integrated irradiances at any level as well as heating and cooling rates below 20km can also be modeled with low uncertainty.

Assimilation of Infrared Radiances in the Context of Observing System Simulation Experiments

AbstractThe Observing System Simulation Experiment (OSSE) capability developed at Environment Canada allows simulation of all observation types currently used operationally as well as future data types. Its infrastructure, based on the operational global data assimilation system used at the Canadian Meteorological Centre, was recently enhanced to conduct data assimilation experiments for two future satellite missions. This study presents a subcomponent of that system, focusing on the assimilation of infrared radiances from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) instruments. The goal is to realistically simulate the radiance observations and to reproduce statistical characteristics of these data seen in the real system, notably background and analysis departures. Care is taken to emulate the operational quality control procedures leading to the assimilation of clear radiances, which implies radiance simulation for all-sky conditions. It is found that the standard deviation of the Gaussian random perturbation applied to the simulated observations should be close to that of the radiometric noise level for sounding channels in the 13.0–14.5-μm region but that it should be significantly higher for water vapor channels in the 5.5–6.7-μm region. The study also allows evaluation of residual biases linked to cloud contamination. For atmospheric window channels, that bias can reach −0.4 K. It reduces rapidly with peak height of the channel response function. This suggests that improvements are needed in low-cloud detection. The realism of the OSSE is further demonstrated through the shown impact consistency of AIRS and IASI radiance assimilation in forecasts up to 5 days from the separate use of simulated and real observations.

Boundary conditions effect on linearized mud-flow shallow model

The occurrence of roll-waves in mud-flows is investigated based on the formulation of the marginal stability threshold of a linearized onedimensional viscoplastic (shear-thinning) flow model. Since for this kind of non-Newtonian rheological models this threshold may occur in a hypocritical flow, the downstream boundary condition may have a nonnegligible effect on the spatial growth/decay of the perturbation. The paper presents the solution of the 1D linearized flow of a Herschel and Bulkley fluid in a channel of finite length, in the neighbourhood of a hypocritical base uniform flow. Both linearly stable and unstable conditions are considered. The analytical solution is found applying the Laplace transform method and obtaining the first-order analytical expressions of the upstream and downstream channel response functions in the time domain. The effects of both the yield stress and the rheological law exponent are discussed, recovering as particular cases both power-law and Bingham fluids. The theoretical achievements may be used to extend semi-empirical criteria commonly employed for predicting roll waves occurrence in clear water even to mud-flows.

窄带电力线通信中对抗突发脉冲的信道估计方法研究

在窄带电力线通信系统中，时域突发脉冲是影响性能的最主要干扰之一。该系统中采用OFDM多载波方式，接收机在频域进行处理时，时域突发脉冲在FFT之后会扩展到整个频段上，进而严重影响系统的性能。因此，接收端需要采取有效的干扰消除机制。置零算法因其操作简单被广泛应用，然而，这种非线性操作会引入载波间干扰(ICI)，导致系统信道估计准确性降低和BER性能变差。本文在此种条件下提出一种新的信道估计方法，迭代消除信道估计中的ICI部分，来降低突发脉冲的影响。仿真结果表明本文提出的改进方案可以有效提高信道估计的准确性，并使系统性能相应提升。 The additive impulsive noise is one of the serious interferences in narrow band power line communication (NB-PLC). With the widely used OFDM (Orthogonal Frequency Division Multiplexing) technology, the influence of the impulsive noise can spread to every subcarrier after DFT in the receiver, which degrades the communication per- formance seriously. Therefore, a simple and effective interference cancelation scheme is required, for example, blanking nonlinearity has been widely used to suppress the impulsive noise due to its convenient operation. However, the nonli- near operation introduces inter-carrier interference (ICI), resulting in degradation in both system performance and the precision of channel estimation. In this paper, a new channel estimation method for OFDM transmission is proposed to reduce the affection of impulsive noise in power line channel, where the ICI part in the estimated channel response function can be iteratively cancelled. The simulation results show that the proposed method can improve the precision of channel estimation and reduce the bit error ratio (BER) significantly at the same time.

Recover soft x-ray spectrum using virtual flat response channels with filtered x-ray diode array

A method for the recovery of soft x-ray spectra in indirect-drive inertial confinement fusion experiments is presented. Virtual detection channels with bandpass responses are obtained using linear combinations of the channel response functions of a filtered x-ray diode array and a weighted correction is introduced to improve the recovery. These virtual channels can be used to calculate radiation fluxes in some specific photon energy bands and hence to recover the spectrum of the whole photon energy range from 80 eV to 4.5 keV. Examples are listed which demonstrate the capability of this method to unfold various spectra such as Planck spectra with different radiation temperatures and to obtain x-ray flux of certain narrow energy interval.

High Dynamic Range Imaging of Magnetized Sheet Plasma

High dynamic range (HDR) imaging was used to obtain a wide intensity map of a magnetized sheet plasma. A set of 12 low dynamic range (LDR) photographs with various shutter speeds (1/200-1/2 s) was captured with an Olympus FE-19 digital camera. The LDR images were processed to recover color channel response functions of the camera needed to produce RGB radiance maps. The HDR image was finally generated from the combined radiance maps via linear tone mapping. By comparison of histograms, the HDR image uses the whole range of intensity values compared with the underexposed and overexposed LDR images.

Improving bit-error-rate performance of the free-space optical communications system with channel estimation based on radiative transfer theory

In order to improve the performance of terrestrial free-space optical communication systems in adverse visibility conditions, we present a method for estimation of the atmospheric channel impulse response function which governs the optical intensity propagation. This method reduces run-time computational demands and system complexity in comparison to our previously proposed dual-wavelength channel estimation technique. We consider propagation of optical wavelengths in fog, where the droplet diameters are close to the wavelength and thus scattering and absorption effects are significant. A method for rapid calculation of a channel response function based on estimating the effective optical depth of the channel and curve-fitting is described. The channel response estimate can then be used to design a receiver-side equalizer (minimum mean-squared error linear equalizer) to correct the signal distortion due to propagation through the dispersive channel. The channel estimates are based on parametric curve-fitting functions which have been developed using the modified-vector radiative transfer theory to model the channel response. The optimal fit parameters are found using particle-swarm optimization to minimize the simulated bit-error rate of the received signal.

Rapid Calibration of Operational and Research Meteorological Satellite Imagers. Part II: Comparison of Infrared Channels

To establish a more reliable reference instrument for calibration normalization, this paper examines the differences between the various thermal infrared imager channels on a set of research and operational satellites. Mean brightness temperatures from the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the second Along-Track Scanning Radiometer (ATSR-2) on the second European Remote Sensing Satellite (ERS-2) are correlated with matched data from the eighth Geostationary Operational Environmental Satellite (GOES-8), the fifth Geostationary Meteorological Satellite (GMS-5), and with each other. VIRS data are also correlated with the Terra satellite’s Moderate Resolution Imaging Spectroradiometer (MODIS) provisional data as a preliminary assessment of their relative calibrations. As an additional check on their long-term stability, the VIRS data are compared to the broadband longwave radiances of the Clouds and the Earth’s Radiant Energy System (CERES) scanners on TRMM. No statistically significant trend in the calibration of any of the three (3.7, 10.8, and 12.0 mm) VIRS thermal channels could be detected from the comparisons with CERES data taken during 1998 and 2000 indicating that the VIRS channels can serve as a reliable reference for intercalibrating satellite imagers. However, a small day‐night difference in the VIRS thermal channels detected at very low temperatures should be taken into account. In general, most of the channels agreed to within less than 60.7 K over a temperature range between 200 and 300 K. Some of the smaller differences can be explained by spectral differences in the channel response functions. A few larger differences were found at 200 K for some of the channels suggesting some basic calibration differences for lower temperatures. A nearly 3-K bias in the ATSR-2 11-mm channel relative to VIRS and GOES-8 was found at the cold end of the temperature range. The intercalibrations described here are being continued on a routine basis.