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At least 55 records · Page 3

Simultaneous Retrieval of Temperature, Water Vapor and Ozone Atmospheric Profiles from IASI: Compression, De-noising, First Guess Retrieval and Inversion Algorithms

A fast temperature water vapor and ozone atmospheric profile retrieval algorithm is developed for the high spectral resolution Infrared Atmospheric Sounding Interferometer (IASI) space-borne instrument. Compression and de-noising of IASI observations are performed using Principal Component Analysis. This preprocessing methodology also allows, for a fast pattern recognition in a climatological data set to obtain a first guess. Then, a neural network using first guess information is developed to retrieve simultaneously temperature, water vapor and ozone atmospheric profiles. The performance of the resulting fast and accurate inverse model is evaluated with a large diversified data set of radiosondes atmospheres including rare events.

Aires, F.↗

Land Surface Temperature Measurements form EOS MODIS Data

We have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE(Delta)T) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 micrometer IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K. Several issues related to the day/night LST algorithm (uncertainties in the day/night registration and in surface emissivity changes caused by dew occurrence, and the cloud cover) have been investigated. The LST algorithms have been validated with MODIS Airborne Simulator (MAS) dada and ground-based measurement data in two field campaigns conducted in Railroad Valley playa, NV in 1995 and 1996. The MODIS LST version 1 software has been delivered.

Wan, Zhengming↗

Evaluation and analysis of Seasat-A scanning multichannel Microwave Radiometer (SMMR) Antenna Pattern Correction (APC) algorithm

The brightness temperature data produced by the SMMR final Antenna Pattern Correction (APC) algorithm is discussed. The algorithm consisted of: (1) a direct comparison of the outputs of the final and interim APC algorithms; and (2) an analysis of a possible relationship between observed cross track gradients in the interim brightness temperatures and the asymmetry in the antenna temperature data. Results indicate a bias between the brightness temperature produced by the final and interim APC algorithm.

Kitzis, J. L.↗

Temperature dependence of optical properties of GaAs

The effect of temperature on the optical properties of GaAs was investigated using spectroscopic ellipsometry measurements, between room temperature and about 610 C in increments of 50 C, of pseudodielectric functions and related optical constants of GaAs. A quantitative analysis of the pseudodielectric function spectrum was carried out using a harmonic-oscillator approximation (HOA) to fit the measured dielectric functions. Good fits were obtained with this model, which provides a convenient means of reproducing the GaAs dielectric function at any temperature, by using the temperature-dependent oscillator parameters. The HOA analysis also provides information about band-gap variation with temperature. Using the measured optical constants at a number of fixed temperatures, an algorithm was developed for computing the dielectric function spectrum at an arbitrary temperature in the range 22-610 C.

Yao, Huade↗

Atmospheric infrared sounder

Work continued on analysis of data from the TOGA-COARE experiment. The MIT Microwave Temperature Sounder was flown on NASA's ER-2 at Wallops Island in the CAMEX experiment during September and October. The preliminary version of the 'microwave first-guess' algorithm for temperature and moisture was delivered to JPL. In the iterative minimum-variance algorithm moisture retrievals from MHS make use of the retrieved temperature profile in calculation of weighting functions and in determining the saturation moisture capacity at each level. Simulations have been run to address the question of how important the temperature profile accuracy is to the moisture retrieval.

Rosenkranz, Philip W.↗

Determination of the horizontal and vertical distribution of clouds from infrared satellite sounding data

A numerical algorithm, based on a physical inversion of the radiative transfer equation, is developed to retrieve the global distribution of the horizontal cloud cover, the cloud-top pressure levels and their temperature. The algorithm makes use of infrared and microwave temperature sounding data to derive the clear-column vertical temperature profiles and then uses the same infrared sounding data to obtain the corresponding cloud parameters. Experimental verification of this method is carried out using data from the High resolution Infrared Sounder (HIRS) and the Microwave Sounding Unit (MSU) operating on the NOAA weather satellite system.

Chahine, M. T.↗

Modeling surface temperature distributions in forest landscapes

A model of the frequency distributions of the spatial variability in surface temperature is presented. Surface temperature data are obtained from two daytime and two nighttime flights of the Thermal IR Multispectral Scanner (TIMS) over forest land in western Oregon in August, 1985. The temperature values are corrected for atmospheric attenuation and thermal radiation emission with the LOWTRAN-6 algorithm. The temperature distributions were modeled with a two-parameter beta probability density distribution and the fit of the model was evaluated by comparison with the TIMS data set. Use of the model's parameters to identify and classify surface types shows good discrimination among various surfaces for the daytime images, with less distinct discrimination for the nighttime images.

Holbo, H. R.↗

Experimental Control of Thermocapillary Convection in a Liquid Bridge

We demonstrate the stabilization of an isolated unstable periodic orbit in a liquid bridge convection experiment. A model independent, nonlinear control algorithm uses temperature measurements near the liquid interface to compute control perturbations which are applied by a thermoelectric element. The algorithm employs a time series reconstruction of a nonlinear control surface in a high dimensional phase space to alter the system dynamics.

Petrov, Valery↗

AVHRR Surface Temperature and Narrow-Band Albedo Comparison with Ground Measurements for the Greenland Ice Sheet

An ice-surface temperature retrieval algorithm for the Greenland ice sheet was developed using NOAA 11 thermal radiances from channels 4 and 5. Temperature, pressure and humidity profiles, cloud observations and skin temperatures from the Swiss Federal Institute of Technology (ETH) camp, located at the equilibrium line altitude at 49 deg17 min W, 69 deg 34 min N, were used in the LOWTRAN 7 model. Through a statistical analysis of daily clear sky profiles, the coefficients that correct for the atmospheric effects were determined for the ETH-Camp field season (May to August). Surface temperatures retrieved by this method were then compared against the in situ observations with a maximum difference of 0.6 K. The NOAA 11 narrow-band planetary albedo values for channels 1 and 2 were calculated using pre-launch calibration coefficients. Scattering and absorption by the atmosphere were modelled with LOWTRAN 7. Then, narrow-band albedo values for the AVHRR visible and near infrared channels were compared with in situ high resolution spectral reflectance measurements. In the visible band (580-680 nm), AVHRR-derived narrow-band albedo and the in situ measurements corrected with radiative transfer model LOWTRAN 7 showed a difference of less than 2%. For the near infrared channel (725-1100 nm) the difference between the measured and modelled narrow-band albedo was 14%. These discrepancies could be either the result of inaccurate aerosol scattering modelling (lack of the in situ observation), or the result of sensor drift due to degradation.

Haefliger, M.↗

A direct algorithm for convective adjustment of the vertical temperature profile for an arbitrary critical lapse rate

An efficient direct algorithm of convective adjustment for an arbitrary critical value of the vertical temperature lapse rate gamma is proposed. The algorithm provides an exact and unique solution of a standard convective adjustment problem for models with temperature specified either on nonuniformly spaced levels or for layers of different thicknesses in pressure, sigma, or other vertical coordinate related to pressure. The algorithm may be recommended for use either directly in atmospheric models not explicitly including a hydrologic cycle with prescribed gamma, or as a part of more complicated parameterizations of moist convection, where gamma may be calculated depending on relative humidity.

Akmaev, Rashid A.↗

A Quantum-Assisted Algorithm for Sampling Applications in Machine Learning

An increase in the efficiency of sampling from Boltzmann distributions would have a significant impact in deep learning and other machine learning applications. Recently, quantum annealers have been proposed as a potential candidate to speed up this task, but several limitations still bar these state-of-the-art technologies from being used effectively. One of the main limitations is that, while the device may indeed sample from a Boltzmann-like distribution, quantum dynamical arguments suggests it will do so with an instance-dependent effective temperature, different from the physical temperature of the device. Unless this unknown temperature can be unveiled, it might not be possible to effectively use a quantum annealer for Boltzmann sampling. In this talk, we present a strategy to overcome this challenge with a simple effective-temperature estimation algorithm. We provide a systematic study assessing the impact of the effective temperatures in the learning of a kind of restricted Boltzmann machine embedded on quantum hardware, which can serve as a building block for deep learning architectures. We also provide a comparison to k-step contrastive divergence (CD-k) with k up to 100. Although assuming a suitable fixed effective temperature also allows to outperform one step contrastive divergence (CD-1), only when using an instance-dependent effective temperature we find a performance close to that of CD-100 for the case studied here. We discuss generalizations of the algorithm to other more expressive generative models, beyond restricted Boltzmann machines.

Perdomo-Ortiz, Alejandro↗

Remote Sensing of In-Flight Icing Conditions: Operational, Meteorological, and Technological Considerations

Remote-sensing systems that map aircraft icing conditions in the flight path from airports or aircraft would allow icing to be avoided and exited. Icing remote-sensing system development requires consideration of the operational environment, the meteorological environment, and the technology available. Operationally, pilots need unambiguous cockpit icing displays for risk management decision-making. Human factors, aircraft integration, integration of remotely sensed icing information into the weather system infrastructures, and avoid-and-exit issues need resolution. Cost, maintenance, power, weight, and space concern manufacturers, operators, and regulators. An icing remote-sensing system detects cloud and precipitation liquid water, drop size, and temperature. An algorithm is needed to convert these conditions into icing potential estimates for cockpit display. Specification development requires that magnitudes of cloud microphysical conditions and their spatial and temporal variability be understood at multiple scales. The core of an icing remote-sensing system is the technology that senses icing microphysical conditions. Radar and microwave radiometers penetrate clouds and can estimate liquid water and drop size. Retrieval development is needed; differential attenuation and neural network assessment of multiple-band radar returns are most promising to date. Airport-based radar or radiometers are the most viable near-term technologies. A radiometer that profiles cloud liquid water, and experimental techniques to use radiometers horizontally, are promising. The most critical operational research needs are to assess cockpit and aircraft system integration, develop avoid-and-exit protocols, assess human factors, and integrate remote-sensing information into weather and air traffic control infrastructures. Improved spatial characterization of cloud and precipitation liquid-water content, drop-size spectra, and temperature are needed, as well as an algorithm to convert sensed conditions into a measure of icing potential. Technology development also requires refinement of inversion techniques. These goals can be accomplished with collaboration among federal agencies including NASA, the FAA, the National Center for Atmospheric Research, NOAA, and the Department of Defense. This report reviews operational, meteorological, and technological considerations in developing the capability to remotely map in-flight icing conditions from the ground and from the air.

Ryerson, Charles C.↗

Advanced methods for preparation and characterization of infrared detector materials

Mercury cadmium telluride crystals were prepared by the Bridgman method with a wide range of crystal growth rates and temperature gradients adequate to prevent constitutional supercooling under diffusion-limited, steady state, growth conditions. The longitudinal compositional gradients for different growth conditions and alloy compositions were calculated and compared with experimental data to develop a quantitative model of the crystal growth kinetics for the Hg(i-x)CdxTe alloys, and measurements were performed to ascertain the effect of growth conditions on radial compositional gradients. The pseudobinary HgTe-CdTe constitutional phase diagram was determined by precision differential thermal analysis measurements and used to calculate the segregation coefficient of Cd as a function of x and interface temperature. Computer algorithms specific to Hg(1-x)CdxTe were developed for calculations of the charge carrier concentrations, charge carrier mobilities, Hall coefficient, optical absorptance, and Fermi energy as functions of x, temperature, ionized donor and acceptor concentrations, and neutral defect concentrations.

Lehoczky, S. L.↗

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

Key, Jeff↗

Device Would Monitor Body Parameters Continuously

Proposed miniature electronic circuit continuously measures temperature of human subject. Once mounted on subject's skin with medical adhesive tape, electronic thermometer remains in thermal equilibrium with subject's body; thereafter, no need to wait until thermometer reaches body temperature before taking reading. Design provides for switches used to set alarm alerting medical attendants if subject's temperature exceeds critical level. For use on very young child, electronic thermometer sewed into shirt or other suitable garment; device held in contact with skin, and child could not swallow it. Replacement of sensor and computing algorithm changes temperature monitor to cardiorespiratory monitor.

Cook, Joseph S., Jr.↗

Overcoming time-integration errors in SINDA's FWDBCK solution routine

The FWDBCK time step, which is usually chosen intuitively to achieve adequate accuracy at reasonable computational costs, can in fact lead to large errors. NASA observed such errors in solving cryogenic problems on the COBE spacecraft, but a similar error is also demonstrated for a single node radiating to space. An algorithm has been developed for selecting the time step during the course of the simulation. The error incurred when the time derivative is replaced by the FWDBCK time difference can be estimated from the Taylor-Series expression for the temperature. The algorithm selects the time step to keep this error small. The efficacy of the method is demonstrated on the COBE and single-node problems.

Skladany, J. T.↗

Thermal Behaviour of Unusual Local-Scale Surface Features on Vesta

On Vesta, the region of the infrared spectrum beyond approximately 3.5 micrometers is dominated by the thermal emission of the asteroid's surface, which can be used to determine surface temperature by means of temperature-retrieval algorithms. The thermal behavior of areas of unusual albedo seen at the local scale can be related to physical properties that can provide information about the origin of those materials. Dawn's Visible and Infrared Mapping Spectrometer (VIR) hyperspectral cubes are used to retrieve surface temperatures, with high accuracy as long as temperatures are greater than 180 K. Data acquired in the Survey phase (23 July through 29 August 2011) show several unusual surface features: 1) high-albedo (bright) and low-albedo (dark) material deposits, 2) spectrally distinct ejecta, 3) regions suggesting finer-grained materials. Some of the unusual dark and bright features were re-observed by VIR in the subsequent High-Altitude Mapping Orbit (HAMO) and Low-Altitude Mapping Orbit (LAMO) phases at increased pixel resolution. To calculate surface temperatures, we applied a Bayesian approach to nonlinear inversion based on the Kirchhoff law and the Planck function. These results were cross-checked through application of alternative methods. Here we present temperature maps of several local-scale features that were observed by Dawn under different illumination conditions and different local solar times. Some bright terrains have an overall albedo in the visible as much as 40% brighter than surrounding areas. Data from the IR channel of VIR show that bright regions generally correspond to regions with lower thermal emission, i.e. lower temperature, while dark regions correspond to areas with higher thermal emission, i.e. higher temperature. This behavior confirms that many of the dark appearances in the VIS mainly reflect albedo variations. In particular, it is shown that during maximum daily insolation, dark features in the equatorial region may rise to temperatures greater than 270 K. However, individual features may show different thermal behaviours, as a result of differences in composition and/or structure (e.g, average grain size of the surface regolith, porosity, etc.). To complement the temperature and near-infrared emissivity derived from the infrared spectra, a separate work is devoted to calculate thermal inertia and other thermal properties using theoretical models which solve the heat equation for airless bodies, and model the distribution of temperatures due to surface roughness variations.

Tosi, F.↗