Estimation of Thermal Sensation Based on Wrist Skin Temperatures.

PubMed

Sim, Soo Young; Koh, Myung Jun; Joo, Kwang Min; Noh, Seungwoo; Park, Sangyun; Kim, Youn Ho; Park, Kwang Suk

2016-03-23

Thermal comfort is an essential environmental factor related to quality of life and work effectiveness. We assessed the feasibility of wrist skin temperature monitoring for estimating subjective thermal sensation. We invented a wrist band that simultaneously monitors skin temperatures from the wrist (i.e., the radial artery and ulnar artery regions, and upper wrist) and the fingertip. Skin temperatures from eight healthy subjects were acquired while thermal sensation varied. To develop a thermal sensation estimation model, the mean skin temperature, temperature gradient, time differential of the temperatures, and average power of frequency band were calculated. A thermal sensation estimation model using temperatures of the fingertip and wrist showed the highest accuracy (mean root mean square error [RMSE]: 1.26 ± 0.31). An estimation model based on the three wrist skin temperatures showed a slightly better result to the model that used a single fingertip skin temperature (mean RMSE: 1.39 ± 0.18). When a personalized thermal sensation estimation model based on three wrist skin temperatures was used, the mean RMSE was 1.06 ± 0.29, and the correlation coefficient was 0.89. Thermal sensation estimation technology based on wrist skin temperatures, and combined with wearable devices may facilitate intelligent control of one's thermal environment.

Estimation of Thermal Sensation Based on Wrist Skin Temperatures

PubMed Central

Sim, Soo Young; Koh, Myung Jun; Joo, Kwang Min; Noh, Seungwoo; Park, Sangyun; Kim, Youn Ho; Park, Kwang Suk

2016-01-01

Thermal comfort is an essential environmental factor related to quality of life and work effectiveness. We assessed the feasibility of wrist skin temperature monitoring for estimating subjective thermal sensation. We invented a wrist band that simultaneously monitors skin temperatures from the wrist (i.e., the radial artery and ulnar artery regions, and upper wrist) and the fingertip. Skin temperatures from eight healthy subjects were acquired while thermal sensation varied. To develop a thermal sensation estimation model, the mean skin temperature, temperature gradient, time differential of the temperatures, and average power of frequency band were calculated. A thermal sensation estimation model using temperatures of the fingertip and wrist showed the highest accuracy (mean root mean square error [RMSE]: 1.26 ± 0.31). An estimation model based on the three wrist skin temperatures showed a slightly better result to the model that used a single fingertip skin temperature (mean RMSE: 1.39 ± 0.18). When a personalized thermal sensation estimation model based on three wrist skin temperatures was used, the mean RMSE was 1.06 ± 0.29, and the correlation coefficient was 0.89. Thermal sensation estimation technology based on wrist skin temperatures, and combined with wearable devices may facilitate intelligent control of one’s thermal environment. PMID:27023538

On the possibility of non-invasive multilayer temperature estimation using soft-computing methods.

PubMed

Teixeira, C A; Pereira, W C A; Ruano, A E; Ruano, M Graça

2010-01-01

This work reports original results on the possibility of non-invasive temperature estimation (NITE) in a multilayered phantom by applying soft-computing methods. The existence of reliable non-invasive temperature estimator models would improve the security and efficacy of thermal therapies. These points would lead to a broader acceptance of this kind of therapies. Several approaches based on medical imaging technologies were proposed, magnetic resonance imaging (MRI) being appointed as the only one to achieve the acceptable temperature resolutions for hyperthermia purposes. However, MRI intrinsic characteristics (e.g., high instrumentation cost) lead us to use backscattered ultrasound (BSU). Among the different BSU features, temporal echo-shifts have received a major attention. These shifts are due to changes of speed-of-sound and expansion of the medium. The originality of this work involves two aspects: the estimator model itself is original (based on soft-computing methods) and the application to temperature estimation in a three-layer phantom is also not reported in literature. In this work a three-layer (non-homogeneous) phantom was developed. The two external layers were composed of (in % of weight): 86.5% degassed water, 11% glycerin and 2.5% agar-agar. The intermediate layer was obtained by adding graphite powder in the amount of 2% of the water weight to the above composition. The phantom was developed to have attenuation and speed-of-sound similar to in vivo muscle, according to the literature. BSU signals were collected and cumulative temporal echo-shifts computed. These shifts and the past temperature values were then considered as possible estimators inputs. A soft-computing methodology was applied to look for appropriate multilayered temperature estimators. The methodology involves radial-basis functions neural networks (RBFNN) with structure optimized by the multi-objective genetic algorithm (MOGA). In this work 40 operating conditions were

Predicting critical temperatures of ionic and non-ionic fluids from thermophysical data obtained near the melting point.

PubMed

Weiss, Volker C

2015-10-14

In the correlation and prediction of thermophysical data of fluids based on a corresponding-states approach, the critical temperature Tc plays a central role. For some fluids, in particular ionic ones, however, the critical region is difficult or even impossible to access experimentally. For molten salts, Tc is on the order of 3000 K, which makes accurate measurements a challenging task. Room temperature ionic liquids (RTILs) decompose thermally between 400 K and 600 K due to their organic constituents; this range of temperatures is hundreds of degrees below recent estimates of their Tc. In both cases, reliable methods to deduce Tc based on extrapolations of experimental data recorded at much lower temperatures near the triple or melting points are needed and useful because the critical point influences the fluid's behavior in the entire liquid region. Here, we propose to employ the scaling approach leading to universal fluid behavior [Román et al., J. Chem. Phys. 123, 124512 (2005)] to derive a very simple expression that allows one to estimate Tc from the density of the liquid, the surface tension, or the enthalpy of vaporization measured in a very narrow range of low temperatures. We demonstrate the validity of the approach for simple and polar neutral fluids, for which Tc is known, and then use the methodology to obtain estimates of Tc for ionic fluids. When comparing these estimates to those reported in the literature, good agreement is found for RTILs, whereas the ones for the molten salts NaCl and KCl are lower than previous estimates by 10%. The coexistence curve for ionic fluids is found to be more adequately described by an effective exponent of βeff = 0.5 than by βeff = 0.33.

Non-Invasive In Vivo Ultrasound Temperature Estimation

NASA Astrophysics Data System (ADS)

Bayat, Mahdi

New emerging technologies in thermal therapy require precise monitoring and control of the delivered thermal dose in a variety of situations. The therapeutic temperature changes in target tissues range from few degrees for releasing chemotherapy drugs encapsulated in the thermosensitive liposomes to boiling temperatures in complete ablation of tumors via cell necrosis. High intensity focused ultrasound (HIFU) has emerged as a promising modality for noninvasive surgery due to its ability to create precise mechanical and thermal effects at the target without affecting surrounding tissues. An essential element in all these procedures, however, is accurate estimation of the target tissue temperature during the procedure to ensure its safety and efficacy. The advent of diagnostic imaging tools for guidance of thermal therapy was a key factor in the clinical acceptance of these minimally invasive or noninvasive methods. More recently, ultrasound and magnetic resonance (MR) thermography techniques have been proposed for guidance, monitoring, and control of noninvasive thermal therapies. MR thermography has shown acceptable sensitivity and accuracy in imaging temperature change and it is currently FDA-approved on clinical HIFU units. However, it suffers from limitations like cost of integration with ultrasound therapy system and slow rate of imaging for real time guidance. Ultrasound, on the other hand, has the advantage of real time imaging and ease of integration with the therapy system. An infinitesimal model for imaging temperature change using pulse-echo ultrasound has been demonstrated, including in vivo small-animal imaging. However, this model suffers from limitations that prevent demonstration in more clinically-relevant settings. One limitation stems from the infinitesimal nature of the model, which results in spatial inconsistencies of the estimated temperature field. Another limitation is the sensitivity to tissue motion and deformation during in vivo, which

US Low-Temperature EGS Resource Potential Estimate

DOE Data Explorer

Katherine Young

2016-06-30

Shapefile of shallow, low-temperature EGS resources for the United States, and accompanying paper (submitted to GRC 2016) describing the methodology and analysis. These data are part of a very rough estimate created for use in the U.S. Department of Energy Geothermal Technology Office's Vision Study. They are not a robust estimate of low-temperature EGS resources in the U.S, and should be used accordingly.

Knock probability estimation through an in-cylinder temperature model with exogenous noise

NASA Astrophysics Data System (ADS)

Bares, P.; Selmanaj, D.; Guardiola, C.; Onder, C.

2018-01-01

This paper presents a new knock model which combines a deterministic knock model based on the in-cylinder temperature and an exogenous noise disturbing this temperature. The autoignition of the end-gas is modelled by an Arrhenius-like function and the knock probability is estimated by propagating a virtual error probability distribution. Results show that the random nature of knock can be explained by uncertainties at the in-cylinder temperature estimation. The model only has one parameter for calibration and thus can be easily adapted online. In order to reduce the measurement uncertainties associated with the air mass flow sensor, the trapped mass is derived from the in-cylinder pressure resonance, which improves the knock probability estimation and reduces the number of sensors needed for the model. A four stroke SI engine was used for model validation. By varying the intake temperature, the engine speed, the injected fuel mass, and the spark advance, specific tests were conducted, which furnished data with various knock intensities and probabilities. The new model is able to predict the knock probability within a sufficient range at various operating conditions. The trapped mass obtained by the acoustical model was compared in steady conditions by using a fuel balance and a lambda sensor and differences below 1 % were found.

Estimation of Regional Evapotranspiration Using Remotely Sensed Land Surface Temperature. Part 2: Application of Equilibrium Evaporation Model to Estimate Evapotranspiration by Remote Sensing Technique. [Japan

NASA Technical Reports Server (NTRS)

Kotoda, K.; Nakagawa, S.; Kai, K.; Yoshino, M. M.; Takeda, K.; Seki, K.

1985-01-01

In a humid region like Japan, it seems that the radiation term in the energy balance equation plays a more important role for evapotranspiration then does the vapor pressure difference between the surface and lower atmospheric boundary layer. A Priestley-Taylor type equation (equilibrium evaporation model) is used to estimate evapotranspiration. Net radiation, soil heat flux, and surface temperature data are obtained. Only temperature data obtained by remotely sensed techniques are used.

An Optimal Estimation Method to Obtain Surface Layer Turbulent Fluxes from Profile Measurements

NASA Astrophysics Data System (ADS)

Kang, D.

2015-12-01

In the absence of direct turbulence measurements, the turbulence characteristics of the atmospheric surface layer are often derived from measurements of the surface layer mean properties based on Monin-Obukhov Similarity Theory (MOST). This approach requires two levels of the ensemble mean wind, temperature, and water vapor, from which the fluxes of momentum, sensible heat, and water vapor can be obtained. When only one measurement level is available, the roughness heights and the assumed properties of the corresponding variables at the respective roughness heights are used. In practice, the temporal mean with large number of samples are used in place of the ensemble mean. However, in many situations the samples of data are taken from multiple levels. It is thus desirable to derive the boundary layer flux properties using all measurements. In this study, we used an optimal estimation approach to derive surface layer properties based on all available measurements. This approach assumes that the samples are taken from a population whose ensemble mean profile follows the MOST. An optimized estimate is obtained when the results yield a minimum cost function defined as a weighted summation of all error variance at each sample altitude. The weights are based one sample data variance and the altitude of the measurements. This method was applied to measurements in the marine atmospheric surface layer from a small boat using radiosonde on a tethered balloon where temperature and relative humidity profiles in the lowest 50 m were made repeatedly in about 30 minutes. We will present the resultant fluxes and the derived MOST mean profiles using different sets of measurements. The advantage of this method over the 'traditional' methods will be illustrated. Some limitations of this optimization method will also be discussed. Its application to quantify the effects of marine surface layer environment on radar and communication signal propagation will be shown as well.

Estimating monthly temperature using point based interpolation techniques

NASA Astrophysics Data System (ADS)

Saaban, Azizan; Mah Hashim, Noridayu; Murat, Rusdi Indra Zuhdi

2013-04-01

This paper discusses the use of point based interpolation to estimate the value of temperature at an unallocated meteorology stations in Peninsular Malaysia using data of year 2010 collected from the Malaysian Meteorology Department. Two point based interpolation methods which are Inverse Distance Weighted (IDW) and Radial Basis Function (RBF) are considered. The accuracy of the methods is evaluated using Root Mean Square Error (RMSE). The results show that RBF with thin plate spline model is suitable to be used as temperature estimator for the months of January and December, while RBF with multiquadric model is suitable to estimate the temperature for the rest of the months.

Estimation of thermal transmittance based on temperature measurements with the application of perturbation numbers

NASA Astrophysics Data System (ADS)

Nowoświat, Artur; Skrzypczyk, Jerzy; Krause, Paweł; Steidl, Tomasz; Winkler-Skalna, Agnieszka

2018-05-01

Fast estimation of thermal transmittance based on temperature measurements is uncertain, and the obtained results can be burdened with a large error. Nevertheless, such attempts should be undertaken merely due to the fact that a precise measurement by means of heat flux measurements is not always possible in field conditions (resentment of the residents during the measurements carried out inside their living quarters), and the calculation methods do not allow for the nonlinearity of thermal insulation, heat bridges or other fragments of building envelope of diversified thermal conductivity. The present paper offers the estimation of thermal transmittance and internal surface resistance with the use of temperature measurements (in particular with the use of thermovision). The proposed method has been verified through tests carried out on a laboratory test stand built in the open space, subjected to the influence of real meteorological conditions. The present elaboration involves the estimation of thermal transmittance by means of temperature measurements. Basing on the mentioned estimation, the authors present correction coefficients which have impact on the estimation accuracy. Furthermore, in the final part of the paper, various types of disturbance were allowed for using perturbation numbers, and the introduced by the authors "credibility area of thermal transmittance estimation" was determined.

Estimation of body temperature rhythm based on heart activity parameters in daily life.

PubMed

Sooyoung Sim; Heenam Yoon; Hosuk Ryou; Kwangsuk Park

2014-01-01

Body temperature contains valuable health related information such as circadian rhythm and menstruation cycle. Also, it was discovered from previous studies that body temperature rhythm in daily life is related with sleep disorders and cognitive performances. However, monitoring body temperature with existing devices during daily life is not easy because they are invasive, intrusive, or expensive. Therefore, the technology which can accurately and nonintrusively monitor body temperature is required. In this study, we developed body temperature estimation model based on heart rate and heart rate variability parameters. Although this work was inspired by previous research, we originally identified that the model can be applied to body temperature monitoring in daily life. Also, we could find out that normalized Mean heart rate (nMHR) and frequency domain parameters of heart rate variability showed better performance than other parameters. Although we should validate the model with more number of subjects and consider additional algorithms to decrease the accumulated estimation error, we could verify the usefulness of this approach. Through this study, we expect that we would be able to monitor core body temperature and circadian rhythm from simple heart rate monitor. Then, we can obtain various health related information derived from daily body temperature rhythm.

Individualized estimation of human core body temperature using noninvasive measurements.

PubMed

Laxminarayan, Srinivas; Rakesh, Vineet; Oyama, Tatsuya; Kazman, Josh B; Yanovich, Ran; Ketko, Itay; Epstein, Yoram; Morrison, Shawnda; Reifman, Jaques

2018-06-01

A rising core body temperature (T c ) during strenuous physical activity is a leading indicator of heat-injury risk. Hence, a system that can estimate T c in real time and provide early warning of an impending temperature rise may enable proactive interventions to reduce the risk of heat injuries. However, real-time field assessment of T c requires impractical invasive technologies. To address this problem, we developed a mathematical model that describes the relationships between T c and noninvasive measurements of an individual's physical activity, heart rate, and skin temperature, and two environmental variables (ambient temperature and relative humidity). A Kalman filter adapts the model parameters to each individual and provides real-time personalized T c estimates. Using data from three distinct studies, comprising 166 subjects who performed treadmill and cycle ergometer tasks under different experimental conditions, we assessed model performance via the root mean squared error (RMSE). The individualized model yielded an overall average RMSE of 0.33 (SD = 0.18)°C, allowing us to reach the same conclusions in each study as those obtained using the T c measurements. Furthermore, for 22 unique subjects whose T c exceeded 38.5°C, a potential lower T c limit of clinical relevance, the average RMSE decreased to 0.25 (SD = 0.20)°C. Importantly, these results remained robust in the presence of simulated real-world operational conditions, yielding no more than 16% worse RMSEs when measurements were missing (40%) or laden with added noise. Hence, the individualized model provides a practical means to develop an early warning system for reducing heat-injury risk. NEW & NOTEWORTHY A model that uses an individual's noninvasive measurements and environmental variables can continually "learn" the individual's heat-stress response by automatically adapting the model parameters on the fly to provide real-time individualized core body temperature estimates. This

Shutterless solution for simultaneous focal plane array temperature estimation and nonuniformity correction in uncooled long-wave infrared camera.

PubMed

Cao, Yanpeng; Tisse, Christel-Loic

2013-09-01

In uncooled long-wave infrared (LWIR) microbolometer imaging systems, temperature fluctuations of the focal plane array (FPA) result in thermal drift and spatial nonuniformity. In this paper, we present a novel approach based on single-image processing to simultaneously estimate temperature variances of FPAs and compensate the resulting temperature-dependent nonuniformity. Through well-controlled thermal calibrations, empirical behavioral models are derived to characterize the relationship between the responses of microbolometer and FPA temperature variations. Then, under the assumption that strong dependency exists between spatially adjacent pixels, we estimate the optimal FPA temperature so as to minimize the global intensity variance across the entire thermal infrared image. We make use of the estimated FPA temperature to infer an appropriate nonuniformity correction (NUC) profile. The performance and robustness of the proposed temperature-adaptive NUC method are evaluated on realistic IR images obtained by a 640 × 512 pixels uncooled LWIR microbolometer imaging system operating in a significantly changed temperature environment.

Estimating past precipitation and temperature from fossil ostracodes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, A.J.; Forester, R.M.

1994-12-31

The fossil records of certain aquatic organisms provide a way of obtaining meaningful estimates of past temperature and precipitation. These estimates of past environmental conditions are derived from multivariate statistical methods that are in turn based on the modern biogeographic distributions and environmental tolerances of the biota of interest. These estimates are helpful in conducting slimate studies as part of the Yucca Mountain site characterization. Ostracodes are microscopic crustaceans that produce bivalved calcite shells which are easily fossilized in the sediments of the lakes and wetlands in which the animals lived. The modern biogeographic distribution and environmental conditions of livingmore » ostracodes are the basis for the interpretation of the past environmental conditions of the fossil ostracodes. The major assumption in this method of interpretation is that the environmental tolerances of ostracodes have not changed substantially over thousands of years. Two methods using these modern analogs to determine past environmental conditions are the modern analog method and the range method. The range method also considers the information provided by fossil ostracode assemblages that have no modern analog in today`s world.« less

Estimating Mixing Heights Using Microwave Temperature Profiler

NASA Technical Reports Server (NTRS)

Nielson-Gammon, John; Powell, Christina; Mahoney, Michael; Angevine, Wayne

2008-01-01

A paper describes the Microwave Temperature Profiler (MTP) for making measurements of the planetary boundary layer thermal structure data necessary for air quality forecasting as the Mixing Layer (ML) height determines the volume in which daytime pollution is primarily concentrated. This is the first time that an airborne temperature profiler has been used to measure the mixing layer height. Normally, this is done using a radar wind profiler, which is both noisy and large. The MTP was deployed during the Texas 2000 Air Quality Study (TexAQS-2000). An objective technique was developed and tested for estimating the ML height from the MTP vertical temperature profiles. In order to calibrate the technique and evaluate the usefulness of this approach, estimates from a variety of measurements during the TexAQS-2000 were compared. Estimates of ML height were used from radiosondes, radar wind profilers, an aerosol backscatter lidar, and in-situ aircraft measurements in addition to those from the MTP.

A new lithium-ion battery internal temperature on-line estimate method based on electrochemical impedance spectroscopy measurement

NASA Astrophysics Data System (ADS)

Zhu, J. G.; Sun, Z. C.; Wei, X. Z.; Dai, H. F.

2015-01-01

The power battery thermal management problem in EV (electric vehicle) and HEV (hybrid electric vehicle) has been widely discussed, and EIS (electrochemical impedance spectroscopy) is an effective experimental method to test and estimate the status of the battery. Firstly, an electrochemical-based impedance matrix analysis for lithium-ion battery is developed to describe the impedance response of electrochemical impedance spectroscopy. Then a method, based on electrochemical impedance spectroscopy measurement, has been proposed to estimate the internal temperature of power lithium-ion battery by analyzing the phase shift and magnitude of impedance at different ambient temperatures. Respectively, the SoC (state of charge) and temperature have different effects on the impedance characteristics of battery at various frequency ranges in the electrochemical impedance spectroscopy experimental study. Also the impedance spectrum affected by SoH (state of health) is discussed in the paper preliminary. Therefore, the excitation frequency selected to estimate the inner temperature is in the frequency range which is significantly influenced by temperature without the SoC and SoH. The intrinsic relationship between the phase shift and temperature is established under the chosen excitation frequency. And the magnitude of impedance related to temperature is studied in the paper. In practical applications, through obtaining the phase shift and magnitude of impedance, the inner temperature estimation could be achieved. Then the verification experiments are conduced to validate the estimate method. Finally, an estimate strategy and an on-line estimation system implementation scheme utilizing battery management system are presented to describe the engineering value.

Estimation of Axial Fretting Fatigue Life at Elevated Temperatures Using Critical Distance Theory

NASA Astrophysics Data System (ADS)

Majzoobi, G. H.; Azhdarzadeh, P.

Fretting fatigue life is traditionally estimated by experiment. The objective of this work is to introduce a special approach for estimation of axial fretting fatigue life at elevated temperatures from plain fatigue test based on the critical distance theory. The method uses Fatemi-Socie parameter as a multiaxial criterion to compute the stress multiaxiality on focus path. This method considers only elastic behavior for materials, and two characteristic diagrams are obtained from plain fatigue tests on two U-shaped and V-shaped notched specimens. The results showed reasonable agreement between the predictions by the proposed method and the experiments for ambient temperature. For elevated temperatures, the results indicated that the predicted fretting fatigue life was considerably overestimated in the low cycle fatigue (LCF) regime and underestimated in the high cycle fatigue (HCF) region with respect to experimental measurements. The reason for such discrepancy is believed to be due to the complex behavior of AL 7075-T6, which exhibits at elevated temperatures because of the problems such as aging, oxidation and reduction of strength.

Validation of Core Temperature Estimation Algorithm

DTIC Science & Technology

2016-01-29

plot of observed versus estimated core temperature with the line of identity (dashed) and the least squares regression line (solid) and line equation...estimated PSI with the line of identity (dashed) and the least squares regression line (solid) and line equation in the top left corner. (b) Bland...for comparison. The root mean squared error (RMSE) was also computed, as given by Equation 2.

Estimating radiative feedbacks from stochastic fluctuations in surface temperature and energy imbalance

NASA Astrophysics Data System (ADS)

Proistosescu, C.; Donohoe, A.; Armour, K.; Roe, G.; Stuecker, M. F.; Bitz, C. M.

2017-12-01

Joint observations of global surface temperature and energy imbalance provide for a unique opportunity to empirically constrain radiative feedbacks. However, the satellite record of Earth's radiative imbalance is relatively short and dominated by stochastic fluctuations. Estimates of radiative feedbacks obtained by regressing energy imbalance against surface temperature depend strongly on sampling choices and on assumptions about whether the stochastic fluctuations are primarily forced by atmospheric or oceanic variability (e.g. Murphy and Forster 2010, Dessler 2011, Spencer and Braswell 2011, Forster 2016). We develop a framework around a stochastic energy balance model that allows us to parse the different contributions of atmospheric and oceanic forcing based on their differing impacts on the covariance structure - or lagged regression - of temperature and radiative imbalance. We validate the framework in a hierarchy of general circulation models: the impact of atmospheric forcing is examined in unforced control simulations of fixed sea-surface temperature and slab ocean model versions; the impact of oceanic forcing is examined in coupled simulations with prescribed ENSO variability. With the impact of atmospheric and oceanic forcing constrained, we are able to predict the relationship between temperature and radiative imbalance in a fully coupled control simulation, finding that both forcing sources are needed to explain the structure of the lagged-regression. We further model the dependence of feedback estimates on sampling interval by considering the effects of a finite equilibration time for the atmosphere, and issues of smoothing and aliasing. Finally, we develop a method to fit the stochastic model to the short timeseries of temperature and radiative imbalance by performing a Bayesian inference based on a modified version of the spectral Whittle likelihood. We are thus able to place realistic joint uncertainty estimates on both stochastic forcing and

Temperature and redox path of biotite-bearing intrusives: A method of estimation applied to S- and I-type granites from Australia

NASA Astrophysics Data System (ADS)

Burkhard, Dorothee J. M.

1991-05-01

Estimations of the oxidation state and development of ƒO 2 during magmatic evolution are usually not possible because ƒO 2 is a function of temperature (and pressure). If two independent equations for ƒO 2 = ƒO 2(T) can be obtained, ƒO 2 and the corresponding temperature can be estimated. For biotite-bearing rocks an estimation of ƒO 2 (bio) can be combined with an estimation of ƒO 2 (rock). This latter estimation requires an extrapolation of high-temperature data because low-temperature data are not available. The combination of the two equations provides a quadratic equation in T with the common (negative) solution: Tint= 1/4 c 2{- k1-2 c 1-√(k 1+2 c 1) 2+8 c 2k 2} which permits back calculation of ƒO 2. The usefulness of the method is demonstrated for typical S-type, ilmenite, and I-type, magnetite granites from Australia. Two distinct oxidation states are obtained. It is suggested that the availability of H 2O during granite emplacement largely determines ƒO 2 conditions.

[IR spectral-analysis-based range estimation for an object with small temperature difference from background].

PubMed

Fu, Xiao-Ning; Wang, Jie; Yang, Lin

2013-01-01

It is a typical passive ranging technology that estimation of distance of an object is based on transmission characteristic of infrared radiation, it is also a hotspot in electro-optic countermeasures. Because of avoiding transmitting energy in the detection, this ranging technology will significantly enhance the penetration capability and infrared conceal capability of the missiles or unmanned aerial vehicles. With the current situation in existing passive ranging system, for overcoming the shortage in ranging an oncoming target object with small temperature difference from background, an improved distance estimation scheme was proposed. This article begins with introducing the concept of signal transfer function, makes clear the working curve of current algorithm, and points out that the estimated distance is not unique due to inherent nonlinearity of the working curve. A new distance calculation algorithm was obtained through nonlinear correction technique. It is a ranging formula by using sensing information at 3-5 and 8-12 microm combined with background temperature and field meteorological conditions. The authors' study has shown that the ranging error could be mainly kept around the level of 10% under the condition of the target and background apparent temperature difference equal to +/- 5 K, and the error in estimating background temperature is no more than +/- 15 K.

Estimating soil temperature using neighboring station data via multi-nonlinear regression and artificial neural network models.

PubMed

Bilgili, Mehmet; Sahin, Besir; Sangun, Levent

2013-01-01

The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the "Enter" method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685-3.65% and 0.9988-0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy.

Correlation Dimension Estimates of Global and Local Temperature Data.

NASA Astrophysics Data System (ADS)

Wang, Qiang

1995-11-01

The author has attempted to detect the presence of low-dimensional deterministic chaos in temperature data by estimating the correlation dimension with the Hill estimate that has been recently developed by Mikosch and Wang. There is no convincing evidence of low dimensionality with either global dataset (Southern Hemisphere monthly average temperatures from 1858 to 1984) or local temperature dataset (daily minimums at Auckland, New Zealand). Any apparent reduction in the dimension estimates appears to be due large1y, if not entirely, to effects of statistical bias, but neither is it a purely random stochastic process. The dimension of the climatic attractor may be significantly larger than 10.

Preliminary estimation of the realistic optimum temperature for vegetation growth in China.

PubMed

Cui, Yaoping

2013-07-01

The estimation of optimum temperature of vegetation growth is very useful for a wide range of applications such as agriculture and climate change studies. Thermal conditions substantially affect vegetation growth. In this study, the normalized difference vegetation index (NDVI) and daily temperature data set from 1982 to 2006 for China were used to examine optimum temperature of vegetation growth. Based on a simple analysis of ecological amplitude and Shelford's law of tolerance, a scientific framework for calculating the optimum temperature was constructed. The optimum temperature range and referenced optimum temperature (ROT) of terrestrial vegetation were obtained and explored over different eco-geographical regions of China. The results showed that the relationship between NDVI and air temperature was significant over almost all of China, indicating that terrestrial vegetation growth was closely related to thermal conditions. ROTs were different in various regions. The lowest ROT, about 7.0 °C, occurred in the Qinghai-Tibet Plateau, while the highest ROT, more than 22.0 °C, occurred in the middle and lower reaches of the Yangtze River and the Southern China region.

Preliminary Estimation of the Realistic Optimum Temperature for Vegetation Growth in China

NASA Astrophysics Data System (ADS)

Cui, Yaoping

2013-07-01

The estimation of optimum temperature of vegetation growth is very useful for a wide range of applications such as agriculture and climate change studies. Thermal conditions substantially affect vegetation growth. In this study, the normalized difference vegetation index (NDVI) and daily temperature data set from 1982 to 2006 for China were used to examine optimum temperature of vegetation growth. Based on a simple analysis of ecological amplitude and Shelford's law of tolerance, a scientific framework for calculating the optimum temperature was constructed. The optimum temperature range and referenced optimum temperature (ROT) of terrestrial vegetation were obtained and explored over different eco-geographical regions of China. The results showed that the relationship between NDVI and air temperature was significant over almost all of China, indicating that terrestrial vegetation growth was closely related to thermal conditions. ROTs were different in various regions. The lowest ROT, about 7.0 °C, occurred in the Qinghai-Tibet Plateau, while the highest ROT, more than 22.0 °C, occurred in the middle and lower reaches of the Yangtze River and the Southern China region.

Estimating trends in atmospheric water vapor and temperature time series over Germany

NASA Astrophysics Data System (ADS)

Alshawaf, Fadwa; Balidakis, Kyriakos; Dick, Galina; Heise, Stefan; Wickert, Jens

2017-08-01

Ground-based GNSS (Global Navigation Satellite System) has efficiently been used since the 1990s as a meteorological observing system. Recently scientists have used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) data and meteorological measurements. We aim to evaluate climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: (1) estimated from ground-based GNSS observations using the method of precise point positioning, (2) inferred from ERA-Interim reanalysis data, and (3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods: the first applies least squares to deseasonalized time series and the second uses the Theil-Sen estimator. The trends estimated at 113 GNSS sites, with 10 to 19 years temporal coverage, vary between -1.5 and 2.3 mm decade-1 with standard deviations below 0.25 mm decade-1. These results were validated by estimating the trends from ERA-Interim data over the same time windows, which show similar values. These values of the trend depend on the length and the variations of the time series. Therefore, to give a mean value of the PWV trend over Germany, we estimated the trends using ERA-Interim spanning from 1991 to 2016 (26 years) at 227 synoptic stations over Germany. The ERA-Interim data show positive PWV trends of 0.33 ± 0.06 mm decade-1 with standard errors below 0.03 mm decade-1. The increment in PWV varies between 4.5 and 6.5 % per degree Celsius rise in temperature, which is comparable to the theoretical rate of the Clausius

Development of a method for estimating oesophageal temperature by multi-locational temperature measurement inside the external auditory canal

NASA Astrophysics Data System (ADS)

Nakada, Hirofumi; Horie, Seichi; Kawanami, Shoko; Inoue, Jinro; Iijima, Yoshinori; Sato, Kiyoharu; Abe, Takeshi

2017-09-01

We aimed to develop a practical method to estimate oesophageal temperature by measuring multi-locational auditory canal temperatures. This method can be applied to prevent heatstroke by simultaneously and continuously monitoring the core temperatures of people working under hot environments. We asked 11 healthy male volunteers to exercise, generating 80 W for 45 min in a climatic chamber set at 24, 32 and 40 °C, at 50% relative humidity. We also exposed the participants to radiation at 32 °C. We continuously measured temperatures at the oesophagus, rectum and three different locations along the external auditory canal. We developed equations for estimating oesophageal temperatures from auditory canal temperatures and compared their fitness and errors. The rectal temperature increased or decreased faster than oesophageal temperature at the start or end of exercise in all conditions. Estimated temperature showed good similarity with oesophageal temperature, and the square of the correlation coefficient of the best fitting model reached 0.904. We observed intermediate values between rectal and oesophageal temperatures during the rest phase. Even under the condition with radiation, estimated oesophageal temperature demonstrated concordant movement with oesophageal temperature at around 0.1 °C overestimation. Our method measured temperatures at three different locations along the external auditory canal. We confirmed that the approach can credibly estimate the oesophageal temperature from 24 to 40 °C for people performing exercise in the same place in a windless environment.

Estimating the extreme low-temperature event using nonparametric methods

NASA Astrophysics Data System (ADS)

D'Silva, Anisha

This thesis presents a new method of estimating the one-in-N low temperature threshold using a non-parametric statistical method called kernel density estimation applied to daily average wind-adjusted temperatures. We apply our One-in-N Algorithm to local gas distribution companies (LDCs), as they have to forecast the daily natural gas needs of their consumers. In winter, demand for natural gas is high. Extreme low temperature events are not directly related to an LDCs gas demand forecasting, but knowledge of extreme low temperatures is important to ensure that an LDC has enough capacity to meet customer demands when extreme low temperatures are experienced. We present a detailed explanation of our One-in-N Algorithm and compare it to the methods using the generalized extreme value distribution, the normal distribution, and the variance-weighted composite distribution. We show that our One-in-N Algorithm estimates the one-in- N low temperature threshold more accurately than the methods using the generalized extreme value distribution, the normal distribution, and the variance-weighted composite distribution according to root mean square error (RMSE) measure at a 5% level of significance. The One-in- N Algorithm is tested by counting the number of times the daily average wind-adjusted temperature is less than or equal to the one-in- N low temperature threshold.

Groundwater temperature estimation and modeling using hydrogeophysics.

NASA Astrophysics Data System (ADS)

Nguyen, F.; Lesparre, N.; Hermans, T.; Dassargues, A.; Klepikova, M.; Kemna, A.; Caers, J.

2017-12-01

Groundwater temperature may be of use as a state variable proxy for aquifer heat storage, highlighting preferential flow paths, or contaminant remediation monitoring. However, its estimation often relies on scarce temperature data collected in boreholes. Hydrogeophysical methods such as electrical resistivity tomography (ERT) and distributed temperature sensing (DTS) may provide more exhaustive spatial information of the bulk properties of interest than samples from boreholes. If a properly calibrated DTS reading provides direct measurements of the groundwater temperature in the well, ERT requires one to determine the fractional change per degree Celsius. One advantage of this petrophysical relationship is its relative simplicity: the fractional change is often found to be around 0.02 per degree Celcius, and represents mainly the variation of electrical resistivity due to the viscosity effect. However, in presence of chemical and kinetics effects, the variation may also depend on the duration of the test and may neglect reactions occurring between the pore water and the solid matrix. Such effects are not expected to be important for low temperature systems (<30 °C), at least for short experiments. In this contribution, we use different field experiments under natural and forced flow conditions to review developments for the joint use of DTS and ERT to map and monitor the temperature distribution within aquifers, to characterize aquifers in terms of heterogeneity and to better understand processes. We show how temperature time-series measurements might be used to constraint the ERT inverse problem in space and time and how combined ERT-derived and DTS estimation of temperature may be used together with hydrogeological modeling to provide predictions of the groundwater temperature field.

Using Machine learning method to estimate Air Temperature from MODIS over Berlin

NASA Astrophysics Data System (ADS)

Marzban, F.; Preusker, R.; Sodoudi, S.; Taheri, H.; Allahbakhshi, M.

2015-12-01

Land Surface Temperature (LST) is defined as the temperature of the interface between the Earth's surface and its atmosphere and thus it is a critical variable to understand land-atmosphere interactions and a key parameter in meteorological and hydrological studies, which is involved in energy fluxes. Air temperature (Tair) is one of the most important input variables in different spatially distributed hydrological, ecological models. The estimation of near surface air temperature is useful for a wide range of applications. Some applications from traffic or energy management, require Tair data in high spatial and temporal resolution at two meters height above the ground (T2m), sometimes in near-real-time. Thus, a parameterization based on boundary layer physical principles was developed that determines the air temperature from remote sensing data (MODIS). Tair is commonly obtained from synoptic measurements in weather stations. However, the derivation of near surface air temperature from the LST derived from satellite is far from straight forward. T2m is not driven directly by the sun, but indirectly by LST, thus T2m can be parameterized from the LST and other variables such as Albedo, NDVI, Water vapor and etc. Most of the previous studies have focused on estimating T2m based on simple and advanced statistical approaches, Temperature-Vegetation index and energy-balance approaches but the main objective of this research is to explore the relationships between T2m and LST in Berlin by using Artificial intelligence method with the aim of studying key variables to allow us establishing suitable techniques to obtain Tair from satellite Products and ground data. Secondly, an attempt was explored to identify an individual mix of attributes that reveals a particular pattern to better understanding variation of T2m during day and nighttime over the different area of Berlin. For this reason, a three layer Feedforward neural networks is considered with LMA algorithm

Non-invasive estimation of temperature using diagnostic ultrasound during HIFU therapy

NASA Astrophysics Data System (ADS)

Georg, O.; Wilkens, V.

2017-03-01

The use of HIFU for thermal ablation of human tissues requires safe real-time monitoring of the lesion formation during the treatment to avoid damage of the surrounding healthy tissues and to control temperature rise. Besides MR imaging, several methods have been proposed for temperature imaging using diagnostic ultrasound, and echoshift estimation (using speckle tracking) is the most promising and commonly used technique. It is based on the thermal dependence of the ultrasound echo that accounts for two different physical phenomena: local change in speed of sound and thermal expansion of the propagating medium due to changes in temperature. In our experiments we have used two separate transducers: HIFU exposure was performed using a 1.06 MHz single element focusing transducer of 64 mm aperture and 63.2 mm focal length; the ultrasound diagnostic probe of 11 MHz operated in B-mode for image guidance. The temperature measurements were performed in an agar-based tissue-mimicking phantom. To verify the obtained results, numerical modeling of the acoustic and temperature fields was carried out using KZK and Pennes Bioheat equations, as well as measurements with thermocouples were performed.

Explicit formula of finite difference method to estimate human peripheral tissue temperatures during exposure to severe cold stress.

PubMed

Khanday, M A; Hussain, Fida

2015-02-01

During cold exposure, peripheral tissues undergo vasoconstriction to minimize heat loss to preserve the maintenance of a normal core temperature. However, vasoconstricted tissues exposed to cold temperatures are susceptible to freezing and frostbite-related tissue damage. Therefore, it is imperative to establish a mathematical model for the estimation of tissue necrosis due to cold stress. To this end, an explicit formula of finite difference method has been used to obtain the solution of Pennes' bio-heat equation with appropriate boundary conditions to estimate the temperature profiles of dermal and subdermal layers when exposed to severe cold temperatures. The discrete values of nodal temperature were calculated at the interfaces of skin and subcutaneous tissues with respect to the atmospheric temperatures of 25 °C, 20 °C, 15 °C, 5 °C, -5 °C and -10 °C. The results obtained were used to identify the scenarios under which various degrees of frostbite occur on the surface of skin as well as the dermal and subdermal areas. The explicit formula of finite difference method proposed in this model provides more accurate predictions as compared to other numerical methods. This model of predicting tissue temperatures provides researchers with a more accurate prediction of peripheral tissue temperature and, hence, the susceptibility to frostbite during severe cold exposure. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spectral and temperature-dependent infrared emissivity measurements of painted metals for improved temperature estimation during laser damage testing

NASA Astrophysics Data System (ADS)

Baumann, Sean M.; Keenan, Cameron; Marciniak, Michael A.; Perram, Glen P.

2014-10-01

A database of spectral and temperature-dependent emissivities was created for painted Al-alloy laser-damage-testing targets for the purpose of improving the uncertainty to which temperature on the front and back target surfaces may be estimated during laser-damage testing. Previous temperature estimates had been made by fitting an assumed gray-body radiance curve to the calibrated spectral radiance data collected from the back surface using a Telops Imaging Fourier Transform Spectrometer (IFTS). In this work, temperature-dependent spectral emissivity measurements of the samples were made from room temperature to 500 °C using a Surface Optics Corp. SOC-100 Hemispherical Directional Reflectometer (HDR) with Nicolet FTS. Of particular interest was a high-temperature matte-black enamel paint used to coat the rear surfaces of the Al-alloy samples. The paint had been assumed to have a spectrally flat and temperatureinvariant emissivity. However, the data collected using the HDR showed both spectral variation and temperature dependence. The uncertainty in back-surface temperature estimation during laser-damage testing made using the measured emissivities was improved from greater than +10 °C to less than +5 °C for IFTS pixels away from the laser burn-through hole, where temperatures never exceeded those used in the SOC-100 HDR measurements. At beam center, where temperatures exceeded those used in the SOC-100 HDR, uncertainty in temperature estimates grew beyond those made assuming gray-body emissivity. Accurate temperature estimations during laser-damage testing are useful in informing a predictive model for future high-energy-laser weapon applications.

Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures

DOE PAGES

Chylek, Petr; Augustine, John A.; Klett, James D.; ...

2017-09-30

At thousands of stations worldwide, the mean daily surface air temperature is estimated as a mean of the daily maximum (T max) and minimum (T min) temperatures. In this paper, we use the NOAA Surface Radiation Budget Network (SURFRAD) of seven US stations with surface air temperature recorded each minute to assess the accuracy of the mean daily temperature estimate as an average of the daily maximum and minimum temperatures and to investigate how the accuracy of the estimate increases with an increasing number of daily temperature observations. We find the average difference between the estimate based on an averagemore » of the maximum and minimum temperatures and the average of 1440 1-min daily observations to be - 0.05 ± 1.56 °C, based on analyses of a sample of 238 days of temperature observations. Considering determination of the daily mean temperature based on 3, 4, 6, 12, or 24 daily temperature observations, we find that 2, 4, or 6 daily observations do not reduce significantly the uncertainty of the daily mean temperature. The bias reduction in a statistically significant manner (95% confidence level) occurs only with 12 or 24 daily observations. The daily mean temperature determination based on 24 hourly observations reduces the sample daily temperature uncertainty to - 0.01 ± 0.20 °C. Finally, estimating the parameters of population of all SURFRAD observations, the 95% confidence intervals based on 24 hourly measurements is from - 0.025 to 0.004 °C, compared to a confidence interval from - 0.15 to 0.05 °C based on the mean of T max and T min.« less

Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chylek, Petr; Augustine, John A.; Klett, James D.

At thousands of stations worldwide, the mean daily surface air temperature is estimated as a mean of the daily maximum (T max) and minimum (T min) temperatures. In this paper, we use the NOAA Surface Radiation Budget Network (SURFRAD) of seven US stations with surface air temperature recorded each minute to assess the accuracy of the mean daily temperature estimate as an average of the daily maximum and minimum temperatures and to investigate how the accuracy of the estimate increases with an increasing number of daily temperature observations. We find the average difference between the estimate based on an averagemore » of the maximum and minimum temperatures and the average of 1440 1-min daily observations to be - 0.05 ± 1.56 °C, based on analyses of a sample of 238 days of temperature observations. Considering determination of the daily mean temperature based on 3, 4, 6, 12, or 24 daily temperature observations, we find that 2, 4, or 6 daily observations do not reduce significantly the uncertainty of the daily mean temperature. The bias reduction in a statistically significant manner (95% confidence level) occurs only with 12 or 24 daily observations. The daily mean temperature determination based on 24 hourly observations reduces the sample daily temperature uncertainty to - 0.01 ± 0.20 °C. Finally, estimating the parameters of population of all SURFRAD observations, the 95% confidence intervals based on 24 hourly measurements is from - 0.025 to 0.004 °C, compared to a confidence interval from - 0.15 to 0.05 °C based on the mean of T max and T min.« less

Improving the quality of parameter estimates obtained from slug tests

USGS Publications Warehouse

Butler, J.J.; McElwee, C.D.; Liu, W.

1996-01-01

The slug test is one of the most commonly used field methods for obtaining in situ estimates of hydraulic conductivity. Despite its prevalence, this method has received criticism from many quarters in the ground-water community. This criticism emphasizes the poor quality of the estimated parameters, a condition that is primarily a product of the somewhat casual approach that is often employed in slug tests. Recently, the Kansas Geological Survey (KGS) has pursued research directed it improving methods for the performance and analysis of slug tests. Based on extensive theoretical and field research, a series of guidelines have been proposed that should enable the quality of parameter estimates to be improved. The most significant of these guidelines are: (1) three or more slug tests should be performed at each well during a given test period; (2) two or more different initial displacements (Ho) should be used at each well during a test period; (3) the method used to initiate a test should enable the slug to be introduced in a near-instantaneous manner and should allow a good estimate of Ho to be obtained; (4) data-acquisition equipment that enables a large quantity of high quality data to be collected should be employed; (5) if an estimate of the storage parameter is needed, an observation well other than the test well should be employed; (6) the method chosen for analysis of the slug-test data should be appropriate for site conditions; (7) use of pre- and post-analysis plots should be an integral component of the analysis procedure, and (8) appropriate well construction parameters should be employed. Data from slug tests performed at a number of KGS field sites demonstrate the importance of these guidelines.

Obtaining Reliable Estimates of Ambulatory Physical Activity in People with Parkinson's Disease.

PubMed

Paul, Serene S; Ellis, Terry D; Dibble, Leland E; Earhart, Gammon M; Ford, Matthew P; Foreman, K Bo; Cavanaugh, James T

2016-05-05

We determined the number of days required, and whether to include weekdays and/or weekends, to obtain reliable measures of ambulatory physical activity in people with Parkinson's disease (PD). Ninety-two persons with PD wore a step activity monitor for seven days. The number of days required to obtain a reliable estimate of daily activity was determined from the mean intraclass correlation (ICC2,1) for all possible combinations of 1-6 consecutive days of monitoring. Two days of monitoring were sufficient to obtain reliable daily activity estimates (ICC2,1 > 0.9). Amount (p = 0.03) but not intensity (p = 0.13) of ambulatory activity was greater on weekdays than weekends. Activity prescription based on amount rather than intensity may be more appropriate for people with PD.

Temperature estimation for the most upper part of magmatic chamber of the Elbrus volcano

NASA Astrophysics Data System (ADS)

Likhodeev, Dmitry

2013-04-01

The results of theoretical and experimental studies on thermal processes in the Elbrus volcanic center and adjacent territories are presented. Distributed temperature measurements on the Elbrus volcano and near the Maloye Azau glacier by means of temperature data loggers («High Capacity Temperature Loggers iButton» and «Rejim-avtomat-termo-10-100») have been performed. The comparative time series analysis is provided. On the basis of the Geophysical Observatory in Northern Caucasus, in the laboratory located some 20 km from the Elbrus volcano in the tunnel at a depth of 4 km the array of temperature sensors has been deployed. Results of continuous observations over variations of underground temperatures, including pin-point measurements in the vicinity of sources of carbonaceous mineral waters are presented and discussed. Temperature estimations for the most upper part of the shallow magmatic chamber of the of the Elbrus volcano were obtained on the basis of experimental measurements in the 180-meter deep borehole drilled through the glacier on the western plateau of Mount Elbrus. The estimations of deep temperatures have confirmed the possibility of existence of the magmatic chamber at depths of 0-1 km below sea level. At the same time the magnitudes of local heat flux were identified with enhanced precision. Thus, the original scientific results provide significant extension to our knowledge on possible resumption of volcanic activity in the vicinity of Mount Elbrus.

Neutral Gas Temperature Estimates in an Inductively Coupled CF4 Plasma by Fitting Diatomic Emission Spectra

NASA Technical Reports Server (NTRS)

Cruden, Brett A.; Rao, M. V. V. S.; Sharma, Surendra P.; Meyyappan, M.

2001-01-01

This work examines the accuracy of plasma neutral temperature estimates by fitting the rotational band envelope of different diatomic species in emission. Experiments are performed in an inductively coupled CF4 plasma generated in a Gaseous Electronics Conference reference cell. Visible and ultraviolet emission spectra are collected at a power of 300 W (approximately 0.7 W/cc) and pressure of 30 mtorr. The emission bands of several molecules (CF, CN, C2, CO, and SiF) are fit simultaneously for rotational and vibrational temperatures and compared. Four different rotational temperatures are obtained: 1250 K for CF and CN, 1600 K for CO, 1800 K for C2, and 2300 K for SiF. The vibrational temperatures obtained vary from 1750-5950 K, with the higher vibrational temperatures generally corresponding to the lower rotational temperatures. These results suggest that the different species have achieved different degrees of equilibration between the rotational and vibrational modes and may not be equilibrated with the translational temperatures. The different temperatures are also related to the likelihood that the species are produced by ion bombardment of the surface, with etch products like SiF, CO, and C2 having higher temperatures than species expected to have formed in the gas phase.

Estimating extreme stream temperatures by the standard deviate method

NASA Astrophysics Data System (ADS)

Bogan, Travis; Othmer, Jonathan; Mohseni, Omid; Stefan, Heinz

2006-02-01

It is now widely accepted that global climate warming is taking place on the earth. Among many other effects, a rise in air temperatures is expected to increase stream temperatures indefinitely. However, due to evaporative cooling, stream temperatures do not increase linearly with increasing air temperatures indefinitely. Within the anticipated bounds of climate warming, extreme stream temperatures may therefore not rise substantially. With this concept in mind, past extreme temperatures measured at 720 USGS stream gauging stations were analyzed by the standard deviate method. In this method the highest stream temperatures are expressed as the mean temperature of a measured partial maximum stream temperature series plus its standard deviation multiplied by a factor KE (standard deviate). Various KE-values were explored; values of KE larger than 8 were found physically unreasonable. It is concluded that the value of KE should be in the range from 7 to 8. A unit error in estimating KE translates into a typical stream temperature error of about 0.5 °C. Using a logistic model for the stream temperature/air temperature relationship, a one degree error in air temperature gives a typical error of 0.16 °C in stream temperature. With a projected error in the enveloping standard deviate dKE=1.0 (range 0.5-1.5) and an error in projected high air temperature d Ta=2 °C (range 0-4 °C), the total projected stream temperature error is estimated as d Ts=0.8 °C.

Combined IR imaging-neural network method for the estimation of internal temperature in cooked chicken meat

NASA Astrophysics Data System (ADS)

Ibarra, Juan G.; Tao, Yang; Xin, Hongwei

2000-11-01

A noninvasive method for the estimation of internal temperature in chicken meat immediately following cooking is proposed. The external temperature from IR images was correlated with measured internal temperature through a multilayer neural network. To provide inputs for the network, time series experiments were conducted to obtain simultaneous observations of internal and external temperatures immediately after cooking during the cooling process. An IR camera working at the spectral band of 3.4 to 5.0 micrometers registered external temperature distributions without the interference of close-to-oven environment, while conventional thermocouples registered internal temperatures. For an internal temperature at a given time, simultaneous and lagged external temperature observations were used as the input of the neural network. Based on practical and statistical considerations, a criterion is established to reduce the nodes in the neural network input. The combined method was able to estimate internal temperature for times between 0 and 540 s within a standard error of +/- 1.01 degree(s)C, and within an error of +/- 1.07 degree(s)C for short times after cooking (3 min), with two thermograms at times t and t+30s. The method has great potential for monitoring of doneness of chicken meat in conveyor belt type cooking and can be used as a platform for similar studies in other food products.

Parallel conductance estimation by hypertonic dilution method with conductance catheter: effects of the bolus concentration and temperature.

PubMed

Herrera, M C; Olivera, J M; Valentinuzzi, M E

1999-07-01

The conductance catheter has gained momentum since its introduction in cardiovascular dynamics back in 1980. However, measuring errors are still blurring its clinical acceptance. The main objective here was to study the effects of the injected saline concentration and temperature on the evaluation of the parallel conductance, Gp, and thus, on the correction volume Vp. That conductance, Gp, and its associated volume, Vp, were computed using 167 saline dilution curves obtained with boluses at different concentrations and temperatures, injected in seven anesthetized closed-chest dogs. The excursion of the total conductance relative to the steady-state value during a saline maneuver showed good correlation with the injected concentration at both studied temperatures. The reference parallel volume (one reference per dog) was defined as the average value obtained with three successive maneuvers, at 6-M concentration and at body temperature; therefore, the method acted as its own reference. The variation of Vp relative to the reference value was clearly dependent on the injected concentration and on its temperature; dispersion was greater at 22 degrees C than at 40 degrees C. The variability would recognize also other causes, such as uncertainty of the extrapolation procedure and the thoracic redistribution of electrical field lines. As conclusion, it is recommended to characterize each maneuver by its concentration and temperature. Body temperature and 6-M concentration appear as the most recommendable combination for the injectate in most animals. Finally, these results intend to characterize the Vp estimation procedure in order to minimize errors. The variability of Vp, in different experimental conditions, demonstrated that both concentration and temperature are additional parameters that may modify the Gp estimate.

Targeted estimation of nuisance parameters to obtain valid statistical inference.

PubMed

van der Laan, Mark J

2014-01-01

In order to obtain concrete results, we focus on estimation of the treatment specific mean, controlling for all measured baseline covariates, based on observing independent and identically distributed copies of a random variable consisting of baseline covariates, a subsequently assigned binary treatment, and a final outcome. The statistical model only assumes possible restrictions on the conditional distribution of treatment, given the covariates, the so-called propensity score. Estimators of the treatment specific mean involve estimation of the propensity score and/or estimation of the conditional mean of the outcome, given the treatment and covariates. In order to make these estimators asymptotically unbiased at any data distribution in the statistical model, it is essential to use data-adaptive estimators of these nuisance parameters such as ensemble learning, and specifically super-learning. Because such estimators involve optimal trade-off of bias and variance w.r.t. the infinite dimensional nuisance parameter itself, they result in a sub-optimal bias/variance trade-off for the resulting real-valued estimator of the estimand. We demonstrate that additional targeting of the estimators of these nuisance parameters guarantees that this bias for the estimand is second order and thereby allows us to prove theorems that establish asymptotic linearity of the estimator of the treatment specific mean under regularity conditions. These insights result in novel targeted minimum loss-based estimators (TMLEs) that use ensemble learning with additional targeted bias reduction to construct estimators of the nuisance parameters. In particular, we construct collaborative TMLEs (C-TMLEs) with known influence curve allowing for statistical inference, even though these C-TMLEs involve variable selection for the propensity score based on a criterion that measures how effective the resulting fit of the propensity score is in removing bias for the estimand. As a particular special

Estimation of daily mean air temperature from satellite derived radiometric data

NASA Technical Reports Server (NTRS)

Phinney, D.

1976-01-01

The Screwworm Eradication Data System (SEDS) at JSC utilizes satellite derived estimates of daily mean air temperature (DMAT) to monitor the effect of temperature on screwworm populations. The performance of the SEDS screwworm growth potential predictions depends in large part upon the accuracy of the DMAT estimates.

An algorithm for the estimation of bounds on the emissivity and temperatures from thermal multispectral airborne remotely sensed data

NASA Technical Reports Server (NTRS)

Jaggi, S.; Quattrochi, D.; Baskin, R.

1992-01-01

The effective flux incident upon the detectors of a thermal sensor, after it has been corrected for atmospheric effects, is a function of a non-linear combination of the emissivity of the target for that channel and the temperature of the target. The sensor system cannot separate the contribution from the emissivity and the temperature that constitute the flux value. A method that estimates the bounds on these temperatures and emissivities from thermal data is described. This method is then tested with remotely sensed data obtained from NASA's Thermal Infrared Multispectral Scanner (TIMS) - a 6 channel thermal sensor. Since this is an under-determined set of equations i.e. there are 7 unknowns (6 emissivities and 1 temperature) and 6 equations (corresponding to the 6 channel fluxes), there exist theoretically an infinite combination of values of emissivities and temperature that can satisfy these equations. Using some realistic bounds on the emissivities, bounds on the temperature are calculated. These bounds on the temperature are refined to estimate a tighter bound on the emissivity of the source. An error analysis is also carried out to quantitatively determine the extent of uncertainty introduced in the estimate of these parameters. This method is useful only when a realistic set of bounds can be obtained for the emissivities of the data. In the case of water the lower and upper bounds were set at 0.97 and 1.00 respectively. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected with the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. Ground truth temperatures using thermometers and radiometers were also obtained over an area of the reservoir. The results of two independent runs of the radiometer data averaged

Inverse heat conduction estimation of inner wall temperature fluctuations under turbulent penetration

NASA Astrophysics Data System (ADS)

Guo, Zhouchao; Lu, Tao; Liu, Bo

2017-04-01

Turbulent penetration can occur when hot and cold fluids mix in a horizontal T-junction pipe at nuclear plants. Caused by the unstable turbulent penetration, temperature fluctuations with large amplitude and high frequency can lead to time-varying wall thermal stress and even thermal fatigue on the inner wall. Numerous cases, however, exist where inner wall temperatures cannot be measured and only outer wall temperature measurements are feasible. Therefore, it is one of the popular research areas in nuclear science and engineering to estimate temperature fluctuations on the inner wall from measurements of outer wall temperatures without damaging the structure of the pipe. In this study, both the one-dimensional (1D) and the two-dimensional (2D) inverse heat conduction problem (IHCP) were solved to estimate the temperature fluctuations on the inner wall. First, numerical models of both the 1D and the 2D direct heat conduction problem (DHCP) were structured in MATLAB, based on the finite difference method with an implicit scheme. Second, both the 1D IHCP and the 2D IHCP were solved by the steepest descent method (SDM), and the DHCP results of temperatures on the outer wall were used to estimate the temperature fluctuations on the inner wall. Third, we compared the temperature fluctuations on the inner wall estimated by the 1D IHCP with those estimated by the 2D IHCP in four cases: (1) when the maximum disturbance of temperature of fluid inside the pipe was 3°C, (2) when the maximum disturbance of temperature of fluid inside the pipe was 30°C, (3) when the maximum disturbance of temperature of fluid inside the pipe was 160°C, and (4) when the fluid temperatures inside the pipe were random from 50°C to 210°C.

Mesospheric temperature estimation from meteor decay times of weak and strong meteor trails

NASA Astrophysics Data System (ADS)

Kim, Jeong-Han; Kim, Yong Ha; Jee, Geonhwa; Lee, Changsup

2012-11-01

Neutral temperatures near the mesopause region were estimated from the decay times of the meteor echoes observed by a VHF meteor radar during a period covering 2007 to 2009 at King Sejong Station (62.22°S, 58.78°W), Antarctica. While some previous studies have used all meteor echoes to determine the slope from a height profile of log inverse decay times for temperature estimation, we have divided meteor echoes into weak and strong groups of underdense meteor trails, depending on the strength of estimated relative electron line densities within meteor trails. We found that the slopes from the strong group are inappropriate for temperature estimation because the decay times of strong meteors are considerably scattered, whereas the slopes from the weak group clearly define the variation of decay times with height. We thus utilize the slopes only from the weak group in the altitude region between 86 km and 96 km to estimate mesospheric temperatures. The meteor estimated temperatures show a typical seasonal variation near the mesopause region and the monthly mean temperatures are in good agreement with SABER temperatures within a mean difference of 4.8 K throughout the year. The meteor temperatures, representing typically the region around the altitude of 91 km, are lower on average by 2.1 K than simultaneously measured SATI OH(6-2) rotational temperatures during winter (March-October).

Insulation disks on the skin to estimate muscle temperature.

PubMed

Brajkovic, Dragan; Ducharme, Michel B; Webb, Paul; Reardon, Frank D; Kenny, Glen P

2006-08-01

This study examined the use of insulation disks placed on the skin to estimate muscle temperature in resting subjects exposed to a thermoneutral (28 degrees C) ambient environment. The working hypothesis was that the skin temperature under each insulation disk would increase to a value corresponding to a specific muscle temperature measured by a control probe at 0.8+/-0.2, 1.3+/-0.2, 1.8+/-0.2, 2.3+/-0.2, and 2.8+/-0.2 cm below the skin surface. Eight subjects sat for 120 min while lateral thigh skin temperatures and vastus lateralis muscle temperature were directly measured. Vastus lateralis temperature was estimated non-invasively using two 5 cm diameter foam neoprene disks which were placed on top of the skin temperature probes (from time 60 to 120 min) located at 15.3 and 26.3 cm superior to the patella. The disks at the two locations were 3.2 and 4.8 mm thick, respectively. The placement of the 3.2- and 4.8-mm disks on the thigh for a minimum of 15 and 20 min, respectively, resulted in an increase in skin temperature under the disks which corresponded to the lateral thigh muscle temperature measured directly and invasively at 0.8+/-0.2 and 1.3+/-0.2 cm, respectively, below the skin.

Estimation of Surface Air Temperature from MODIS 1km Resolution Land Surface Temperature Over Northern China

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2010-01-01

Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).

Estimation of river and stream temperature trends under haphazard sampling

USGS Publications Warehouse

Gray, Brian R.; Lyubchich, Vyacheslav; Gel, Yulia R.; Rogala, James T.; Robertson, Dale M.; Wei, Xiaoqiao

2015-01-01

Long-term temporal trends in water temperature in rivers and streams are typically estimated under the assumption of evenly-spaced space-time measurements. However, sampling times and dates associated with historical water temperature datasets and some sampling designs may be haphazard. As a result, trends in temperature may be confounded with trends in time or space of sampling which, in turn, may yield biased trend estimators and thus unreliable conclusions. We address this concern using multilevel (hierarchical) linear models, where time effects are allowed to vary randomly by day and date effects by year. We evaluate the proposed approach by Monte Carlo simulations with imbalance, sparse data and confounding by trend in time and date of sampling. Simulation results indicate unbiased trend estimators while results from a case study of temperature data from the Illinois River, USA conform to river thermal assumptions. We also propose a new nonparametric bootstrap inference on multilevel models that allows for a relatively flexible and distribution-free quantification of uncertainties. The proposed multilevel modeling approach may be elaborated to accommodate nonlinearities within days and years when sampling times or dates typically span temperature extremes.

Measurements of temperature characteristics and estimation of terahertz negative differential conductance in resonant-tunneling-diode oscillators

NASA Astrophysics Data System (ADS)

Asada, M.; Suzuki, S.; Fukuma, T.

2017-11-01

The temperature dependences of output power, oscillation frequency, and current-voltage curve are measured for resonant-tunneling-diode terahertz (THz) oscillators. The output power largely changes with temperature owing to the change in Ohmic loss. In contrast to the output power, the oscillation frequency and current-voltage curve are almost insensitive to temperature. The measured temperature dependence of output power is compared with the theoretical calculation including the negative differential conductance (NDC) as a fitting parameter assumed to be independent of temperature. Very good agreement was obtained between the measurement and calculation, and the NDC in the THz frequency region is estimated. The results show that the absolute values of NDC in the THz region significantly decrease relative to that at DC, and increases with increasing frequency in the measured frequency range.

Assessment of a Technique for Estimating Total Column Water Vapor Using Measurements of the Infrared Sky Temperature

NASA Technical Reports Server (NTRS)

Merceret, Francis J.; Huddleston, Lisa L.

2014-01-01

A method for estimating the integrated precipitable water (IPW) content of the atmosphere using measurements of indicated infrared zenith sky temperature was validated over east-central Florida. The method uses inexpensive, commercial off the shelf, hand-held infrared thermometers (IRT). Two such IRTs were obtained from a commercial vendor, calibrated against several laboratory reference sources at KSC, and used to make IR zenith sky temperature measurements in the vicinity of KSC and Cape Canaveral Air Force Station (CCAFS). The calibration and comparison data showed that these inexpensive IRTs provided reliable, stable IR temperature measurements that were well correlated with the NOAA IPW observations.

A new method for the estimation of high temperature radiant heat emittance by means of aero-acoustic levitation

NASA Astrophysics Data System (ADS)

Greffrath, Fabian; Prieler, Robert; Telle, Rainer

2014-11-01

A new method for the experimental estimation of radiant heat emittance at high temperatures has been developed which involves aero-acoustic levitation of samples, laser heating and contactless temperature measurement. Radiant heat emittance values are determined from the time dependent development of the sample temperature which requires analysis of both the radiant and convective heat transfer towards the surroundings by means of fluid dynamics calculations. First results for the emittance of a corundum sample obtained with this method are presented in this article and found in good agreement with literature values.

Low-Temperature Hydrothermal Resource Potential Estimate

DOE Data Explorer

Katherine Young

2016-06-30

Compilation of data (spreadsheet and shapefiles) for several low-temperature resource types, including isolated springs and wells, delineated area convection systems, sedimentary basins and coastal plains sedimentary systems. For each system, we include estimates of the accessible resource base, mean extractable resource and beneficial heat. Data compiled from USGS and other sources. The paper (submitted to GRC 2016) describing the methodology and analysis is also included.

A Temperature-Based Bioimpedance Correction for Water Loss Estimation During Sports.

PubMed

Ring, Matthias; Lohmueller, Clemens; Rauh, Manfred; Mester, Joachim; Eskofier, Bjoern M

2016-11-01

The amount of total body water (TBW) can be estimated based on bioimpedance measurements of the human body. In sports, TBW estimations are of importance because mild water losses can impair muscular strength and aerobic endurance. Severe water losses can even be life threatening. TBW estimations based on bioimpedance, however, fail during sports because the increased body temperature corrupts bioimpedance measurements. Therefore, this paper proposes a machine learning method that eliminates the effects of increased temperature on bioimpedance and, consequently, reveals the changes in bioimpedance that are due to TBW loss. This is facilitated by utilizing changes in skin and core temperature. The method was evaluated in a study in which bioimpedance, temperature, and TBW loss were recorded every 15 min during a 2-h running workout. The evaluation demonstrated that the proposed method is able to reduce the error of TBW loss estimation by up to 71%, compared to the state of art. In the future, the proposed method in combination with portable bioimpedance devices might facilitate the development of wearable systems for continuous and noninvasive TBW loss monitoring during sports.

Estimating Evaporative Fraction From Readily Obtainable Variables in Mangrove Forests of the Everglades, U.S.A.

NASA Technical Reports Server (NTRS)

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John; Barr, Jordan

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) the ratio of latent heat (LE; energy equivalent of evapotranspiration -ET-) to total available energy from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micro-meteorological and flux tower observations, or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature [T(sub s)] normalized difference vegetation index (NDVI)and daily maximum air temperature [T(sub a)]. The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using T(sub s) and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the T(sub s) from Landsat relative to the T(sub s) from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Estimating evaporative fraction from readily obtainable variables in mangrove forests of the Everglades, U.S.A.

USGS Publications Warehouse

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John W.; Barr, Jordan G.

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) – the ratio of latent heat (LE; energy equivalent of evapotranspiration –ET–) to total available energy – from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micrometeorological and flux tower observations or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature (Ts) normalized difference vegetation index (NDVI) and daily maximum air temperature (Ta). The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using Ts and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the Ts from Landsat relative to the Ts from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Using pairs of physiological models to estimate temporal variation in amphibian body temperature.

PubMed

Roznik, Elizabeth A; Alford, Ross A

2014-10-01

Physical models are often used to estimate ectotherm body temperatures, but designing accurate models for amphibians is difficult because they can vary in cutaneous resistance to evaporative water loss. To account for this variability, a recently published technique requires a pair of agar models that mimic amphibians with 0% and 100% resistance to evaporative water loss; the temperatures of these models define the lower and upper boundaries of possible amphibian body temperatures for the location in which they are placed. The goal of our study was to develop a method for using these pairs of models to estimate parameters describing the distributions of body temperatures of frogs under field conditions. We radiotracked green-eyed treefrogs (Litoria serrata) and collected semi-continuous thermal data using both temperature-sensitive radiotransmitters with an automated datalogging receiver, and pairs of agar models placed in frog locations, and we collected discrete thermal data using a non-contact infrared thermometer when frogs were located. We first examined the accuracy of temperature-sensitive transmitters in estimating frog body temperatures by comparing transmitter data with direct temperature measurements taken simultaneously for the same individuals. We then compared parameters (mean, minimum, maximum, standard deviation) characterizing the distributions of temperatures of individual frogs estimated from data collected using each of the three methods. We found strong relationships between thermal parameters estimated from data collected using automated radiotelemetry and both types of thermal models. These relationships were stronger for data collected using automated radiotelemetry and impermeable thermal models, suggesting that in the field, L. serrata has a relatively high resistance to evaporative water loss. Our results demonstrate that placing pairs of thermal models in frog locations can provide accurate estimates of the distributions of temperatures

Estimation of daily minimum land surface air temperature using MODIS data in southern Iran

NASA Astrophysics Data System (ADS)

Didari, Shohreh; Norouzi, Hamidreza; Zand-Parsa, Shahrokh; Khanbilvardi, Reza

2017-11-01

Land surface air temperature (LSAT) is a key variable in agricultural, climatological, hydrological, and environmental studies. Many of their processes are affected by LSAT at about 5 cm from the ground surface (LSAT5cm). Most of the previous studies tried to find statistical models to estimate LSAT at 2 m height (LSAT2m) which is considered as a standardized height, and there is not enough study for LSAT5cm estimation models. Accurate measurements of LSAT5cm are generally acquired from meteorological stations, which are sparse in remote areas. Nonetheless, remote sensing data by providing rather extensive spatial coverage can complement the spatiotemporal shortcomings of meteorological stations. The main objective of this study was to find a statistical model from the previous day to accurately estimate spatial daily minimum LSAT5cm, which is very important in agricultural frost, in Fars province in southern Iran. Land surface temperature (LST) data were obtained using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra satellites at daytime and nighttime periods with normalized difference vegetation index (NDVI) data. These data along with geometric temperature and elevation information were used in a stepwise linear model to estimate minimum LSAT5cm during 2003-2011. The results revealed that utilization of MODIS Aqua nighttime data of previous day provides the most applicable and accurate model. According to the validation results, the accuracy of the proposed model was suitable during 2012 (root mean square difference ( RMSD) = 3.07 °C, {R}_{adj}^2 = 87 %). The model underestimated (overestimated) high (low) minimum LSAT5cm. The accuracy of estimation in the winter time was found to be lower than the other seasons ( RMSD = 3.55 °C), and in summer and winter, the errors were larger than in the remaining seasons.

Gaussian interferometric power and Black box estimation of Unruh temperature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jieci, E-mail: jcwang@hunnu.edu.cn; Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190; Cao, Haixin

2016-10-15

We present a black box estimation paradigm of Unruh temperature in a relativistic bosonic continuous-variable setting. It is shown that the guaranteed precision for the estimation of Unruh temperature can be evaluated by the Gaussian interferometric power for a given probe state. We demonstrate that the amount of interferometric power is always beyond the entanglement type quantum correlations in a relativistic setting. It is found that due to the fact that Unruh radiation acts as a thermal bath on the probe system, it destroys available resources of the probe system and reduces the guaranteed precision of the estimation of Unruhmore » temperature. We also find that the thermal noise induced by Unruh effect will generate interferometric power between accelerated Bob and his auxiliary partner anti-Bob, while it does not generate any correlation between inertial Alice and anti-Bob.« less

NMR permeability estimators in 'chalk' carbonate rocks obtained under different relaxation times and MICP size scalings

NASA Astrophysics Data System (ADS)

Rios, Edmilson Helton; Figueiredo, Irineu; Moss, Adam Keith; Pritchard, Timothy Neil; Glassborow, Brent Anthony; Guedes Domingues, Ana Beatriz; Bagueira de Vasconcellos Azeredo, Rodrigo

2016-07-01

The effect of the selection of different nuclear magnetic resonance (NMR) relaxation times for permeability estimation is investigated for a set of fully brine-saturated rocks acquired from Cretaceous carbonate reservoirs in the North Sea and Middle East. Estimators that are obtained from the relaxation times based on the Pythagorean means are compared with estimators that are obtained from the relaxation times based on the concept of a cumulative saturation cut-off. Select portions of the longitudinal (T1) and transverse (T2) relaxation-time distributions are systematically evaluated by applying various cut-offs, analogous to the Winland-Pittman approach for mercury injection capillary pressure (MICP) curves. Finally, different approaches to matching the NMR and MICP distributions using different mean-based scaling factors are validated based on the performance of the related size-scaled estimators. The good results that were obtained demonstrate possible alternatives to the commonly adopted logarithmic mean estimator and reinforce the importance of NMR-MICP integration to improving carbonate permeability estimates.

Crowdsourcing urban air temperatures through smartphone battery temperatures in São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Droste, Arjan; Pape, Jan-Jaap; Overeem, Aart; Leijnse, Hidde; Steeneveld, Gert-Jan; Van Delden, Aarnout; Uijlenhoet, Remko

2017-04-01

Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where traditional measurements are scarce. Earlier studies showed that smartphone battery temperature readings allow for estimating the daily and city-wide air temperature via a straightforward heat transfer model. This study advances these model estimations by studying spatially and temporally smaller scales. The accuracy of temperature retrievals as a function of the number of battery readings is also studied. An extensive dataset of over 10 million battery temperature readings is available for São Paulo (Brazil), for estimating hourly and daily air temperatures. The air temperature estimates are validated with air temperature measurements from a WMO station, an Urban Fluxnet site, and crowdsourced data from 7 hobby meteorologists' private weather stations. On a daily basis temperature estimates are good, and we show they improve by optimizing model parameters for neighbourhood scales as categorized in Local Climate Zones. Temperature differences between Local Climate Zones can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, initial results are poor, but are vastly improved by using a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The obtained results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking.

Estimation of Circadian Body Temperature Rhythm Based on Heart Rate in Healthy, Ambulatory Subjects.

PubMed

Sim, Soo Young; Joo, Kwang Min; Kim, Han Byul; Jang, Seungjin; Kim, Beomoh; Hong, Seungbum; Kim, Sungwan; Park, Kwang Suk

2017-03-01

Core body temperature is a reliable marker for circadian rhythm. As characteristics of the circadian body temperature rhythm change during diverse health problems, such as sleep disorder and depression, body temperature monitoring is often used in clinical diagnosis and treatment. However, the use of current thermometers in circadian rhythm monitoring is impractical in daily life. As heart rate is a physiological signal relevant to thermoregulation, we investigated the feasibility of heart rate monitoring in estimating circadian body temperature rhythm. Various heart rate parameters and core body temperature were simultaneously acquired in 21 healthy, ambulatory subjects during their routine life. The performance of regression analysis and the extended Kalman filter on daily body temperature and circadian indicator (mesor, amplitude, and acrophase) estimation were evaluated. For daily body temperature estimation, mean R-R interval (RRI), mean heart rate (MHR), or normalized MHR provided a mean root mean square error of approximately 0.40 °C in both techniques. The mesor estimation regression analysis showed better performance than the extended Kalman filter. However, the extended Kalman filter, combined with RRI or MHR, provided better accuracy in terms of amplitude and acrophase estimation. We suggest that this noninvasive and convenient method for estimating the circadian body temperature rhythm could reduce discomfort during body temperature monitoring in daily life. This, in turn, could facilitate more clinical studies based on circadian body temperature rhythm.

Global climatology and variability of potential new production estimated from remote sensing of sea-surface temperature

NASA Technical Reports Server (NTRS)

Dugdale, Richard C.; Wilkerson, Frances P.

1995-01-01

During this project we have collected numerous shipboard data-bases of oceanic nitrate and silicate versus temperature for both equatorial and coastal upwelling regions. These cruises all have accompanying N-15 measurements of new production. The inverse relationships between nutrients and temperatures have been determined and are being used to obtain surface nutrient fields from sea surface temperatures measured remotely by satellite borne sensors- i.e. AVHRR data from NOAA satellites contained in the MCSST data set for the world ocean provided by the University of Miami. The images and data derived from space in this way show the strong seasonal fluctuations and interannual el Nino fluctuations of the nitrate field. the nitrate data has been used to make estimates of new production for the equatorial pacific which are compared with shipboard measurements when available. The importance of silicate as a nutrient driving new production and the ratio of nitrate to silicate has been discovered to be crucial to better understand the causes of new production variability, so we have added these parameters to our study and have begun to make estimates of these for the equatorial Pacific, derived from the weekly averaged sea surface temperatures (SSTs).

Temperature-based death time estimation with only partially known environmental conditions.

PubMed

Mall, Gita; Eckl, Mona; Sinicina, Inga; Peschel, Oliver; Hubig, Michael

2005-07-01

The temperature-oriented death time determination is based on mathematical model curves of postmortem rectal cooling. All mathematical models require knowledge of the environmental conditions. In medico-legal practice homicide is sometimes not immediately suspected at the death scene but afterwards during external examination of the body. The environmental temperature at the death scene remains unknown or can only be roughly reconstructed. In such cases the question arises whether it is possible to estimate the time since death from rectal temperature data alone recorded over a longer time span. The present study theoretically deduces formulae which are independent of the initial and environmental temperatures and thus proves that the information needed for death time estimation is contained in the rectal temperature data. Since the environmental temperature at the death scene may differ from that during the temperature recording, an additional factor has to be used. This is that the body core is thermally well isolated from the environment and that the rectal temperature decrease after a sudden change of environmental temperature will continue for some time at a rate similar to that before the sudden change. The present study further provides a curve-fitting procedure for such scenarios. The procedure was tested in rectal cooling data of from 35 corpses using the most commonly applied model of Henssge. In all cases the time of death was exactly known. After admission to the medico-legal institute the bodies were kept at a constant environmental temperature for 12-36 h and the rectal temperatures were recorded continuously. The curve-fitting procedure led to valid estimates of the time since death in all experiments despite the unknown environmental conditions before admission to the institute. The estimation bias was investigated statistically. The 95% confidence intervals amounted to +/-4 h, which seems reasonable compared to the 95% confidence intervals of the

Estimation of daily maximum and minimum air temperatures in urban landscapes using MODIS time series satellite data

NASA Astrophysics Data System (ADS)

Yoo, Cheolhee; Im, Jungho; Park, Seonyoung; Quackenbush, Lindi J.

2018-03-01

Urban air temperature is considered a significant variable for a variety of urban issues, and analyzing the spatial patterns of air temperature is important for urban planning and management. However, insufficient weather stations limit accurate spatial representation of temperature within a heterogeneous city. This study used a random forest machine learning approach to estimate daily maximum and minimum air temperatures (Tmax and Tmin) for two megacities with different climate characteristics: Los Angeles, USA, and Seoul, South Korea. This study used eight time-series land surface temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS), with seven auxiliary variables: elevation, solar radiation, normalized difference vegetation index, latitude, longitude, aspect, and the percentage of impervious area. We found different relationships between the eight time-series LSTs with Tmax/Tmin for the two cities, and designed eight schemes with different input LST variables. The schemes were evaluated using the coefficient of determination (R2) and Root Mean Square Error (RMSE) from 10-fold cross-validation. The best schemes produced R2 of 0.850 and 0.777 and RMSE of 1.7 °C and 1.2 °C for Tmax and Tmin in Los Angeles, and R2 of 0.728 and 0.767 and RMSE of 1.1 °C and 1.2 °C for Tmax and Tmin in Seoul, respectively. LSTs obtained the day before were crucial for estimating daily urban air temperature. Estimated air temperature patterns showed that Tmax was highly dependent on the geographic factors (e.g., sea breeze, mountains) of the two cities, while Tmin showed marginally distinct temperature differences between built-up and vegetated areas in the two cities.

Improved Estimation of Electron Temperature from Rocket-borne Impedance Probes

NASA Astrophysics Data System (ADS)

Rowland, D. E.; Wolfinger, K.; Stamm, J. D.

2017-12-01

The impedance probe technique is a well known method for determining high accuracy measurements of electron number density in the Earth's ionosphere. We present analysis of impedance probe data from several sounding rockets at low, mid-, and auroral latitudes, including high cadence estimates of the electron temperature, derived from analytical fits to the antenna impedance curves. These estimates compare favorably with independent estimates from Langmuir Probes, but at much higher temporal and spatial resolution, providing a capability to resolve small-scale temperature fluctuations. We also present some considerations for the design of impedance probes, including assessment of the effects of resonance damping due to rocket motion, effects of wake and spin modulation, and aspect angle to the magnetic field.

Stability of individual loudness functions obtained by magnitude estimation and production

NASA Technical Reports Server (NTRS)

Hellman, R. P.

1981-01-01

A correlational analysis of individual magnitude estimation and production exponents at the same frequency is performed, as is an analysis of individual exponents produced in different sessions by the same procedure across frequency (250, 1000, and 3000 Hz). Taken as a whole, the results show that individual exponent differences do not decrease by counterbalancing magnitude estimation with magnitude production and that individual exponent differences remain stable over time despite changes in stimulus frequency. Further results show that although individual magnitude estimation and production exponents do not necessarily obey the .6 power law, it is possible to predict the slope of an equal-sensation function averaged for a group of listeners from individual magnitude estimation and production data. On the assumption that individual listeners with sensorineural hearing also produce stable and reliable magnitude functions, it is also shown that the slope of the loudness-recruitment function measured by magnitude estimation and production can be predicted for individuals with bilateral losses of long duration. Results obtained in normal and pathological ears thus suggest that individual listeners can produce loudness judgements that reveal, although indirectly, the input-output characteristic of the auditory system.

Estimating methane emissions from landfills based on rainfall, ambient temperature, and waste composition: The CLEEN model.

PubMed

Karanjekar, Richa V; Bhatt, Arpita; Altouqui, Said; Jangikhatoonabad, Neda; Durai, Vennila; Sattler, Melanie L; Hossain, M D Sahadat; Chen, Victoria

2015-12-01

Accurately estimating landfill methane emissions is important for quantifying a landfill's greenhouse gas emissions and power generation potential. Current models, including LandGEM and IPCC, often greatly simplify treatment of factors like rainfall and ambient temperature, which can substantially impact gas production. The newly developed Capturing Landfill Emissions for Energy Needs (CLEEN) model aims to improve landfill methane generation estimates, but still require inputs that are fairly easy to obtain: waste composition, annual rainfall, and ambient temperature. To develop the model, methane generation was measured from 27 laboratory scale landfill reactors, with varying waste compositions (ranging from 0% to 100%); average rainfall rates of 2, 6, and 12 mm/day; and temperatures of 20, 30, and 37°C, according to a statistical experimental design. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Based on the data collected, a multiple linear regression equation (R(2)=0.75) was developed to predict first-order methane generation rate constant values k as functions of waste composition, annual rainfall, and temperature. Because, laboratory methane generation rates exceed field rates, a second scale-up regression equation for k was developed using actual gas-recovery data from 11 landfills in high-income countries with conventional operation. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating both regression equations into the first-order decay based model for estimating methane generation rates from landfills. CLEEN model values were compared to actual field data from 6 US landfills, and to estimates from LandGEM and IPCC. For 4 of the 6 cases, CLEEN model estimates were the closest to actual. Copyright © 2015 Elsevier Ltd. All rights reserved.

Influence of spatial temperature estimation method in ecohydrologic modeling in the western Oregon Cascades

Treesearch

E. Garcia; C.L. Tague; J. Choate

2013-01-01

Most spatially explicit hydrologic models require estimates of air temperature patterns. For these models, empirical relationships between elevation and air temperature are frequently used to upscale point measurements or downscale regional and global climate model estimates of air temperature. Mountainous environments are particularly sensitive to air temperature...

Comparing techniques for estimating flame temperature of prescribed fires

Treesearch

Deborah K. Kennard; Kenneth W. Outcalt; David Jones; Joseph J. O' Brien

2005-01-01

A variety of techniques that estimate temperature and/or heat output during fires are available. We assessed the predictive ability of metal and tile pyrometers, calorimeters of different sizes, and fuel consumption to time-temperature metrics derived from thick and thin thermocouples at 140 points distributed over 9 management-scale burns in a longleaf pine forest in...

Estimation of temperature in micromaser-type systems

NASA Astrophysics Data System (ADS)

Farajollahi, B.; Jafarzadeh, M.; Rangani Jahromi, H.; Amniat-Talab, M.

2018-06-01

We address the estimation of the number of photons and temperature in a micromaser-type system with Fock state and thermal fields. We analyze the behavior of the quantum Fisher information (QFI) for both fields. In particular, we show that in the Fock state field model, the QFI for non-entangled initial state of the atoms increases monotonously with time, while for entangled initial state of the atoms, it shows oscillatory behavior, leading to non-Markovian dynamics. Moreover, it is observed that the QFI, entropy of entanglement and fidelity have collapse and revival behavior. Focusing on each period that the collapses and revivals occur, we see that the optimal points of the QFI and entanglement coincide. In addition, when one of the subsystems evolved state fidelity becomes maximum, the QFI also achieves its maximum. We also address the evolved fidelity versus the initial state as a good witness of non-Markovianity. Moreover, we interestingly find that the entropy of the composite system can be used as a witness of non-Markovian evolution of the subsystems. For the thermal field model, we similarly investigate the relation among the QFI associated with the temperature, von Neumann entropy, and fidelity. In particular, it is found that at the instants when the maximum values of the QFI are achieved, the entanglement between the two-qubit system and the environment is maximized while the entanglement between the probe and its environment is minimized. Moreover, we show that the thermometry may lead to optimal estimation of practical temperatures. Besides, extending our computation to the two-qubit system, we find that using a two-qubit probe generally leads to more effective estimation than the one-qubit scenario. Finally, we show that initial state entanglement plays a key role in the advent of non-Markovianity and determination of its strength in the composite system and its subsystems.

Estimating daily air temperature across the Southeastern United States using high-resolution satellite data: a statistical modeling study

PubMed Central

Shi, Liuhua; Liu, Pengfei; Kloog, Itai; Lee, Mihye; Kosheleva, Anna; Schwartz, Joel

2015-01-01

Accurate estimates of spatio-temporal resolved near-surface air temperature (Ta) are crucial for environmental epidemiological studies. However, values of Ta are conventionally obtained from weather stations, which have limited spatial coverage. Satellite surface temperature (Ts) measurements offer the possibility of local exposure estimates across large domains. The Southeastern United States has different climatic conditions, more small water bodies and wetlands, and greater humidity in contrast to other regions, which add to the challenge of modeling air temperature. In this study, we incorporated satellite Ts to estimate high resolution (1 km × 1 km) daily Ta across the southeastern USA for 2000-2014. We calibrated Ts to Ta measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R2 of 0.952 indicated excellent model performance. When satellite Ts were unavailable, linear regression on nearby monitors and spatio-temporal smoothing was used to estimate Ta. The daily Ta estimations were compared to the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) model. A good agreement with an R2 of 0.969 and a mean squared prediction error (RMSPE) of 1.376 °C was achieved. Our results demonstrate that Ta can be reliably predicted using this Ts-based prediction model, even in a large geographical area with topography and weather patterns varying considerably. PMID:26717080

Temperature-related mortality estimates after accounting for the cumulative effects of air pollution in an urban area.

PubMed

Stanišić Stojić, Svetlana; Stanišić, Nemanja; Stojić, Andreja

2016-07-11

To propose a new method for including the cumulative mid-term effects of air pollution in the traditional Poisson regression model and compare the temperature-related mortality risk estimates, before and after including air pollution data. The analysis comprised a total of 56,920 residents aged 65 years or older who died from circulatory and respiratory diseases in Belgrade, Serbia, and daily mean PM10, NO2, SO2 and soot concentrations obtained for the period 2009-2014. After accounting for the cumulative effects of air pollutants, the risk associated with cold temperatures was significantly lower and the overall temperature-attributable risk decreased from 8.80 to 3.00 %. Furthermore, the optimum range of temperature, within which no excess temperature-related mortality is expected to occur, was very broad, between -5 and 21 °C, which differs from the previous findings that most of the attributable deaths were associated with mild temperatures. These results suggest that, in polluted areas of developing countries, most of the mortality risk, previously attributed to cold temperatures, can be explained by the mid-term effects of air pollution. The results also showed that the estimated relative importance of PM10 was the smallest of four examined pollutant species, and thus, including PM10 data only is clearly not the most effective way to control for the effects of air pollution.

Estimation of the base temperature and growth phase duration in terms of thermal time for four grapevine cultivars

NASA Astrophysics Data System (ADS)

Zapata, D.; Salazar, M.; Chaves, B.; Keller, M.; Hoogenboom, G.

2015-12-01

Thermal time models have been used to predict the development of many different species, including grapevine ( Vitis vinifera L.). These models normally assume that there is a linear relationship between temperature and plant development. The goal of this study was to estimate the base temperature and duration in terms of thermal time for predicting veraison for four grapevine cultivars. Historical phenological data for four cultivars that were collected in the Pacific Northwest were used to develop the thermal time model. Base temperatures ( T b) of 0 and 10 °C and the best estimated T b using three different methods were evaluated for predicting veraison in grapevine. Thermal time requirements for each individual cultivar were evaluated through analysis of variance, and means were compared using the Fisher's test. The methods that were applied to estimate T b for the development of wine grapes included the least standard deviation in heat units, the regression coefficient, and the development rate method. The estimated T b varied among methods and cultivars. The development rate method provided the lowest T b values for all cultivars. For the three methods, Chardonnay had the lowest T b ranging from 8.7 to 10.7 °C, while the highest T b values were obtained for Riesling and Cabernet Sauvignon with 11.8 and 12.8 °C, respectively. Thermal time also differed among cultivars, when either the fixed or estimated T b was used. Predictions of the beginning of ripening with the estimated temperature resulted in the lowest variation in real days when compared with predictions using T b = 0 or 10 °C, regardless of the method that was used to estimate the T b.

Estimating cumulative effects of clearcutting on stream temperatures

USGS Publications Warehouse

Bartholow, J.M.

2000-01-01

The Stream Segment Temperature Model was used to estimate cumulative effects of large-scale timber harvest on stream temperature. Literature values were used to create parameters for the model for two hypothetical situations, one forested and the other extensively clearcut. Results compared favorably with field studies of extensive forest canopy removal. The model provided insight into the cumulative effects of clearcutting. Change in stream shading was, as expected, the most influential factor governing increases in maximum daily water temperature, accounting for 40% of the total increase. Altered stream width was found to be more influential than changes to air temperature. Although the net effect from clearcutting was a 4oC warming, increased wind and reduced humidity tended to cool the stream. Temperature increases due to clearcutting persisted 10 km downstream into an unimpacted forest segment of the hypothetical stream, but those increases were moderated by cooler equilibrium conditions downstream. The model revealed that it is a complex set of factors, not single factors such as shade or air temperature, that governs stream temperature dynamics.

Cluster mass estimators from CMB temperature and polarization lensing

NASA Astrophysics Data System (ADS)

Hu, Wayne; DeDeo, Simon; Vale, Chris

2007-12-01

Upcoming Sunyaev Zel'dovich surveys are expected to return ~104 intermediate mass clusters at high redshift. Their average masses must be known to the same accuracy as desired for the dark energy properties. Internal to the surveys, the cosmic microwave background (CMB) potentially provides a source for lensing mass measurements whose distance is precisely known and behind all clusters. We develop statistical mass estimators from six quadratic combinations of CMB temperature and polarization fields that can simultaneously recover large-scale structure and cluster mass profiles. The performance of these estimators on idealized Navarro Frenk White (NFW) clusters suggests that surveys with a ~1' beam and 10\\,\\muK^{\\prime} noise in uncontaminated temperature maps can make a ~10σ detection, or equivalently a ~10% mass measurement for each 103 set of clusters. With internal or external acoustic scale E-polarization measurements, the ET cross-correlation estimator can provide a stringent test for contaminants on a first detection at ~1/3 the significance. For surveys that reach below 3\\,\\muK^{\\prime}, the EB cross-correlation estimator should provide the most precise measurements and potentially the strongest control over contaminants.

Neutral gas temperature estimates and metastable resonance energy transfer for argon-nitrogen discharges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greig, A., E-mail: amelia.greig@anu.edu.au; Charles, C.; Boswell, R. W.

2016-01-15

Rovibrational spectroscopy band fitting of the nitrogen (N{sub 2}) second positive system is a technique used to estimate the neutral gas temperature of N{sub 2} discharges, or atomic discharges with trace amounts of a N{sub 2} added. For mixtures involving argon and N{sub 2}, resonant energy transfer between argon metastable atoms (Ar*) and N{sub 2} molecules may affect gas temperature estimates made using the second positive system. The effect of Ar* resonance energy transfer is investigated here by analyzing neutral gas temperatures of argon-N{sub 2} mixtures, for N{sub 2} percentages from 1% to 100%. Neutral gas temperature estimates are highermore » than expected for mixtures involving greater than 5% N{sub 2} addition, but are reasonable for argon with less than 5% N{sub 2} addition when compared with an analytic model for ion-neutral charge exchange collisional heating. Additional spatiotemporal investigations into neutral gas temperature estimates with 10% N{sub 2} addition demonstrate that although absolute temperature values may be affected by Ar* resonant energy transfer, spatiotemporal trends may still be used to accurately diagnose the discharge.« less

Digital camera auto white balance based on color temperature estimation clustering

NASA Astrophysics Data System (ADS)

Zhang, Lei; Liu, Peng; Liu, Yuling; Yu, Feihong

2010-11-01

Auto white balance (AWB) is an important technique for digital cameras. Human vision system has the ability to recognize the original color of an object in a scene illuminated by a light source that has a different color temperature from D65-the standard sun light. However, recorded images or video clips, can only record the original information incident into the sensor. Therefore, those recorded will appear different from the real scene observed by the human. Auto white balance is a technique to solve this problem. Traditional methods such as gray world assumption, white point estimation, may fail for scenes with large color patches. In this paper, an AWB method based on color temperature estimation clustering is presented and discussed. First, the method gives a list of several lighting conditions that are common for daily life, which are represented by their color temperatures, and thresholds for each color temperature to determine whether a light source is this kind of illumination; second, an image to be white balanced are divided into N blocks (N is determined empirically). For each block, the gray world assumption method is used to calculate the color cast, which can be used to estimate the color temperature of that block. Third, each calculated color temperature are compared with the color temperatures in the given illumination list. If the color temperature of a block is not within any of the thresholds in the given list, that block is discarded. Fourth, the remaining blocks are given a majority selection, the color temperature having the most blocks are considered as the color temperature of the light source. Experimental results show that the proposed method works well for most commonly used light sources. The color casts are removed and the final images look natural.

Estimation of minimum ventilation requirement of dairy cattle barns for different outdoor temperature and its affects on indoor temperature: Bursa case.

PubMed

Yaslioglu, Erkan; Simsek, Ercan; Kilic, Ilker

2007-04-15

In the study, 10 different dairy cattle barns with natural ventilation system were investigated in terms of structural aspects. VENTGRAPH software package was used to estimate minimum ventilation requirements for three different outdoor design temperatures (-3, 0 and 1.7 degrees C). Variation in indoor temperatures was also determined according to the above-mentioned conditions. In the investigated dairy cattle barns, on condition that minimum ventilation requirement to be achieved for -3, 0 and 1.7 degrees C outdoor design temperature and 70, 80% Indoor Relative Humidity (IRH), estimated indoor temperature were ranged from 2.2 to 12.2 degrees C for 70% IRH, 4.3 to 15.0 degrees C for 80% IRH. Barn type, outdoor design temperature and indoor relative humidity significantly (p < 0.01) affect the indoor temperature. The highest ventilation requirement was calculated for straw yard (13879 m3 h(-1)) while the lowest was estimated for tie-stall (6169.20 m3 h(-1)). Estimated minimum ventilation requirements per animal were significantly (p < 0.01) different according to the barn types. Effect of outdoor esign temperatures on minimum ventilation requirements and minimum ventilation requirements per animal was found to be significant (p < 0.05, p < 0.01). Estimated indoor temperatures were in thermoneutral zone (-2 to 20 degrees C). Therefore, one can be said that use of naturally ventilated cold dairy barns in the region will not lead to problems associated with animal comfort in winter.

Surface Temperature Data Analysis

NASA Technical Reports Server (NTRS)

Hansen, James; Ruedy, Reto

2012-01-01

Small global mean temperature changes may have significant to disastrous consequences for the Earth's climate if they persist for an extended period. Obtaining global means from local weather reports is hampered by the uneven spatial distribution of the reliably reporting weather stations. Methods had to be developed that minimize as far as possible the impact of that situation. This software is a method of combining temperature data of individual stations to obtain a global mean trend, overcoming/estimating the uncertainty introduced by the spatial and temporal gaps in the available data. Useful estimates were obtained by the introduction of a special grid, subdividing the Earth's surface into 8,000 equal-area boxes, using the existing data to create virtual stations at the center of each of these boxes, and combining temperature anomalies (after assessing the radius of high correlation) rather than temperatures.

Maximum likelihood estimation for predicting the probability of obtaining variable shortleaf pine regeneration densities

Treesearch

Thomas B. Lynch; Jean Nkouka; Michael M. Huebschmann; James M. Guldin

2003-01-01

A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (...

Comparison of dew point temperature estimation methods in Southwestern Georgia

Treesearch

Marcus D. Williams; Scott L. Goodrick; Andrew Grundstein; Marshall Shepherd

2015-01-01

Recent upward trends in acres irrigated have been linked to increasing near-surface moisture. Unfortunately, stations with dew point data for monitoring near-surface moisture are sparse. Thus, models that estimate dew points from more readily observed data sources are useful. Daily average dew temperatures were estimated and evaluated at 14 stations in...

Vicarious Calibration of sUAS Microbolometer Temperature Imagery for Estimation of Radiometric Land Surface Temperature.

PubMed

Torres-Rua, Alfonso

2017-06-26

In recent years, the availability of lightweight microbolometer thermal cameras compatible with small unmanned aerial systems (sUAS) has allowed their use in diverse scientific and management activities that require sub-meter pixel resolution. Nevertheless, as with sensors already used in temperature remote sensing (e.g., Landsat satellites), a radiance atmospheric correction is necessary to estimate land surface temperature. This is because atmospheric conditions at any sUAS flight elevation will have an adverse impact on the image accuracy, derived calculations, and study replicability using the microbolometer technology. This study presents a vicarious calibration methodology (sUAS-specific, time-specific, flight-specific, and sensor-specific) for sUAS temperature imagery traceable back to NIST-standards and current atmospheric correction methods. For this methodology, a three-year data collection campaign with a sUAS called "AggieAir", developed at Utah State University, was performed for vineyards near Lodi, California, for flights conducted at different times (early morning, Landsat overpass, and mid-afternoon") and seasonal conditions. From the results of this study, it was found that, despite the spectral response of microbolometer cameras (7.0 to 14.0 μm), it was possible to account for the effects of atmospheric and sUAS operational conditions, regardless of time and weather, to acquire accurate surface temperature data. In addition, it was found that the main atmospheric correction parameters (transmissivity and atmospheric radiance) significantly varied over the course of a day. These parameters fluctuated the most in early morning and partially stabilized in Landsat overpass and in mid-afternoon times. In terms of accuracy, estimated atmospheric correction parameters presented adequate statistics (confidence bounds under ±0.1 for transmissivity and ±1.2 W/m²/sr/um for atmospheric radiance, with a range of RMSE below 1.0 W/m²/sr/um) for all s

Vicarious Calibration of sUAS Microbolometer Temperature Imagery for Estimation of Radiometric Land Surface Temperature

PubMed Central

2017-01-01

In recent years, the availability of lightweight microbolometer thermal cameras compatible with small unmanned aerial systems (sUAS) has allowed their use in diverse scientific and management activities that require sub-meter pixel resolution. Nevertheless, as with sensors already used in temperature remote sensing (e.g., Landsat satellites), a radiance atmospheric correction is necessary to estimate land surface temperature. This is because atmospheric conditions at any sUAS flight elevation will have an adverse impact on the image accuracy, derived calculations, and study replicability using the microbolometer technology. This study presents a vicarious calibration methodology (sUAS-specific, time-specific, flight-specific, and sensor-specific) for sUAS temperature imagery traceable back to NIST-standards and current atmospheric correction methods. For this methodology, a three-year data collection campaign with a sUAS called “AggieAir”, developed at Utah State University, was performed for vineyards near Lodi, California, for flights conducted at different times (early morning, Landsat overpass, and mid-afternoon”) and seasonal conditions. From the results of this study, it was found that, despite the spectral response of microbolometer cameras (7.0 to 14.0 μm), it was possible to account for the effects of atmospheric and sUAS operational conditions, regardless of time and weather, to acquire accurate surface temperature data. In addition, it was found that the main atmospheric correction parameters (transmissivity and atmospheric radiance) significantly varied over the course of a day. These parameters fluctuated the most in early morning and partially stabilized in Landsat overpass and in mid-afternoon times. In terms of accuracy, estimated atmospheric correction parameters presented adequate statistics (confidence bounds under ±0.1 for transmissivity and ±1.2 W/m2/sr/um for atmospheric radiance, with a range of RMSE below 1.0 W/m2/sr/um) for all s

Estimated effects of temperature on secondary organic aerosol concentrations.

PubMed

Sheehan, P E; Bowman, F M

2001-06-01

The temperature-dependence of secondary organic aerosol (SOA) concentrations is explored using an absorptive-partitioning model under a variety of simplified atmospheric conditions. Experimentally determined partitioning parameters for high yield aromatics are used. Variation of vapor pressures with temperature is assumed to be the main source of temperature effects. Known semivolatile products are used to define a modeling range of vaporization enthalpy of 10-25 kcal/mol-1. The effect of diurnal temperature variations on model predictions for various assumed vaporization enthalpies, precursor emission rates, and primary organic concentrations is explored. Results show that temperature is likely to have a significant influence on SOA partitioning and resulting SOA concentrations. A 10 degrees C decrease in temperature is estimated to increase SOA yields by 20-150%, depending on the assumed vaporization enthalpy. In model simulations, high daytime temperatures tend to reduce SOA concentrations by 16-24%, while cooler nighttime temperatures lead to a 22-34% increase, compared to constant temperature conditions. Results suggest that currently available constant temperature partitioning coefficients do not adequately represent atmospheric SOA partitioning behavior. Air quality models neglecting the temperature dependence of partitioning are expected to underpredict peak SOA concentrations as well as mistime their occurrence.

Obtaining Cue Rate Estimates for Some Mysticete Species using Existing Data

DTIC Science & Technology

2014-09-30

primary focus is to obtain cue rates for humpback whales (Megaptera novaeangliae) off the California coast and on the PMRF range. To our knowledge, no... humpback whale cue rates have been calculated for these populations. Once a cue rate is estimated for the populations of humpback whales off the...rates for humpback whales on breeding grounds, in addition to average cue rates for other species of mysticete whales . Cue rates of several other

Reliability of fish size estimates obtained from multibeam imaging sonar

USGS Publications Warehouse

Hightower, Joseph E.; Magowan, Kevin J.; Brown, Lori M.; Fox, Dewayne A.

2013-01-01

Multibeam imaging sonars have considerable potential for use in fisheries surveys because the video-like images are easy to interpret, and they contain information about fish size, shape, and swimming behavior, as well as characteristics of occupied habitats. We examined images obtained using a dual-frequency identification sonar (DIDSON) multibeam sonar for Atlantic sturgeon Acipenser oxyrinchus oxyrinchus, striped bass Morone saxatilis, white perch M. americana, and channel catfish Ictalurus punctatus of known size (20–141 cm) to determine the reliability of length estimates. For ranges up to 11 m, percent measurement error (sonar estimate – total length)/total length × 100 varied by species but was not related to the fish's range or aspect angle (orientation relative to the sonar beam). Least-square mean percent error was significantly different from 0.0 for Atlantic sturgeon (x̄  =  −8.34, SE  =  2.39) and white perch (x̄  = 14.48, SE  =  3.99) but not striped bass (x̄  =  3.71, SE  =  2.58) or channel catfish (x̄  = 3.97, SE  =  5.16). Underestimating lengths of Atlantic sturgeon may be due to difficulty in detecting the snout or the longer dorsal lobe of the heterocercal tail. White perch was the smallest species tested, and it had the largest percent measurement errors (both positive and negative) and the lowest percentage of images classified as good or acceptable. Automated length estimates for the four species using Echoview software varied with position in the view-field. Estimates tended to be low at more extreme azimuthal angles (fish's angle off-axis within the view-field), but mean and maximum estimates were highly correlated with total length. Software estimates also were biased by fish images partially outside the view-field and when acoustic crosstalk occurred (when a fish perpendicular to the sonar and at relatively close range is detected in the side lobes of adjacent beams). These sources of

Estimation of dew point temperature using neuro-fuzzy and neural network techniques

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Kim, Sungwon; Shiri, Jalal

2013-11-01

This study investigates the ability of two different artificial neural network (ANN) models, generalized regression neural networks model (GRNNM) and Kohonen self-organizing feature maps neural networks model (KSOFM), and two different adaptive neural fuzzy inference system (ANFIS) models, ANFIS model with sub-clustering identification (ANFIS-SC) and ANFIS model with grid partitioning identification (ANFIS-GP), for estimating daily dew point temperature. The climatic data that consisted of 8 years of daily records of air temperature, sunshine hours, wind speed, saturation vapor pressure, relative humidity, and dew point temperature from three weather stations, Daego, Pohang, and Ulsan, in South Korea were used in the study. The estimates of ANN and ANFIS models were compared according to the three different statistics, root mean square errors, mean absolute errors, and determination coefficient. Comparison results revealed that the ANFIS-SC, ANFIS-GP, and GRNNM models showed almost the same accuracy and they performed better than the KSOFM model. Results also indicated that the sunshine hours, wind speed, and saturation vapor pressure have little effect on dew point temperature. It was found that the dew point temperature could be successfully estimated by using T mean and R H variables.

Estimation of surface temperature in remote pollution measurement experiments

NASA Technical Reports Server (NTRS)

Gupta, S. K.; Tiwari, S. N.

1978-01-01

A simple algorithm has been developed for estimating the actual surface temperature by applying corrections to the effective brightness temperature measured by radiometers mounted on remote sensing platforms. Corrections to effective brightness temperature are computed using an accurate radiative transfer model for the 'basic atmosphere' and several modifications of this caused by deviations of the various atmospheric and surface parameters from their base model values. Model calculations are employed to establish simple analytical relations between the deviations of these parameters and the additional temperature corrections required to compensate for them. Effects of simultaneous variation of two parameters are also examined. Use of these analytical relations instead of detailed radiative transfer calculations for routine data analysis results in a severalfold reduction in computation costs.

Estimation of Transformation Temperatures in Ti-Ni-Pd Shape Memory Alloys

NASA Astrophysics Data System (ADS)

Narayana, P. L.; Kim, Seong-Woong; Hong, Jae-Keun; Reddy, N. S.; Yeom, Jong-Taek

2018-03-01

The present study focused on estimating the complex nonlinear relationship between the composition and phase transformation temperatures of Ti-Ni-Pd shape memory alloys by artificial neural networks (ANN). The ANN models were developed by using the experimental data of Ti-Ni-Pd alloys. It was found that the predictions are in good agreement with the trained and unseen test data of existing alloys. The developed model was able to simulate new virtual alloys to quantitatively estimate the effect of Ti, Ni, and Pd on transformation temperatures. The transformation temperature behavior of these virtual alloys is validated by conducting new experiments on the Ti-rich thin film that was deposited using multi target sputtering equipment. The transformation behavior of the film was measured by varying the composition with the help of aging treatment. The predicted trend of transformational temperatures was explained with the help of experimental results.

All-weather Land Surface Temperature Estimation from Satellite Data

NASA Astrophysics Data System (ADS)

Zhou, J.; Zhang, X.

2017-12-01

Satellite remote sensing, including the thermal infrared (TIR) and passive microwave (MW), provides the possibility to observe LST at large scales. For better modeling the land surface processes with high temporal resolutions, all-weather LST from satellite data is desirable. However, estimation of all-weather LST faces great challenges. On the one hand, TIR remote sensing is limited to clear-sky situations; this drawback reduces its usefulness under cloudy conditions considerably, especially in regions with frequent and/or permanent clouds. On the other hand, MW remote sensing suffers from much greater thermal sampling depth (TSD) and coarser spatial resolution than TIR; thus, MW LST is generally lower than TIR LST, especially at daytime. Two case studies addressing the challenges mentioned previously are presented here. The first study is for the development of a novel thermal sampling depth correction method (TSDC) to estimate the MW LST over barren land; this second study is for the development of a feasible method to merge the TIR and MW LSTs by addressing the coarse resolution of the latter one. In the first study, the core of the TSDC method is a new formulation of the passive microwave radiation balance equation, which allows linking bulk MW radiation to the soil temperature at a specific depth, i.e. the representative temperature: this temperature is then converted to LST through an adapted soil heat conduction equation. The TSDC method is applied to the 6.9 GHz channel in vertical polarization of AMSR-E. Evaluation shows that LST estimated by the TSDC method agrees well with the MODIS LST. Validation is based on in-situ LSTs measured at the Gobabeb site in western Namibia. The results demonstrate the high accuracy of the TSDC method: it yields a root-mean squared error (RMSE) of 2 K and ignorable systematic error over barren land. In the second study, the method consists of two core processes: (1) estimation of MW LST from MW brightness temperature and (2

Volcanic explosion clouds - Density, temperature, and particle content estimates from cloud motion

NASA Technical Reports Server (NTRS)

Wilson, L.; Self, S.

1980-01-01

Photographic records of 10 vulcanian eruption clouds produced during the 1978 eruption of Fuego Volcano in Guatemala have been analyzed to determine cloud velocity and acceleration at successive stages of expansion. Cloud motion is controlled by air drag (dominant during early, high-speed motion) and buoyancy (dominant during late motion when the cloud is convecting slowly). Cloud densities in the range 0.6 to 1.2 times that of the surrounding atmosphere were obtained by fitting equations of motion for two common cloud shapes (spheres and vertical cylinders) to the observed motions. Analysis of the heat budget of a cloud permits an estimate of cloud temperature and particle weight fraction to be made from the density. Model results suggest that clouds generally reached temperatures within 10 K of that of the surrounding air within 10 seconds of formation and that dense particle weight fractions were less than 2% by this time. The maximum sizes of dense particles supported by motion in the convecting clouds range from 140 to 1700 microns.

A fully redundant double difference algorithm for obtaining minimum variance estimates from GPS observations

NASA Technical Reports Server (NTRS)

Melbourne, William G.

1986-01-01

In double differencing a regression system obtained from concurrent Global Positioning System (GPS) observation sequences, one either undersamples the system to avoid introducing colored measurement statistics, or one fully samples the system incurring the resulting non-diagonal covariance matrix for the differenced measurement errors. A suboptimal estimation result will be obtained in the undersampling case and will also be obtained in the fully sampled case unless the color noise statistics are taken into account. The latter approach requires a least squares weighting matrix derived from inversion of a non-diagonal covariance matrix for the differenced measurement errors instead of inversion of the customary diagonal one associated with white noise processes. Presented is the so-called fully redundant double differencing algorithm for generating a weighted double differenced regression system that yields equivalent estimation results, but features for certain cases a diagonal weighting matrix even though the differenced measurement error statistics are highly colored.

A soft-computing methodology for noninvasive time-spatial temperature estimation.

PubMed

Teixeira, César A; Ruano, Maria Graça; Ruano, António E; Pereira, Wagner C A

2008-02-01

The safe and effective application of thermal therapies is restricted due to lack of reliable noninvasive temperature estimators. In this paper, the temporal echo-shifts of backscattered ultrasound signals, collected from a gel-based phantom, were tracked and assigned with the past temperature values as radial basis functions neural networks input information. The phantom was heated using a piston-like therapeutic ultrasound transducer. The neural models were assigned to estimate the temperature at different intensities and points arranged across the therapeutic transducer radial line (60 mm apart from the transducer face). Model inputs, as well as the number of neurons were selected using the multiobjective genetic algorithm (MOGA). The best attained models present, in average, a maximum absolute error less than 0.5 degrees C, which is pointed as the borderline between a reliable and an unreliable estimator in hyperthermia/diathermia. In order to test the spatial generalization capacity, the best models were tested using spatial points not yet assessed, and some of them presented a maximum absolute error inferior to 0.5 degrees C, being "elected" as the best models. It should be also stressed that these best models present implementational low-complexity, as desired for real-time applications.

Estimation of Surface Air Temperature Over Central and Eastern Eurasia from MODIS Land Surface Temperature

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.

2011-01-01

Surface air temperature (T(sub a)) is a critical variable in the energy and water cycle of the Earth.atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T(sub a) from satellite remotely sensed land surface temperature (T(sub s)) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T(sub a) and MODIS T(sub s). The relationships between the maximum T(sub a) and daytime T(sub s) depend significantly on land cover types, but the minimum T(sub a) and nighttime T(sub s) have little dependence on the land cover types. The largest difference between maximum T(sub a) and daytime T(sub s) appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T(sub a) were estimated from 1 km resolution MODIS T(sub s) under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T(sub a) were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T(sub a) varies from 2.4 C over closed shrublands to 3.2 C over grasslands, and the MAE of the estimated minimum Ta is about 3.0 C.

Comparison of estimated core body temperature measured with the BioHarness and rectal temperature under several heat stress conditions.

PubMed

Seo, Yongsuk; DiLeo, Travis; Powell, Jeffrey B; Kim, Jung-Hyun; Roberge, Raymond J; Coca, Aitor

2016-08-01

Monitoring and measuring core body temperature is important to prevent or minimize physiological strain and cognitive dysfunction for workers such as first responders (e.g., firefighters) and military personnel. The purpose of this study is to compare estimated core body temperature (Tco-est), determined by heart rate (HR) data from a wearable chest strap physiology monitor, to standard rectal thermometry (Tre) under different conditions.  Tco-est and Tre measurements were obtained in thermoneutral and heat stress conditions (high temperature and relative humidity) during four different experiments including treadmill exercise, cycling exercise, passive heat stress, and treadmill exercise while wearing personal protective equipment (PPE).  Overall, the mean Tco-est did not differ significantly from Tre across the four conditions. During exercise at low-moderate work rates under heat stress conditions, Tco-est was consistently higher than Tre at all-time points. Tco-est underestimated temperature compared to Tre at rest in heat stress conditions and at a low work rate under heat stress while wearing PPE. The mean differences between the two measurements ranged from -0.1 ± 0.4 to 0.3 ± 0.4°C and Tco-est correlated well with HR (r = 0.795 - 0.849) and mean body temperature (r = 0.637 - 0.861).  These results indicate that, the comparison of Tco-est to Tre may result in over- or underestimation which could possibly lead to heat-related illness during monitoring in certain conditions. Modifications to the current algorithm should be considered to address such issues.

Mesospheric temperatures estimated from the meteor radar observations at Mohe, China

NASA Astrophysics Data System (ADS)

Liu, Libo; Liu, Huixin; Le, Huijun; Chen, Yiding; Sun, Yang-Yi; Ning, Baiqi; Hu, Lianhuan; Wan, Weixing; Li, Na; Xiong, Jiangang

2017-02-01

In this work, we report the estimation of mesospheric temperatures at 90 km height from the observations of the VHF all-sky meteor radar operated at Mohe (53.5°N, 122.3°E), China, since August 2011. The kinetic temperature profiles retrieved from the observations of Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) on board the Thermosphere, Ionosphere, Mesosphere, Energetics, and Dynamics satellite are processed to provide the temperature (TSABER) and temperature gradient (dT/dh) at 90 km height. Based on the SABER temperature profile data an empirical dT/dh model is developed for the Mohe latitude. First, we derive the temperatures from the meteor decay times (Tmeteor) and the Mohe dT/dh model gives prior information of temperature gradients. Second, the full width at half maximum (FWHM) of the meteor height profiles is calculated and further used to deduce the temperatures (TFWHM) based on the strong linear relationship between FWHM and TSABER. The temperatures at 90 km deduced from the decay times (Tmeteor) and from the meteor height distributions (TFWHM) at Mohe are validated/calibrated with TSABER. The temperatures present a considerable annual variation, being maximum in winter and minimum in summer. Harmonic analyses reveal that the temperatures have an annual variation consistent with TSABER. Our work suggests that FWHM has a good performance in routine estimation of the temperatures. It should be pointed out that the slope of FWHM as a function of TSABER is 10.1 at Mohe, which is different from that of 15.71 at King Sejong (62.2°S, 58.8°E) station.

Comparison of Temperature Measurements in the Middle Atmosphere by Satellite with Profiles Obtained by Meteorological Rockets

NASA Technical Reports Server (NTRS)

Goldberg, Richard A.; Schmidlin, Francis J.; Feofilov, Artem; Bedrick, M.; Rose, R. Lynn

2012-01-01

Measurements using the inflatable falling sphere technique have occasionally been used to obtain temperature results from density data and thereby provide comparison with temperature profiles obtained by satellite sounders in the mesosphere and stratosphere. To insure density measurements within narrow time frames and close in space, the inflatable falling sphere is launched within seconds of the nearly overhead satellite pass. Sphere measurements can be used to validate remotely measured temperatures but also have the advantage of measuring small-scale atmospheric features. Even so, with the dearth of remaining falling spheres available (the manufacture of these systems has been discontinued), it may be time to consider whether the remote measurements are mature enough to stand alone. Three field studies are considered, one in 2003 from Northern Sweden, and two in 2010 from the vicinity of Kwajalein Atoll in the South Pacific and from Barking Sands, Hawaii. All three sites are used to compare temperature retrievals between satellite and in situ falling spheres. The major satellite instruments employed are SABER, MLS, and AIRS. The comparisons indicate that remotely measured temperatures mimic the sphere temperature measurements quite well. The data also confirm that satellite retrievals, while not always at the exact location required for detailed studies in space and time, compare sufficiently well to be highly useful. Although the falling sphere will provide a measurement at a specific location and time, satellites only pass a given location daily or less frequently. This report reveals that averaged satellite measurements can provide temperatures and densities comparable to those obtained from the falling sphere, thereby providing a reliable measure of global temperature

Temperature-based estimation of global solar radiation using soft computing methodologies

NASA Astrophysics Data System (ADS)

Mohammadi, Kasra; Shamshirband, Shahaboddin; Danesh, Amir Seyed; Abdullah, Mohd Shahidan; Zamani, Mazdak

2016-07-01

Precise knowledge of solar radiation is indeed essential in different technological and scientific applications of solar energy. Temperature-based estimation of global solar radiation would be appealing owing to broad availability of measured air temperatures. In this study, the potentials of soft computing techniques are evaluated to estimate daily horizontal global solar radiation (DHGSR) from measured maximum, minimum, and average air temperatures ( T max, T min, and T avg) in an Iranian city. For this purpose, a comparative evaluation between three methodologies of adaptive neuro-fuzzy inference system (ANFIS), radial basis function support vector regression (SVR-rbf), and polynomial basis function support vector regression (SVR-poly) is performed. Five combinations of T max, T min, and T avg are served as inputs to develop ANFIS, SVR-rbf, and SVR-poly models. The attained results show that all ANFIS, SVR-rbf, and SVR-poly models provide favorable accuracy. Based upon all techniques, the higher accuracies are achieved by models (5) using T max- T min and T max as inputs. According to the statistical results, SVR-rbf outperforms SVR-poly and ANFIS. For SVR-rbf (5), the mean absolute bias error, root mean square error, and correlation coefficient are 1.1931 MJ/m2, 2.0716 MJ/m2, and 0.9380, respectively. The survey results approve that SVR-rbf can be used efficiently to estimate DHGSR from air temperatures.

Rock magnetic properties estimated from coercivity - blocking temperature diagram: application to recent volcanic rocks

NASA Astrophysics Data System (ADS)

Terada, T.; Sato, M.; Mochizuki, N.; Yamamoto, Y.; Tsunakawa, H.

2013-12-01

-Tb diagram. The curves are calculated using the single domain theory, since coercivity and blocking temperature of uniaxial SD grains can be expressed as a function of size and shape. (2) Boundary between SD and MD grains are calculated and drawn on the Hc-Tb diagram according to the theory by Butler and Banerjee (1975). (3) Theoretical predictions by (1) and (2) are compared with the obtained ARM spectra to estimate quantitive distribution of size, shape and domain state of magnetic grains in the sample. This mapping method has been applied to three samples: Hawaiian basaltic lava extruded in 1995, Ueno basaltic lava formed during Matsuyama chron, and Oshima basaltic lava extruded in 1986. We will discuss physical states of magnetic grains (size, shape, domain state, etc.) and their possible origins.

Estimate of subsurface formation temperature in the Tarim basin, northwest China

NASA Astrophysics Data System (ADS)

Liu, Shaowen; Lei, Xiao; Feng, Changge; Hao, Chunyan

2015-04-01

Subsurface formation temperature in the Tarim basin, the largest sedimentary basin in China, is significant for its hydrocarbon generation, preservation and geothermal energy potential assessment, but till now is not well understood, due to poor data coverage and a lack of highly accurate temperature data. Here, we combined recently acquired steady-state temperature logging data, drill stem test temperature data and measured rock thermal properties, to investigate the geothermal regime, and estimate the formation temperature at specific depths in the range 1000~5000 m in this basin. Results show that the heat flow of the Tarim basin ranges between 26.2 and 66.1 mW/m2, with a mean of 42.5±7.6 mW/m2; geothermal gradient at the depth of 3000 m varies from 14.9 to 30.2 °C/km, with a mean of 20.7±2.9 °C/km. Formation temperature at the depth of 1000 m is estimated to be between 29 °C and 41°C, with a mean of 35°C; whilst the temperature at 2000 m ranges from 46~71°C with an average of 59°C; 63~100°C is for that at the depth of 3000 m, and the mean is 82°C; the temperature at 4000 m varies from 80 to 130°C, with a mean of 105°C; 97~160°C is for the temperature at 5000 m depth. In addition, the general pattern of the subsurface formation temperatures at different depths is basically similar and is characterized by high temperatures in the uplift areas and low temperatures in the sags. Basement structure and lateral variations in thermal properties account for this pattern of the geo-temperature field in the Tarim basin.

Temperature estimation from molecular nitrogen UV spectra in atmospheric pressure plasmas

NASA Astrophysics Data System (ADS)

Pepper, Keenan; Kim, Yongho; Kim, Jihun

2008-11-01

Atmospheric pressure plasmas have many potential applications to fuel processing, surface treatment, and manipulation of chemical reactions. These plasmas are often non-thermal, which means different species are not in equilibrium and have different effective temperatures. This is critical for many applications because it allows high concentrations of reactive species to be produced without using a prohibitive amount of power. In the present work, numerical software was developed to estimate the vibrational and rotational temperatures (Tvib and Trot) of N2 molecules from their ultraviolet emission spectra. The electron temperature Te can also be estimated by comparing the N2 spectrum to that of the N2^+ molecular ion. This technique is applied to several plasma sources including audio frequency, RF, and microwave devices. The results are presented and their implications for practical applications are discussed.

Re-estimating temperature-dependent consumption parameters in bioenergetics models for juvenile Chinook salmon

USGS Publications Warehouse

Plumb, John M.; Moffitt, Christine M.

2015-01-01

Researchers have cautioned against the borrowing of consumption and growth parameters from other species and life stages in bioenergetics growth models. In particular, the function that dictates temperature dependence in maximum consumption (Cmax) within the Wisconsin bioenergetics model for Chinook Salmon Oncorhynchus tshawytscha produces estimates that are lower than those measured in published laboratory feeding trials. We used published and unpublished data from laboratory feeding trials with subyearling Chinook Salmon from three stocks (Snake, Nechako, and Big Qualicum rivers) to estimate and adjust the model parameters for temperature dependence in Cmax. The data included growth measures in fish ranging from 1.5 to 7.2 g that were held at temperatures from 14°C to 26°C. Parameters for temperature dependence in Cmax were estimated based on relative differences in food consumption, and bootstrapping techniques were then used to estimate the error about the parameters. We found that at temperatures between 17°C and 25°C, the current parameter values did not match the observed data, indicating that Cmax should be shifted by about 4°C relative to the current implementation under the bioenergetics model. We conclude that the adjusted parameters for Cmax should produce more accurate predictions from the bioenergetics model for subyearling Chinook Salmon.

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

USGS Publications Warehouse

Flint, L.E.; Flint, A.L.

2008-01-01

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 ?? 0.6??C at the 95% confidence interval. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Temperature-profile methods for estimating percolation rates in arid environments

USGS Publications Warehouse

Constantz, Jim; Tyler, Scott W.; Kwicklis, Edward

2003-01-01

Percolation rates are estimated using vertical temperature profiles from sequentially deeper vadose environments, progressing from sediments beneath stream channels, to expansive basin-fill materials, and finally to deep fractured bedrock underlying mountainous terrain. Beneath stream channels, vertical temperature profiles vary over time in response to downward heat transport, which is generally controlled by conductive heat transport during dry periods, or by advective transport during channel infiltration. During periods of stream-channel infiltration, two relatively simple approaches are possible: a heat-pulse technique, or a heat and liquid-water transport simulation code. Focused percolation rates beneath stream channels are examined for perennial, seasonal, and ephemeral channels in central New Mexico, with estimated percolation rates ranging from 100 to 2100 mm d−1 Deep within basin-fill and underlying mountainous terrain, vertical temperature gradients are dominated by the local geothermal gradient, which creates a profile with decreasing temperatures toward the surface. If simplifying assumptions are employed regarding stratigraphy and vapor fluxes, an analytical solution to the heat transport problem can be used to generate temperature profiles at specified percolation rates for comparison to the observed geothermal gradient. Comparisons to an observed temperature profile in the basin-fill sediments beneath Frenchman Flat, Nevada, yielded water fluxes near zero, with absolute values <10 mm yr−1 For the deep vadose environment beneath Yucca Mountain, Nevada, the complexities of stratigraphy and vapor movement are incorporated into a more elaborate heat and water transport model to compare simulated and observed temperature profiles for a pair of deep boreholes. Best matches resulted in a percolation rate near zero for one borehole and 11 mm yr−1 for the second borehole.

Use of NMR logging to obtain estimates of hydraulic conductivity in the High Plains aquifer, Nebraska, USA

USGS Publications Warehouse

Dlubac, Katherine; Knight, Rosemary; Song, Yi-Qiao; Bachman, Nate; Grau, Ben; Cannia, Jim; Williams, John

2013-01-01

Hydraulic conductivity (K) is one of the most important parameters of interest in groundwater applications because it quantifies the ease with which water can flow through an aquifer material. Hydraulic conductivity is typically measured by conducting aquifer tests or wellbore flow (WBF) logging. Of interest in our research is the use of proton nuclear magnetic resonance (NMR) logging to obtain information about water-filled porosity and pore space geometry, the combination of which can be used to estimate K. In this study, we acquired a suite of advanced geophysical logs, aquifer tests, WBF logs, and sidewall cores at the field site in Lexington, Nebraska, which is underlain by the High Plains aquifer. We first used two empirical equations developed for petroleum applications to predict K from NMR logging data: the Schlumberger Doll Research equation (KSDR) and the Timur-Coates equation (KT-C), with the standard empirical constants determined for consolidated materials. We upscaled our NMR-derived K estimates to the scale of the WBF-logging K(KWBF-logging) estimates for comparison. All the upscaled KT-C estimates were within an order of magnitude of KWBF-logging and all of the upscaled KSDR estimates were within 2 orders of magnitude of KWBF-logging. We optimized the fit between the upscaled NMR-derived K and KWBF-logging estimates to determine a set of site-specific empirical constants for the unconsolidated materials at our field site. We conclude that reliable estimates of K can be obtained from NMR logging data, thus providing an alternate method for obtaining estimates of K at high levels of vertical resolution.

Statistical evaluation of accelerated stability data obtained at a single temperature. I. Effect of experimental errors in evaluation of stability data obtained.

PubMed

Yoshioka, S; Aso, Y; Takeda, Y

1990-06-01

Accelerated stability data obtained at a single temperature is statistically evaluated, and the utility of such data for assessment of stability is discussed focussing on the chemical stability of solution-state dosage forms. The probability that the drug content of a product is observed to be within the lower specification limit in the accelerated test is interpreted graphically. This probability depends on experimental errors in the assay and temperature control, as well as the true degradation rate and activation energy. Therefore, the observation that the drug content meets the specification in the accelerated testing can provide only limited information on the shelf-life of the drug, without the knowledge of the activation energy and the accuracy and precision of the assay and temperature control.

Rectal temperature-based death time estimation in infants.

PubMed

Igari, Yui; Hosokai, Yoshiyuki; Funayama, Masato

2016-03-01

In determining the time of death in infants based on rectal temperature, the same methods used in adults are generally used. However, whether the methods for adults are suitable for infants is unclear. In this study, we examined the following 3 methods in 20 infant death cases: computer simulation of rectal temperature based on the infinite cylinder model (Ohno's method), computer-based double exponential approximation based on Marshall and Hoare's double exponential model with Henssge's parameter determination (Henssge's method), and computer-based collinear approximation based on extrapolation of the rectal temperature curve (collinear approximation). The interval between the last time the infant was seen alive and the time that he/she was found dead was defined as the death time interval and compared with the estimated time of death. In Ohno's method, 7 cases were within the death time interval, and the average deviation in the other 12 cases was approximately 80 min. The results of both Henssge's method and collinear approximation were apparently inferior to the results of Ohno's method. The corrective factor was set within the range of 0.7-1.3 in Henssge's method, and a modified program was newly developed to make it possible to change the corrective factors. Modification A, in which the upper limit of the corrective factor range was set as the maximum value in each body weight, produced the best results: 8 cases were within the death time interval, and the average deviation in the other 12 cases was approximately 80min. There was a possibility that the influence of thermal isolation on the actual infants was stronger than that previously shown by Henssge. We conclude that Ohno's method and Modification A are useful for death time estimation in infants. However, it is important to accept the estimated time of death with certain latitude considering other circumstances. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Ultrahigh Strength Copper Obtained by Surface Mechanical Attrition Treatment at Cryogenic Temperature

NASA Astrophysics Data System (ADS)

Shen, Yu; Wen, Cuie; Yang, Xincheng; Pang, Yanzhao; Sun, Lele; Tao, Jingmei; Gong, Yulan; Zhu, Xinkun

2015-12-01

The purpose of this paper is to investigate the effect of dynamic recovery on the mechanical properties of copper (Cu) during surface mechanical attrition treatment (SMAT) at both room temperature (RT) and cryogenic temperature (CT). Copper sheets were processed by SMAT at RT and at CT for 5, 15, and 30 min, respectively. The Cu samples after SMAT at RT for 30 min exhibited better ductility but lower strength than the samples after SMAT at CT for 30 min due to dynamic recovery. X-ray diffraction analysis indicated that decreasing temperature during SMAT led to an increase in the twin and dislocation densities. In addition, a thicker gradient structure layer with finer grains was obtained in the SMAT-processed Cu samples at CT than at RT. The results indicated that SMAT at CT can effectively suppress the occurring of dynamic recovery and produce ultrahigh strength pure copper without seriously sacrificing its ductility.

Nonlinear regression method for estimating neutral wind and temperature from Fabry-Perot interferometer data.

PubMed

Harding, Brian J; Gehrels, Thomas W; Makela, Jonathan J

2014-02-01

The Earth's thermosphere plays a critical role in driving electrodynamic processes in the ionosphere and in transferring solar energy to the atmosphere, yet measurements of thermospheric state parameters, such as wind and temperature, are sparse. One of the most popular techniques for measuring these parameters is to use a Fabry-Perot interferometer to monitor the Doppler width and breadth of naturally occurring airglow emissions in the thermosphere. In this work, we present a technique for estimating upper-atmospheric winds and temperatures from images of Fabry-Perot fringes captured by a CCD detector. We estimate instrument parameters from fringe patterns of a frequency-stabilized laser, and we use these parameters to estimate winds and temperatures from airglow fringe patterns. A unique feature of this technique is the model used for the laser and airglow fringe patterns, which fits all fringes simultaneously and attempts to model the effects of optical defects. This technique yields accurate estimates for winds, temperatures, and the associated uncertainties in these parameters, as we show with a Monte Carlo simulation.

Comparison of ArcGIS and SAS Geostatistical Analyst to Estimate Population-Weighted Monthly Temperature for US Counties.

PubMed

Xiaopeng, Q I; Liang, Wei; Barker, Laurie; Lekiachvili, Akaki; Xingyou, Zhang

Temperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature's association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly-or 30-day-basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R 2 , mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R 2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS's merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects.

Effects of measurement resolution on the analysis of temperature time series for stream-aquifer flux estimation

NASA Astrophysics Data System (ADS)

Soto-López, Carlos D.; Meixner, Thomas; Ferré, Ty P. A.

2011-12-01

From its inception in the mid-1960s, the use of temperature time series (thermographs) to estimate vertical fluxes has found increasing use in the hydrologic community. Beginning in 2000, researchers have examined the impacts of measurement and parameter uncertainty on the estimates of vertical fluxes. To date, the effects of temperature measurement discretization (resolution), a characteristic of all digital temperature loggers, on the determination of vertical fluxes has not been considered. In this technical note we expand the analysis of recently published work to include the effects of temperature measurement resolution on estimates of vertical fluxes using temperature amplitude and phase shift information. We show that errors in thermal front velocity estimation introduced by discretizing thermographs differ when amplitude or phase shift data are used to estimate vertical fluxes. We also show that under similar circumstances sensor resolution limits the range over which vertical velocities are accurately reproduced more than uncertainty in temperature measurements, uncertainty in sensor separation distance, and uncertainty in the thermal diffusivity combined. These effects represent the baseline error present and thus the best-case scenario when discrete temperature measurements are used to infer vertical fluxes. The errors associated with measurement resolution can be minimized by using the highest-resolution sensors available. But thoughtful experimental design could allow users to select the most cost-effective temperature sensors to fit their measurement needs.

Estimation of human core temperature from sequential heart rate observations.

PubMed

Buller, Mark J; Tharion, William J; Cheuvront, Samuel N; Montain, Scott J; Kenefick, Robert W; Castellani, John; Latzka, William A; Roberts, Warren S; Richter, Mark; Jenkins, Odest Chadwicke; Hoyt, Reed W

2013-07-01

Core temperature (CT) in combination with heart rate (HR) can be a good indicator of impending heat exhaustion for occupations involving exposure to heat, heavy workloads, and wearing protective clothing. However, continuously measuring CT in an ambulatory environment is difficult. To address this problem we developed a model to estimate the time course of CT using a series of HR measurements as a leading indicator using a Kalman filter. The model was trained using data from 17 volunteers engaged in a 24 h military field exercise (air temperatures 24-36 °C, and 42%-97% relative humidity and CTs ranging from 36.0-40.0 °C). Validation data from laboratory and field studies (N = 83) encompassing various combinations of temperature, hydration, clothing, and acclimation state were examined using the Bland-Altman limits of agreement (LoA) method. We found our model had an overall bias of -0.03 ± 0.32 °C and that 95% of all CT estimates fall within ±0.63 °C (>52 000 total observations). While the model for estimating CT is not a replacement for direct measurement of CT (literature comparisons of esophageal and rectal methods average LoAs of ±0.58 °C) our results suggest it is accurate enough to provide practical indication of thermal work strain for use in the work place.

A Useful Tool for Atmospheric Correction and Surface Temperature Estimation of Landsat Infrared Thermal Data

NASA Astrophysics Data System (ADS)

Rivalland, Vincent; Tardy, Benjamin; Huc, Mireille; Hagolle, Olivier; Marcq, Sébastien; Boulet, Gilles

2016-04-01

Land Surface temperature (LST) is a critical variable for studying the energy and water budgets at the Earth surface, and is a key component of many aspects of climate research and services. The Landsat program jointly carried out by NASA and USGS has been providing thermal infrared data for 40 years, but no associated LST product has been yet routinely proposed to community. To derive LST values, radiances measured at sensor-level need to be corrected for the atmospheric absorption, the atmospheric emission and the surface emissivity effect. Until now, existing LST products have been generated with multi channel methods such as the Temperature/Emissivity Separation (TES) adapted to ASTER data or the generalized split-window algorithm adapted to MODIS multispectral data. Those approaches are ill-adapted to the Landsat mono-window data specificity. The atmospheric correction methodology usually used for Landsat data requires detailed information about the state of the atmosphere. This information may be obtained from radio-sounding or model atmospheric reanalysis and is supplied to a radiative transfer model in order to estimate atmospheric parameters for a given coordinate. In this work, we present a new automatic tool dedicated to Landsat thermal data correction which improves the common atmospheric correction methodology by introducing the spatial dimension in the process. The python tool developed during this study, named LANDARTs for LANDsat Automatic Retrieval of surface Temperature, is fully automatic and provides atmospheric corrections for a whole Landsat tile. Vertical atmospheric conditions are downloaded from the ERA Interim dataset from ECMWF meteorological organization which provides them at 0.125 degrees resolution, at a global scale and with a 6-hour-time step. The atmospheric correction parameters are estimated on the atmospheric grid using the commercial software MODTRAN, then interpolated to 30m resolution. We detail the processing steps

Semi-empirical estimation of organic compound fugacity ratios at environmentally relevant system temperatures.

PubMed

van Noort, Paul C M

2009-06-01

Fugacity ratios of organic compounds are used to calculate (subcooled) liquid properties, such as solubility or vapour pressure, from solid properties and vice versa. They can be calculated from the entropy of fusion, the melting temperature, and heat capacity data for the solid and the liquid. For many organic compounds, values for the fusion entropy are lacking. Heat capacity data are even scarcer. In the present study, semi-empirical compound class specific equations were derived to estimate fugacity ratios from molecular weight and melting temperature for polycyclic aromatic hydrocarbons and polychlorinated benzenes, biphenyls, dibenzo[p]dioxins and dibenzofurans. These equations estimate fugacity ratios with an average standard error of about 0.05 log units. In addition, for compounds with known fusion entropy values, a general semi-empirical correction equation based on molecular weight and melting temperature was derived for estimation of the contribution of heat capacity differences to the fugacity ratio. This equation estimates the heat capacity contribution correction factor with an average standard error of 0.02 log units for polycyclic aromatic hydrocarbons, polychlorinated benzenes, biphenyls, dibenzo[p]dioxins and dibenzofurans.

A Probabilistic Model for Estimating the Depth and Threshold Temperature of C-fiber Nociceptors

PubMed Central

Dezhdar, Tara; Moshourab, Rabih A.; Fründ, Ingo; Lewin, Gary R.; Schmuker, Michael

2015-01-01

The subjective experience of thermal pain follows the detection and encoding of noxious stimuli by primary afferent neurons called nociceptors. However, nociceptor morphology has been hard to access and the mechanisms of signal transduction remain unresolved. In order to understand how heat transducers in nociceptors are activated in vivo, it is important to estimate the temperatures that directly activate the skin-embedded nociceptor membrane. Hence, the nociceptor’s temperature threshold must be estimated, which in turn will depend on the depth at which transduction happens in the skin. Since the temperature at the receptor cannot be accessed experimentally, such an estimation can currently only be achieved through modeling. However, the current state-of-the-art model to estimate temperature at the receptor suffers from the fact that it cannot account for the natural stochastic variability of neuronal responses. We improve this model using a probabilistic approach which accounts for uncertainties and potential noise in system. Using a data set of 24 C-fibers recorded in vitro, we show that, even without detailed knowledge of the bio-thermal properties of the system, the probabilistic model that we propose here is capable of providing estimates of threshold and depth in cases where the classical method fails. PMID:26638830

Estimating stellar effective temperatures and detected angular parameters using stochastic particle swarm optimization

NASA Astrophysics Data System (ADS)

Zhang, Chuan-Xin; Yuan, Yuan; Zhang, Hao-Wei; Shuai, Yong; Tan, He-Ping

2016-09-01

Considering features of stellar spectral radiation and sky surveys, we established a computational model for stellar effective temperatures, detected angular parameters and gray rates. Using known stellar flux data in some bands, we estimated stellar effective temperatures and detected angular parameters using stochastic particle swarm optimization (SPSO). We first verified the reliability of SPSO, and then determined reasonable parameters that produced highly accurate estimates under certain gray deviation levels. Finally, we calculated 177 860 stellar effective temperatures and detected angular parameters using data from the Midcourse Space Experiment (MSX) catalog. These derived stellar effective temperatures were accurate when we compared them to known values from literatures. This research makes full use of catalog data and presents an original technique for studying stellar characteristics. It proposes a novel method for calculating stellar effective temperatures and detecting angular parameters, and provides theoretical and practical data for finding information about radiation in any band.

Probabilities and statistics for backscatter estimates obtained by a scatterometer with applications to new scatterometer design data

NASA Technical Reports Server (NTRS)

Pierson, Willard J., Jr.

1989-01-01

The values of the Normalized Radar Backscattering Cross Section (NRCS), sigma (o), obtained by a scatterometer are random variables whose variance is a known function of the expected value. The probability density function can be obtained from the normal distribution. Models for the expected value obtain it as a function of the properties of the waves on the ocean and the winds that generated the waves. Point estimates of the expected value were found from various statistics given the parameters that define the probability density function for each value. Random intervals were derived with a preassigned probability of containing that value. A statistical test to determine whether or not successive values of sigma (o) are truly independent was derived. The maximum likelihood estimates for wind speed and direction were found, given a model for backscatter as a function of the properties of the waves on the ocean. These estimates are biased as a result of the terms in the equation that involve natural logarithms, and calculations of the point estimates of the maximum likelihood values are used to show that the contributions of the logarithmic terms are negligible and that the terms can be omitted.

Estimation Of Rheological Law By Inverse Method From Flow And Temperature Measurements With An Extrusion Die

NASA Astrophysics Data System (ADS)

Pujos, Cyril; Regnier, Nicolas; Mousseau, Pierre; Defaye, Guy; Jarny, Yvon

2007-05-01

Simulation quality is determined by the knowledge of the parameters of the model. Yet the rheological models for polymer are often not very accurate, since the viscosity measurements are made under approximations as homogeneous temperature and empirical corrections as Bagley one. Furthermore rheological behaviors are often traduced by mathematical laws as the Cross or the Carreau-Yasuda ones, whose parameters are fitted from viscosity values, obtained with corrected experimental data, and not appropriate for each polymer. To correct these defaults, a table-like rheological model is proposed. This choice makes easier the estimation of model parameters, since each parameter has the same order of magnitude. As the mathematical shape of the model is not imposed, the estimation process is appropriate for each polymer. The proposed method consists in minimizing the quadratic norm of the difference between calculated variables and measured data. In this study an extrusion die is simulated, in order to provide us temperature along the extrusion channel, pressure and flow references. These data allow to characterize thermal transfers and flow phenomena, in which the viscosity is implied. Furthermore the different natures of data allow to estimate viscosity for a large range of shear rates. The estimated rheological model improves the agreement between measurements and simulation: for numerical cases, the error on the flow becomes less than 0.1% for non-Newtonian rheology. This method couples measurements and simulation, constitutes a very accurate mean of rheology determination, and allows to improve the prediction abilities of the model.

Mathematical model of cycad cones' thermogenic temperature responses: inverse calorimetry to estimate metabolic heating rates.

PubMed

Roemer, R B; Booth, D; Bhavsar, A A; Walter, G H; Terry, L I

2012-12-21

A mathematical model based on conservation of energy has been developed and used to simulate the temperature responses of cones of the Australian cycads Macrozamia lucida and Macrozamia. macleayi during their daily thermogenic cycle. These cones generate diel midday thermogenic temperature increases as large as 12 °C above ambient during their approximately two week pollination period. The cone temperature response model is shown to accurately predict the cones' temperatures over multiple days as based on simulations of experimental results from 28 thermogenic events from 3 different cones, each simulated for either 9 or 10 sequential days. The verified model is then used as the foundation of a new, parameter estimation based technique (termed inverse calorimetry) that estimates the cones' daily metabolic heating rates from temperature measurements alone. The inverse calorimetry technique's predictions of the major features of the cones' thermogenic metabolism compare favorably with the estimates from conventional respirometry (indirect calorimetry). Because the new technique uses only temperature measurements, and does not require measurements of oxygen consumption, it provides a simple, inexpensive and portable complement to conventional respirometry for estimating metabolic heating rates. It thus provides an additional tool to facilitate field and laboratory investigations of the bio-physics of thermogenic plants. Copyright © 2012 Elsevier Ltd. All rights reserved.

Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

NASA Technical Reports Server (NTRS)

Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.;

Similar estimates of temperature impacts on global wheat yield by three independent methods

NASA Astrophysics Data System (ADS)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

2016-12-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Near infrared spectroscopy to estimate the temperature reached on burned soils: strategies to develop robust models.

NASA Astrophysics Data System (ADS)

Guerrero, César; Pedrosa, Elisabete T.; Pérez-Bejarano, Andrea; Keizer, Jan Jacob

2014-05-01

The temperature reached on soils is an important parameter needed to describe the wildfire effects. However, the methods for measure the temperature reached on burned soils have been poorly developed. Recently, the use of the near-infrared (NIR) spectroscopy has been pointed as a valuable tool for this purpose. The NIR spectrum of a soil sample contains information of the organic matter (quantity and quality), clay (quantity and quality), minerals (such as carbonates and iron oxides) and water contents. Some of these components are modified by the heat, and each temperature causes a group of changes, leaving a typical fingerprint on the NIR spectrum. This technique needs the use of a model (or calibration) where the changes in the NIR spectra are related with the temperature reached. For the development of the model, several aliquots are heated at known temperatures, and used as standards in the calibration set. This model offers the possibility to make estimations of the temperature reached on a burned sample from its NIR spectrum. However, the estimation of the temperature reached using NIR spectroscopy is due to changes in several components, and cannot be attributed to changes in a unique soil component. Thus, we can estimate the temperature reached by the interaction between temperature and the thermo-sensible soil components. In addition, we cannot expect the uniform distribution of these components, even at small scale. Consequently, the proportion of these soil components can vary spatially across the site. This variation will be present in the samples used to construct the model and also in the samples affected by the wildfire. Therefore, the strategies followed to develop robust models should be focused to manage this expected variation. In this work we compared the prediction accuracy of models constructed with different approaches. These approaches were designed to provide insights about how to distribute the efforts needed for the development of robust

A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

PubMed Central

Li, Huashan; Cao, Fei; Wang, Xianlong; Ma, Weibin

2014-01-01

Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China. PMID:24605046

A Method for Estimating Missing Hourly Temperatures Using Daily Maximum and Minimum Temperatures

DTIC Science & Technology

1991-08-01

work documented by USAFETAC/PR-90/006, S/urt-Termn Hourl ’y Iernpcrature Interlyolaion, by Mal Wvalter F . Miller, December 1990. In his study, Miller...temperatures for the missing hours and concluded that the best model %as one developed by Hoogenboom and [luck (1986). The Hoogcnboom/Huck model uses a...mean of the error estimate, was determined from the following equation: - 7)) BIAS = 1 N", f (14) where the difference between the observed hourly

Batch Effect Confounding Leads to Strong Bias in Performance Estimates Obtained by Cross-Validation

PubMed Central

Delorenzi, Mauro

2014-01-01

Background With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences (“batch effects”) as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. Focus The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. Data We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., ‘control’) or group 2 (e.g., ‘treated’). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. Methods We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data. PMID:24967636

Mesospheric temperatures estimated from the meteor radar observations at Mohe, China

NASA Astrophysics Data System (ADS)

Liu, Libo; Liu, Huixin; Chen, Yiding; Le, Huijun

2017-04-01

In this work, we report the estimation of mesospheric temperatures at 90 km height from the observations of the VHF all-sky meteor radar operated at Mohe (53.5 °N, 122.3° E), China, since August 2011. The kinetic temperature profiles retrieved from the observations of Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) onboard the Thermosphere, Ionosphere, Mesosphere, Energetics, and Dynamics (TIMED) satellite are processed to provide the temperature (TSABER) and temperature gradient (dT/dh) at 90 km height. Based on the SABER temperature profile data an empirical dT/dh model is developed for the Mohe latitude. First, we derive the temperatures from the meteor decay times (Tmeteor) and the Mohe dT/dh model gives prior information of temperature gradients. Secondly, the full-width of half maximum (FWHM) of the meteor height profiles is calculated and further used to deduce the temperatures (TFWHM) based on the strong linear relationship between FWHM and TSABER. The temperatures at 90 km deduced from the decay times (Tmeteor) and from the meteor height distributions (TFWHM) at Mohe are validated/calibrated with TSABER. The temperatures present a considerable annual variation, being maximum in winter and minimum in summer. Harmonic analyses reveal that the temperatures have an annual variation consistent with TSABER. Our work suggests that the FWHM has a good performance in routine estimation of the temperatures. It should be pointed out that the slope of FWHM and TSABER is 10.1 at Mohe, which is different from that of 15.71 at King Sejong (62.2° S, 58.8° E) station. Acknowledgments The TIMED/SABER kinetic temperature (version 2.0) data are provided by the SABER team through http://saber.gats-inc.com/. The temperatures from the NRLMSISE-00 model are calculated using Aerospace Blockset toolbox of MATLAB (2016a). This research was supported by National Natural Science Foundation of China (41231065, 41321003). We acknowledge the use of meteor radar

How to apply the optimal estimation method to your lidar measurements for improved retrievals of temperature and composition

NASA Astrophysics Data System (ADS)

Sica, R. J.; Haefele, A.; Jalali, A.; Gamage, S.; Farhani, G.

2018-04-01

The optimal estimation method (OEM) has a long history of use in passive remote sensing, but has only recently been applied to active instruments like lidar. The OEM's advantage over traditional techniques includes obtaining a full systematic and random uncertainty budget plus the ability to work with the raw measurements without first applying instrument corrections. In our meeting presentation we will show you how to use the OEM for temperature and composition retrievals for Rayleigh-scatter, Ramanscatter and DIAL lidars.

Comparison of ArcGIS and SAS Geostatistical Analyst to Estimate Population-Weighted Monthly Temperature for US Counties

PubMed Central

Xiaopeng, QI; Liang, WEI; BARKER, Laurie; LEKIACHVILI, Akaki; Xingyou, ZHANG

2015-01-01

Temperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature’s association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly—or 30-day—basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R2, mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS’s merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects. PMID:26167169

Estimation of Temperature Range for Cryo Cutting of Frozen Mackerel using DSC

NASA Astrophysics Data System (ADS)

Okamoto, Kiyoshi; Hagura, Yoshio; Suzuki, Kanichi

Frozen mackerel flesh was subjected to measurement of its fracture stress (bending energy) in a low temperature range. The optimum conditions for low temperature cutting, "cryo cutting," were estimated from the results of enthalpy changes measured by a differential scanning calorimeter (DSC). There were two enthalpy changes for gross transition on the DSC chart for mackerel, one was at -63°C to -77°C and the other at -96°C to -112°C. Thus we estimated that mackerel was able to cut by bending below -63°C and that there would be a great decrease in bending energy occurring at around -77°C and -112°C. In testing, there were indeed two great decreases of bending energy for the test pieces of mackerel that had been frozen at -40°C, one was at -70°C to -90°C and the other was at -100°C to -120°C. Therefore, the test pieces of mackerel could be cut by bending at -70°C. The results showed that the DSC measurement of mackerel flesh gave a good estimation of the appropriate cutting temperature of mackerel.

Crowdsourcing urban air temperatures from smartphone battery temperatures

NASA Astrophysics Data System (ADS)

Overeem, A.; Robinson, J. C. R.; Leijnse, H.; Steeneveld, G. J.; Horn, B. K. P.; Uijlenhoet, R.

2013-08-01

Accurate air temperature observations in urban areas are important for meteorology and energy demand planning. They are indispensable to study the urban heat island effect and the adverse effects of high temperatures on human health. However, the availability of temperature observations in cities is often limited. Here we show that relatively accurate air temperature information for the urban canopy layer can be obtained from an alternative, nowadays omnipresent source: smartphones. In this study, battery temperatures were collected by an Android application for smartphones. A straightforward heat transfer model is employed to estimate daily mean air temperatures from smartphone battery temperatures for eight major cities around the world. The results demonstrate the enormous potential of this crowdsourcing application for real-time temperature monitoring in densely populated areas.

Estimating trends in the global mean temperature record

NASA Astrophysics Data System (ADS)

Poppick, Andrew; Moyer, Elisabeth J.; Stein, Michael L.

2017-06-01

Given uncertainties in physical theory and numerical climate simulations, the historical temperature record is often used as a source of empirical information about climate change. Many historical trend analyses appear to de-emphasize physical and statistical assumptions: examples include regression models that treat time rather than radiative forcing as the relevant covariate, and time series methods that account for internal variability in nonparametric rather than parametric ways. However, given a limited data record and the presence of internal variability, estimating radiatively forced temperature trends in the historical record necessarily requires some assumptions. Ostensibly empirical methods can also involve an inherent conflict in assumptions: they require data records that are short enough for naive trend models to be applicable, but long enough for long-timescale internal variability to be accounted for. In the context of global mean temperatures, empirical methods that appear to de-emphasize assumptions can therefore produce misleading inferences, because the trend over the twentieth century is complex and the scale of temporal correlation is long relative to the length of the data record. We illustrate here how a simple but physically motivated trend model can provide better-fitting and more broadly applicable trend estimates and can allow for a wider array of questions to be addressed. In particular, the model allows one to distinguish, within a single statistical framework, between uncertainties in the shorter-term vs. longer-term response to radiative forcing, with implications not only on historical trends but also on uncertainties in future projections. We also investigate the consequence on inferred uncertainties of the choice of a statistical description of internal variability. While nonparametric methods may seem to avoid making explicit assumptions, we demonstrate how even misspecified parametric statistical methods, if attuned to the

Online estimation of internal stack temperatures in solid oxide fuel cell power generating units

NASA Astrophysics Data System (ADS)

Dolenc, B.; Vrečko, D.; Juričić, Ɖ.; Pohjoranta, A.; Pianese, C.

2016-12-01

Thermal stress is one of the main factors affecting the degradation rate of solid oxide fuel cell (SOFC) stacks. In order to mitigate the possibility of fatal thermal stress, stack temperatures and the corresponding thermal gradients need to be continuously controlled during operation. Due to the fact that in future commercial applications the use of temperature sensors embedded within the stack is impractical, the use of estimators appears to be a viable option. In this paper we present an efficient and consistent approach to data-driven design of the estimator for maximum and minimum stack temperatures intended (i) to be of high precision, (ii) to be simple to implement on conventional platforms like programmable logic controllers, and (iii) to maintain reliability in spite of degradation processes. By careful application of subspace identification, supported by physical arguments, we derive a simple estimator structure capable of producing estimates with 3% error irrespective of the evolving stack degradation. The degradation drift is handled without any explicit modelling. The approach is experimentally validated on a 10 kW SOFC system.

Orbital and suborbital variability in North Atlantic bottom water temperature obtained from deep-sea ostracod Mg/Ca ratios

USGS Publications Warehouse

Cronin, T. M.; Dwyer, G.S.; Baker, P.A.; Rodriguez-Lazaro, J.; DeMartino, D.M.

2000-01-01

Magnesium/calcium (Mg/Ca) ratios were measured in the deep-sea ostracod (Crustacea) genus Krithe from Chain core 82-24-4PC from the western mid-Atlantic Ridge (3427 m) in order to estimate ocean circulation and bottom water temperature (BWT) variability over the past 200,000 years. Mg/Ca ratios have been used as a paleothermometer because the ratios are controlled primarily by ambient water temperatures at the time the organism secretes its adult carapace. Over the past two glacial–interglacial cycles, Mg/Ca values oscillated between about 7 mmol/mol and 12 mmol/mol, equivalent to a BWT range of 0 to >3.5°C. The lowest values were obtained on specimens from glacial marine isotope stages (MISs) 2, 4 and 6; the highest values were obtained from specimens from the early part of the Holocene interglacial (MIS 1), and also from MISs 5 and 7. These trends suggest that BWTs in the North Atlantic Ocean fluctuate over orbital time scales.Suborbital variability in Mg/Ca ratios and BWT was also observed for the past 100,000 years. Ratios rose from ∼8 mmol/mol to ∼10 mmol/mol (implying a BWT increase of ∼1 to 3°C) during 14 Mg/Ca excursions. The highest ratios were found in Krithe dated at approximately 32, 36–38, 43, 48, 73, 85 and 93 ka. Although the age model for the Chain 82-24-4PC and temporal resolution do not allow precise correlation, some of these deep-sea bottom temperature excursions appear to correspond to Heinrich events recorded in other regions of the North Atlantic and perhaps Dansgaard–Oeschger interstadial events recorded in Greenland ice cores. If confirmed, this would support the hypothesis that millennial-scale oscillations of climate in the North Atlantic are capable of affecting global climate via thermohaline circulation changes.

A method for estimating the diffuse attenuation coefficient (KdPAR)from paired temperature sensors

USGS Publications Warehouse

Read, Jordan S.; Rose, Kevin C.; Winslow, Luke A.; Read, Emily K.

2015-01-01

A new method for estimating the diffuse attenuation coefficient for photosynthetically active radiation (KdPAR) from paired temperature sensors was derived. We show that during cases where the attenuation of penetrating shortwave solar radiation is the dominant source of temperature changes, time series measurements of water temperatures at multiple depths (z1 and z2) are related to one another by a linear scaling factor (a). KdPAR can then be estimated by the simple equation KdPAR ln(a)/(z2/z1). A suggested workflow is presented that outlines procedures for calculating KdPAR according to this paired temperature sensor (PTS) method. This method is best suited for conditions when radiative temperature gains are large relative to physical noise. These conditions occur frequently on water bodies with low wind and/or high KdPARs but can be used for other types of lakes during time periods of low wind and/or where spatially redundant measurements of temperatures are available. The optimal vertical placement of temperature sensors according to a priori knowledge of KdPAR is also described. This information can be used to inform the design of future sensor deployments using the PTS method or for campaigns where characterizing sub-daily changes in temperatures is important. The PTS method provides a novel method to characterize light attenuation in aquatic ecosystems without expensive radiometric equipment or the user subjectivity inherent in Secchi depth measurements. This method also can enable the estimation of KdPAR at higher frequencies than many manual monitoring programs allow.

Estimating Hardness from the USDC Tool-Bit Temperature Rise

NASA Technical Reports Server (NTRS)

Bar-Cohen, Yoseph; Sherrit, Stewart

2008-01-01

A method of real-time quantification of the hardness of a rock or similar material involves measurement of the temperature, as a function of time, of the tool bit of an ultrasonic/sonic drill corer (USDC) that is being used to drill into the material. The method is based on the idea that, other things being about equal, the rate of rise of temperature and the maximum temperature reached during drilling increase with the hardness of the drilled material. In this method, the temperature is measured by means of a thermocouple embedded in the USDC tool bit near the drilling tip. The hardness of the drilled material can then be determined through correlation of the temperature-rise-versus-time data with time-dependent temperature rises determined in finite-element simulations of, and/or experiments on, drilling at various known rates of advance or known power levels through materials of known hardness. The figure presents an example of empirical temperature-versus-time data for a particular 3.6-mm USDC bit, driven at an average power somewhat below 40 W, drilling through materials of various hardness levels. The temperature readings from within a USDC tool bit can also be used for purposes other than estimating the hardness of the drilled material. For example, they can be especially useful as feedback to control the driving power to prevent thermal damage to the drilled material, the drill bit, or both. In the case of drilling through ice, the temperature readings could be used as a guide to maintaining sufficient drive power to prevent jamming of the drill by preventing refreezing of melted ice in contact with the drill.

Method for determining waveguide temperature for acoustic transceiver used in a gas turbine engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeSilva, Upul P.; Claussen, Heiko; Ragunathan, Karthik

A method for determining waveguide temperature for at least one waveguide of a transceiver utilized for generating a temperature map. The transceiver generates an acoustic signal that travels through a measurement space in a hot gas flow path defined by a wall such as in a combustor. The method includes calculating a total time of flight for the acoustic signal and subtracting a waveguide travel time from the total time of flight to obtain a measurement space travel time. A temperature map is calculated based on the measurement space travel time. An estimated wall temperature is obtained from the temperaturemore » map. An estimated waveguide temperature is then calculated based on the estimated wall temperature wherein the estimated waveguide temperature is determined without the use of a temperature sensing device.« less

Using groundwater temperature data to constrain parameter estimation in a groundwater flow model of a wetland system

USGS Publications Warehouse

Bravo, Hector R.; Jiang, Feng; Hunt, Randall J.

2002-01-01

Parameter estimation is a powerful way to calibrate models. While head data alone are often insufficient to estimate unique parameters due to model nonuniqueness, flow‐and‐heat‐transport modeling can constrain estimation and allow simultaneous estimation of boundary fluxes and hydraulic conductivity. In this work, synthetic and field models that did not converge when head data were used did converge when head and temperature were used. Furthermore, frequency domain analyses of head and temperature data allowed selection of appropriate modeling timescales. Inflows in the Wilton, Wisconsin, wetlands could be estimated over periods such as a growing season and over periods of a few days when heads were nearly steady and groundwater temperature varied during the day. While this methodology is computationally more demanding than traditional head calibration, the results gained are unobtainable using the traditional approach. These results suggest that temperature can efficiently supplement head data in systems where accurate flux calibration targets are unavailable.

Mesospheric temperatures estimated from the meteor decay times over King Sejong Station(62.2°S, 58.8°W), Antarctica

NASA Astrophysics Data System (ADS)

Kim, J.; Kim, Y.; Jee, G.

2010-12-01

A VHF meteor radar has ben operated at King Sejong Station (62.2°S, 58.8°W), Antarctica since March 2007 for the observations of the neutral winds in the mesosphere and lower thermosphere region. In addition, the radar observation allows usto estimate the neutral temperature from the measured meteor decay times of the meteor echoes by utilizing Hocking's method (Hocking, 1999). For this temperature estimation, the meteor echoes observed from March 2007 to July 2009 were divded, for the first time, into weak and strong echoes depending on the strength of estimated relative electron line densities. The estimated temperatures are then compared the temperature measurements from the spectral airglow temperature imager (SATI) which has also been operated at the same location since 2002. The estimated temperatures from strong echoes were significantly lower than the temperatures estimated from weak echoes by on average about 31 K. As was done in most previous studies, we also derived the temperature by using all echoes without dividing into weak and strong, which produces about 10 K lower than the weak echoes. Among these hree estimated temperatures, the one from weak echoes was most similar to the SATI temperature. This result indicates that the strong echoes tend to reduce the estimated temperature and therefore need to be removed in the estimation procedure. We will also present the comparison of the estimated temperature with other measurements, for example, from the TIMED/SABER instrument and the NRLMSISE-00 empirical model results as a further validation.

Crowdsourcing urban air temperatures from smartphone battery temperatures

NASA Astrophysics Data System (ADS)

Overeem, Aart; Robinson, James C. R.; Leijnse, Hidde; Steeneveld, Gert-Jan; Horn, Berthold K. P.; Uijlenhoet, Remko

2014-05-01

Accurate air temperature observations in urban areas are important for meteorology and energy demand planning. They are indispensable to study the urban heat island effect and the adverse effects of high temperatures on human health. However, the availability of temperature observations in cities is often limited. Here we show that relatively accurate air temperature information for the urban canopy layer can be obtained from an alternative, nowadays omnipresent source: smartphones. In this study, battery temperatures were collected by an Android application for smartphones. It has been shown that a straightforward heat transfer model can be employed to estimate daily mean air temperatures from smartphone battery temperatures for eight major cities around the world. The results demonstrate the enormous potential of this crowdsourcing application for real-time temperature monitoring in densely populated areas. Battery temperature data were collected by users of an Android application for cell phones (opensignal.com). The application automatically sends battery temperature data to a server for storage. In this study, battery temperatures are averaged in space and time to obtain daily averaged battery temperatures for each city separately. A regression model, which can be related to a physical model, is employed to retrieve daily air temperatures from battery temperatures. The model is calibrated with observed air temperatures from a meteorological station of an airport located in or near the city. Time series of air temperatures are obtained for each city for a period of several months, where 50% of the data is for independent verification. The methodology has been applied to Buenos Aires, London, Los Angeles, Paris, Mexico City, Moscow, Rome, and Sao Paulo. The evolution of the retrieved air temperatures often correspond well with the observed ones. The mean absolute error of daily air temperatures is less than 2 degrees Celsius, and the bias is within 1 degree

Comparison of different methods of estimating the mean radiant temperature in outdoor thermal comfort studies.

PubMed

Krüger, E L; Minella, F O; Matzarakis, A

2014-10-01

Correlations between outdoor thermal indices and the calculated or measured mean radiant temperature T(mrt) are in general of high importance because of the combined effect on human energy balance in outdoor spaces. The most accurate way to determine T(mrt) is by means of integral radiation measurements, i.e. measuring the short- and long-wave radiation from six directions using pyranometers and pyrgeometers, an expensive and not always an easily available procedure. Some studies use globe thermometers combined with air temperature and wind speed sensors. An alternative way to determine T(mrt) is based on output from the RayMan model from measured data of incoming global radiation and morphological features of the monitoring site in particular sky view factor (SVF) data. The purpose of this paper is to compare different methods to assess the mean radiant temperature T(mrt) in terms of differences to a reference condition (T(mrt) calculated from field measurements) and to resulting outdoor comfort levels expressed as PET and UTCI values. The T(mrt) obtained from field measurements is a combination of air temperature, wind speed and globe temperature data according to the forced ventilation formula of ISO 7726 for data collected in Glasgow, UK. Four different methods were used in the RayMan model for T(mrt) calculations: input data consisting exclusively of data measured at urban sites; urban data excluding solar radiation, estimated SVF data and solar radiation data measured at a rural site; urban data excluding solar radiation with SVF data for each site; urban data excluding solar radiation and including solar radiation at the rural site taking no account of SVF information. Results show that all methods overestimate T(mrt) when compared to ISO calculations. Correlations were found to be significant for the first method and lower for the other three. Results in terms of comfort (PET, UTCI) suggest that reasonable estimates could be made based on global radiation

Estimation of Surface Heat Flux and Surface Temperature during Inverse Heat Conduction under Varying Spray Parameters and Sample Initial Temperature

PubMed Central

Aamir, Muhammad; Liao, Qiang; Zhu, Xun; Aqeel-ur-Rehman; Wang, Hong

2014-01-01

An experimental study was carried out to investigate the effects of inlet pressure, sample thickness, initial sample temperature, and temperature sensor location on the surface heat flux, surface temperature, and surface ultrafast cooling rate using stainless steel samples of diameter 27 mm and thickness (mm) 8.5, 13, 17.5, and 22, respectively. Inlet pressure was varied from 0.2 MPa to 1.8 MPa, while sample initial temperature varied from 600°C to 900°C. Beck's sequential function specification method was utilized to estimate surface heat flux and surface temperature. Inlet pressure has a positive effect on surface heat flux (SHF) within a critical value of pressure. Thickness of the sample affects the maximum achieved SHF negatively. Surface heat flux as high as 0.4024 MW/m2 was estimated for a thickness of 8.5 mm. Insulation effects of vapor film become apparent in the sample initial temperature range of 900°C causing reduction in surface heat flux and cooling rate of the sample. A sensor location near to quenched surface is found to be a better choice to visualize the effects of spray parameters on surface heat flux and surface temperature. Cooling rate showed a profound increase for an inlet pressure of 0.8 MPa. PMID:24977219

Improved vertical streambed flux estimation using multiple diurnal temperature methods in series

USGS Publications Warehouse

Irvine, Dylan J.; Briggs, Martin A.; Cartwright, Ian; Scruggs, Courtney; Lautz, Laura K.

2017-01-01

Analytical solutions that use diurnal temperature signals to estimate vertical fluxes between groundwater and surface water based on either amplitude ratios (Ar) or phase shifts (Δϕ) produce results that rarely agree. Analytical solutions that simultaneously utilize Ar and Δϕ within a single solution have more recently been derived, decreasing uncertainty in flux estimates in some applications. Benefits of combined (ArΔϕ) methods also include that thermal diffusivity and sensor spacing can be calculated. However, poor identification of either Ar or Δϕ from raw temperature signals can lead to erratic parameter estimates from ArΔϕ methods. An add-on program for VFLUX 2 is presented to address this issue. Using thermal diffusivity selected from an ArΔϕ method during a reliable time period, fluxes are recalculated using an Ar method. This approach maximizes the benefits of the Ar and ArΔϕ methods. Additionally, sensor spacing calculations can be used to identify periods with unreliable flux estimates, or to assess streambed scour. Using synthetic and field examples, the use of these solutions in series was particularly useful for gaining conditions where fluxes exceeded 1 m/d.

Estimating changes to groundwater discharge temperature under altered climate conditions

NASA Astrophysics Data System (ADS)

Manga, M.; Burns, E. R.; Zhu, Y.; Zhan, H.; Williams, C. F.; Ingebritsen, S.; Dunham, J.

2017-12-01

Changes in groundwater temperature resulting from climate-driven boundary conditions (recharge and land surface temperature) can be evaluated using new analytical solutions of the groundwater heat transport equation. These steady-state solutions account for land-surface boundary conditions, hydrology, and geothermal and viscous heating, and can be used to identify the key physical processes that control thermal responses of groundwater-fed ecosystems to climate change, in particular (1) groundwater recharge rate and temperature and (2) land-surface temperature transmitted through the vadose zone. Also, existing transient solutions of conduction are compared with a new solution for advective transport of heat to estimate the timing of groundwater-discharge response to changes in recharge and land surface temperature. As an example, the new solutions are applied to the volcanic Medicine Lake highlands, California, USA, and associated Fall River Springs complexes that host groundwater-dependent ecosystems. In this system, high-elevation groundwater temperatures are strongly affected only by recharge conditions, but as the vadose zone thins away from the highlands, changes to the average annual land surface temperature will also influence groundwater temperatures. Transient response to temperature change depends on both the conductive timescale and the rate at which recharge delivers heat. Most of the thermal response of groundwater at high elevations will occur within 20 years of a shift in recharge temperatures, but the lower-elevation Fall River Springs will respond more slowly, with about half of the conductive response occurring within the first 20 years and about half of the advective response to higher recharge temperatures occurring in approximately 60 years.

Accuracy of patient-specific organ dose estimates obtained using an automated image segmentation algorithm.

PubMed

Schmidt, Taly Gilat; Wang, Adam S; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-10-01

The overall goal of this work is to develop a rapid, accurate, and automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using simulations to generate dose maps combined with automated segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. We hypothesized that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates, since small errors delineating organ boundaries will have minimal effect when computing mean organ dose. A leave-one-out validation study of the automated algorithm was performed with 20 head-neck CT scans expertly segmented into nine regions. Mean organ doses of the automatically and expertly segmented regions were computed from Monte Carlo-generated dose maps and compared. The automated segmentation algorithm estimated the mean organ dose to be within 10% of the expert segmentation for regions other than the spinal canal, with the median error for each organ region below 2%. In the spinal canal region, the median error was [Formula: see text], with a maximum absolute error of 28% for the single-atlas approach and 11% for the multiatlas approach. The results demonstrate that the automated segmentation algorithm can provide accurate organ dose estimates despite some segmentation errors.

Accuracy of patient-specific organ dose estimates obtained using an automated image segmentation algorithm

PubMed Central

Schmidt, Taly Gilat; Wang, Adam S.; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-01-01

Abstract. The overall goal of this work is to develop a rapid, accurate, and automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using simulations to generate dose maps combined with automated segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. We hypothesized that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates, since small errors delineating organ boundaries will have minimal effect when computing mean organ dose. A leave-one-out validation study of the automated algorithm was performed with 20 head-neck CT scans expertly segmented into nine regions. Mean organ doses of the automatically and expertly segmented regions were computed from Monte Carlo-generated dose maps and compared. The automated segmentation algorithm estimated the mean organ dose to be within 10% of the expert segmentation for regions other than the spinal canal, with the median error for each organ region below 2%. In the spinal canal region, the median error was −7%, with a maximum absolute error of 28% for the single-atlas approach and 11% for the multiatlas approach. The results demonstrate that the automated segmentation algorithm can provide accurate organ dose estimates despite some segmentation errors. PMID:27921070

Temperature-Dependent Estimation of Gibbs Energies Using an Updated Group-Contribution Method.

PubMed

Du, Bin; Zhang, Zhen; Grubner, Sharon; Yurkovich, James T; Palsson, Bernhard O; Zielinski, Daniel C

2018-06-05

Reaction-equilibrium constants determine the metabolite concentrations necessary to drive flux through metabolic pathways. Group-contribution methods offer a way to estimate reaction-equilibrium constants at wide coverage across the metabolic network. Here, we present an updated group-contribution method with 1) additional curated thermodynamic data used in fitting and 2) capabilities to calculate equilibrium constants as a function of temperature. We first collected and curated aqueous thermodynamic data, including reaction-equilibrium constants, enthalpies of reaction, Gibbs free energies of formation, enthalpies of formation, entropy changes of formation of compounds, and proton- and metal-ion-binding constants. Next, we formulated the calculation of equilibrium constants as a function of temperature and calculated the standard entropy change of formation (Δ f S ∘ ) using a model based on molecular properties. The median absolute error in estimating Δ f S ∘ was 0.013 kJ/K/mol. We also estimated magnesium binding constants for 618 compounds using a linear regression model validated against measured data. We demonstrate the improved performance of the current method (8.17 kJ/mol in median absolute residual) over the current state-of-the-art method (11.47 kJ/mol) in estimating the 185 new reactions added in this work. The efforts here fill in gaps for thermodynamic calculations under various conditions, specifically different temperatures and metal-ion concentrations. These, to our knowledge, new capabilities empower the study of thermodynamic driving forces underlying the metabolic function of organisms living under diverse conditions. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Soil temperature synchronisation improves estimation of daily variation of ecosystem respiration in Sphagnum peatlands

NASA Astrophysics Data System (ADS)

D'Angelo, Benoît; Gogo, Sébastien; Le Moing, Franck; Jégou, Fabrice; Guimbaud, Christophe; Laggoun, Fatima

2015-04-01

Ecosystem respiration (ER) is a key process in the global C cycle and thus, plays an important role in the climate regulation. Peatlands contain a third of the world soil C in spite of their relatively low global area (3% of land area). Although these ecosystems represent potentially a significant source of C under global change, they are still not taken into account accordingly in global climatic models. Therefore, ER variations have to be accounted for, especially by estimating its dependence to temperature.s The relationship between ER and temperature often relies only on one soil temperature depth and the latter is generally taken in the first 10 centimetres. Previous studies showed that the temperature dependence of ER depends on the depth at which the temperature is recorded. The depth selection for temperature measurement is thus a predominant issue. A way to deal with this is to analyse the time-delay between ER and temperature. The aim of this work is to assess whether using synchronised data in models leads to a better ER daily variation estimation than using non-synchronised data. ER measurements were undertaken in 2013 in 4 Sphagnum peatlands across France: La Guette (N 47°19'44', E 2°17'04', 154m) in July, Landemarais (N 48°26'30', E -1°10'54', 145m) in August, Frasne (N 46°49'35', E 6°10'20', 836m) in September, and Bernadouze (N 42°48'09', E 1°25'24', 1500m) in October. A closed method chamber was used to measure ER hourly during 72 hours in each of the 4 replicates installed in each site. Average ER ranged from 1.75 μmol m-2 s-1 to 6.13 μmol m-2 s-1. A weather station was used to record meteorological data and soil temperature profiles (5, 10, 20 and 30 cm). Synchronised data were determined for each depth by selecting the time-delay leading to the best correlation between ER and soil temperature. The data were used to simulate ER according to commonly used equations: linear, exponential with Q10, Arrhenius, Lloyd and Taylor. Models

Heritability of body surface temperature in hens estimated by infrared thermography at normal or hot temperatures and genetic correlations with egg and feather quality.

PubMed

Loyau, T; Zerjal, T; Rodenburg, T B; Fablet, J; Tixier-Boichard, M; Pinard-van der Laan, M H; Mignon-Grasteau, S

2016-10-01

Exposure of laying hens to chronic heat stress results in loss of egg production. It should be possible to improve hen resilience to chronic heat stress by genetic selection but measuring their sensitivity through internal temperature is time consuming and is not very precise. In this study we used infrared thermography to measure the hen's capacity to dissipate heat, in a commercial line of laying hens subjected to cycles of neutral (N, 19.6°C) or high (H, 28.4°C) ambient temperatures. Mean body temperatures (BT) were estimated from 9355 infrared images of wing, comb and shank taken from 1200 hens. Genetic parameters were estimated separately for N and H temperatures. Correlations between BT and plumage condition were also investigated. Wing temperature had low heritability (0.00 to 0.09), consistent with the fact that wing temperature mainly reflects the environmental temperature and is not a zone of heat dissipation. The heritability of comb temperature was higher, from 0.15 to 0.19 in N and H conditions, respectively. Finally, the shank temperature provided the highest heritability estimates, with values of 0.20 to 0.22 in H and N conditions, respectively. Taken together, these results show that heat dissipation is partly under genetic control. Interestingly, the genetic correlation between plumage condition and shank and comb temperatures indicated that birds with poor condition plumage also had the possibility to dissipate heat through featherless areas. Genetic correlations of temperature measurements with egg quality showed that temperatures were correlated with egg width and weight, yolk brightness and yellowness and Haugh units only under H conditions. In contrast, shell colour was correlated with leg temperature only at thermo-neutrality.

Black-box modeling to estimate tissue temperature during radiofrequency catheter cardiac ablation: Feasibility study on an agar phantom model.

PubMed

Blasco-Gimenez, Ramón; Lequerica, Juan L; Herrero, Maria; Hornero, Fernando; Berjano, Enrique J

2010-04-01

The aim of this work was to study linear deterministic models to predict tissue temperature during radiofrequency cardiac ablation (RFCA) by measuring magnitudes such as electrode temperature, power and impedance between active and dispersive electrodes. The concept involves autoregressive models with exogenous input (ARX), which is a particular case of the autoregressive moving average model with exogenous input (ARMAX). The values of the mode parameters were determined from a least-squares fit of experimental data. The data were obtained from radiofrequency ablations conducted on agar models with different contact pressure conditions between electrode and agar (0 and 20 g) and different flow rates around the electrode (1, 1.5 and 2 L min(-1)). Half of all the ablations were chosen randomly to be used for identification (i.e. determination of model parameters) and the other half were used for model validation. The results suggest that (1) a linear model can be developed to predict tissue temperature at a depth of 4.5 mm during RF cardiac ablation by using the variables applied power, impedance and electrode temperature; (2) the best model provides a reasonably accurate estimate of tissue temperature with a 60% probability of achieving average errors better than 5 degrees C; (3) substantial errors (larger than 15 degrees C) were found only in 6.6% of cases and were associated with abnormal experiments (e.g. those involving the displacement of the ablation electrode) and (4) the impact of measuring impedance on the overall estimate is negligible (around 1 degrees C).

Similar negative impacts of temperature on global wheat yield estimated by three independent methods

USDA-ARS?s Scientific Manuscript database

The potential impact of global temperature change on global wheat production has recently been assessed with different methods, scaling and aggregation approaches. Here we show that grid-based simulations, point-based simulations, and statistical regressions produce similar estimates of temperature ...

Estimation of water diffusion coefficient into polycarbonate at different temperatures using numerical simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nasirabadi, P. Shojaee; Jabbari, M.; Hattel, J. H.

2016-06-08

Nowadays, many electronic systems are exposed to harsh conditions of relative humidity and temperature. Mass transport properties of electronic packaging materials are needed in order to investigate the influence of moisture and temperature on reliability of electronic devices. Polycarbonate (PC) is widely used in the electronics industry. Thus, in this work the water diffusion coefficient into PC is investigated. Furthermore, numerical methods used for estimation of the diffusion coefficient and their assumptions are discussed. 1D and 3D numerical solutions are compared and based on this, it is shown how the estimated value can be different depending on the choice ofmore » dimensionality in the model.« less

Infrared thermal imaging of the inner canthus of the eye as an estimator of body core temperature.

PubMed

Teunissen, L P J; Daanen, H A M

2011-01-01

Several studies suggest that the temperature of the inner canthus of the eye (T(ca)), determined with infrared thermal imaging, is an appropriate method for core temperature estimation in mass screening of fever. However, these studies used the error prone tympanic temperature as a reference. Therefore, we compared T(ca) to oesophageal temperature (T(es)) as gold standard in 10 subjects during four conditions: rest, exercise, recovery and passive heating. T(ca) and T(es) differed significantly during all conditions (mean ΔT(es) - T(ca) 1.80 ± 0.89°C) and their relationship was inconsistent between conditions. Also within the rest condition alone, intersubject variability was too large for a reliable estimation of core temperature. This poses doubts on the use of T(ca) as a technique for core temperature estimation, although generalization of these results to fever detection should be verified experimentally using febrile patients.

Gold nanoparticle assemblies of controllable size obtained by hydroxylamine reduction at room temperature

NASA Astrophysics Data System (ADS)

Tódor, István Sz.; Szabó, László; Marişca, Oana T.; Chiş, Vasile; Leopold, Nicolae

2014-12-01

Colloidal nanoparticle assemblies (NPAs) were obtained in a one-step procedure, by reduction of HAuCl4 by hydroxylamine hydrochloride, at room temperature, without the use of any additional nucleating agent. By changing the order of the reactants, NPAs with mean size of 20 and 120 nm were obtained. Because of their size and irregular popcorn like shape, the larger size NPAs show absorption in the NIR spectral region. The building blocks of the resulted nanoassemblies are spherical nanoparticles with diameters of 4-8 and 10-30 nm, respectively. Moreover, by stabilizing the colloid with bovine serum albumin at different time moments after synthesis, NPAs of controlled size between 20 and 120 nm, could be obtained. The NPAs were characterized using UV-Vis spectroscopy, TEM and SEM electron microscopies. In addition, the possibility of using the here proposed NPAs as surface-enhanced Raman scattering (SERS) substrate was assessed and found to provide a higher enhancement compared to conventional citrate-reduced nanoparticles.

Estimating changes in mean body temperature for humans during exercise using core and skin temperatures is inaccurate even with a correction factor.

PubMed

Jay, Ollie; Reardon, Francis D; Webb, Paul; Ducharme, Michel B; Ramsay, Tim; Nettlefold, Lindsay; Kenny, Glen P

2007-08-01

Changes in mean body temperature (DeltaT(b)) estimated by the traditional two-compartment model of "core" and "shell" temperatures and an adjusted two-compartment model incorporating a correction factor were compared with values derived by whole body calorimetry. Sixty participants (31 men, 29 women) cycled at 40% of peak O(2) consumption for 60 or 90 min in the Snellen calorimeter at 24 or 30 degrees C. The core compartment was represented by esophageal, rectal (T(re)), and aural canal temperature, and the shell compartment was represented by a 12-point mean skin temperature (T(sk)). Using T(re) and conventional core-to-shell weightings (X) of 0.66, 0.79, and 0.90, mean DeltaT(b) estimation error (with 95% confidence interval limits in parentheses) for the traditional model was -95.2% (-83.0, -107.3) to -76.6% (-72.8, -80.5) after 10 min and -47.2% (-40.9, -53.5) to -22.6% (-14.5, -30.7) after 90 min. Using T(re), X = 0.80, and a correction factor (X(0)) of 0.40, mean DeltaT(b) estimation error for the adjusted model was +9.5% (+16.9, +2.1) to -0.3% (+11.9, -12.5) after 10 min and +15.0% (+27.2, +2.8) to -13.7% (-4.2, -23.3) after 90 min. Quadratic analyses of calorimetry DeltaT(b) data was subsequently used to derive best-fitting values of X for both models and X(0) for the adjusted model for each measure of core temperature. The most accurate model at any time point or condition only accounted for 20% of the variation observed in DeltaT(b) for the traditional model and 56% for the adjusted model. In conclusion, throughout exercise the estimation of DeltaT(b) using any measure of core temperature together with mean skin temperature irrespective of weighting is inaccurate even with a correction factor customized for the specific conditions.

Calculations of atmospheric transmittance in the 11 micrometer window for estimating skin temperature from VISSR infrared brightness temperatures

NASA Technical Reports Server (NTRS)

Chesters, D.

1984-01-01

An algorithm for calculating the atmospheric transmittance in the 10 to 20 micro m spectral band from a known temperature and dewpoint profile, and then using this transmittance to estimate the surface (skin) temperature from a VISSR observation in the 11 micro m window is presented. Parameterizations are drawn from the literature for computing the molecular absorption due to the water vapor continuum, water vapor lines, and carbon dioxide lines. The FORTRAN code is documented for this application, and the sensitivity of the derived skin temperature to variations in the model's parameters is calculated. The VISSR calibration uncertainties are identified as the largest potential source of error.

Impact of air temperature on physically-based maximum precipitation estimation through change in moisture holding capacity of air

NASA Astrophysics Data System (ADS)

Ishida, K.; Ohara, N.; Kavvas, M. L.; Chen, Z. Q.; Anderson, M. L.

2018-01-01

Impact of air temperature on the Maximum Precipitation (MP) estimation through change in moisture holding capacity of air was investigated. A series of previous studies have estimated the MP of 72-h basin-average precipitation over the American River watershed (ARW) in Northern California by means of the Maximum Precipitation (MP) estimation approach, which utilizes a physically-based regional atmospheric model. For the MP estimation, they have selected 61 severe storm events for the ARW, and have maximized them by means of the atmospheric boundary condition shifting (ABCS) and relative humidity maximization (RHM) methods. This study conducted two types of numerical experiments in addition to the MP estimation by the previous studies. First, the air temperature on the entire lateral boundaries of the outer model domain was increased uniformly by 0.0-8.0 °C with 0.5 °C increments for the two severest maximized historical storm events in addition to application of the ABCS + RHM method to investigate the sensitivity of the basin-average precipitation over the ARW to air temperature rise. In this investigation, a monotonous increase was found in the maximum 72-h basin-average precipitation over the ARW with air temperature rise for both of the storm events. The second numerical experiment used specific amounts of air temperature rise that is assumed to happen under future climate change conditions. Air temperature was increased by those specified amounts uniformly on the entire lateral boundaries in addition to application of the ABCS + RHM method to investigate the impact of air temperature on the MP estimate over the ARW under changing climate. The results in the second numerical experiment show that temperature increases in the future climate may amplify the MP estimate over the ARW. The MP estimate may increase by 14.6% in the middle of the 21st century and by 27.3% in the end of the 21st century compared to the historical period.

Estimating Air Temperature over the Tibetan Plateau Using MODIS Data

NASA Astrophysics Data System (ADS)

Huang, Fangfang; Ma, Weiqiang; Ma, Yaoming; Li, Maoshan; Hu, Zeyong

2016-04-01

Time series of MODIS land surface temperature (LST) data and normalized difference vegetation index (NDVI) data, combined with digital elevation model (DEM) and meterological data for 2001-2012, were used to estimate and map the spatial distribution of monthly mean air temperature over the Tibatan Plateau (TP). Time series and regression analysis of monthly mean land surface temperature (Ts) and air temperature (Ta) were both conducted by ordinary liner regression (OLR) and geographical weighted regression (GWR) methods. Analysis showed that GWR method had much better result (Adjusted R2 > 0.79, root mean square error (RMSE) is between 0.51° C and 1.12° C) for estimating Ta than OLR method. The GWR model, with MODIS LST, NDVI and altitude as independent variables, was used to estimate Ta over the Tibetan Plateau. All GWR models in each month were tested by F-test with significant level of α=0.01 and the regression coefficients were all tested by T-test with significant level of α=0.01. This illustrated that Ts, NDVI and altitude play an important role on estimating Ta over the Tibetan Plateau. Finally, the major conclusions are as follows: (1) GWR method has higher accuracy for estimating Ta than OLR (Adjusted R2=0.40˜0.78, RMSE=1.60˜4.38° C), and the Ta control precision can be up to 1.12° C. (2) Over the Northern TP, the range of Ta variation in January is -29.28 ˜ -5.0° C, and that in July is -0.53 ˜ 14.0° C. Ta in summer half year (from May to October) is between -15.92 ˜ 14.0° C. From October on, 0° C isothermal level is gradually declining from the altitude of 4˜5 kilometers, and hits the bottom with altitude of 3200 meters in December, and Ta is all under 0° C in January. 10° C isothermal level gradually starts rising from the altitude of 3200 meters from May, and reaches the highest level with altitude of 4˜5 kilometers in July. In addition, Ta in south slope of the Tanggula Mountains is obviously higher than that in the north slope. Ta

An Integrated Approach to Estimate Instantaneous Near-Surface Air Temperature and Sensible Heat Flux Fields during the SEMAPHORE Experiment.

NASA Astrophysics Data System (ADS)

Bourras, Denis; Eymard, Laurence; Liu, W. Timothy; Dupuis, Hélène

2002-03-01

A new technique was developed to retrieve near-surface instantaneous air temperatures and turbulent sensible heat fluxes using satellite data during the Structure des Echanges Mer-Atmosphere, Proprietes des Heterogeneites Oceaniques: Recherche Experimentale (SEMAPHORE) experiment, which was conducted in 1993 under mainly anticyclonic conditions. The method is based on a regional, horizontal atmospheric temperature advection model whose inputs are wind vectors, sea surface temperature fields, air temperatures around the region under study, and several constants derived from in situ measurements. The intrinsic rms error of the method is 0.7°C in terms of air temperature and 9 W m2 for the fluxes, both at 0.16° × 0.16° and 1.125° × 1.125° resolution. The retrieved air temperature and flux horizontal structures are in good agreement with fields from two operational general circulation models. The application to SEMAPHORE data involves the First European Remote Sensing Satellite (ERS-1) wind fields, Advanced Very High Resolution Radiometer (AVHRR) SST fields, and European Centre for Medium-Range Weather Forecasts (ECMWF) air temperature boundary conditions. The rms errors obtained by comparing the estimations with research vessel measurements are 0.3°C and 5 W m2.

Precise attitude rate estimation using star images obtained by mission telescope for satellite missions

NASA Astrophysics Data System (ADS)

Inamori, Takaya; Hosonuma, Takayuki; Ikari, Satoshi; Saisutjarit, Phongsatorn; Sako, Nobutada; Nakasuka, Shinichi

2015-02-01

Recently, small satellites have been employed in various satellite missions such as astronomical observation and remote sensing. During these missions, the attitudes of small satellites should be stabilized to a higher accuracy to obtain accurate science data and images. To achieve precise attitude stabilization, these small satellites should estimate their attitude rate under the strict constraints of mass, space, and cost. This research presents a new method for small satellites to precisely estimate angular rate using star blurred images by employing a mission telescope to achieve precise attitude stabilization. In this method, the angular velocity is estimated by assessing the quality of a star image, based on how blurred it appears to be. Because the proposed method utilizes existing mission devices, a satellite does not require additional precise rate sensors, which makes it easier to achieve precise stabilization given the strict constraints possessed by small satellites. The research studied the relationship between estimation accuracy and parameters used to achieve an attitude rate estimation, which has a precision greater than 1 × 10-6 rad/s. The method can be applied to all attitude sensors, which use optics systems such as sun sensors and star trackers (STTs). Finally, the method is applied to the nano astrometry satellite Nano-JASMINE, and we investigate the problems that are expected to arise with real small satellites by performing numerical simulations.

Model-based estimation of adiabatic flame temperature during coal gasification

NASA Astrophysics Data System (ADS)

Sarigul, Ihsan Mert

Coal gasification temperature distribution in the gasifier is one of the important issues. High temperature may increase the risk of corrosion of the gasifier wall or it may cause an increase in the amount of volatile compounds. At the same time, gasification temperature is a dominant factor for high conversion of products and completing the reactions during coal gasification in a short time. In the light of this information it can be said that temperature is one of key parameters of coal gasification to enhance the production of high heating value syngas and maximize refractory longevity. This study aims to predict the adiabatic flame temperatures of Australian bituminous coal and Indonesian roto coal in an entrained flow gasifier using different operating conditions with the ChemCAD simulation and design program. To achieve these objectives, two types of gasification parameters were carried out using simulation of a vertical entrained flow reactor: oxygen-to-coal feed ratio by kg/kg and pressure and steam-to-coal feed ratio by kg/kg and pressure. In the first part of study the adiabatic flame temperatures, coal gasification products and other coal characteristics of two types of coals were determined using ChemCAD software. During all simulations, coal feed rate, coal particle size, initial temperature of coal, water and oxygen were kept constant. The relationships between flame temperature, coal gasification products and operating parameters were fundamentally investigated. The second part of this study addresses the modeling of the flame temperature relation to methane production and other input parameters used previous chapter. The scope of this work was to establish a reasonable model in order to estimate flame temperature without any theoretical calculation. Finally, sensitivity analysis was performed after getting some basic correlations between temperature and input variables. According to the results, oxygen-to-coal feed ratio has the most influential

Effect of windowing on lithosphere elastic thickness estimates obtained via the coherence method: Results from northern South America

NASA Astrophysics Data System (ADS)

Ojeda, GermáN. Y.; Whitman, Dean

2002-11-01

The effective elastic thickness (Te) of the lithosphere is a parameter that describes the flexural strength of a plate. A method routinely used to quantify this parameter is to calculate the coherence between the two-dimensional gravity and topography spectra. Prior to spectra calculation, data grids must be "windowed" in order to avoid edge effects. We investigated the sensitivity of Te estimates obtained via the coherence method to mirroring, Hanning and multitaper windowing techniques on synthetic data as well as on data from northern South America. These analyses suggest that the choice of windowing technique plays an important role in Te estimates and may result in discrepancies of several kilometers depending on the selected windowing method. Te results from mirrored grids tend to be greater than those from Hanning smoothed or multitapered grids. Results obtained from mirrored grids are likely to be over-estimates. This effect may be due to artificial long wavelengths introduced into the data at the time of mirroring. Coherence estimates obtained from three subareas in northern South America indicate that the average effective elastic thickness is in the range of 29-30 km, according to Hanning and multitaper windowed data. Lateral variations across the study area could not be unequivocally determined from this study. We suggest that the resolution of the coherence method does not permit evaluation of small (i.e., ˜5 km), local Te variations. However, the efficiency and robustness of the coherence method in rendering continent-scale estimates of elastic thickness has been confirmed.

Temperature Observation Time and Type Influence Estimates of Heat-Related Mortality in Seven U.S. Cities.

PubMed

Davis, Robert E; Hondula, David M; Patel, Anjali P

2016-06-01

Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat-mortality relationships. We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method. Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series. In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature-mortality relationships were associated with maximum temperature, although mean temperature results were comparable. There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature-mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum

Linear topology in amorphous metal oxide electrochromic networks obtained via low-temperature solution processing

NASA Astrophysics Data System (ADS)

Llordés, Anna; Wang, Yang; Fernandez-Martinez, Alejandro; Xiao, Penghao; Lee, Tom; Poulain, Agnieszka; Zandi, Omid; Saez Cabezas, Camila A.; Henkelman, Graeme; Milliron, Delia J.

2016-12-01

Amorphous transition metal oxides are recognized as leading candidates for electrochromic window coatings that can dynamically modulate solar irradiation and improve building energy efficiency. However, their thin films are normally prepared by energy-intensive sputtering techniques or high-temperature solution methods, which increase manufacturing cost and complexity. Here, we report on a room-temperature solution process to fabricate electrochromic films of niobium oxide glass (NbOx) and `nanocrystal-in-glass’ composites (that is, tin-doped indium oxide (ITO) nanocrystals embedded in NbOx glass) via acid-catalysed condensation of polyniobate clusters. A combination of X-ray scattering and spectroscopic characterization with complementary simulations reveals that this strategy leads to a unique one-dimensional chain-like NbOx structure, which significantly enhances the electrochromic performance, compared to a typical three-dimensional NbOx network obtained from conventional high-temperature thermal processing. In addition, we show how self-assembled ITO-in-NbOx composite films can be successfully integrated into high-performance flexible electrochromic devices.

Estimation of Electron Temperature on Glass Spherical Tokamak (GLAST)

NASA Astrophysics Data System (ADS)

Hussain, S.; Sadiq, M.; Shah, S. I. W.; GLAST Team

2015-03-01

Glass Spherical Tokamak (GLAST) is a small spherical tokamak indigenously developed in Pakistan with an insulating vacuum vessel. A commercially available 2.45 GHz magnetron is used as pre-ionization source for plasma current startup. Different diagnostic systems like Rogowski coils, magnetic probes, flux loops, Langmuir probe, fast imaging and emission spectroscopy are installed on the device. The plasma temperature inside of GLAST, at the time of maxima of plasma current, is estimated by taking into account the Spitzer resistivity calculations with some experimentally determined plasma parameters. The plasma resistance is calculated by using Ohm's law with plasma current and loop voltage as experimentally determined inputs. The plasma resistivity is then determined by using length and area of the plasma column. Finally, the average plasma electron temperature is predicted to be 12.65eV for taking neon (Ne) as a working gas.

Uncertainty in temperature response of current consumption-based emissions estimates

NASA Astrophysics Data System (ADS)

Karstensen, J.; Peters, G. P.; Andrew, R. M.

2014-09-01

Several studies have connected emissions of greenhouse gases to economic and trade data to quantify the causal chain from consumption to emissions and climate change. These studies usually combine data and models originating from different sources, making it difficult to estimate uncertainties in the end results. We estimate uncertainties in economic data, multi-pollutant emission statistics and metric parameters, and use Monte Carlo analysis to quantify contributions to uncertainty and to determine how uncertainty propagates to estimates of global temperature change from regional and sectoral territorial- and consumption-based emissions for the year 2007. We find that the uncertainties are sensitive to the emission allocations, mix of pollutants included, the metric and its time horizon, and the level of aggregation of the results. Uncertainties in the final results are largely dominated by the climate sensitivity and the parameters associated with the warming effects of CO2. The economic data have a relatively small impact on uncertainty at the global and national level, while much higher uncertainties are found at the sectoral level. Our results suggest that consumption-based national emissions are not significantly more uncertain than the corresponding production based emissions, since the largest uncertainties are due to metric and emissions which affect both perspectives equally. The two perspectives exhibit different sectoral uncertainties, due to changes of pollutant compositions. We find global sectoral consumption uncertainties in the range of ±9-±27% using the global temperature potential with a 50 year time horizon, with metric uncertainties dominating. National level uncertainties are similar in both perspectives due to the dominance of CO2 over other pollutants. The consumption emissions of the top 10 emitting regions have a broad uncertainty range of ±9-±25%, with metric and emissions uncertainties contributing similarly. The Absolute global

Gaussian quadrature exponential sum modeling of near infrared methane laboratory spectra obtained at temperatures from 106 to 297 K

NASA Technical Reports Server (NTRS)

Giver, Lawrence P.; Benner, D. C.; Tomasko, M. G.; Fink, U.; Kerola, D.

1990-01-01

Transmission measurements made on near-infrared laboratory methane spectra have previously been fit using a Malkmus band model. The laboratory spectra were obtained in three groups at temperatures averaging 112, 188, and 295 K; band model fitting was done separately for each temperature group. These band model parameters cannot be used directly in scattering atmosphere model computations, so an exponential sum model is being developed which includes pressure and temperature fitting parameters. The goal is to obtain model parameters by least square fits at 10/cm intervals from 3800 to 9100/cm. These results will be useful in the interpretation of current planetary spectra and also NIMS spectra of Jupiter anticipated from the Galileo mission.

Accuracy of patient specific organ-dose estimates obtained using an automated image segmentation algorithm

NASA Astrophysics Data System (ADS)

Gilat-Schmidt, Taly; Wang, Adam; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-03-01

The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Equation solver and automated CT segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. The investigated algorithm uses a combination of feature-based and atlas-based methods. A multiatlas approach was also investigated. We hypothesize that the auto-segmentation algorithm is sufficiently accurate to provide organ dose estimates since random errors at the organ boundaries will average out when computing the total organ dose. To test this hypothesis, twenty head-neck CT scans were expertly segmented into nine regions. A leave-one-out validation study was performed, where every case was automatically segmented with each of the remaining cases used as the expert atlas, resulting in nineteen automated segmentations for each of the twenty datasets. The segmented regions were applied to gold-standard Monte Carlo dose maps to estimate mean and peak organ doses. The results demonstrated that the fully automated segmentation algorithm estimated the mean organ dose to within 10% of the expert segmentation for regions other than the spinal canal, with median error for each organ region below 2%. In the spinal canal region, the median error was 7% across all data sets and atlases, with a maximum error of 20%. The error in peak organ dose was below 10% for all regions, with a median error below 4% for all organ regions. The multiple-case atlas reduced the variation in the dose estimates and additional improvements may be possible with more robust multi-atlas approaches. Overall, the results support potential feasibility of an automated segmentation algorithm to provide accurate organ dose estimates.

Estimation of reliable range of electron temperature measurements with sets of given optical bandpass filters for KSTAR Thomson scattering system based on synthetic Thomson data

NASA Astrophysics Data System (ADS)

Kim, K.-h.; Oh, T.-s.; Park, K.-r.; Lee, J. H.; Ghim, Y.-c.

2017-11-01

One factor determining the reliability of measurements of electron temperature using a Thomson scattering (TS) system is transmittance of the optical bandpass filters in polychromators. We investigate the system performance as a function of electron temperature to determine reliable range of measurements for a given set of the optical bandpass filters. We show that such a reliability, i.e., both bias and random errors, can be obtained by building a forward model of the KSTAR TS system to generate synthetic TS data with the prescribed electron temperature and density profiles. The prescribed profiles are compared with the estimated ones to quantify both bias and random errors.

Time and temperature dependent modulus of pyrrone and polyimide moldings

NASA Technical Reports Server (NTRS)

Lander, L. L.

1972-01-01

A method is presented by which the modulus obtained from a stress relaxation test can be used to estimate the modulus which would be obtained from a sonic vibration test. The method was applied to stress relaxation, sonic vibration, and high speed stress-strain data which was obtained on a flexible epoxy. The modulus as measured by the three test methods was identical for identical test times, and a change of test temperature was equivalent to a shift in the logarithmic time scale. An estimate was then made of the dynamic modulus of moldings of two Pyrrones and two polyimides, using stress relaxation data and the method of analysis which was developed for the epoxy. Over the common temperature range (350 to 500 K) in which data from both types of tests were available, the estimated dynamic modulus value differed by only a few percent from the measured value. As a result, it is concluded that, over the 500 to 700 K temperature range, the estimated dynamic modulus values are accurate.

EQUILGAS: Program to estimate temperatures and in situ two-phase conditions in geothermal reservoirs using three combined FT-HSH gas equilibria models

NASA Astrophysics Data System (ADS)

Barragán, Rosa María; Núñez, José; Arellano, Víctor Manuel; Nieva, David

2016-03-01

Exploration and exploitation of geothermal resources require the estimation of important physical characteristics of reservoirs including temperatures, pressures and in situ two-phase conditions, in order to evaluate possible uses and/or investigate changes due to exploitation. As at relatively high temperatures (>150 °C) reservoir fluids usually attain chemical equilibrium in contact with hot rocks, different models based on the chemistry of fluids have been developed that allow deep conditions to be estimated. Currently either in water-dominated or steam-dominated reservoirs the chemistry of steam has been useful for working out reservoir conditions. In this context, three methods based on the Fischer-Tropsch (FT) and combined H2S-H2 (HSH) mineral-gas reactions have been developed for estimating temperatures and the quality of the in situ two-phase mixture prevailing in the reservoir. For these methods the mineral buffers considered to be controlling H2S-H2 composition of fluids are as follows. The pyrite-magnetite buffer (FT-HSH1); the pyrite-hematite buffer (FT-HSH2) and the pyrite-pyrrhotite buffer (FT-HSH3). Currently from such models the estimations of both, temperature and steam fraction in the two-phase fluid are obtained graphically by using a blank diagram with a background theoretical solution as reference. Thus large errors are involved since the isotherms are highly nonlinear functions while reservoir steam fractions are taken from a logarithmic scale. In order to facilitate the use of the three FT-HSH methods and minimize visual interpolation errors, the EQUILGAS program that numerically solves the equations of the FT-HSH methods was developed. In this work the FT-HSH methods and the EQUILGAS program are described. Illustrative examples for Mexican fields are also given in order to help the users in deciding which method could be more suitable for every specific data set.

Characterization of dynamics in complex lyophilized formulations: I. Comparison of relaxation times measured by isothermal calorimetry with data estimated from the width of the glass transition temperature region.

PubMed

Chieng, Norman; Mizuno, Masayasu; Pikal, Michael

2013-10-01

The purposes of this study are to characterize the relaxation dynamics in complex freeze dried formulations and to investigate the quantitative relationship between the structural relaxation time as measured by thermal activity monitor (TAM) and that estimated from the width of the glass transition temperature (ΔT(g)). The latter method has advantages over TAM because it is simple and quick. As part of this objective, we evaluate the accuracy in estimating relaxation time data at higher temperatures (50 °C and 60 °C) from TAM data at lower temperature (40 °C) and glass transition region width (ΔT(g)) data obtained by differential scanning calorimetry. Formulations studied here were hydroxyethyl starch (HES)-disaccharide, HES-polyol, and HES-disaccharide-polyol at various ratios. We also re-examine, using TAM derived relaxation times, the correlation between protein stability (human growth hormone, hGH) and relaxation times explored in a previous report, which employed relaxation time data obtained from ΔT(g). Results show that most of the freeze dried formulations exist in single amorphous phase, and structural relaxation times were successfully measured for these systems. We find a reasonably good correlation between TAM measured relaxation times and corresponding data obtained from estimates based on ΔT(g), but the agreement is only qualitative. The comparison plot showed that TAM data are directly proportional to the 1/3 power of ΔT(g) data, after correcting for an offset. Nevertheless, the correlation between hGH stability and relaxation time remained qualitatively the same as found with using ΔT(g) derived relaxation data, and it was found that the modest extrapolation of TAM data to higher temperatures using ΔT(g) method and TAM data at 40 °C resulted in quantitative agreement with TAM measurements made at 50 °C and 60 °C, provided the TAM experiment temperature, is well below the Tg of the sample. Copyright © 2013 Elsevier B.V. All rights

Characterization of Dynamics in Complex Lyophilized Formulations: I. Comparison of Relaxation Times Measured by Isothermal Calorimetry with Data Estimated from the Width of the Glass Transition Temperature Region

PubMed Central

Chieng, Norman; Mizuno, Masayasu; Pikal, Michael

2013-01-01

The purposes of this study are to characterize the relaxation dynamics in complex freeze dried formulations and to investigate the quantitative relationship between the structural relaxation time as measured by thermal activity monitor (TAM) and that estimated from the width of the glass transition temperature (ΔTg). The latter method has advantages over TAM because it is simple and quick. As part of this objective, we evaluate the accuracy in estimating relaxation time data at higher temperatures (50°C and 60°C) from TAM data at lower temperature (40°C) and glass transition region width (ΔTg) data obtained by differential scanning calorimetry. Formulations studied here were hydroxyethyl starch (HES)-disaccharide, HES-polyol and HES-disaccharide-polyol at various ratios. We also re-examine, using TAM derived relaxation times, the correlation between protein stability (human growth hormone, hGH) and relaxation times explored in a previous report, which employed relaxation time data obtained from ΔTg. Results show that most of the freeze dried formulations exist in single amorphous phase, and structural relaxation times were successfully measured for these systems. We find a reasonably good correlation between TAM measured relaxation times and corresponding data obtained from estimates based on ΔTg, but the agreement is only qualitative. The comparison plot showed that TAM data is directly proportional to the 1/3 power of ΔTg data, after correcting for an offset. Nevertheless, the correlation between hGH stability and relaxation time remained qualitatively the same as found with using ΔTg derived relaxation data, and it was found that the modest extrapolation of TAM data to higher temperatures using ΔTg method and TAM data at 40°C resulted in quantitative agreement with TAM measurements made at 50 °C and 60 °C, provided the TAM experiment temperature is well below the Tg of the sample. PMID:23608636

Systematic errors in temperature estimates from MODIS data covering the western Palearctic and their impact on a parasite development model.

PubMed

Alonso-Carné, Jorge; García-Martín, Alberto; Estrada-Peña, Agustin

2013-11-01

The modelling of habitat suitability for parasites is a growing area of research due to its association with climate change and ensuing shifts in the distribution of infectious diseases. Such models depend on remote sensing data and require accurate, high-resolution temperature measurements. The temperature is critical for accurate estimation of development rates and potential habitat ranges for a given parasite. The MODIS sensors aboard the Aqua and Terra satellites provide high-resolution temperature data for remote sensing applications. This paper describes comparative analysis of MODIS-derived temperatures relative to ground records of surface temperature in the western Palaearctic. The results show that MODIS overestimated maximum temperature values and underestimated minimum temperatures by up to 5-6 °C. The combined use of both Aqua and Terra datasets provided the most accurate temperature estimates around latitude 35-44° N, with an overestimation during spring-summer months and an underestimation in autumn-winter. Errors in temperature estimation were associated with specific ecological regions within the target area as well as technical limitations in the temporal and orbital coverage of the satellites (e.g. sensor limitations and satellite transit times). We estimated error propagation of temperature uncertainties in parasite habitat suitability models by comparing outcomes of published models. Error estimates reached 36% of annual respective measurements depending on the model used. Our analysis demonstrates the importance of adequate image processing and points out the limitations of MODIS temperature data as inputs into predictive models concerning parasite lifecycles.

An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions, Addendum

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Walker, H. F.

1975-01-01

New results and insights concerning a previously published iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions were discussed. It was shown that the procedure converges locally to the consistent maximum likelihood estimate as long as a specified parameter is bounded between two limits. Bound values were given to yield optimal local convergence.

Comparison of MODIS-derived land surface temperature with air temperature measurements

NASA Astrophysics Data System (ADS)

Georgiou, Andreas; Akçit, Nuhcan

2017-09-01

Air surface temperature is an important parameter for a wide range of applications such as agriculture, hydrology and climate change studies. Air temperature data is usually obtained from measurements made in meteorological stations, providing only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of air surface temperature at both regional and global scales. Land Surface (skin) Temperatures (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to groundbased near surface air (Tair) measurements obtained from 14 observational stations during 2011 to 2015, covering coastal, mountainous and urban areas over Cyprus. Combining Terra and Aqua LST-8 Day and Night acquisitions into a mean monthly value, provide a large number of LST observations and a better overall agreement with Tair. Comparison between mean monthly LSTs and mean monthly Tair for all sites and all seasons pooled together yields a very high correlation and biases. In addition, the presented high standard deviation can be explained by the influence of surface heterogeneity within MODIS 1km2 grid cells, the presence of undetected clouds and the inherent difference between LST and Tair. However, MODIS LST data proved to be a reliable proxy for surface temperature and mostly for studies requiring temperature reconstruction in areas with lack of observational stations.

New Correction Factors Based on Seasonal Variability of Outdoor Temperature for Estimating Annual Radon Concentrations in UK.

PubMed

Daraktchieva, Z

2017-06-01

Indoor radon concentrations generally vary with season. Radon gas enters buildings from beneath due to a small air pressure difference between the inside of a house and outdoors. This underpressure which draws soil gas including radon into the house depends on the difference between the indoor and outdoor temperatures. The variation in a typical house in UK showed that the mean indoor radon concentration reaches a maximum in January and a minimum in July. Sine functions were used to model the indoor radon data and monthly average outdoor temperatures, covering the period between 2005 and 2014. The analysis showed a strong negative correlation between the modelled indoor radon data and outdoor temperature. This correlation was used to calculate new correction factors that could be used for estimation of annual radon concentration in UK homes. The comparison between the results obtained with the new correction factors and the previously published correction factors showed that the new correction factors perform consistently better on the selected data sets. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Estimation of the biphasic property in a female's menstrual cycle from cutaneous temperature measured during sleep.

PubMed

Chen, Wenxi; Kitazawa, Masumi; Togawa, Tatsuo

2009-09-01

This paper proposes a method to estimate a woman's menstrual cycle based on the hidden Markov model (HMM). A tiny device was developed that attaches around the abdominal region to measure cutaneous temperature at 10-min intervals during sleep. The measured temperature data were encoded as a two-dimensional image (QR code, i.e., quick response code) and displayed in the LCD window of the device. A mobile phone captured the QR code image, decoded the information and transmitted the data to a database server. The collected data were analyzed by three steps to estimate the biphasic temperature property in a menstrual cycle. The key step was an HMM-based step between preprocessing and postprocessing. A discrete Markov model, with two hidden phases, was assumed to represent higher- and lower-temperature phases during a menstrual cycle. The proposed method was verified by the data collected from 30 female participants, aged from 14 to 46, over six consecutive months. By comparing the estimated results with individual records from the participants, 71.6% of 190 menstrual cycles were correctly estimated. The sensitivity and positive predictability were 91.8 and 96.6%, respectively. This objective evaluation provides a promising approach for managing premenstrual syndrome and birth control.

Shallow subsurface temperatures and some estimates of heat flow from the Colorado Plateau of northeastern Arizona

USGS Publications Warehouse

Sass, J.H.; Stone, Claudia; Bills, D.J.

1982-01-01

Temperature data to depths of a few hundred meters were obtained from 29 wells in northeastern Arizona; 12 in the region surrounding the San Francisco Volcanic Field, 8 in the Black Mesa area, and 9 in the south-central Colorado Plateau which includes the White Mountains. Although there was evidence for local hydrologic disturbances in many temperature profiles, most wells provided an estimate of the conductive thermal gradient at the site. A few thermal conductivities were measured and were combined with published regional averages for the north-central part of the Colorado Plateau to produce crude estimates of regional heat flux. None of the wells was accessible below the regional aquifers. To these depths, heat flow in the area of the San Francisco Volcanic Field appears to be controlled primarily by regional lateral water movement having a significant downward vertical component of velocity. The mean heat flow of 27?5 mW^-2 is only a third to a quarter of what we would expect in this tectonic setting. The heat that is being carried laterally and downward probably is being discharged at low enthalpy and low elevation in springs and streams of the Colorado Plateau and Mogollon Rim. In the vicinity of Black Mesa, heat-flow averages about 60 mW^-2, characteristic of the 'cool interior' of the Colorado Plateau. North of the White Mountain Volcanic Field, the average heat flow is about 95 mW^-2.

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor

PubMed Central

Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-01-01

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times. PMID:29393862

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor.

PubMed

Li, Xin; Ou, Xingtao; Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-02-02

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘ C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

Estimation of the lower flammability limit of organic compounds as a function of temperature.

PubMed

Rowley, J R; Rowley, R L; Wilding, W V

2011-02-15

A new method of estimating the lower flammability limit (LFL) of general organic compounds is presented. The LFL is predicted at 298 K for gases and the lower temperature limit for solids and liquids from structural contributions and the ideal gas heat of formation of the fuel. The average absolute deviation from more than 500 experimental data points is 10.7%. In a previous study, the widely used modified Burgess-Wheeler law was shown to underestimate the effect of temperature on the lower flammability limit when determined in a large-diameter vessel. An improved version of the modified Burgess-Wheeler law is presented that represents the temperature dependence of LFL data determined in large-diameter vessels more accurately. When the LFL is estimated at increased temperatures using a combination of this model and the proposed structural-contribution method, an average absolute deviation of 3.3% is returned when compared with 65 data points for 17 organic compounds determined in an ASHRAE-style apparatus. Copyright © 2010 Elsevier B.V. All rights reserved.

Miocene Surface Temperature Estimates of the Southern Altiplano and Their Implications for Surface Uplift

NASA Astrophysics Data System (ADS)

Smith, J. J.; Garzione, C.; Higgins, P.; MacFadden, B.; Auerbach, D.; Croft, D.

2008-12-01

Surface temperature estimates derived from stable isotopes can be used to infer tectonic history and subsequent climate change of the Bolivian Altiplano. This study compares surface temperatures calculated from two fossil localities (Cerdas and Quehua) that span middle to late Miocene age in the southern Altiplano. Temperatures were calculated using the approach of Zanazzi et al. (2007) by comparing the stable isotopes of fossil tooth enamel and concurrent fossilized bones. The δ18O of the surface water is derived from fossil tooth enamel that mineralized at a known mammal body temperature. Surface water compositions are then used to calculate the temperature at which fossil bones were diagenetically altered, using the assumption that most alteration of fossil bones occurs within 20 to 50 thousand years of deposition. These surface temperature estimates can be used as a proxy for the amount of surface uplift based on modern temperature lapse rates. The vertical surface temperature gradient observed in the present-day Andes is about 4.66°C/km. Changes in surface elevations may explain large temperature changes reflected throughout the middle to late Miocene. Cerdas and Quehua, at modern elevations of ~3800m, have fossil records that include teeth and diagenetically altered bones that were deposited before and during a period of inferred rapid surface uplift of the northern Altiplano of 2.5 ± 1 km between ~10 to 6 Ma. Both sites have been dated by magnetostratigraphy and by 40Ar/39Ar dating of tuffs: Cerdas dates from 16.358 ± 0.071 to 15.105 ± 0.073 Ma, and Quehua ranges from 12.611 ± 0.034 to 6.844 ± 0.386 Ma. The close proximity and current elevation of Cerdas (21.9°S, 3800m) and Quehua (20.0°S, 3800m) allows for the assumption that their elevations were closely correlated through time. Thus the temperatures and elevation estimates derived from each location are assumed to reflect the larger extent of the southern Altiplano. If analysis of fossil enamel

Challenges in Obtaining Estimates of the Risk of Tuberculosis Infection During Overseas Deployment.

PubMed

Mancuso, James D; Geurts, Mia

2015-12-01

Estimates of the risk of tuberculosis (TB) infection resulting from overseas deployment among U.S. military service members have varied widely, and have been plagued by methodological problems. The purpose of this study was to estimate the incidence of TB infection in the U.S. military resulting from deployment. Three populations were examined: 1) a unit of 2,228 soldiers redeploying from Iraq in 2008, 2) a cohort of 1,978 soldiers followed up over 5 years after basic training at Fort Jackson in 2009, and 3) 6,062 participants in the 2011-2012 National Health and Nutrition Examination Survey (NHANES). The risk of TB infection in the deployed population was low-0.6% (95% confidence interval [CI]: 0.1-2.3%)-and was similar to the non-deployed population. The prevalence of latent TB infection (LTBI) in the U.S. population was not significantly different among deployed and non-deployed veterans and those with no military service. The limitations of these retrospective studies highlight the challenge in obtaining valid estimates of risk using retrospective data and the need for a more definitive study. Similar to civilian long-term travelers, risks for TB infection during deployment are focal in nature, and testing should be targeted to only those at increased risk. © The American Society of Tropical Medicine and Hygiene.

Electrical properties of Si-Si interfaces obtained by room temperature covalent wafer bonding

NASA Astrophysics Data System (ADS)

Jung, A.; Zhang, Y.; Arroyo Rojas Dasilva, Y.; Isa, F.; von Känel, H.

2018-02-01

We study covalent bonds between p-doped Si wafers (resistivity ˜10 Ω cm) fabricated on a recently developed 200 mm high-vacuum system. Oxide- and void free interfaces were obtained by argon (Ar) or neon (Ne) sputtering prior to wafer bonding at room temperature. The influence of the sputter induced amorphous Si layer at the bonding interface on the electrical behavior is accessed with temperature-dependent current-voltage measurements. In as-bonded structures, charge transport is impeded by a potential barrier of 0.7 V at the interface with thermionic emission being the dominant charge transport mechanism. Current-voltage characteristics are found to be asymmetric which can tentatively be attributed to electric dipole formation at the interface as a result of the time delay between the surface preparation of the two bonding partners. Electron beam induced current measurements confirm the corresponding asymmetric double Schottky barrier like band-alignment. Moreover, we demonstrate that defect annihilation at a low temperature of 400 °C increases the electrical conductivity by up to three orders of magnitude despite the lack of recrystallization of the amorphous layer. This effect is found to be more pronounced for Ne sputtered surfaces which is attributed to the lighter atomic mass compared to Ar, inducing weaker lattice distortions during the sputtering.

Temperature Observation Time and Type Influence Estimates of Heat-Related Mortality in Seven U.S. Cities

PubMed Central

Davis, Robert E.; Hondula, David M.; Patel, Anjali P.

2015-01-01

Background: Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat–mortality relationships. Objectives: We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method. Methods: Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series. Results: In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature–mortality relationships were associated with maximum temperature, although mean temperature results were comparable. Conclusions: There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature–mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat

Estimating surface temperature in forced convection nucleate boiling - A simplified method

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Papell, S. S.

1977-01-01

A simplified expression to estimate surface temperatures in forced convection boiling was developed using a liquid nitrogen data base. Using the principal of corresponding states and the Kutateladze relation for maximum pool boiling heat flux, the expression was normalized for use with other fluids. The expression was applied also to neon and water. For the neon data base, the agreement was acceptable with the exclusion of one set suspected to be in the transition boiling regime. For the water data base at reduced pressure greater than 0.05 the agreement is generally good. At lower reduced pressures, the water data scatter and the calculated temperature becomes a function of flow rate.

Temperature estimation from hydroxyl airglow emission in the Venus night side mesosphere

NASA Astrophysics Data System (ADS)

Migliorini, A.; Snels, M.; Gérard, J.-C.; Soret, L.; Piccioni, G.; Drossart, P.

2018-01-01

The temperature of the night side of Venus at about 95 km has been determined by using spectral features of the hydroxyl airglow emission around 3 μm, recorded from July 2006 to July 2008 by VIRTIS onboard Venus Express. The retrieved temperatures vary from 145.5 to about 198.1 K with an average value of 176.3 ± 14.3 K and are in good agreement with previous ground-based and space observations. The variability with respect to latitude and local time has been studied, showing a minimum of temperature at equatorial latitudes, while temperature values increase toward mid latitudes with a local maximum at about 35°N. The present work provides an independent contribution to the temperature estimation in the transition region between the Venus upper mesosphere and the lower thermosphere, by using the OH emission as a thermometer, following the technique previously applied to the high-resolution O2(a1Δg) airglow emissions observed from ground.

Temperature-dependent Development of Parasarcophaga similis (Meade 1876) and its Significance in Estimating Postmortem Interval.

PubMed

Yang, Lijun; Wang, Yu; Li, Liangliang; Wang, Jiangfeng; Wang, Min; Zhang, Yingna; Chu, Jun; Liu, Kun; Hou, Yiding; Tao, Luyang

2017-09-01

Flesh flies are commonly found insects on decaying corpses that appears slightly later than blowflies, and their development patterns are significant indicators for minimum postmortem interval (PMI min ) estimation. In this study, the flesh fly Parasarcophaga similis (Meade 1876) was reared at nine constant temperatures ranging from 15°C to 35°C to examine indicators for estimating their age. We generated three development models, including isomorphen diagram, isomegalen diagram, and thermal summation model. Larval body length at different rearing temperatures was fit into an L = a + bT + cT 2 + dT 3 equation with which the relationship between the larval body length (L) and the time after larviposition (T) was confirmed. The pupal stage was categorized into 13 substages according to intrapuparial morphological changes, and a detailed table was generated of the pupal developmental stages at five rearing temperatures, 15°C, 20°C, 25°C, 30°C, and 35°C. This study provides fundamental data in supporting P. similis as an indicator for PMI min estimation. © 2017 American Academy of Forensic Sciences.

Unveiling acoustic physics of the CMB using nonparametric estimation of the temperature angular power spectrum for Planck

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aghamousa, Amir; Shafieloo, Arman; Arjunwadkar, Mihir

2015-02-01

Estimation of the angular power spectrum is one of the important steps in Cosmic Microwave Background (CMB) data analysis. Here, we present a nonparametric estimate of the temperature angular power spectrum for the Planck 2013 CMB data. The method implemented in this work is model-independent, and allows the data, rather than the model, to dictate the fit. Since one of the main targets of our analysis is to test the consistency of the ΛCDM model with Planck 2013 data, we use the nuisance parameters associated with the best-fit ΛCDM angular power spectrum to remove foreground contributions from the data atmore » multipoles ℓ ≥50. We thus obtain a combined angular power spectrum data set together with the full covariance matrix, appropriately weighted over frequency channels. Our subsequent nonparametric analysis resolves six peaks (and five dips) up to ℓ ∼1850 in the temperature angular power spectrum. We present uncertainties in the peak/dip locations and heights at the 95% confidence level. We further show how these reflect the harmonicity of acoustic peaks, and can be used for acoustic scale estimation. Based on this nonparametric formalism, we found the best-fit ΛCDM model to be at 36% confidence distance from the center of the nonparametric confidence set—this is considerably larger than the confidence distance (9%) derived earlier from a similar analysis of the WMAP 7-year data. Another interesting result of our analysis is that at low multipoles, the Planck data do not suggest any upturn, contrary to the expectation based on the integrated Sachs-Wolfe contribution in the best-fit ΛCDM cosmology.« less

Uncertainty in temperature response of current consumption-based emissions estimates

NASA Astrophysics Data System (ADS)

Karstensen, J.; Peters, G. P.; Andrew, R. M.

2015-05-01

Several studies have connected emissions of greenhouse gases to economic and trade data to quantify the causal chain from consumption to emissions and climate change. These studies usually combine data and models originating from different sources, making it difficult to estimate uncertainties along the entire causal chain. We estimate uncertainties in economic data, multi-pollutant emission statistics, and metric parameters, and use Monte Carlo analysis to quantify contributions to uncertainty and to determine how uncertainty propagates to estimates of global temperature change from regional and sectoral territorial- and consumption-based emissions for the year 2007. We find that the uncertainties are sensitive to the emission allocations, mix of pollutants included, the metric and its time horizon, and the level of aggregation of the results. Uncertainties in the final results are largely dominated by the climate sensitivity and the parameters associated with the warming effects of CO2. Based on our assumptions, which exclude correlations in the economic data, the uncertainty in the economic data appears to have a relatively small impact on uncertainty at the national level in comparison to emissions and metric uncertainty. Much higher uncertainties are found at the sectoral level. Our results suggest that consumption-based national emissions are not significantly more uncertain than the corresponding production-based emissions since the largest uncertainties are due to metric and emissions which affect both perspectives equally. The two perspectives exhibit different sectoral uncertainties, due to changes of pollutant compositions. We find global sectoral consumption uncertainties in the range of ±10 to ±27 % using the Global Temperature Potential with a 50-year time horizon, with metric uncertainties dominating. National-level uncertainties are similar in both perspectives due to the dominance of CO2 over other pollutants. The consumption emissions of the top

The color temperature of (2060) Chiron: A warm and small nucleus

NASA Technical Reports Server (NTRS)

Campins, H.; Telesco, C. M.; Osip, D. J.; Rieke, G. H.; Rieke, M. J.; Schulz, B.

1994-01-01

We present three sets of thermal-infrared observations of (2060) Chiron, obtained in 1991, 1993, and 1994. These observations allow the first estimates of the color temperature of Chiron as well as refined estimates of the radius and albedo of its nucleus. 10/20 micrometer color temperatures of 126(sub -6 sup +11) and 137(sub -9 sup +14) K are obtained from the 1993 and 1994 observations, respectively. These temperatures are consistent with the Standard Thermal Model (STM; Lebofsky & Spencer, 1989), but significantly higher than those predicted by the Isothermal Latitude Model. Our estimates of Chiron's radius based on the STM are in agreement with each other, with the observations of Lebofsky et al. (1984), and with recent occultation results (Buie et al., (1993). We obtained values for the radius of 74 +/- 11 km in 1991, 88 +/- 10 and 104 +/- 10 km in 1993, and, 94 +/- 6 and 91 +/- 13 km in 1994.

ESTIMATION OF CRACK-ARREST TOUGHNESS TRANSITION AND NDT TEMPERATURES FROM CHARPY FORCE-DISPLACEMENT IMPACT TRACES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sokolov, Mikhail A

2010-01-01

A force-displacement trace of a Charpy impact test of a reactor pressure vessel (RPV) steel in the transition range has a characteristic point, the so-called force at the end of unstable crack propagation , Fa. A two-parameter Weibull probability function is used to model the distribution of the Fa in Charpy tests performed at ORNL on different RPV steels in the unirradiated and irradiated conditions. These data have a good replication at a given test temperature, thus, the statistical analysis was applicable. It is shown that when temperature is normalized to TNDT (T-TNDT) or to T100a (T-T100a), the median Famore » values of different RPV steels have a tendency to form the same shape of temperature dependence. Depending on normalization temperature, TNDT or T100a, it suggests a universal shape of the temperature dependence of Fa for different RPV steels. The best fits for these temperature dependencies are presented. These dependencies are suggested for use in estimation of NDT or T100a from randomly generated Charpy impact tests. The maximum likelihood methods are used to derive equations to estimate TNDT and T100a from randomly generated Charpy impact tests.« less

Tympanic temperature versus temporal temperature in patients with pyrexia and chills

PubMed Central

Yang, Wen-Chieh; Kuo, Huang-Tsung; Lin, Ching-Hsiao; Wu, Kang-Hsi; Chang, Yu-Jun; Chen, Chun-Yu; Wu, Han-Ping

2016-01-01

Abstract Accurate body temperature (BT) measurement is critical for immediate and correct estimation of core BT; measurement of changes in BT can provide physicians the initial information for selecting appropriate diagnostic approach and may prevent unnecessary diagnostic investigation. This study aimed to assess differences in tympanic and temporal temperatures among patients with fever in different conditions, especially in those with and without chills. This prospective study included patients from the emergency department between 2011 and 2012. All temperature measurements were obtained using tympanic thermometers and infrared skin thermometers. Differences in tympanic and temporal temperatures were analyzed according to 6 age groups, 5 ambient temperature groups, and 6 tympanic and temporal temperature subgroups. General linear model analysis and receiver operating characteristic curve analysis were used to estimate the differences in mean tympanic and temporal temperatures. Of the 710 patients enrolled, 246 had tympanic temperature more than 38.0°C, including 46 with chills (18.7%). Fourteen patients (3.0%) had chills and tympanic temperature less than 38°C. In the tympanic temperature subgroup of 39.0 to less than 39.5°C, approximately one-third of the patients had chills (32.3%). In the tympanic temperature subgroup of 38.0 to less than 39.0°C, the tympanic temperature was 0.4°C higher than the temporal temperature in patients without chills and 0.9°C higher in patients with chills. In the tympanic temperature subgroup of 39.0°C or more, tympanic temperature was 0.7°C higher than temporal temperature in patients without chills and 0.8°C higher in patients with chills. Temporal thermometer is more reliable in the age group of less than 1 year and 18 to less than 65 years. When the patients show tympanic temperature range of 38.0 to less than 39.0°C, 0.4°C should be added for patients without chills and 0.9°C for patients with chills to obtain

Estimation of stream temperature in support of fish production modeling under future climates in the Klamath River Basin

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.

2012-01-01

Stream temperature estimates under future climatic conditions were needed in support of fish production modeling for evaluation of effects of dam removal in the Klamath River Basin. To allow for the persistence of the Klamath River salmon fishery, an upcoming Secretarial Determination in 2012 will review potential changes in water quality and stream temperature to assess alternative scenarios, including dam removal. Daily stream temperature models were developed by using a regression model approach with simulated net solar radiation, vapor density deficit calculated on the basis of air temperature, and mean daily air temperature. Models were calibrated for 6 streams in the Lower, and 18 streams in the Upper, Klamath Basin by using measured stream temperatures for 1999-2008. The standard error of the y-estimate for the estimation of stream temperature for the 24 streams ranged from 0.36 to 1.64°C, with an average error of 1.12°C for all streams. The regression models were then used with projected air temperatures to estimate future stream temperatures for 2010-99. Although the mean change from the baseline historical period of 1950-99 to the projected future period of 2070-99 is only 1.2°C, it ranges from 3.4°C for the Shasta River to no change for Fall Creek and Trout Creek. Variability is also evident in the future with a mean change in temperature for all streams from the baseline period to the projected period of 2070-99 of only 1°C, while the range in stream temperature change is from 0 to 2.1°C. The baseline period, 1950-99, to which the air temperature projections were corrected, established the starting point for the projected changes in air temperature. The average measured daily air temperature for the calibration period 1999-2008, however, was found to be as much as 2.3°C higher than baseline for some rivers, indicating that warming conditions have already occurred in many areas of the Klamath River Basin, and that the stream temperature

Estimation and Modelling of Land Surface Temperature Using Landsat 7 ETM+ Images and Fuzzy System Techniques

NASA Astrophysics Data System (ADS)

Bisht, K.; Dodamani, S. S.

2016-12-01

Modelling of Land Surface Temperature is essential for short term and long term management of environmental studies and management activities of the Earth's resources. The objective of this research is to estimate and model Land Surface Temperatures (LST). For this purpose, Landsat 7 ETM+ images period from 2007 to 2012 were used for retrieving LST and processed through MATLAB software using Mamdani fuzzy inference systems (MFIS), which includes pre-monsoon and post-monsoon LST in the fuzzy model. The Mangalore City of Karnataka state, India has been taken for this research work. Fuzzy model inputs are considered as the pre-monsoon and post-monsoon retrieved temperatures and LST was chosen as output. In order to develop a fuzzy model for LST, seven fuzzy subsets, nineteen rules and one output are considered for the estimation of weekly mean air temperature. These are very low (VL), low (L), medium low (ML), medium (M), medium high (MH), high (H) and very high (VH). The TVX (Surface Temperature Vegetation Index) and the empirical method have provided estimated LST. The study showed that the Fuzzy model M4/7-19-1 (model 4, 7 fuzzy sets, 19 rules and 1 output) which developed over Mangalore City has provided more accurate outcomes than other models (M1, M2, M3, M5). The result of this research was evaluated according to statistical rules. The best correlation coefficient (R) and root mean squared error (RMSE) between estimated and measured values for pre-monsoon and post-monsoon LST found to be 0.966 - 1.607 K and 0.963- 1.623 respectively.

The first step toward genetic selection for host tolerance to infectious pathogens: obtaining the tolerance phenotype through group estimates

PubMed Central

Doeschl-Wilson, Andrea B.; Villanueva, Beatriz; Kyriazakis, Ilias

2012-01-01

Reliable phenotypes are paramount for meaningful quantification of genetic variation and for estimating individual breeding values on which genetic selection is based. In this paper, we assert that genetic improvement of host tolerance to disease, although desirable, may be first of all handicapped by the ability to obtain unbiased tolerance estimates at a phenotypic level. In contrast to resistance, which can be inferred by appropriate measures of within host pathogen burden, tolerance is more difficult to quantify as it refers to change in performance with respect to changes in pathogen burden. For this reason, tolerance phenotypes have only been specified at the level of a group of individuals, where such phenotypes can be estimated using regression analysis. However, few stsudies have raised the potential bias in these estimates resulting from confounding effects between resistance and tolerance. Using a simulation approach, we demonstrate (i) how these group tolerance estimates depend on within group variation and co-variation in resistance, tolerance, and vigor (performance in a pathogen free environment); and (ii) how tolerance estimates are affected by changes in pathogen virulence over the time course of infection and by the timing of measurements. We found that in order to obtain reliable group tolerance estimates, it is important to account for individual variation in vigor, if present, and that all individuals are at the same stage of infection when measurements are taken. The latter requirement makes estimation of tolerance based on cross-sectional field data challenging, as individuals become infected at different time points and the individual onset of infection is unknown. Repeated individual measurements of within host pathogen burden and performance would not only be valuable for inferring the infection status of individuals in field conditions, but would also provide tolerance estimates that capture the entire time course of infection. PMID

Venus: estimates of the surface temperature and pressure from radio and radar measurements.

PubMed

Wood, A T; Wattson, R B; Pollack, J B

1968-10-04

The radio brightness temperature and radar cross section spectra of Venus are in much better accord with surface boundary conditions deduced from a combination of the Mariner V results and the radar radius than those obtained by the Venera 4 space probe. The average surface temperature and pressure are approximately 750 degrees K and 90 atmospheres.

Water surface temperature estimation from Landsat 7 ETM+ thermal infrared data using the generalized single-channel method: Case study of Embalse del Río Tercero (Córdoba, Argentina)

NASA Astrophysics Data System (ADS)

Lamaro, Anabel Alejandra; Mariñelarena, Alejandro; Torrusio, Sandra Edith; Sala, Silvia Estela

2013-02-01

Monitoring of warm distribution in water is fundamental to understand the performance and functioning of reservoirs and lakes. Surface water temperature is a key parameter in the physics of aquatic systems processes since it is closely related to the energy fluxes through the water-atmosphere interface. Remote sensing applied to water quality studies in inland waterbodies is a powerful tool that can provide additional information difficult to achieve by other means. The combination of good real-time coverage, spatial resolution and free availability of data makes Landsat system a proper alternative. Many papers have developed algorithms to retrieve surface temperature (principally, land surface temperature) from at-sensor and surface emissivity data. The aim of this study is to apply the single-channel generalized method (SCGM) developed by Jiménez-Muñoz and Sobrino (2003) for the estimation of water surface temperature from Landsat 7 ETM+ thermal bands. We consider a constant water emissivity value (0.9885) and we compare the results with radiative transfer classic method (RTM). We choose Embalse del Río Tercero (Córdoba, Argentina) as case study because it is a reservoir affected by the outlet of the cooling system of a nuclear power plant, whose thermal plume could influence the biota's distribution and biodiversity. These characteristics and the existence of long term studies make it an adequate place to test the methodology. Values of estimated and observed water surface temperatures obtained by the two compared methods were correlated applying a simple regression model. Correlation coefficients were significant (R2: 0.9498 for SCGM method and R2: 0.9584 for RTM method) while their standard errors were acceptable in both cases (SCGM method: RMS = 1.2250 and RTM method: RMS = 1.0426). Nevertheless, SCGM could estimate rather small differences in temperature between sites consistently with the results obtained in field measurements. Besides, it has the

Estimation of the activation energy in the Belousov-Zhabotinsky reaction by temperature effect on excitable waves.

PubMed

Zhang, Jinzhong; Zhou, Luqun; Ouyang, Qi

2007-02-15

We report the temperature effect on the propagation of excitable traveling waves in a quasi-two-dimensional Belousov-Zhabotinsky reaction-diffusion system. The onset of excitable waves as a function of the sulfuric acid concentration and temperature is identified, on which the sulfuric acid concentration exhibits an Arrhenius dependence on temperature. On the basis of this experimental data, the activation energy of the self-catalyzed reaction in the Oregonator model is estimated to be 83-113 kJ/mol, which is further supported by our numerical simulations. The estimation proceeds without analyzing detailed reaction steps but rather through observing the global dynamic behaviors in the BZ reaction. For a supplement, the wave propagation velocities are calculated based on our results and compared with the experimental observations.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

Estimates of the solar internal angular velocity obtained with the Mt. Wilson 60-foot solar tower

NASA Technical Reports Server (NTRS)

Rhodes, Edward J., Jr.; Cacciani, Alessandro; Woodard, Martin; Tomczyk, Steven; Korzennik, Sylvain

1987-01-01

Estimates are obtained of the solar internal angular velocity from measurements of the frequency splittings of p-mode oscillations. A 16-day time series of full-disk Dopplergrams obtained during July and August 1984 at the 60-foot tower telescope of the Mt. Wilson Observatory is analyzed. Power spectra were computed for all of the zonal, tesseral, and sectoral p-modes from l = 0 to 89 and for all of the sectoral p-modes from l = 90 to 200. A mean power spectrum was calculated for each degree up to 89. The frequency differences of all of the different nonzonal modes were calculated for these mean power spectra.

Interpreting Repeated Temperature-Depth Profiles for Groundwater Flow

NASA Astrophysics Data System (ADS)

Bense, Victor F.; Kurylyk, Barret L.; van Daal, Jonathan; van der Ploeg, Martine J.; Carey, Sean K.

2017-10-01

Temperature can be used to trace groundwater flows due to thermal disturbances of subsurface advection. Prior hydrogeological studies that have used temperature-depth profiles to estimate vertical groundwater fluxes have either ignored the influence of climate change by employing steady-state analytical solutions or applied transient techniques to study temperature-depth profiles recorded at only a single point in time. Transient analyses of a single profile are predicated on the accurate determination of an unknown profile at some time in the past to form the initial condition. In this study, we use both analytical solutions and a numerical model to demonstrate that boreholes with temperature-depth profiles recorded at multiple times can be analyzed to either overcome the uncertainty associated with estimating unknown initial conditions or to form an additional check for the profile fitting. We further illustrate that the common approach of assuming a linear initial temperature-depth profile can result in significant errors for groundwater flux estimates. Profiles obtained from a borehole in the Veluwe area, Netherlands in both 1978 and 2016 are analyzed for an illustrative example. Since many temperature-depth profiles were collected in the late 1970s and 1980s, these previously profiled boreholes represent a significant and underexploited opportunity to obtain repeat measurements that can be used for similar analyses at other sites around the world.

Estimation of metabolic energy expenditure from core temperature using a human thermoregulatory model.

PubMed

Welles, Alexander P; Buller, Mark J; Looney, David P; Rumpler, William V; Gribok, Andrei V; Hoyt, Reed W

2018-02-01

Human metabolic energy expenditure is critical to many scientific disciplines but can only be measured using expensive and/or restrictive equipment. The aim of this work is to determine whether the SCENARIO thermoregulatory model can be adapted to estimate metabolic rate (M) from core body temperature (T C ). To validate this method of M estimation, data were collected from fifteen test volunteers (age = 23 ± 3yr, height = 1.73 ± 0.07m, mass = 68.6 ± 8.7kg, body fat = 16.7 ± 7.3%; mean ± SD) who wore long sleeved nylon jackets and pants (I tot,clo = 1.22, I m = 0.41) during treadmill exercise tasks (32 trials; 7.8 ± 0.5km in 1h; air temp. = 22°C, 50% RH, wind speed = 0.35ms -1 ). Core body temperatures were recorded by ingested thermometer pill and M data were measured via whole room indirect calorimetry. Metabolic rate was estimated for 5min epochs in a two-step process. First, for a given epoch, a range of M values were input to the SCENARIO model and a corresponding range of T C values were output. Second, the output T C range value with the lowest absolute error relative to the observed T C for the given epoch was identified and its corresponding M range input was selected as the estimated M for that epoch. This process was then repeated for each subsequent remaining epoch. Root mean square error (RMSE), mean absolute error (MAE), and bias between observed and estimated M were 186W, 130 ± 174W, and 33 ± 183W, respectively. The RMSE for total energy expenditure by exercise period was 0.30 MJ. These results indicate that the SCENARIO model is useful for estimating M from T C when measurement is otherwise impractical. Published by Elsevier Ltd.

Spectroscopic ellipsometry analysis of nanocrystalline silicon carbide obtained at low temperature

NASA Astrophysics Data System (ADS)

Kerdiles, S.; Madelon, R.; Rizk, R.

2001-12-01

Thin films of silicon carbide obtained by hydrogen-reactive magnetron sputtering with various substrate temperatures TS (100-600 °C) were analysed by transmission electron microscopy (TEM) and spectroscopic ellipsometry (SE). The TEM images show evidence of the growth of hydrogenated nanocrystalline silicon carbide (nc-SiC:H) deposited at TS as low as 300 °C, with an average grain size of 4-5 nm. The SE spectra were reproduced by using the Forouhi-Bloomer model and assuming a 7 nm thick overlayer with a void fraction of 45%. The observed increase of the refractive index with TS is assigned to the improvement of both crystallinity and compactness of the layer. The expected increase of the optical gap seems to be offset by the drop of hydrogen content, leaving the gap unchanged. The fabrication and characteristics of nc-SiC:H/c-Si diode are finally described and the data indicate a good rectifying behaviour, together with a low leakage current.

Validation of Nimbus-7 temperature-humidity infrared radiometer estimates of cloud type and amount

NASA Technical Reports Server (NTRS)

Stowe, L. L.

1982-01-01

Estimates of clear and low, middle and high cloud amount in fixed geographical regions approximately (160 km) squared are being made routinely from 11.5 micron radiance measurements of the Nimbus-7 Temperature-Humidity Infrared Radiometer (THIR). The purpose of validation is to determine the accuracy of the THIR cloud estimates. Validation requires that a comparison be made between the THIR estimates of cloudiness and the 'true' cloudiness. The validation results reported in this paper use human analysis of concurrent but independent satellite images with surface meteorological and radiosonde observations to approximate the 'true' cloudiness. Regression and error analyses are used to estimate the systematic and random errors of THIR derived clear amount.

Estimation of sampling error uncertainties in observed surface air temperature change in China

NASA Astrophysics Data System (ADS)

Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun

2017-08-01

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.

The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review

PubMed Central

Arbuthnott, Katherine; Kovats, Sari; Hajat, Shakoor; Falloon, Pete

2017-01-01

Background and objectives Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research. Methods The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis. Results A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on

The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review.

PubMed

Sanderson, Michael; Arbuthnott, Katherine; Kovats, Sari; Hajat, Shakoor; Falloon, Pete

2017-01-01

Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research. The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis. A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have

Estimating water temperatures in small streams in western Oregon using neural network models

USGS Publications Warehouse

Risley, John C.; Roehl, Edwin A.; Conrads, Paul

2003-01-01

Artificial neural network models were developed to estimate water temperatures in small streams using data collected at 148 sites throughout western Oregon from June to September 1999. The sites were located on 1st-, 2nd-, or 3rd-order streams having undisturbed or minimally disturbed conditions. Data collected at each site for model development included continuous hourly water temperature and description of riparian habitat. Additional data pertaining to the landscape characteristics of the basins upstream of the sites were assembled using geographic information system (GIS) techniques. Hourly meteorological time series data collected at 25 locations within the study region also were assembled. Clustering analysis was used to partition 142 sites into 3 groups. Separate models were developed for each group. The riparian habitat, basin characteristic, and meteorological time series data were independent variables and water temperature time series were dependent variables to the models, respectively. Approximately one-third of the data vectors were used for model training, and the remaining two-thirds were used for model testing. Critical input variables included riparian shade, site elevation, and percentage of forested area of the basin. Coefficient of determination and root mean square error for the models ranged from 0.88 to 0.99 and 0.05 to 0.59 oC, respectively. The models also were tested and validated using temperature time series, habitat, and basin landscape data from 6 sites that were separate from the 142 sites that were used to develop the models. The models are capable of estimating water temperatures at locations along 1st-, 2nd-, and 3rd-order streams in western Oregon. The model user must assemble riparian habitat and basin landscape characteristics data for a site of interest. These data, in addition to meteorological data, are model inputs. Output from the models include simulated hourly water temperatures for the June to September period

Channel Temperature Estimates for Microwave AlGaN/GaN Power HEMTS on SiC and Sapphire

NASA Technical Reports Server (NTRS)

Freeman, Jon C.

2003-01-01

A simple technique to estimate the channel temperature of a generic AlGaN/GaN HEMTs on SiC or Sapphire, while incorporating temperature dependence of the thermal conductivity is presented. The procedure is validated b y comparing it's predictions with the experimentally measured temperatures in devices presented in three recently published articles.

An alternative estimation of the RF-enhanced plasma temperature during SPEAR artificial heating experiments: Early results

NASA Astrophysics Data System (ADS)

Vickers, H.; Baddeley, L.

2011-11-01

RF heating of the F region plasma at high latitudes has long been known to produce electron temperature increases that can vary from tens to hundreds of percent above the background, unperturbed level. In contrast, artificial ionospheric modification experiments conducted using the Space Plasma Exploration by Active Radar (SPEAR) heating facility on Svalbard have often failed to produce obvious enhancements in the electron temperatures when measured using the European Incoherent Scatter Svalbard radar (ESR), colocated with the heater. Contamination of the ESR ion line spectra by the zero-frequency purely growing mode (PGM) feature is known to persist at varying amplitudes throughout SPEAR heating, and such spectral features can lead to significant temperature underestimations when the incoherent scatter spectra are analyzed using conventional methods. In this study, we present the first results of applying a recently developed technique to correct the PGM-contaminated spectra to SPEAR-enhanced ESR spectra and derive an alternative estimate of the SPEAR-heated electron temperature. We discuss how the effectiveness of the spectrum corrections can be affected by the data variance, estimated over the integration period. The subsequent electron temperatures, inferred from corrected spectra, range from a few tens to a few hundred Kelvin above the average background temperature. These temperatures are found to be in reasonable agreement with the theoretical “enhanced” temperature, calculated for the peak of the stationary temperature perturbation profile, when realistic absorption effects are accounted for.

Multivariate estimation of the limit of detection by orthogonal partial least squares in temperature-modulated MOX sensors.

PubMed

Burgués, Javier; Marco, Santiago

2018-08-17

Metal oxide semiconductor (MOX) sensors are usually temperature-modulated and calibrated with multivariate models such as partial least squares (PLS) to increase the inherent low selectivity of this technology. The multivariate sensor response patterns exhibit heteroscedastic and correlated noise, which suggests that maximum likelihood methods should outperform PLS. One contribution of this paper is the comparison between PLS and maximum likelihood principal components regression (MLPCR) in MOX sensors. PLS is often criticized by the lack of interpretability when the model complexity increases beyond the chemical rank of the problem. This happens in MOX sensors due to cross-sensitivities to interferences, such as temperature or humidity and non-linearity. Additionally, the estimation of fundamental figures of merit, such as the limit of detection (LOD), is still not standardized in multivariate models. Orthogonalization methods, such as orthogonal projection to latent structures (O-PLS), have been successfully applied in other fields to reduce the complexity of PLS models. In this work, we propose a LOD estimation method based on applying the well-accepted univariate LOD formulas to the scores of the first component of an orthogonal PLS model. The resulting LOD is compared to the multivariate LOD range derived from error-propagation. The methodology is applied to data extracted from temperature-modulated MOX sensors (FIS SB-500-12 and Figaro TGS 3870-A04), aiming at the detection of low concentrations of carbon monoxide in the presence of uncontrolled humidity (chemical noise). We found that PLS models were simpler and more accurate than MLPCR models. Average LOD values of 0.79 ppm (FIS) and 1.06 ppm (Figaro) were found using the approach described in this paper. These values were contained within the LOD ranges obtained with the error-propagation approach. The mean LOD increased to 1.13 ppm (FIS) and 1.59 ppm (Figaro) when considering validation samples

Supersaturation Control using Analytical Crystal Size Distribution Estimator for Temperature Dependent in Nucleation and Crystal Growth Phenomena

NASA Astrophysics Data System (ADS)

Zahari, Zakirah Mohd; Zubaidah Adnan, Siti; Kanthasamy, Ramesh; Saleh, Suriyati; Samad, Noor Asma Fazli Abdul

2018-03-01

The specification of the crystal product is usually given in terms of crystal size distribution (CSD). To this end, optimal cooling strategy is necessary to achieve the CSD. The direct design control involving analytical CSD estimator is one of the approaches that can be used to generate the set-point. However, the effects of temperature on the crystal growth rate are neglected in the estimator. Thus, the temperature dependence on the crystal growth rate needs to be considered in order to provide an accurate set-point. The objective of this work is to extend the analytical CSD estimator where Arrhenius expression is employed to cover the effects of temperature on the growth rate. The application of this work is demonstrated through a potassium sulphate crystallisation process. Based on specified target CSD, the extended estimator is capable of generating the required set-point where a proposed controller successfully maintained the operation at the set-point to achieve the target CSD. Comparison with other cooling strategies shows a reduction up to 18.2% of the total number of undesirable crystals generated from secondary nucleation using linear cooling strategy is achieved.

Analysis of the relationship between the monthly temperatures and weather types in Iberian Peninsula

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Nicola, Cortesi; José Carlos, González-Hidalgo

2016-04-01

In this study, the relationship between the atmospheric circulation and weather types and the monthly average maximum and minimum temperatures in the Iberian Peninsula is modeled (period 1950-2010). The temperature data used were obtained from a high spatial resolution (10km x 10km) dataset (MOTEDAS dataset, Gonzalez-Hidalgo et al., 2015a). In addition, a dataset of Portuguese temperatures was used (obtained from the Portuguese Institute of Sea and Atmosphere). The weather type classification used was the one developed by Jenkinson and Collison, which was adapted for the Iberian Peninsula by Trigo and DaCamara (2000), using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The analysis of the behaviour of monthly temperatures based on the weather types was carried out using a stepwise regression procedure of type forward to estimate temperatures in each cell of the considered grid, for each month, and for both maximum and minimum monthly average temperatures. The model selects the weather types that best estimate the temperatures. From the validation model it was obtained the error distribution in the time (months) and space (Iberian Peninsula). The results show that best estimations are obtained for minimum temperatures, during the winter months and in coastal areas. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298

STATEQ: a nonlinear least-squares code for obtaining Martin thermodynamic representations of fluids in the gaseous and dense gaseous regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Milora, S. L.

1976-02-01

The use of the code NLIN (IBM Share Program No. 1428) to obtain empirical thermodynamic pressure-volume-temperature (P-V-T) relationships for substances in the gaseous and dense gaseous states is described. When sufficient experimental data exist, the code STATEQ will provide least-squares estimates for the 21 parameters of the Martin model. Another code, APPROX, is described which also obtains parameter estimates for the model by making use of the approximate generalized behavior of fluids. Use of the codes is illustrated in obtaining thermodynamic representations for isobutane. (auth)

Prediction of the distillation temperatures of crude oils using ¹H NMR and support vector regression with estimated confidence intervals.

PubMed

Filgueiras, Paulo R; Terra, Luciana A; Castro, Eustáquio V R; Oliveira, Lize M S L; Dias, Júlio C M; Poppi, Ronei J

2015-09-01

This paper aims to estimate the temperature equivalent to 10% (T10%), 50% (T50%) and 90% (T90%) of distilled volume in crude oils using (1)H NMR and support vector regression (SVR). Confidence intervals for the predicted values were calculated using a boosting-type ensemble method in a procedure called ensemble support vector regression (eSVR). The estimated confidence intervals obtained by eSVR were compared with previously accepted calculations from partial least squares (PLS) models and a boosting-type ensemble applied in the PLS method (ePLS). By using the proposed boosting strategy, it was possible to identify outliers in the T10% property dataset. The eSVR procedure improved the accuracy of the distillation temperature predictions in relation to standard PLS, ePLS and SVR. For T10%, a root mean square error of prediction (RMSEP) of 11.6°C was obtained in comparison with 15.6°C for PLS, 15.1°C for ePLS and 28.4°C for SVR. The RMSEPs for T50% were 24.2°C, 23.4°C, 22.8°C and 14.4°C for PLS, ePLS, SVR and eSVR, respectively. For T90%, the values of RMSEP were 39.0°C, 39.9°C and 39.9°C for PLS, ePLS, SVR and eSVR, respectively. The confidence intervals calculated by the proposed boosting methodology presented acceptable values for the three properties analyzed; however, they were lower than those calculated by the standard methodology for PLS. Copyright © 2015 Elsevier B.V. All rights reserved.

New estimates of temperature response of leaf photosynthesis in Amazon forest trees, its acclimation to mean temperature change and consequences for modelling climate response to rain forests.

NASA Astrophysics Data System (ADS)

Kruijt, B.; Jans, W.; Vasconcelos, S.; Tribuzy, E. S.; Felsemburgh, C.; Eliane, M.; Rowland, L.; da Costa, A. C. L.; Meir, P.

2014-12-01

In many dynamic vegetation models, degradation of the tropical forests is induced because they assume that productivity falls rapidly when temperatures rise in the region of 30-40°C. Apart plant respiration, this is due to the assumptions on the temperature optima of photosynthetic capacity, which are low and can differ widely between models, where in fact hardly any empirical information is available for tropical forests. Even less is known about the possibility that photosynthesis will acclimate to changing temperatures. The objective of this study to is to provide better estimates for optima, as well as to determine whether any acclimation to temperature change is to be expected. We present both new and hitherto unpublished data on the temperature response of photosynthesis of Amazon rainforest trees, encompassing three sites, several species and five field campaigns. Leaf photosynthesis and its parameters were determined at a range of temperatures. To study the long-term (seasonal) acclimation of this response, this was combined with an artificial, in situ, multi-season leaf heating experiment. The data show that, on average for all non-heated cases, the photosynthetic parameter Vcmax weakly peaks between 35 and 40 ˚C, while heating does not have a clearly significant effect. Results for Jmax are slightly different, with sharper peaks. Scatter was relatively high, which could indicate weak overall temperature dependence. The combined results were used to fit new parameters to the various temperature response curve functions in a range of DGVMs. The figure shows a typical example: while the default Jules model assumes a temperature optimum for Vcmax at around 33 ˚C, the data suggest that Vcmax keeps rising up to at least 40 ˚C. Of course, calculated photosynthesis, obtained by applying this Vcmax in the Farquhar model, peaks at lower temperature. Finally, the implication of these new model parameters for modelled climate change impact on modelled Amazon

Sapwood temperature gradients between lower stems and the crown do not influence estimates of stand-level stem CO(2) efflux.

PubMed

Bowman, William P; Turnbull, Matthew H; Tissue, David T; Whitehead, David; Griffin, Kevin L

2008-10-01

Temperature plays a critical role in the regulation of respiration rates and is often used to scale measurements of respiration to the stand-level and calculate annual respiratory fluxes. Previous studies have indicated that failure to consider temperature gradients between sun-exposed stems and branches in the crown and shaded lower stems may result in errors when deriving stand-level estimates of stem CO(2) efflux. We measured vertical gradients in sapwood temperature in a mature lowland podocarp rain forest in New Zealand to: (1) estimate the effects of within-stem temperature variation on the vertical distribution of stem CO(2) efflux; and (2) use these findings to estimate stand-level stem CO(2) efflux for this forest. Large within-stem gradients in sapwood temperature (1.6 +/- 0.1 to 6.0 +/- 0.5 degrees C) were observed. However, these gradients did not significantly influence the stand-level estimate of stem CO(2) efflux in this forest (536 +/- 42 mol CO(2) ha(-1) day(-1)) or the vertical distribution of stem CO(2) efflux, because of the opposing effects of daytime warming and nighttime cooling on CO(2) efflux in the canopy, and the small fraction of the woody biomass in the crowns of forest trees. Our findings suggest that detailed measurements of within-stand temperature gradients are unlikely to greatly improve the accuracy of tree- or stand-level estimates of stem CO(2) efflux.

Dinosaur fossils predict body temperatures.

PubMed

Gillooly, James F; Allen, Andrew P; Charnov, Eric L

2006-07-01

Perhaps the greatest mystery surrounding dinosaurs concerns whether they were endotherms, ectotherms, or some unique intermediate form. Here we present a model that yields estimates of dinosaur body temperature based on ontogenetic growth trajectories obtained from fossil bones. The model predicts that dinosaur body temperatures increased with body mass from approximately 25 degrees C at 12 kg to approximately 41 degrees C at 13,000 kg. The model also successfully predicts observed increases in body temperature with body mass for extant crocodiles. These results provide direct evidence that dinosaurs were reptiles that exhibited inertial homeothermy.

Mantle potential temperature estimates and primary melt compositions of the Low-Ti Emeishan flood basalt

NASA Astrophysics Data System (ADS)

Shellnutt, J. G.; Pham, Thuy T.

2018-05-01

The Late Permian Emeishan large igneous province (ELIP) is considered to be one of the best examples of a mantle plume derived large igneous province. One of the primary observations that favour a mantle plume regime is the presence of ultramafic volcanic rocks. The picrites suggest primary mantle melts erupted and that mantle potential temperatures (TP) of the ELIP were > 200oC above ambient mantle conditions. However, they may represent a mixture of liquid and cumulus olivine and pyroxene rather than primary liquids. Consequently, temperature estimates based on the picrite compositions may not be accurate. Here we calculate mantle potential temperature (TP) estimates and primary liquids compositions using PRIMELT3 for the low-Ti (Ti/Y < 500) Emeishan basalt as they represent definite liquid compositions. The calculated TP yield a range from 1400oC to 1550oC, which is consistent with variability across a mantle plume axis. The primary melt compositions of the basalts are mostly picritic. The results of this study indicate that the Emeishan basalt was produced by a high temperature regime and that a few of the ultramafic volcanic rocks may be indicative of primary liquids.

Post-Colonization Interval Estimates Using Multi-Species Calliphoridae Larval Masses and Spatially Distinct Temperature Data Sets: A Case Study

PubMed Central

Weatherbee, Courtney R.; Pechal, Jennifer L.; Stamper, Trevor; Benbow, M. Eric

2017-01-01

Common forensic entomology practice has been to collect the largest Diptera larvae from a scene and use published developmental data, with temperature data from the nearest weather station, to estimate larval development time and post-colonization intervals (PCIs). To evaluate the accuracy of PCI estimates among Calliphoridae species and spatially distinct temperature sources, larval communities and ambient air temperature were collected at replicate swine carcasses (N = 6) throughout decomposition. Expected accumulated degree hours (ADH) associated with Cochliomyia macellaria and Phormia regina third instars (presence and length) were calculated using published developmental data sets. Actual ADH ranges were calculated using temperatures recorded from multiple sources at varying distances (0.90 m–7.61 km) from the study carcasses: individual temperature loggers at each carcass, a local weather station, and a regional weather station. Third instars greatly varied in length and abundance. The expected ADH range for each species successfully encompassed the average actual ADH for each temperature source, but overall under-represented the range. For both calliphorid species, weather station data were associated with more accurate PCI estimates than temperature loggers associated with each carcass. These results provide an important step towards improving entomological evidence collection and analysis techniques, and developing forensic error rates. PMID:28375172

Mesospheric temperature estimation from meteor decay times during Geminids meteor shower

NASA Astrophysics Data System (ADS)

Kozlovsky, Alexander; Lukianova, Renata; Shalimov, Sergey; Lester, Mark

2016-02-01

Meteor radar observations at the Sodankylä Geophysical Observatory (67° 22'N, 26° 38'E, Finland) indicate that the mesospheric temperature derived from meteor decay times is systematically underestimated by 20-50 K during the Geminids meteor shower which has peak on 13 December. A very good coincidence of the minimum of routinely calculated temperature and maximum of meteor flux (the number of meteors detected per day) was observed regularly on that day in December 2008-2014. These observations are for a specific height-lifetime distribution of the Geminids meteor trails and indicate a larger percentage of overdense trails compared to that for sporadic meteors. A consequence of this is that the routine estimates of mesospheric temperature during the Geminids are in fact underestimates. The observations do, however, indicate unusual properties (e.g., mass, speed, or chemical composition) of the Geminids meteoroids. Similar properties were found also for Quadrantids in January 2009-2015, which like the Geminids has as a parent body an asteroid, but not for other meteor showers.

Skin temperature over the carotid artery provides an accurate noninvasive estimation of core temperature in infants and young children during general anesthesia.

PubMed

Jay, Ollie; Molgat-Seon, Yannick; Chou, Shirley; Murto, Kimmo

2013-12-01

The accurate measurement of core temperature is an essential aspect of intraoperative management in children. Invasive measurement sites are accurate but carry some health risks and cannot be used in certain patients. An accurate form of noninvasive thermometry is therefore needed. Our aim was to develop, and subsequently validate, separate models for estimating core temperature using different skin temperatures with an individualized correction factor. Forty-eight pediatric patients (0-36 months) undergoing elective surgery were separated into a modeling group (MG, n = 28) and validation group (VG, n = 20). Skin temperature was measured over the carotid artery (Tsk_carotid ), upper abdomen (Tsk_abd ), and axilla (Tsk_axilla ), while nasopharyngeal temperature (Tnaso ) was measured as a reference. In the MG, derived models for estimating Tnaso were: Tsk_carotid  + 0.52; Tsk_abd  + (0.076[body mass] + 0.02); and Tsk_axilla  + (0.081[body mass]-0.66). After adjusting raw Tsk_carotid, Tsk_abd , and Tsk_axilla values in the independent VG using these models, the mean bias (Predicted Tnaso - Actual Tnaso [with 95% confidence intervals]) was +0.03[+0.53, -0.50]°C, -0.05[+1.02, -1.07]°C, and -0.06[+1.21, -1.28°C], respectively. The percentage of values within ±0.5°C of Tnaso was 93.2%, 75.4%, and 66.1% for Tsk_carotid, Tsk_abd , and Tsk_axilla , respectively. Sensitivity and specificity for detecting hypothermia (Tnaso  < 36.0°C) was 0.88 and 0.91 for Tsk_carotid , 0.61 and 0.76 for Tsk_abd , and 0.91 and 0.73 for Tsk_axilla . Goodness-of-fit (R(2) ) relative to the line-of-identity was 0.74 (Tsk_carotid ), 0.34 (Tsk_abd ), and 0.15 (Tsk_axilla ). Skin temperature over the carotid artery, with a simple correction factor of +0.52°C, provides a viable noninvasive estimate of Tnaso in young children during elective surgery with a general anesthetic. © 2013 John Wiley & Sons Ltd.

A hybrid downscaling procedure for estimating the vertical distribution of ambient temperature in local scale

NASA Astrophysics Data System (ADS)

Yiannikopoulou, I.; Philippopoulos, K.; Deligiorgi, D.

2012-04-01

The vertical thermal structure of the atmosphere is defined by a combination of dynamic and radiation transfer processes and plays an important role in describing the meteorological conditions at local scales. The scope of this work is to develop and quantify the predictive ability of a hybrid dynamic-statistical downscaling procedure to estimate the vertical profile of ambient temperature at finer spatial scales. The study focuses on the warm period of the year (June - August) and the method is applied to an urban coastal site (Hellinikon), located in eastern Mediterranean. The two-step methodology initially involves the dynamic downscaling of coarse resolution climate data via the RegCM4.0 regional climate model and subsequently the statistical downscaling of the modeled outputs by developing and training site-specific artificial neural networks (ANN). The 2.5ox2.5o gridded NCEP-DOE Reanalysis 2 dataset is used as initial and boundary conditions for the dynamic downscaling element of the methodology, which enhances the regional representivity of the dataset to 20km and provides modeled fields in 18 vertical levels. The regional climate modeling results are compared versus the upper-air Hellinikon radiosonde observations and the mean absolute error (MAE) is calculated between the four grid point values nearest to the station and the ambient temperature at the standard and significant pressure levels. The statistical downscaling element of the methodology consists of an ensemble of ANN models, one for each pressure level, which are trained separately and employ the regional scale RegCM4.0 output. The ANN models are theoretically capable of estimating any measurable input-output function to any desired degree of accuracy. In this study they are used as non-linear function approximators for identifying the relationship between a number of predictor variables and the ambient temperature at the various vertical levels. An insight of the statistically derived input

IR temperatures of Mauna Loa caldera obtained with multispectral thermal imager

NASA Astrophysics Data System (ADS)

Pendergast, Malcolm M.; O'Steen, Byron L.; Kurzeja, Robert J.

2002-01-01

A survey of surface temperatures of the Mauna Loa caldera during 7/14/00 and 7/15/00 was made by SRTC in conjunction with a MTI satellite image collection. The general variation of surface temperature appears quite predictable responding to solar heating. The analysis of detailed times series of temperature indicates systematic variations in temperature of 5 C corresponding to time scales of 3-5 minutes and space scales of 10-20 m. The average temperature patterns are consistent with those predicted by the Regional Atmospheric Modeling System (RAMS).

The inverse Numerical Computer Program FLUX-BOT for estimating Vertical Water Fluxes from Temperature Time-Series.

NASA Astrophysics Data System (ADS)

Trauth, N.; Schmidt, C.; Munz, M.

2016-12-01

Heat as a natural tracer to quantify water fluxes between groundwater and surface water has evolved to a standard hydrological method. Typically, time series of temperatures in the surface water and in the sediment are observed and are subsequently evaluated by a vertical 1D representation of heat transport by advection and dispersion. Several analytical solutions as well as their implementation into user-friendly software exist in order to estimate water fluxes from the observed temperatures. Analytical solutions can be easily implemented but assumptions on the boundary conditions have to be made a priori, e.g. sinusoidal upper temperature boundary. Numerical models offer more flexibility and can handle temperature data which is characterized by irregular variations such as storm-event induced temperature changes and thus cannot readily be incorporated in analytical solutions. This also reduced the effort of data preprocessing such as the extraction of the diurnal temperature variation. We developed a software to estimate water FLUXes Based On Temperatures- FLUX-BOT. FLUX-BOT is a numerical code written in MATLAB which is intended to calculate vertical water fluxes in saturated sediments, based on the inversion of measured temperature time series observed at multiple depths. It applies a cell-centered Crank-Nicolson implicit finite difference scheme to solve the one-dimensional heat advection-conduction equation. Besides its core inverse numerical routines, FLUX-BOT includes functions visualizing the results and functions for performing uncertainty analysis. We provide applications of FLUX-BOT to generic as well as to measured temperature data to demonstrate its performance.

Lesion size estimator of cardiac radiofrequency ablation at different common locations with different tip temperatures.

PubMed

Lai, Yu-Chi; Choy, Young Bin; Haemmerich, Dieter; Vorperian, Vicken R; Webster, John G

2004-10-01

Finite element method (FEM) analysis has become a common method to analyze the lesion formation during temperature-controlled radiofrequency (RF) cardiac ablation. We present a process of FEM modeling a system including blood, myocardium, and an ablation catheter with a thermistor embedded at the tip. The simulation used a simple proportional-integral (PI) controller to control the entire process operated in temperature-controlled mode. Several factors affect the lesion size such as target temperature, blood flow rate, and application time. We simulated the time response of RF ablation at different locations by using different target temperatures. The applied sites were divided into two groups each with a different convective heat transfer coefficient. The first group was high-flow such as the atrioventricular (AV) node and the atrial aspect of the AV annulus, and the other was low-flow such as beneath the valve or inside the coronary sinus. Results showed the change of lesion depth and lesion width with time, under different conditions. We collected data for all conditions and used it to create a database. We implemented a user-interface, the lesion size estimator, where the user enters set temperature and location. Based on the database, the software estimated lesion dimensions during different applied durations. This software could be used as a first-step predictor to help the electrophysiologist choose treatment parameters.

An Estimate of Shallow, Low-Temperature Geothermal Resources of the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mullane, Michelle; Gleason, Michael; Reber, Tim

Low-temperature geothermal resources in the United States potentially hold an enormous quantity of thermal energy, useful for direct use in residential, commercial and industrial applications such as space and water heating, greenhouse warming, pool heating, aquaculture, and low-temperature manufacturing processes. Several studies published over the past 40 years have provided assessments of the resource potential for multiple types of low-temperature geothermal systems (e.g. hydrothermal convection, hydrothermal conduction, and enhanced geothermal systems) with varying temperature ranges and depths. This paper provides a summary and additional analysis of these assessments of shallow (= 3 km), low-temperature (30-150 degrees C) geothermal resources inmore » the United States, suitable for use in direct-use applications. This analysis considers six types of geothermal systems, spanning both hydrothermal and enhanced geothermal systems (EGS). We outline the primary data sources and quantitative parameters used to describe resources in each of these categories, and present summary statistics of the total resources available. In sum, we find that low-temperature hydrothermal resources and EGS resources contain approximately 8 million and 800 million TWh of heat-in-place, respectively. In future work, these resource potential estimates will be used for modeling of the technical and market potential for direct-use geothermal applications for the U.S. Department of Energy's Geothermal Vision Study.« less

Finite Element Analysis in the Estimation of Air-Gap Torque and Surface Temperature of Induction Machine

NASA Astrophysics Data System (ADS)

Mr., J. Ravi Kumar; Banakara, Basavaraja, Dr.

2017-08-01

This paper presents electromagnetic and thermal behavior of Induction Motor (IM) through the modeling and analysis by applying multiphysics coupled Finite Element Analysis (FEA). Therefore prediction of the magnetic flux, electromagnetic torque, stator and rotor losses and temperature distribution inside an operating electric motor are the most important issues during its design. Prediction and estimation of these parameters allows design engineers to decide capability of the machine for the proposed load, temperature rating and its application for which it is being designed ensuring normal motor operation at rated conditions. In this work, multiphysics coupled electromagnetic - thermal modeling and analysis of induction motor at rated and high frequency has carried out applying Arkkio’s torque method. COMSOL Multiphysics software is used for modeling and finite element analysis of IM. Transient electromagnetic torque, magnetic field distribution, speed-torque characteristics of IM were plotted and studied at different frequencies. This proposed work helps in the design and prediction of accurate performance of induction motor specific to various industrial drive applications. Results obtained are also validated with experimental analysis. The main purpose of this model is to use it as an integral part of the design aiming to system optimization of Variable Speed Drive (VSD) and its components using coupled simulations.

Air temperature-related human health outcomes: current impact and estimations of future risks in Central Italy.

PubMed

Morabito, Marco; Crisci, Alfonso; Moriondo, Marco; Profili, Francesco; Francesconi, Paolo; Trombi, Giacomo; Bindi, Marco; Gensini, Gian Franco; Orlandini, Simone

2012-12-15

The association between air temperature and human health is described in detail in a large amount of literature. However, scientific publications estimating how climate change will affect the population's health are much less extensive. In this study current evaluations and future predictions of the impact of temperature on human health in different geographical areas have been carried out. Non-accidental mortality and hospitalizations, and daily average air temperatures have been obtained for the 1999-2008 period for the ten main cities in Tuscany (Central Italy). High-resolution city-specific climatologic A1B scenarios centered on 2020 and 2040 have been assessed. Generalized additive and distributed lag models have been used to identify the relationships between temperature and health outcomes stratified by age: general adults (<65), elderly (aged 65-74) and very elderly (≥75). The cumulative impact (over a lag-period of 30 days) of the effects of cold and especially heat, was mainly significant for mortality in the very elderly, with a higher impact on coastal plain than inland cities: 1 °C decrease/increase in temperature below/above the threshold was associated with a 2.27% (95% CI: 0.17-4.93) and 15.97% (95% CI: 7.43-24.51) change in mortality respectively in the coastal plain cities. A slight unexpected increase in short-term cold-related mortality in the very elderly, with respect to the baseline period, is predicted for the following years in half of the cities considered. Most cities also showed an extensive predicted increase in short-term heat-related mortality and a general increase in the annual temperature-related elderly mortality rate. These findings should encourage efforts to implement adaptation actions conducive to policy-making decisions, especially for planning short- and long-term health intervention strategies and mitigation aimed at preventing and minimizing the consequences of climate change on human health. Copyright © 2012 Elsevier

Detection of surface temperature from LANDSAT-7/ETM+

NASA Astrophysics Data System (ADS)

Suga, Y.; Ogawa, H.; Ohno, K.; Yamada, K.

2003-12-01

Hiroshima Institute of Technology (HIT) in Japan has established a LANDSAT-7 Ground Station in cooperation with NASDA for receiving and processing the ETM+ data on March 15 th, 2000 in Japan. The authors performed a verification study on the surface temperature derived from thermal infrared band image data of LANDSAT 7/Enhanced Thematic Mapper Plus (ETM+) for the estimation of temperatures around Hiroshima city and bay area in the western part of Japan as a test site. As to the thermal infrared band, the approximate functions for converting the spectral radiance into the surface temperature are estimated by considering both typical surface temperatures measured by the simultaneous field survey with the satellite observation and the spectral radiance observed by ETM+ band 6 (10.40-12.50μm), and then the estimation of the surface temperature distribution around the test site was examined.In this study, the authors estimated the surface temperature distribution equivalent to the land cover categories around the test site for establishing a guideline of surface temperature detection by LANDSAT7/ETM+ data. As the result of comparison of the truth data and the estimated surface temperature, the correlation coefficients of the approximate function referred to the truth data are from 0.9821 to 0.9994, and the differences are observed from +0.7 to -1.5°C in summer, from +0.4 to -0.9 *C in autumn, from -1.6 to -3.4°C in winter and from +0.5 to -0.5C in spring season respectively. It is clearly found that the estimation of surface temperature based on the approximate functions for converting the spectral radiance into the surface temperature referred to the truth data is improved over the directly estimated surface temperature obtained from satellite data. Finally, the successive seasonal change of surface temperature distribution pattern of the test site is precisely detected with the temperature legend of 0 to 80'C derived from LANDSAT-7/ETM+ band 6 image data for the

Estimation of effective temperatures in a quantum annealer: Towards deep learning applications

NASA Astrophysics Data System (ADS)

Realpe-Gómez, John; Benedetti, Marcello; Perdomo-Ortiz, Alejandro

Sampling is at the core of deep learning and more general machine learning applications; an increase in its efficiency would have a significant impact across several domains. Recently, quantum annealers have been proposed as a potential candidate to speed up these tasks, but several limitations still bar them from being used effectively. One of the main limitations, and the focus of this work, is that using the device's experimentally accessible temperature as a reference for sampling purposes leads to very poor correlation with the Boltzmann distribution it is programmed to sample from. Based on quantum dynamical arguments, one can expect that if the device indeed happens to be sampling from a Boltzmann-like distribution, it will correspond to one with an instance-dependent effective temperature. Unless this unknown temperature can be unveiled, it might not be possible to effectively use a quantum annealer for Boltzmann sampling processes. In this work, we propose 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 quantum-assisted training of Boltzmann machines, which can serve as a building block for deep learning architectures. This work was supported by NASA Ames Research Center.

An alternative method to estimate zero flow temperature differences for Granier's thermal dissipation technique.

PubMed

Regalado, Carlos M; Ritter, Axel

2007-08-01

Calibration of the Granier thermal dissipation technique for measuring stem sap flow in trees requires determination of the temperature difference (DeltaT) between a heated and an unheated probe when sap flow is zero (DeltaT(max)). Classically, DeltaT(max) has been estimated from the maximum predawn DeltaT, assuming that sap flow is negligible at nighttime. However, because sap flow may continue during the night, the maximum predawn DeltaT value may underestimate the true DeltaT(max). No alternative method has yet been proposed to estimate DeltaT(max) when sap flow is non-zero at night. A sensitivity analysis is presented showing that errors in DeltaT(max) may amplify through sap flux density computations in Granier's approach, such that small amounts of undetected nighttime sap flow may lead to large diurnal sap flux density errors, hence the need for a correct estimate of DeltaT(max). By rearranging Granier's original formula, an optimization method to compute DeltaT(max) from simultaneous measurements of diurnal DeltaT and micrometeorological variables, without assuming that sap flow is negligible at night, is presented. Some illustrative examples are shown for sap flow measurements carried out on individuals of Erica arborea L., which has needle-like leaves, and Myrica faya Ait., a broadleaf species. We show that, although DeltaT(max) values obtained by the proposed method may be similar in some instances to the DeltaT(max) predicted at night, in general the values differ. The procedure presented has the potential of being applied not only to Granier's method, but to other heat-based sap flow systems that require a zero flow calibration, such as the Cermák et al. (1973) heat balance method and the T-max heat pulse system of Green et al. (2003).

Estimating Temperature Rise Due to Flashlamp Heating Using Irreversible Temperature Indicators

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

1999-01-01

One of the nondestructive thermography inspection techniques uses photographic flashlamps. The flashlamps provide a short duration (about 0.005 sec) heat pulse. The short burst of energy results in a momentary rise in the surface temperature of the part. The temperature rise may be detrimental to the top layer of the part being exposed. Therefore, it is necessary to ensure the nondestructive nature of the technique. Amount of the temperature rise determines whether the flashlamp heating would be detrimental to the part. A direct method for the temperature measurement is to use of an infrared pyrometer that has much shorter response time than the flash duration. In this paper, an alternative technique is given using the irreversible temperature 'indicators. This is an indirect technique and it measures the temperature rise on the irreversible temperature indicators and computes the incident heat flux. Once the heat flux is known, the temperature rise on the part can be computed. A wedge shaped irreversible temperature indicator for measuring the heat flux is proposed. A procedure is given to use the wedge indicator.

Analysis of temperature time series to estimate direction and magnitude of water fluxes in near-surface sediments

NASA Astrophysics Data System (ADS)

Munz, Matthias; Oswald, Sascha E.; Schmidt, Christian

2017-04-01

The application of heat as a hydrological tracer has become a standard method for quantifying water fluxes between groundwater and surface water. Typically, time series of temperatures in the surface water and in the sediment are observed and are subsequently evaluated by a vertical 1D representation of heat transport by advection and dispersion. Several analytical solutions as well as their implementation into user-friendly software exist in order to estimate water fluxes from the observed temperatures. The underlying assumption of a stationary, one-dimensional vertical flow field is frequently violated in natural systems. Here subsurface water flow often has a significant horizontal component. We developed a methodology for identifying the geometry of the subsurface flow field based on the variations of diurnal temperature amplitudes with depths. For instance: Purely vertical heat transport is characterized by an exponential decline of temperature amplitudes with increasing depth. Pure horizontal flow would be indicated by a constant, depth independent vertical amplitude profile. The decline of temperature amplitudes with depths could be fitted by polynomials of different order whereby the best fit was defined by the highest Akaike Information Criterion. The stepwise model optimization and selection, evaluating the shape of vertical amplitude ratio profiles was used to determine the predominant subsurface flow field, which could be systematically categorized in purely vertical and horizontal (hyporheic, parafluvial) components. Analytical solutions to estimate water fluxes from the observed temperatures are restricted to specific boundary conditions such as a sinusoidal upper temperature boundary. In contrast numerical solutions offer higher flexibility and can handle temperature data which is characterized by irregular variations such as storm-event induced temperature changes and thus cannot readily be incorporated in analytical solutions. There are several

Estimated winter wheat yield from crop growth predicted by LANDSAT

NASA Technical Reports Server (NTRS)

Kanemasu, E. T.

1977-01-01

An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

Comparison of internal dose estimates obtained using organ-level, voxel S value, and Monte Carlo techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grimes, Joshua, E-mail: grimes.joshua@mayo.edu; Celler, Anna

2014-09-15

Purpose: The authors’ objective was to compare internal dose estimates obtained using the Organ Level Dose Assessment with Exponential Modeling (OLINDA/EXM) software, the voxel S value technique, and Monte Carlo simulation. Monte Carlo dose estimates were used as the reference standard to assess the impact of patient-specific anatomy on the final dose estimate. Methods: Six patients injected with{sup 99m}Tc-hydrazinonicotinamide-Tyr{sup 3}-octreotide were included in this study. A hybrid planar/SPECT imaging protocol was used to estimate {sup 99m}Tc time-integrated activity coefficients (TIACs) for kidneys, liver, spleen, and tumors. Additionally, TIACs were predicted for {sup 131}I, {sup 177}Lu, and {sup 90}Y assuming themore » same biological half-lives as the {sup 99m}Tc labeled tracer. The TIACs were used as input for OLINDA/EXM for organ-level dose calculation and voxel level dosimetry was performed using the voxel S value method and Monte Carlo simulation. Dose estimates for {sup 99m}Tc, {sup 131}I, {sup 177}Lu, and {sup 90}Y distributions were evaluated by comparing (i) organ-level S values corresponding to each method, (ii) total tumor and organ doses, (iii) differences in right and left kidney doses, and (iv) voxelized dose distributions calculated by Monte Carlo and the voxel S value technique. Results: The S values for all investigated radionuclides used by OLINDA/EXM and the corresponding patient-specific S values calculated by Monte Carlo agreed within 2.3% on average for self-irradiation, and differed by as much as 105% for cross-organ irradiation. Total organ doses calculated by OLINDA/EXM and the voxel S value technique agreed with Monte Carlo results within approximately ±7%. Differences between right and left kidney doses determined by Monte Carlo were as high as 73%. Comparison of the Monte Carlo and voxel S value dose distributions showed that each method produced similar dose volume histograms with a minimum dose covering 90% of the volume

Estimation of the temperature spatial variability in confined spaces based on thermal imaging

NASA Astrophysics Data System (ADS)

Augustyn, Grzegorz; Jurasz, Jakub; Jurczyk, Krzysztof; Korbiel, Tomasz; Mikulik, Jerzy; Pawlik, Marcin; Rumin, Rafał

2017-11-01

In developed countries the salaries of office workers are several times higher than the total cost of maintaining and operating the building. Therefore even a small improvement in human work productivity and performance as a result of enhancing the quality of their work environment may lead to a meaningful economic benefits. The air temperature is the most commonly used indicator in assessing the indoor environment quality. What is more, it is well known that thermal comfort has the biggest impact on employees performance and their ability to work efficiently. In majority of office buildings, indoor temperature is managed by heating, ventilation and air conditioning (HVAC) appliances. However the way how they are currently managed and controlled leads to the nonhomogeneous distribution of temperature in certain space. An approach to determining the spatial variability of temperature in confined spaces was introduced based on thermal imaging temperature measurements. The conducted research and obtained results enabled positive verification of the method and creation of surface plot illustrating the temperature variability.

Age Spreads and the Temperature Dependence of Age Estimates in Upper Sco

NASA Astrophysics Data System (ADS)

Fang, Qiliang; Herczeg, Gregory J.; Rizzuto, Aaron

2017-06-01

Past estimates for the age of the Upper Sco Association are typically 11–13 Myr for intermediate-mass stars and 4–5 Myr for low-mass stars. In this study, we simulate populations of young stars to investigate whether this apparent dependence of estimated age on spectral type may be explained by the star formation history of the association. Solar and intermediate mass stars begin their pre-main sequence evolution on the Hayashi track, with fully convective interiors and cool photospheres. Intermediate-mass stars quickly heat up and transition onto the radiative Henyey track. As a consequence, for clusters in which star formation occurs on a timescale similar to that of the transition from a convective to a radiative interior, discrepancies in ages will arise when ages are calculated as a function of temperature instead of mass. Simple simulations of a cluster with constant star formation over several Myr may explain about half of the difference in inferred ages versus photospheric temperature; speculative constructions that consist of a constant star formation followed by a large supernova-driven burst could fully explain the differences, including those between F and G stars where evolutionary tracks may be more accurate. The age spreads of low-mass stars predicted from these prescriptions for star formation are consistent with the observed luminosity spread of Upper Sco. The conclusion that a lengthy star formation history will yield a temperature dependence in ages is expected from the basic physics of pre-main sequence evolution, and is qualitatively robust to the large uncertainties in pre-main sequence evolutionary models.

3-D in vitro estimation of temperature using the change in backscattered ultrasonic energy.

PubMed

Arthur, R Martin; Basu, Debomita; Guo, Yuzheng; Trobaugh, Jason W; Moros, Eduardo G

2010-08-01

Temperature imaging with a non-invasive modality to monitor the heating of tumors during hyperthermia treatment is an attractive alternative to sparse invasive measurement. Previously, we predicted monotonic changes in backscattered energy (CBE) of ultrasound with temperature for certain sub-wavelength scatterers. We also measured CBE values similar to our predictions in bovine liver, turkey breast muscle, and pork rib muscle in 2-D in vitro studies and in nude mice during 2-D in vivo studies. To extend these studies to three dimensions, we compensated for motion and measured CBE in turkey breast muscle. 3-D data sets were assembled from images formed by a phased-array imager with a 7.5-MHz linear probe moved in 0.6-mm steps in elevation during uniform heating from 37 to 45 degrees C in 0.5 degrees C increments. We used cross-correlation as a similarity measure in RF signals to automatically track feature displacement as a function of temperature. Feature displacement was non-rigid. Envelopes of image regions, compensated for non-rigid motion, were found with the Hilbert transform then smoothed with a 3 x 3 running average filter before forming the backscattered energy at each pixel. CBE in 3-D motion-compensated images was nearly linear with an average sensitivity of 0.30 dB/ degrees C. 3-D estimation of temperature in separate tissue regions had errors with a maximum standard deviation of about 0.5 degrees C over 1-cm(3) volumes. Success of CBE temperature estimation based on 3-D non-rigid tracking and compensation for real and apparent motion of image features could serve as the foundation for the eventual generation of 3-D temperature maps in soft tissue in a non-invasive, convenient, and low-cost way in clinical hyperthermia.

Effects of post exposure bake temperature and exposure time on SU-8 nanopattern obtained by electron beam lithography

NASA Astrophysics Data System (ADS)

Yasui, Manabu; Kazawa, Elito; Kaneko, Satoru; Takahashi, Ryo; Kurouchi, Masahito; Ozawa, Takeshi; Arai, Masahiro

2014-11-01

SU-8 is a photoresist imaged using UV rays. However, we investigated the characteristics of an SU-8 nanopattern obtained by electron beam lithography (EBL). In particular, we studied the relationship between post-exposure bake (PEB) temperature and exposure time on an SU-8 nanopattern with a focus on phase transition temperature. SU-8 residue was formed by increasing both PEB temperature and exposure time. To prevent the formation of this, Monte Carlo simulation was performed; the results of such simulation showed that decreasing the thickness of SU-8 can reduce the amount of residue from the SU-8 nanopattern. We confirmed that decreasing the thickness of SU-8 can also prevent the formation of residue from the SU-8 nanopattern with EBL.

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

NASA Technical Reports Server (NTRS)

Ryan, Robert E.; Irons, James; Spruce, Joseph P.; Underwood, Lauren W.; Pagnutti, Mary

2006-01-01

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Walker, H. F.

1978-01-01

This paper addresses the problem of obtaining numerically maximum-likelihood estimates of the parameters for a mixture of normal distributions. In recent literature, a certain successive-approximations procedure, based on the likelihood equations, was shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, we introduce a general iterative procedure, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. We show that, with probability 1 as the sample size grows large, this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. We also show that the step-size which yields optimal local convergence rates for large samples is determined in a sense by the 'separation' of the component normal densities and is bounded below by a number between 1 and 2.

Influence of annealing temperature on optical properties of the photonic-crystal structures obtained by self-organization of colloidal microspheres of polystyrene and silica

NASA Astrophysics Data System (ADS)

Mikhnev, L. V.; Bondarenko, E. A.; Chapura, O. M.; Skomorokhov, A. A.; Kravtsov, A. A.

2018-01-01

The influence of annealing temperature on the transmission spectra of photonic crystals composed of polystyrene and silicon dioxide microspheres was studied. It was found that annealing of photonic crystals based on polystyrene and silica leads to a shift in the photonic band gap to the short-wavelength region. Based on the results of optical studies, the dependences of the structural parameters of the obtained opal-like crystals on annealing temperature were obtained. In the case of polystyrene photonic crystals, the displacement of the photonic band gap is observed in a narrow temperature range above the glass transition temperature. For SiO2 photonic crystals, it was found that the process of microspheres sintering is complex and involves three stages of structural modification.

Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates

NASA Technical Reports Server (NTRS)

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe;

Temperature increase reduces global yields of major crops in four independent estimates

PubMed Central

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A.; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Peng, Shushi; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-01-01

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population. PMID:28811375

Temperature increase reduces global yields of major crops in four independent estimates.

PubMed

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Müller, Christoph; Peng, Shushi; Peñuelas, Josep; Ruane, Alex C; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-08-29

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO 2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Dinosaur Fossils Predict Body Temperatures

PubMed Central

Allen, Andrew P; Charnov, Eric L

2006-01-01

Perhaps the greatest mystery surrounding dinosaurs concerns whether they were endotherms, ectotherms, or some unique intermediate form. Here we present a model that yields estimates of dinosaur body temperature based on ontogenetic growth trajectories obtained from fossil bones. The model predicts that dinosaur body temperatures increased with body mass from approximately 25 °C at 12 kg to approximately 41 °C at 13,000 kg. The model also successfully predicts observed increases in body temperature with body mass for extant crocodiles. These results provide direct evidence that dinosaurs were reptiles that exhibited inertial homeothermy. PMID:16817695

Estimation of viscoelastic shear properties of vocal-fold tissues based on time-temperature superposition.

PubMed

Chan, R W

2001-09-01

Empirical data on the viscoelastic shear properties of human vocal-fold mucosa (cover) were recently reported at relatively low frequency (0.01-15 Hz). For the data to become relevant to voice production, attempts have been made to parametrize and extrapolate the data to higher frequencies using constitutive modeling [Chan and Titze, J. Acoust. Soc. Am. 107, 565-580 (2000)]. This study investigated the feasibility of an alternative approach for data extrapolation, namely the principle of time-temperature superposition (TTS). TTS is a hybrid theoretical-empirical approach widely used by rheologists to estimate the viscoelastic properties of polymeric systems at time or frequency scales not readily accessible experimentally. It is based on the observation that for many polymers, the molecular configurational changes that occur in a given time scale at a low temperature correspond to those that occur in a shorter time scale at a higher temperature. Using a rotational rheometer, the elastic shear modulus (G') and viscous shear modulus (G'') of vocal-fold cover (superficial layer of lamina propria) tissue samples were measured at 0.01-15 Hz at relatively low temperatures (5 degrees-37 degrees C). Data were empirically shifted according to TTS, yielding composite "master curves" for predicting the magnitude of the shear moduli at higher frequencies at 37 degrees C. Results showed that TTS may be a feasible approach for estimating the viscoelastic shear properties of vocal-fold tissues at frequencies of phonation (on the order of 100-1000 Hz).

Estimation of the core temperature control during ambient temperature changes and the influence of circadian rhythm and metabolic conditions in mice.

PubMed

Tokizawa, Ken; Yoda, Tamae; Uchida, Yuki; Kanosue, Kazuyuki; Nagashima, Kei

2015-07-01

It has been speculated that the control of core temperature is modulated by physiological demands. We could not prove the modulation because we did not have a good method to evaluate the control. In the present study, the control of core temperature in mice was assessed by exposing them to various ambient temperatures (Ta), and the influence of circadian rhythm and feeding condition was evaluated. Male ICR mice (n=20) were placed in a box where Ta was increased or decreased from 27°C to 40°C or to -4°C (0.15°C/min) at 0800 and 2000 (daytime and nighttime, respectively). Intra-abdominal temperature (Tcore) was monitored by telemetry. The relationship between Tcore and Ta was assessed. The range of Ta where Tcore was relatively stable (range of normothermia, RNT) and Tcore corresponding to the RNT median (regulated Tcore) were estimated by model analysis. In fed mice, the regression slope within the RNT was smaller in the nighttime than in the daytime (0.02 and 0.06, respectively), and the regulated Tcore was higher in the nighttime than in the daytime (37.5°C and 36.0°C, respectively). In the fasted mice, the slope remained unchanged, and the regulated Tcore decreased in the nighttime (0.05 and 35.9°C, respectively), while the slopes in the daytime became greater (0.13). Without the estimating individual thermoregulatory response such as metabolic heat production and skin vasodilation, the analysis of the Ta-Tcore relationship could describe the character of the core temperature control. The present results show that the character of the system changes depending on time of day and feeding conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Time and temperature dependent breakdown characteristics of ZnS:Mn films obtained by rf-magnetron sputtering

NASA Astrophysics Data System (ADS)

Zhigal'Skii, A. A.; Mukhachev, V. A.; Troyan, P. E.

1994-04-01

Breakdown delay times (tdel) for films of managanese-doped zinc sulfide (ZnS:Mn) were measured in the range 10-6-10-1 s. The maximum value was tdel=10-3-10-2 s. The electrical strength (Ebr) was found to increase as the voltage pulse duration was reduced, the more so the thinner the ZnS:Mn film. The temperature dependence of Ebr exhibited a weak reduction in Ebr as the temperature was raised to roughly 80°C and a sharp reduction in Ebr for T>130°C. A maximum in Ebr was observed at T≈130°C which is presumably explained by a structural modification of the ZnS:Mn film. The experimental results obtained are explained in terms of a combined electronic and thermal breakdown mechanism.

Model for Increasing the Power Obtained from a Thermoelectric Generator Module

NASA Astrophysics Data System (ADS)

Huang, Gia-Yeh; Hsu, Cheng-Ting; Yao, Da-Jeng

2014-06-01

We have developed a model for finding the most efficient way of increasing the power obtained from a thermoelectric generator (TEG) module with a variety of operating conditions and limitations. The model is based on both thermoelectric principles and thermal resistance circuits, because a TEG converts heat into electricity consistent with these two theories. It is essential to take into account thermal contact resistance when estimating power generation. Thermal contact resistance causes overestimation of the measured temperature difference between the hot and cold sides of a TEG in calculation of the theoretical power generated, i.e. the theoretical power is larger than the experimental power. The ratio of the experimental open-loop voltage to the measured temperature difference, the effective Seebeck coefficient, can be used to estimate the thermal contact resistance in the model. The ratio of the effective Seebeck coefficient to the theoretical Seebeck coefficient, the Seebeck coefficient ratio, represents the contact conditions. From this ratio, a relationship between performance and different variables can be developed. The measured power generated by a TEG module (TMH400302055; Wise Life Technology, Taiwan) is consistent with the result obtained by use of the model; the relative deviation is 10%. Use of this model to evaluate the most efficient means of increasing the generated power reveals that the TEG module generates 0.14 W when the temperature difference is 25°C and the Seebeck coefficient ratio is 0.4. Several methods can be used triple the amount of power generated. For example, increasing the temperature difference to 43°C generates 0.41 W power; improving the Seebeck coefficient ratio to 0.65 increases the power to 0.39 W; simultaneously increasing the temperature difference to 34°C and improving the Seebeck coefficient ratio to 0.5 increases the power to 0.41 W. Choice of the appropriate method depends on the limitations of system, the cost, and

Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon

USGS Publications Warehouse

Perry, Russell W.; Plumb, John M.; Huntington, Charles

2015-01-01

To estimate the parameters that govern mass- and temperature-dependent growth, we conducted a meta-analysis of existing growth data from juvenile Chinook Salmon Oncorhynchus tshawytscha that were fed an ad libitum ration of a pelleted diet. Although the growth of juvenile Chinook Salmon has been well studied, research has focused on a single population, a narrow range of fish sizes, or a narrow range of temperatures. Therefore, we incorporated the Ratkowsky model for temperature-dependent growth into an allometric growth model; this model was then fitted to growth data from 11 data sources representing nine populations of juvenile Chinook Salmon. The model fit the growth data well, explaining 98% of the variation in final mass. The estimated allometric mass exponent (b) was 0.338 (SE = 0.025), similar to estimates reported for other salmonids. This estimate of b will be particularly useful for estimating mass-standardized growth rates of juvenile Chinook Salmon. In addition, the lower thermal limit, optimal temperature, and upper thermal limit for growth were estimated to be 1.8°C (SE = 0.63°C), 19.0°C (SE = 0.27°C), and 24.9°C (SE = 0.02°C), respectively. By taking a meta-analytical approach, we were able to provide a growth model that is applicable across populations of juvenile Chinook Salmon receiving an ad libitum ration of a pelleted diet.

Different combination of MODIS land surface temperature data for daily air surface temperature estimation in North West Vietnam

NASA Astrophysics Data System (ADS)

Noi Phan, Thanh; Kappas, Martin; Degener, Jan

2017-04-01

Land air temperature (Ta) with high spatial and temporal resolution plays an important role in various applications, such as: crop growth monitoring and simulations, environmental risk models, weather forecasting, land use cover change, urban heat islands, etc. Daily Ta (including Ta-max, Ta-min, and Ta-mean) is usually measured by weather stations (often at 2 m above the ground); thus, Ta is limited in spatial coverage. Satellite data, especially MODIS land surface temperature (LST) data at 1 kilometre and high temporal resolution (4 times per day, combining TERRA and AQUA) are free available and easily to access. However, there is a difference between Ta and LST because of the complex surface energy budget and multiple related variables between them. Several researches states that the Ta could be estimated using MODIS LST data with accurate of 2-4oC. However, there are only a handful of studies using dynamically combining of four MODIS LST data for Ta estimation. In this study, we evaluated all 15 - possible - combinations of four MODIS LST using support vector machine (SVM) and random forests (RFs) models. MODIS LST and Ta data was extracted from 4 weather stations in rural area in North West Vietnam from 2010 to 2012 (three years). Our results indicated that the accuracy of Ta estimation was affected by the different combination and the combined data (multiple variables) gave better results than those of single LST (solely variable), the best result was achieved (coefficient of determination (R2) = 0.95, 0.97, 0.97; root mean square error (RMSE) =1.7, 1.4, 1.2 oC for Ta-min, Ta-max, Ta-mean respectively) when all four LSTs were combined and RFs performed better than SVM.

Estimation of Surface Temperature and Heat Flux by Inverse Heat Transfer Methods Using Internal Temperatures Measured While Radiantly Heating a Carbon/Carbon Specimen up to 1920 F

NASA Technical Reports Server (NTRS)

Pizzo, Michelle; Daryabeigi, Kamran; Glass, David

2015-01-01

The ability to solve the heat conduction equation is needed when designing materials to be used on vehicles exposed to extremely high temperatures; e.g. vehicles used for atmospheric entry or hypersonic flight. When using test and flight data, computational methods such as finite difference schemes may be used to solve for both the direct heat conduction problem, i.e., solving between internal temperature measurements, and the inverse heat conduction problem, i.e., using the direct solution to march forward in space to the surface of the material to estimate both surface temperature and heat flux. The completed research first discusses the methods used in developing a computational code to solve both the direct and inverse heat transfer problems using one dimensional, centered, implicit finite volume schemes and one dimensional, centered, explicit space marching techniques. The developed code assumed the boundary conditions to be specified time varying temperatures and also considered temperature dependent thermal properties. The completed research then discusses the results of analyzing temperature data measured while radiantly heating a carbon/carbon specimen up to 1920 F. The temperature was measured using thermocouple (TC) plugs (small carbon/carbon material specimens) with four embedded TC plugs inserted into the larger carbon/carbon specimen. The purpose of analyzing the test data was to estimate the surface heat flux and temperature values from the internal temperature measurements using direct and inverse heat transfer methods, thus aiding in the thermal and structural design and analysis of high temperature vehicles.

Wavelet and Fractal Analysis of Remotely Sensed Surface Temperature with Applications to Estimation of Surface Sensible Heat Flux Density

NASA Technical Reports Server (NTRS)

Schieldge, John

2000-01-01

Wavelet and fractal analyses have been used successfully to analyze one-dimensional data sets such as time series of financial, physical, and biological parameters. These techniques have been applied to two-dimensional problems in some instances, including the analysis of remote sensing imagery. In this respect, these techniques have not been widely used by the remote sensing community, and their overall capabilities as analytical tools for use on satellite and aircraft data sets is not well known. Wavelet and fractal analyses have the potential to provide fresh insight into the characterization of surface properties such as temperature and emissivity distributions, and surface processes such as the heat and water vapor exchange between the surface and the lower atmosphere. In particular, the variation of sensible heat flux density as a function of the change In scale of surface properties Is difficult to estimate, but - in general - wavelets and fractals have proved useful in determining the way a parameter varies with changes in scale. We present the results of a limited study on the relationship between spatial variations in surface temperature distribution and sensible heat flux distribution as determined by separate wavelet and fractal analyses. We analyzed aircraft imagery obtained in the thermal infrared (IR) bands from the multispectral TIMS and hyperspectral MASTER airborne sensors. The thermal IR data allows us to estimate the surface kinetic temperature distribution for a number of sites in the Midwestern and Southwestern United States (viz., San Pedro River Basin, Arizona; El Reno, Oklahoma; Jornada, New Mexico). The ground spatial resolution of the aircraft data varied from 5 to 15 meters. All sites were instrumented with meteorological and hydrological equipment including surface layer flux measuring stations such as Bowen Ratio systems and sonic anemometers. The ground and aircraft data sets provided the inputs for the wavelet and fractal analyses

Estimation of water level and steam temperature using ensemble Kalman filter square root (EnKF-SR)

NASA Astrophysics Data System (ADS)

Herlambang, T.; Mufarrikoh, Z.; Karya, D. F.; Rahmalia, D.

2018-04-01

The equipment unit which has the most vital role in the steam-powered electric power plant is boiler. Steam drum boiler is a tank functioning to separate fluida into has phase and liquid phase. The existence in boiler system has a vital role. The controlled variables in the steam drum boiler are water level and the steam temperature. If the water level is higher than the determined level, then the gas phase resulted will contain steam endangering the following process and making the resulted steam going to turbine get less, and the by causing damages to pipes in the boiler. On the contrary, if less than the height of determined water level, the resulted height will result in dry steam likely to endanger steam drum. Thus an error was observed between the determined. This paper studied the implementation of the Ensemble Kalman Filter Square Root (EnKF-SR) method in nonlinear model of the steam drum boiler equation. The computation to estimate the height of water level and the temperature of steam was by simulation using Matlab software. Thus an error was observed between the determined water level and the steam temperature, and that of estimated water level and steam temperature. The result of simulation by Ensemble Kalman Filter Square Root (EnKF-SR) on the nonlinear model of steam drum boiler showed that the error was less than 2%. The implementation of EnKF-SR on the steam drum boiler r model comprises of three simulations, each of which generates 200, 300 and 400 ensembles. The best simulation exhibited the error between the real condition and the estimated result, by generating 400 ensemble. The simulation in water level in order of 0.00002145 m, whereas in the steam temperature was some 0.00002121 kelvin.

LC-MS/MS-based approach for obtaining exposure estimates of metabolites in early clinical trials using radioactive metabolites as reference standards.

PubMed

Zhang, Donglu; Raghavan, Nirmala; Chando, Theodore; Gambardella, Janice; Fu, Yunlin; Zhang, Duxi; Unger, Steve E; Humphreys, W Griffith

2007-12-01

An LC-MS/MS-based approach that employs authentic radioactive metabolites as reference standards was developed to estimate metabolite exposures in early drug development studies. This method is useful to estimate metabolite levels in studies done with non-radiolabeled compounds where metabolite standards are not available to allow standard LC-MS/MS assay development. A metabolite mixture obtained from an in vivo source treated with a radiolabeled compound was partially purified, quantified, and spiked into human plasma to provide metabolite standard curves. Metabolites were analyzed by LC-MS/MS using the specific mass transitions and an internal standard. The metabolite concentrations determined by this approach were found to be comparable to those determined by valid LC-MS/MS assays. This approach does not requires synthesis of authentic metabolites or the knowledge of exact structures of metabolites, and therefore should provide a useful method to obtain early estimates of circulating metabolites in early clinical or toxicological studies.

Electrical Conductivity of HgTe at High Temperatures

NASA Technical Reports Server (NTRS)

Li, C.; Lehoczky, S. L.; Su, C.-H.; Scripa, R. N.

2004-01-01

The electrical conductivity of HgTe was measured using a rotating magnetic field method from 300 K to the melting point (943 K). A microscopic theory for electrical conduction was used to calculate the expected temperature dependence of the HgTe conductivity. A comparison between the measured and calculated conductivities was used to obtain the estimates of the temperature dependence of Gamma(sub 6)-Gamma(sub 8) energy gap from 300 K to 943 K. The estimated temperature coefficient for the energy gap was comparable to the previous results at lower temperatures (less than or equal to 300 K). A rapid increase in the conductivity just above 300 K and a subsequent decrease at 500 K is attributed to band crossover effects. This paper describes the experimental approach and some of the theoretical calculation details.

Effects of vegetation types on soil moisture estimation from the normalized land surface temperature versus vegetation index space

NASA Astrophysics Data System (ADS)

Zhang, Dianjun; Zhou, Guoqing

2015-12-01

Soil moisture (SM) is a key variable that has been widely used in many environmental studies. Land surface temperature versus vegetation index (LST-VI) space becomes a common way to estimate SM in optical remote sensing applications. Normalized LST-VI space is established by the normalized LST and VI to obtain the comparable SM in Zhang et al. (Validation of a practical normalized soil moisture model with in situ measurements in humid and semiarid regions [J]. International Journal of Remote Sensing, DOI: 10.1080/01431161.2015.1055610). The boundary conditions in the study were set to limit the point A (the driest bare soil) and B (the wettest bare soil) for surface energy closure. However, no limitation was installed for point D (the full vegetation cover). In this paper, many vegetation types are simulated by the land surface model - Noah LSM 3.2 to analyze the effects on soil moisture estimation, such as crop, grass and mixed forest. The locations of point D are changed with vegetation types. The normalized LST of point D for forest is much lower than crop and grass. The location of point D is basically unchanged for crop and grass.

Impact of revised and potential future albedo estimates on CCSM3 simulations of growing-season surface temperature fields for North America

Treesearch

Warren E. Heilman; David Y. Hollinger; Xiuping Li; Xindi Bain; Shiyuan. Zhong

2010-01-01

Recently published albedo research has resulted in improved growing-season albedo estimates for forest and grassland vegetation. The impact of these improved estimates on the ability of climate models to simulate growing-season surface temperature patterns is unknown. We have developed a set of current-climate surface temperature scenarios for North America using the...

Solutions for the diurnally forced advection-diffusion equation to estimate bulk fluid velocity and diffusivity in streambeds from temperature time series

Treesearch

Charles H. Luce; Daniele Tonina; Frank Gariglio; Ralph Applebee

2013-01-01

Work over the last decade has documented methods for estimating fluxes between streams and streambeds from time series of temperature at two depths in the streambed. We present substantial extension to the existing theory and practice of using temperature time series to estimate streambed water fluxes and thermal properties, including (1) a new explicit analytical...

Temperature measurements at IODP 337 Expedition, off Shimokita, NE Japan.

NASA Astrophysics Data System (ADS)

Yamada, Y.; Sanada, Y.; Moe, K.; Kubo, Y.; Inagaki, F.

2014-12-01

Precise estimation of underground temperature is a challenging issue, since direct measurements require drill holes that disturb the original underground environment. During IODP 337 expedition, we have obtained in-situ temperature datasets for several times by using geophysical logging tools. A common procedure to estimate the undisturbed maximum underground temperature is by approximating that the 'build-up' pattern of measured values in the borehole should reach to the equilibrium temperature. At the Shimokita site, this was 63.7 oC at a depth of 2466 m. We have much more measurement dataset and all of these were used to analyze detailed in-site temperatures at various depths. The result shows a non-linear temperature profile to the depth and this may be reflected by the thermal properties of the surrounding rocks.

A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Cai, Jianhua

2017-05-01

The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

Obtaining Parts

Science.gov Websites

The Cosmic Connection Parts for the Berkeley Detector Suppliers: Scintillator Eljen Technology 1 obtain the components needed to build the Berkeley Detector. These companies have helped previous the last update. He estimates that the cost to build a detector varies from $1500 to $2700 depending

Postmortem time estimation using body temperature and a finite-element computer model.

PubMed

den Hartog, Emiel A; Lotens, Wouter A

2004-09-01

In the Netherlands most murder victims are found 2-24 h after the crime. During this period, body temperature decrease is the most reliable method to estimate the postmortem time (PMT). Recently, two murder cases were analysed in which currently available methods did not provide a sufficiently reliable estimate of the PMT. In both cases a study was performed to verify the statements of suspects. For this purpose a finite-element computer model was developed that simulates a human torso and its clothing. With this model, changes to the body and the environment can also be modelled; this was very relevant in one of the cases, as the body had been in the presence of a small fire. In both cases it was possible to falsify the statements of the suspects by improving the accuracy of the PMT estimate. The estimated PMT in both cases was within the range of Henssge's model. The standard deviation of the PMT estimate was 35 min in the first case and 45 min in the second case, compared to 168 min (2.8 h) in Henssge's model. In conclusion, the model as presented here can have additional value for improving the accuracy of the PMT estimate. In contrast to the simple model of Henssge, the current model allows for increased accuracy when more detailed information is available. Moreover, the sensitivity of the predicted PMT for uncertainty in the circumstances can be studied, which is crucial to the confidence of the judge in the results.

Future PMPs Estimation in Korea under AR5 RCP 8.5 Climate Change Scenario: Focus on Dew Point Temperature Change

NASA Astrophysics Data System (ADS)

Okjeong, Lee; Sangdan, Kim

2016-04-01

According to future climate change scenarios, future temperature is expected to increase gradually. Therefore, it is necessary to reflect the effects of these climate changes to predict Probable Maximum Precipitations (PMPs). In this presentation, PMPs will be estimated with future dew point temperature change. After selecting 174 major storm events from 1981 to 2005, new PMPs will be proposed with respect to storm areas (25, 100, 225, 400, 900, 2,025, 4,900, 10,000 and 19,600 km2) and storm durations (1, 2, 4, 6, 8, 12, 18, 24, 48 and 72 hours) using the Korea hydro-meteorological method. Also, orographic transposition factor will be applied in place of the conventional terrain impact factor which has been used in previous Korean PMPs estimation reports. After estimating dew point temperature using future temperature and representative humidity information under the Korea Meteorological Administration AR5 RCP 8.5, changes in the PMPs under dew point temperature change will be investigated by comparison with present and future PMPs. This research was supported by a grant(14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

How to estimate exposure when studying the temperature-mortality relationship? A case study of the Paris area.

PubMed

Schaeffer, Laura; de Crouy-Chanel, Perrine; Wagner, Vérène; Desplat, Julien; Pascal, Mathilde

2016-01-01

Time series studies assessing the effect of temperature on mortality generally use temperatures measured by a single weather station. In the Paris region, there is a substantial measurement network, and a variety of exposure indicators created from multiple stations can be tested. The aim of this study is to test the influence of exposure indicators on the temperature-mortality relationship in the Paris region. The relationship between temperature and non-accidental mortality was assessed based on a time series analysis using Poisson regression and a generalised additive model. Twenty-five stations in Paris and its three neighbouring departments were used to create four exposure indicators. These indicators were (1) the temperature recorded by one reference station, (2) a simple average of the temperatures of all stations, (3) an average weighted on the departmental population and (4) a classification of the stations based on land use and an average weighted on the population in each class. The relative risks and the Akaike criteria were similar for all the exposure indicators. The estimated temperature-mortality relationship therefore did not appear to be significantly affected by the indicator used, regardless of study zone (departments or region) or age group. The increase in temperatures from the 90(th) to the 99(th) percentile of the temperature distribution led to a significant increase in mortality over 75 years (RR = 1.10 [95% CI, 1.07; 1.14]). Conversely, the decrease in temperature between the 10(th) and 1(st) percentile had a significant effect on the mortality under 75 years (RR = 1.04 [95% CI, 1.01; 1.06]). In the Paris area, there is no added value in taking multiple climatic stations into account when estimating exposure in time series studies. Methods to better represent the subtle temperature variations in densely populated areas in epidemiological studies are needed.

Multispectral pyrometry for surface temperature measurement of oxidized Zircaloy claddings

NASA Astrophysics Data System (ADS)

Bouvry, B.; Cheymol, G.; Ramiandrisoa, L.; Javaudin, B.; Gallou, C.; Maskrot, H.; Horny, N.; Duvaut, T.; Destouches, C.; Ferry, L.; Gonnier, C.

2017-06-01

Non-contact temperature measurement in a nuclear reactor is still a huge challenge because of the numerous constraints to consider, such as the high temperature, the steam atmosphere, and irradiation. A device is currently developed at CEA to study the nuclear fuel claddings behavior during a Loss-of-Coolant Accident. As a first step of development, we designed and tested an optical pyrometry procedure to measure the surface temperature of nuclear fuel claddings without any contact, under air, in the temperature range 700-850 °C. The temperature of Zircaloy-4 cladding samples was retrieved at various temperature levels. We used Multispectral Radiation Thermometry with the hypothesis of a constant emissivity profile in the spectral ranges 1-1.3 μm and 1.45-1.6 μm. To allow for comparisons, a reference temperature was provided by a thermocouple welded on the cladding surface. Because of thermal losses induced by the presence of the thermocouple, a heat transfer simulation was also performed to estimate the bias. We found a good agreement between the pyrometry measurement and the temperature reference, validating the constant emissivity profile hypothesis used in the MRT estimation. The expanded measurement uncertainty (k = 2) of the temperature obtained by the pyrometry method was ±4 °C, for temperatures between 700 and 850 °C. Emissivity values, between 0.86 and 0.91 were obtained.

An Estimate of Shallow, Low-Temperature Geothermal Resources of the United States: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mullane, Michelle; Gleason, Michael; McCabe, Kevin

Low-temperature geothermal resources in the United States potentially hold an enormous quantity of thermal energy, useful for direct use in residential, commercial and industrial applications such as space and water heating, greenhouse warming, pool heating, aquaculture, and low-temperature manufacturing processes. Several studies published over the past 40 years have provided assessments of the resource potential for multiple types of low-temperature geothermal systems (e.g. hydrothermal convection, hydrothermal conduction, and enhanced geothermal systems) with varying temperature ranges and depths. This paper provides a summary and additional analysis of these assessments of shallow (= 3 km), low-temperature (30-150 degrees C) geothermal resources inmore » the United States, suitable for use in direct-use applications. This analysis considers six types of geothermal systems, spanning both hydrothermal and enhanced geothermal systems (EGS). We outline the primary data sources and quantitative parameters used to describe resources in each of these categories, and present summary statistics of the total resources available. In sum, we find that low-temperature hydrothermal resources and EGS resources contain approximately 8 million and 800 million TWh of heat-in-place, respectively. In future work, these resource potential estimates will be used for modeling of the technical and market potential for direct-use geothermal applications for the U.S. Department of Energy's Geothermal Vision Study.« less

A simple-harmonic model for depicting the annual cycle of seasonal temperatures of streams

USGS Publications Warehouse

Steele, Timothy Doak

1978-01-01

Due to economic or operational constraints, stream-temperature records cannot always be collected at all sites where information is desired or at frequencies dictated by continuous or near-continuous surveillance requirements. For streams where only periodic measurements are made during the year, and that are not appreciably affected by regulation or by thermal loading , a simple harmonic function may adequately depict the annual seasonal cycle of stream temperature at any given site. Resultant harmonic coefficients obtained from available stream-temperature records may be used in the following ways: (1) To interpolate between discrete measurements by solving the harmonic function at specified times, thereby filling in estimates of stream-temperature values; (2) to characterize areal or regional patterns of natural stream-temperature values; (2) to characterize areal or regional patterns of natural stream-temperature conditions; and (3) to detect and to assess any significant at a site brought about by streamflow regulation or basin development. Moreover, less-than-daily or sampling frequencies at a given site may give estimates of annual variation of stream temperatures that are statistically comparable to estimates obtained from a daily or continuous sampling scheme. The latter procedure may result in potential savings of resources in network operations, with negligible loss in information on annual stream-temperature variations. (Woodard -USGS)

Using Integrated Assessment Models to Estimate the Economic Damages from Temperature Related Human Health Effects in the US

NASA Astrophysics Data System (ADS)

Gilmore, E.; Calvin, K. V.; Puett, R.; Sapkota, A.; Schwarber, A.

2014-12-01

Climate change is projected to increase risks to human health. One pathway that may be particularly difficult to manage is adverse human health impacts (e.g. premature mortality and morbidity) from increases in mean temperatures and changing patterns of temperature extremes. Modeling how these health risks evolve over decadal time-scales is challenging as the severity of the impacts depends on changes in climate as well as socioeconomic conditions. Here, we show estimates of health damages as well as both direct and indirect economic damages that span climate and socioeconomic dimensions for each US state to 2050. We achieve this objective by extending the integrated assessment model (IAM), Global Change Assessment Model (GCAM-USA). First, we quantify the change in premature mortality. We identify a range of exposure-response relationships for temperature related mortality through a critical review of the literature. We then implement these relationships in the GCAM by coupling them with projections of future temperature patterns and population estimates. Second, we monetize the effect of these adverse health effects, including both direct and indirect economic costs through labor force participation and productivity along a range of possible economic pathways. Finally, we evaluate how uncertainty in the parameters and assumptions affects the range of possible estimates. We conclude that the model is sensitive to assumptions regarding exposure-response relationship and population growth. The economic damages, however, are driven by the estimates of income and GDP growth as well as the potential for adaptation measures, namely the use and effectiveness of air conditioning.

Obtaining parsimonious hydraulic conductivity fields using head and transport observations: A Bayesian geostatistical parameter estimation approach

NASA Astrophysics Data System (ADS)

Fienen, M.; Hunt, R.; Krabbenhoft, D.; Clemo, T.

2009-08-01

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained.

Obtaining parsimonious hydraulic conductivity fields using head and transport observations: A Bayesian geostatistical parameter estimation approach

USGS Publications Warehouse

Fienen, M.; Hunt, R.; Krabbenhoft, D.; Clemo, T.

2009-01-01

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained.

A New Multi-Basin Calibration for Estimating Paleo-Temperature Using Mg/Ca from Tests of Neogloboquadrina dutertrei

NASA Astrophysics Data System (ADS)

Collins, M. S.; Hertzberg, J. E.; Mekik, F.; Schmidt, M. W.

2017-12-01

Based on the thermodynamics of solid-solution substitution of Mg for Ca in biogenic calcite, magnesium to calcium ratios in planktonic foraminifera have been proposed as a means by which variations in habitat water temperatures can be reconstructed. Doing this accurately has been a problem, however, as we demonstrate that various calibration equations provide disparate temperature estimates from the same Mg/Ca dataset. We examined both new and published data to derive a globally applicable temperature-Mg/Ca relationship and from this relationship to accurately predict habitat depth for Neogloboquadrina dutertrei - a deep chlorophyll maximum dweller. N. dutertrei samples collected from Atlantic core tops were analyzed for trace element compositions at Texas A&M University, and the measured Mg/Ca ratios were used to predict habitat temperatures using multiple pre-existing calibration equations. When combining Atlantic and previously published Pacific Mg/Ca datasets for N. dutertrei, a notable dissolution effect was evident. To overcome this issue, we used the G. menardii Fragmentation Index (MFI) to account for dissolution and generated a multi-basin temperature equation using multiple linear regression to predict habitat temperature. However, the correlations between Mg/Ca and temperature, as well as the calculated MFI percent dissolved, suggest that N. dutertrei Mg/Ca ratios are affected equally by both variables. While correcting for dissolution makes habitat depth estimation more accurate, the lack of a definitively strong correlation between Mg/Ca and temperature is likely an effect of variable habitat depth for this species because most calibration equations have assumed a uniform habitat depth for this taxon.

Mechanisms Controlling Global Mean Sea Surface Temperature Determined From a State Estimate

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Piecuch, C. G.

2018-04-01

Global mean sea surface temperature (T¯) is a variable of primary interest in studies of climate variability and change. The temporal evolution of T¯ can be influenced by surface heat fluxes (F¯) and by diffusion (D¯) and advection (A¯) processes internal to the ocean, but quantifying the contribution of these different factors from data alone is prone to substantial uncertainties. Here we derive a closed T¯ budget for the period 1993-2015 based on a global ocean state estimate, which is an exact solution of a general circulation model constrained to most extant ocean observations through advanced optimization methods. The estimated average temperature of the top (10-m thick) level in the model, taken to represent T¯, shows relatively small variability at most time scales compared to F¯, D¯, or A¯, reflecting the tendency for largely balancing effects from all the latter terms. The seasonal cycle in T¯ is mostly determined by small imbalances between F¯ and D¯, with negligible contributions from A¯. While D¯ seems to simply damp F¯ at the annual period, a different dynamical role for D¯ at semiannual period is suggested by it being larger than F¯. At periods longer than annual, A¯ contributes importantly to T¯ variability, pointing to the direct influence of the variable ocean circulation on T¯ and mean surface climate.

Do We Really Need Sinusoidal Surface Temperatures to Apply Heat Tracing Techniques to Estimate Streambed Fluid Fluxes?

NASA Astrophysics Data System (ADS)

Luce, C. H.; Tonina, D.; Applebee, R.; DeWeese, T.

2017-12-01

Two common refrains about using the one-dimensional advection diffusion equation to estimate fluid fluxes, thermal conductivity, or bed surface elevation from temperature time series in streambeds are that the solution assumes that 1) the surface boundary condition is a sine wave or nearly so, and 2) there is no gradient in mean temperature with depth. Concerns on these subjects are phrased in various ways, including non-stationarity in frequency, amplitude, or phase. Although the mathematical posing of the original solution to the problem might lead one to believe these constraints exist, the perception that they are a source of error is a fallacy. Here we re-derive the inverse solution of the 1-D advection-diffusion equation starting with an arbitrary surface boundary condition for temperature. In doing so, we demonstrate the frequency-independence of the solution, meaning any single frequency can be used in the frequency-domain solutions to estimate thermal diffusivity and 1-D fluid flux in streambeds, even if the forcing has multiple frequencies. This means that diurnal variations with asymmetric shapes, gradients in the mean temperature with depth, or `non-stationary' amplitude and frequency (or phase) do not actually represent violations of assumptions, and they should not cause errors in estimates when using one of the suite of existing solution methods derived based on a single frequency. Misattribution of errors to these issues constrains progress on solving real sources of error. Numerical and physical experiments are used to verify this conclusion and consider the utility of information at `non-standard' frequencies and multiple frequencies to augment the information derived from time series of temperature.

Color temperature measurement in laser-driven shock waves

NASA Astrophysics Data System (ADS)

Hall, T. A.; Benuzzi, A.; Batani, D.; Beretta, D.; Bossi, S.; Faral, B.; Koenig, M.; Krishnan, J.; Löautwer, Th.; Mahdieh, M.

1997-06-01

A simultaneous measurement of color temperature and shock velocity in laser-driven shocks is presented. The color temperature was measured from the target rear side emissivity, and the shock velocity by using stepped targets. A very good planarity of the shock was ensured by the phase zone plate smoothing technique. A simple model of the shock luminosity has been developed in order to estimate the shock temperature from the experimental rear side emissivity. Results have been compared to temperatures obtained from the shock velocity for a material of a known equation of state.

Low temperature process for obtaining thin glass films

DOEpatents

Brinker, C. Jeffrey; Reed, Scott T.

1984-01-01

A method for coating a substrate with a glass-like film comprises, applying to the substrate an aqueous alcoholic solution containing a polymeric network of partially hydrolyzed metal alkoxide into which network there is incorporated finely powdered glass, whereby there is achieved on the substrate a coherent and adherent initial film; and heating said film to a temperature sufficient to melt said powdered glass component, thereby converting said initial film to a final densified film.

Low temperature process for obtaining thin glass films

DOEpatents

Brinker, C.J.; Reed, S.T.

A method for coating a substrate with a glass-like film comprises, applying to the substrate an aqueous alcoholic solution containing a polymeric network of partially hydrolyzed metal alkoxide into which network there is incorporated finely powdered glass, whereby there is achieved on the substrate a coherent and adherent initial film; and heating said film to a temperature sufficient to melt said powdered glass component, thereby converting said initial film to a final densified film.

Correlation of Mixture Temperature Data Obtained from Bare Intake-manifold Thermocouples

NASA Technical Reports Server (NTRS)

White, H. Jack; Gammon, Goldie L

1946-01-01

A relatively simple equation has been found to express with fair accuracy, variation in manifold-charge temperature with charge in engine operating conditions. This equation and associated curves have been checked by multi cylinder-engine data, both test stand and flight, over a wide range of operating conditions. Average mixture temperatures, predicted by the equations of this report, agree reasonably well with results within the same range of carburetor-air temperatures from laboratories and test stands other than the NACA.

An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions, 2

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Walker, H. F.

1976-01-01

The problem of obtaining numerically maximum likelihood estimates of the parameters for a mixture of normal distributions is addressed. In recent literature, a certain successive approximations procedure, based on the likelihood equations, is shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, a general iterative procedure is introduced, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. With probability 1 as the sample size grows large, it is shown that this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. The step-size which yields optimal local convergence rates for large samples is determined in a sense by the separation of the component normal densities and is bounded below by a number between 1 and 2.

Methods for estimating heterocyclic amine concentrations in cooked meats in the US diet.

PubMed

Keating, G A; Bogen, K T

2001-01-01

Heterocyclic amines (HAs) are formed in numerous cooked foods commonly consumed in the diet. A method was developed to estimate dietary HA levels using HA concentrations in experimentally cooked meats reported in the literature and meat consumption data obtained from a national dietary survey. Cooking variables (meat internal temperature and weight loss, surface temperature and time) were used to develop relationships for estimating total HA concentrations in six meat types. Concentrations of five individual HAs were estimated for specific meat type/cooking method combinations based on linear regression of total and individual HA values obtained from the literature. Using these relationships, total and individual HA concentrations were estimated for 21 meat type/cooking method combinations at four meat doneness levels. Reported consumption of the 21 meat type/cooking method combinations was obtained from a national dietary survey and the age-specific daily HA intake calculated using the estimated HA concentrations (ng/g) and reported meat intakes. Estimated mean daily total HA intakes for children (to age 15 years) and adults (30+ years) were 11 and 7.0 ng/kg/day, respectively, with 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) estimated to comprise approximately 65% of each intake. Pan-fried meats were the largest source of HA in the diet and chicken the largest source of HAs among the different meat types.

Estimation of Al2O3 critical temperature using a Langmuir probe in laser ablation

NASA Astrophysics Data System (ADS)

Yahiaoui, K.; Abdelli-Messaci, S.; Messaoud Aberkane, S.; Kellou, A.

2016-11-01

Pulsed laser deposition (PLD) has demonstrated its capacity in thin films growing under the moderate laser intensity. But when the laser intensity increases, the presence of droplets on the thin film limits the PLD efficiency such that the process needs an optimization study. In this way, an experimental study has been conducted in order to correlate between the appearance of those droplets and the laser fluence. The comprehension of the physical mechanism during ablation and the control of the deposition parameters allowed to get a safe process. Our experiment consists in measuring the amount of ejected matter from polycrystalline alumina target as a function of the laser fluence when irradiated by a KrF laser. According to laser fluence, several kinds of ablation regimes have been identified. Below a threshold value found as 12 J/cm2, the mechanism of ablation was assigned to normal evaporation, desorption and nonthermal processes. While above this threshold value, the mechanism of ablation was assigned to phase explosion phenomenon which is responsible of droplets formation when the surface temperature approaches the critical temperature T tc. A negative charge collector was used to collect the positive ions in the plume. Their times of flight (TOF) signal were used to estimate the appropriate T tc for alumina target. Ions yield, current as well as kinetic energy were deduced from the TOF signal. Their evolutions show the occurrence of an optical breakdown in the vapor plume which is well correlated with the onset of the phase explosion phenomenon. At 10 J/cm2, the ions velocities collected by the probe have been compared to those obtained from optical emission spectroscopy diagnostic and were discussed. To prove the occurrence of phase explosion by the appearance of droplets, several thin films were elaborated on Si (100) substrate at different laser fluence into vacuum. They have been characterized by scanning electron microscope. The results were well

A Gridded Daily Min/Max Temperature Dataset With 0.1° Resolution for the Yangtze River Valley and its Error Estimation

NASA Astrophysics Data System (ADS)

Xiong, Qiufen; Hu, Jianglin

2013-05-01

The minimum/maximum (Min/Max) temperature in the Yangtze River valley is decomposed into the climatic mean and anomaly component. A spatial interpolation is developed which combines the 3D thin-plate spline scheme for climatological mean and the 2D Barnes scheme for the anomaly component to create a daily Min/Max temperature dataset. The climatic mean field is obtained by the 3D thin-plate spline scheme because the relationship between the decreases in Min/Max temperature with elevation is robust and reliable on a long time-scale. The characteristics of the anomaly field tend to be related to elevation variation weakly, and the anomaly component is adequately analyzed by the 2D Barnes procedure, which is computationally efficient and readily tunable. With this hybridized interpolation method, a daily Min/Max temperature dataset that covers the domain from 99°E to 123°E and from 24°N to 36°N with 0.1° longitudinal and latitudinal resolution is obtained by utilizing daily Min/Max temperature data from three kinds of station observations, which are national reference climatological stations, the basic meteorological observing stations and the ordinary meteorological observing stations in 15 provinces and municipalities in the Yangtze River valley from 1971 to 2005. The error estimation of the gridded dataset is assessed by examining cross-validation statistics. The results show that the statistics of daily Min/Max temperature interpolation not only have high correlation coefficient (0.99) and interpolation efficiency (0.98), but also the mean bias error is 0.00 °C. For the maximum temperature, the root mean square error is 1.1 °C and the mean absolute error is 0.85 °C. For the minimum temperature, the root mean square error is 0.89 °C and the mean absolute error is 0.67 °C. Thus, the new dataset provides the distribution of Min/Max temperature over the Yangtze River valley with realistic, successive gridded data with 0.1° × 0.1° spatial resolution and

Estimation of tropical forest canopy temperatures, thermal response numbers, and evapotranspiration using an aircraft-based thermal sensor

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Lieberman, Diana; Lieberman, Milton; Hartshorn, Gary S.; Peralta, Rodolfo

1990-01-01

Thermal infrared Multispectral Scanner (TIMS) data were collected at a resolution of 5 to 10 m from a tropical rain forest over an elevation gradient from 35 to 2700 m in the Braulio Carrillo National Park in Costa Rica. Flight lines were repeated with a 15 to 30 minute time difference for measurement of forest canopy thermal response over time. Concurrent radiosonde measurements of atmospheric profiles of air temperature and moisture provided inputs to LOWTRAN6 for atmospheric radiance corrections of the TIMS data. Techniques for using calibrated aircraft-based thermal scanner data to examine tropical forest canopy thermal properties are described. Forest canopy temperature changes over time assessed between repeated, duplicated flight lines were combined with estimates of surface radiative energy measurements from towers above the forest canopy to determine temperature spatial variability, calculate Thermal Response Numbers (TRN), and estimate evapotranspiration along the elevation gradient from selected one hectare forest inventory plots.

A convenient method of obtaining percentile norms and accompanying interval estimates for self-report mood scales (DASS, DASS-21, HADS, PANAS, and sAD).

PubMed

Crawford, John R; Garthwaite, Paul H; Lawrie, Caroline J; Henry, Julie D; MacDonald, Marie A; Sutherland, Jane; Sinha, Priyanka

2009-06-01

A series of recent papers have reported normative data from the general adult population for commonly used self-report mood scales. To bring together and supplement these data in order to provide a convenient means of obtaining percentile norms for the mood scales. A computer program was developed that provides point and interval estimates of the percentile rank corresponding to raw scores on the various self-report scales. The program can be used to obtain point and interval estimates of the percentile rank of an individual's raw scores on the DASS, DASS-21, HADS, PANAS, and sAD mood scales, based on normative sample sizes ranging from 758 to 3822. The interval estimates can be obtained using either classical or Bayesian methods as preferred. The computer program (which can be downloaded at www.abdn.ac.uk/~psy086/dept/MoodScore.htm) provides a convenient and reliable means of supplementing existing cut-off scores for self-report mood scales.

Developing a Model to Estimate Freshwater Gross Primary Production Using MODIS Surface Temperature Observations

NASA Astrophysics Data System (ADS)

Saberi, S. J.; Weathers, K. C.; Norouzi, H.; Prakash, S.; Solomon, C.; Boucher, J. M.

2016-12-01

Lakes contribute to local and regional climate conditions, cycle nutrients, and are viable indicators of climate change due to their sensitivity to disturbances in their water and airsheds. Utilizing spaceborne remote sensing (RS) techniques has considerable potential in studying lake dynamics because it allows for coherent and consistent spatial and temporal observations as well as estimates of lake functions without in situ measurements. However, in order for RS products to be useful, algorithms that relate in situ measurements to RS data must be developed. Estimates of lake metabolic rates are of particular scientific interest since they are indicative of lakes' roles in carbon cycling and ecological function. Currently, there are few existing algorithms relating remote sensing products to in-lake estimates of metabolic rates and more in-depth studies are still required. Here we use satellite surface temperature observations from Moderate Resolution Imaging Spectroradiometer (MODIS) product (MYD11A2) and published in-lake gross primary production (GPP) estimates for eleven globally distributed lakes during a one-year period to produce a univariate quadratic equation model. The general model was validated using other lakes during an equivalent one-year time period (R2=0.76). The statistical analyses reveal significant positive relationships between MODIS temperature data and the previously modeled in-lake GPP. Lake-specific models for Lake Mendota (USA), Rotorua (New Zealand), and Taihu (China) showed stronger relationships than the general combined model, pointing to local influences such as watershed characteristics on in-lake GPP in some cases. These validation data suggest that the developed algorithm has a potential to predict lake GPP on a global scale.

Neural network-based preprocessing to estimate the parameters of the X-ray emission of a single-temperature thermal plasma

NASA Astrophysics Data System (ADS)

Ichinohe, Y.; Yamada, S.; Miyazaki, N.; Saito, S.

2018-04-01

We present data preprocessing based on an artificial neural network to estimate the parameters of the X-ray emission spectra of a single-temperature thermal plasma. The method finds appropriate parameters close to the global optimum. The neural network is designed to learn the parameters of the thermal plasma (temperature, abundance, normalization and redshift) of the input spectra. After training using 9000 simulated X-ray spectra, the network has grown to predict all the unknown parameters with uncertainties of about a few per cent. The performance dependence on the network structure has been studied. We applied the neural network to an actual high-resolution spectrum obtained with Hitomi. The predicted plasma parameters agree with the known best-fitting parameters of the Perseus cluster within uncertainties of ≲10 per cent. The result shows that neural networks trained by simulated data might possibly be used to extract a feature built in the data. This would reduce human-intensive preprocessing costs before detailed spectral analysis, and would help us make the best use of the large quantities of spectral data that will be available in the coming decades.

Estimates of crystalline LiF thermal conductivity at high temperature and pressure by a Green-Kubo method

DOE PAGES

Jones, R. E.; Ward, D. K.

2016-07-18

Here, given the unique optical properties of LiF, it is often used as an observation window in high-temperature and -pressure experiments; hence, estimates of its transmission properties are necessary to interpret observations. Since direct measurements of the thermal conductivity of LiF at the appropriate conditions are difficult, we resort to molecular simulation methods. Using an empirical potential validated against ab initio phonon density of states, we estimate the thermal conductivity of LiF at high temperatures (1000–4000 K) and pressures (100–400 GPa) with the Green-Kubo method. We also compare these estimates to those derived directly from ab initio data. To ascertainmore » the correct phase of LiF at these extreme conditions, we calculate the (relative) phase stability of the B1 and B2 structures using a quasiharmonic ab initio model of the free energy. We also estimate the thermal conductivity of LiF in an uniaxial loading state that emulates initial stages of compression in high-stress ramp loading experiments and show the degree of anisotropy induced in the conductivity due to deformation.« less

Estimating core temperature in infants and children after cardiac surgery: a comparison of six methods.

PubMed

Maxton, Fiona J C; Justin, Linda; Gillies, Donna

2004-01-01

Monitoring temperature in critically ill children is an important component of care, yet the accuracy of methods is often questioned. Temperature measured in the pulmonary artery is considered the 'gold standard', but this route is unsuitable for the majority of patients. An accurate, reliable and less invasive method is, however, yet to be established in paediatric intensive care work. To determine which site most closely reflects core temperature in babies and children following cardiac surgery, by comparing pulmonary artery temperature to the temperature measured at rectal, bladder, nasopharyngeal, axillary and tympanic sites. A convenience sample of 19 postoperative cardiac patients was studied. Temperature was recorded as a continuous measurement from pulmonary artery, rectal, nasopharyngeal and bladder sites. Axillary and tympanic temperatures were recorded at 30 minute intervals for 6 1/2 hours postoperatively. The small sample size of 19 infants and children limits the generalizability of the study. Repeated measures analysis of variance demonstrated no significant difference between pulmonary artery and bladder temperatures, and pulmonary artery and nasopharyngeal temperatures. Intraclass correlation showed that agreement was greatest between pulmonary artery temperature and temperature measured by bladder catheter. There was a significant difference between pulmonary artery temperature and temperature measured at rectal, tympanic and pulmonary artery and axillary sites. Repeated measures analysis showed a significant lag between pulmonary artery and rectal temperature of between 0 and 150 minutes after the 6-hour measurement period. In this study, bladder temperature was shown to be the best estimate of pulmonary artery temperature, closely followed by the temperature measured by nasopharyngeal probe. The results support the use of bladder or nasopharyngeal catheters to monitor temperature in critically ill children after cardiac surgery.

Sapphire Fabry-Perot high-temperature sensor study

NASA Astrophysics Data System (ADS)

Yao, Yi-qiang; Liang, Wei-long; Gui, Xinwang; Fan, Dian

2017-04-01

A new structure sapphire fiber Fabry-Perot (F-P) high-temperature sensor based on sapphire wafer was proposed and fabricated. The sensor uses the sapphire fiber as a transmission waveguide, the sapphire wafer as an Fabry-Perot (F-P) interferometer and the new structure of "Zirconia ferrule-Zirconia tube" as the sensor fixing structure of the sensor. The reflection spectrum of the interferometer was demodulated by a serial of data processing including FIR bandpass filter, FFT (Fast Fourier Transformation) estimation and LSE (least squares estimation) compensation to obtain more precise OPD. Temperature measurement range is from 20 to 1000°C in experiment. The experimental results show that the sensor has the advantages of small size, low cost, simple fabrication and high repeatability. It can be applied for longterm, stable and high-precision high temperature measurement in harsh environments.

Body Segment Differences in Surface Area, Skin Temperature and 3D Displacement and the Estimation of Heat Balance during Locomotion in Hominins

PubMed Central

Cross, Alan; Collard, Mark; Nelson, Andrew

2008-01-01

The conventional method of estimating heat balance during locomotion in humans and other hominins treats the body as an undifferentiated mass. This is problematic because the segments of the body differ with respect to several variables that can affect thermoregulation. Here, we report a study that investigated the impact on heat balance during locomotion of inter-segment differences in three of these variables: surface area, skin temperature and rate of movement. The approach adopted in the study was to generate heat balance estimates with the conventional method and then compare them with heat balance estimates generated with a method that takes into account inter-segment differences in surface area, skin temperature and rate of movement. We reasoned that, if the hypothesis that inter-segment differences in surface area, skin temperature and rate of movement affect heat balance during locomotion is correct, the estimates yielded by the two methods should be statistically significantly different. Anthropometric data were collected on seven adult male volunteers. The volunteers then walked on a treadmill at 1.2 m/s while 3D motion capture cameras recorded their movements. Next, the conventional and segmented methods were used to estimate the volunteers' heat balance while walking in four ambient temperatures. Lastly, the estimates produced with the two methods were compared with the paired t-test. The estimates of heat balance during locomotion yielded by the two methods are significantly different. Those yielded by the segmented method are significantly lower than those produced by the conventional method. Accordingly, the study supports the hypothesis that inter-segment differences in surface area, skin temperature and rate of movement impact heat balance during locomotion. This has important implications not only for current understanding of heat balance during locomotion in hominins but also for how future research on this topic should be approached. PMID

Body segment differences in surface area, skin temperature and 3D displacement and the estimation of heat balance during locomotion in hominins.

PubMed

Cross, Alan; Collard, Mark; Nelson, Andrew

2008-06-18

The conventional method of estimating heat balance during locomotion in humans and other hominins treats the body as an undifferentiated mass. This is problematic because the segments of the body differ with respect to several variables that can affect thermoregulation. Here, we report a study that investigated the impact on heat balance during locomotion of inter-segment differences in three of these variables: surface area, skin temperature and rate of movement. The approach adopted in the study was to generate heat balance estimates with the conventional method and then compare them with heat balance estimates generated with a method that takes into account inter-segment differences in surface area, skin temperature and rate of movement. We reasoned that, if the hypothesis that inter-segment differences in surface area, skin temperature and rate of movement affect heat balance during locomotion is correct, the estimates yielded by the two methods should be statistically significantly different. Anthropometric data were collected on seven adult male volunteers. The volunteers then walked on a treadmill at 1.2 m/s while 3D motion capture cameras recorded their movements. Next, the conventional and segmented methods were used to estimate the volunteers' heat balance while walking in four ambient temperatures. Lastly, the estimates produced with the two methods were compared with the paired t-test. The estimates of heat balance during locomotion yielded by the two methods are significantly different. Those yielded by the segmented method are significantly lower than those produced by the conventional method. Accordingly, the study supports the hypothesis that inter-segment differences in surface area, skin temperature and rate of movement impact heat balance during locomotion. This has important implications not only for current understanding of heat balance during locomotion in hominins but also for how future research on this topic should be approached.

The Temperature of the Icelandic Mantle Plume from Aluminium-in-Olivine Thermometry

NASA Astrophysics Data System (ADS)

Matthews, S.; Shorttle, O.; Maclennan, J.

2015-12-01

Temperature is a key control on the physical properties of the mantle, in particular the extent of melting during upwelling. It is not, however, a unique control on many of the parameters used to estimate mantle temperature. For example igneous crustal thickness which has often been used as a first-order proxy for mantle temperature, is also affected by mantle lithology and plume flux. Alternatives to geophysical indicators of mantle temperature are petrological thermometers. However, these record crystallisation temperatures, therefore a series of assumptions about the coupled melt- solid mantle thermal history must be made when calculating back to mantle potential temperature. In this study we investigate how these assumptions may affect mantle temperature estimates and how crystallisation temperatures may offer insights into the melting and melt transport processes, focussing on a new set of crystallisation temperature estimates we have made on primitive Icelandic basalts.We used the aluminium-in-olivine thermometer of Coogan et al. (2014) to estimate crystallisation temperatures of olivine phenocrysts in a suite of samples from the Northern Volcanic Zone (NVZ) of Iceland. The data suggest that within a single volcanic system crystallisation temperature depends strongly on the olivine forsterite content, thus the history of melt evolution, and how the eruption samples this, must be considered when extrapolating to mantle temperature. To assess the influence of the assumptions required to obtain mantle temperature we constructed a simple thermal model incorporating varying proportions of lherzolite, pyroxenite and harzburgite undergoing decompression melting. A trade off between increasing mantle temperature and decreasing pyroxenite (or increasing harzburgite) in the source is observed. Using this dataset and our model, calculations reveal a potential temperature of 1470±130 °C for Iceland, and a temperature excess of 150±40 °C relative to ambient mantle

Inversion of AMSR-E observations for land surface temperature estimation: 2. Global comparison with infrared satellite temperature

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Jiménez, C.; Prigent, C.; Trigo, I. F.; DaCamara, C. C.

2017-03-01

A comparison of land surface temperature (Ts) derived from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) with infrared Ts is presented. The infrared Ts include clear-sky estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Spinning Enhanced Visible and Infrared Imager, the Geostationary Operational Environmental Satellite (GOES) Imager, and the Japanese Meteorological Imager. The higher discrepancies between AMSR-E and MODIS are observed over deserts and snow-covered areas. The former seems to be associated with Ts underestimation by MODIS, whereas the latter is mostly related to uncertainties in microwave emissivity over snow/ice. Ts differences between AMSR-E and MODIS are significantly reduced after masking out snow and deserts, with a bias change from 2.6/4.6 K to 3.0/1.4 K for daytime/nighttime and a standard deviation (STD) decrease from 7.3/7.9 K to 5.1/3.9 K. When comparing with all infrared sensors, the STD of the differences between microwave and infrared Ts is generally higher than between IR retrievals. However, the biases between microwave and infrared Ts are, in some cases, of the same order as the ones observed between infrared products. This is the case for GOES, with daytime biases with respect to AMSR-E and MODIS of 0.45 K and 0.60 K, respectively. While the infrared Ts are clear-sky estimates, AMSR-E also provides Ts under cloudy conditions. For frequently cloudy regions, this results in a large increase of available Ts estimates (>250%), making the microwave Ts a very powerful complement of the infrared estimates.

3D brain tumor localization and parameter estimation using thermographic approach on GPU.

PubMed

Bousselham, Abdelmajid; Bouattane, Omar; Youssfi, Mohamed; Raihani, Abdelhadi

2018-01-01

The aim of this paper is to present a GPU parallel algorithm for brain tumor detection to estimate its size and location from surface temperature distribution obtained by thermography. The normal brain tissue is modeled as a rectangular cube including spherical tumor. The temperature distribution is calculated using forward three dimensional Pennes bioheat transfer equation, it's solved using massively parallel Finite Difference Method (FDM) and implemented on Graphics Processing Unit (GPU). Genetic Algorithm (GA) was used to solve the inverse problem and estimate the tumor size and location by minimizing an objective function involving measured temperature on the surface to those obtained by numerical simulation. The parallel implementation of Finite Difference Method reduces significantly the time of bioheat transfer and greatly accelerates the inverse identification of brain tumor thermophysical and geometrical properties. Experimental results show significant gains in the computational speed on GPU and achieve a speedup of around 41 compared to the CPU. The analysis performance of the estimation based on tumor size inside brain tissue also presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimates of the temperatures of hydrocarbon generation in the region of the Sea of Okhotsk

NASA Astrophysics Data System (ADS)

Verzhbitsky, E. V.; Berlin, Yu. M.; Kononov, M. V.; Marina, M. M.

2006-07-01

Particular features of the tectonic structure and anomalous distribution of the geothermal, geomagnetic, and gravity fields in the region of the Sea of Okhotsk are considered. On the basis of heat flow data, the ages of large-scale structures in the Sea of Okhotsk are estimated at 65 Ma for the Central Okhotsk Rise and 36 Ma for the South Okhotsk Basin. The age of the South Okhotsk Basin is confirmed by the data on the kinematics and corresponds to a 50-km thickness of the lithosphere. This is in accordance with the thickness value obtained by magnetotelluric soundings. A comparative analysis of the model geothermal background and the measured heat flow values on the Akademii Nauk Rise is performed. The analysis points to an abnormally high (by approximately 20%) measured heat flow, which agrees with the high negative gradient of gravity anomalies. The estimates of the deep heat flow and the basement age of the riftogenic basins in the Sea of Okhotsk were carried out in the following areas: the Deryugin Basin (18 Ma, Early Miocene), the TINRO Basin (12 Ma, Middle Miocene), and the West Kamchatka Basin (23 Ma, Late Oligocene). The temperatures at the boundaries of the main lithological complexes of the sedimentary cover are calculated and the zones of oil and gas generation are defined. On the basis of geothermal, magnetic, structural, and other geological-geophysical data, a kinematic model of the region of the Sea of Okhotsk for a period of 36 Ma was calculated and constructed.

Uncertainty Estimates of Psychoacoustic Thresholds Obtained from Group Tests

NASA Technical Reports Server (NTRS)

Rathsam, Jonathan; Christian, Andrew

2016-01-01

Adaptive psychoacoustic test methods, in which the next signal level depends on the response to the previous signal, are the most efficient for determining psychoacoustic thresholds of individual subjects. In many tests conducted in the NASA psychoacoustic labs, the goal is to determine thresholds representative of the general population. To do this economically, non-adaptive testing methods are used in which three or four subjects are tested at the same time with predetermined signal levels. This approach requires us to identify techniques for assessing the uncertainty in resulting group-average psychoacoustic thresholds. In this presentation we examine the Delta Method of frequentist statistics, the Generalized Linear Model (GLM), the Nonparametric Bootstrap, a frequentist method, and Markov Chain Monte Carlo Posterior Estimation and a Bayesian approach. Each technique is exercised on a manufactured, theoretical dataset and then on datasets from two psychoacoustics facilities at NASA. The Delta Method is the simplest to implement and accurate for the cases studied. The GLM is found to be the least robust, and the Bootstrap takes the longest to calculate. The Bayesian Posterior Estimate is the most versatile technique examined because it allows the inclusion of prior information.

Joint Assimilation of SMOS Brightness Temperature and GRACE Terrestrial Water Storage Observations for Improved Soil Moisture Estimation

NASA Technical Reports Server (NTRS)

Girotto, Manuela; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Rodell, Matthew

2017-01-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0 - 5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Joint assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for improved soil moisture estimation

NASA Astrophysics Data System (ADS)

Girotto, M.; Reichle, R. H.; De Lannoy, G.; Rodell, M.

2017-12-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0-5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Estimating Long-Term Survival Temperatures at the Assemblage Level in the Marine Environment: Towards Macrophysiology

PubMed Central

Richard, Joëlle; Morley, Simon Anthony; Thorne, Michael A. S.; Peck, Lloyd Samuel

2012-01-01

Defining ecologically relevant upper temperature limits of species is important in the context of environmental change. The approach used in the present paper estimates the relationship between rates of temperature change and upper temperature limits for survival in order to evaluate the maximum long-term survival temperature (Ts). This new approach integrates both the exposure time and the exposure temperature in the evaluation of temperature limits. Using data previously published for different temperate and Antarctic marine environments, we calculated Ts in each environment, which allowed us to calculate a new index: the Warming Allowance (WA). This index is defined as the maximum environmental temperature increase which an ectotherm in a given environment can tolerate, possibly with a decrease in performance but without endangering survival over seasonal or lifetime time-scales. It is calculated as the difference between maximum long-term survival temperature (Ts) and mean maximum habitat temperature. It provides a measure of how close a species, assemblage or fauna are living to their temperature limits for long-term survival and hence their vulnerability to environmental warming. In contrast to data for terrestrial environments showing that warming tolerance increases with latitude, results here for marine environments show a less clear pattern as the smallest WA value was for the Peru upwelling system. The method applied here, relating upper temperature limits to rate of experimental warming, has potential for wide application in the identification of faunas with little capacity to survive environmental warming. PMID:22509340

Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures

EPA Pesticide Factsheets

This is a presentation titled Estimating the Effect of Climate Change on Crop Yields and Farmland Values: The Importance of Extreme Temperatures that was given for the National Center for Environmental Economics

Soil moisture and properties estimation by assimilating soil temperatures using particle batch smoother: A new perspective for DTS

NASA Astrophysics Data System (ADS)

Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Van De Giesen, N.

2015-12-01

Soil moisture, hydraulic and thermal properties are critical for understanding the soil surface energy balance and hydrological processes. Here, we will discuss the potential of using soil temperature observations from Distributed Temperature Sensing (DTS) to investigate the spatial variability of soil moisture and soil properties. With DTS soil temperature can be measured with high resolution (spatial <1m, and temporal < 1min) in cables up to kilometers in length. Soil temperature evolution is primarily controlled by the soil thermal properties, and the energy balance at the soil surface. Hence, soil moisture, which affects both soil thermal properties and the energy that participates the evaporation process, is strongly correlated to the soil temperatures. In addition, the dynamics of the soil moisture is determined by the soil hydraulic properties.Here we will demonstrate that soil moisture, hydraulic and thermal properties can be estimated by assimilating observed soil temperature at shallow depths using the Particle Batch Smoother (PBS). The PBS can be considered as an extension of the particle filter, which allows us to infer soil moisture and soil properties using the dynamics of soil temperature within a batch window. Both synthetic and real field data will be used to demonstrate the robustness of this approach. We will show that the proposed method is shown to be able to handle different sources of uncertainties, which may provide a new view of using DTS observations to estimate sub-meter resolution soil moisture and properties for remote sensing product validation.

Experimental estimation of the bisulfite isomer quotient as a function of temperature: Implications for sulfur isotope fractionations in aqueous sulfite solutions

NASA Astrophysics Data System (ADS)

Eldridge, Daniel L.; Mysen, Bjorn O.; Cody, George D.

2018-01-01

Bisulfite (HSO3-) and sulfite (SO32-) compounds play key roles in numerous geochemical and biochemical processes extending from the atmosphere to the subseafloor biosphere. Despite decades of spectroscopic investigations, the molecular composition of HSO3- in solution remains uncertain and, thus, the role of bisulfite in (bio)chemical and isotope fractionation processes is unclear. We report new experimental estimates for the bisulfite isomer quotient (Qi = [(HO)SO2-]/[(HS)O3-]; [] = concentration) as a function of temperature from the interpretation of Raman spectra collected from aqueous NaHSO3 solutions contained in fused silica capsules. In pure NaHSO3 solutions (1Na+:1HSO3-, stoichiometric) over [NaHSO3] = 0.2-0.4 m (moles/kg H2O), the following relationship is obtained:

TEMperature Pressure ESTimation of a homogeneous boiling fuel-steel mixture in an LMFBR core. [TEMPEST code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pyun, J.J.; Majumdar, D.

The paper describes TEMPEST, a simple computer program for the temperature and pressure estimation of a boiling fuel-steel pool in an LMFBR core. The time scale of interest of this program is large, of the order of ten seconds. Further, the vigorous boiling in the pool will generate a large contact, and hence a large heat transfer between fuel and steel. The pool is assumed to be a uniform mixture of fuel and steel, and consequently vapor production is also assumed to be uniform throughout the pool. The pool is allowed to expand in volume if there is steel meltingmore » at the walls. In this program, the total mass of liquid and vapor fuel is always kept constant, but the total steel mass in the pool may change by steel wall melting. Because of a lack of clear understanding of the physical phenomena associated with the progression of a fuel-steel mixture at high temperature, various input options have been built-in to enable one to perform parametric studies. For example, the heat transfer from the pool to the surrounding steel structure may be controlled by input values for the heat transfer coefficients, or, the heat transfer may be calculated by a correlation obtained from the literature. Similarly, condensation of vapor on the top wall can be specified by input values of the condensation coefficient; the program can otherwise calculate condensation according to the non-equilibrium model predictions. Meltthrough rates of the surrounding steel walls can be specified by a fixed melt-rate or can be determined by a fraction of the heat loss that goes to steel-melting. The melted steel is raised to the pool temperature before it is joined with the pool material. Several applications of this program to various fuel-steel pools in the FFTF and the CRBR cores are discussed.« less

Differences between the most used equations in BAT-human studies to estimate parameters of skin temperature in young lean men.

PubMed

Martinez-Tellez, Borja; Sanchez-Delgado, Guillermo; Acosta, Francisco M; Alcantara, Juan M A; Boon, Mariëtte R; Rensen, Patrick C N; Ruiz, Jonatan R

2017-09-05

Cold exposure is necessary to activate human brown adipose tissue (BAT), resulting in heat production. Skin temperature is an indirect measure to monitor the body's reaction to cold. The aim of this research was to study whether the most used equations to estimate parameters of skin temperature in BAT-human studies measure the same values of temperature in young lean men (n = 11: 23.4 ± 0.5 years, fat mass: 19.9 ± 1.2%). Skin temperature was measured with 26 ibuttons at 1-minute intervals in warm and cold room conditions. We used 12 equations to estimate parameters of mean, proximal, and distal skin temperature as well as skin temperature gradients. Data were analysed with Temperatus software. Significant differences were found across equations to measure the same parameters of skin temperature in warm and cold room conditions, hampering comparison across studies. Based on these findings, we suggest to use a set of 14 ibuttons at anatomical positions reported by ISO STANDARD 9886:2004 plus five ibuttons placed on the right supraclavicular fossa, right middle clavicular bone, right middle upper forearm, right top of forefinger, and right upper chest.

Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

NASA Astrophysics Data System (ADS)

Famiglietti, C.; Fisher, J.; Halverson, G. H.

2017-12-01

This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

Estimate of Shock-Hugoniot Adiabat of Liquids from Hydrodynamics

NASA Astrophysics Data System (ADS)

Bouton, E.; Vidal, P.

2007-12-01

Shock states are generally obtained from shock velocity (D) and material velocity (u) measurements. In this paper, we propose a hydrodynamical method for estimating the (D-u) relation of Nitromethane from easily measured properties of the initial state. The method is based upon the differentiation of the Rankine-Hugoniot jump relations with the initial temperature considered as a variable and under the constraint of a unique nondimensional shock-Hugoniot. We then obtain an ordinary differential equation for the shock velocity D in the variable u. Upon integration, this method predicts the shock Hugoniot of liquid Nitromethane with a 5% accuracy for initial temperatures ranging from 250 K to 360 K.

Greenhouse gases inventory and carbon balance of two dairy systems obtained from two methane-estimation methods.

PubMed

Cunha, C S; Lopes, N L; Veloso, C M; Jacovine, L A G; Tomich, T R; Pereira, L G R; Marcondes, M I

2016-11-15

The adoption of carbon inventories for dairy farms in tropical countries based on models developed from animals and diets of temperate climates is questionable. Thus, the objectives of this study were to estimate enteric methane (CH4) emissions through the SF6 tracer gas technique and through equations proposed by the Intergovernmental Panel on Climate Change (IPCC) Tier 2 and to calculate the inventory of greenhouse gas (GHG) emissions from two dairy systems. In addition, the carbon balance of these properties was estimated using enteric CH4 emissions obtained using both methodologies. In trial 1, the CH4 emissions were estimated from seven Holstein dairy cattle categories based on the SF6 tracer gas technique and on IPCC equations. The categories used in the study were prepubertal heifers (n=6); pubertal heifers (n=4); pregnant heifers (n=5); high-producing (n=6); medium-producing (n=5); low-producing (n=4) and dry cows (n=5). Enteric methane emission was higher for the category comprising prepubertal heifers when estimated by the equations proposed by the IPCC Tier 2. However, higher CH4 emissions were estimated by the SF6 technique in the categories including medium- and high-producing cows and dry cows. Pubertal heifers, pregnant heifers, and low-producing cows had equal CH4 emissions as estimated by both methods. In trial 2, two dairy farms were monitored for one year to identify all activities that contributed in any way to GHG emissions. The total emission from Farm 1 was 3.21t CO2e/animal/yr, of which 1.63t corresponded to enteric CH4. Farm 2 emitted 3.18t CO2e/animal/yr, with 1.70t of enteric CH4. IPCC estimations can underestimate CH4 emissions from some categories while overestimate others. However, considering the whole property, these discrepancies are offset and we would submit that the equations suggested by the IPCC properly estimate the total CH4 emission and carbon balance of the properties. Thus, the IPCC equations should be utilized with

Land Surface Temperature in Łódź Obtained from Landsat 5TM

NASA Astrophysics Data System (ADS)

Jędruszkiewicz, Joanna; Zieliński, Mariusz

2012-01-01

The main aim of this paper is to present the spatial differentiation of Land Surface Temperature LST in Łódź based on Landsat 5 Thematic Mapper (L5TM) images. Analysis was performed for all L5TM images from 2011, with clear sky over Łódź. Land surface temperature (LST) play an important role in determination of weather conditions in boundary layer of atmosphere, especially connected with convection. Environmental satellites from Landsat series delivers the high resolution images of Earth's surface and according to the estimations made on the ground of it are precise. LST depends widely on surface emissivity. In this paper the emissivity was estimated from MODIS sensor as well as NDVI index, then both method were compared. The processed images allowed to determine the warmest and the coldest areas in the administrative boundaries of Łódź. The highest LST values has been found in industrial areas and the in the heart of the city. However, there are some places lying in city outskirts, where the LST values are as high, for instance Lodz Airport. On the contrary the lowest LST values occur mostly in terrains covered with vegetation i.e. forests or city parks. Głównym celem tego opracowania było oszacowanie temperatury powierzchni Ziemi w Łodzi, na podstawie obrazów satelitarnych pochodzących z satelity Landsat 5 Thematic Mapper (L5TM). Analizę wykonane dla obrazów wszystkich dostępnych obrazów z 2011 roku, na których zachmurzenie nie wystąpiło nad obszarem Łodzi. Temperatura powierzchni Ziemi odgrywa istotną rolę w kształtowaniu warunków pogodowych w warstwie granicznej, szczególnie związanych z konwekcją. Satelity środowiskowe z serii Landsat dostarczają obrazów w dużej rozdzielczości, dzięki czemu pozwalają na stosunkowo dokładne oszacowanie tego parametru. Wielkość temperatury w dużym stopniu zależy od emisyjności danej powierzchni. W niniejszym opracowaniu porównano temperaturę powierzchniową obliczoną dla emisyjno

First practical applications of eye temperature measurements for estimation of the time of death in casework. Report of three cases.

PubMed

Kaliszan, Michał

2012-06-10

This paper presents first three successive cases of death where at scene measurements of the internal eyeball temperature soon after death allowed to precisely estimate the times of deaths based on this data (33.1°C, 32.2°C and 29.5°C, respectively), which were later confirmed during the police investigation. Simultaneously the rectal temperatures in all three cases were measured and appeared to be between 36.3 and 36.8°C-reflecting a living individual's body temperature. Thanks to a significantly faster postmortem decrease of the eye temperature and a residual or nonexistent plateau effect affecting the eye, using the formula developed in previous comprehensive studies in pigs, the time of death in real cases could be estimated with good precision: 1 h 33 min, 2 h 24 min and 3 h 17 min since death respectively. The actual TOD established during investigation appeared to be: between 1 h 30 min and 1 h 50 min in case 1; 1 h 55 min in case 2 and between 2 h 55 min and 3 h 05 min in case 3. Such precise estimation, mainly due to the plateau effect lasting up to a few hours, could not have been done based only on rectal temperature, commonly measured in forensic practice. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Equilibrium Climate Sensitivity Obtained From Multimillennial Runs of Two GFDL Climate Models

NASA Astrophysics Data System (ADS)

Paynter, D.; Frölicher, T. L.; Horowitz, L. W.; Silvers, L. G.

2018-02-01

Equilibrium climate sensitivity (ECS), defined as the long-term change in global mean surface air temperature in response to doubling atmospheric CO2, is usually computed from short atmospheric simulations over a mixed layer ocean, or inferred using a linear regression over a short-time period of adjustment. We report the actual ECS from multimillenial simulations of two Geophysical Fluid Dynamics Laboratory (GFDL) general circulation models (GCMs), ESM2M, and CM3 of 3.3 K and 4.8 K, respectively. Both values are 1 K higher than estimates for the same models reported in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change obtained by regressing the Earth's energy imbalance against temperature. This underestimate is mainly due to changes in the climate feedback parameter (-α) within the first century after atmospheric CO2 has stabilized. For both GCMs it is possible to estimate ECS with linear regression to within 0.3 K by increasing CO2 at 1% per year to doubling and using years 51-350 after CO2 is constant. We show that changes in -α differ between the two GCMs and are strongly tied to the changes in both vertical velocity at 500 hPa (ω500) and estimated inversion strength that the GCMs experience during the progression toward the equilibrium. This suggests that while cloud physics parametrizations are important for determining the strength of -α, the substantially different atmospheric state resulting from a changed sea surface temperature pattern may be of equal importance.

Non-invasive body temperature measurement of wild chimpanzees using fecal temperature decline.

PubMed

Jensen, Siv Aina; Mundry, Roger; Nunn, Charles L; Boesch, Christophe; Leendertz, Fabian H

2009-04-01

New methods are required to increase our understanding of pathologic processes in wild mammals. We developed a noninvasive field method to estimate the body temperature of wild living chimpanzees habituated to humans, based on statistically fitting temperature decline of feces after defecation. The method was established with the use of control measures of human rectal temperature and subsequent changes in fecal temperature over time. The method was then applied to temperature data collected from wild chimpanzee feces. In humans, we found good correspondence between the temperature estimated by the method and the actual rectal temperature that was measured (maximum deviation 0.22 C). The method was successfully applied and the average estimated temperature of the chimpanzees was 37.2 C. This simple-to-use field method reliably estimates the body temperature of wild chimpanzees and probably also other large mammals.

Analytical estimation of ultrasound properties, thermal diffusivity, and perfusion using magnetic resonance-guided focused ultrasound temperature data

PubMed Central

Dillon, C R; Borasi, G; Payne, A

2016-01-01

For thermal modeling to play a significant role in treatment planning, monitoring, and control of magnetic resonance-guided focused ultrasound (MRgFUS) thermal therapies, accurate knowledge of ultrasound and thermal properties is essential. This study develops a new analytical solution for the temperature change observed in MRgFUS which can be used with experimental MR temperature data to provide estimates of the ultrasound initial heating rate, Gaussian beam variance, tissue thermal diffusivity, and Pennes perfusion parameter. Simulations demonstrate that this technique provides accurate and robust property estimates that are independent of the beam size, thermal diffusivity, and perfusion levels in the presence of realistic MR noise. The technique is also demonstrated in vivo using MRgFUS heating data in rabbit back muscle. Errors in property estimates are kept less than 5% by applying a third order Taylor series approximation of the perfusion term and ensuring the ratio of the fitting time (the duration of experimental data utilized for optimization) to the perfusion time constant remains less than one. PMID:26741344

Estimation of groundwater flow from temperature monitoring in a borehole heat exchanger during a thermal response test

NASA Astrophysics Data System (ADS)

Yoshioka, Mayumi; Takakura, Shinichi; Uchida, Youhei

2018-05-01

To estimate the groundwater flow around a borehole heat exchanger (BHE), thermal properties of geological core samples were measured and a thermal response test (TRT) was performed in the Tsukuba upland, Japan. The thermal properties were measured at 57 points along a 50-m-long geological core, consisting predominantly of sand, silt, and clay, drilled near the BHE. In this TRT, the vertical temperature in the BHE was also monitored during and after the test. Results for the thermal properties of the core samples and from the monitoring indicated that groundwater flow enhanced thermal transfers, especially at shallow depths. The groundwater velocities around the BHE were estimated using a two-dimensional numerical model with monitoring data on temperature changes. According to the results, the estimated groundwater velocity was generally consistent with hydrogeological data from previous studies, except for the data collected at shallow depths consisting of a clay layer. The reasons for this discrepancy at shallow depths were predicted to be preferential flow and the occurrence of vertical flow through the BHE grout, induced by the hydrogeological conditions.

Pressure - temperature estimates of a phengite eclogite from the Grapesvåre Nappe, Norrbotten, Swedish Caledonides

NASA Astrophysics Data System (ADS)

Bukała, Michał; Majka, Jarosław; Walczak, Katarzyna; Barnes, Christopher; Klonowska, Iwona

2017-04-01

The Seve Nappe Complex (SNC) of the Scandinavian Caledonides has well documented history of high pressure (HP) and ultra-high pressure (UHP) metamorphism (e.g. Klonowska et al. 2014). Eclogites of the SNC occur in two areas in Sweden, namely Jämtland and Norrbotten. The Jämtland eclogites and associated rocks are well studied and provide evidence for the Late Ordovician UHP metamorphism, whereas the Norrbotten eclogites, formed during the Late Cambrian/Early Ordovician, have not been studied in detail, especially in terms of pressure-temperature (P-T) conditions of their formation. Within the SNC in Norrbotten, eclogites are limited to two tectonic lenses - Vaimok and Tsäkkok (e.g. Albrecht, 2000). Within the Vaimok Lens three nappes have been distinguished: (1) the eclogite-free Lower Seve Nappe, (2) the Grapesvåre Nappe and (3) the Maddåive Nappe. The two latter nappes are eclogite-bearing. For this study eclogites were collected from the lowermost part of the Grapesvåre Nappe (from the highly heterogeneous Daunasvagge unit dominated by garnet-bearing mica schists, quartzites and marbles). Eclogite boudins (former dolerite dikes and sills) are usually highly altered due to retrogressive recrystallization. Rare fresh eclogites occur within large boudins (>5m in diameter) and display only minor alteration limited to the scarce veinlets composed of amphibole + feldspar + garnet + zoisite + biotite + rutile + titanite. Metamorphic peak conditions mineral assemblage consists of garnet + omphacite + phengite + quartz + rutile. For P-T estimates the geothermobarometric method of Ravna & Terry (2004) has been used. The garnet-clinopyroxene Fe2+-Mg exchange thermometer and the net-transfer reaction barometer based on the garnet-phengite-omphacite equilibrium yielded a maximum pressure of 26.7 kbar and temperature of 677°C. The obtained temperature might be underestimated due to uncertainties in Fe2+/Fe3+ ratio in pyroxene. Therefore Zr-in-rutile geothermometer by

Temperature and pressure effects on capacitance probe cryogenic liquid level measurement accuracy

NASA Technical Reports Server (NTRS)

Edwards, Lawrence G.; Haberbusch, Mark

1993-01-01

The inaccuracies of liquid nitrogen and liquid hydrogen level measurements by use of a coaxial capacitance probe were investigated as a function of fluid temperatures and pressures. Significant liquid level measurement errors were found to occur due to the changes in the fluids dielectric constants which develop over the operating temperature and pressure ranges of the cryogenic storage tanks. The level measurement inaccuracies can be reduced by using fluid dielectric correction factors based on measured fluid temperatures and pressures. The errors in the corrected liquid level measurements were estimated based on the reported calibration errors of the temperature and pressure measurement systems. Experimental liquid nitrogen (LN2) and liquid hydrogen (LH2) level measurements were obtained using the calibrated capacitance probe equations and also by the dielectric constant correction factor method. The liquid levels obtained by the capacitance probe for the two methods were compared with the liquid level estimated from the fluid temperature profiles. Results show that the dielectric constant corrected liquid levels agreed within 0.5 percent of the temperature profile estimated liquid level. The uncorrected dielectric constant capacitance liquid level measurements deviated from the temperature profile level by more than 5 percent. This paper identifies the magnitude of liquid level measurement error that can occur for LN2 and LH2 fluids due to temperature and pressure effects on the dielectric constants over the tank storage conditions from 5 to 40 psia. A method of reducing the level measurement errors by using dielectric constant correction factors based on fluid temperature and pressure measurements is derived. The improved accuracy by use of the correction factors is experimentally verified by comparing liquid levels derived from fluid temperature profiles.

Effect of input data variability on estimations of the equivalent constant temperature time for microbial inactivation by HTST and retort thermal processing.

PubMed

Salgado, Diana; Torres, J Antonio; Welti-Chanes, Jorge; Velazquez, Gonzalo

2011-08-01

Consumer demand for food safety and quality improvements, combined with new regulations, requires determining the processor's confidence level that processes lowering safety risks while retaining quality will meet consumer expectations and regulatory requirements. Monte Carlo calculation procedures incorporate input data variability to obtain the statistical distribution of the output of prediction models. This advantage was used to analyze the survival risk of Mycobacterium avium subspecies paratuberculosis (M. paratuberculosis) and Clostridium botulinum spores in high-temperature short-time (HTST) milk and canned mushrooms, respectively. The results showed an estimated 68.4% probability that the 15 sec HTST process would not achieve at least 5 decimal reductions in M. paratuberculosis counts. Although estimates of the raw milk load of this pathogen are not available to estimate the probability of finding it in pasteurized milk, the wide range of the estimated decimal reductions, reflecting the variability of the experimental data available, should be a concern to dairy processors. Knowledge of the C. botulinum initial load and decimal thermal time variability was used to estimate an 8.5 min thermal process time at 110 °C for canned mushrooms reducing the risk to 10⁻⁹ spores/container with a 95% confidence. This value was substantially higher than the one estimated using average values (6.0 min) with an unacceptable 68.6% probability of missing the desired processing objective. Finally, the benefit of reducing the variability in initial load and decimal thermal time was confirmed, achieving a 26.3% reduction in processing time when standard deviation values were lowered by 90%. In spite of novel technologies, commercialized or under development, thermal processing continues to be the most reliable and cost-effective alternative to deliver safe foods. However, the severity of the process should be assessed to avoid under- and over

Obtaining Potential Virtual Temperature Profiles, Entrainment Fluxes, and Spectra from Mini Unmanned Aerial Vehicle Data

NASA Astrophysics Data System (ADS)

Dias, N. L.; Gonçalves, J. E.; Freire, L. S.; Hasegawa, T.; Malheiros, A. L.

2012-10-01

We present a simple but effective small unmanned aerial vehicle design that is able to make high-resolution temperature and humidity measurements of the atmospheric boundary layer. The air model used is an adapted commercial design, and is able to carry all the instrumentation (barometer, temperature and humidity sensor, and datalogger) required for such measurements. It is fitted with an autopilot that controls the plane's ascent and descent in a spiral to 1800 m above ground. We describe the results obtained on three different days when the plane, called Aerolemma-3, flew continuously throughout the day. Surface measurements of the sensible virtual heat flux made simultaneously allowed the calculation of all standard convective turbulence scales for the boundary layer, as well as a rigorous test of existing models for the entrainment flux at the top of the boundary layer, and for its growth. A novel approach to calculate the entrainment flux from the top-down, bottom-up model of Wynagaard and Brost is used. We also calculated temperature fluctuations by means of a spectral high-pass filter, and calculated their spectra. Although the time series are small, tapering proved ineffective in this case. The spectra from the untapered series displayed a consistent -5/3 behaviour, and from them it was possible to calculate a dimensionless dissipation function, which exhibited the expected similarity behaviour against boundary-layer bulk stability. The simplicity, ease of use and economy of such small aircraft make us optimistic about their usefulness in boundary-layer research.

Analysis of Ion Composition Estimation Accuracy for Incoherent Scatter Radars

NASA Astrophysics Data System (ADS)

Martínez Ledesma, M.; Diaz, M. A.

2017-12-01

The Incoherent Scatter Radar (ISR) is one of the most powerful sounding methods developed to estimate the Ionosphere. This radar system determines the plasma parameters by sending powerful electromagnetic pulses to the Ionosphere and analyzing the received backscatter. This analysis provides information about parameters such as electron and ion temperatures, electron densities, ion composition, and ion drift velocities. Nevertheless in some cases the ISR analysis has ambiguities in the determination of the plasma characteristics. It is of particular relevance the ion composition and temperature ambiguity obtained between the F1 and the lower F2 layers. In this case very similar signals are obtained with different mixtures of molecular ions (NO2+ and O2+) and atomic oxygen ions (O+), and consequently it is not possible to completely discriminate between them. The most common solution to solve this problem is the use of empirical or theoretical models of the ionosphere in the fitting of ambiguous data. More recent works take use of parameters estimated from the Plasma Line band of the radar to reduce the number of parameters to determine. In this work we propose to determine the error estimation of the ion composition ambiguity when using Plasma Line electron density measurements. The sensibility of the ion composition estimation has been also calculated depending on the accuracy of the ionospheric model, showing that the correct estimation is highly dependent on the capacity of the model to approximate the real values. Monte Carlo simulations of data fitting at different signal to noise (SNR) ratios have been done to obtain valid and invalid estimation probability curves. This analysis provides a method to determine the probability of erroneous estimation for different signal fluctuations. Also it can be used as an empirical method to compare the efficiency of the different algorithms and methods on when solving the ion composition ambiguity.

Solutions for the diurnally forced advection-diffusion equation to estimate bulk fluid velocity and diffusivity in streambeds from temperature time series

NASA Astrophysics Data System (ADS)

Luce, C.; Tonina, D.; Gariglio, F. P.; Applebee, R.

2012-12-01

Differences in the diurnal variations of temperature at different depths in streambed sediments are commonly used for estimating vertical fluxes of water in the streambed. We applied spatial and temporal rescaling of the advection-diffusion equation to derive two new relationships that greatly extend the kinds of information that can be derived from streambed temperature measurements. The first equation provides a direct estimate of the Peclet number from the amplitude decay and phase delay information. The analytical equation is explicit (e.g. no numerical root-finding is necessary), and invertable. The thermal front velocity can be estimated from the Peclet number when the thermal diffusivity is known. The second equation allows for an independent estimate of the thermal diffusivity directly from the amplitude decay and phase delay information. Several improvements are available with the new information. The first equation uses a ratio of the amplitude decay and phase delay information; thus Peclet number calculations are independent of depth. The explicit form also makes it somewhat faster and easier to calculate estimates from a large number of sensors or multiple positions along one sensor. Where current practice requires a priori estimation of streambed thermal diffusivity, the new approach allows an independent calculation, improving precision of estimates. Furthermore, when many measurements are made over space and time, expectations of the spatial correlation and temporal invariance of thermal diffusivity are valuable for validation of measurements. Finally, the closed-form explicit solution allows for direct calculation of propagation of uncertainties in error measurements and parameter estimates, providing insight about error expectations for sensors placed at different depths in different environments as a function of surface temperature variation amplitudes. The improvements are expected to increase the utility of temperature measurement methods for

Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

NASA Technical Reports Server (NTRS)

SUsskind, Joel

2008-01-01

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 pm C02 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 pm C02 observations are now used primarily in the generation of cloud cleared radiances Ri. This approach allows for the generation of accurate values of Ri and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by- channel error estimates for Ri. These error estimates are used for quality control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of quality control using the NASA GEOS-5 data assimilation system. Assimilation of quality controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done Operationally by ECMWF and NCEP. Forecasts resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

Using Diurnal Temperature Signals to Infer Vertical Groundwater-Surface Water Exchange.

PubMed

Irvine, Dylan J; Briggs, Martin A; Lautz, Laura K; Gordon, Ryan P; McKenzie, Jeffrey M; Cartwright, Ian

2017-01-01

Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer. © 2016, National Ground Water Association.

Using diurnal temperature signals to infer vertical groundwater-surface water exchange

USGS Publications Warehouse

Irvine, Dylan J.; Briggs, Martin A.; Lautz, Laura K.; Gordon, Ryan P.; McKenzie, Jeffrey M.; Cartwright, Ian

2017-01-01

Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer.

A statistical model for estimating stream temperatures in the Salmon and Clearwater River basins, central Idaho

USGS Publications Warehouse

Donato, Mary M.

2002-01-01

A water-quality standard for temperature is critical for the protection of threatened and endangered salmonids, which need cold, clean water to sustain life. The Idaho Department of Environmental Quality has established temperature standards to protect salmonids, yet little is known about the normal range of temperatures of most Idaho streams. A single temperature standard for all streams does not take into account the natural temperature variation of streams or the existence of naturally warm waters. To address these issues and to help the Idaho Department of Environmental Quality revise the existing State temperature standards for aquatic life, temperature data from more than 200 streams and rivers in the salmon and Clearwater River Basins were collected. From these data, a statistical model was developed for estimating stream temperatures on the basis of subbasin and site characteristics and climatic factors. Stream temperatures were monitored hourly for approximately 58 days during July, August, and September 2000 at relatively undisturbed sites in subbasins in the Salmon and Clearwater River Basins in central Idaho. The monitored subbasins vary widely in size, elevation, drainage area, vegetation cover, and other characteristics. The resulting data were analyzed for statistical correlations with subbasin and site characteristics to establish the most important factors affecting stream temperature. Maximum daily average stream temperatures were strongly correlated with elevation and total upstream drainage area; weaker correlations were noted with stream depth and width and aver-age subbasin slope. Stream temperatures also were correlated with certain types of vegetation cover, but these variables were not significant in the final model. The model takes into account seasonal temperature fluctuations, site elevation, total drainage area, average subbasin slope, and the deviation of daily average air temperature from a 30-year normal daily average air temperature

Estimation of subsurface formation temperature in the Tarim Basin, northwest China: implications for hydrocarbon generation and preservation

NASA Astrophysics Data System (ADS)

Liu, Shaowen; Lei, Xiao; Feng, Changge; Hao, Chunyan

2016-07-01

Subsurface formation temperature in the Tarim Basin, northwest China, is vital for assessment of hydrocarbon generation and preservation, and of geothermal energy potential. However, it has not previously been well understood, due to poor data coverage and a lack of highly accurate temperature data. Here, we combined recently acquired steady-state temperature logging data with drill stem test temperature data and measured rock thermal properties, to investigate the geothermal regime and estimate the subsurface formation temperature at depth in the range of 1000-5000 m, together with temperatures at the lower boundary of each of four major Lower Paleozoic marine source rocks buried in this basin. Results show that heat flow of the Tarim Basin ranges between 26.2 and 66.1 mW/m2, with a mean of 42.5 ± 7.6 mW/m2; the geothermal gradient at depth of 3000 m varies from 14.9 to 30.2 °C/km, with a mean of 20.7 ± 2.9 °C/km. Formation temperature estimated at the depth of 1000 m is between 29 and 41 °C, with a mean of 35 °C, while 63-100 °C is for the temperature at the depth of 3000 m with a mean of 82 °C. Temperature at 5000 m ranges from 97 to 160 °C, with a mean of 129 °C. Generally spatial patterns of the subsurface formation temperature at depth are basically similar, characterized by higher temperatures in the uplift areas and lower temperatures in the sags, which indicates the influence of basement structure and lateral variations in thermal properties on the geotemperature field. Using temperature to identify the oil window in the source rocks, most of the uplifted areas in the basin are under favorable condition for oil generation and/or preservation, whereas the sags with thick sediments are favorable for gas generation and/or preservation. We conclude that relatively low present-day geothermal regime and large burial depth of the source rocks in the Tarim Basin are favorable for hydrocarbon generation and preservation. In addition, it is found that the

Toward a "molecular thermometer" to estimate the charring temperature of wildland charcoals derived from different biomass sources

Treesearch

Maximilian P. W. Schneider; Lacey A. Pyle; Kenneth L. Clark; William C. Hockaday; Caroline A. Masiello; Michael W.I. Schmidt

2013-01-01

The maximum temperature experienced by biomass during combustion has a strong effect on chemical properties of the resulting charcoal, such as sorption capacity (water and nonpolar materials) and microbial degradability. However, information about the formation temperature of natural charcoal can be difficult to obtain in ecosystems that are not instrumented prior to...

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal

Using the product threshold model for estimating separately the effect of temperature on male and female fertility.

PubMed

Tusell, L; David, I; Bodin, L; Legarra, A; Rafel, O; López-Bejar, M; Piles, M

2011-12-01

Animals under environmental thermal stress conditions have reduced fertility due to impairment of some mechanisms involved in their reproductive performance that are different in males and females. As a consequence, the most sensitive periods of time and the magnitude of effect of temperature on fertility can differ between sexes. The objective of this study was to estimate separately the effect of temperature in different periods around the insemination time on male and on female fertility by using the product threshold model. This model assumes that an observed reproduction outcome is the result of the product of 2 unobserved variables corresponding to the unobserved fertilities of the 2 individuals involved in the mating. A total of 7,625 AI records from rabbits belonging to a line selected for growth rate and indoor daily temperature records were used. The average maximum daily temperature and the proportion of days in which the maximum temperature was greater than 25°C were used as temperature descriptors. These descriptors were calculated for several periods around the day of AI. In the case of males, 4 periods of time covered different stages of the spermatogenesis, the transit through the epididymus of the sperm, and the day of AI. For females, 5 periods of time covered the phases of preovulatory follicular maturation including day of AI and ovulation, fertilization and peri-implantational stage of the embryos, embryonic and early fetal periods of gestation, and finally, late gestation until birth. The effect of the different temperature descriptors was estimated in the corresponding male and female liabilities in a set of threshold product models. The temperature of the day of AI seems to be the most relevant temperature descriptor affecting male fertility because greater temperature records on the day of AI caused a decrease in male fertility (-6% in male fertility rate with respect to thermoneutrality). Departures from the thermal zone in temperature

Comparison of Species Richness Estimates Obtained Using Nearly Complete Fragments and Simulated Pyrosequencing-Generated Fragments in 16S rRNA Gene-Based Environmental Surveys▿ †

PubMed Central

Youssef, Noha; Sheik, Cody S.; Krumholz, Lee R.; Najar, Fares Z.; Roe, Bruce A.; Elshahed, Mostafa S.

2009-01-01

Pyrosequencing-based 16S rRNA gene surveys are increasingly utilized to study highly diverse bacterial communities, with special emphasis on utilizing the large number of sequences obtained (tens to hundreds of thousands) for species richness estimation. However, it is not yet clear how the number of operational taxonomic units (OTUs) and, hence, species richness estimates determined using shorter fragments at different taxonomic cutoffs correlates with the number of OTUs assigned using longer, nearly complete 16S rRNA gene fragments. We constructed a 16S rRNA clone library from an undisturbed tallgrass prairie soil (1,132 clones) and used it to compare species richness estimates obtained using eight pyrosequencing candidate fragments (99 to 361 bp in length) and the nearly full-length fragment. Fragments encompassing the V1 and V2 (V1+V2) region and the V6 region (generated using primer pairs 8F-338R and 967F-1046R) overestimated species richness; fragments encompassing the V3, V7, and V7+V8 hypervariable regions (generated using primer pairs 338F-530R, 1046F-1220R, and 1046F-1392R) underestimated species richness; and fragments encompassing the V4, V5+V6, and V6+V7 regions (generated using primer pairs 530F-805R, 805F-1046R, and 967F-1220R) provided estimates comparable to those obtained with the nearly full-length fragment. These patterns were observed regardless of the alignment method utilized or the parameter used to gauge comparative levels of species richness (number of OTUs observed, slope of scatter plots of pairwise distance values for short and nearly complete fragments, and nonparametric and parametric species richness estimates). Similar results were obtained when analyzing three other datasets derived from soil, adult Zebrafish gut, and basaltic formations in the East Pacific Rise. Regression analysis indicated that these observed discrepancies in species richness estimates within various regions could readily be explained by the proportions of

COSMIC MICROWAVE BACKGROUND POLARIZATION AND TEMPERATURE POWER SPECTRA ESTIMATION USING LINEAR COMBINATION OF WMAP 5 YEAR MAPS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samal, Pramoda Kumar; Jain, Pankaj; Saha, Rajib

We estimate cosmic microwave background (CMB) polarization and temperature power spectra using Wilkinson Microwave Anisotropy Probe (WMAP) 5 year foreground contaminated maps. The power spectrum is estimated by using a model-independent method, which does not utilize directly the diffuse foreground templates nor the detector noise model. The method essentially consists of two steps: (1) removal of diffuse foregrounds contamination by making linear combination of individual maps in harmonic space and (2) cross-correlation of foreground cleaned maps to minimize detector noise bias. For the temperature power spectrum we also estimate and subtract residual unresolved point source contamination in the cross-power spectrummore » using the point source model provided by the WMAP science team. Our TT, TE, and EE power spectra are in good agreement with the published results of the WMAP science team. We perform detailed numerical simulations to test for bias in our procedure. We find that the bias is small in almost all cases. A negative bias at low l in TT power spectrum has been pointed out in an earlier publication. We find that the bias-corrected quadrupole power (l(l + 1)C{sub l} /2{pi}) is 532 {mu}K{sup 2}, approximately 2.5 times the estimate (213.4 {mu}K{sup 2}) made by the WMAP team.« less

Surface tension estimation of high temperature melts of the binary alloys Ag-Au

NASA Astrophysics Data System (ADS)

Dogan, Ali; Arslan, Hüseyin

2017-11-01

Surface tension calculation of the binary alloys Ag-Au at the temperature of 1381 K, where Ag and Au have similar electronic structures and their atomic radii are comparable, are carried out in this study using several equations over entire composition range of Au. Apparently, the deviations from ideality of the bulk solutions, such as activities of Ag and Au are small and the maximum excess Gibbs free energy of mixing of the liquid phase is for instance -4500 J/mol at XAu = 0.5. Besides, the results obtained in Ag-Au alloys that at a constant temperature the surface tension increases with increasing composition while the surface tension decreases as the temperature increases for entire composition range of Au. Although data about surface tension of the Ag-Au alloy are limited, it was possible to make a comparison for the calculated results for the surface tension in this study with the available experimental data. Taken together, the average standard error analysis that especially the improved Guggenheim model in the other models gives the best agreement along with the experimental results at temperature 1383 K although almost all models are mutually in agreement with the other one.

Estimation of soil thermal properties using in-situ temperature measurements in the active layer and permafrost.

Treesearch

D.J. Nicolsky; V.E. Romanovsky; G.G. Panteleev

2008-01-01

A variational data assimilation algorithm is developed to reconstruct thermal properties, porosity, and parametrization of the unfrozen water content for fully saturated soils. The algorithm is tested with simulated synthetic temperatures. The simulations are performed to determine the robustness and sensitivity of algorithm to estimate soil properties from in-situ...

Using Landsat data to estimate evapotranspiration of winter wheat

NASA Technical Reports Server (NTRS)

Kanemasu, E. T.; Heilman, J. L.; Bagley, J. O.; Powers, W. L.

1977-01-01

Results obtained from an evapotranspiration model as applied to Kansas winter wheatfields were compared with results determined by a weighing lysimeter, and the standard deviation was found to be less than 0.5 mm/day (however, the 95% confidence interval was between plus and minus 0.2 mm/day). Model inputs are solar radiation, temperature, precipitation, and leaf area index; an equation was developed to estimate the leaf area index from Landsat data. The model provides estimates of transpiration, evaporation, and soil moisture.

Estimation of brittleness indices for pay zone determination in a shale-gas reservoir by using elastic properties obtained from micromechanics

NASA Astrophysics Data System (ADS)

Lizcano-Hernández, Edgar G.; Nicolás-López, Rubén; Valdiviezo-Mijangos, Oscar C.; Meléndez-Martínez, Jaime

2018-04-01

The brittleness indices (BI) of gas-shales are computed by using their effective mechanical properties obtained from micromechanical self-consistent modeling with the purpose of assisting in the identification of the more-brittle regions in shale-gas reservoirs, i.e., the so-called ‘pay zone’. The obtained BI are plotted in lambda-rho versus mu-rho λ ρ -μ ρ and Young’s modulus versus Poisson’s ratio E-ν ternary diagrams along with the estimated elastic properties from log data of three productive shale-gas wells where the pay zone is already known. A quantitative comparison between the obtained BI and the well log data allows for the delimitation of regions where BI values could indicate the best reservoir target in regions with the highest shale-gas exploitation potential. Therefore, a range of values for elastic properties and brittleness indexes that can be used as a data source to support the well placement procedure is obtained.

Temperature-dependent development of Aleyrodes proletella (Homoptera: Aleyrodidae) on two cultivars of broccoli under constant temperatures.

PubMed

Alonso, Daniel; Gómez, Ana Azahara; Nombela, Gloria; Muñiz, Mariano

2009-02-01

Laboratory experiments were conducted to estimate developmental rates and nymphal survival of Aleyrodes proletella Linnaeus (Homoptera: Aleyrodidae) on two broccoli Brassica oleracea L. variety italica Plenck cultivars (Marathon and Agripa) at eight constant temperatures (16, 18, 20, 22, 24, 26, 28, and 30 degrees C). The times required to complete development of egg and first instar decreased with increasing temperature, but the developmental times of second, third, fourth instars, all instars, and egg-adult period were greater at 30 degrees C than at 28degrees C. The relationships between developmental rate of A. proletella and temperature were slightly influenced by broccoli cultivar. The optimal temperatures and thermal constant as well as the lower and upper thresholds of development for all immature stages were estimated by fitting the observed developmental rates versus temperature with a nonlinear model and two linear models. For all stages, graphs obtained by plotting the developmental rates against temperature could be described by the modification two of the Logan's model. Overall, developmental times for immature stages and egg-adult periods were similar on both Agripa and Marathon cultivars. The most favorable temperature range for nymphal development seemed to be 28-29 (second and third instars) and 31-33 degrees C (fourth instar). Mean generation times (egg-adult) ranged from 19 d ('Marathon' and 'Agripa') at 28 degrees C to 47 ('Marathon') and 46 d ('Agripa') at 16 degrees C.

Integrating Temperature-Dependent Life Table Data into a Matrix Projection Model for Drosophila suzukii Population Estimation

PubMed Central

Wiman, Nik G.; Walton, Vaughn M.; Dalton, Daniel T.; Anfora, Gianfranco; Burrack, Hannah J.; Chiu, Joanna C.; Daane, Kent M.; Grassi, Alberto; Miller, Betsey; Tochen, Samantha; Wang, Xingeng; Ioriatti, Claudio

2014-01-01

Temperature-dependent fecundity and survival data was integrated into a matrix population model to describe relative Drosophila suzukii Matsumura (Diptera: Drosophilidae) population increase and age structure based on environmental conditions. This novel modification of the classic Leslie matrix population model is presented as a way to examine how insect populations interact with the environment, and has application as a predictor of population density. For D. suzukii, we examined model implications for pest pressure on crops. As case studies, we examined model predictions in three small fruit production regions in the United States (US) and one in Italy. These production regions have distinctly different climates. In general, patterns of adult D. suzukii trap activity broadly mimicked seasonal population levels predicted by the model using only temperature data. Age structure of estimated populations suggest that trap and fruit infestation data are of limited value and are insufficient for model validation. Thus, we suggest alternative experiments for validation. The model is advantageous in that it provides stage-specific population estimation, which can potentially guide management strategies and provide unique opportunities to simulate stage-specific management effects such as insecticide applications or the effect of biological control on a specific life-stage. The two factors that drive initiation of the model are suitable temperatures (biofix) and availability of a suitable host medium (fruit). Although there are many factors affecting population dynamics of D. suzukii in the field, temperature-dependent survival and reproduction are believed to be the main drivers for D. suzukii populations. PMID:25192013

Multiphysics and Thermal Response Models to Improve Accuracy of Local Temperature Estimation in Rat Cortex under Microwave Exposure

PubMed Central

Kodera, Sachiko; Gomez-Tames, Jose; Hirata, Akimasa; Masuda, Hiroshi; Arima, Takuji; Watanabe, Soichi

2017-01-01

The rapid development of wireless technology has led to widespread concerns regarding adverse human health effects caused by exposure to electromagnetic fields. Temperature elevation in biological bodies is an important factor that can adversely affect health. A thermophysiological model is desired to quantify microwave (MW) induced temperature elevations. In this study, parameters related to thermophysiological responses for MW exposures were estimated using an electromagnetic-thermodynamics simulation technique. To the authors’ knowledge, this is the first study in which parameters related to regional cerebral blood flow in a rat model were extracted at a high degree of accuracy through experimental measurements for localized MW exposure at frequencies exceeding 6 GHz. The findings indicate that the improved modeling parameters yield computed results that match well with the measured quantities during and after exposure in rats. It is expected that the computational model will be helpful in estimating the temperature elevation in the rat brain at multiple observation points (that are difficult to measure simultaneously) and in explaining the physiological changes in the local cortex region. PMID:28358345

Estimation of soil hydraulic properties with microwave techniques

NASA Technical Reports Server (NTRS)

Oneill, P. E.; Gurney, R. J.; Camillo, P. J.

1985-01-01

Useful quantitative information about soil properties may be obtained by calibrating energy and moisture balance models with remotely sensed data. A soil physics model solves heat and moisture flux equations in the soil profile and is driven by the surface energy balance. Model generated surface temperature and soil moisture and temperature profiles are then used in a microwave emission model to predict the soil brightness temperature. The model hydraulic parameters are varied until the predicted temperatures agree with the remotely sensed values. This method is used to estimate values for saturated hydraulic conductivity, saturated matrix potential, and a soil texture parameter. The conductivity agreed well with a value measured with an infiltration ring and the other parameters agreed with values in the literature.

Glass Transition Temperature of Saccharide Aqueous Solutions Estimated with the Free Volume/Percolation Model.

PubMed

Constantin, Julian Gelman; Schneider, Matthias; Corti, Horacio R

2016-06-09

The glass transition temperature of trehalose, sucrose, glucose, and fructose aqueous solutions has been predicted as a function of the water content by using the free volume/percolation model (FVPM). This model only requires the molar volume of water in the liquid and supercooled regimes, the molar volumes of the hypothetical pure liquid sugars at temperatures below their pure glass transition temperatures, and the molar volumes of the mixtures at the glass transition temperature. The model is simplified by assuming that the excess thermal expansion coefficient is negligible for saccharide-water mixtures, and this ideal FVPM becomes identical to the Gordon-Taylor model. It was found that the behavior of the water molar volume in trehalose-water mixtures at low temperatures can be obtained by assuming that the FVPM holds for this mixture. The temperature dependence of the water molar volume in the supercooled region of interest seems to be compatible with the recent hypothesis on the existence of two structure of liquid water, being the high density liquid water the state of water in the sugar solutions. The idealized FVPM describes the measured glass transition temperature of sucrose, glucose, and fructose aqueous solutions, with much better accuracy than both the Gordon-Taylor model based on an empirical kGT constant dependent on the saccharide glass transition temperature and the Couchman-Karasz model using experimental heat capacity changes of the components at the glass transition temperature. Thus, FVPM seems to be an excellent tool to predict the glass transition temperature of other aqueous saccharides and polyols solutions by resorting to volumetric information easily available.

Bias Correction of MODIS AOD using DragonNET to obtain improved estimation of PM2.5

NASA Astrophysics Data System (ADS)

Gross, B.; Malakar, N. K.; Atia, A.; Moshary, F.; Ahmed, S. A.; Oo, M. M.

2014-12-01

MODIS AOD retreivals using the Dark Target algorithm is strongly affected by the underlying surface reflection properties. In particular, the operational algorithms make use of surface parameterizations trained on global datasets and therefore do not account properly for urban surface differences. This parameterization continues to show an underestimation of the surface reflection which results in a general over-biasing in AOD retrievals. Recent results using the Dragon-Network datasets as well as high resolution retrievals in the NYC area illustrate that this is even more significant at the newest C006 3 km retrievals. In the past, we used AERONET observation in the City College to obtain bias-corrected AOD, but the homogeneity assumptions using only one site for the region is clearly an issue. On the other hand, DragonNET observations provide ample opportunities to obtain better tuning the surface corrections while also providing better statistical validation. In this study we present a neural network method to obtain bias correction of the MODIS AOD using multiple factors including surface reflectivity at 2130nm, sun-view geometrical factors and land-class information. These corrected AOD's are then used together with additional WRF meteorological factors to improve estimates of PM2.5. Efforts to explore the portability to other urban areas will be discussed. In addition, annual surface ratio maps will be developed illustrating that among the land classes, the urban pixels constitute the largest deviations from the operational model.

A methodology for using borehole temperature-depth profiles under ambient, single and cross-borehole pumping conditions to estimate fracture hydraulic properties

NASA Astrophysics Data System (ADS)

Klepikova, Maria V.; Le Borgne, Tanguy; Bour, Olivier; Davy, Philippe

2011-09-01

SummaryTemperature profiles in the subsurface are known to be sensitive to groundwater flow. Here we show that they are also strongly related to vertical flow in the boreholes themselves. Based on a numerical model of flow and heat transfer at the borehole scale, we propose a method to invert temperature measurements to derive borehole flow velocities. This method is applied to an experimental site in fractured crystalline rocks. Vertical flow velocities deduced from the inversion of temperature measurements are compared with direct heat-pulse flowmeter measurements showing a good agreement over two orders of magnitudes. Applying this methodology under ambient, single and cross-borehole pumping conditions allows us to estimate fracture hydraulic head and local transmissivity, as well as inter-borehole fracture connectivity. Thus, these results provide new insights on how to include temperature profiles in inverse problems for estimating hydraulic fracture properties.

Contribution of Modis Satellite Image to Estimate the Daily Air Temperature in the Casablanca City, Morocco

NASA Astrophysics Data System (ADS)

Bahi, Hicham; Rhinane, Hassan; Bensalmia, Ahmed

2016-10-01

Air temperature is considered to be an essential variable for the study and analysis of meteorological regimes and chronics. However, the implementation of a daily monitoring of this variable is very difficult to achieve. It requires sufficient of measurements stations density, meteorological parks and favourable logistics. The present work aims to establish relationship between day and night land surface temperatures from MODIS data and the daily measurements of air temperature acquired between [2011-20112] and provided by the Department of National Meteorology [DMN] of Casablanca, Morocco. The results of the statistical analysis show significant interdependence during night observations with correlation coefficient of R2=0.921 and Root Mean Square Error RMSE=1.503 for Tmin while the physical magnitude estimated from daytime MODIS observation shows a relatively coarse error with R2=0.775 and RMSE=2.037 for Tmax. A method based on Gaussian process regression was applied to compute the spatial distribution of air temperature from MODIS throughout the city of Casablanca.

Combined two-dimensional velocity and temperature measurements of natural convection using a high-speed camera and temperature-sensitive particles

NASA Astrophysics Data System (ADS)

Someya, Satoshi; Li, Yanrong; Ishii, Keiko; Okamoto, Koji

2011-01-01

This paper proposes a combined method for two-dimensional temperature and velocity measurements in liquid and gas flows using temperature-sensitive particles (TSPs), a pulsed ultraviolet laser, and a high-speed camera. TSPs respond to temperature changes in the flow and can also serve as tracers for the velocity field. The luminescence from the TSPs was recorded at 15,000 frames per second as sequential images for a lifetime-based temperature analysis. These images were also used for the particle image velocimetry calculations. The temperature field was estimated using several images, based on the lifetime method. The decay curves for various temperature conditions fit well to exponential functions, and from these the decay constants at each temperature were obtained. The proposed technique was applied to measure the temperature and velocity fields in natural convection driven by a Marangoni force and buoyancy in a rectangular tank. The accuracy of the temperature measurement of the proposed technique was ±0.35-0.40°C.

A methodology for using borehole temperature-depth profiles under ambient, single and cross-borehole pumping conditions to estimate fracture hydraulic properties

NASA Astrophysics Data System (ADS)

Klepikova, M.; Le Borgne, T.; Bour, O.; Lavenant, N.

2011-12-01

In fractured aquifers flow generally takes place in a few fractured zones. The identification of these main flow paths is critical as it controls the transfer of fluids in the subsurface. For realistic modeling of the flow the knowledge about the spatial variability of hydraulic properties is required. Inverse problems based on hydraulic head data are generally strongly underconstrained. A possible way of reducing the uncertainty is to combine different type of data, such as flow measurements, temperature profiles or tracer test data. Here, we focus on the use of temperature, which can be seen as a natural tracer of ground water flow. Previous studies used temperature anomalies to quantify vertical or horizontal regional groundwater flow velocities. Most of these studies assume that water in the borehole is stagnant, and, thus, the temperature profile in the well is representative of the temperature in the aquifer. In fractured media, differences in hydraulic head between flow paths connected to a borehole generally create ambient vertical flow within the borehole. These differences in hydraulic head are in general due to regional flow conditions. Estimation of borehole vertical flow is of interest as it can be used to derive large scale hydraulic connections. Under a single-borehole configuration, the estimation of vertical flow can be used to estimate the local transimissivities and the hydraulic head differences driving the flow through the borehole. Under a cross-borehole set up, it can be used to characterize hydraulic connections and estimate their hydraulic properties. Using a flow and heat transfer numerical model, we find that the slope of the temperature profile is related directly to vertical borehole flow velocity. Thus, we propose a method to invert temperature measurements to derive borehole flow velocities and subsequently the fracture zone hydraulic and connectivity properties. The advantage of temperature measurements compared to flowmeter

Using Annual Data to Estimate the Public Health Impact of Extreme Temperatures.

PubMed

Goggins, William B; Yang, Chunyuh; Hokama, Tomiko; Law, Lewis S K; Chan, Emily Y Y

2015-07-01

Short-term associations between both hot and cold ambient temperatures and higher mortality have been found worldwide. Few studies have examined these associations on longer time scales. Age-standardized mortality rates (ASMRs) were calculated for 1976-2012 for Hong Kong SAR, People's Republic of China, defining "annual" time periods in 2 ways: from May through April of the following year and from November through October. Annual frequency and severity of extreme temperatures were summarized by using a degree-days approach with extreme heat expressed as annual degree-days >29.3°C and cold as annual degree-days <27.5°C. For example, a day with a mean temperature of 25.0°C contributes 2.5 cold degree-days to the annual total. Generalized additive models were used to estimate the association between annual hot and cold degree-days and the ASMR, with adjustment for long-term trends. Increases of 10 hot or 200 cold degree-days in an annual period, the approximate interquartile ranges for these variables, were significantly (all P's ≤ 0.011) associated with 1.9% or 3.1% increases, respectively, in the annual ASMR for the May-April analyses and with 2.2% or 2.8% increases, respectively, in the November-October analyses. Associations were stronger for noncancer and elderly mortality. Mortality increases associated with extreme temperature are not simply due to short-term forward displacement of deaths that would have occurred anyway within a few weeks. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Obtaining continuous BrAC/BAC estimates in the field: A hybrid system integrating transdermal alcohol biosensor, Intellidrink smartphone app, and BrAC Estimator software tools.

PubMed

Luczak, Susan E; Hawkins, Ashley L; Dai, Zheng; Wichmann, Raphael; Wang, Chunming; Rosen, I Gary

2018-08-01

Biosensors have been developed to measure transdermal alcohol concentration (TAC), but converting TAC into interpretable indices of blood/breath alcohol concentration (BAC/BrAC) is difficult because of variations that occur in TAC across individuals, drinking episodes, and devices. We have developed mathematical models and the BrAC Estimator software for calibrating and inverting TAC into quantifiable BrAC estimates (eBrAC). The calibration protocol to determine the individualized parameters for a specific individual wearing a specific device requires a drinking session in which BrAC and TAC measurements are obtained simultaneously. This calibration protocol was originally conducted in the laboratory with breath analyzers used to produce the BrAC data. Here we develop and test an alternative calibration protocol using drinking diary data collected in the field with the smartphone app Intellidrink to produce the BrAC calibration data. We compared BrAC Estimator software results for 11 drinking episodes collected by an expert user when using Intellidrink versus breath analyzer measurements as BrAC calibration data. Inversion phase results indicated the Intellidrink calibration protocol produced similar eBrAC curves and captured peak eBrAC to within 0.0003%, time of peak eBrAC to within 18min, and area under the eBrAC curve to within 0.025% alcohol-hours as the breath analyzer calibration protocol. This study provides evidence that drinking diary data can be used in place of breath analyzer data in the BrAC Estimator software calibration procedure, which can reduce participant and researcher burden and expand the potential software user pool beyond researchers studying participants who can drink in the laboratory. Copyright © 2017. Published by Elsevier Ltd.

Wind effect on PV module temperature: Analysis of different techniques for an accurate estimation.

NASA Astrophysics Data System (ADS)

Schwingshackl, Clemens; Petitta, Marcello; Ernst Wagner, Jochen; Belluardo, Giorgio; Moser, David; Castelli, Mariapina; Zebisch, Marc; Tetzlaff, Anke

2013-04-01

temperature estimation using meteorological parameters. References: [1] Skoplaki, E. et al., 2008: A simple correlation for the operating temperature of photovoltaic modules of arbitrary mounting, Solar Energy Materials & Solar Cells 92, 1393-1402 [2] Skoplaki, E. et al., 2008: Operating temperature of photovoltaic modules: A survey of pertinent correlations, Renewable Energy 34, 23-29 [3] Koehl, M. et al., 2011: Modeling of the nominal operating cell temperature based on outdoor weathering, Solar Energy Materials & Solar Cells 95, 1638-1646 [4] Mattei, M. et al., 2005: Calculation of the polycrystalline PV module temperature using a simple method of energy balance, Renewable Energy 31, 553-567 [5] Kurtz, S. et al.: Evaluation of high-temperature exposure of rack-mounted photovoltaic modules