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.

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.

Estimation of hydraulic conductivity in an alluvial system using temperatures.

PubMed

Su, Grace W; Jasperse, James; Seymour, Donald; Constantz, Jim

2004-01-01

Well water temperatures are often collected simultaneously with water levels; however, temperature data are generally considered only as a water quality parameter and are not utilized as an environmental tracer. In this paper, water levels and seasonal temperatures are used to estimate hydraulic conductivities in a stream-aquifer system. To demonstrate this method, temperatures and water levels are analyzed from six observation wells along an example study site, the Russian River in Sonoma County, California. The range in seasonal ground water temperatures in these wells varied from <0.2 degrees C in two wells to approximately 8 degrees C in the other four wells from June to October 2000. The temperature probes in the six wells are located at depths between 3.5 and 7.1 m relative to the river channel. Hydraulic conductivities are estimated by matching simulated ground water temperatures to the observed ground water temperatures. An anisotropy of 5 (horizontal to vertical hydraulic conductivity) generally gives the best fit to the observed temperatures. Estimated conductivities vary over an order of magnitude in the six locations analyzed. In some locations, a change in the observed temperature profile occurred during the study, most likely due to deposition of fine-grained sediment and organic matter plugging the streambed. A reasonable fit to this change in the temperature profile is obtained by decreasing the hydraulic conductivity in the simulations. This study demonstrates that seasonal ground water temperatures monitored in observation wells provide an effective means of estimating hydraulic conductivities in alluvial aquifers.

Estimation of hydraulic conductivity in an alluvial system using temperatures

USGS Publications Warehouse

Su, G.W.; Jasperse, James; Seymour, D.; Constantz, J.

2004-01-01

Well water temperatures are often collected simultaneously with water levels; however, temperature data are generally considered only as a water quality parameter and are not utilized as an environmental tracer. In this paper, water levels and seasonal temperatures are used to estimate hydraulic conductivities in a stream-aquifer system. To demonstrate this method, temperatures and water levels are analyzed from six observation wells along an example study site, the Russian River in Sonoma County, California. The range in seasonal ground water temperatures in these wells varied from < 0.2??C in two wells to ???8??C in the other four wells from June to October 2000. The temperature probes in the six wells are located at depths between 3.5 and 7.1 m relative to the river channel. Hydraulic conductivities are estimated by matching simulated ground water temperatures to the observed ground water temperatures. An anisotropy of 5 (horizontal to vertical hydraulic conductivity) generally gives the best fit to the observed temperatures. Estimated conductivities vary over an order of magnitude in the six locations analyzed. In some locations, a change in the observed temperature profile occurred during the study, most likely due to deposition of fine-grained sediment and organic matter plugging the streambed. A reasonable fit to this change in the temperature profile is obtained by decreasing the hydraulic conductivity in the simulations. This study demonstrates that seasonal ground water temperatures monitored in observation wells provide an effective means of estimating hydraulic conductivities in alluvial aquifers.

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.

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.

Estimating Arrhenius parameters using temperature programmed molecular dynamics.

PubMed

Imandi, Venkataramana; Chatterjee, Abhijit

2016-07-21

Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.

Estimating Arrhenius parameters using temperature programmed molecular dynamics

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

Imandi, Venkataramana; Chatterjee, Abhijit, E-mail: abhijit@che.iitb.ac.in

2016-07-21

Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight variousmore » aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.« less

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

Surface Temperature Assimilation in Land Surface Models

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman

1997-01-01

This paper examines the utilization of surface temperature as a variable to be assimilated in offline land surface hydrological models. Comparisons between the model computed and satellite observed surface temperatures have been carried out. The assimilation of surface temperature is carried out twice a day (corresponding to the AM and PM overpass of the NOAA10) over the Red- Arkansas basin in the Southwestern United States (31 deg 50 min N - 36 deg N, 94 deg 30 min W - 104 deg 30 min W) for a period of one year (August 1987 to July 1988). The effect of assimilation is to reduce the difference between the surface soil moisture computed for the precipitation and/or shortwave radiation perturbed case and the unperturbed case compared to no assimilation.

Surface Temperature Assimilation in Land Surface Models

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman

1999-01-01

This paper examines the utilization of surface temperature as a variable to be assimilated in offline land surface hydrological models. Comparisons between the model computed and satellite observed surface temperatures have been carried out. The assimilation of surface temperature is carried out twice a day (corresponding to the AM and PM overpass of the NOAA10) over the Red-Arkansas basin in the Southwestern United States (31 degs 50 sec N - 36 degrees N, 94 degrees 30 seconds W - 104 degrees 3 seconds W) for a period of one year (August 1987 to July 1988). The effect of assimilation is to reduce the difference between the surface soil moisture computed for the precipitation and/or shortwave radiation perturbed case and the unperturbed case compared to no assimilation.

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.

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.

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.

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.

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

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

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.

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

Optimal estimation retrieval of aerosol microphysical properties from SAGE~II satellite observations in the volcanically unperturbed lower stratosphere

NASA Astrophysics Data System (ADS)

Wurl, D.; Grainger, R. G.; McDonald, A. J.; Deshler, T.

2010-05-01

Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003). An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE) method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths) with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities), even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal) size distributions naturally

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.

Estimation of subsurface thermal structure using sea surface height and sea surface temperature

NASA Technical Reports Server (NTRS)

Kang, Yong Q. (Inventor); Jo, Young-Heon (Inventor); Yan, Xiao-Hai (Inventor)

2012-01-01

A method of determining a subsurface temperature in a body of water is disclosed. The method includes obtaining surface temperature anomaly data and surface height anomaly data of the body of water for a region of interest, and also obtaining subsurface temperature anomaly data for the region of interest at a plurality of depths. The method further includes regressing the obtained surface temperature anomaly data and surface height anomaly data for the region of interest with the obtained subsurface temperature anomaly data for the plurality of depths to generate regression coefficients, estimating a subsurface temperature at one or more other depths for the region of interest based on the generated regression coefficients and outputting the estimated subsurface temperature at the one or more other depths. Using the estimated subsurface temperature, signal propagation times and trajectories of marine life in the body of water are determined.

A Model of an Integrated Immune System Pathway in Homo sapiens and Its Interaction with Superantigen Producing Expression Regulatory Pathway in Staphylococcus aureus: Comparing Behavior of Pathogen Perturbed and Unperturbed Pathway

PubMed Central

Tomar, Namrata; De, Rajat K.

2013-01-01

Response of an immune system to a pathogen attack depends on the balance between the host immune defense and the virulence of the pathogen. Investigation of molecular interactions between the proteins of a host and a pathogen helps in identifying the pathogenic proteins. It is necessary to understand the dynamics of a normally behaved host system to evaluate the capacity of its immune system upon pathogen attack. In this study, we have compared the behavior of an unperturbed and pathogen perturbed host system. Moreover, we have developed a formalism under Flux Balance Analysis (FBA) for the optimization of conflicting objective functions. We have constructed an integrated pathway system, which includes Staphylococcal Superantigen (SAg) expression regulatory pathway and TCR signaling pathway of Homo sapiens. We have implemented the method on this pathway system and observed the behavior of host signaling molecules upon pathogen attack. The entire study has been divided into six different cases, based on the perturbed/unperturbed conditions. In other words, we have investigated unperturbed and pathogen perturbed human TCR signaling pathway, with different combinations of optimization of concentrations of regulatory and signaling molecules. One of these cases has aimed at finding out whether minimization of the toxin production in a pathogen leads to the change in the concentration levels of the proteins coded by TCR signaling pathway genes in the infected host. Based on the computed results, we have hypothesized that the balance between TCR signaling inhibitory and stimulatory molecules can keep TCR signaling system into resting/stimulating state, depending upon the perturbation. The proposed integrated host-pathogen interaction pathway model has accurately reflected the experimental evidences, which we have used for validation purpose. The significance of this kind of investigation lies in revealing the susceptible interaction points that can take back the

ATM regulates Cdt1 stability during the unperturbed S phase to prevent re-replication

PubMed Central

Iwahori, Satoko; Kohmon, Daisuke; Kobayashi, Junya; Tani, Yuhei; Yugawa, Takashi; Komatsu, Kenshi; Kiyono, Tohru; Sugimoto, Nozomi; Fujita, Masatoshi

2014-01-01

Ataxia-telangiectasia mutated (ATM) plays crucial roles in DNA damage responses, especially with regard to DNA double-strand breaks (DSBs). However, it appears that ATM can be activated not only by DSB, but also by some changes in chromatin architecture, suggesting potential ATM function in cell cycle control. Here, we found that ATM is involved in timely degradation of Cdt1, a critical replication licensing factor, during the unperturbed S phase. At least in certain cell types, degradation of p27Kip1 was also impaired by ATM inhibition. The novel ATM function for Cdt1 regulation was dependent on its kinase activity and NBS1. Indeed, we found that ATM is moderately phosphorylated at Ser1981 during the S phase. ATM silencing induced partial reduction in levels of Skp2, a component of SCFSkp2 ubiquitin ligase that controls Cdt1 degradation. Furthermore, Skp2 silencing resulted in Cdt1 stabilization like ATM inhibition. In addition, as reported previously, ATM silencing partially prevented Akt phosphorylation at Ser473, indicative of its activation, and Akt inhibition led to modest stabilization of Cdt1. Therefore, the ATM-Akt-SCFSkp2 pathway may partly contribute to the novel ATM function. Finally, ATM inhibition rendered cells hypersensitive to induction of re-replication, indicating importance for maintenance of genome stability. PMID:24280901

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.

A generalised age- and phase-structured model of human tumour cell populations both unperturbed and exposed to a range of cancer therapies.

PubMed

Basse, Britta; Ubezio, Paolo

2007-07-01

We develop a general mathematical model for a population of cells differentiated by their position within the cell division cycle. A system of partial differential equations governs the kinetics of cell densities in certain phases of the cell division cycle dependent on time t (hours) and an age-like variable tau (hours) describing the time since arrival in a particular phase of the cell division cycle. Transition rate functions control the transfer of cells between phases. We first obtain a theoretical solution on the infinite domain -infinity < t < infinity. We then assume that age distributions at time t=0 are known and write our solution in terms of these age distributions on t=0. In practice, of course, these age distributions are unknown. All is not lost, however, because a cell line before treatment usually lies in a state of asynchronous balanced growth where the proportion of cells in each phase of the cell cycle remain constant. We assume that an unperturbed cell line has four distinct phases and that the rate of transition between phases is constant within a short period of observation ('short' relative to the whole history of the tumour growth) and we show that under certain conditions, this is equivalent to exponential growth or decline. We can then gain expressions for the age distributions. So, in short, our approach is to assume that we have an unperturbed cell line on t

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.

Linear Transformation of the Polarization Modes in Coiled Optical Spun-Fibers with Strong Unperturbed Linear Birefringence. I. Nonresonant Transformation

NASA Astrophysics Data System (ADS)

Malykin, G. B.; Pozdnyakova, V. I.

2018-03-01

A linear transformation of orthogonal polarization modes in coiled optical spun-fibers with strong unperturbed linear birefringence, which causes the emergence of the dependences of the integrated elliptical birefringence and the ellipticity and azimuth of the major axis of the ellipse, as well as the polarization state of radiation (PSR), on the length of optical fiber has been considered. Optical spun-fibers are subjected to a strong mechanical twisting, which is frozen into the structure of the optical fiber upon cooling, in the process of being drawn out from the workpiece. Since the values of the local polarization parameters of coiled spunwaveguides vary according to a rather complex law, the calculations were carried out by numerical modeling of the parameters of the Jones matrices. Since the rotation speed of the axes of the birefringence is constant on a relatively short segment of a coiled optical spun-fiber in the accompanying torsion (helical) coordinate system, the so-called "Ginzburg helical polarization modes" (GHPMs)—two mutually orthogonal ellipses with the opposite directions of traversal, the axis of which rotate relative to the fixed coordinate system uniformly and unidirectionally—are approximately the local normal polarization modes of such optical fiber. It has been shown that, despite the fact that the unperturbed linear birefringence of the spun-fibers significantly exceeds the linear birefringence, which is caused by the winding on a coil, the integral birefringence of an extended segment of such a fiber coincides in order of magnitude with the linear birefringence, which is caused by the winding on the coil, and the integral polarization modes tend asymptotically to circular ones. It has been also shown that the values of the circular birefringence of twisted single-mode fibers, which were calculated in a nonrotating and torsion helical coordinate systems, differ significantly. It has been shown that the polarization phenomena occur

Neuro-genetic non-invasive temperature estimation: intensity and spatial prediction.

PubMed

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

2008-06-01

The existence of proper non-invasive temperature estimators is an essential aspect when thermal therapy applications are envisaged. These estimators must be good predictors to enable temperature estimation at different operational situations, providing better control of the therapeutic instrumentation. In this work, radial basis functions artificial neural networks were constructed to access temperature evolution on an ultrasound insonated medium. The employed models were radial basis functions neural networks with external dynamics induced by their inputs. Both the most suited set of model inputs and number of neurons in the network were found using the multi-objective genetic algorithm. The neural models were validated in two situations: the operating ones, as used in the construction of the network; and in 11 unseen situations. The new data addressed two new spatial locations and a new intensity level, assessing the intensity and space prediction capacity of the proposed model. Good performance was obtained during the validation process both in terms of the spatial points considered and whenever the new intensity level was within the range of applied intensities. A maximum absolute error of 0.5 degrees C+/-10% (0.5 degrees C is the gold-standard threshold in hyperthermia/diathermia) was attained with low computationally complex models. The results confirm that the proposed neuro-genetic approach enables foreseeing temperature propagation, in connection to intensity and space parameters, thus enabling the assessment of different operating situations with proper temperature resolution.

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.

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...

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

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.

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

Estimated Viscosities and Thermal Conductivities of Gases at High Temperatures

NASA Technical Reports Server (NTRS)

Svehla, Roger A.

1962-01-01

Viscosities and thermal conductivities, suitable for heat-transfer calculations, were estimated for about 200 gases in the ground state from 100 to 5000 K and 1-atmosphere pressure. Free radicals were included, but excited states and ions were not. Calculations for the transport coefficients were based upon the Lennard-Jones (12-6) potential for all gases. This potential was selected because: (1) It is one of the most realistic models available and (2) intermolecular force constants can be estimated from physical properties or by other techniques when experimental data are not available; such methods for estimating force constants are not as readily available for other potentials. When experimental viscosity data were available, they were used to obtain the force constants; otherwise the constants were estimated. These constants were then used to calculate both the viscosities and thermal conductivities tabulated in this report. For thermal conductivities of polyatomic gases an Eucken-type correction was made to correct for exchange between internal and translational energies. Though this correction may be rather poor at low temperatures, it becomes more satisfactory with increasing temperature. It was not possible to obtain force constants from experimental thermal conductivity data except for the inert atoms, because most conductivity data are available at low temperatures only (200 to 400 K), the temperature range where the Eucken correction is probably most in error. However, if the same set of force constants is used for both viscosity and thermal conductivity, there is a large degree of cancellation of error when these properties are used in heat-transfer equations such as the Dittus-Boelter equation. It is therefore concluded that the properties tabulated in this report are suitable for heat-transfer calculations of gaseous systems.

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.

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

Mechanochemical effect in the iron(III) spin crossover complex [Fe(3-MeO-salenEt2]PF6 as studied by heat capacity calorimetry.

PubMed

Sorai, Michio; Burriel, Ramón; Westrum, Edgar F; Hendrickson, David N

2008-04-10

Magnetic and thermal properties of the iron(III) spin crossover complex [Fe(3MeO-salenEt)(2)]PF(6) are very sensitive to mechanochemical perturbations. Heat capacities for unperturbed and differently perturbed samples were precisely determined by adiabatic calorimetry at temperatures in the 10-300 K range. The unperturbed compound shows a cooperative spin crossover transition at 162.31 K, presenting a hysteresis of 2.8 K. The anomalous enthalpy and entropy contents of the transition were evaluated to be Delta(trs)H = 5.94 kJ mol(-1) and Delta(trs)S = 36.7 J K(-1) mol(-1), respectively. By mechanochemical treatments, (1) the phase transition temperature was lowered by 1.14 K, (2) the enthalpy and entropy gains at the phase transition due to the spin crossover phenomenon were diminished to Delta(trs)H = 4.94 kJ mol(-1) and Delta(trs)S = 31.1 J K(-1) mol(-1), and (3) the lattice heat capacities were larger than those of the unperturbed sample over the whole temperature range. In spite of different mechanical perturbations (grinding with a mortar and pestle and grinding in a ball-mill), two sets of heat capacity measurements provided basically the same results. The mechanochemical perturbation exerts its effect more strongly on the low-spin state than on the high-spin state. It shows a substantial increase of the number of iron(III) ions in the high-spin state below the transition temperature. The heat capacities of the diamagnetic cobalt(III) analogue [Co(3MeO-salenEt)(2)]PF(6) also were measured. The lattice heat capacity of the iron compounds has been estimated from either the measurements on the cobalt complex using a corresponding states law or the effective frequency distribution method. These estimations have been used for the evaluation of the transition anomaly.

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.

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.

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.

Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model

NASA Technical Reports Server (NTRS)

Morris, A. Terry

1999-01-01

This paper examines various sources of error in MIT's improved top oil temperature rise over ambient temperature model and estimation process. The sources of error are the current parameter estimation technique, quantization noise, and post-processing of the transformer data. Results from this paper will show that an output error parameter estimation technique should be selected to replace the current least squares estimation technique. The output error technique obtained accurate predictions of transformer behavior, revealed the best error covariance, obtained consistent parameter estimates, and provided for valid and sensible parameters. This paper will also show that the output error technique should be used to minimize errors attributed to post-processing (decimation) of the transformer data. Models used in this paper are validated using data from a large transformer in service.

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.

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.

Using ultrasound CBE imaging without echo shift compensation for temperature estimation.

PubMed

Tsui, Po-Hsiang; Chien, Yu-Ting; Liu, Hao-Li; Shu, Yu-Chen; Chen, Wen-Shiang

2012-09-01

Clinical trials have demonstrated that hyperthermia improves cancer treatments. Previous studies developed ultrasound temperature imaging methods, based on the changes in backscattered energy (CBE), to monitor temperature variations during hyperthermia. Echo shift, induced by increasing temperature, contaminates the CBE image, and its tracking and compensation should normally ensure that estimations of CBE at each pixel are correct. To obtain a simplified algorithm that would allow real-time computation of CBE images, this study evaluated the usefulness of CBE imaging without echo shift compensation in detecting distributions in temperature. Experiments on phantoms, using different scatterer concentrations, and porcine livers were conducted to acquire raw backscattered data at temperatures ranging from 37°C to 45°C. Tissue samples of pork tenderloin were ablated in vitro by microwave irradiation to evaluate the feasibility of using the CBE image without compensation to monitor tissue ablation. CBE image construction was based on a ratio map obtained from the envelope image divided by the reference envelope image at 37°C. The experimental results demonstrated that the CBE image obtained without echo shift compensation has the ability to estimate temperature variations induced during uniform heating or tissue ablation. The magnitude of the CBE as a function of temperature obtained without compensation is stronger than that with compensation, implying that the CBE image without compensation has a better sensitivity to detect temperature. These findings suggest that echo shift tracking and compensation may be unnecessary in practice, thus simplifying the algorithm required to implement real-time CBE imaging. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

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.

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.

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 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

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.

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.

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.

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

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

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

On estimating total daily evapotranspiration from remote surface temperature measurements

NASA Technical Reports Server (NTRS)

Carlson, Toby N.; Buffum, Martha J.

1989-01-01

A method for calculating daily evapotranspiration from the daily surface energy budget using remotely sensed surface temperature and several meteorological variables is presented. Vaules of the coefficients are determined from simulations with a one-dimensional boundary layer model with vegetation cover. Model constants are obtained for vegetation and bare soil at two air temperature and wind speed levels over a range of surface roughness and wind speeds. A different means of estimating the daily evapotranspiration based on the time rate of increase of surface temperature during the morning is also considered. Both the equations using our model-derived constants and field measurements are evaluated, and a discussion of sources of error in the use of the formulation is given.

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.

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

The impact of threat of shock on the framing effect and temporal discounting: executive functions unperturbed by acute stress?

PubMed

Robinson, Oliver J; Bond, Rebecca L; Roiser, Jonathan P

2015-01-01

Anxiety and stress-related disorders constitute a large global health burden, but are still poorly understood. Prior work has demonstrated clear impacts of stress upon basic cognitive function: biasing attention toward unexpected and potentially threatening information and instantiating a negative affective bias. However, the impact that these changes have on higher-order, executive, decision-making processes is unclear. In this study, we examined the impact of a translational within-subjects stress induction (threat of unpredictable shock) on two well-established executive decision-making biases: the framing effect (N = 83), and temporal discounting (N = 36). In both studies, we demonstrate (a) clear subjective effects of stress, and (b) clear executive decision-making biases but (c) no impact of stress on these decision-making biases. Indeed, Bayes factor analyses confirmed substantial preference for decision-making models that did not include stress. We posit that while stress may induce subjective mood change and alter low-level perceptual and action processes (Robinson et al., 2013c), some higher-level executive processes remain unperturbed by these impacts. As such, although stress can induce a transient affective biases and altered mood, these need not result in poor financial decision-making.

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.

Discovery of functional interactions among actin regulators by analysis of image fluctuations in an unperturbed motile cell system.

PubMed

Isogai, Tadamoto; Danuser, Gaudenz

2018-05-26

Cell migration is driven by propulsive forces derived from polymerizing actin that pushes and extends the plasma membrane. The underlying actin network is constantly undergoing adaptation to new mechano-chemical environments and intracellular conditions. As such, mechanisms that regulate actin dynamics inherently contain multiple feedback loops and redundant pathways. Given the highly adaptable nature of such a system, studies that use only perturbation experiments (e.g. knockdowns, overexpression, pharmacological activation/inhibition, etc.) are challenged by the nonlinearity and redundancy of the pathway. In these pathway configurations, perturbation experiments at best describe the function(s) of a molecular component in an adapting (e.g. acutely drug-treated) or fully adapted (e.g. permanent gene silenced) cell system, where the targeted component now resides in a non-native equilibrium. Here, we propose how quantitative live-cell imaging and analysis of constitutive fluctuations of molecular activities can overcome these limitations. We highlight emerging actin filament barbed-end biology as a prime example of a complex, nonlinear molecular process that requires a fluctuation analytic approach, especially in an unperturbed cellular system, to decipher functional interactions of barbed-end regulators, actin polymerization and membrane protrusion.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

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.

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

Temperature and relative humidity estimation and prediction in the tobacco drying process using Artificial Neural Networks.

PubMed

Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M; Aguiar, Javier M; Carro, Belén

2012-10-17

This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.

Temperature and Relative Humidity Estimation and Prediction in the Tobacco Drying Process Using Artificial Neural Networks

PubMed Central

Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M.; Aguiar, Javier M.; Carro, Belén

2012-01-01

This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed. PMID:23202032

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.

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.

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.

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

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.

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.

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.

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

[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.

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.

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.

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.

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.

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.

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

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

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

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

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.

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.

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.

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

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 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.

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.

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.

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

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

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 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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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

Magnetic properties of ferromagnetic minerals generally depend on their chemical composition, crystal structure, size, and shape. In the usual paleomagnetic study, we use a bulk sample which is the assemblage of magnetic minerals showing broad distributions of various magnetic properties. Microscopic and Curie-point observations of the bulk sample enable us to identify the constituent magnetic minerals, while other measurements, for example, stepwise thermal and/or alternating field demagnetizations (ThD, AFD) make it possible to estimate size, shape and domain state of the constituent magnetic grains. However, estimation based on stepwise demagnetizations has a limitation that magnetic grains with the same coercivity Hc (or blocking temperature Tb) can be identified as the single population even though they could have different size and shape. Dunlop and West (1969) carried out mapping of grain size and coercivity (Hc) using pTRM. However, it is considered that their mapping method is basically applicable to natural rocks containing only SD grains, since the grain sizes are estimated on the basis of the single domain theory (Neel, 1949). In addition, it is impossible to check thermal alteration due to laboratory heating in their experiment. In the present study we propose a new experimental method which makes it possible to estimate distribution of size and shape of magnetic minerals in a bulk sample. The present method is composed of simple procedures: (1) imparting ARM to a bulk sample, (2) ThD at a certain temperature, (3) stepwise AFD on the remaining ARM, (4) repeating the steps (1) ~ (3) with ThD at elevating temperatures up to the Curie temperature of the sample. After completion of the whole procedures, ARM spectra are calculated and mapped on the HC-Tb plane (hereafter called HC-Tb diagram). We analyze the Hc-Tb diagrams as follows: (1) For uniaxial SD populations, theoretical curve for a certain grain size (or shape anisotropy) is drawn on the Hc

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

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.

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

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.

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.

Stability basin estimates fall risk from observed kinematics, demonstrated on the Sit-to-Stand task.

PubMed

Shia, Victor; Moore, Talia Yuki; Holmes, Patrick; Bajcsy, Ruzena; Vasudevan, Ram

2018-04-27

The ability to quantitatively measure stability is essential to ensuring the safety of locomoting systems. While the response to perturbation directly reflects the stability of a motion, this experimental method puts human subjects at risk. Unfortunately, existing indirect methods for estimating stability from unperturbed motion have been shown to have limited predictive power. This paper leverages recent advances in dynamical systems theory to accurately estimate the stability of human motion without requiring perturbation. This approach relies on kinematic observations of a nominal Sit-to-Stand motion to construct an individual-specific dynamic model, input bounds, and feedback control that are then used to compute the set of perturbations from which the model can recover. This set, referred to as the stability basin, was computed for 14 individuals, and was able to successfully differentiate between less and more stable Sit-to-Stand strategies for each individual with greater accuracy than existing methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

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.

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.

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

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.

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.

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).

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.

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...

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

Evaluating linear response in active systems with no perturbing field: Application to the calculation of an effective temperature

NASA Astrophysics Data System (ADS)

Szamel, Grzegorz

We present a method for the evaluation of time-dependent linear response functions for systems of active particles propelled by a persistent (colored) noise from unperturbed simulations. The method is inspired by the Malliavin weights sampling method proposed earlier for systems of (passive) Brownian particles. We illustrate our method by evaluating a linear response function for a single active particle in an external harmonic potential. As an application, we calculate the time-dependent mobility function and an effective temperature, defined through the Einstein relation between the self-diffusion and mobility coefficients, for a system of active particles interacting via a screened-Coulomb potential. We find that this effective temperature decreases with increasing persistence time of the self-propulsion. Initially, for not too large persistence times, it changes rather slowly, but then it decreases markedly when the persistence length of the self-propelled motion becomes comparable with the particle size. Supported by NSF and ERC.

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.

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

Unperturbed volume transition of thermosensitive poly-(N-isopropylacrylamide) microgel particles embedded in a hydrogel matrix.

PubMed

Musch, Judith; Schneider, Stefanie; Lindner, Peter; Richtering, Walter

2008-05-22

The thermoresponsive behavior of poly-(N-isopropylacrylamide) (PNiPAM) microgels embedded in a covalently cross-linked polyacrylamide hydrogel matrix was investigated using ultraviolet-visible (UV-vis) spectroscopy, small-angle neutron scattering (SANS), and confocal laser scanning microscopy. The hydrogel synthesis was performed at two different temperatures, below and above the volume phase transition temperature of PNiPAM, resulting in highly swollen or fully collapsed PNiPAM microgel particles during the incorporation step. UV-vis spectroscopy experiments verify that the incorporation of thermosensitive microgels leads to temperature-sensitive optical properties of the composite materials. SANS measurements at different temperatures show that the thermosensitive swelling behavior of the PNiPAM microgels is fully retained in the composite material. Volume and structure criteria of the embedded microgel particles are compared to those of the free microgels in acrylamide solution. To visualize the temperature responsive behavior of larger PNiPAM particles, confocal fluorescence microscopy images of PNiPAM beads, of 40-microm size, were taken at two different temperatures. The micrographs also demonstrate the retained temperature sensitivity of the embedded microgels.

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.

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

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

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.

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

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

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...

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

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.

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

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

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.

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

The Value Estimation of an HFGW Frequency Time Standard for Telecommunications Network Optimization

NASA Astrophysics Data System (ADS)

Harper, Colby; Stephenson, Gary

2007-01-01

The emerging technology of gravitational wave control is used to augment a communication system using a development roadmap suggested in Stephenson (2003) for applications emphasized in Baker (2005). In the present paper consideration is given to the value of a High Frequency Gravitational Wave (HFGW) channel purely as providing a method of frequency and time reference distribution for use within conventional Radio Frequency (RF) telecommunications networks. Specifically, the native value of conventional telecommunications networks may be optimized by using an unperturbed frequency time standard (FTS) to (1) improve terminal navigation and Doppler estimation performance via improved time difference of arrival (TDOA) from a universal time reference, and (2) improve acquisition speed, coding efficiency, and dynamic bandwidth efficiency through the use of a universal frequency reference. A model utilizing a discounted cash flow technique provides an estimation of the additional value using HFGW FTS technology could bring to a mixed technology HFGW/RF network. By applying a simple net present value analysis with supporting reference valuations to such a network, it is demonstrated that an HFGW FTS could create a sizable improvement within an otherwise conventional RF telecommunications network. Our conservative model establishes a low-side value estimate of approximately 50B USD Net Present Value for an HFGW FTS service, with reasonable potential high-side values to significant multiples of this low-side value floor.

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.

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.

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.

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.

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

Using passive fiber-optic distributed temperature sensing to estimate soil water content at a discontinuous permafrost site

NASA Astrophysics Data System (ADS)

Wagner, A. M.; Lindsey, N.; Ajo Franklin, J. B.; Gelvin, A.; Saari, S.; Ekblaw, I.; Ulrich, C.; Dou, S.; James, S. R.; Martin, E. R.; Freifeld, B. M.; Bjella, K.; Daley, T. M.

2016-12-01

We present preliminary results from an experimental study targeting the use of passive fiber-optic distributed temperature sensing (DTS) in a variety of geometries to estimate moisture content evolution in a dynamic permafrost system. A 4 km continuous 2D array of multi-component fiber optic cable (6 SM/6 MM) was buried at the Fairbanks Permafrost Experiment Station to investigate the possibility of using fiber optic distributed sensing as an early detection system for permafrost thaw. A heating experiment using 120 60 Watt heaters was conducted in a 140 m2 area to artificially thaw the topmost section of permafrost. The soils at the site are primarily silt but some disturbed areas include backfilled gravel to depths of approximately 1.0 m. Where permafrost exists, the depth to permafrost ranges from 1.5 to approximately 5 m. The experiment was also used to spatially estimate soil water content distribution throughout the fiber optic array. The horizontal fiber optic cable was buried at depths between 10 and 20 cm. Soil temperatures were monitored with a DTS system at 25 cm increments along the length of the fiber. At five locations, soil water content time-domain reflectometer (TDR) probes were also installed at two depths, in line with the fiber optic cable and 15 to 25 cm below the cable. The moisture content along the fiber optic array was estimated using diurnal effects from the dual depth temperature measurements. In addition to the horizontally installed fiber optic cable, vertical lines of fiber optic cable were also installed inside and outside the heater plot to a depth of 10 m in small diameter (2 cm) boreholes. These arrays were installed in conjunction with thermistor strings and are used to monitor the thawing process and to cross correlate with soil temperatures at the depth of the TDR probes. Results will be presented from the initiation of the artificial thawing through subsequent freeze-up. A comparison of the DTS measured temperatures and

Estimation of Monthly Near Surface Air Temperature Using Geographically Weighted Regression in China

NASA Astrophysics Data System (ADS)

Wang, M. M.; He, G. J.; Zhang, Z. M.; Zhang, Z. J.; Liu, X. G.

2018-04-01

Near surface air temperature (NSAT) is a primary descriptor of terrestrial environment conditions. The availability of NSAT with high spatial resolution is deemed necessary for several applications such as hydrology, meteorology and ecology. In this study, a regression-based NSAT mapping method is proposed. This method is combined remote sensing variables with geographical variables, and uses geographically weighted regression to estimate NSAT. The altitude was selected as geographical variable; and the remote sensing variables include land surface temperature (LST) and Normalized Difference vegetation index (NDVI). The performance of the proposed method was assessed by predict monthly minimum, mean, and maximum NSAT from point station measurements in China, a domain with a large area, complex topography, and highly variable station density, and the NSAT maps were validated against the meteorology observations. Validation results with meteorological data show the proposed method achieved an accuracy of 1.58 °C. It is concluded that the proposed method for mapping NSAT is very operational and has good precision.

Estimating Sea Surface Temperature Measurement Methods Using Characteristic Differences in the Diurnal Cycle

NASA Astrophysics Data System (ADS)

Carella, G.; Kennedy, J. J.; Berry, D. I.; Hirahara, S.; Merchant, C. J.; Morak-Bozzo, S.; Kent, E. C.

2018-01-01

Lack of reliable observational metadata represents a key barrier to understanding sea surface temperature (SST) measurement biases, a large contributor to uncertainty in the global surface record. We present a method to identify SST measurement practice by comparing the observed SST diurnal cycle from individual ships with a reference from drifting buoys under similar conditions of wind and solar radiation. Compared to existing estimates, we found a larger number of engine room-intake (ERI) reports post-World War II and in the period 1960-1980. Differences in the inferred mixture of observations lead to a systematic warmer shift of the bias adjusted SST anomalies from 1980 compared to previous estimates, while reducing the ensemble spread. Changes in mean field differences between bucket and ERI SST anomalies in the Northern Hemisphere over the period 1955-1995 could be as large as 0.5°C and are not well reproduced by current bias adjustment models.

Estimation of core body temperature from skin temperature, heat flux, and heart rate using a Kalman filter.

PubMed

Welles, Alexander P; Xu, Xiaojiang; Santee, William R; Looney, David P; Buller, Mark J; Potter, Adam W; Hoyt, Reed W

2018-05-18

Core body temperature (T C ) is a key physiological metric of thermal heat-strain yet it remains difficult to measure non-invasively in the field. This work used combinations of observations of skin temperature (T S ), heat flux (HF), and heart rate (HR) to accurately estimate T C using a Kalman Filter (KF). Data were collected from eight volunteers (age 22 ± 4 yr, height 1.75 ± 0.10 m, body mass 76.4 ± 10.7 kg, and body fat 23.4 ± 5.8%, mean ± standard deviation) while walking at two different metabolic rates (∼350 and ∼550 W) under three conditions (warm: 25 °C, 50% relative humidity (RH); hot-humid: 35 °C, 70% RH; and hot-dry: 40 °C, 20% RH). Skin temperature and HF data were collected from six locations: pectoralis, inner thigh, scapula, sternum, rib cage, and forehead. Kalman filter variables were learned via linear regression and covariance calculations between T C and T S , HF, and HR. Root mean square error (RMSE) and bias were calculated to identify the best performing models. The pectoralis (RMSE 0.18 ± 0.04 °C; bias -0.01 ± 0.09 °C), rib (RMSE 0.18 ± 0.09 °C; bias -0.03 ± 0.09 °C), and sternum (RMSE 0.20 ± 0.10 °C; bias -0.04 ± 0.13 °C) were found to have the lowest error values when using T S , HF, and HR but, using only two of these measures provided similar accuracy. Copyright © 2018. Published by Elsevier Ltd.

Estimations of temperature deviations in chromatographic columns using isenthalpic plots. I. Theory for isocratic systems.

PubMed

Tarafder, Abhijit; Iraneta, Pamela; Guiochon, Georges; Kaczmarski, Krzysztof; Poe, Donald P

2014-10-31

We propose to use constant enthalpy or isenthalpic diagrams as a tool to estimate the extent of the temperature variations caused by the mobile phase pressure drop along a chromatographic column, e.g. of its cooling in supercritical fluid and its heating in ultra-performance liquid chromatography. Temperature strongly affects chromatographic phenomena. Any of its variations inside the column, whether intended or not, can lead to significant changes in separation performance. Although instruments use column ovens in order to keep constant the column temperature, operating conditions leading to a high pressure drop may cause significant variations of the column temperature, both in the axial and the radial directions, from the set value. Different ways of measuring these temperature variations are available but they are too inconvenient to be employed in many practical situations. In contrast, the thermodynamic plot-based method that we describe here can easily be used with only a ruler and a pencil. They should be helpful in developing methods or in analyzing results in analytical laboratories. Although the most effective application area for this approach should be SFC (supercritical fluid chromatography), it can be applied to any chromatographic conditions in which temperature variations take place along the column due to the pressure drop, e.g. in ultra-high pressure liquid chromatography (UHPLC). The method proposed here is applicable to isocractic conditions only. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Potential impact of thermal effects during ultrasonic neurostimulation: retrospective numerical estimation of temperature elevation in seven rodent setups

NASA Astrophysics Data System (ADS)

Constans, Charlotte; Mateo, Philippe; Tanter, Mickaël; Aubry, Jean-François

2018-01-01

In the past decade, a handful but growing number of groups have reported worldwide successful low intensity focused ultrasound induced neurostimulation trials on rodents. Its effects range from movement elicitations to reduction of anesthesia time or reduction of the duration of drug induced seizures. The mechanisms underlying ultrasonic neuromodulation are still not fully understood. Given the low intensities used in most of the studies, a mechanical effect is more likely to be responsible for the neuromodulation effect, but a clear description of the thermal and mechanical effects is necessary to optimize clinical applications. Based on five studies settings, we calculated the temperature rise and thermal doses in order to evaluate its implication in the neuromodulation phenomenon. Our retrospective analysis shows thermal rise ranging from 0.002 °C to 0.8 °C in the brain for all setups, except for one setup for which the temperature increase is estimated to be as high as 7 °C. We estimate that in the latter case, temperature rise cannot be neglected as a possible cause of neuromodulation. Simulations results were supported by temperature measurements on a mouse with two different sets of parameters. Although the calculated temperature is compatible with the absence of visible thermal lesions on the skin, it is high enough to impact brain circuits. Our study highlights the usefulness of performing thermal simulations prior to experiment in order to fully take into account not only the impact of the peak intensity but also pulse duration and pulse repetition.

Use of thermal imagery for estimation of core body temperature during precooling, exertion, and recovery in wildland firefighter protective clothing.

PubMed

Bourlai, Thirimachos; Pryor, Riana R; Suyama, Joe; Reis, Steven E; Hostler, David

2012-01-01

Monitoring core body temperature to identify heat stress in first responders and in individuals participating in mass gatherings (e.g., marathons) is difficult. This study utilized high-sensitivity thermal imaging technology to predict the core temperature of human subjects at a distance while performing simulated field operations wearing thermal protective garments. Six male subjects participating in a study of precooling prior to exertion in wildland firefighter thermal protective clothing had thermal images of the face captured with a high-resolution thermal imaging camera concomitant with measures of core and skin temperature before, during, and after treadmill exercise in a heated room. Correlations and measures of agreement between core temperature and thermal imaging-based temperature were performed. The subjects walked an average (± standard deviation) of 42.6 (±5.9) minutes and a distance of 4.2 (±0.6) km on the treadmill. Mean heart rate at the end of exercise was 152 (±33) bpm and core body temperature at the end of exercise was 38.3°C (±0.7°C). A visual relationship and a strong correlation between core temperature and thermal imaging of the face were identified in all subjects, with the closest relationship and best agreement occurring during exercise. The Bland-Altman test of agreement during exercise revealed the majority of measurement pairs to be within two standard deviations of the measured temperature. High-resolution thermal imaging in the middle-wave infrared spectrum (3-5 μm) can be used to accurately estimate core body temperature during exertion in a hot room while participants are wearing wildland firefighting garments. Although this technology is promising, it must be refined. Using alternative measurement sites such as the skin over the carotid artery, using multiple measurement sites, or adding pulse detection may improve the estimation of body temperature by thermal imagery.

Observational estimation of radiative feedback to surface air temperature over Northern High Latitudes

NASA Astrophysics Data System (ADS)

Hwang, Jiwon; Choi, Yong-Sang; Kim, WonMoo; Su, Hui; Jiang, Jonathan H.

2018-01-01

The high-latitude climate system contains complicated, but largely veiled physical feedback processes. Climate predictions remain uncertain, especially for the Northern High Latitudes (NHL; north of 60°N), and observational constraint on climate modeling is vital. This study estimates local radiative feedbacks for NHL based on the CERES/Terra satellite observations during March 2000-November 2014. The local shortwave (SW) and longwave (LW) radiative feedback parameters are calculated from linear regression of radiative fluxes at the top of the atmosphere on surface air temperatures. These parameters are estimated by the de-seasonalization and 12-month moving average of the radiative fluxes over NHL. The estimated magnitudes of the SW and the LW radiative feedbacks in NHL are 1.88 ± 0.73 and 2.38 ± 0.59 W m-2 K-1, respectively. The parameters are further decomposed into individual feedback components associated with surface albedo, water vapor, lapse rate, and clouds, as a product of the change in climate variables from ERA-Interim reanalysis estimates and their pre-calculated radiative kernels. The results reveal the significant role of clouds in reducing the surface albedo feedback (1.13 ± 0.44 W m-2 K-1 in the cloud-free condition, and 0.49 ± 0.30 W m-2 K-1 in the all-sky condition), while the lapse rate feedback is predominant in LW radiation (1.33 ± 0.18 W m-2 K-1). However, a large portion of the local SW and LW radiative feedbacks were not simply explained by the sum of these individual feedbacks.

Improving Soil Moisture and Temperature Profile and Surface Turbulent Fluxes Estimations in Irrigated Field by Assimilating Multi-source Data into Land Surface Model

NASA Astrophysics Data System (ADS)

Chen, Weijing; Huang, Chunlin; Shen, Huanfeng; Wang, Weizhen

2016-04-01

The optimal estimation of hydrothermal conditions in irrigation field is restricted by the deficiency of accurate irrigation information (when and how much to irrigate). However, the accurate estimation of soil moisture and temperature profile and surface turbulent fluxes are crucial to agriculture and water management in irrigated field. In the framework of land surface model, soil temperature is a function of soil moisture - subsurface moisture influences the heat conductivity at the interface of layers and the heat storage in different layers. In addition, soil temperature determines the phase of soil water content with the transformation between frozen and unfrozen. Furthermore, surface temperature affects the partitioning of incoming radiant energy into ground (sensible and latent heat flux), as a consequence changes the delivery of soil moisture and temperature. Given the internal positive interaction lying in these variables, we attempt to retrieve the accurate estimation of soil moisture and temperature profile via assimilating the observations from the surface under unknown irrigation. To resolve the input uncertainty of imprecise irrigation quantity, original EnKS is implemented with inflation and localization (referred to as ESIL) aiming at solving the underestimation of the background error matrix and the extension of observation information from the top soil to the bottom. EnKS applied in this study includes the states in different time points which tightly connect with adjacent ones. However, this kind of relationship gradually vanishes along with the increase of time interval. Thus, the localization is also employed to readjust temporal scale impact between states and filter out redundant or invalid correlation. Considering the parameter uncertainty which easily causes the systematic deviation of model states, two parallel filters are designed to recursively estimate both states and parameters. The study area consists of irrigated farmland and is

Analysis of a resistance-energy balance method for estimating daily evaporation from wheat plots using one-time-of-day infrared temperature observations

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Idso, S. B.; Reginato, R. J.

1986-01-01

Accurate estimates of evaporation over field-scale or larger areas are needed in hydrologic studies, irrigation scheduling, and meteorology. Remotely sensed surface temperature might be used in a model to calculate evaporation. A resistance-energy balance model, which combines an energy balance equation, the Penman-Monteith (1981) evaporation equation, and van den Honert's (1948) equation for water extraction by plant roots, is analyzed for estimating daily evaporation from wheat using postnoon canopy temperature measurements. Additional data requirements are half-hourly averages of solar radiation, air and dew point temperatures, and wind speed, along with reasonable estimates of canopy emissivity, albedo, height, and leaf area index. Evaporation fluxes were measured in the field by precision weighing lysimeters for well-watered and water-stressed wheat. Errors in computed daily evaporation were generally less than 10 percent, while errors in cumulative evaporation for 10 clear sky days were less than 5 percent for both well-watered and water-stressed wheat. Some results from sensitivity analysis of the model are also given.

Estimation of subsurface formation temperature in the Yangtze area, South China: implications for shale gas generation and preservation

NASA Astrophysics Data System (ADS)

Liu, S.; Hao, C.; Li, X.; Xu, M.

2015-12-01

Temperature is one key parameter for hydrocarbon generation and preservation, also playing important role in geothermal energy assessment;however, accurate regional temperature pattern is still challenging, owing to a lack of data coverage and data quality as well. The Yangtze area, located in the South China, is considered as the most favorable target for shale gas resource exploration in China, and attracts more and more attention recently. Here we used the newly acquired steady-state temperature loggings, reliable Drilling Stem Test temperature data available and thermal properties, estimated the subsurface temperature-at-depth for the Yangtze area. Results show that the geothermal gradient ranges between 17 K/m and 74K/m, mainly falling into 20~30K/m, with a mean of 24 K/m; heat flow varies from 25 mW/m2 to 92 mW/m2, with a mean of 65 mW/m2. For the estimated temperature-at-depth, it is about 20~50 ℃ at the depth of 1000m, 50~80℃ for that at 2000m; while the highest temperature can be up to 110℃ at 3000m depth. Generally, the present-day geothermal regime of the Yangtze area is characterized by high in the northeast, low in the middle and localized high again in the southwest, and this pattern is well consistent with the tectono-thermal processes occurred in the area. Due to Cenozoic crustal extension in the northeastern Yangtze area, magmatism is prevailed, accounting for the high heat flow observed. Precambrian basement exists in the middle Yangtze area, such as the Xuefeng and Wuling Mountains, heat flow and subsurface temperature accordingly show relatively low as well. While for the southwestern Yangtze area, especially Yunnan and western Sichuan provinces, localized Cenozoic magmatism and tectonic activities are available, which is attributed to the high geothermal regime there. Considering the Paleozoic intensive tectonic deformation in the Yangtze area, tectonically stable area is prerequisite for shale gas preservation. Geothermal regime analysis

A comparison of temperature and humidity effects on phosphor-converted LED packages and the prediction of remaining useful life with state estimation

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

Lall, Pradeep; Zhang, Hao; Davis, Lynn

This paper focuses on the failure mechanisms and color stability of a commercially available high power LED under harsh environmental conditions. 3 groups of the same pc-HB warm white LED were used in the experiment. The first group was subjected to both high temperature and high relative humidity (85°C/85%RH) with a 350mA bias current. The second group was subjected to only temperature stress at 105°C with a 350mA bias current. The last group was subjected to extreme high temperature 175°C and high bias current (500mA). Samples were taken out from the chamber for both photometric and colorimetric analysis at periodicmore » intervals to investigate the change of the optical parameters. The physics of failure due to the material degradation has been correlated with the change in the photometric and colorimetric parameters of the LED packages. At the end of the experiment, 6000 hours of data is projected forward with state estimation methods to compare with projections made with the TM-21 method. Experimental results shows that only optical parts degrades at high temperature conditions. However, at both high temperature and high relative humidity condition, the phosphor layer of the pc-LED can swell and the color stability of LEDs degrades significantly. Also, comparison between TM-21 method and state estimation method shows that state estimation can achieve the same goal with a relatively easy method.« less

[Soil moisture estimation method based on both ground-based remote sensing data and air temperature in a summer maize ecosystem.

PubMed

Wang, Min Zheng; Zhou, Guang Sheng

2016-06-01

Soil moisture is an important component of the soil-vegetation-atmosphere continuum (SPAC). It is a key factor to determine the water status of terrestrial ecosystems, and is also the main source of water supply for crops. In order to estimate soil moisture at different soil depths at a station scale, based on the energy balance equation and the water deficit index (WDI), a soil moisture estimation model was established in terms of the remote sensing data (the normalized difference vegetation index and surface temperature) and air temperature. The soil moisture estimation model was validated based on the data from the drought process experiment of summer maize (Zea mays) responding to different irrigation treatments carried out during 2014 at Gucheng eco-agrometeorological experimental station of China Meteorological Administration. The results indicated that the soil moisture estimation model developed in this paper was able to evaluate soil relative humidity at different soil depths in the summer maize field, and the hypothesis was reasonable that evapotranspiration deficit ratio (i.e., WDI) linearly depended on soil relative humidity. It showed that the estimation accuracy of 0-10 cm surface soil moisture was the highest (R 2 =0.90). The RMAEs of the estimated and measured soil relative humidity in deeper soil layers (up to 50 cm) were less than 15% and the RMSEs were less than 20%. The research could provide reference for drought monitoring and irrigation management.

Quadratic Zeeman effect in hydrogen Rydberg states: Rigorous bound-state error estimates in the weak-field regime

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

Falsaperla, P.; Fonte, G.

1993-05-01

Applying a method based on some results due to Kato [Proc. Phys. Soc. Jpn. 4, 334 (1949)], we show that series of Rydberg eigenvalues and Rydberg eigenfunctions of hydrogen in a uniform magnetic field can be calculated with a rigorous error estimate. The efficiency of the method decreases as the eigenvalue density increases and as [gamma][ital n][sup 3][r arrow]1, where [gamma] is the magnetic-field strength in units of 2.35[times]10[sup 9] G and [ital n] is the principal quantum number of the unperturbed hydrogenic manifold from which the diamagnetic Rydberg states evolve. Fixing [gamma] at the laboratory value 2[times]10[sup [minus]5] andmore » confining our calculations to the region [gamma][ital n][sup 3][lt]1 (weak-field regime), we obtain extremely accurate results up to states corresponding to the [ital n]=32 manifold.« less

Soil moisture status estimation over Three Gorges area with Landsat TM data based on temperature vegetation dryness index

NASA Astrophysics Data System (ADS)

Xu, Lina; Niu, Ruiqing; Li, Jiong; Dong, Yanfang

2011-12-01

Soil moisture is the important indicator of climate, hydrology, ecology, agriculture and other parameters of the land surface and atmospheric interface. Soil moisture plays an important role on the water and energy exchange at the land surface/atmosphere interface. Remote sensing can provide information on large area quickly and easily, so it is significant to do research on how to monitor soil moisture by remote sensing. This paper presents a method to assess soil moisture status using Landsat TM data over Three Gorges area in China based on TVDI. The potential of Temperature- Vegetation Dryness Index (TVDI) from Landsat TM data in assessing soil moisture was investigated in this region. After retrieving land surface temperature and vegetation index a TVDI model based on the features of Ts-NDVI space is established. And finally, soil moisture status is estimated according to TVDI. It shows that TVDI has the advantages of stability and high accuracy to estimating the soil moisture status.

Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Q.; Minnis, P.; daSilva, A. M., Jr.; Palikonda, R.; Yost, C. R.

2012-01-01

Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

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).

Estimating eruption temperature from thermal emission spectra of lava fountain activity in the Erta'Ale (Ethiopia) volcano lava lake: Implications for observing Io's volcanoes

USGS Publications Warehouse

Davies, Ashley G.; Keszthelyi, Laszlo P.; McEwen, Alfred S.

2011-01-01

We have analysed high-spatial-resolution and high-temporal-resolution temperature measurements of the active lava lake at Erta'Ale volcano, Ethiopia, to derive requirements for measuring eruption temperatures at Io's volcanoes. Lava lakes are particularly attractive targets because they are persistent in activity and large, often with ongoing lava fountain activity that exposes lava at near-eruption temperature. Using infrared thermography, we find that extracting useful temperature estimates from remote-sensing data requires (a) high spatial resolution to isolate lava fountains from adjacent cooler lava and (b) rapid acquisition of multi-color data. Because existing spacecraft data of Io's volcanoes do not meet these criteria, it is particularly important to design future instruments so that they will be able to collect such data. Near-simultaneous data at more than two relatively short wavelengths (shorter than 1 μm) are needed to constrain eruption temperatures. Resolving parts of the lava lake or fountains that are near the eruption temperature is also essential, and we provide a rough estimate of the required image scale.

Estimating eruption temperature from thermal emission spectra of lava fountain activity in the Erta'Ale (Ethiopia) volcano lava lake: Implications for observing Io's volcanoes

USGS Publications Warehouse

Davies, A.G.; Keszthelyi, L.; McEwen, A.S.

2011-01-01

We have analysed high-spatial-resolution and high-temporal-resolution temperature measurements of the active lava lake at Erta'Ale volcano, Ethiopia, to derive requirements for measuring eruption temperatures at Io's volcanoes. Lava lakes are particularly attractive targets because they are persistent in activity and large, often with ongoing lava fountain activity that exposes lava at near-eruption temperature. Using infrared thermography, we find that extracting useful temperature estimates from remote-sensing data requires (a) high spatial resolution to isolate lava fountains from adjacent cooler lava and (b) rapid acquisition of multi-color data. Because existing spacecraft data of Io's volcanoes do not meet these criteria, it is particularly important to design future instruments so that they will be able to collect such data. Near-simultaneous data at more than two relatively short wavelengths (shorter than 1 ??m) are needed to constrain eruption temperatures. Resolving parts of the lava lake or fountains that are near the eruption temperature is also essential, and we provide a rough estimate of the required image scale. ?? 2011 by the American Geophysical Union.

Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

NASA Technical Reports Server (NTRS)

Hearty, Thomas J.; Savtchenko, Andrey K.; Tian, Baijun; Fetzer, Eric; Yung, Yuk L.; Theobald, Michael; Vollmer, Bruce; Fishbein, Evan; Won, Young-In

2014-01-01

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

Modeling Lunar Borehole Temperature in order to Reconstruct Historical Total Solar Irradiance and Estimate Surface Temperature in Permanently Shadowed Regions

NASA Astrophysics Data System (ADS)

Wen, G.; Cahalan, R. F.; Miyahara, H.; Ohmura, A.

2007-12-01

The Moon is an ideal place to reconstruct historical total solar irradiance (TSI). With undisturbed lunar surface albedo and the very low thermal diffusivity of lunar regolith, changes in solar input lead to changes in lunar surface temperature that diffuse downward to be recorded in the temperature profile in the near-surface layer. Using regolith thermal properties from Apollo, we model the heat transfer in the regolith layer, and compare modeled surface temperature to Apollo observations to check model performance. Using as alternative input scenarios two reconstructed TSI time series from 1610 to 2000 (Lean, 2000; Wang, Lean, and Sheeley 2005), we conclude that the two scenarios can be distinguished by detectable differences in regolith temperature, with the peak difference of about 10 mK occuring at a depth of about 10 m (Miyahara et al., 2007). The possibility that water ice exists in permanently shadowed areas near the lunar poles (Nozette et al., 1997; Spudis et al, 1998), makes it of interest to estimate surface temperature in such dark regions. "Turning off" the Sun in our time dependent model, we found it would take several hundred years for the surface temperature to drop from ~~100K immediately after sunset down to a nearly constant equilibrium temperature of about 24~~38 K, with the range determined by the range of possible input from Earth, from 0 W/m2 without Earth visible, up to about 0.1 W/m2 at maximum Earth phase. A simple equilibrium model (e.g., Huang 2007) is inappropriate to relate the Apollo-observed nighttime temperature to Earth's radiation budget, given the long multi- centennial time scale needed for equilibration of the lunar surface layer after sunset. Although our results provide the key mechanisms for reconstructing historical TSI, further research is required to account for topography of lunar surfaces, and new measurements of regolith thermal properties will also be needed once a new base of operations is

Estimation of the Total Atmospheric Water Vapor Content and Land Surface Temperature Based on AATSR Thermal Data

PubMed Central

Zhang, Tangtang; Wen, Jun; van der Velde, Rogier; Meng, Xianhong; Li, Zhenchao; Liu, Yuanyong; Liu, Rong

2008-01-01

The total atmospheric water vapor content (TAWV) and land surface temperature (LST) play important roles in meteorology, hydrology, ecology and some other disciplines. In this paper, the ENVISAT/AATSR (The Advanced Along-Track Scanning Radiometer) thermal data are used to estimate the TAWV and LST over the Loess Plateau in China by using a practical split window algorithm. The distribution of the TAWV is accord with that of the MODIS TAWV products, which indicates that the estimation of the total atmospheric water vapor content is reliable. Validations of the LST by comparing with the ground measurements indicate that the maximum absolute derivation, the maximum relative error and the average relative error is 4.0K, 11.8% and 5.0% respectively, which shows that the retrievals are believable; this algorithm can provide a new way to estimate the LST from AATSR data. PMID:27879795

Influence of core body temperature on Tryptophan metabolism, kynurenines, and estimated IDO activity in critically ill patients receiving target temperature management following cardiac arrest.

PubMed

Schefold, Joerg C; Fritschi, Nora; Fusch, Gerhard; Bahonjic, Aldin; Doehner, Wolfram; von Haehling, Stephan; Pschowski, Rene; Storm, Christian; Schroeder, Tim

2016-10-01

Temperature control improves neurological prognosis in comatose cardiac arrest (CA) survivors. Previous reports demonstrate that most affected patients show signs of significant systemic inflammation. In an effort to better characterize potential temperature-related effects on key inflammatory pathways, we investigate the course of Tryptophan (Trp) levels, Tryptophan catabolites (including kynurenines) and indoleamine-2,3-dioxygenase (IDO)-activity in post CA patients. In an observational blinded endpoint analysis, a total of n=270 serial samples from 20 post CA patients (63.1±16.6 yrs., 45% shockable rhythm, mean time to return of spontaneous circulation (ROSC) 26.6±16.0min) treated with target temperature management (TTM) were analyzed. Core body temperatures, course of Trp, Trp catabolites (incl. kynurenines), and estimated IDO-activity were followed up for a maximum of 7 days after ROSC. Patients were followed up until hospital discharge or death and functional outcome was recorded. Over the 7-day observational interval, marked changes in Trp serum levels and IDO-activity were noted. In general, Trp serum levels but not IDO-activity seemed to parallel with the course of core body temperature. In explorative analyses, a correlation of Trp (rho=0.271 (95%-CI: 0.16-0.38, p<0.0001) and IDO-activity (rho=-0.155, 95%-CI: -0.27 to -0.037, p=0.01) with core body temperature was observed. Linear mixed effect models revealed a positive significant association of core body temperature with Trp serum levels (Likelihood ratio test χ(2)=6.35, p=0.012). In patients with good (vs. unfavorable) outcome, a tendency toward higher Trp serum levels, lower IDO-activity, and lower Kynurenic acid levels was noted. We observed significant changes in Trp catabolism and IDO-activity that appeared temperature associated in post CA patients. Under hypothermia, decreased serum levels of Trp and increased IDO-activity were noted. We speculate from our data that IDO-induction during

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.

Optimization of tissue physical parameters for accurate temperature estimation from finite-element simulation of radiofrequency ablation.

PubMed

Subramanian, Swetha; Mast, T Douglas

2015-10-07

Computational finite element models are commonly used for the simulation of radiofrequency ablation (RFA) treatments. However, the accuracy of these simulations is limited by the lack of precise knowledge of tissue parameters. In this technical note, an inverse solver based on the unscented Kalman filter (UKF) is proposed to optimize values for specific heat, thermal conductivity, and electrical conductivity resulting in accurately simulated temperature elevations. A total of 15 RFA treatments were performed on ex vivo bovine liver tissue. For each RFA treatment, 15 finite-element simulations were performed using a set of deterministically chosen tissue parameters to estimate the mean and variance of the resulting tissue ablation. The UKF was implemented as an inverse solver to recover the specific heat, thermal conductivity, and electrical conductivity corresponding to the measured area of the ablated tissue region, as determined from gross tissue histology. These tissue parameters were then employed in the finite element model to simulate the position- and time-dependent tissue temperature. Results show good agreement between simulated and measured temperature.

Accuracy of the Estimated Core Temperature (ECTemp) Algorithm in Estimating Circadian Rhythm Indicators

DTIC Science & Technology

2017-04-12

measurement of CT outside of stringent laboratory environments. This study evaluated ECTempTM, a heart rate-based extended Kalman Filter CT...based CT-estimation algorithms [7, 13, 14]. One notable example is ECTempTM, which utilizes an extended Kalman Filter to estimate CT from...3. The extended Kalman filter mapping function variance coefficient (Ct) was computed using the following equation: = −9.1428 ×

Estimating Density and Temperature Dependence of Juvenile Vital Rates Using a Hidden Markov Model

PubMed Central

McElderry, Robert M.

2017-01-01

Organisms in the wild have cryptic life stages that are sensitive to changing environmental conditions and can be difficult to survey. In this study, I used mark-recapture methods to repeatedly survey Anaea aidea (Nymphalidae) caterpillars in nature, then modeled caterpillar demography as a hidden Markov process to assess if temporal variability in temperature and density influence the survival and growth of A. aidea over time. Individual encounter histories result from the joint likelihood of being alive and observed in a particular stage, and I have included hidden states by separating demography and observations into parallel and independent processes. I constructed a demographic matrix containing the probabilities of all possible fates for each stage, including hidden states, e.g., eggs and pupae. I observed both dead and live caterpillars with high probability. Peak caterpillar abundance attracted multiple predators, and survival of fifth instars declined as per capita predation rate increased through spring. A time lag between predator and prey abundance was likely the cause of improved fifth instar survival estimated at high density. Growth rates showed an increase with temperature, but the preferred model did not include temperature. This work illustrates how state-space models can include unobservable stages and hidden state processes to evaluate how environmental factors influence vital rates of cryptic life stages in the wild. PMID:28505138

Estimates of Ground Temperature and Atmospheric Moisture from CERES Observations

NASA Technical Reports Server (NTRS)

Wu, Man Li C.; Schubert, Siegfried; Einaudi, Franco (Technical Monitor)

2000-01-01

A method is developed to retrieve surface ground temperature (Tg) and atmospheric moisture using clear sky fluxes (CSF) from CERES-TRMM observations. In general, the clear sky outgoing long-wave radiation (CLR) is sensitive to upper level moisture (q(sub h)) over wet regions and Tg over dry regions The clear sky window flux from 800 to 1200 /cm (RadWn) is sensitive to low level moisture (q(sub j)) and Tg. Combining these two measurements (CLR and RadWn), Tg and q(sub h) can be estimated over land, while q(sub h) and q(sub t) can be estimated over the oceans. The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic CSF data from two different global 4-dimensional data assimilation products. Simple linear regression is used to relate discrepancies in CSF to discrepancies in Tg, q(sub h) and q(sub t). The slopes of the regression lines define sensitivity parameters that can be exploited to help interpret mismatches between satellite observations and model-based estimates of CSF. For illustration, we analyze the discrepancies in the CSF between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) and a recent operational version of the European Center for Medium-Range Weather Prediction data assimilation system. In particular, our analysis of synthetic total and window region SCF differences (computed from two different assimilated data sets) shows that simple linear regression employing (Delta)Tg and broad layer (Delta)q(sub l) from 500 hPa to surface and (Delta)q(sub h) from 200 to 500 hPa provides a good approximation to the full radiative transfer calculations, typically explaining more than 90% of the 6-hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters

Estimating effective particle size of tropical deep convective clouds with a look-up table method using satellite measurements of brightness temperature differences

NASA Astrophysics Data System (ADS)

Hong, Gang; Minnis, Patrick; Doelling, David; Ayers, J. Kirk; Sun-Mack, Szedung

2012-03-01

A method for estimating effective ice particle radius Re at the tops of tropical deep convective clouds (DCC) is developed on the basis of precomputed look-up tables (LUTs) of brightness temperature differences (BTDs) between the 3.7 and 11.0 μm bands. A combination of discrete ordinates radiative transfer and correlated k distribution programs, which account for the multiple scattering and monochromatic molecular absorption in the atmosphere, is utilized to compute the LUTs as functions of solar zenith angle, satellite zenith angle, relative azimuth angle, Re, cloud top temperature (CTT), and cloud visible optical thickness τ. The LUT-estimated DCC Re agrees well with the cloud retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for the NASA Clouds and Earth's Radiant Energy System with a correlation coefficient of 0.988 and differences of less than 10%. The LUTs are applied to 1 year of measurements taken from MODIS aboard Aqua in 2007 to estimate DCC Re and are compared to a similar quantity from CloudSat over the region bounded by 140°E, 180°E, 0°N, and 20°N in the Western Pacific Warm Pool. The estimated DCC Re values are mainly concentrated in the range of 25-45 μm and decrease with CTT. Matching the LUT-estimated Re with ice cloud Re retrieved by CloudSat, it is found that the ice cloud τ values from DCC top to the vertical location where LUT-estimated Re is located at the CloudSat-retrieved Re profile are mostly less than 2.5 with a mean value of about 1.3. Changes in the DCC τ can result in differences of less than 10% for Re estimated from LUTs. The LUTs of 0.65 μm bidirectional reflectance distribution function (BRDF) are built as functions of viewing geometry and column amount of ozone above upper troposphere. The 0.65 μm BRDF can eliminate some noncore portions of the DCCs detected using only 11 μm brightness temperature thresholds, which result in a mean difference of only 0.6 μm for DCC Re estimated from BTD LUTs.

Challenging the distributed temperature sensing technique for estimating groundwater discharge to streams through controlled artificial point source experiment

NASA Astrophysics Data System (ADS)

Lauer, F.; Frede, H.-G.; Breuer, L.

2012-04-01

Spatially confined groundwater discharge can contribute significantly to stream discharge. Distributed fibre optic temperature sensing (DTS) of stream water has been successfully used to localize- and quantify groundwater discharge from this type "point sources" (PS) in small first-order streams. During periods when stream and groundwater temperatures differ PS appear as abrupt step in longitudinal stream water temperature distribution. Based on stream temperature observation up- and downstream of a point source and estimated or measured groundwater temperature the proportion of groundwater inflow to stream discharge can be quantified using simple mixing models. However so far this method has not been quantitatively verified, nor has a detailed uncertainty analysis of the method been conducted. The relative accuracy of this method is expected to decrease nonlinear with decreasing proportions of lateral inflow. Furthermore it depends on the temperature differences (ΔT) between groundwater and surface water and on the accuracy of temperature measurement itself. The latter could be affected by different sources of errors. For example it has been shown that a direct impact of solar radiation on fibre optic cables can lead to errors in temperature measurements in small streams due to low water depth. Considerable uncertainty might also be related to the determination of groundwater temperature through direct measurements or derived from the DTS signal. In order to directly validate the method and asses it's uncertainty we performed a set of artificial point source experiments with controlled lateral inflow rates to a natural stream. The experiments were carried out at the Vollnkirchener Bach, a small head water stream in Hessen, Germany in November and December 2011 during a low flow period. A DTS system was installed along a 1.2 km sub reach of the stream. Stream discharge was measured using a gauging flume installed directly upstream of the artificial PS. Lateral

Effects of air temperature and discharge on Upper Mississippi River summer water temperatures

USGS Publications Warehouse

Gray, Brian R.; Robertson, Dale M.; Rogala, James T.

2018-01-01

Recent interest in the potential effects of climate change has prompted studies of air temperature and precipitation associations with water temperatures in rivers and streams. We examined associations between summer surface water temperatures and both air temperature and discharge for 5 reaches of the Upper Mississippi River during 1994–2011. Water–air temperature associations at a given reach approximated 1:1 when estimated under an assumption of reach independence but declined to approximately 1:2 when water temperatures were permitted to covary among reaches and were also adjusted for upstream air temperatures. Estimated water temperature–discharge associations were weak. An apparently novel feature of this study is that of addressing changes in associations between water and air temperatures when both are correlated among reaches.

Modelling of surface-water temperature for the estimation of the Czech fishery productivity under the climate change

NASA Astrophysics Data System (ADS)

Svobodová, Eva; Trnka, Miroslav; Kopp, Radovan; Mareš, Jan; Dubrovský, Martin; Spurný, Petr; Žalud, Zděněk

2015-04-01

Freshwater fish production is significantly correlated with water temperature which is expected to increase under the climate change. This study is dealing with the estimation of the change of water temperature in productive ponds and its impact on the fishery in the Czech Republic. Calculation of surface-water temperature which was based on three-day mean of the air temperature was developed and tested in several ponds in three main fish production areas. Output of surface-water temperature model was compared with measured data and showed that the lower range of model accuracy is surface-water temperature 3°C, under this temperature threshold the model loses its predictive competence. In the expecting of surface-water temperature above the temperature 3°C the model has proved the well consistence between observed and modelled surface-water temperature (R 0.79 - 0.96). Verified model was applied in the conditions of climate change determined by the pattern scaling method, in which standardised scenarios were derived from five global circulation models MPEH5, CSMK3, IPCM4, GFCM21 and HADGEM. Results were evaluated with regard to thresholds which characterise the fish species requirements on water temperature. Used thresholds involved the upper temperature threshold for fish survival and the tolerable number of days in continual period with mentioned threshold surface-water temperature. Target fish species were Common carp (Cyprinus carpio), Maraene whitefish (Coregonus maraena), Northern whitefish (Coregonus peled) and Rainbow trout (Oncorhynchus mykis). Results indicated the limitation of the Czech fish-farming in terms of i) the increase of the length of continual periods with surface-water temperature above the threshold appropriate to given fish species toleration, ii) the increase of the number of continual periods with surface-water temperature above the threshold, both appropriate to given fish species toleration, and iii) the increase of overall number of

A comparison of fisheries biological reference points estimated from temperature-specific multi-species and single-species climate-enhanced stock assessment models

NASA Astrophysics Data System (ADS)

Holsman, Kirstin K.; Ianelli, James; Aydin, Kerim; Punt, André E.; Moffitt, Elizabeth A.

2016-12-01

Multi-species statistical catch at age models (MSCAA) can quantify interacting effects of climate and fisheries harvest on species populations, and evaluate management trade-offs for fisheries that target several species in a food web. We modified an existing MSCAA model to include temperature-specific growth and predation rates and applied the modified model to three fish species, walleye pollock (Gadus chalcogrammus), Pacific cod (Gadus macrocephalus) and arrowtooth flounder (Atheresthes stomias), from the eastern Bering Sea (USA). We fit the model to data from 1979 through 2012, with and without trophic interactions and temperature effects, and use projections to derive single- and multi-species biological reference points (BRP and MBRP, respectively) for fisheries management. The multi-species model achieved a higher over-all goodness of fit to the data (i.e. lower negative log-likelihood) for pollock and Pacific cod. Variability from water temperature typically resulted in 5-15% changes in spawning, survey, and total biomasses, but did not strongly impact recruitment estimates or mortality. Despite this, inclusion of temperature in projections did have a strong effect on BRPs, including recommended yield, which were higher in single-species models for Pacific cod and arrowtooth flounder that included temperature compared to the same models without temperature effects. While the temperature-driven multi-species model resulted in higher yield MBPRs for arrowtooth flounder than the same model without temperature, we did not observe the same patterns in multi-species models for pollock and Pacific cod, where variability between harvest scenarios and predation greatly exceeded temperature-driven variability in yield MBRPs. Annual predation on juvenile pollock (primarily cannibalism) in the multi-species model was 2-5 times the annual harvest of adult fish in the system, thus predation represents a strong control on population dynamics that exceeds temperature

SDR input power estimation algorithms

NASA Astrophysics Data System (ADS)

Briones, J. C.; Nappier, J. M.

The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.

SDR Input Power Estimation Algorithms

NASA Technical Reports Server (NTRS)

Nappier, Jennifer M.; Briones, Janette C.

2013-01-01

The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.

Reference breast temperature: proposal of an equation.

PubMed

Souza, Gladis Aparecida Galindo Reisemberger de; Brioschi, Marcos Leal; Vargas, José Viriato Coelho; Morais, Keli Cristiane Correia; Dalmaso Neto, Carlos; Neves, Eduardo Borba

2015-01-01

To develop an equation to estimate the breast reference temperature according to the variation of room and core body temperatures. Four asymptomatic women were evaluated for three consecutive menstrual cycles. Using thermography, the temperature of breasts and eyes was measured as indirect reference of core body and room temperatures. To analyze the thermal behavior of the breasts during the cycle, the core body and room temperatures were normalized by means of a mathematical equation. We performed 180 observations and the core temperature had the highest correlation with the breast temperature, followed by room temperature. The proposed prediction model could explain 45.3% of the breast temperature variation, with variable room temperature variable; it can be accepted as a way to estimate the reference breast temperature at different room temperatures. The average breast temperature in healthy women had a direct relation with the core and room temperature and can be estimated mathematically. It is suggested that an equation could be used in clinical practice to estimate the normal breast reference temperature in young women, regardless of the day of the cycle, therefore assisting in evaluation of anatomical studies.

Reference breast temperature: proposal of an equation

PubMed Central

de Souza, Gladis Aparecida Galindo Reisemberger; Brioschi, Marcos Leal; Vargas, José Viriato Coelho; Morais, Keli Cristiane Correia; Dalmaso, Carlos; Neves, Eduardo Borba

2015-01-01

ABSTRACT Objective To develop an equation to estimate the breast reference temperature according to the variation of room and core body temperatures. Methods Four asymptomatic women were evaluated for three consecutive menstrual cycles. Using thermography, the temperature of breasts and eyes was measured as indirect reference of core body and room temperatures. To analyze the thermal behavior of the breasts during the cycle, the core body and room temperatures were normalized by means of a mathematical equation. Results We performed 180 observations and the core temperature had the highest correlation with the breast temperature, followed by room temperature. The proposed prediction model could explain 45.3% of the breast temperature variation, with variable room temperature variable; it can be accepted as a way to estimate the reference breast temperature at different room temperatures. Conclusion The average breast temperature in healthy women had a direct relation with the core and room temperature and can be estimated mathematically. It is suggested that an equation could be used in clinical practice to estimate the normal breast reference temperature in young women, regardless of the day of the cycle, therefore assisting in evaluation of anatomical studies. PMID:26761549

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.

Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin.

PubMed

Longato, Enrico; Garrido, Maria; Saccardo, Desy; Montesinos Guevara, Camila; Mani, Ali R; Bolognesi, Massimo; Amodio, Piero; Facchinetti, Andrea; Sparacino, Giovanni; Montagnese, Sara

2017-01-01

A popular method to estimate proximal/distal temperature (TPROX and TDIST) consists in calculating a weighted average of nine wireless sensors placed on pre-defined skin locations. Specifically, TPROX is derived from five sensors placed on the infra-clavicular and mid-thigh area (left and right) and abdomen, and TDIST from four sensors located on the hands and feet. In clinical practice, the loss/removal of one or more sensors is a common occurrence, but limited information is available on how this affects the accuracy of temperature estimates. The aim of this study was to determine the accuracy of temperature estimates in relation to number/position of sensors removed. Thirteen healthy subjects wore all nine sensors for 24 hours and reference TPROX and TDIST time-courses were calculated using all sensors. Then, all possible combinations of reduced subsets of sensors were simulated and suitable weights for each sensor calculated. The accuracy of TPROX and TDIST estimates resulting from the reduced subsets of sensors, compared to reference values, was assessed by the mean squared error, the mean absolute error (MAE), the cross-validation error and the 25th and 75th percentiles of the reconstruction error. Tables of the accuracy and sensor weights for all possible combinations of sensors are provided. For instance, in relation to TPROX, a subset of three sensors placed in any combination of three non-homologous areas (abdominal, right or left infra-clavicular, right or left mid-thigh) produced an error of 0.13°C MAE, while the loss/removal of the abdominal sensor resulted in an error of 0.25°C MAE, with the greater impact on the quality of the reconstruction. This information may help researchers/clinicians: i) evaluate the expected goodness of their TPROX and TDIST estimates based on the number of available sensors; ii) select the most appropriate subset of sensors, depending on goals and operational constraints.

Expected accuracy of proximal and distal temperature estimated by wireless sensors, in relation to their number and position on the skin

PubMed Central

Longato, Enrico; Garrido, Maria; Saccardo, Desy; Montesinos Guevara, Camila; Mani, Ali R.; Bolognesi, Massimo; Amodio, Piero; Facchinetti, Andrea; Sparacino, Giovanni

2017-01-01

A popular method to estimate proximal/distal temperature (TPROX and TDIST) consists in calculating a weighted average of nine wireless sensors placed on pre-defined skin locations. Specifically, TPROX is derived from five sensors placed on the infra-clavicular and mid-thigh area (left and right) and abdomen, and TDIST from four sensors located on the hands and feet. In clinical practice, the loss/removal of one or more sensors is a common occurrence, but limited information is available on how this affects the accuracy of temperature estimates. The aim of this study was to determine the accuracy of temperature estimates in relation to number/position of sensors removed. Thirteen healthy subjects wore all nine sensors for 24 hours and reference TPROX and TDIST time-courses were calculated using all sensors. Then, all possible combinations of reduced subsets of sensors were simulated and suitable weights for each sensor calculated. The accuracy of TPROX and TDIST estimates resulting from the reduced subsets of sensors, compared to reference values, was assessed by the mean squared error, the mean absolute error (MAE), the cross-validation error and the 25th and 75th percentiles of the reconstruction error. Tables of the accuracy and sensor weights for all possible combinations of sensors are provided. For instance, in relation to TPROX, a subset of three sensors placed in any combination of three non-homologous areas (abdominal, right or left infra-clavicular, right or left mid-thigh) produced an error of 0.13°C MAE, while the loss/removal of the abdominal sensor resulted in an error of 0.25°C MAE, with the greater impact on the quality of the reconstruction. This information may help researchers/clinicians: i) evaluate the expected goodness of their TPROX and TDIST estimates based on the number of available sensors; ii) select the most appropriate subset of sensors, depending on goals and operational constraints. PMID:28666029

Estimations of electron densities and temperatures in He-3 dominated plasmas. [in nuclear pumped lasers

NASA Technical Reports Server (NTRS)

Depaola, B. D.; Marcum, S. D.; Wrench, H. K.; Whitten, B. L.; Wells, W. E.

1979-01-01

It is very useful to have a method of estimation for electron temperature and electron densities in nuclear pumped plasmas because measurements of such quantities are very difficult. This paper describes a method, based on rate equation analysis of the ionized species in the plasma and the electron energy balance. In addition to the ionized species, certain neutral species must also be calculated. Examples are given for pure helium and a mixture of helium and argon. In the HeAr case, He(+), He2(+), He/2 3S/, Ar(+), Ar2(+), and excited Ar are evaluated.

Sex ratio estimations of loggerhead sea turtle hatchlings by histological examination and nest temperatures at Fethiye beach, Turkey

NASA Astrophysics Data System (ADS)

Kaska, Yakup; Ilgaz, Çetin; Özdemir, Adem; Başkale, Eyüp; Türkozan, Oğuz; Baran, Ibrahim; Stachowitsch, Michael

2006-07-01

Hatchling sex ratios in the loggerhead turtle ( Caretta caretta) were estimated by placing electronic temperature recorders in 21 nests at Fethiye beach during 2000 2002. Over the seasons, the mean temperature in the middle third of the incubation period ranged from 26.7 to 32.1°C, and incubation periods ranged from 49 to 67 days. Based on the mean temperatures during the middle third of the incubation period, and on histologically sexed dead hatchlings, the sex ratios of hatchlings at Fethiye beach were roughly equal, i.e. 60 65% of the hatchlings were females. This contrasts with the highly female-skewed sex ratios in loggerhead turtles elsewhere; Fethiye has a relatively high proportion of male hatchlings. For endangered sea turtles, the knowledge of hatchling sex ratios at different beaches, coupled with appropriate conservation measures, can make an important contribution to their survival.

Development of temperature-based algorithms for the estimation of microphytobenthic primary production in a tidal flat: A case study in Daebu mudflat, Korea.

PubMed

Kwon, Bong-Oh; Kim, Hae-Cheol; Koh, Chul-Hwan; Ryu, Jongseong; Son, SeungHyun; Kim, Yong Hoon; Khim, Jong Seong

2018-05-23

This study presents the results of field experiments that were designed to investigate the photophysiological characteristics of microphytobenthos (MPB) and to estimate primary production (PP) in Daebu mudflat, which is located at the west coast of Korea. A typical seasonal (or monthly) fluctuation of intertidal MPB PP was found in association with biotic (benthic Chl-a) and/or abiotic parameters (irradiance and temperature) over a period of three years. From a series of field-laboratory experiments using the oxygen micro-profiling method (totaling 28 surveys), three consistent phenomena were observed: 1) winter to early spring algal blooms, 2) seasonal changes in Q 10 , and 3) temperature dependent MPB photosynthesis-irradiance (P-I). In particular, both the chlorophyll-specific maximum photosynthetic capacity (P b max ) and the saturated light intensity (I k ), derived from 126 P-I curves (1870 data sets of oxygen micro-profiling in the sediment), were significantly correlated with sediment temperature (p < 0.01). To develop an empirical MPB PP model, the relationships between P-I parameters and environmental variables were parameterized following established exponential forms (e.g., Q 10 ). It was possible to estimate the MPB PP in Daebu mudflat area by using easily accessible explanatory factor, suitable to be used for future explorations of parameters such as sediment temperature, irradiance, chlorophyll concentration, and tidal height. The estimated annual MPB PP based on the empirical PP model were found to be greater than that in the Wadden Sea and average annual PP in the temperate zones of the world. Authors believe that the present approach of the MPB PP estimation could be combined with remote-sensing techniques (e.g., satellites) to support coastal ecosystem management. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

Estimates of Ground Temperature and Atmospheric Moisture from CERES Observations

NASA Technical Reports Server (NTRS)

Wu, Man Li C.; Schubert, Siegfried; Einaudi, Franco (Technical Monitor)

2000-01-01

A method is developed to retrieve surface ground temperature (T(sub g)) and atmospheric moisture using clear sky fluxes (CSF) from CERES-TRMM observations. In general, the clear sky outgoing longwave radiation (CLR) is sensitive to upper level moisture (q(sub l)) over wet regions and (T(sub g)) over dry regions The clear sky window flux from 800 to 1200/cm (RadWn) is sensitive to low level moisture (q(sub t)) and T(sub g). Combining these two measurements (CLR and RadWn), Tg and q(sub h) can be estimated over land, while q(sub h) and q(sub l) can be estimated over the oceans. The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic CSF data from two different global 4-dimensional data assimilation products. Simple linear regression is used to relate discrepancies in CSF to discrepancies in T(sub g), q(sub h) and q(sub l). The slopes of the regression lines define sensitivity parameters that can be exploited to help interpret mismatches between satellite observations and model-based estimates of CSF. For illustration, we analyze the discrepancies in the CSF between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) and a recent operational version of the European Center for Medium-Range Weather Prediction data assimilation system. In particular, our analysis of synthetic total and window region SCF differences (computed from two different assimilated data sets) shows that simple linear regression employing Delta(T(sub g)) and broad layer Delta(q(sub l) from .500 hPa to surface and Delta(q(sub h)) from 200 to .300 hPa provides a good approximation to the full radiative transfer calculations. typically explaining more than 90% of the 6-hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the

Real-time core body temperature estimation from heart rate for first responders wearing different levels of personal protective equipment.

PubMed

Buller, Mark J; Tharion, William J; Duhamel, Cynthia M; Yokota, Miyo

2015-01-01

First responders often wear personal protective equipment (PPE) for protection from on-the-job hazards. While PPE ensembles offer individuals protection, they limit one's ability to thermoregulate, and can place the wearer in danger of heat exhaustion and higher cardiac stress. Automatically monitoring thermal-work strain is one means to manage these risks, but measuring core body temperature (Tc) has proved problematic. An algorithm that estimates Tc from sequential measures of heart rate (HR) was compared to the observed Tc from 27 US soldiers participating in three different chemical/biological training events (45-90 min duration) while wearing PPE. Hotter participants (higher Tc) averaged (HRs) of 140 bpm and reached Tc around 39 °C. Overall the algorithm had a small bias (0.02 °C) and root mean square error (0.21 °C). Limits of agreement (LoA ± 0.48 °C) were similar to comparisons of Tc measured by oesophageal and rectal probes. The algorithm shows promise for use in real-time monitoring of encapsulated first responders. An algorithm to estimate core temperature (Tc) from non-invasive measures of HR was validated. Three independent studies (n = 27) compared the estimated Tc to the observed Tc in humans participating in chemical/ biological hazard training. The algorithm’s bias and variance to observed data were similar to that found from comparisons of oesophageal and rectal measurements.

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

Estimation of Land Surface Temperature from GCOM-W1 AMSR2 Data over the Chinese Landmass

NASA Astrophysics Data System (ADS)

Zhou, Ji; Dai, Fengnan; Zhang, Xiaodong

2016-04-01

As one of the most important parameter at the interface between the earth's surface and atmosphere, land surface temperature (LST) plays a crucial role in many fields, such as climate change monitoring and hydrological modeling. Satellite remote sensing provides the unique possibility to observe LST of large regions at diverse spatial and temporal scales. Compared with thermal infrared (TIR) remote sensing, passive microwave (PW) remote sensing has a better ability in overcoming the influences of clouds; thus, it can be used to improve the temporal resolution of current satellite TIR LST. However, most of current methods for estimation LST from PW remote sensing are empirical and have unsatisfied generalization. In this study, a semi-empirical method is proposed to estimate LST from the observation of the Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the Global Change Observation Mission 1st-WATER "SHIZUKU" satellite (GCOM-W1). The method is based on the PW radiation transfer equation, which is simplified based on (1) the linear relationship between the emissivities of horizontal and vertical polarization channels at the same frequency and (2) the significant relationship between atmospheric parameters and the atmospheric water vapor content. An iteration approach is used to best fit the pixel-based coefficients in the simplified radiation transfer equation of the horizontal and vertical polarization channels at each frequency. Then an integration approach is proposed to generate the ensemble estimation from estimations of multiple frequencies for different land cover types. This method is trained with the AMSR2 brightness temperature and MODIS LST in 2013 over the entire Chinese landmass and then it is tested with the data in 2014. Validation based on in situ LSTs measured in northwestern China demonstrates that the proposed method has a better accuracy than the polarization radiation method, with a root-mean squared error of 3 K. Although the proposal

New estimates for Io eruption temperatures: Implications for the interior

USGS Publications Warehouse

Keszthelyi, L.; Jaeger, W.; Milazzo, M.; Radebaugh, J.; Davies, A.G.; Mitchell, K.L.

2007-01-01

The initial interpretation of Galileo data from Jupiter's moon, Io, suggested eruption temperatures ≥1600°C. Tidal heating models have difficulties explaining Io's prodigious heat flow if the mantle is >1300°C, although we suggest that temperatures up to ~1450°C may be possible. In general, Io eruption temperatures have been overestimated because the incorrect thermal model has been applied. Much of the thermal emission from high-temperature hot spots comes from lava fountains but lava flow models were utilized. We apply a new lava fountain model to the highest reported eruption temperature, the SSI observation of the 1997 eruption at Pillan. This resets the lower temperature limit for the eruption from ~1600 to ~1340°C . Additionally, viscous heating of the magma may have increased eruption temperature by ~50-100°C as a result of the strong compressive stresses in the ionian lithosphere. While further work is needed, it appears that the discrepancy between observations and interior models is largely resolved.

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.

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

Temperature and volume estimation of under-seafloor fluid from the logging-while-drilling data beneath an active hydrothermal field

NASA Astrophysics Data System (ADS)

Hamada, Y.; Saito, S.; Sanada, Y.; Masaki, Y.; Moe, K.; Kido, Y. N.; Kumagai, H.; Takai, K.; Suzuki, K.

2015-12-01

In July of 2014, offshore drillings on Iheya-North Knoll, Okinawa Trough, was executed as part of Next-generation technology for ocean resources survey, which is a research program in Cross-ministerial Strategic Innovation Promotion Program (SIP). In this expedition, logging-while- drilling (LWD) and measuring-while-drilling (MWD) were inserted into 6 holes (C9011 - C9016) to investigate spatial distribution of hydrothermal deposit and geothermal fluid reservoir. Both of these tools included annular pressure-while-drilling (APWD). Annular pressure and temperature were monitored by the APWD to detect possible exceedingly-high-temperature geofluid. In addition, drilling fluid was continuously circulated at sufficient flow rate to protect LWD tools against high temperature (non-stop driller system). At C9012 and C9016, the LWD tool clearly detected pressure and temperature anomaly at 234 meter below the seafloor (mbsf) and 80 mbsf, respectively. Annular pressure and temperature quickly increases at that depth and it would reflect the injection of high-temperature fluid. During the drilling, however, drilling water was continuously circulated at high flow-rate (2600L/min) and the measured temperature is not exactly in-situ temperature. To investigate the detail of the heat source, such as in-situ temperature and quantity of heat, we performed numerical analyses of thermal fluid and energy-balance assuming injection of high-temperature fluid. We combined pressure loss theory of double cylinders and temperature equation to replicate the fluid flow and its temperature between borehole wall and drilling pipe during the thermofluid injection. As the result, we estimated the temperature and the volume of injected fluid to be 115oC~ and 17.3 m3, respectively (at C9012) from the calculation. This temperature is lower than that of a hydrothermall vent which had been found near the hole (300oC).

Estimation of thermal sensation during varied air temperature conditions.

PubMed

Katsuura, T; Tabuchi, R; Iwanaga, K; Harada, H; Kikuchi, Y

1998-03-01

Seven male students were exposed to four varied air temperature environments: hot (37 degrees C) to neutral (27 degrees C) (HN), neutral to hot (NH), cool (17 degrees C) to neutral (CN), and neutral to cool (NC). The air temperature was maintained at the first condition for 20 min, then was changed to the second condition after 15 min and was held there for 20 min. Each subject wore a T-shirt, briefs, trunks, and socks. Each sat on a chair and was continuously evaluated for thermal sensation, thermal comfort, and air velocity sensation. Some physiological and thermal parameters were also measured every 5 s during the experiment. The correlation between thermal sensation and skin temperature at 15 sites was found to be poor. The subjects felt much warmer during the rising phase of the air temperature (CN, NH) than during the descending phase (HN, NC) at a given mean skin temperature. However, thermal sensation at the same heat flux or at the same value of the difference between skin and air temperature (delta(Tsk - Ta)) was not so different among the four experimental conditions, and the correlation between thermal sensation and heat flux or delta(Tsk - Ta) was fairly good. The multiple regression equation of the thermal sensation (TS) on 15 sites of skin temperature (Tsk; degrees C) was calculated and the coefficient of determination (R*2) was found to be 0.656. Higher coefficients of determination were found in the equations of thermal sensation for the heat flux (H; kcal.m-2.h-1) at the right and left thighs of the subjects and on delta(Tsk - Ta) (degrees C) at 4 sites. They were as follows: TS = 2.04 - 0.016 Hright - 0.036 Hleft; R*2 = 0.717, TS = 1.649 + 0.013 delta(Tsk - Ta)UpperArm - 0.036 delta(Tsk - Ta)Chest - 0.223 delta(Tsk - Ta)Thigh-0.083 delta(Tsk - Ta)LowerLeg; R*2 = 0.752, respectively.

Estimation of effective temperatures in quantum annealers for sampling applications: A case study with possible applications in deep learning

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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.

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

Comparison of potential temperature gradient estimates from various temperature profile data sources

DOT National Transportation Integrated Search

2017-01-22

From July through September 2015, concurrent and collocated measurements of temperature profiles from two passive radiometers and a RADAR-RASS (Radio Acoustic Sounding System) were made at a site near the ocean just to the west of Los Angeles Interna...

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

PubMed Central

Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

2018-01-01

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system. PMID:29473877

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module.

PubMed

Lo, Yuan-Chieh; Hu, Yuh-Chung; Chang, Pei-Zen

2018-02-23

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe). Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t|) °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR) technique and implemented into the real-time embedded system.

Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data*

PubMed Central

Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen

2013-01-01

The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T a estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T a based on MODIS land surface temperature (LST) data. The verification results of maximum T a, minimum T a, GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001–2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale. PMID:23365013

Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data.

PubMed

Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen

2013-02-01

The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on MODIS land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.

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

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.

Temperature and atmospheric CO2 concentration estimates through the PETM using triple oxygen isotope analysis of mammalian bioapatite

PubMed Central

Gehler, Alexander; Pack, Andreas

2016-01-01

The Paleocene–Eocene Thermal Maximum (PETM) is a remarkable climatic and environmental event that occurred 56 Ma ago and has importance for understanding possible future climate change. The Paleocene–Eocene transition is marked by a rapid temperature rise contemporaneous with a large negative carbon isotope excursion (CIE). Both the temperature and the isotopic excursion are well-documented by terrestrial and marine proxies. The CIE was the result of a massive release of carbon into the atmosphere. However, the carbon source and quantities of CO2 and CH4 greenhouse gases that contributed to global warming are poorly constrained and highly debated. Here we combine an established oxygen isotope paleothermometer with a newly developed triple oxygen isotope paleo-CO2 barometer. We attempt to quantify the source of greenhouse gases released during the Paleocene–Eocene transition by analyzing bioapatite of terrestrial mammals. Our results are consistent with previous estimates of PETM temperature change and suggest that not only CO2 but also massive release of seabed methane was the driver for CIE and PETM. PMID:27354522

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

Estimating Clothing Thermal Insulation Using an Infrared Camera

PubMed Central

Lee, Jeong-Hoon; Kim, Young-Keun; Kim, Kyung-Soo; Kim, Soohyun

2016-01-01

In this paper, a novel algorithm for estimating clothing insulation is proposed to assess thermal comfort, based on the non-contact and real-time measurements of the face and clothing temperatures by an infrared camera. The proposed method can accurately measure the clothing insulation of various garments under different clothing fit and sitting postures. The proposed estimation method is investigated to be effective to measure its clothing insulation significantly in different seasonal clothing conditions using a paired t-test in 99% confidence interval. Temperatures simulated with the proposed estimated insulation value show closer to the values of actual temperature than those with individual clothing insulation values. Upper clothing’s temperature is more accurate within 3% error and lower clothing’s temperature is more accurate by 3.7%~6.2% error in indoor working scenarios. The proposed algorithm can reflect the effect of air layer which makes insulation different in the calculation to estimate clothing insulation using the temperature of the face and clothing. In future, the proposed method is expected to be applied to evaluate the customized passenger comfort effectively. PMID:27005625

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.

First-Principles Estimation of Electronic Temperature from X-Ray Thomson Scattering Spectrum of Isochorically Heated Warm Dense Matter

NASA Astrophysics Data System (ADS)

Mo, Chongjie; Fu, Zhenguo; Kang, Wei; Zhang, Ping; He, X. T.

2018-05-01

Through the perturbation formula of time-dependent density functional theory broadly employed in the calculation of solids, we provide a first-principles calculation of x-ray Thomson scattering spectrum of isochorically heated aluminum foil, as considered in the experiments of Sperling et al. [Phys. Rev. Lett. 115, 115001 (2015), 10.1103/PhysRevLett.115.115001], where ions were constrained near their lattice positions. From the calculated spectra, we find that the electronic temperature cannot exceed 2 eV, much smaller than the previous estimation of 6 eV via the detailed balance relation. Our results may well be an indication of unique electronic properties of warm dense matter, which can be further illustrated by future experiments. The lower electronic temperature predicted partially relieves the concern on the heating of x-ray free electron laser to the sample when used in structure measurement.

SNAP 10A ESTIMATED ELECTRICAL CHARACTERISTICS

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

Cooper, J.C.

1961-06-01

The electrical power characteristics of a SNAP 10A converter are estimated for given fractions of power degradation. Graphs are included showing the power characteristics for instantaneous transients from stabilized operation at the maximum efficiency point, and after system temperature stabilization at the operating point. Open-circuit emf's of the converter are estimated for instantaneous and temperature-stabilized cases. (D.L.C.)

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models

NASA Astrophysics Data System (ADS)

Kostov, Yavor; Marshall, John; Hausmann, Ute; Armour, Kyle C.; Ferreira, David; Holland, Marika M.

2017-03-01

We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern Annular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the response of the Southern Ocean SST (55°S-70°S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step response function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only 3 years after a step increase in the SAM. This intermodel diversity can be related to differences in the models' climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use observational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

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 nanoparticle optical absorption with magnetic resonance temperature imaging and bioheat transfer simulation.

PubMed

MacLellan, Christopher J; Fuentes, David; Elliott, Andrew M; Schwartz, Jon; Hazle, John D; Stafford, R Jason

2014-02-01

Optically activated nanoparticle-mediated heating for thermal therapy applications is an area of intense research. The ability to characterise the spatio-temporal heating potential of these particles for use in modelling under various exposure conditions can aid in the exploration of new approaches for therapy as well as more quantitative prospective approaches to treatment planning. The purpose of this research was to investigate an inverse solution to the heat equation using magnetic resonance temperature imaging (MRTI) feedback, for providing optical characterisation of two types of nanoparticles (gold-silica nanoshells and gold nanorods). The optical absorption of homogeneous nanoparticle-agar mixtures was measured during exposure to an 808 nm laser using real-time MRTI. A coupled finite element solution of heat transfer was registered with the data and used to solve the inverse problem. The L2 norm of the difference between the temperature increase in the model and MRTI was minimised using a pattern search algorithm by varying the absorption coefficient of the mixture. Absorption fractions were within 10% of literature values for similar nanoparticles. Comparison of temporal and spatial profiles demonstrated good qualitative agreement between the model and the MRTI. The weighted root mean square error was <1.5 σMRTI and the average Dice similarity coefficient for ΔT = 5 °C isotherms was >0.9 over the measured time interval. This research demonstrates the feasibility of using an indirect method for making minimally invasive estimates of nanoparticle absorption that might be expanded to analyse a variety of geometries and particles of interest.

Average Potential Temperature of the Upper Mantle and Excess Temperatures Beneath Regions of Active Upwelling

NASA Astrophysics Data System (ADS)

Putirka, K. D.

2006-05-01

The question as to whether any particular oceanic island is the result of a thermal mantle plume, is a question of whether volcanism is the result of passive upwelling, as at mid-ocean ridges, or active upwelling, driven by thermally buoyant material. When upwelling is passive, mantle temperatures reflect average or ambient upper mantle values. In contrast, sites of thermally driven active upwellings will have elevated (or excess) mantle temperatures, driven by some source of excess heat. Skeptics of the plume hypothesis suggest that the maximum temperatures at ocean islands are similar to maximum temperatures at mid-ocean ridges (Anderson, 2000; Green et al., 2001). Olivine-liquid thermometry, when applied to Hawaii, Iceland, and global MORB, belie this hypothesis. Olivine-liquid equilibria provide the most accurate means of estimating mantle temperatures, which are highly sensitive to the forsterite (Fo) contents of olivines, and the FeO content of coexisting liquids. Their application shows that mantle temperatures in the MORB source region are less than temperatures at both Hawaii and Iceland. The Siqueiros Transform may provide the most precise estimate of TpMORB because high MgO glass compositions there have been affected only by olivine fractionation, so primitive FeOliq is known; olivine thermometry yields TpSiqueiros = 1430 ±59°C. A global database of 22,000 MORB show that most MORB have slightly higher FeOliq than at Siqueiros, which translates to higher calculated mantle potential temperatures. If the values for Fomax (= 91.5) and KD (Fe-Mg)ol-liq (= 0.29) at Siqueiros apply globally, then upper mantle Tp is closer to 1485 ± 59°C. Averaging this global estimate with that recovered at Siqueiros yields TpMORB = 1458 ± 78°C, which is used to calculate plume excess temperatures, Te. The estimate for TpMORB defines the convective mantle geotherm, and is consistent with estimates from sea floor bathymetry and heat flow (Stein and Stein, 1992), and

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

[Estimation of the time of death based on the measurements of the eye temperature in comparison with other body sites].

PubMed

Kaliszan, Michał; Hauser, Roman

2007-01-01

A systematic two-stage study was conducted in pigs to verify the models of postmortem body temperature decrease currently employed in forensic medicine. During the investigations, temperature recordings were performed in four body sites (eyeballs, orbit soft tissues, muscles and rectums). The results of the study support the possible use of the eyeball and also the orbit soft tissues as temperature measuring sites at the early phase after death; they have narrowed the significance of rectum temperature measurements to the late stage of postmortem body temperature decrease, shown insignificant correlations between the body weight and the temperature decrease rate constant and illustrated the functional increase of the time of death estimation error as the body cools, expressed in the distinct tendency to overestimate the calculated time of death as compared to the actual one. In the second stage of the experiment, a lack of a plateau phase was demonstrated, at least from 30 min post mortem. It was also found that in the very early post mortem period, the kinetics of cooling of all the body sites studied was better described by the two-exponential model than the single exponential one. The study also showed that the weak airflow present in the experimental conditions did not practically affect the course of cooling of the investigated body sites. Eyeball temperature measurements with an infra-red laser thermometer performed during the experiment proved to be of no use for determination of the time of death. The experiments allowed for defining the so far unreported value of physiological temperature of pig eyeball as 38 degrees C.

Impact of temperature on childhood pneumonia estimated from satellite remote sensing.

PubMed

Xu, Zhiwei; Liu, Yang; Ma, Zongwei; Li, Shenghui; Hu, Wenbiao; Tong, Shilu

2014-07-01

The effect of temperature on childhood pneumonia in subtropical regions is largely unknown so far. This study examined the impact of temperature on childhood pneumonia in Brisbane, Australia. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood pneumonia in Brisbane from 2001 to 2010. The model residuals were checked to identify added effects due to heat waves or cold spells. Both high and low temperatures were associated with an increase in EDVs for childhood pneumonia. Children aged 2-5 years, and female children were particularly vulnerable to the impacts of heat and cold, and Indigenous children were sensitive to heat. Heat waves and cold spells had significant added effects on childhood pneumonia, and the magnitude of these effects increased with intensity and duration. There were changes over time in both the main and added effects of temperature on childhood pneumonia. Children, especially those female and Indigenous, should be particularly protected from extreme temperatures. Future development of early warning systems should take the change over time in the impact of temperature on children's health into account. Copyright © 2014 Elsevier Inc. All rights reserved.

Effect of Water Vapor, Temperature, and Rapid Annealing on Formamidinium Lead Triiodide Perovskite Crystallization

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

Aguiar, Jeffery A.; Wozny, Sarah; Alkurd, Nooraldeen R.

Perovskite-based solar cells are one of the emerging candidates for radically lower cost photovoltaics. Herein, we report on the synthesis and crystallization of organic-inorganic formamidinium lead triiodide perovskite films under controlled atmospheric and environmental conditions. Using in situ (scanning) transmission electron microscopy, we make observations of the crystallization process of these materials in nitrogen and oxygen gas with and without the presence of water vapor. Complementary planar samples were also fabricated in the presence of water vapor and characterized by in situ X-ray diffraction. Direct observations of the material structure and final morphology indicate that the exposure to water vapormore » results in a porous film that is metastable, regardless of the presence of argon, nitrogen, or oxygen. However, the optimal crystallization temperature of 175 degrees C is unperturbed across conditions. Rapid modulation about the annealing temperature of 175 degrees C in +/-25 degrees C steps (150-200 degrees C) promotes crystallization and significantly improves the film morphology by overcoming the presence of impregnated water trapped in the material. Following this processing protocol, we demonstrate substantial growth to micron-size grains via observation inside of an environmentally controlled transmission electron microscope. Adapting this insight from our in situ microscopy, we are able to provide an informed materials protocol to control the structure and morphology of these organic-inorganic semiconductors, which is readily applicable to benchtop device growth strategies.« less

Effect of Water Vapor, Temperature, and Rapid Annealing on Formamidinium Lead Triiodide Perovskite Crystallization

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

Aguiar, Jeffery A.; Wozny, Sarah; Alkurd, Nooraldeen R.

Perovskite-based solar cells are one of the emerging candidates for radically lower cost photovoltaics. Herein, we report on the synthesis and crystallization of organic-inorganic formamidinium lead triiodide perovskite films under controlled atmospheric and environmental conditions. Using in situ (scanning) transmission electron microscopy, we make observations of the crystallization process of these materials in nitrogen and oxygen gas with and without the presence of water vapor. Complementary planar samples were also fabricated in the presence of water vapor and characterized by in situ X-ray diffraction. Direct observations of the material structure and final morphology indicate that the exposure to water vapormore » results in a porous film that is metastable, regardless of the presence of argon, nitrogen, or oxygen. However, the optimal crystallization temperature of 175 °C is unperturbed across conditions. Rapid modulation about the annealing temperature of 175 °C in ±25 °C steps (150-200 °C) promotes crystallization and significantly improves the film morphology by overcoming the presence of impregnated water trapped in the material. Following this processing protocol, we demonstrate substantial growth to micron-size grains via observation inside of an environmentally controlled transmission electron microscope. Adapting this insight from our in situ microscopy, we are able to provide an informed materials protocol to control the structure and morphology of these organic-inorganic semiconductors, which is readily applicable to benchtop device growth strategies.« less

Estimation of wind speeds inside Super Typhoon Nepartak from AMSR2 low-frequency brightness temperatures

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yin, Xiaobin; Shi, Hanqing; Wang, Zhenzhan; Xu, Qing

2018-04-01

Accurate estimations of typhoon-level winds are highly desired over the western Pacific Ocean. A wind speed retrieval algorithm is used to retrieve the wind speeds within Super Typhoon Nepartak (2016) using 6.9- and 10.7-GHz brightness temperatures from the Japanese Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor on board the Global Change Observation Mission-Water 1 (GCOM-W1) satellite. The results show that the retrieved wind speeds clearly represent the intensification process of Super Typhoon Nepartak. A good agreement is found between the retrieved wind speeds and the Soil Moisture Active Passive wind speed product. The mean bias is 0.51 m/s, and the root-mean-square difference is 1.93 m/s between them. The retrieved maximum wind speeds are 59.6 m/s at 04:45 UTC on July 6 and 71.3 m/s at 16:58 UTC on July 6. The two results demonstrate good agreement with the results reported by the China Meteorological Administration and the Joint Typhoon Warning Center. In addition, Feng-Yun 2G (FY-2G) satellite infrared images, Feng-Yun 3C (FY-3C) microwave atmospheric sounder data, and AMSR2 brightness temperature images are also used to describe the development and structure of Super Typhoon Nepartak.

Application of a temperature-dependent fluorescent dye (Rhodamine B) to the measurement of radiofrequency radiation-induced temperature changes in biological samples.

PubMed

Chen, Yuen Y; Wood, Andrew W

2009-10-01

We have applied a non-contact method for studying the temperature changes produced by radiofrequency (RF) radiation specifically to small biological samples. A temperature-dependent fluorescent dye, Rhodamine B, as imaged by laser scanning confocal microscopy (LSCM) was used to do this. The results were calibrated against real-time temperature measurements from fiber optic probes, with a calibration factor of 3.4% intensity change degrees C(-1) and a reproducibility of +/-6%. This non-contact method provided two-dimensional and three-dimensional images of temperature change and distributions in biological samples, at a spatial resolution of a few micrometers and with an estimated absolute precision of around 1.5 degrees C, with a differential precision of 0.4 degree C. Temperature rise within tissue was found to be non-uniform. Estimates of specific absorption rate (SAR) from absorbed power measurements were greater than those estimated from rate of temperature rise, measured at 1 min intervals, probably because this interval is too long to permit accurate estimation of initial temperature rise following start of RF exposure. Future experiments will aim to explore this.

Temperature deviation index and elderly mortality in Japan.

PubMed

Lim, Youn-Hee; Reid, Colleen E; Honda, Yasushi; Kim, Ho

2016-07-01

Few studies have examined how the precedence of abnormal temperatures in previous neighboring years affects the population's health. In the present study, we attempted to quantify the health effects of abnormal weather patterns by creating a metric called the temperature deviation index (TDI) and estimated the effects of TDI on mortality in Japan. We used data from 47 prefectures in Japan to compute the TDI on days between May and September from 1966 to 2010. The TDI is a summed product of an indicator of absence of high temperatures in the neighboring years, and more weights were assigned to the years closest to the current year. To estimate the TDI effects on elderly mortality, we used generalized linear modeling with a Poisson distribution after adjusting for apparent temperature, barometric pressure, day of the week, and time trend. For each prefecture, we estimated the TDI effects and pooled the estimates to yield a national average for 1991-2010 in Japan. The estimated effects of TDI in middle- or high-latitude prefectures were greater than in low-latitude prefectures. The estimated national average of TDI effects was a 0.5 % (95 % confidence intervals [CI], 0.1, 1.0) increase in elderly mortality per 1-unit (around 1 standard deviation) increase in the TDI. The significant pooled estimation of TDI effects was mainly due to the TDI effects on summer days with moderate temperature (25th-49th percentile, mean temperature 22.9 °C): a 1.9 % (95 % CI, 1.1, 2.6) increase in elderly mortality per 1-unit increase in the TDI. However, TDI effects were insignificant in other temperature ranges. These findings suggest that elderly deaths increased on moderate temperature days in the summer that differed substantially from days during that time window in the neighboring years. Therefore, not only high temperature itself but also temperature deviation compared to previous years could be considered to be a risk factor for elderly mortality in the summer.

Studies on time of death estimation in the early post mortem period -- application of a method based on eyeball temperature measurement to human bodies.

PubMed

Kaliszan, Michał

2013-09-01

This paper presents a verification of the thermodynamic model allowing an estimation of the time of death (TOD) by calculating the post mortem interval (PMI) based on a single eyeball temperature measurement at the death scene. The study was performed on 30 cases with known PMI, ranging from 1h 35min to 5h 15min, using pin probes connected to a high precision electronic thermometer (Dostmann-electronic). The measured eye temperatures ranged from 20.2 to 33.1°C. Rectal temperature was measured at the same time and ranged from 32.8 to 37.4°C. Ambient temperatures which ranged from -1 to 24°C, environmental conditions (still air to light wind) and the amount of hair on the head were also recorded every time. PMI was calculated using a formula based on Newton's law of cooling, previously derived and successfully tested in comprehensive studies on pigs and a few human cases. Thanks to both the significantly faster post mortem decrease of eye temperature and a residual or nonexistent plateau effect in the eye, as well as practically no influence of body mass, TOD in the human death cases could be estimated with good accuracy. The highest TOD estimation error during the post mortem intervals up to around 5h was 1h 16min, 1h 14min and 1h 03min, respectively in three cases among 30, while for the remaining 27 cases it was not more than 47min. The mean error for all 30 cases was ±31min. All that indicates that the proposed method is of quite good precision in the early post mortem period, with an accuracy of ±1h for a 95% confidence interval. On the basis of the presented method, TOD can be also calculated at the death scene with the use of a proposed portable electronic device (TOD-meter). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Cherry blossom phenological data since the seventeenth century for Edo (Tokyo), Japan, and their application to estimation of March temperatures

NASA Astrophysics Data System (ADS)

Aono, Yasuyuki

2015-04-01

The changes in March mean temperatures in Edo (Tokyo), Japan, since the seventeenth century, were reconstructed using phenological data for the cherry blossoms of Prunus jamasakura deduced from old diaries and chronicles. The observations of the time of full blossoming and of cherry blossom viewing parties were acquired and used to construct a full-blossoming phenological data series for P. jamasakura. Phenological data from 207 of the years from 1601 to 1905 were used for this study. The reconstructed temperatures suggested the existence of two cold periods (the second half of the seventeenth century and the beginning of the nineteenth century), during which times the estimated March mean temperatures were about 4 °C and 5 °C, respectively. These two cold periods at Edo coincided with those reconstructed at Kyoto in previous studies. These cold periods coincided with two less extreme periods, the Maunder and Dalton minima, in the long-term solar variation cycle.

A data centred method to estimate and map changes in the full distribution of daily surface temperature

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2016-04-01

Characterizing how our climate is changing includes local information which can inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles or thresholds in distributions of variables such as daily surface temperature. Here we focus on these local changes and on a model independent method to transform daily observations into patterns of local climate change. Our method [1] is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of the distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. For temperature, changes in the distribution itself can yield robust results [2]. We demonstrate how the fundamental timescales of anthropogenic climate change limit the identification of societally relevant aspects of changes. We show that it is nevertheless possible to extract, solely from observations, some confident quantified assessments of change at certain thresholds and locations [3]. We demonstrate this approach using E-OBS gridded data [4] timeseries of local daily surface temperature from specific locations across Europe over the last 60 years. [1] Chapman, S. C., D. A. Stainforth, N. W. Watkins, On estimating long term local climate trends, Phil. Trans. Royal Soc., A,371 20120287 (2013) [2] Stainforth, D. A. S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, ERL 8, 034031 (2013) [3] Chapman, S. C., Stainforth, D. A., Watkins, N. W. Limits to the quantification of local climate change, ERL 10, 094018 (2015) [4] Haylock M. R. et al ., A European daily high-resolution gridded dataset of

Estimation of the Temperature-Dependent Nitrogen Solubility in Stainless Fe-Cr-Mn-Ni-Si-C Steel Melts During Processing

NASA Astrophysics Data System (ADS)

Wendler, Marco; Hauser, Michael; Sandig, Eckhard Frank; Volkova, Olena

2018-04-01

The influence of chemical composition, temperature, and pressure on the nitrogen solubility of various high alloy stainless steel grades, namely Fe-14Cr-(0.17-7.77)Mn-6Ni-0.5Si-0.03C [wt pct], Fe-15Cr-3Mn-4Ni-0.5Si-0.1C [wt pct], and Fe-19Cr-3Mn-4Ni-0.5Si-0.15C [wt pct], was studied in the melt. The temperature-dependent N-solubility was determined using an empirical approach proposed by Wada and Pehlke. The thus calculated N-concentrations overestimate the actual N-solubility of all the studied Fe-Cr-Mn-Ni-Si-C steel melts at a given temperature and pressure. Consequently, the calculation model has to be modified by Si and C because both elements are not recognized in the original equation. The addition of the 1st and 2nd order interaction parameters for Si and C to the model by Wada and Pehlke allows a precise estimation of the temperature-dependent nitrogen solubility in the liquid steel bath, and fits very well with the measured nitrogen concentrations during processing of the steels. Moreover, the N-solubility enhancing effect of Cr- and Mn-additions has been demonstrated.

Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy

DOE PAGES

Serbin, Shawn P.; Singh, Aditya; Desai, Ankur R.; ...

2015-06-11

To date, the utility of ecosystem and Earth system models (EESMs) has been limited by poor spatial and temporal representation of critical input parameters. For example, EESMs often rely on leaf-scale or literature-derived estimates for a key determinant of canopy photosynthesis, the maximum velocity of RuBP carboxylation (Vcmax, μmol m –2 s –1). Our recent work (Ainsworth et al., 2014; Serbin et al., 2012) showed that reflectance spectroscopy could be used to estimate Vcmax at the leaf level. Here, we present evidence that imaging spectroscopy data can be used to simultaneously predict Vcmax and its sensitivity to temperature (E V)more » at the canopy scale. In 2013 and 2014, high-altitude Airborne Visible/Infrared Imaging Spectroscopy (AVIRIS) imagery and contemporaneous ground-based assessments of canopy structure and leaf photosynthesis were acquired across an array of monospecific agroecosystems in central and southern California, USA. A partial least-squares regression (PLSR) modeling approach was employed to characterize the pixel-level variation in canopy V cmax (at a standardized canopy temperature of 30 °C) and E V, based on visible and shortwave infrared AVIRIS spectra (414–2447 nm). Our approach yielded parsimonious models with strong predictive capability for Vcmax (at 30 °C) and E V (R 2 of withheld data = 0.94 and 0.92, respectively), both of which varied substantially in the field (≥ 1.7 fold) across the sampled crop types. The models were applied to additional AVIRIS imagery to generate maps of V cmax and E V, as well as their uncertainties, for agricultural landscapes in California. The spatial patterns exhibited in the maps were consistent with our in-situ observations. As a result, these findings highlight the considerable promise of airborne and, by implication, space-borne imaging spectroscopy, such as the proposed HyspIRI mission, to map spatial and temporal variation in key drivers of photosynthetic metabolism in terrestrial

High Temperature Chemistry in the Columbia Accident Investigation

NASA Technical Reports Server (NTRS)

Jacobson, Nathan; Opila, Elizabeth; Tallant, David; Simpson, Regina

2004-01-01

Initial estimates on the temperature and conditions of the breach in Columbia's wing focused on analyses of the slag deposits. These deposits are complex mixtures of the reinforced carbon/carbon (RCC) constituents, insulation material, and wing structural materials. However it was possible to clearly discern melted/solidified Cerachrome(R) insulation, indicating the temperatures had exceeded 1760 C. Current research focuses on the carbon/carbon in the path from the breach. Carbon morphology indicates heavy oxidation and erosion. Raman spectroscopy yielded further temperature estimates. A technique developed at Sandia National Laboratories is based on crystallite size in carbon chars. Lower temperatures yield nanocrystalline graphite; whereas higher temperatures yield larger graphite crystals. By comparison to standards the temperatures on the recovered RCC fragments were estimated to have been greater than 2700 C.

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.

A simple temperature-based method to estimate heterogeneous frozen ground within a distributed watershed model

NASA Astrophysics Data System (ADS)

Follum, Michael L.; Niemann, Jeffrey D.; Parno, Julie T.; Downer, Charles W.

2018-05-01

Frozen ground can be important to flood production and is often heterogeneous within a watershed due to spatial variations in the available energy, insulation by snowpack and ground cover, and the thermal and moisture properties of the soil. The widely used continuous frozen ground index (CFGI) model is a degree-day approach and identifies frozen ground using a simple frost index, which varies mainly with elevation through an elevation-temperature relationship. Similarly, snow depth and its insulating effect are also estimated based on elevation. The objective of this paper is to develop a model for frozen ground that (1) captures the spatial variations of frozen ground within a watershed, (2) allows the frozen ground model to be incorporated into a variety of watershed models, and (3) allows application in data sparse environments. To do this, we modify the existing CFGI method within the gridded surface subsurface hydrologic analysis watershed model. Among the modifications, the snowpack and frost indices are simulated by replacing air temperature (a surrogate for the available energy) with a radiation-derived temperature that aims to better represent spatial variations in available energy. Ground cover is also included as an additional insulator of the soil. Furthermore, the modified Berggren equation, which accounts for soil thermal conductivity and soil moisture, is used to convert the frost index into frost depth. The modified CFGI model is tested by application at six test sites within the Sleepers River experimental watershed in Vermont. Compared to the CFGI model, the modified CFGI model more accurately captures the variations in frozen ground between the sites, inter-annual variations in frozen ground depths at a given site, and the occurrence of frozen ground.

Responding to bioterror concerns by increasing milk pasteurization temperature would increase estimated annual deaths from listeriosis.

PubMed

Stasiewicz, Matthew J; Martin, Nicole; Laue, Shelley; Gröhn, Yrjo T; Boor, Kathryn J; Wiedmann, Martin

2014-05-01

In a 2005 analysis of a potential bioterror attack on the food supply involving a botulinum toxin release into the milk supply, the authors recommended adopting a toxin inactivation step during milk processing. In response, some dairy processors increased the times and temperatures of pasteurization well above the legal minimum for high temperature, short time pasteurization (72 °C for 15 s), with unknown implications for public health. The present study was conducted to determine whether an increase in high temperature, short time pasteurization temperature would affect the growth of Listeria monocytogenes, a potentially lethal foodborne pathogen normally eliminated with proper pasteurization but of concern when milk is contaminated postpasteurization. L. monocytogenes growth during refrigerated storage was higher in milk pasteurized at 82 °C than in milk pasteurized at 72 °C. Specifically, the time lag before exponential growth was decreased and the maximum population density was increased. The public health impact of this change in pasteurization was evaluated using a quantitative microbial risk assessment of deaths from listeriosis attributable to consumption of pasteurized fluid milk that was contaminated postprocessing. Conservative estimates of the effect of pasteurizing all fluid milk at 82 °C rather than 72 °C are that annual listeriosis deaths from consumption of this milk would increase from 18 to 670, a 38-fold increase (8.7- to 96-fold increase, 5th and 95th percentiles). These results exemplify a situation in which response to a rare bioterror threat may have the unintended consequence of putting the public at increased risk of a known, yet severe harm and illustrate the need for a paradigm shift toward multioutcome risk benefit analyses when proposing changes to established food safety practices.

Geothermal Reservoir Temperatures in Southeastern Idaho using Multicomponent Geothermometry

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

Neupane, Ghanashyam; Mattson, Earl D.; McLing, Travis L.

Southeastern Idaho exhibits numerous warm springs, warm water from shallow wells, and hot water within oil and gas test wells that indicate a potential for geothermal development in the area. Although the area exhibits several thermal expressions, the measured geothermal gradients vary substantially (19 – 61 ºC/km) within this area, potentially suggesting a redistribution of heat in the overlying ground water from deeper geothermal reservoirs. We have estimated reservoir temperatures from measured water compositions using an inverse modeling technique (Reservoir Temperature Estimator, RTEst) that calculates the temperature at which multiple minerals are simultaneously at equilibrium while explicitly accounting for themore » possible loss of volatile constituents (e.g., CO2), boiling and/or water mixing. Compositions of a selected group of thermal waters representing southeastern Idaho hot/warm springs and wells were used for the development of temperature estimates. The temperature estimates in the the region varied from moderately warm (59 ºC) to over 175 ºC. Specifically, hot springs near Preston, Idaho resulted in the highest temperature estimates in the region.« less

Estimated phase transition and melting temperature of APTES self-assembled monolayer using surface-enhanced anti-stokes and stokes Raman scattering

NASA Astrophysics Data System (ADS)

Sun, Yingying; Yanagisawa, Masahiro; Kunimoto, Masahiro; Nakamura, Masatoshi; Homma, Takayuki

2016-02-01

A structure's temperature can be determined from the Raman spectrum using the frequency and the ratio of the intensities of the anti-Stokes and Stokes signals (the Ias/Is ratio). In this study, we apply this approach and an equation relating the temperature, Raman frequency, and Ias/Is ratio to in-situ estimation of the phase change point of a (3-aminopropyl)triethoxysilane self-assembled monolayer (APTES SAM). Ag nanoparticles were deposited on APTES to enhance the Raman signals. A time-resolved measurement mode was used to monitor the variation in the Raman spectra in situ. Moreover, the structural change in APTES SAM (from ordered to disordered structure) under heating was discussed in detail, and the phase change point (around 118 °C) was calculated.

RPM-WEBBSYS: A web-based computer system to apply the rational polynomial method for estimating static formation temperatures of petroleum and geothermal wells

NASA Astrophysics Data System (ADS)

Wong-Loya, J. A.; Santoyo, E.; Andaverde, J. A.; Quiroz-Ruiz, A.

2015-12-01

A Web-Based Computer System (RPM-WEBBSYS) has been developed for the application of the Rational Polynomial Method (RPM) to estimate static formation temperatures (SFT) of geothermal and petroleum wells. The system is also capable to reproduce the full thermal recovery processes occurred during the well completion. RPM-WEBBSYS has been programmed using advances of the information technology to perform more efficiently computations of SFT. RPM-WEBBSYS may be friendly and rapidly executed by using any computing device (e.g., personal computers and portable computing devices such as tablets or smartphones) with Internet access and a web browser. The computer system was validated using bottomhole temperature (BHT) measurements logged in a synthetic heat transfer experiment, where a good matching between predicted and true SFT was achieved. RPM-WEBBSYS was finally applied to BHT logs collected from well drilling and shut-in operations, where the typical problems of the under- and over-estimation of the SFT (exhibited by most of the existing analytical methods) were effectively corrected.

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

X-Ray Fluorescence to Estimate the Maximum Temperature Reached at Soil Surface during Experimental Slash-and-Burn Fires.

PubMed

Melquiades, Fábio L; Thomaz, Edivaldo L

2016-05-01

An important aspect for the evaluation of fire effects in slash-and-burn agricultural system, as well as in wildfire, is the soil burn severity. The objective of this study is to estimate the maximum temperature reached in real soil burn events using energy dispersive X-ray fluorescence (EDXRF) as an analytical tool, combined with partial least square (PLS) regression. Muffle-heated soil samples were used for PLS regression model calibration and two real slash-and-burn soils were tested as external samples in the model. It was possible to associate EDXRF spectra alterations to the maximum temperature reached in the heat affected soils with about 17% relative standard deviation. The results are promising since the analysis is fast, nondestructive, and conducted after the burn event, although local calibration for each type of burned soil is necessary. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Ice Surface Temperature Variability in the Polar Regions and the Relationships to 2 Meter Air Temperatures

NASA Astrophysics Data System (ADS)

Hoyer, J.; Madsen, K. S.; Englyst, P. N.

2017-12-01

Determining the surface and near surface air temperature from models or observations in the Polar Regions is challenging due to the extreme conditions and the lack of in situ observations. The errors in near surface temperature products are typically larger than for other regions of the world, and the potential for using Earth Observations is large. As part of the EU project, EUSTACE, we have developed empirical models for the relationship between the satellite observed skin ice temperatures and 2m air temperatures. We use the Arctic and Antarctic Sea and sea ice Surface Temperatures from thermal Infrared satellite sensors (AASTI) reanalysis to estimate daily surface air temperature over land ice and sea ice for the Arctic and the Antarctic. Large efforts have been put into collecting and quality controlling in situ observations from various data portals and research projects. The reconstruction is independent of numerical weather prediction models and thus provides an important alternative to modelled air temperature estimates. The new surface air temperature data record has been validated against more than 58.000 independent in situ measurements for the four surface types: Arctic sea ice, Greenland ice sheet, Antarctic sea ice and Antarctic ice sheet. The average correlations are 92-97% and average root mean square errors are 3.1-3.6°C for the four surface types. The root mean square error includes the uncertainty of the in-situ measurement, which ranges from 0.5 to 2°C. A comparison with ERA-Interim shows a consistently better performance of the satellite based air temperatures than the ERA-Interim for the Greenland ice sheet, when compared against observations not used in any of the two estimates. This is encouraging and demonstrates the values of these products. In addition, the procedure presented here works on satellite observations that are available in near real time and this opens up for a near real time estimation of the surface air temperature over

Core body temperature control by total liquid ventilation using a virtual lung temperature sensor.

PubMed

Nadeau, Mathieu; Micheau, Philippe; Robert, Raymond; Avoine, Olivier; Tissier, Renaud; Germim, Pamela Samanta; Vandamme, Jonathan; Praud, Jean-Paul; Walti, Herve

2014-12-01

In total liquid ventilation (TLV), the lungs are filled with a breathable liquid perfluorocarbon (PFC) while a liquid ventilator ensures proper gas exchange by renewal of a tidal volume of oxygenated and temperature-controlled PFC. Given the rapid changes in core body temperature generated by TLV using the lung has a heat exchanger, it is crucial to have accurate and reliable core body temperature monitoring and control. This study presents the design of a virtual lung temperature sensor to control core temperature. In the first step, the virtual sensor, using expired PFC to estimate lung temperature noninvasively, was validated both in vitro and in vivo. The virtual lung temperature was then used to rapidly and automatically control core temperature. Experimentations were performed using the Inolivent-5.0 liquid ventilator with a feedback controller to modulate inspired PFC temperature thereby controlling lung temperature. The in vivo experimental protocol was conducted on seven newborn lambs instrumented with temperature sensors at the femoral artery, pulmonary artery, oesophagus, right ear drum, and rectum. After stabilization in conventional mechanical ventilation, TLV was initiated with fast hypothermia induction, followed by slow posthypothermic rewarming for 1 h, then by fast rewarming to normothermia and finally a second fast hypothermia induction phase. Results showed that the virtual lung temperature was able to provide an accurate estimation of systemic arterial temperature. Results also demonstrate that TLV can precisely control core body temperature and can be favorably compared to extracorporeal circulation in terms of speed.

Prediction of the optimum hybridization conditions of dot-blot-SNP analysis using estimated melting temperature of oligonucleotide probes.

PubMed

Shiokai, Sachiko; Kitashiba, Hiroyasu; Nishio, Takeshi

2010-08-01

Although the dot-blot-SNP technique is a simple cost-saving technique suitable for genotyping of many plant individuals, optimization of hybridization and washing conditions for each SNP marker requires much time and labor. For prediction of the optimum hybridization conditions for each probe, we compared T (m) values estimated from nucleotide sequences using the DINAMelt web server, measured T (m) values, and hybridization conditions yielding allele-specific signals. The estimated T (m) values were comparable to the measured T (m) values with small differences of less than 3 degrees C for most of the probes. There were differences of approximately 14 degrees C between the specific signal detection conditions and estimated T (m) values. Change of one level of SSC concentrations of 0.1, 0.2, 0.5, and 1.0x SSC corresponded to a difference of approximately 5 degrees C in optimum signal detection temperature. Increasing the sensitivity of signal detection by shortening the exposure time to X-ray film changed the optimum hybridization condition for specific signal detection. Addition of competitive oligonucleotides to the hybridization mixture increased the suitable hybridization conditions by 1.8. Based on these results, optimum hybridization conditions for newly produced dot-blot-SNP markers will become predictable.

Updates to Enhanced Geothermal System Resource Potential Estimate

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

Augustine, Chad

The deep EGS electricity generation resource potential estimate maintained by the National Renewable Energy Laboratory was updated using the most recent temperature-at-depth maps available from the Southern Methodist University Geothermal Laboratory. The previous study dates back to 2011 and was developed using the original temperature-at-depth maps showcased in the 2006 MIT Future of Geothermal Energy report. The methodology used to update the deep EGS resource potential is the same as in the previous study and is summarized in the paper. The updated deep EGS resource potential estimate was calculated for depths between 3 and 7 km and is binned inmore » 25 degrees C increments. The updated deep EGS electricity generation resource potential estimate is 4,349 GWe. A comparison of the estimates from the previous and updated studies shows a net increase of 117 GWe in the 3-7 km depth range, due mainly to increases in the underlying temperature-at-depth estimates from the updated maps.« less

Use of CMIP3 simulations to estimate the changes of temperature indicators over France and Europe during the 21st century

NASA Astrophysics Data System (ADS)

Leboucher, V.; Couillaux, A.; Parey, S.; Fil, C.

2007-12-01

Projections of changes in temperature are essential to assess the impact of climate change on the energy supply sector as heating and cooling, energy demand highly depends on temperature. A selection of temperature indicators and their changes are examined for several simulations using SRES Emission Scenario A2 from the CMIP3 archive. We compare the present day simulated indicators to those in European Center for Medium-Range Weather Forecasts (ECMWF) ERA40 reanalysis The results are analysed for six areas over Europe and two time periods during the 21st century. We focus our study on changes in number and duration of hot and cold events and on changes in heating degree-days and cooling degree-days, which are commonly used to estimate the weather-related variations in energy consumption. Results are presented for the different models with some comparisons to the regional model simulations from the European PRUDENCE project to evaluate uncertainties.

Synergistically combining Optical and Thermal radiative transfer modelswithin the EO-LDAS data assimilation framework to estimate land surfaceand component temperatures from MODIS and Sentinel-3

NASA Astrophysics Data System (ADS)

Timmermans, J.; Gomez-Dans, J. L.; Verhoef, W.; Tol, C. V. D.; Lewis, P.

2017-12-01

Evapotranspiration (ET) cannot be directly measured from space. Instead it relies on modelling approaches that use several land surface parameters (LSP), LAI and LST, in conjunction with meteorological parameters. Such a modelling approach presents two caveats: the validity of the model, and the consistency between the different input parameters. Often this second step is not considered, ignoring that without good inputs no decent output can provided. When LSP- dynamics contradict each other, the output of the model cannot be representative of reality. At present however, the LSPs used in large scale ET estimations originate from different single-sensor retrieval-approaches and even from different satellite sensors. In response, the Earth Observation Land Data Assimilation System (EOLDAS) was developed. EOLDAS uses a multi-sensor approach to couple different satellite observations/types to radiative transfer models (RTM), consistently. It is therefore capable of synergistically estimating a variety of LSPs. Considering that ET is most sensitive to the temperatures of the land surface (components), the goal of this research is to expand EOLDAS to the thermal domain. This research not only focuses on estimating LST, but also on retrieving (soil/vegetation, Sunlit/shaded) component temperatures, to facilitate dual/quad-source ET models. To achieve this, The Soil Canopy Observations of Photosynthesis and Energy (SCOPE) model was integrated into EOLDAS. SCOPE couples key-parameters to key-processes, such as photosynthesis, ET and optical/thermal RT. In this research SCOPE was also coupled to MODTRAN RTM, in order to estimate BOA component temperatures directly from TOA observations. This paper presents the main modelling steps of integrating these complex models into an operational platform. In addition it highlights the actual retrieval using different satellite observations, such as MODIS and Sentinel-3, and meteorological variables from the ERA-Interim.

Capital cost estimate

NASA Technical Reports Server (NTRS)

1975-01-01

The capital cost estimate for the nuclear process heat source (NPHS) plant was made by: (1) using costs from the current commercial HTGR for electricity production as a base for items that are essentially the same and (2) development of new estimates for modified or new equipment that is specifically for the process heat application. Results are given in tabular form and cover the total investment required for each process temperature studied.

Implementation of a subcanopy solar radiation model on a forested headwater basin in the Southern Appalachians to estimate riparian canopy density and stream insolation for stream temperature models

NASA Astrophysics Data System (ADS)

Belica, L.; Petras, V.; Iiames, J. S., Jr.; Caldwell, P.; Mitasova, H.; Nelson, S. A. C.

2016-12-01

Water temperature is a key aspect of water quality and understanding how the thermal regimes of forested headwater streams may change in response to climatic and land cover changes is increasingly important to scientists and resource managers. In recent years, the forested mountain watersheds of the Southeastern U.S. have experienced changing climatic patterns as well as the loss of a keystone riparian tree species and anticipated hydrologic responses include lower summer stream flows and decreased stream shading. Solar radiation is the main source of thermal energy to streams and a key parameter in heat-budget models of stream temperature; a decrease in flow volume combined with a reduction in stream shading during summer have the potential to increase stream temperatures. The high spatial variability of forest canopies and the high spatio-temporal variability in sky conditions make estimating the solar radiation reaching small forested headwater streams difficult. The Subcanopy Solar Radiation Model (SSR) (Bode et al. 2014) is a GIS model that generates high resolution, spatially explicit estimates of solar radiation by incorporating topographic and vegetative shading with a light penetration index derived from leaf-on airborne LIDAR data. To evaluate the potential of the SSR model to provide estimates of stream insolation to parameterize heat-budget models, it was applied to the Coweeta Basin in the Southern Appalachians using airborne LIDAR (NCALM 2009, 1m resolution). The LIDAR derived canopy characteristics were compared to current hyperspectral images of the canopy for changes and the SSR estimates of solar radiation were compared with pyranometer measurements of solar radiation at several subcanopy sites during the summer of 2016. Preliminary results indicate the SSR model was effective in identifying variations in canopy density and light penetration, especially in areas associated with road and stream corridors and tree mortality. Current LIDAR data and

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.

Occurrence of pristine aerosol environments on a polluted planet

PubMed Central

Hamilton, Douglas S.; Lee, Lindsay A.; Pringle, Kirsty J.; Reddington, Carly L.; Spracklen, Dominick V.; Carslaw, Kenneth S.

2014-01-01

Natural aerosols define a preindustrial baseline state from which the magnitude of anthropogenic aerosol effects on climate are calculated and are a major component of the large uncertainty in anthropogenic aerosol−cloud radiative forcing. This uncertainty would be reduced if aerosol environments unperturbed by air pollution could be studied in the present-day atmosphere, but the pervasiveness of air pollution makes identification of unperturbed regions difficult. Here, we use global model simulations to define unperturbed aerosol regions in terms of two measures that compare 1750 and 2000 conditions—the number of days with similar aerosol concentrations and the similarity of the aerosol response to perturbations in model processes and emissions. The analysis shows that the aerosol system in many present-day environments looks and behaves like it did in the preindustrial era. On a global annual mean, unperturbed aerosol regions cover 12% of the Earth (16% of the ocean surface and 2% of the land surface). There is a strong seasonal variation in unperturbed regions of between 4% in August and 27% in January, with the most persistent conditions occurring over the equatorial Pacific. About 90% of unperturbed regions occur in the Southern Hemisphere, but in the Northern Hemisphere, unperturbed conditions are transient and spatially patchy. In cloudy regions with a radiative forcing relative to 1750, model results suggest that unperturbed aerosol conditions could still occur on a small number of days per month. However, these environments are mostly in the Southern Hemisphere, potentially limiting the usefulness in reducing Northern Hemisphere forcing uncertainty. PMID:25512511

Occurrence of pristine aerosol environments on a polluted planet.

PubMed

Hamilton, Douglas S; Lee, Lindsay A; Pringle, Kirsty J; Reddington, Carly L; Spracklen, Dominick V; Carslaw, Kenneth S

2014-12-30

Natural aerosols define a preindustrial baseline state from which the magnitude of anthropogenic aerosol effects on climate are calculated and are a major component of the large uncertainty in anthropogenic aerosol-cloud radiative forcing. This uncertainty would be reduced if aerosol environments unperturbed by air pollution could be studied in the present--day atmosphere, but the pervasiveness of air pollution makes identification of unperturbed regions difficult. Here, we use global model simulations to define unperturbed aerosol regions in terms of two measures that compare 1750 and 2000 conditions-the number of days with similar aerosol concentrations and the similarity of the aerosol response to perturbations in model processes and emissions. The analysis shows that the aerosol system in many present-day environments looks and behaves like it did in the preindustrial era. On a global annual mean, unperturbed aerosol regions cover 12% of the Earth (16% of the ocean surface and 2% of the land surface). There is a strong seasonal variation in unperturbed regions of between 4% in August and 27% in January, with the most persistent conditions occurring over the equatorial Pacific. About 90% of unperturbed regions occur in the Southern Hemisphere, but in the Northern Hemisphere, unperturbed conditions are transient and spatially patchy. In cloudy regions with a radiative forcing relative to 1750, model results suggest that unperturbed aerosol conditions could still occur on a small number of days per month. However, these environments are mostly in the Southern Hemisphere, potentially limiting the usefulness in reducing Northern Hemisphere forcing uncertainty.

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 and application of the thermodynamic properties of aqueous phenanthrene and isomers of methylphenanthrene at high temperature

NASA Astrophysics Data System (ADS)

Dick, Jeffrey M.; Evans, Katy A.; Holman, Alex I.; Jaraula, Caroline M. B.; Grice, Kliti

2013-12-01

Estimates of standard molal Gibbs energy (ΔGf°) and enthalpy (ΔHf°) of formation, entropy (S°), heat capacity (CP°) and volume (V°) at 25 °C and 1 bar of aqueous phenanthrene (P) and 1-, 2-, 3-, 4- and 9-methylphenanthrene (1-MP, 2-MP, 3-MP, 4-MP, 9-MP) were made by combining reported standard-state properties of the crystalline compounds, solubilities and enthalpies of phenanthrene and 1-MP, and relative Gibbs energies, enthalpies and entropies of aqueous MP isomers from published quantum chemical simulations. The calculated properties are consistent with greater stabilities of the β isomers (2-MP and 3-MP) relative to the α isomers (1-MP and 9-MP) at 25 °C. However, the metastable equilibrium values of the abundance ratios 2-MP/1-MP (MPR) and (2-MP + 3-MP)/(1-MP + 9-MP) (MPI-3) decrease with temperature, becoming <1 at ∼375-455 °C. The thermodynamic model is consistent with observations of reversals of these organic maturity parameters at high temperature in hydrothermal and metamorphic settings. Application of the model to data reported for the Paleoproterozoic Here’s Your Chance (HYC) Pb-Zn-Ag ore deposit (McArthur River, Northern Territory, Australia) indicates a likely effect of high-temperature equilibration on reported values of MPR and MPI-3, but this finding is contingent on the location within the deposit. If metastable equilibrium holds, a third aromatic maturity ratio, 1.5 × (2-MP + 3-MP)/(P + 1-MP + 9-MP) (MPI-1), can be used as a proxy for oxidation potential. Values of logaH2aq determined from data reported for HYC and for a sequence of deeply buried source rocks are indicative of more reducing conditions at a given temperature than those inferred from data reported for two sets of samples exposed to contact or regional metamorphism. These results are limiting-case scenarios for the modeled systems that do not account for effects of non-ideal mixing or kinetics, or external sources or transport of the organic matter. Nevertheless

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.

Triaxial thermopile array geo-heat-flow sensor

DOEpatents

Carrigan, C.R.; Hardee, H.C.; Reynolds, G.D.; Steinfort, T.D.

1990-01-01

A triaxial thermopile array geothermal heat flow sensor is designed to measure heat flow in three dimensions in a reconstituted or unperturbed subsurface regime. Heat flow can be measured in conductive or permeable convective media. The sensor may be encased in protective pvc tubing and includes a plurality of thermistors and an array of heat flow transducers produce voltage proportional to heat flux along the subsurface regime and permit direct measurement of heat flow in the subsurface regime. The presence of the thermistor array permits a comparison to be made between the heat flow estimates obtained from the transducers and heat flow calculated using temperature differences and Fourier's Law. The device is extremely sensitive with an accuracy of less than 0.1 Heat Flow Units (HFU) and may be used for long term readings. 6 figs.

Triaxial thermopile array geo-heat-flow sensor

DOEpatents

Carrigan, Charles R.; Hardee, Harry C.; Reynolds, Gerald D.; Steinfort, Terry D.

1992-01-01

A triaxial thermopile array geothermal heat flow sensor is designed to measure heat flow in three dimensions in a reconstituted or unperturbed subsurface regime. Heat flow can be measured in conductive or permeable convective media. The sensor may be encased in protective pvc tubing and includes a plurality of thermistors and an array of heat flow transducers arranged in a vertical string. The transducers produce voltage proportional to heat flux along the subsurface regime and permit direct measurement of heat flow in the subsurface regime. The presence of the thermistor array permits a comparison to be made between the heat flow estimates obtained from the transducers and heat flow calculated using temperature differences and Fourier's Law. The device is extremely sensitive with an accuracy of less than 0.1 Heat Flow Units (HFU) and may be used for long term readings.

Summary of Temperature Data Collected to Improve Emergence Timing Estimates for Chum and Fall Chinook Salmon in the Lower Columbia River, 1998-2004 Progress Report.

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

Arntzen, E.; Geist, D.; Hanrahan, T.

2005-10-01

From 1999 through 2004, Pacific Northwest National Laboratory collected temperature data from within chum and fall Chinook salmon spawning gravels and the overlying river at 21 locations in the Ives Island area approximately 5 km downstream from Bonneville Dam. Sample locations included areas where riverbed temperatures were elevated, potentially influencing alevin development and emergence timing. The study objectives were to (1) collect riverbed and river temperature data each year from the onset of spawning (October) to the end of emergence (June) and (2) provide those data in-season to fisheries management agencies to assist with fall Chinook and chum salmon emergencemore » timing estimates. Three systems were used over the life of the study. The first consisted of temperature sensors deployed inside piezometers that were screened to the riverbed or the river within chum and fall Chinook salmon spawning areas. These sensors required direct access by staff to download data and were difficult to recover during high river discharge. The second system consisted of a similar arrangement but with a wire connecting the thermistor to a data logger attached to a buoy at the water surface. This system allowed for data retrieval at high river discharge but proved relatively unreliable. The third system consisted of temperature sensors installed in piezometers such that real-time data could be downloaded remotely via radio telemetry. After being downloaded, data were posted hourly on the Internet. Several times during the emergence season of each year, temperature data were downloaded manually and provided to management agencies. During 2003 and 2004, the real-time data were made available on the Internet to assist with emergence timing estimates. Examination of temperature data reveals several important patterns. Piezometer sites differ in the direction of vertical flow between surface and subsurface water. Bed temperatures in upwelling areas are more stable during

Reevaluation of mid-Pliocene North Atlantic sea surface temperatures

USGS Publications Warehouse

Robinson, Marci M.; Dowsett, Harry J.; Dwyer, Gary S.; Lawrence, Kira T.

2008-01-01

Multiproxy temperature estimation requires careful attention to biological, chemical, physical, temporal, and calibration differences of each proxy and paleothermometry method. We evaluated mid-Pliocene sea surface temperature (SST) estimates from multiple proxies at Deep Sea Drilling Project Holes 552A, 609B, 607, and 606, transecting the North Atlantic Drift. SST estimates derived from faunal assemblages, foraminifer Mg/Ca, and alkenone unsaturation indices showed strong agreement at Holes 552A, 607, and 606 once differences in calibration, depth, and seasonality were addressed. Abundant extinct species and/or an unrecognized productivity signal in the faunal assemblage at Hole 609B resulted in exaggerated faunal-based SST estimates but did not affect alkenone-derived or Mg/Ca–derived estimates. Multiproxy mid-Pliocene North Atlantic SST estimates corroborate previous studies documenting high-latitude mid-Pliocene warmth and refine previous faunal-based estimates affected by environmental factors other than temperature. Multiproxy investigations will aid SST estimation in high-latitude areas sensitive to climate change and currently underrepresented in SST reconstructions.

A one- and two-layer model for estimating evapotranspiration with remotely sensed surface temperature and ground-based meteorological data over partial canopy cover

NASA Technical Reports Server (NTRS)

Kustas, William P.; Choudhury, Bhaskar J.; Kunkel, Kenneth E.

1989-01-01

Surface-air temperature differences are commonly used in a bulk resistance equation for estimating sensible heat flux (H), which is inserted in the one-dimensional energy balance equation to solve for the latent heat flux (LE) as a residual. Serious discrepancies between estimated and measured LE have been observed for partial-canopy-cover conditions, which are mainly attributed to inappropriate estimates of H. To improve the estimates of H over sparse canopies, one- and two-layer resistance models that account for some of the factors causing poor agreement are developed. The utility of the two models is tested with remotely sensed and micrometeorological data for a furrowed cotton field with 20 percent cover and a dry soil surface. It is found that the one-layer model performs better than the two-layer model when a theoretical bluff-body correction for heat transfer is used instead of an empirical adjustment; otherwise, the two-layer model is better.

Performance of MODIS satellite and mesoscale model based land surface temperature for soil moisture deficit estimation using Neural Network

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Petropoulos, George P.; Gupta, Manika; Islam, Tanvir

2015-04-01

Soil Moisture Deficit (SMD) is a key variable in the water and energy exchanges that occur at the land-surface/atmosphere interface. Monitoring SMD is an alternate method of irrigation scheduling and represents the use of the suitable quantity of water at the proper time by combining measurements of soil moisture deficit. In past it is found that LST has a strong relation to SMD, which can be estimated by MODIS or numerical weather prediction model such as WRF (Weather Research and Forecasting model). By looking into the importance of SMD, this work focused on the application of Artificial Neural Network (ANN) for evaluating its capabilities towards SMD estimation using the LST data estimated from MODIS and WRF mesoscale model. The benchmark SMD estimated from Probability Distribution Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the calibration and validation experiments. The performances between observed and simulated SMD are assessed in terms of the Nash-Sutcliffe Efficiency (NSE), the Root Mean Square Error (RMSE) and the percentage of bias (%Bias). The application of the ANN confirmed a high capability WRF and MODIS LST for prediction of SMD. Performance during the ANN calibration and validation showed a good agreement between benchmark and estimated SMD with MODIS LST information with significantly higher performance than WRF simulated LST. The work presented showed the first comprehensive application of LST from MODIS and WRF mesoscale model for hydrological SMD estimation, particularly for the maritime climate. More studies in this direction are recommended to hydro-meteorological community, so that useful information will be accumulated in the technical literature domain for different geographical locations and climatic conditions. Keyword: WRF, Land Surface Temperature, MODIS satellite, Soil Moisture Deficit, Neural Network

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

Estimating stratospheric temperature trends using satellite microwave radiances

NASA Technical Reports Server (NTRS)

Hudson, Robert D.; Newman, Paul A.; Schoeberl, Mark R.

1990-01-01

The objective was to evaluate and intercompare stratospheric temperatures using Microwave Sounding Unit (MSU) data as a basis data set. The MSU, aboard the NOAA polar orbiter satellite series, provides twice daily global coverage over a layer (50-150 mb) at approximately a (170km)(exp 2) resolution. Conventional data sets will be compared to the satellite data in the lower stratosphere in order to assess their quality for trend computations.

A Calibration-Free Laser-Induced Breakdown Spectroscopy (CF-LIBS) Quantitative Analysis Method Based on the Auto-Selection of an Internal Reference Line and Optimized Estimation of Plasma Temperature.

PubMed

Yang, Jianhong; Li, Xiaomeng; Xu, Jinwu; Ma, Xianghong

2018-01-01

The quantitative analysis accuracy of calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is severely affected by the self-absorption effect and estimation of plasma temperature. Herein, a CF-LIBS quantitative analysis method based on the auto-selection of internal reference line and the optimized estimation of plasma temperature is proposed. The internal reference line of each species is automatically selected from analytical lines by a programmable procedure through easily accessible parameters. Furthermore, the self-absorption effect of the internal reference line is considered during the correction procedure. To improve the analysis accuracy of CF-LIBS, the particle swarm optimization (PSO) algorithm is introduced to estimate the plasma temperature based on the calculation results from the Boltzmann plot. Thereafter, the species concentrations of a sample can be calculated according to the classical CF-LIBS method. A total of 15 certified alloy steel standard samples of known compositions and elemental weight percentages were used in the experiment. Using the proposed method, the average relative errors of Cr, Ni, and Fe calculated concentrations were 4.40%, 6.81%, and 2.29%, respectively. The quantitative results demonstrated an improvement compared with the classical CF-LIBS method and the promising potential of in situ and real-time application.

Estimate of temperature change due to ice and snow accretion in the boreal forest regions