Surface Temperature Mapping of a Metal Plate using Ultrasound-Guided Wave Technique

Surface temperature mapping is crucial for the monitoring and control of an object of interest, such as furnace, reactor pipes carrying hot fluids, or a component under a temperature dependant process. While the use of waveguides for temperature measurement is well documented in literature, the attachment of the waveguide to a metallic component poses challenges. These include the relationship between the local waveguide temperature and that of the metal component; and wave leakage into the component. In this paper, the authors study the propagation of Shear Horizontal (SH) guided wave in a strip waveguide and its interaction with the notch embodiments in the waveguide. The effects of the type of notch and its depth on the SH mode characteristics are investigated through simulation studies. The mode of attachment of the waveguide to the metal component is by means a slot made in the component. The area of contact between the waveguide and metal component is optimized such that there is minimum wave leakage into the bulk material. Based on the simulation results, a waveguide strip is fabricated and used to monitor the local surface temperature of a test metal component. The waveguide is calibrated by correlating the time of flight shift in the waveforms against reference temperature values. Thereafter, the instantaneous temperature of the metal component is determined from the calibration equations. A set of experimental trials are performed to check for repeatability. The experiments are conducted in near steady-state conditions for better accuracy in the measurements.

Evaluation of Multiple Methods for the Production of Continuous Evapotranspiration Estimates from TIR Remote Sensing

Continuous daily estimates of evapotranspiration (ET) spatially distributed at plot scale are required to monitor the water loss and manage crop irrigation needs. Remote sensing approaches in the thermal infrared (TIR) domain are relevant to assess actual ET and soil moisture status but due to lengthy return intervals and cloud cover, data acquisition is not continuous over time. This study aims to assess the performances of 6 commonly used as well as two new reference quantities including rainfall as an index of soil moisture availability to reconstruct seasonal ET from sparse estimates and as a function of the revisit frequency. In a first step, instantaneous in situ eddy-covariance flux tower data collected over multiple ecosystems and climatic areas were used as a proxy for perfect retrievals on satellite overpass dates. In a second step, instantaneous estimations at the time of satellite overpass were produced using the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) energy balance model in order to evaluate the errors concurrent to the use of an energy balance model simulating the instantaneous IRT products from the local surface temperature. Significant variability in the performances from site to site was observed particularly for long revisit frequencies over 8 days, suggesting that the revisit frequency necessary to achieve accurate estimates of ET via temporal upscaling needs to be fewer than 8 days whatever the reference quantity used. For shorter return interval, small differences among the interpolation techniques and reference quantities were found. At the seasonal scale, very simple methods using reference quantities such as the global radiation or clear sky radiation appeared relevant and robust against long revisit frequencies. For infra-seasonal studies targeting stress detection and irrigation management, taking the amount of precipitation into account seemed necessary, especially to avoid the underestimation of ET over cloudy days during a long period without data acquisitions.

A full relativistic thin disc - the physics of the plunging region and the value of the stress at the ISCO

The widely used Novikov-Thorne relativistic thin disc equations are only valid down to the radius of the innermost-stable circular orbit (ISCO). This leads to an undetermined boundary condition at the ISCO, known as the inner stress of the disc, which sets the luminosity of the disc at the ISCO and introduces considerable ambiguity in accurately determining the mass, spin and accretion rate of black holes from observed spectra. We resolve this ambiguity by self-consistently extending the relativistic disc solution through the ISCO to the black hole horizon by calculating the inspiral of an average disc particle subject to turbulent disc forces, using a new particle-in-disc technique. Traditionally it has been assumed that the stress at the ISCO is zero, with material plunging approximately radially into the black hole at close to the speed of light. We demonstrate that in fact the inspiral is less severe, with several (∼4 − 17) orbits completed before the horizon. This leads to a small non-zero stress and luminosity at and inside the ISCO, with a local surface temperature at the ISCO between ∼0.15 − 0.3 times the maximum surface temperature of the disc, in the case where no dynamically important net magnetic field is present. For a range of disc parameters we calculate the value of the inner stress/surface temperature, which is required when fitting relativistic thin disc models to observations. We resolve a problem in relativistic slim disc models in which turbulent heating becomes inaccurate and falls to zero inside the plunging region.

Isotopes of molecular nitrogen, oxygen, and argon in the South Pole ice core document local and global climate change through the last deglaciation.

<p>Ice core gas records are an invaluable paleoclimatic archive. The three most abundant gases in air, nitrogen (N<sub>2</sub>), oxygen (O<sub>2</sub>), and argon (Ar), provide paleoclimatic information about both global and regional processes including tropical rainfall patterns and local surface temperature changes. We present a large dataset of elemental and isotopic ratios of N<sub>2</sub>, O<sub>2</sub>, and Ar (O<sub>2</sub>/N<sub>2</sub>, Ar/N<sub>2</sub>, δ<sup>15</sup>N, δ<sup>18</sup>O, & δ<sup>40</sup>Ar) from the South Pole Ice Core between 0 – 52,000 yr BP, with a focus on high precision δ<sup>15</sup>N and δ<sup>40</sup>Ar measurements between 5,000 – 32,000 yr BP. The unprecedented precision of our measurements allows us to use δ<sup>15</sup>N<sub>excess </sub>(= δ<sup>15</sup>N - δ<sup>40</sup>Ar/4) to reconstruct past temperature change at the South Pole. Although this proxy has been widely applied in Greenland, this is the first time it has been successfully applied to Antarctic ice and provides a valuable independent check on the more traditional water isotopes temperature proxy. We find good agreement between the two during the relatively stable climate of the glacial period and the Holocene. However the temperature reconstructions diverge during the deglaciation. We present several hypotheses that could explain the discrepancy and look to other emerging ice core temperature proxies to support our interpretation.</p>

Climate velocities and lagged species elevational shifts in mountain ranges

Mountain ranges support concentrations of climate-endangered endemic species, and are potential refugia for species retreating from the lowlands under anthropogenic climate change. Predicting the outcome for biodiversity requires knowledge of whether species are shifting uphill at the same rate as temperature isotherms (i.e. whether they are successfully tracking the velocity of climatic changes)1. Here, we provide a global assessment of the velocity of climate change in mountain ranges: applying thermal dynamic theory, deriving moist adiabatic lapse rates (MALR) using local surface temperature and water vapor. MALR varied substantially around the world, from 3 to 9°C cooling per km elevation increase. Consider the rate of terrestrial surface warming from 1971 to 2015, 24 regions can be identified as exhibiting high velocities where the isotherms have shifted more than one standard deviation of the global mean value (> 8.45 m yr-1). High velocities are typically found in relatively dry parts of the world, but also occur in wet regions with low lapse rates, such as in Northern Sumatra, Western Guiana Shield, Northern Andes, Costa Rica, Nepal, and Madagascar. Analysis of biodiversity data in relation to mountain-specific velocities revealed more cases of tracking between species and isotherms than previously suggested2 and more likely occurred at lower climate velocity. Nevertheless, upslope migrations of montane species have generally been lagging behind climate velocity. Such lags could continue to effect change even if the climate were to stabilize immediately. Reducing emissions would be expected to minimize lags, as well as slow the velocities of warming and required responses everywhere.

Axisymmetric Hadley Cell Theory with a Fixed Tropopause Temperature Rather than Height

Axisymmetric Hadley cell theory has traditionally assumed that the tropopause height (Ht) is uniform and unchanged from its radiative–convective equilibrium (RCE) value by the cells’ emergence. Recent studies suggest that the tropopause temperature (Tt), not height, is nearly invariant in RCE, which would require appreciable meridional variations in Ht. Here, we derive modified expressions of axisymmetric theory by assuming a fixed Tt and compare the results to their fixed-Ht counterparts. If Tt and the depth-averaged lapse rate are meridionally uniform, then at each latitude Ht varies linearly with the local surface temperature, altering the diagnosed gradient-balanced zonal wind at the tropopause appreciably (up to tens of meters per second) but the minimal Hadley cell extent predicted by Hide’s theorem only weakly (≲1°) under standard annual-mean and solsticial forcings. A uniform Tt alters the thermal field required to generate an angular-momentum-conserving Hadley circulation, but these changes and the resulting changes to the equal-area model solutions for the cell edges again are modest (<10%). In numerical simulations of latitude-by-latitude RCE under annual-mean forcing using a single-column model, assuming a uniform Tt is reasonably accurate up to the midlatitudes, and the Hide’s theorem metrics are again qualitatively insensitive to the tropopause definition. However imperfectly axisymmetric theory portrays the Hadley cells in Earth’s macroturbulent atmosphere, evidently its treatment of the tropopause is not an important error source.

Contribution of clouds radiative forcing to the local surface temperature variability

<p>The local contribution of clouds to the surface energy balance and temperature variability is an important topic in order to apprehend how this intake affects local climate variability and extreme events, how this contribution varies from one place to another, and how it evolves in a warming climate. The scope of this study is to understand how clouds impact temperature variability, to quantify their contribution, and to compare their effects to other surface processes. To do so, we develop a method to estimate the different terms that control temperature variability at the surface (∂T<sub>2m</sub> /∂t) by using this equation: <strong>∂T<sub>2m</sub> /∂t=R+HA+HG+Adv</strong> where R is the radiation that is separated into the cloud term (R<sub>cloud</sub>) and the clear sky one (R<sub>CS</sub>), HA the atmospheric heat exchange, HG the ground heat exchange, and Adv the advection. These terms are estimated hourly, almost only using direct measurements from SIRTA-ReOBS dataset (an hourly long-term multi-variables dataset retrieved from SIRTA, an observatory located in a semi-urban area 20-km South-West of Paris; Chiriaco et al., 2019) for a five-years period. The method gives good results for the hourly temperature variability, with a 0.8 correlation coefficient and a weak residual term between left part (directly measured) and right part of the equation.</p><p>A bagged decision trees analysis of this equation shows that R<sub>CS</sub> dominates temperature variability during daytime and is mainly modulated by cloud radiative effect (R<sub>cloud</sub>). During nighttime, the bagged decision trees analysis determines that R<sub>cloud</sub> is the term controlling temperature changes. When a diurnal cycle analysis (split into seasons) is performed for each term, HA becomes an important negative modulator in the late afternoon, chiefly in spring and summer, when evaporation and thermal conduction are increased. In contrast, HG and Adv terms do not play an essential role on temperature variability at this temporal scale and their contribution is barely considerable in the one-hour variability, but still they remain necessary in order to obtain the best coefficient estimator between the directly measured observations and the method estimated. All terms except advection have a marked monthly-hourly cycle.</p><p>Next steps consist in characterize the types of clouds and study their physical properties corresponding to the cases where R<sub>cloud</sub> is significant, using the Lidar profiles also available in the SIRTA-ReOBS dataset.</p>

How large does a large ensemble need to be?

Initial-condition large ensembles with ensemble sizes ranging from 30 to 100 members have become a commonly used tool to quantify the forced response and internal variability in various components of the climate system. However, there is no consensus on the ideal or even sufficient ensemble size for a large ensemble. Here, we introduce an objective method to estimate the required ensemble size that can be applied to any given application and demonstrate its use on the examples of global mean surface temperature, local surface temperature and precipitation and variability in the ENSO region and central America. Where possible, we base our estimate of the required ensemble size on the pre-industrial control simulation, which is available for every model. First, we determine how much of an available ensemble size is interpretable without a substantial impact of resampling ensemble members. Then, we show that more ensemble members are needed to quantify variability than the forced response, with the largest ensemble sizes needed to detect changes in internal variability itself. Finally, we highlight that the required ensemble size depends on both the acceptable error to the user and the studied quantity.

Near Critical Carbon Dioxide Characteristics of Heat Transfer Processes in Microchannels

Convective heat transfer of CO2 flows near the critical condition in a 300 μm hydraulic diameter microchannel was visualized and measured. Flow patterns of the gas, liquid, and supercritical phases are presented and discussed. An experimental rig and a microfluidic device were designed and constructed to enable precise control and measurements of temperature, pressure, and mass flux. Heaters and resistive temperature detectors (RTDs) were formed on the microchannel wall to provide heating power and to measure local surface temperature. Flow patterns for the near-critical condition of CO2 were visualized, and local heat transfer coefficient (HTC) of 4.5, 6.1, and 150 kW/m2K were measured, for gas supercritical and liquid cases, respectively. It was observed that there is a distinct difference in flow and heat transfer patterns of different phases near the critical point, which leads to the deviation of the HTC. Also, CO2 presents high HTC coefficients for supercritical and boiling conditions that make it a viable option as thermal fluid for different micro scale applications.

The Nonradiative Effect Dominates Local Surface Temperature Change Caused by Afforestation in China

China is several decades into large-scale afforestation programs to help address significant ecological and environmental degradation, with further afforestation planned for the future. However, the biophysical impact of afforestation on local surface temperature remains poorly understood, particularly in midlatitude regions where the importance of the radiative effect driven by albedo and the nonradiative effect driven by energy partitioning is uncertain. To examine this issue, we investigated the local impact of afforestation by comparing adjacent forest and open land pixels using satellite observations between 2001 and 2012. We attributed local surface temperature change between adjacent forest and open land to radiative and nonradiative effects over China based on the Intrinsic Biophysical Mechanism (IBM) method. Our results reveal that forest causes warming of 0.23°C (±0.21°C) through the radiative effect and cooling of −0.74°C (±0.50°C) through the nonradiative effect on local surface temperature compared with open land. The nonradiative effect explains about 79% (±16%) of local surface temperature change between adjacent forest and open land. The contribution of the nonradiative effect varies with forest and open land types. The largest cooling is achieved by replacing grasslands or rain-fed croplands with evergreen tree types. Conversely, converting irrigated croplands to deciduous broadleaf forest leads to warming. This provides new guidance on afforestation strategies, including how these should be informed by local conditions to avoid amplifying climate-related warming.