Temperature Standard Deviation Research Articles

Temperature difference relationship among precipitation, dry days, and spells in Turkey

Strong logical relationships exist between temperature difference and hydro-meteorological variables such as precipitation, dry days, and dry spells. These relationships can be used for knowing how the differences of total and top 10% heavy precipitations, dry days, and dry spells will change with respect to temperature differences? Here, daily precipitation and temperature records over Turkey are considered from 1971 to 2010, inclusive. First 30-year (1971–2000) data are used for training for temperature difference function (ΔT) and the remaining 10-year (2001–2010) is reserved for validation. The temperature difference function is validated by mean relative error, and the results are calculated for total and top 10% heavy precipitation, dry days, and spells as 14.60%, 6.14%, 2.81%, and 11.89%, respectively. The strong relationship exists between temperature difference function and standard deviation of corresponding climatic variables. Results show that standard deviation and mean relative error (MRE) have linear correlation. Also, ΔT model predictions are compared with CMIP5 RCPs projections from 2020 to 2100. The suggested model predictions fall within the range of various atmosphere-ocean global circulation (climate) model (AOGCM) scenario RCP 4.5 and RCP 8.5 projections, in addition to model predictions cross-correlation for RCP 2.6 and RCP 6.0.

Evaluation of atmospheric empirical model based on TIMED/SABER satellite temperature data

A total of 15 years of global temperature data from 2002–2016 as measured by TIMED/SABER were taken as standard to compare with those of USSA-76 and NRLMSISE-00. The accuracy of the two atmospheric models was analyzed by calculating daily mean and monthly mean temperature deviations and standard deviations of temperature deviations at different altitudes. The confidence of the model under different temperature deviations is calculated through setting the deviation between the models and the satellite observation temperature. The results show that the temperature data calculated by the two atmospheric models are in good agreement with the temperature observed by satellite. The daily mean and monthly mean accuracy of the NRLMSISE-00 are higher than those of the USSA-76. In the UMLT region, the two atmospheric models have yet to be improved to characterize the true atmosphere at the mid-high latitudes of upper mesosphere in summer and winter. The overall ability of the NRLMSISE-00 to represent the true atmosphere is superior to the USSA-76. In addition, the confidence decreases with the increase of altitude in the same latitude area and temperature deviation requirements. The confidence decreases with increasing latitude in the same altitude and temperature deviation requirements. By analyzing the differences between the atmospheric models and satellite observations. This paper provides a reference for the application of atmospheric models in engineering and provides the basis for the subsequent correction of atmospheric modes.

Impacts of Grading Rule on Urban Thermal Landscape Pattern Research

The thermodynamic landscape method is becoming a more popular approach for urban heat island research with the development of remote sensing technology. However, a limited amount of research discusses the theoretical and methodological issues of this method. This paper analyzed the reliability and stability of the results of thermal landscape pattern analysis with six different grading rules through surface temperature retrieval, landscape pattern analysis, and Geographic Information System (GIS) spatial analysis. The results demonstrate the following points. (1) The six grading methods can be categorized into two types: pixel number methods and temperature range methods. The grading results of the two kinds of methods lack comparability, whereas the grading results within one kind of method have high comparability. The temperature range methods have good consistency. The average value of the consistency indices (Si) of thermal landscape levels reaches up to 81.55%. The anomaly temperature method and standard deviation method are recommended for future research. (2) The grading rule significantly affects the stability of landscape indices, and its average variation coefficient reaches up to 22.36%. The authors suggest the use of landscape indices that have strong stability, such as shape index and landscape division index, in future research. (3) The results of the sensitivity analysis show that the change of the temperature range of thermal landscape levels affects landscape indices slightly, whereas the effect of the change of the level number of thermal landscapes on landscape indices is intense. The authors suggest categorizing the thermal landscape into six levels in future research in order to enhance the consistency and comparability among case studies.

Thermal properties of selected bee products

Knowledge of bee products’ physical properties has a decisive importance for the monitoring of their quality. Thermophysical parameters are very important properties. Thermal conductivity and thermal diffusivity of selected bee products (honey, bee pollen and perga) were measured by two different methods. For identification of thermal conductivity and thermal diffusivity transient methods were used: Hot Wire (HW) and Dynamic Plane Source (DPS) method with an instrument Isomet 2104. The principle of measuring process is based on the analysis of timetemperature relation. In the first series of measurements thermal conductivity and diffusivity at constant laboratory temperature of 20 °C were measured. The second series was focused on identification of the changes in the thermophysical parameters during temperature stabilisation in the temperature range of 5–25 °C. For samples with constant temperature standard deviations and probable errors in % were calculated. For relations of thermal parameters to temperature graphical dependencies were obtained. Two different thermophysical methods were used for improvement of data reliability and data statistics.

Comparison between seasonal variations in tidal and internal gravity wave activity as derived from observations at Maimaga and Tiksi

Since 2015, simultaneous observations of temperature of the high-latitude mesopause (87 km) have been made at Maimaga (63.04° N, 129.51° E) and Tiksi (71.58° N, 128.77° E) stations. These stations record spectra with Shamrock (Andor) photosensitive infrared spectrographs detecting the OH (3, 1) band in the near-infrared region (about 1.5 μm). We analyze temperature data obtained in observation seasons from 2015 to 2017. Standard deviations of temperature σ from its mean values are taken as characteristics of wave activity at night. We have obtained standard temperature deviations corresponding to internal gravity waves (IGW) (σgw) and tidal waves (σtd). Mean night rotational temperatures of hydroxyl emission almost coincide, and seasonal variations of gravity and tidal waves have a similar form during two seasons of simultaneous observations at Tiksi and Maimaga.

Сравнение сезонных вариаций активности приливных и внутренних гравитационных волн по наблюдениям на станциях Маймага и Тикси

Since 2015, simultaneous observations of temperature of the high-latitude mesopause (87 km) have been made at Maimaga (63.04° N, 129.51° E) and Tiksi (71.58° N, 128.77° E) stations. These stations record spectra with Shamrock (Andor) photosensitive infrared spectrographs detecting the OH (3, 1) band in the near-infrared region (about 1.5 μm). We analyze temperature data obtained in observation seasons from 2015 to 2017. Standard deviations of temperature σ from its mean values are taken as characteristics of wave activity at night. We have obtained standard temperature deviations corresponding to internal gravity waves (IGW) (σgw) and tidal waves (σtd). Mean night rotational temperatures of hydroxyl emission almost coincide, and seasonal variations of gravity and tidal waves have a similar form during two seasons of simultaneous observations at Tiksi and Maimaga.

Scalar-Flux Similarity in the Layer Near the Surface Over Mountainous Terrain

The scaled standard deviations of temperature and humidity are investigated in complex terrain. The study area is a steep Alpine valley, with six measurement sites of different slope, orientation and roughness (i-Box experimental site, Inn Valley, Austria). Examined here are several assumptions forming the basis of Monin–Obukhov similarity theory (MOST), including constant turbulence fluxes with height and the degree of self-correlation between the involved turbulence variables. Since the basic assumptions for the applicability of the MOST approach—horizontally homogeneous and flat conditions—are violated, the analysis is performed based on a local similarity hypothesis. The scaled standard deviations as a function of local stability are compared with previous studies from horizontally homogeneous and flat terrain, horizontally inhomogeneous and flat terrain, weakly inhomogeneous and flat terrain, as well as complex terrain. As a reference, similarity relations for unstable and stable conditions are evaluated using turbulence data from the weakly inhomogeneous and flat terrain of the Cabauw experimental site in the Netherlands, and assessed with the same post-processing method as the i-Box data. Significant differences from the reference curve and also among the i-Box sites are noted, especially for data derived from the i-Box sites with steep slopes. These differences concern the slope and the magnitude of the best-fit curves, illustrating the site dependence of any similarity theory.

Spatial Distribution of Flexural Strength in Y–Ba–Cu–O Bulk Superconductors

In order to determine the spatial distribution of the flexural strength, three-point bend tests have been performed on bar specimens cut from four YBa <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Cu <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">7-δ</sub> single-grain bulk superconductors. A relatively large spread of the room temperature flexural strength, average and standard deviation of 49.3 MPa and 12.7 MPa, respectively, was observed across the four bulk samples. This is attributed to the systemic microstructural variation introduced by the seeded melt growth. In particular, the strength was shown to be related to the local porosity and Y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> BaCuO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sub> content. To further examine bulk-to-bulk variability, indirect tensile (Brazilian) tests were conducted on twelve 16-mm-diameter bulk superconductors from three production batches. The Weibull modulus for these was calculated to be 8.76, suggesting that, despite the large spread in strength with position within a bulk, the batch processing of bulk superconductors can consistently yield samples with comparable overall mechanical strengths.

Oscillatory heat transfer in coated sorber beds: An analytical solution

This paper outlines a novel closed-form analytical model that considers the thermal contact resistance (TCR) at the interface between the sorbent layer and heat exchanger (HEX). Governing energy equations with oscillatory boundary conditions are solved using an orthogonal expansion technique and closed-form relationships are reported to calculate the temperature distribution and heat flux inside the sorbent coating and HEX. In addition, a new gravimetric large pressure jump (GLAP) test bed is designed to measure the uptake of sorption material. The performance of sorber beds are evaluated in terms of specific cooling power, heat flux at HEX base and sorbent temperature standard deviation. It is found that the sorbent thermal diffusivity and TCR at the interface between the sorption coating and HEX are the key parameters that determine the thermal performance of a sorption cooling system (SCS).

Thermal energy and stress properties as the main drivers of regional distribution of coral species richness in the Indian Ocean

AbstractAimLarge‐scale variation in species richness results from multiple environmental controls. We proposed to identify the main factors that influence species richness of reef corals to provide insight into natural forces and their implications for future climate impacts.LocationIndian Ocean.MethodsWe applied quantile regression (QR) to predict coral species richness and to evaluate the influence of reef area, biogeographical connection – represented by reef area up‐current, geological provinces defined by plate tectonics, latitude, longitude and mainland‐island separation, the physico‐chemical factors of photosynthetically active radiation (PAR), salinity and primary productivity and seven properties of sea surface temperature (mean, minimum, maximum, standard deviation, range, kurtosis and skewness) on coral species richness. Predictions at three quantiles (0.50, 0.75 and 0.95) were compared against ordinary least squares regression (OLS) analysis.ResultsAll four models successfully predicted species richness, with the 95% QR model showing the best fit. According to this model, reef area, number of reefs up‐current and mean‐SST had positive effects while maximum and kurtosis‐SST had negative effects on richness. The distribution of observed richness values in relation to the regression line suggested this model revealed the main limiting factors. High predicted richness sites were located in the region from Western Australia to Central Indian Ocean Islands and southern India, the Mozambique Channel and East Africa and Southern Red Sea and Gulf of Aden. Sites with low predicted richness were Arabian/Persian Gulf and Gulf of Oman, South Africa and south‐west Madagascar, Gulf of Kutch, Bay of Bengal and the Mascarenes.ConclusionsTemperature properties played a prominent role in influencing species richness mainly as latent energy and stress rather than thermal stability. These thermal properties indicate the conditions needed to promote coral diversity and selecting climate refugia for conservation management.

A new look at the decomposition of agricultural productivity growth incorporating weather effects.

Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960–2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time.

Theoretical foundations of emergent constraints: relationships between climate sensitivity and global temperature variability in conceptual models

There is as yet no theoretical framework to guide the search for emergent constraints. As a result, there are significant risks that indiscriminate data-mining of the multidimensional outputs from GCMs could lead to spurious correlations and less than robust constraints on future changes. To mitigate against this risk, Cox et al (hereafter CHW18) proposed a theory-motivated emergent constraint, using the one-box Hasselmann model to identify a linear relationship between ECS and a metric of global temperature variability involving both temperature standard deviation and autocorrelation ($\Psi$). A number of doubts have been raised about this approach, some concerning the theory and the application of the one-box model to understand relationships in complex GCMs which are known to have more than the single characteristic timescale. We illustrate theory driven testing of emergent constraints using this as an example, namely we demonstrate that the linear $\Psi$-ECS proportionality is not an artifact of the one-box model and rigorously features to a good approximation in more realistic, yet still analytically soluble conceptual models, namely the two-box and diffusion models. Each of the conceptual models predict different power spectra with only the diffusion model's pink spectrum being compatible with observations and the complex CMIP5 GCMs. We also show that the theoretically predicted $\Psi$-ECS relationship exists in the \texttt{piControl} as well as \texttt{historical} CMIP5 experiments and that the differing gradients of the proportionality are inversely related to the effective forcing in that experiment.

IR thermographic visualization of flow separation in applications with low thermal contrast

A measurement method for IR thermographic visualization of separated flow on rotor blades for wind turbines is demonstrated. Flow separation has a negative influence on the performance of airfoils, e.g., at wind turbine rotors. Thermographic flow visualization is a non-invasive measurement technique to identify different flow regimes, but the visualization of separated flow without explicit additional heating of the measured object has not been possible to date. For this reason, a measurement approach with an enhanced sensitivity is presented, which evaluates temporal temperature fluctuations from a thermographic images series by means of the standard deviation as well as the analysis of selected Fourier coefficients. The approach is validated by wind tunnel experiments with a non-heated circular cylinder as well as a 2D 6 digit NACA-airfoil. The flow and measurement conditions are chosen to be similar to wind turbines in operation. As a result, the flow regimes including the flow separation are resolved and are in agreement with reference measurements, while the sensitivity of standard thermographic flow visualization was too low. In addition, the Fourier analyses method results in an improvement of the contrast to noise ratio between turbulent and separated flow by 11.6 % compared to the evaluation of the temperature standard deviation. Further improvements are expected in future when taking the complete spatiotemporal temperature fluctuations into account.

Lattice Boltzmann investigation on phase change of nanoparticle-enhanced phase change material in a cavity with separate plate

The phase change material (PCM) can be used in thermal energy storage (TES) with large latent heat. However, due to the heat accumulation in the upper region, the solid-liquid phase change process will be slowed down. In this paper, in order to enhance the heat transfer of nanoparticle-enhanced PCM (NEPCM) in TES, a separate plate is applied to weaken the heat accumulation. The phase change multiple-relaxation-times lattice Boltzmann (MRT-LB) model is employed to solve the numerical problem and the effects of separate plate location, nanoparticle volume fraction and Rayleigh number are investigated. The results show that for all the Rayleigh numbers and volume fractions, the NEPCM of the case that separate plate is located in the middle of cavity melts fastest. Furthermore, the separate plate can reduce the temperature standard deviation. However, when the location of separate plate is less than 0.3, the melting process is slowed down, resulted from the heat accumulation near the separate plate.

Influence of fin size and distribution on solid-liquid phase change in a rectangular enclosure

This paper details a numerical study of solid-liquid phase change heat transfer in a rectangular enclosure with the aim of optimizing the number, dimension, and positioning of fins in the enclosure. The enclosure is exposed on one side to a constant heat flux of 1000 W/m2 for 3 h and both the total fin mass and the PCM mass are kept constant in all simulated cases. The heat diffusion equation in the PCM uses the equivalent heat capacity method while natural convection driven PCM motion in the enclosure is modeled through the buoyancy force, using a modified viscosity and an additional volume force term in the Navier-Stokes momentum conservation equation. Three efficiency assessment parameters are used: (i) the height-averaged temperature of the front hot plate which should remain as low as possible for the longer possible time, (ii) the energy stored inside the PCM as a function of time, and (iii) the heat transfer rate and heat flux between the front plate and the PCM. For each simulated case, complementary data such as the standard deviation of temperature along the heated plate and the ratio of sensible heat to latent accumulation are also calculated. Results show that increasing the number of fins diminishes both the stabilization temperature and the stabilization time of the front plate during phase change, and accelerates the sensible and latent storage of energy in the PCM. Using thinner but longer fins provides the same impact except that the stabilization time also increases as the fin length is increased. Besides, at constant fin mass, varying fin spacing have marginal impact on the latent heat storage performance and on the hot plate temperature stabilization. The study also shows that the surface area plays the largest role in the increase of the heat transfer rate between the front plate and the PCM, while configurations which can promote stronger natural convection lead to higher heat flux. Finally, it was observed that systems allowing easier heat transfer to the back plate during melting provide a higher ratio of sensible heat to latent accumulation, while the standard deviation of the front plate temperature decreases as the number of fins or the spacing between fins increases.

Classification of Solar Wind With Machine Learning

AbstractWe present a four‐category classification algorithm for the solar wind, based on Gaussian Process. The four categories are the ones previously adopted in Xu and Borovsky (2015): ejecta, coronal hole origin plasma, streamer belt origin plasma, and sector reversal origin plasma. The algorithm is trained and tested on a labeled portion of the OMNI data set. It uses seven inputs: the solar wind speed Vsw, the temperature standard deviation σT, the sunspot number R, the F10.7 index, the Alfven speed vA, the proton specific entropy Sp, and the proton temperature Tp compared to a velocity‐dependent expected temperature. The output of the Gaussian Process classifier is a four‐element vector containing the probabilities that an event (one reading from the hourly averaged OMNI database) belongs to each category. The probabilistic nature of the prediction allows for a more informative and flexible interpretation of the results, for instance, being able to classify events as “undecided.” The new method has a median accuracy larger than 90% for all categories, even using a small set of data for training. The Receiver Operating Characteristic curve and the reliability diagram also demonstrate the excellent quality of this new method. Finally, we use the algorithm to classify a large portion of the OMNI data set, and we present for the first time transition probabilities between different solar wind categories. Such probabilities represent the “climatological” statistics that determine the solar wind baseline.

The mortality burden of hourly temperature variability in five capital cities, Australia: Time-series and meta-regression analysis

BackgroundUnstable weather, such as intra- and inter-day temperature variability, can impair the health and shorten the survival time of population around the world. Climate change will cause Earth's surface temperature rise, but has unclear effects on temperature variability, making it urgent to understand the characteristics of the burden of temperature variability on mortality, regionally and nationally. ObjectivesThis paper aims to quantify the mortality risk of exposure to short-term temperature variability, estimate the resulting death toll and explore how the strength of temperature variability effects will vary as a function of city-level characteristics. MethodsTen-year (2000–2009) time-series data on temperature and mortality were collected for five largest Australia's cities (Sydney, Melbourne, Brisbane, Perth and Adelaide), collectively registering 708,751 deaths in different climates. Short-term temperature variability was captured and represented as the hourly temperature standard deviation within two days. Three-stage analyses were used to assess the burden of temperature variability on mortality. First, we modelled temperature variability-mortality relation and estimated the relative risk of death for each city, using a time-series quasi-Poisson regression model. Second, we used meta-analysis to pool the city-specific estimates, and meta-regression to explore if some city-level factors will modify the population vulnerability to temperature variability. Finally, we calculated the city-specific deaths attributable to temperature variability, and applied such estimates to the whole of Australia as a reflection of the nation-wide death burden associated with temperature variability. ResultsWe found evidence of significant associations between temperature variability and mortality in all cities assessed. Deaths associated with each 1°C rise in temperature variability elevated by 0.28% (95% confidence interval (CI): 0.05%, 0.52%) in Melbourne to 1.00% (95%CI: 0.52%, 1.48%) in Brisbane, with a pooled estimate of 0.51% (95%CI: 0.33%, 0.69%) for Australia. Subtropical and temperate regions showed no apparent difference in temperature variability impacts. Meta-regression analyses indicated that the mortality risk could be influenced by city-specific factors: latitude, mean temperature, population density and the prevalence of several chronic diseases. Taking account of contributions from the entire time-series, temperature variability was estimated to account for 0.99% to 3.24% of deaths across cities, with a nation-wide attributable fraction of 1.67% (9.59 deaths per 100, 000 population per year). ConclusionsHourly temperature variability may be an important risk factor of weather-related deaths and led to a sizeable mortality burden. This study underscores the need for developing specific and effective interventions in Australia to lessen the health consequences of temperature variability.

Volumetric MRI thermometry using a three-dimensional stack-of-stars echo-planar imaging pulse sequence.

To measure temperature over a large brain volume with fine spatiotemporal resolution. A three-dimensional stack-of-stars echo-planar imaging sequence combining echo-planar imaging and radial sampling with golden angle spacing was implemented at 3T for proton resonance frequency-shift temperature imaging. The sequence acquires a 188x188x43 image matrix with 1.5x1.5x2.75 mm3 spatial resolution. Temperature maps were reconstructed using sensitivity encoding (SENSE) image reconstruction followed by the image domain hybrid method, and using the k-space hybrid method. In vivo temperature maps were acquired without heating to measure temperature precision in the brain, and in a phantom during high-intensity focused ultrasound sonication. In vivo temperature standard deviation was less than 1°C at dynamic scan times down to 0.75 s. For a given frame rate, scanning at a minimum repetition time (TR) with minimum acceleration yielded the lowest standard deviation. With frame rates around 3 s, the scan was tolerant to a small number of receive coils, and temperature standard deviation was 48% higher than a standard two-dimensional Fourier transform temperature mapping scan, but provided whole-brain coverage. Phantom temperature maps with no visible aliasing were produced for dynamic scan times as short as 0.38 s. k-Space hybrid reconstructions were more tolerant to acceleration. Three-dimensional stack-of-stars echo-planar imaging temperature mapping provides volumetric brain coverage and fine spatiotemporal resolution. Magn Reson Med 79:2003-2013, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The vertical distribution characteristics of integral turbulence statistics in the atmospheric boundary layer over an urban area in Beijing

Turbulence data (2008–2012) from a 325 m meteorological tower in Beijing, which consisted of three layers (47, 140, and 280 m), was used to analyze the vertical distribution characteristics of turbulent transfer over Beijing city according to similarity theory. The conclusions were as follows. (1) Normalized standard deviations of wind speeds σ i / u * were plotted as a function only of a local stability parameter. The values under near-neutral conditions were 2.15, 1.61, and 1.19 at 47 m, 2.39, 1.75, and 1.21 at 140 m, and 2.51, 1.77, and 1.30 at 280 m, showing a clear increase with height. The normalized standard deviation of wind components fitted the 1/3 law under unstable stratification conditions and decreased with height under both stable and unstable conditions. (2) The normalized standard deviation of temperature fitted the ‒1/3 law in the free convection limit, but was quite scattered with different characteristics under near-neutral conditions. The normalized standard deviations of humidity and the CO2 concentration fitted the ‒1/3 law under unstable conditions, and remained constant under near-neutral and stable stratification. The normalized standard deviation of scalars, i.e., temperature, humidity, and CO2 concentration, all increased with height. (3) Compared with momentum, and the water vapor and CO2 concentrations, the turbulence correlation coefficient for heat was smaller under near-neutral conditions, but larger under both stable and unstable conditions. A dissimilarity between heat, and the water vapor and CO2 concentrations was observed in urban areas. The relative correlation coefficients between heat and each of momentum, humidity, and CO2 concentration (| r wT / r uw |, | r wT / r wc | and | r wT / r uq |) in the lower layers were always larger than in higher layers, except for the relative correlation coefficient between heat and humidity in an unstable stratification. Therefore, the ratio between heat and each of momentum, humidity, and CO2 concentration decreased with height.

Observing the thermodynamic effects in cavitating flow by IR thermography

When dealing with liquid flows, where operating temperature gets close to the liquid critical temperature, cavitation cannot be assumed as an isothermal phenomenon. Due to the relatively high density of vapor, the thermodynamic effect (decrease of temperature in the bulk liquid due to latent heat flow) becomes considerable and should not be neglected. For applications like pumping cryogenic fuel and oxidizer in liquid propulsion space launchers, consideration of the thermodynamic effect is essential - consequently the physical understanding of the phenomenon and its direct experimental observation has a great value.This study presents temperature measurements in a cavitating flow on a simple convergent-divergent constriction by infrared (IR) thermography. Developed cavitating flow of hot water (∼100°C) was evaluated by high-speed IR thermography and compared with conventional high-speed visualization, at different operating conditions with the velocity range at the nozzle throat between 9.6 and 20.6m/s and inlet pressure range between 143 and 263kPa.Temperature depression near the nozzle throat - near the leading edge of cavitation was measured in a range up to ΔT=0.5K. This confirms the presence of the thermodynamic effects by cavitation phenomenon and it is in agreement with its theory. In the study, average temperature fields, fields of temperature standard deviation and time-resolved temperatures, are presented and discussed. In addition, statistical analysis between temperature drop and cavitation flow characteristics is shown.