Estimates Of Temperature Changes Research Articles

Understanding seasonal cycle of daily extreme temperatures based on generalized additive model for location, scale and shape with smoothing spline

AbstractThe seasonal cycle (SC) of surface air temperature is a substantial element in climatology. Some basic and important topics in climate change studies are based on accurate and reliable estimation of SCs, such as percentile‐based indices of extremes and probability density function (PDF) changes of daily temperatures. For both of them, most studies characterized SCs using averages of multi‐days windows, which is not smooth and accurate enough representing the extreme thresholds and climatological normal of SCs. It is necessary to construct smooth and reasonable SCs for more accurate estimation of temperature changes on extreme thresholds and PDFs. In this study, we propose a flexible method based on generalized additive models for location scale and shape and penalized b‐spline smoothing technique with respective distributions to construct smooth SCs and SC for extreme temperatures (SCETs). The accuracy of the constructed smooth SCETs is good with the estimation biases of percentiles tending to be zero. The constructed smooth SCET also exhibits good stability over time, such that the magnitude changes of temperatures on each calendar day are close to climatic changes of mean temperature when the concerned period shifts. Based on the constructed smooth SCs, climatic changes by seasons and PDFs between two periods, 1961–1990 and 1991–2020, are examined over China. The increase of thresholds for hot extremes in spring during the recent period is prominent, while the increase of thresholds for daytime cold extremes in summer over a part of central to southern China is also notable. The smooth SCs and SCETs based on our flexible statistical modelling framework can characterize daily extreme temperatures reasonably and accurately, and should be expected to have more applications for a better understanding of climate changes related to distributions and seasonal cycles.

Noninvasive Monitoring of Tissue Temperature Changes Induced by Focused Ultrasound Exposure using Sparse Expression of Ultrasonic Radio Frequency Echo Signals.

Noninvasive therapies such as focused ultrasound were developed to be used for cancer therapies, vessel bleeding, and drug delivery. The main purpose of focused ultrasound therapy is to affect regions of interest (ROI) of tissues without any injuries to surrounding tissues. In this regard, an appropriate monitoring method is required to control the treatment. This study is aimed to develop a noninvasive monitoring technique of focused ultrasound (US) treatment using sparse representation of US radio frequency (RF) echo signals. To this end, reasonable results in temperature change estimation in the tissue under focused US radiation were obtained by utilizing algorithms related to sparse optimization as orthogonal matching pursuit (OMP) and accompanying Shannon's entropy. Consequently, ex vivo tissue experimental tests yielded two datasets, including low-intensity focused US (LIFU) and high-intensity focused US (HIFU) data. The proposed processing method analyzed the ultrasonic RF echo signal and expressed it as a sparse signal and calculated the entropy of each frame. The results indicated that the suggested approach could noninvasively estimate temperature changes between 37°C and 47°C during LIFU therapy. In addition, it represented temperature changes during HIFU ablation at various powers, ranging from 10 to 130 W. The normalized mean square error of the proposed method is 0.28, approximately 2.15 on previous related methods. These results demonstrated that this novel proposed approach, including the combination of sparsity and Shanoon's entropy, is more feasible and effective in temperature change estimation than its predecessors.

Window size analysis in ultrasonic temperature estimation with timeshifts

In this work, ultrasonic timeshift method for temperature change estimation was investigated for 2D simulated in-silico synthetic ultrasonic signals. Digital phantom tissue was created in MATLAB environment and acoustic simulation was running on k-Wave toolbox for two different temperature conditions. First temperature distribution was assigned to tissue as uniform 37 °C. Second temperature distribution is Gaussian form with peak at tissue center as 45 °C and tails of Gaussian curve is 37 °C. Signal was analyzed with ultrasonic timeshift method for temperature change estimation. This method is based on four steps, calibration with tissue constant, finding timeshift with cross correlation algorithm, find slope of timeshift vector respect to timestep, and multiply tissue constant and slope of local timeshift vector. This multiplication gives temperature change of local point. In this work, window size of smoothing filter of timeshift vector and linear fitting to timeshift—timestep data was analyzed as parametrically with range 3λ to 10λ with a 1λ increment for both windows equally. As a result, window parameters as 5λ to 7λ give best results, maximum absolute error is 0.82 °C, 0.97 °C and 0.92 °C respectively and mean absolute error is ∼0.35 °C. As a verify, different analysis was performed on different temperature distribution with discrete two peak curves.

Estimating Thermal Impact on Groundwater Systems from Heat Pump Technologies: A Simplified Method for High Flow Rates

This research delves into the potential thermal effects on underground water systems caused by the use of thermal technologies involving extraction and injection wells. We developed a unique approach that combines straightforward calculations with computer-based modeling to evaluate thermal impacts when water flow rates exceed 2 L/s. Our model, based on a system with two wells and a steady water flow, was used to pinpoint the area around the thermal technology where the temperature varied by more than 1 °C. Our findings suggest that the data-based relationships we derived from our model calculations provide a cautious estimate of the size of the affected area, or ‘thermal cloud’. However, it is important to note that our model’s assumptions might not fully account for the complex variables present in real-world underground water systems. This highlights a need for more research and testing. A key contribution of our study is the development of a new method to assess the thermal impact of operations involving heat pumps. In conclusion, while our proposed method needs more fine-tuning, it shows promise in estimating temperature changes within water-bearing rock layers, or aquifers. This is crucial in the effective use of thermal technologies while also ensuring the protection and sustainable management of our underground water resources.

Late Holocene glacier and climate fluctuations in the Mackenzie and Selwyn mountain ranges, northwestern Canada

Abstract. Over the last century, northwestern Canada experienced some of the highest rates of tropospheric warming globally, which caused glaciers in the region to rapidly retreat. Our study seeks to extend the record of glacier fluctuations and assess climate drivers prior to the instrumental record in the Mackenzie and Selwyn mountains of northwestern Canada. We collected 27 10Be surface exposure ages across nine cirque and valley glacier moraines to constrain the timing of their emplacement. Cirque and valley glaciers in this region reached their greatest Holocene extents in the latter half of the Little Ice Age (1600–1850 CE). Four erratic boulders, 10–250 m distal from late Holocene moraines, yielded 10Be exposure ages of 10.9–11.6 ka, demonstrating that by ca. 11 ka, alpine glaciers were no more extensive than during the last several hundred years. Estimated temperature change obtained through reconstruction of equilibrium line altitudes shows that since ca. 1850 CE, mean annual temperatures have risen 0.2–2.3 ∘C. We use our glacier chronology and the Open Global Glacier Model (OGGM) to estimate that from 1000 CE, glaciers in this region reached a maximum total volume of 34–38 km3 between 1765 and 1855 CE and had lost nearly half their ice volume by 2019 CE. OGGM was unable to produce modeled glacier lengths that match the timing or magnitude of the maximum glacier extent indicated by the 10Be chronology. However, when applied to the entire Mackenzie and Selwyn mountain region, past millennium OGGM simulations using the Max Planck Institute Earth System Model (MPI-ESM) and the Community Climate System Model 4 (CCSM4) yield late Holocene glacier volume change temporally consistent with our moraine and remote sensing record, while the Meteorological Research Institute Earth System Model 2 (MRI-ESM2) and the Model for Interdisciplinary Research on Climate (MIROC) fail to produce modeled glacier change consistent with our glacier chronology. Finally, OGGM forced by future climate projections under varying greenhouse gas emission scenarios predicts 85 % to over 97 % glacier volume loss by the end of the 21st century. The loss of glaciers from this region will have profound impacts on local ecosystems and communities that rely on meltwater from glacierized catchments.

Retrospective and projected warming-equivalent emissions from global livestock and cattle calculated with an alternative climate metric denoted GWP.

Limiting warming by the end of the century to 1.5°C compared to pre-Industrial times requires reaching and sustaining net zero global carbon dioxide (CO2) emissions and declining radiative forcing from non-CO2 greenhouse gas (GHG) sources such as methane (CH4). This implies eliminating CO2 emissions or balancing them with removals while mitigating CH4 emissions to reduce their radiative forcing over time. The global cattle sector (including Buffalo) mainly emits CH4 and N2O and will benefit from understanding the extent and speed of CH4 reductions necessary to align its mitigation ambitions with global temperature goals. This study explores the utility of an alternative usage of global warming potentials (GWP*) in combination with the Transient Climate Response to cumulative carbon Emissions (TCRE) to compare retrospective and projected climate impacts of global livestock emission pathways with other sectors (e.g. fossil fuel and land use change). To illustrate this, we estimated the amount and fraction of total warming attributable to direct CH4 livestock emissions from 1750 to 2019 using existing emissions datasets and projected their contributions to future warming under three historical and three future emission scenarios. These historical and projected estimates were transformed into cumulative CO2 equivalent (GWP100) and warming equivalent (GWP*) emissions that were multiplied by a TCRE coefficient to express induced warming as globally averaged surface temperature change. In general, temperature change estimates from this study are comparable to those obtained from other climate models. Sustained annual reductions in CH4 emissions of 0.32% by the global cattle sector would stabilize their future effect on global temperature while greater reductions would reverse historical past contributions to global warming by the sector in a similar fashion to increasing C sinks. The extent and speed with which CH4 mitigation interventions are introduced by the sector will determine the peak temperature achieved in the path to net-zero GHG.

Constrained tropical land temperature-precipitation sensitivity reveals decreasing evapotranspiration and faster vegetation greening in CMIP6 projections

Over the tropical land surface, accurate estimates of future changes in temperature, precipitation and evapotranspiration are crucial for ecological sustainability, but remain highly uncertain. Here we develop a series of emergent constraints (ECs) by using historical and future outputs from the Coupled Model Inter-comparison Project Phase 6 (CMIP6) Earth System Models under the four basic Shared Socio-economic Pathway scenarios (SSP126, SSP245, SSP370, and SSP585). Results show that the temperature sensitivity to precipitation during 2015–2100, which varies substantially in the original CMIP6 outputs, becomes systematically negative across SSPs after application of the EC, with absolute values between −1.10 °C mm−1 day and −3.52 °C mm−1 day, and with uncertainties reduced by 9.4% to 41.4%. The trend in tropical land-surface evapotranspiration, which was increasing by 0.292 mm yr−1 in the original CMIP6 model outputs, becomes significantly negative (−0.469 mm yr−1) after applying the constraint. Moreover, we find a significant increase of 58.7% in the leaf area index growth rate.

Three Diverse Applications of General-Purpose Parameter Optimization Algorithm

Parameters often take key roles in determining the accuracy of algorithms, logics, and models for practical applications. Previously, we have proposed a general-purpose parameter optimization algorithm, and studied its applications in various practical problems. This algorithm optimizes the parameter values by repeating small changes of them based on a local search method with hill-climbing capabilities. In this paper, we present three diverse applications of this algorithm to show the versatility and effectiveness. The first application is the fingerprint-based indoor localization system using IEEE802.15.4 devices called FILS15.4 that can detect the location of a user in an indoor environment. It is shown that the number of fingerprints for each detection point, the fingerprint values, and the detection interval are optimized together, and the average detection accuracy exceeds 99%. The second application is the human face contour approximation model that is described by a combination of half circles, line segments, and a quadratic curve. It is shown that the simple functions can well approximate the face contour of various persons by optimizing the center coordinates, radii, and coefficients. The third application is the computational fluid dynamic (CFD) simulation to estimate temperature changes in a room. It is shown that the thermal conductivity is optimized to make the average temperature difference between the estimated and measured 0.22∘C.

Twenty-first century regional temperature response in Chile based on empirical-statistical downscaling

Local scale estimates of temperature change in the twenty-first century are necessary for informed decision making in both the public and private sector. In order to generate such estimates for Chile, weather station data of the Dirección Meteorológica de Chile are used to identify large-scale predictors for local-scale temperature changes and construct individual empirical-statistical models for each station. The geographical coverage of weather stations ranges from Arica in the North to Punta Arenas in the South. Each model is trained in a cross-validated stepwise linear multiple regression procedure based on (24) weather station records and predictor time series derived from ERA-Interim reanalysis data. The time period 1979–2000 is used for training, while independent data from 2001 to 2015 serves as a basis for assessing model performance. The resulting transfer functions for each station are then directly coupled to MPI-ESM simulations for future climate change under emission scenarios RCP2.6, RCP4.5 and RCP 8.5 to estimate the local temperature response until 2100 A.D. Our investigation into predictors for local scale temperature changes support established knowledge of the main drivers of Chilean climate, i.e. a strong influence of the El Niño Southern Oscillation in northern Chile and frontal system-governed climate in central and southern Chile. Temperature downscaling yields high prediction skill scores (ca. 0.8), with highest scores for the mid-latitudes. When forced with MPI-ESM simulations, the statistical models predict local temperature deviations from the 1979–2015 mean that range between − 0.5–2 K, 0.5–3 K and 2–7 K for RCP2.6, RCP4.5 and RCP8.5 respectively.

Urbanisation’s contribution to climate warming in Great Britain

Urbanisation is changing the climate of the world we live in. In Great Britain (GB) 5.8% of the total land area is covered by artificial surfaces, increasing from 4.3% in 1975. Aside from associated loss of farmland, biodiversity and a range of ecosystem services, changing to urban form warms the Earth’s surface: the urban heat island (UHI) effect. Standard estimates of temperature changes do not account for urbanisation (i.e. use of rural-only stations or removal of urban bias in observations), meaning that anthropogenic modifications to the land surface may be causing the surface-level atmosphere to warm quicker than those estimates suggest. Using observations from a high-density urban monitoring network, we show that locally this warming (instantaneously) may be over 8 °C. Based on the relationships between UHI intensity, urban fraction and wind speed in this network, we create a statistical model and use it to estimate the current daily-mean urban warming across GB to be 0.04 °C [0.02 °C –0.06 °C]. Despite this climate contribution appearing small (94% of GB’s land cover for the time-being is still rural), we show that half of GB’s population currently live in areas with average daily-mean warming ∼0.4 °C. Under heatwave conditions our high estimates show 40% of GB’s population may experience over a 1 °C daily-mean UHI. Furthermore, simply due to urbanisation (1975–2014) we estimate GB is warming at a rate equivalent and in addition to 3.4% [1.9%–5.0%] of the observed surface-level warming calculated from background stations. In the fastest urbanising region, South East GB, we find that these warming rates are up to three times faster. The methodology is straightforward and can be readily extended to other countries or updated as future land cover data becomes available.

Simultaneous Temperature Estimation of Multiple Gratings Using a Multi-Layer Neural Network

This paper introduces a method to do simultaneous temperature estimations of multiple gratings in an FBG array. The method involves training a multi-layer neural network using simulated training data. The network is then used to estimate the temperature changes of multiple gratings simultaneously using only the experimentally obtained spectrum of the FBG array. The versatility of the method is seen from the results of three different setups. That is the broadband lightsource with OSA, the broadband lightsource with spectrometer, and incoherent optical frequency domain reflectometry. The method can estimate the temperature changes with high accuracy and low root mean squared error (RMSE) for the setups under consideration. Finally, the method is shown to be capable of simultaneous estimation of temperature changes for 19 FBGs using the BLS setup with a maximum absolute error of $6.64~\mathrm {\textbf {K}}$ and an RMSE of $1.69~\mathrm {\textbf {K}}$ in only 1.74 ms/FBG.

A Hydrothermal Coupling Model for Estimating Temperature Variations in the Riparian Zone

In research using heat tracing technology to investigate the lateral hyporheic exchange in the shallow geological body of the riparian zone, the accurate estimation of temperature changes can provide a scientific basis for quantifying the process of lateral hyporheic exchange. To improve the accuracy of estimating temperature changes in the riparian zone, a hydrothermal coupling model considering parameter heterogeneity was established based on existing models of the relationship between thermal conductivity and saturation. The model was verified by temperature data from laboratory experiments, and the effect of the thermal conductivity prediction models was compared with that of the partial differential equation (PDE) modeling approach. The results show that the established hydrothermal coupling model can effectively characterize the temperature changes observed in a generalized laboratory model of the riparian zone, and the model simulation effects vary with the equivalent thermal conductivity models. In addition, several thermal conductivity empirical models are suggested for further application. The model parameter sensitivity analysis indicated that the hydraulic conductivityks, VG model parameters (αandβ) and heat capacity of soilCshave a relatively large effect on the temperature output of the model. The results of this study will provide reference for the selection of equivalent thermal conductivity model for simulating temperature variations in the riparian zone.

Commentary: Anatomic and Thermometric Analysis of Cranial Nerve Palsy after Laser Amygdalohippocampotomy for Mesial Temporal Lobe Epilepsy.

BACKGROUND Laser interstitial thermal therapy (LITT) is a minimally invasive therapy for treating medication-resistant mesial temporal lobe epilepsy. Cranial nerve (CN) palsy has been reported as a procedural complication, but the mechanism of this complication is not understood. OBJECTIVE To identify the cause of postoperative CN palsy after LITT. METHODS Four medial temporal lobe epilepsy patients with CN palsy after LITT were identified for comparison with 22 consecutive patients with no palsy. We evaluated individual variation in the distance between CN III and the uncus, and CN IV and the parahippocampal gyrus using preoperative T1- and T2-weighted magnetic resonance (MR) images. Intraoperative MR thermometry was used to estimate temperature changes. RESULTS CN III (n = 2) and CN IV palsies (n = 2) were reported. On preoperative imaging, the majority of identified CN III (54%) and CN IV (43%) were located within 1 to 2 mm of the uncus and parahippocampal gyrus tissue border, respectively. Affected CN III and CN IV were more likely to be found < 1 mm of the tissue border (PCNIII = .03, PCNIV < .01; chi-squared test). Retrospective assessment of thermal profile during ablation showed higher temperature rise along the mesial temporal lobe tissue border in affected CNs than unaffected CNs after controlling for distance (12.9°C vs 5.8°C; P = .03; 2-sample t-test). CONCLUSION CN palsy after LITT likely results from direct heating of the respective CN running at extreme proximity to the mesial temporal lobe. Low-temperature thresholds set at the border of the mesial temporal lobe in patients whose CNs are at close proximity may reduce this risk.

Anatomic and Thermometric Analysis of Cranial Nerve Palsy after Laser Amygdalohippocampotomy for Mesial Temporal Lobe Epilepsy.

Laser interstitial thermal therapy (LITT) is a minimally invasive therapy for treating medication-resistant mesial temporal lobe epilepsy. Cranial nerve (CN) palsy has been reported as a procedural complication, but the mechanism of this complication is not understood. To identify the cause of postoperative CN palsy after LITT. Four medial temporal lobe epilepsy patients with CN palsy after LITT were identified for comparison with 22 consecutive patients with no palsy. We evaluated individual variation in the distance between CN III and the uncus, and CN IV and the parahippocampal gyrus using preoperative T1- and T2-weighted magnetic resonance (MR) images. Intraoperative MR thermometry was used to estimate temperature changes. CN III (n=2) and CN IV palsies (n=2) were reported. On preoperative imaging, the majority of identified CN III (54%) and CN IV (43%) were located within 1 to 2 mm of the uncus and parahippocampal gyrus tissue border, respectively. Affected CN III and CN IV were more likely to be found<1 mm of the tissue border (PCNIII=.03, PCNIV<.01; chi-squared test). Retrospective assessment of thermal profile during ablation showed higher temperature rise along the mesial temporal lobe tissue border in affected CNs than unaffected CNs after controlling for distance (12.9°C vs 5.8°C; P=.03; 2-sample t-test). CN palsy after LITT likely results from direct heating of the respective CN running at extreme proximity to the mesial temporal lobe. Low-temperature thresholds set at the border of the mesial temporal lobe in patients whose CNs are at close proximity may reduce this risk.

Clumped isotope constraints on changes in latest Pleistocene hydroclimate in the northwestern Great Basin: Lake Surprise, California

AbstractDuring the Last Glacial Maximum (LGM) and subsequent deglaciation, the Great Basin in the southwestern United States was covered by numerous extensive closed-basin lakes, in stark contrast with the predominately arid climate observed today. This transition from lakes in the Late Pleistocene to modern aridity implies large changes in the regional water balance. Whether these changes were driven by increased precipitation rates due to changes in atmospheric dynamics, decreased evaporation rates resulting from temperature depression and summer insolation changes, or some combination of the two remains uncertain. The factors contributing to these large-scale changes in hydroclimate are critical to resolve, given that this region is poised to undergo future anthropogenic-forced climate changes with large uncertainties in model simulations for the 21st century. Furthermore, there are ambiguous constraints on the magnitude and even the sign of changes in key hydroclimate variables between the Last Glacial Maximum and the present day in both proxy reconstructions and climate model analyses of the region. Here we report thermodynamically derived estimates of changes in temperature, precipitation, and evaporation rates, as well as the isotopic composition of lake water, using clumped isotope data from an ancient lake in the northwestern Great Basin, Lake Surprise (California). Compared to modern climate, mean annual air temperature at Lake Surprise was 4.7 °C lower during the Last Glacial Maximum, with decreased evaporation rates and similar precipitation rates to modern. During the mid-deglacial period, the growth of Lake Surprise implied that the lake hydrologic budget briefly departed from steady state. Our reconstructions indicate that this growth took place rapidly, while the subsequent lake regression took place over several thousand years. Using models for precipitation and evaporation constrained from clumped isotope results, we determine that the disappearance of Lake Surprise coincided with a moderate increase in lake temperature, along with increasing evaporation rates outpacing increasing precipitation rates. Concomitant analysis of proxy data and climate model simulations for the Last Glacial Maximum are used to provide a robust means to understand past climate change, and by extension, predict how current hydroclimates may respond to expected future climate forcings. We suggest that an expansion of this analysis to more basins across a larger spatial scale could provide valuable insight into proposed climate forcings, and aid in climate model process depiction. Ultimately, our analysis highlights the importance of temperature-driven evaporation as a mechanism for lake growth and retreat in this region.

Thermal Resistance and Condensation in the Light-frame Timber Wall Structures with Various Composition of Insulation Layers

As energy costs increase, more people has become interested on energy efficiency and savings in residential buildings. The two main subjects related to energy in residential buildings are insulation and condensation. There are two approaches to prevent condensation; increasing air tightness and maintaining the temperature inside of the wall structure over the dew point, which is in turn related to insulation. Even though the Korean government has highlighted the importance of energy efficiency for residential housings, and in spite of the customers’ demands, the timber construction industry is still using conventional light-frame construction without even trying to improve energy efficiency. In this study, various types and combinations of wall structures were tested under cold outdoor and warm indoor temperatures to analyse the temperature gradients and to determine the possible sites of condensation in the wall structures. In addition to the experimental tests, three theoretical models were developed and their estimations of temperature change through the wall structure were compared with the actual measurements to evaluate accuracy of the models. The results of the three models agree relatively well with the experimental values, indicating that they can be used to estimate temperature changes in wall structures. The theoretical analysis of different insulation layers’ combinations show that condensation may occur within the mid-layer in the conventional light-frame wall structures for any combination of inner-, mid-, and outer-layers of insulation. Therefore, it can be concluded that the addition of an inner and outer insulation layer or increasing the thickness of insulation may not be adequate to prevent condensation in the wall structure without preventing penetration of warm moist air into the wall structure.

Temperature estimation using Boltzmann plot method of many calcium emission lines in laser plasma produced on river clamshell sample

Temperature as one very important characteristics of a laser-induced plasma was estimated using many calcium emission spectral lines. This was possible due to the availability of a wide coverage and high resolution optical multichannel analyser (OMA) system allowing a simultaneous detection of many emission spectral lines from one element. The plasma emission was produced after focusing an Nd-YAG (neodymium-doped yttrium aluminium garnet) laser onto a river clamshell samples under air as surrounding gas at low and high pressures. The emission spectrum was acquired using the OMA system equipped with an echelle spectrograph system. The clamshell sample was collected from Panga River, Panga, Aceh Jaya, Aceh, Indonesia. The plasma temperature estimation was carried out by Boltzmann plot method. All calcium spectral lines either atomic and ionic emission were identified including resonant emission spectral lines in the recorded spectrum. Boltzmann distribution function firstly was plotted for all identified calcium spectral lines either atomic and ionic emission including their respective resonant emission spectral lines. In the further stage, the resonant emission lines then were excluded from the Boltzmann plot. As the results, the estimated temperature changes significantly with the number emission lines included and also with inclusion of the resonant spectral lines. The plasma temperature heavily influenced by inclusion the resonant emission lines. Thus, this work demonstrated clearly the influence of number emission lines used in Boltzmann plot to the plasma temperature estimation. The results also demonstrated explicitly the apparent effect of self-absorption of the resonant spectral line in estimation the plasma temperature.

The influence of climate change in Superpave binder selection for Chile

One of the relevant effects of anthropogenic climate change has been an anomalous increase in temperature near the earth’s surface. In the context of pavement engineering, materials that are thermally susceptible could be affected by these changes. For this reason, the possible effects of global warming in binder selection for asphalt pavements in Chile were studied. Two global warming scenario results obtained with MICRO5 model plus local downscaling with WRF model were used. The estimated temperature changes were calculated for the period 2030–2059 for the 94 weather stations previously used for the Chilean Superpave zonings. Three pavement temperatures models were used together with these new air temperature databases: SHRP, LTPP 2.1 and LTPP 3.1. The results were compared with the original Superpave zonings obtained with the same models. A significant number of stations underwent a change in PG grade for the period considered. Most of the predicted changes were increased in the high-temperature PG grade. The areas of use for the softer binder PG52-34 gradually decreased, while the areas for the stiffer PG64-22 increased. A new even stiffer binder PG70-16 had to be introduced into the new Superpave zonings.

Mass, height of burst, and source-receiver distance constraints on the acoustic coda phase delay method.

This research uses the acoustic coda phase delay method to estimate relative changes in air temperature between explosions with varying event masses and heights of burst. It also places a bound on source-receiver distance for the method. Previous studies used events with different shapes, height of bursts, and masses and recorded the acoustic codas at source-receiver distances less than 1 km. This research further explores the method using explosions that differ in mass (by up to an order of magnitude) and are placed at varying heights. Source-receiver distances also cover an area out to 7 km. Relative air temperature change estimates are compared to complementary meteorological observations. Results show that two explosions that differ by an order of magnitude cannot be used with this method because their propagation times in the near field and their fundamental frequencies are different. These differences are expressed as inaccuracies in the relative air temperature change estimates. An order of magnitude difference in mass is also shown to bias estimates higher. Small differences in height of burst do not affect the accuracy of the method. An upper bound of 1 km on source-receiver distance is provided based on the standard deviation characteristics of the estimates.

Variations in the temperature and circulation of the atmosphere during the 11-year cycle of solar activity derived from the ERA-Interim reanalysis data

Using the data of the ERA-Interim reanalysis, we have obtained estimates of changes in temperature, the geopotential and its large-scale zonal harmonics, wind velocity, and potential vorticity in the troposphere and stratosphere of the Northern and Southern hemispheres during the 11-year solar cycle. The estimates have been obtained using the method of multiple linear regression. Specific features of response of the indicated atmospheric parameters to the solar cycle have been revealed in particular regions of the atmosphere for a whole year and depending on the season. The results of the analysis indicate the existence of a reliable statistical relationship of large-scale dynamic and thermodynamic processes in the troposphere and stratosphere with the 11-year solar cycle.