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The employment of 1D model of the thermal stratification in the tank of an air to water heat pump (AWHP) may accurately predict the evolution of the temperatures at the different layers. The study predicted the water temperatures at different levels in a 150 L tank coupled with 1.2 kW heat pump unit. A data acquisition system was designed and built to monitor the input and output parameters used in the model to evaluate the evolution of the water layers’ temperatures. The results depicted that the 1D linear model accurately predicted the evolution of the water temperatures at each layer due to thermal stratification with a determination coefficient ( R 2) and root mean square error (RMSE) of 0.9932 and 0.9253. The modelled validation showed a very good R 2 and RMSE of 0.9940 and 0.8595. The average thermal energy gained and the average COP due to the first hour heating rating (the withdrawal of 150 L of the hot water) was 5.67% lowered under the stratification condition when compared to the scenario without stratification. The p -values show no significant differences among the water temperatures at the different layers due to first hour heating rating. The study will encourage researchers and energy service companies to highlight the impact of thermal stratification regarding to the dynamics of an AWHP.

The process of engine warming-up leads to additional fuel consumption. Energy management strategy considering engine warming-up is expected to further improve the energy economy of hybrid electric vehicles. This study provides a simple yet practical model for engine thermal dynamics. Then, the optimization problem of energy management considering engine warming-up is formulated on the basis of the control-oriented engine thermal dynamics. Thereafter, the optimal solution is derived by using the dynamic programming algorithm. Finally, the proposed engine thermal dynamics and energy management strategy are evaluated through simulation and experiments. Results show that the established engine thermal model effectively captures the main thermal behavior, simulation results reveal a high degree of approximation to experimental results for the engine temperature and fuel consumption, and the energy management strategy with engine temperature can further improve the energy efficiency.

Water shortage and salinity are crucial factors affecting plant growth in arid and semi-arid regions, where irrigation water shortage and capillary rise from shallow saline water tables are often encountered. The objectives of this study are to construct a prototype of solar driven desalination plant in an arid area of Jordan Rift Valley, to develop a mathematical model predicting thermal dynamics in the prototype, to calibrate model parameters with measured physical parameters, and to discuss the performance of the prototype as well as its applicability to other areas under different environment. Results of measurement and numerical simulation show that the model is capable to reproduce the thermal dynamics of the desalination plant and to predict dew yield. Overall, the developed model provides a sound basis for describing and explaining the mass and energy balance mechanisms in the developed desalination plant. This study offers also a useful tool for analysis and assessment of the dew yield and thermal dynamics of such a desalination plant in general. Using the constructed prototype, performance analysis based on crop cultivation is ongoing.

International audience; Temperature is one of the best investigated environmental factors in ecological life-history studies and is increasingly considered in the contexts of climate change and urbanization. In avian ecology, few studies have examined the associations between thermal dynamics in the nest environment and its neighbouring air. Here, we placed avian nests and non-incubated eggs inside nest boxes at various air temperatures that ranged from 0.3 to 33.1°C, both in the field and in laboratory conditions. We measured how the design of the boxes, their compass orientation and their location in more or less urbanized environments affected the surface temperature of nests and eggs. We also assessed whether covering the eggs with lining material influenced their surface temperature. Overall, across all performed tests, we found that the surface temperature of nests and eggs strongly reflected the air temperature measured outside of the nest boxes. While the design of the nest boxes had little influence on the temperature of nests and eggs, orienting the nest boxes to the north or to the west significantly decreased their surface temperature. The presence of lining material also kept eggs slightly warmer when air temperatures were low. Altogether these results suggest that non-incubated eggs are not well protected against extreme air temperatures prior to the onset of incubation. From an evolutionary point of view, producers of ectotherm eggs need therefore to time egg-laying appropriately in order to avoid unfavourable thermal nest environments.

Studies on the impact of climate change in lakes have mainly focused on the average response of lake surface temperature during three summer months (July, August, September, usually termed JAS). Focusing on the Laurentian Great Lakes, we challenge this common assumption by showing that the thermal behaviour is diversified in time both among different lakes and within a single one. Deep regions experience a stronger warming concentrated in early summer, mainly due to anticipated stratification, while shallow parts respond more uniformly throughout the year. To perform such analysis, we use the difference between the five warmest and coldest years in a series of 20 years as a proxy of possible effects of climate alterations, and compare the warming of lake surface temperature with that of air temperature. In this way, based on past observations obtained from satellite images, we show how the warming is heterogeneously distributed in time and in space, and that the quantification of lakes' thermal response to climate change is chiefly influenced by the time window used in the analysis. Should we be more careful when considering averaged indicators of lake thermal response to climate change?, Environmental Research Letters, 15 (3), ISSN:1748-9326, ISSN:1748-9318

This study investigates and compares soil moisture and hydrology projections of broadly used land models with permafrost processes and highlights the causes and impacts of permafrost zone soil moisture projections. Climate models project warmer temperatures and increases in precipitation (P) which will intensify evapotranspiration (ET) and runoff in land models. However, this study shows that most models project a long-term drying of the surface soil (0–20 cm) for the permafrost region despite increases in the net air–surface water flux (P-ET). Drying is generally explained by infiltration of moisture to deeper soil layers as the active layer deepens or permafrost thaws completely. Although most models agree on drying, the projections vary strongly in magnitude and spatial pattern. Land models tend to agree with decadal runoff trends but underestimate runoff volume when compared to gauge data across the major Arctic river basins, potentially indicating model structural limitations. Coordinated efforts to address the ongoing challenges presented in this study will help reduce uncertainty in our capability to predict the future Arctic hydrological state and associated land–atmosphere biogeochemical processes across spatial and temporal scales.

Stratification dynamics in reservoirs have a great impact on ecosystem functioning and biogeochemical cycling, and can be strongly influenced by wind events. In this study, a well‐established one‐dimensional hydrodynamic model (GLM) was used to investigate the response of stratification dynamics in Rappbode Reservoir to different wind conditions, in particular to episodic strong wind events. In years with increased wind speed, stratification duration and intensity were reduced. Episodic wind forcing by strong wind events are important determinants of thermal structure and can induce persisting shifts in the thermal structure that remain over the season until the next overturn. The results showed that reductions in stratification intensity were particularly distinct when the strong wind occurred in early summer. Strong wind events outside of this sensitive time window did not exert an important impact on the thermal dynamics of the reservoir. Our research confirms the decisive impact of wind speed on stratification of lakes and reservoirs. It effectively illustrates the sensitive time window of thermal dynamics to episodic wind events.

Permafrost is characterized by low temperature, and its thermal stability is key to geohydrological cycles, energy exchange, and climate regulation. Increasing engineering activities, i.e., road construction and operations, are affecting the thermal stability in permafrost regions and have already led to the degradation of permafrost and caused environmental problems. To understand the spatiotemporal influence of road construction and operations on the thermal dynamics in permafrost regions, we conducted a study in the Ela Mountain Pass where multiple roads intersect on the Qinghai&ndash, Tibet Plateau (QTP) and calculated the thermal dynamics from 2000 to 2017 using normalized spectral entropy (measuring the disorderliness of time-series data). Our results indicate that road level is a significant influencing factor, where high-level roads (expressways) exhibit stronger thermal impacts than low-level roads (province- and county-level roads). Our results also indicate that duration of operation is the most significant factor that determines the thermal impacts of roads on permafrost: the thermal impacts of the newly paved expressway are positively related to elevation, while the thermal impacts of the old expressway are positively related to less vegetated areas. The study provides an excellent method for understanding the spatiotemporal impacts of engineering activities on the temperature dynamics in permafrost regions, thereby helping policymakers in China and other countries to better plan their infrastructure projects to avoid environmentally vulnerable regions. The study also calls for advanced techniques in road maintenance, which can reduce the accumulated disturbance of road operations on permafrost regions.

Changes in meteorological patterns to drier conditions alter the hydrodynamic processes of reservoirs and can affect their thermal structure. The aim of this study was to assess the impacts of a se...

The concerns of global warming effect have elevated the global inclination to interpret the mystery of surface temperature variations with respect to various aspects. Surface temperature (ST) plays a role as most substantial parameter in any environment. The effort attempts to present the satellite image processing methods for utilizing the state-of-the-art-enhanced adaptive technique (AET) to illustrate the spatial variability of ST. These methods can be helpful in computing the spatial variability at macro- to micro-scales. Therefore, spatial variability through AET was explored to demonstrate spatial scattering of surface temperatures. The outcomes seemingly revealed the aggregation and dispersion of spatial thermal configuration at the test area. The current work also presented the approach for assimilation of spatial variability information as a powerful reliable instrument to monitor the thermal dynamics within the region.

The existence of time delay usually results in the mismatch between the heat source output and the users’ heating load. In the research, a dynamic model is built to predict the supply water temperature in the substation and the heat loss from the heat source to the substation by identifying the time delay, α and β. α and β are parameters obtained by Regression. α is determined by the length of pipeline, velocity, heat transfer coefficient, etc., β is determined by outdoor air temperature besides those above elements. In the feasibility and prediction ability analysis of the model, two groups of tested supply water temperature in the substation are fitted well with the predicted supply water temperatures, respectively. Results show that the proposed method can improve the prediction accuracy of the supply water temperature in the heating substation, and the prediction error of the supply line heat loss can be restricted within -10%-2%. This indicates that the model have great ability in the temperature prediction and heat loss calculation.

Climate change in the Arctic is expected to have a major impact on stream ecosystems, affecting hydrological and thermal regimes. Although temperature is important to a range of in-stream processes, previous Arctic stream temperature research is limited—focused on glacierised headwaters in summer—with limited attention to snowmelt streams and winter. This is the first high-resolution study on stream temperature in north-east Greenland (Zackenberg). Data were collected from five streams from September 2013 to September 2015 (24 months). During the winter, streams were largely frozen solid and water temperature variability low. Spring ice-off date occurred simultaneously across all streams, but 11 days earlier in 2014 compared with 2015 due to thicker snow insulation. During summer, water temperature was highly variable and exhibited a strong relationship with meteorological variables, particularly incoming shortwave radiation and air temperature. Mean summer water temperature in these snowmelt streams was high compared with streams studied previously in Svalbard, yet was lower in Swedish Lapland, as was expected given latitude. With global warning, Arctic stream thermal variability may be less in summer and increased during the winter due to higher summer air temperature and elevated winter precipitation, and the spring and autumn ice-on and ice-off dates may extend the flowing water season—in turn affecting stream productivity and diversity.

Italian dry-stone wall terracing represents one of the most iconic features of agricultural landscapes across Europe, with sites listed among UNESCO World Heritage Sites and FAO Globally Important Agricultural Heritage Systems (GIAHS). The analysis of microclimate modifications induced by alterations of hillslope and by dry-stone walls is of particular interest for the valuation of benefits and drawbacks of terraces cultivation, a global land management technique. The aim of this paper is to perform a thermal characterization of a dry-stone wall terraced vineyard in the Chianti area (Tuscany, Italy), to detect possible microclimate dynamics induced by dry-stone terracing. The aerial surveys were carried out by using two sensors, in the Visible (VIS) and Thermal InfraRed (TIR) spectral range, mounted on Unmanned Aerial Vehicles (UAVs), with two different flights. Our results reveal that, in the morning, vineyard rows close to dry-stone walls have statistically lower temperatures with respect to the external ones. In the afternoon, due to solar insulation, temperatures raised to the same value for each row. The results of this early study, jointly with the latest developments in UAV and sensor technologies, justify and encourage further analyses on local climatic modifications in terraced landscapes.

Permafrost thermal conditions across the Qinghai⁻Tibet Engineering Corridor (QTEC) is of growing interest due to infrastructure development. Most modeling of the permafrost thermal regime has been conducted at coarser spatial resolution, which is not suitable for engineering construction in a warming climate. Here we model the spatial permafrost thermal dynamics across the QTEC from the 2010 to the 2060 using the ground thermal model. Soil properties are defined based on field measurements and ecosystem types. The climate forcing datasets are synthesized from MODIS-LST products and the reanalysis product of near-surface air temperature. The climate projections are based on long-term observations of air temperature across the QTEC. The comparison of model results to field measurements demonstrates a satisfactory agreement for the purpose of permafrost thermal modeling. The results indicate a discontinuous permafrost distribution in the QTEC. Mean annual ground temperatures (MAGT) are lowest (

The thermal dynamics of lakes are affected by climate change, and in turn affect most aspects of lake ecology, including primary and secondary production, biogeochemistry, and biodiversity. These effects may be particularly large in polymictic lakes which have variable durations and degrees of thermal stratification. A one-dimensional model, the Dynamic Reservoir Simulation Model (DYRESM), was used to evaluate the impacts of predicted climate change on temperature and stability in Oneida Lake, a 207 km 2 shallow, polymictic lake in central New York State. Field data were collected on stream temperature and discharge, weather, and lake temperatures at varying depths to calibrate and validate the model for Oneida Lake. Modeled temperatures at 2 m and 10 m were generally within ±1 °C of observed values, but only after wind speeds from a nearby airport were decreased by 25%. Downscaled climate data from three general circulation models and two emissions scenarios were used to assess the impacts of different anticipated climate scenarios on the lake for 2041–2050 and 2090–2099. By 2050, under the higher emissions scenario, water temperatures (April–November) at 2 m and 10 m depths indicated an increase of 1.36 °C and 1.43 °C, respectively; however, 2011 simulation temperatures already aligned with mid-century predictions. By the end of the century, the prediction of the higher emissions scenario indicated an increase in 2 m and 10 m water temperatures (April–November) of 3.70 °C and 3.37 °C, respectively, and an increase of 61 consecutive days of stratification in Oneida Lake. These impacts would lead to increased periods of lack of oxygen in the bottom waters of this lake and changes in the biotic species composition, including extirpation of a coldwater fish species, burbot ( Lota lota ). This study contributes to our understanding of the thermal regime of polymictic lakes in a warmer world.

The thermal inertia of aircraft cabins and galleys is significant for commercial aircraft. The aircraft cabin is controlled by the Environment Control System (ECS) to reach, among other targets, a prescribed temperature. By allowing a temperature band of ± 2 K instead of a fixed temperature, it is possible to use this thermal dynamic of the cabin as energy storage. This storage can then be used to reduce electrical peak power, increase efficiency of the ECS, reduce thermal cooling peak power, or reduce engine offtake if it is costly or not sufficiently available. In the same way, also the aircraft galleys can be exploited. Since ECS and galleys are among the largest consumers of electrical power or bleed air, there is a large potential on improving energy efficiency or reducing system mass to reduce fuel consumption of aircraft. This paper investigates different exploitation strategies of cabin and galley dynamics using modelling and simulation. Modelica models of the thermal and the electrical system are used to assess and compare these different strategies. Potential impacts on passenger comfort are discussed. Additionally, the gained performance is compared to more conventional storage elements like electrical batteries. Finally, the potential of fuel reduction will be quantified using a reference aircraft model and the optimal strategy is selected.

The spatiotemporal distribution characteristics of soil temperature are a significant, but seldom described signal of climate warming. This study examines the spatiotemporal trends in soil temperature at depths of 10, 20, and 50 cm in the conterminous US during 1948- 2008. We find a warming trend of between 0.2 and 0.4 °C at all depths from 1948 to 2008. The lowest soil temperatures are in Colorado and the area where Wyoming, Idaho, and Montana meet. The coastal areas, such as Texas, Florida, and California, experienced the highest soil temperature. In addition, areas that experienced weak cooling in summer soil temperature include Texas, Oklahoma, and Arkansas. Warming was recorded in Arizona, Nevada, and Oregon. In winter, Mississippi, Alabama, and Georgia show a cooling trend, and Montana, North Dakota, and South Dakota have been warming over the 61-year period. Additionally, mix-forest areas experience slightly cooler soil temperature in comparison with air temperature. Shrubland areas experience slightly warmer soiltemperaturein comparison with air temperature. This study is among the first to analyze the spatiotemporal distribution characteristics of soil temperature in the conterminous US by using multiple site observational data. Improved understanding of the spatially complex responses of soil temperature shall have significant implications for future studies in climate change over the region.

Biogeochemical feedback processes between soil organic carbon (SOC) in high-latitude organic soils and climate change is of great concern for projecting future climate. More accurate models of the SOC stock and its dynamics in organic soil are of increasing importance. As a first step toward creating a soil model that accurately represents SOC dynamics, we have created the Physical and Biogeochemical Soil Dynamics Model (PB-SDM) that couples a land surface model with a SOC dynamics model to simulate the feedback cycle of SOC accumulation and thermal hydrological dynamics of high-latitude soils. The model successfully simulated soil temperatures for observed data from a boreal forest near Fairbanks, and 2000 year simulations indicated that the effect of the feedback cycle of SOC accumulation on soil thickness would result in a significant differences in the amount of SOC.

This paper represents the beginning of a reference data base for the long term assessment and control of environmental impacts on the coral reef habitat of the Balhaf Bay, Gulf of Aden, following the development of an industrial complex on the bay. Present results reveal a high surface water temperature in summer with the tendency for relatively low temperature in the winter months. Bottom water temperature undergoes significant seasonal variation, with the annual difference at the two studied stations found to be up to 13.9 °C in the deep station (D), and 11 °C between August and September in the shallow station (F). Winter salinity variation was found not to exceed 0.5 g/l (measurements between 35.7 and 36.2 g/l), though salinity did vary seasonally: increasing at the beginning of the summer monsoon from 35.7 g/l to reach an annual maximum in this region (36.5 g/l) in the first days of July. The general lack of difference in the index of salinity for the studied depths is worth noting. Whatever the reason, such results call for more detailed studies of the habitats under reference.

The data-driven technique, evolutionary polynomial regression, has been tested and used for the study of water temperature behaviour in the River Barle (south-west England). The study aimed to produce multiple models for forecasting water temperature, using air temperature as input. In addition, river discharge data were used to describe the hydrological regime of the study stream, even if they are not involved in the modelling phase. The availability of data sampled at hourly intervals allowed behaviour to be studied at several time scales, including short-term lags between air temperature and water temperature. The approach to model building differs from previous studies in that the relationship between air temperature and water temperature is not evaluated on the basis of a multi-parameter regression, nor does it identify particular structures; rather the evolutionary technique identifies the model by itself. In fact, the non-linear relationship between air temperature and water temperature is investigated by an evolutionary search in the space of particular pseudo-polynomials structures.

Selective withdrawal systems can take advantage of thermal stratification in reservoirs to manage downstream temperatures. Selective withdrawal might also help adapt operations to environmental changes, such as increased stream temperatures expected with climate change. This exploratory study develops a linear programming model to release water from different thermal pools in reservoirs to minimize deviations from target downstream temperatures. The model is applied with representative thermal dynamics to Lake Spaulding, a multipurpose reservoir on the South Fork Yuba River in California with climate warming represented by uniform increases in air temperature. Optimization results for thermal pool management with selective withdrawal are compared to a single, low-level outlet release model. Optimal selective withdrawal hedges the winter release of cold water to decrease summer stream temperatures. With climate warming, selective withdrawal can help lessen stream warming in the summer but at a cost...

Water temperature controls many biochemical and ecological processes in rivers, and theoretically depends on multiple factors. Here we formulate a model to predict daily averaged river water temperature as a function of air temperature and discharge, with the latter variable being more relevant in some specific cases (e.g., snowmelt-fed rivers, rivers impacted by hydropower production). The model uses a hybrid formulation characterized by a physically based structure associated with a stochastic calibration of the parameters. The interpretation of the parameter values allows for better understanding of river thermal dynamics and the identification of the most relevant factors affecting it. The satisfactory agreement of different versions of the model with measurements in three different rivers (root mean square error smaller than 1oC, at a daily timescale) suggests that the proposed model can represent a useful tool to synthetically describe medium- and long-term behavior, and capture the changes induced by varying external conditions.

During the last several decades, the Great Lakes region has been experiencing a significant rise in temperatures, with the extraordinary summer warming that affected Lake Superior in 1998 as an example of the marked response of the lake to increasingly warmer atmospheric conditions. In this work, we combine the analysis of this exceptional event with some synthetic scenarios, to achieve a deeper understanding of the main processes driving the thermal dynamics of surface water temperature in Lake Superior. The analysis is performed by means of the lumped model air2water, which simulates lake surface temperature as a function of air temperature alone. The model provides information about the seasonal stratification dynamics, suggesting that unusual warming events can result from two factors: anomalously high summer air temperatures, and increased strength of stratification resulting from a warm spring. The relative contribution of the two factors is quantified using the model by means of synthetic scenarios, which provide a simple but effective description of the positive feedback between the thermal behavior and the stratification dynamics of the lake.

In this study, we use the one-dimensional hydrodynamic model DYRESM to simulate the Lake Kinneret thermal structure over a period of 45 months. We focus on the application of a new version of the one-dimensional hydrodynamic model to Lake Kinneret and simulation of the physical processes. DYRESM is calibration-free process-based model that simulates the vertical distribution of temperature and salinity in lakes and reservoirs. The current model is a complete rewrite of the original DYRESM code. Each algorithm was simplified to the essential minimum physical description yielding a more robust and faster model. The new model underwent validation with a high quality dataset from Lake Kinneret. The model simulation reproduced the temperature of the surface layer of the water column to within less than 1 °C. Results of a sensitivity analysis indicated that the surface and bottom water temperatures were most sensitive to changes in long-wave radiation. We conclude from the results that the simplified version of DYRESM accurately simulated the physical processes in the lake although planned inclusion of a benthic boundary-layer routine will improve the model’s ability to simulate the bottom temperatures.

The dynamics of permafrost soils is manifest in the soil temperature which can be measured with high accuracy and high temporal resolution. Using continuous data over a period of 778 days from a mineral hummock field at the Bayelva site, Svalbard, we deduce and quantify the processes which constitute the dynamics. In particular, conductive heat flux, generation of heat from phase transitions, and migration of water vapor are analyzed. Support for the interpretation of the data comes from high-resolution time domain reflectometry measurements of the liquid water content.

EOLE is a hydrodynamic thermal model (one-dimensional vertical model) which simulates the evolution of the seasonal thermal stratification of a reservoir. It is a model based on representation of individual physical mechanisms, which takes into account the bathymetry of the reservoir, surface energy exchanges, and throughflow in the reservoir (rivers, pumping, turbining, residual stream flow, etc.). EOLE was applied to two reservoirs with extremely different characteristics: Pareloup Lake, a hydroelectric reservoir with a long residence time (1 year), and Rochebut, a reservoir with a short residence time (1 month). The good agreement between the calculated and measured thermal profiles in both cases indicates that the model enables very good reproduction of the thermal stratification in each reservoir, the vertical dynamics of water masses, the thermal regime of water restituted downstream, and year-to-year fluctuations over extended periods (12 consecutive 1 year cycles for Pareloup). The model was applied using the same set of coefficients in both studies, demonstrating that the predominant hydrodynamic phenomena in both reservoirs are well taken into account, providing the input data are sufficiently representative of the site under study. The precision of the results obtained and the relative simplicity of the EOLE representation have enabled us to use the model as a basic structure for modeling of an ecosystem.

Researches about thermal dynamics of the wetlands soil has not been explored in order to have a better understanding of this dynamic in the region, m...

Climate change, in particular the increase in air temperature, has been shown to influence lake thermal dynamics, with climatic warming resulting in higher surface temperatures, stronger stratification, and altered mixing regimes. Less studied is the influence on lake thermal dynamics of atmospheric stilling, the decrease in near-surface wind speed observed in recent decades. Here we use a lake model to assess the influence of atmospheric stilling, on lake thermal dynamics across the Northern Hemisphere. From 1980 to 2016, lake thermal responses to warming have accelerated as a result of atmospheric stilling. Lake surface temperatures and thermal stability have changed at respective rates of 0.33 and 0.38 °C/decade, with atmospheric stilling contributing 15% and 27% of the calculated changes, respectively. Atmospheric stilling also resulted in a lengthening of stratification, contributing 23% of the calculated changes. Our results demonstrate that atmospheric stilling has influenced lake thermal responses to warming., This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie grant agreement No. 791812. C. A.‐M. received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska‐Curie Grant agreement 703733. The authors acknowledge the European Space Agency funding of the ARC‐Lake project.