Heat Content Research Articles

The Mechanical Equivalent of Heat Interpreted as the Angular Momentum of Thermons

There were derived many forms of theories of heat during the past three hundred years. At its origins, thermodynamics was the study of heat and engines and therefore, we should be connected to these roots. In this model we present thermons as carriers of heat from hot bodies to cold bodies. The flow of heat is modelled as the transfer of angular momentum of these thermons in the direction from the higher angular momentum to the lower angular momentum of thermons. The mechanical equivalent of heat J is defined as the ratio of the angular momentum of thermons to the temperature of the surrounding. This model newly defines the quantity of heat – entropy S – as the ratio of the angular momentum of thermons to the temperature of the surrounding. This model can open a new window to the microworld where quantum particles transfer their heat content in one direction. However, this direction can be changed via the work done on these quantum particles and to reverse the flow of the angular momentum from lower angular momentum to higher angular momentum of those quantum particles. It will be shown that these very well-known formulae of S to all scholars might still keep some hidden surprising properties.

The modelled climatic response to the 18.6-year lunar nodal cycle and its role in decadal temperature trends

Abstract. The 18.6-year lunar nodal cycle arises from variations in the angle of the Moon's orbital plane. Previous work has linked the nodal cycle to climate but has been limited by either the length of observations analysed or geographical regions considered in model simulations of the pre-industrial period. Here we examine the global effect of the lunar nodal cycle in multi-centennial climate model simulations of the pre-industrial period. We find cyclic signals in global and regional surface air temperature (with amplitudes of around 0.1 K) and in ocean heat uptake and ocean heat content. The timing of anomalies of global surface air temperature and heat uptake is consistent with the so-called slowdown in global warming in the first decade of the 21st century. The lunar nodal cycle causes variations in mean sea level pressure exceeding 0.5 hPa in the Nordic Seas region, thus affecting the North Atlantic Oscillation during boreal winter. Our results suggest that the contribution of the lunar nodal cycle to global temperature should be negative in the mid-2020s before becoming positive again in the early 2030s, reducing the uncertainty in time at which projected global temperature reaches 1.5 ∘C above pre-industrial levels.

EFFICIENT USE OF STEAM THERMAL ENERGY

The results of theoretical studies of the use of selective steam of various parameters in consumer installations
 are presented. The values of heat losses during the transportation of steam to the consumer are determined.
 Heat losses during transportation are insignificant and do not exceed 0.05%. A TH-diagram of the thermodynamic
 process of operation of selected steam during adiabatic expansion and condensation is presented. It is shown that
 the main share of the thermal energy of steam is determined by the process of its condensation (up to 90% of the
 initial heat content). To convert the thermal energy of the selected steam into mechanical energy during its adiabatic
 expansion in the drive turbines of the consumer, it is necessary to choose the steam of the highest pressure.
 This will allow saving up to 50% of heat compared to low pressure steam. An exergy analysis of the system for
 the use of selective steam prior to its condensation has been carried out. The degree of thermodynamic perfection
 of steam use in this area is 45%.
 
 The steam parameters for heat exchange units with condensation are determined by the temperature difference
 in the final section of the heat exchange path; otherwise, the initial steam parameters are practically
 indifferent to them. The main requirement for such installations is the presence of a steam trap in the condensate
 removal path and a reliable system for diagnosing its technical condition.

Rectified Ocean Heat Uptake from Oscillatory Surface Forcing

Abstract Ocean heat uptake is asymmetric with respect to the sign of radiative forcing. It is already known that surface cooling anomalies penetrate into the ocean faster than surface warming anomalies. Because of this asymmetry, the time-variable component of radiative forcing can induce a long-term, rectified cooling trend in ocean heat content, which is this work’s primary focus. Here, we explore this asymmetry and rectification on global and interannual scales, its implications, and its possible dependence on model parameters. We do so using a full-complexity global ocean–sea ice general circulation model and an idealized one-dimensional vertical mixing model, both forced with idealized abrupt and oscillatory surface forcing anomalies. In both models, the ocean heat uptake response to an abrupt cooling perturbation is larger than an equal-magnitude warming perturbation. This asymmetry is shown to be larger when the background vertical diffusivity is smaller, and is therefore likely model dependent. Sinusoidal oscillatory forcing with zero time mean induces a rectified cooling trend in both models, whose magnitude depends on both the diffusivity and the frequency of the interannual oscillatory forcing. The net rectified cooling can reach a rate of approximately −0.11 W m−2, which is substantial relative to the estimated anthropogenic warming rate of 0.47 W m−2 (von Schuckmann et al.). We discuss this rectification effect in the context of volcanic forcing in climate models, whose time-variable component may cause model-dependent ocean cooling in CMIP6 historical simulations, reaching 5%–30% the size of the total impact of volcanic forcing in our one-dimensional model. Correcting for this cooling may help reduce uncertainties in modeled ocean heat content evolution.

Upper-Oceanic Warming in the Gulf of Mexico between 1950 and 2020

Abstract We estimate ocean heat content (OHC) change in the upper 2000 m in the Gulf of Mexico (GOM) from 1950 to 2020 to improve understanding of regional warming. Our estimates are based on 192 890 temperature profiles from the World Ocean Database. Warming occurs at all depths and in most regions except for a small region at northeastern GOM between 200 and 600 m. GOM OHC in the upper 2000 m increases at a rate of 0.38 ± 0.13 ZJ decade−1 between 1970 and 2020, which is equivalent to 1.21 ± 0.41 terawatts (TW). The GOM sea surface temperature (SST) increased ∼1.0° ± 0.25°C between 1970 and 2020, equivalent to a warming rate of 0.19° ± 0.05°C decade−1. Although SST in the GOM increases at a rate approximately twice that for the global ocean, the full-depth ocean heat storage rate in the GOM (0.86 ± 0.26 W m−2) applied to the entire GOM surface is comparable to that for the global ocean (0.82–1.11 W m−2). The upper-1000-m layer accounts for approximately 80%–90% of the total warming and variations in the upper 2000 m in the GOM. The Loop Current advective net heat flux is estimated to be 40.7 ± 6.3 TW through the GOM. A heat budget analysis shows the difference between the advective heat flux and the ocean heat storage rate (1.76 ± 1.36 TW, 1992–2017) can be roughly balanced with the annual net surface heat flux from ECCO (−37.9 TW).

Laws of Physics Define the Insignificant Warming of Earth by CO2

This study provides temperature estimates about the effect of carbon dioxide (CO2) in warming the Earth’s atmosphere using readily available information. It compares the grams of water vapor per kilogram (kg) of dry air with the number of grams of CO2 per kg of dry air. This comparison is over a year for 20 representative areas of the Earth. It shows the grams of water vapor range from 0.1 to 44.0 times that of CO2. The increased heat content (enthalpy) of the atmosphere by CO2 causes a maximum temperature increase of 0.006oC from the Poles to the Equator. This amount is too small to measure. These quantitative results indicate that the Tropics, representing 39.8% of the Earth’s surface, contain almost three-quarters of the atmosphere’s water vapor. In contrast, the Arctic and Antarctic areas at the Poles have an estimated 0.9% of the atmosphere’s water vapor. Water vapor is the significant greenhouse gas that keeps the Earth from being a frozen planet.

A simple diagnostic based on sea surface height with an application to central Pacific ENSO

Abstract. We use output from a freely running NEMO model simulation for the equatorial Pacific to investigate the utility of linearly removing the local influence of vertical displacements of the thermocline from variations in sea surface height. We show that the resulting time series of residual sea surface height, denoted ηnlti, measures variations in near-surface heat content that are independent of the local vertical displacement of the thermocline and can arise from horizontal advection, surface heat flux, and diapycnal mixing processes. We find that the variance of ηnlti and its correlation with sea surface temperature are focused on the Niño4 region. Furthermore, ηnlti averaged over the Niño4 region is highly correlated with indices of central Pacific El Niño–Southern Oscillation (CP ENSO), and its variance in 21-year running windows shows a strong upward trend over the past 50 years, corresponding to the emergence of CP ENSO following the 1976/77 climate shift. We show that ηnlti can be estimated from observations, using satellite altimeter data and a linear multi-mode model. The time series of ηnlti, especially when estimated using the linear model, show pronounced westward propagation in the western equatorial Pacific, arguing for an important role for zonal advective feedback in the dynamics of CP ENSO, in particular for cold events. We also present evidence that the role of the thermocline displacement in influencing sea surface height increased strongly after 2000 in the eastern part of the Niño4 region, at a time when CP ENSO was particularly active. Finally, the diagnostic is easy to compute and can be easily applied to mooring data or coupled climate models.

Characterizing the Variability of Boundary Currents and Ocean Heat Content Around New Zealand Using a Multi‐Decadal High‐Resolution Regional Ocean Model

AbstractNew Zealand is located in the southwest Pacific Ocean and is surrounded by a complex system of boundary currents that vary on a variety of time scales, with important impacts on weather, primary productivity, and fisheries. While various observational and modeling studies have shed light on many of the characteristics of New Zealand's ocean circulation, this study provides a comprehensive, quantitative, seamless, 3‐dimensional characterization of the region's boundary current circulation and ocean heat content. We use a 28 yr long hydrodynamic model simulation that accurately represents the mean and variability of the ocean circulation to characterize and quantify the temporal and spatial variability across the region. We show that low‐frequency variability in boundary current transport and upper ocean heat content are correlated over the entire New Zealand oceanic region. Oceanic eddies dominate heat content variability at intra‐annual scales in the northeast of the region, while on the west and southeast coasts heat content varies predominantly at interannual scales controlled by large‐scale changes in the subtropical and sub‐Antarctic fronts. The model shows a significant downstream strengthening and deepening of the boundary currents off northeast New Zealand which, if confirmed by observations, could suggest a significant new understanding of this Western Boundary Current system. This study presents a region‐wide characterization of the temporal and spatial variability of ocean currents and heat content, and their interconnections, providing a vital basis for understanding climate change impacts and the increasing occurrence of marine heatwaves.

Improving Seasonal Prediction of Summer Precipitation in the Middle–Lower Reaches of the Yangtze River Using a TU-Net Deep Learning Approach

Abstract The two-step U-Net model (TU-Net) contains a western North Pacific subtropical high (WNPSH) prediction model and a precipitation prediction model fed by the WNPSH predictions, oceanic heat content, and surface temperature. The data-driven forecast model provides improved 4-month lead predictions of the WNPSH and precipitation in the middle and lower reaches of the Yangtze River (MLYR), which has important implications for water resources management and precipitation-related disaster prevention in China. When compared with five state-of-the-art dynamical climate models including the Climate Forecast System of Nanjing University of Information Science and Technology (NUIST-CFS1.0) and four models participating in the North American Multi-Model Ensemble (NMME) project, the TU-Net produces comparable skills in forecasting 4-month lead geopotential height and winds at the 500- and 850-hPa levels. For the 4-month lead prediction of precipitation over the MLYR region, the TU-Net has the best correlation scores and mean latitude-weighted RMSE in each summer month and in boreal summer [June–August (JJA)], and pattern correlation coefficient scores are slightly lower than the dynamical models only in June and JJA. In addition, the results show that the constructed TU-Net is also superior to most of the dynamical models in predicting 2-m air temperature in the MLYR region at a 4-month lead. Thus, the deep learning-based TU-Net model can provide a rapid and inexpensive way to improve the seasonal prediction of summer precipitation and 2-m air temperature over the MLYR region. Significance Statement The purpose of this study is to examine the seasonal predictive skill of the western North Pacific subtropical high anomalies and summer rainfall anomalies over the middle and lower reaches of the Yangtze River region by means of deep learning methods. Our deep learning model provides a rapid and inexpensive way to improve the seasonal prediction of summer precipitation as well as 2-m air temperature. The work has important implications for water resources management and precipitation-related disaster prevention in China and can be extended in the future to predict other climate variables as well.

Dirichlet Sub-Laplacians on Homogeneous Carnot Groups: Spectral Properties, Asymptotics, and Heat Content

Abstract We consider sub-Laplacians in open bounded sets in a homogeneous Carnot group and study their spectral properties. We prove that these operators have a pure point spectrum and prove the existence of the spectral gap. In addition, we give applications to the small ball problem for a hypoelliptic Brownian motion and the large time behavior of the heat content in a regular domain.

Heat Storage in the Upper Indian Ocean: The Role of Wind-Driven Redistribution

Abstract The heat content in the Indian Ocean has been increasing owing to anthropogenic greenhouse warming. Yet, where and how the anthropogenic heat is stored in the Indian Ocean have not been comprehended. Analysis of various observational and model-based datasets since the 1950s reveals a robust spatial pattern of the 0–700 m ocean heat content trend (ΔOHC), with enhanced warming in the subtropical southern Indian Ocean (SIO) but weak to minimal warming in the tropical Indian Ocean (TIO). The meridional temperature gradient between the TIO and SIO declined by 16.4% ± 7.5% during 1958–2014. The heat redistribution driven by time-varying surface winds plays a crucial role in shaping this ΔOHC pattern. Sensitivity experiments using a simplified ocean dynamical model suggest that changes in surface winds over the Indian Ocean, particularly those of the SIO, caused a convergence trend in the upper SIO and a divergence trend in the upper TIO. These wind changes primarily include the enhancements of westerlies in the Southern Ocean and the subtropical anticyclone in the SIO. Albeit with systematic biases, the ΔOHC pattern and surface wind changes simulated by phase 6 of the Coupled Model Intercomparison Project (CMIP6) models broadly resemble the observation and highlight the essence of external forcing in causing these changes. This heat storage pattern is projected to persist in the model-projected future, potentially impacting future climate.

Bias Correction and Statistical Modeling of Variable Oceanic Forcing of Greenland Outlet Glaciers

AbstractVariability in oceanic conditions directly impacts ice loss from marine outlet glaciers in Greenland, influencing the ice sheet mass balance. Oceanic conditions are available from Atmosphere‐Ocean Global Climate Model (AOGCM) output, but these models require extensive computational resources and lack the fine resolution needed to simulate ocean dynamics on the Greenland continental shelf and close to glacier marine termini. Here, we develop a statistical approach to generate ocean forcing for ice sheet model simulations, which incorporates natural spatiotemporal variability and anthropogenic changes. Starting from raw AOGCM ocean heat content, we apply: (a) a bias‐correction using ocean reanalysis, (b) an extrapolation accounting for on‐shelf ocean dynamics, and (c) stochastic time series models to generate realizations of natural variability. The bias‐correction reduces model errors by ∼25% when compared to independent in‐situ measurements. The bias‐corrected time series are subsequently extrapolated to fjord mouth locations using relations constrained from available high‐resolution regional ocean model results. The stochastic time series models reproduce the spatial correlation, characteristic timescales, and the amplitude of natural variability of bias‐corrected AOGCMs, but at negligible computational expense. We demonstrate the efficiency of this method by generating >6,000 time series of ocean forcing for >200 Greenland marine‐terminating glacier locations until 2100. As our method is computationally efficient and adaptable to any ocean model output and reanalysis product, it provides flexibility in exploring sensitivity to ocean conditions in Greenland ice sheet model simulations. We provide the output and workflow in an open‐source repository, and discuss advantages and future developments for our method.

Historical Ocean Heat Uptake in Two Pairs of CMIP6 Models: Global and Regional Perspectives

Abstract Ocean heat content (OHC) is one of the most relevant metrics tracking the current global heating. Therefore, simulated OHC time series are a cornerstone for assessing the scientific performance of Earth system models and global climate models. Here we present a detailed analysis of OHC change in simulations of the historical climate (1850–2014) performed with two pairs of CMIP6 models: U.K. Earth System Model 1 (UKESM1.0) and HadGEM3-GC3.1-LL, and CNRM-ESM2-1 and CNRM-CM6-1. The small number of models enables us to analyze OHC change globally and for individual ocean basins, making use of a novel ensemble of observational products. For the top 700 m of the global ocean, the two CNRM models reproduce the observed OHC change since the 1960s closely. The two U.K. models (UKESM1.0-LL and HadGEM3-GC3.1-LL) compensate a lack of warming in the 0–700 m layer in the 1970s and 1980s with warming below 2000 m. The observed warming between 700 and 2000 m is substantially underestimated by all models. An increased relevance for ocean heat uptake in the Atlantic after 1991—suggested by observations—is picked up by the U.K. models but less so by the CNRM models, probably related to an AMOC strengthening in the U.K. models. The regional ocean heat uptake characteristics differ even though all four models share the same ocean component (NEMO ORCA1). Differences in the simulated global, full-depth OHC time series can be attributed to differences in the model’s total effective radiative forcing.

The Potential of Landfill Waste in Rembang City as Raw Material for Refuse Derived Fuel (RDF)

The Landoh landfillwas expired in 2022 due to the increasing amount of waste generated. The solution is to extend the service life of the landfill using the landfill mining method. The waste in the landfill is used as raw material for refuse derived fuel (RDF). The aim of the research is to find out the potential of landfill mining at Landoh landfillwhether it can be used as raw material for RDF. Primary data was taken from Landoh landfill in February 2022 with a depth of 1-2 meters and 3-4 meters from the surface of the waste generation and interviews with landfill officials. The waste samples were analyzed for waste composition, moisture content, volatile content, ash content and heating content. The waste composition is dominated by organic waste which has a large moisture content but a small caloric content. From the results of the research that the waste needs to be pre-treated (chopping and drying) for 21 days in order to fulfil the standard values of moisture content, volatile content, ash content and calorific content according to RDF raw material requirements. This method is a solution to overcoming expired landfills, reducing the volume of waste and landfill area requairements.

Quantification of The Performance of CMIP6 Models for Dynamic Downscaling in The North Pacific and Northwest Pacific Oceans

Selecting a reliable global climate model as the driving forcing in simulations with dynamic downscaling is critical for obtaining a reliable regional ocean climate. With respect to their accuracy in providing physical quantities and long-term trends, we quantify the performances of 17 models from the Coupled Model Inter-comparison Project Phase 6 (CMIP6) over the North Pacific (NP) and Northwest Pacific (NWP) oceans for 1979–2014. Based on normalized evaluation measures, each model’s performance for a physical quantity is mainly quantified by the performance score (PS), which ranges from 0 to 100. Overall, the CMIP6 models reasonably reproduce the physical quantities of the driving variables and the warming ocean heat content and temperature trends. However, their performances significantly depend on the variables and region analyzed. The EC-Earth-Veg and CNRM-CM6-1 models show the best performances for the NP and NWP oceans, respectively, with the highest PS values of 85.89 and 76.97, respectively. The EC-Earth3 model series are less sensitive to the driving variables in the NP ocean, as reflected in their PS. The model performance is significantly dependent on the driving variables in the NWP ocean. Nevertheless, providing a better physical quantity does not correlate with a better performance for trend. However, MRI-ESM2-0 model shows a high performance for the physical quantity in the NWP ocean with warming trends similar to references, and it could thus be used as an appropriate driving forcing in dynamic downscaling of this ocean. This study provides objective information for studies involving dynamic downscaling of the NP and NWP oceans.

Bay of Bengal upper-ocean stratification and the sub-seasonal variability in convection: Role of rivers in a coupled ocean-atmosphere model

The Bay of Bengal (BoB) receives a large amount of freshwater from rains and rivers, resulting in large upper-ocean stratification due to the freshening effect. This salinity stratification has been theorized to impact sea-surface temperature (SST) and convection on intra-seasonal time scales by affecting the ocean mixed layer and the barrier layer. This article aims to quantify the impact of salinity stratification on the sub-seasonal variability in SST and convection by using in-situ ocean observations and coupled model experiments. It is shown that monsoon intra-seasonal oscillations (MISOs) exhibit varied levels of intra-seasonal variability in SST and rainfall based on the underlying ocean conditions. The largest intra-seasonal variability in SST does not cause the largest convection variability in the north-western BoB. Instead, moderate variability in SST and rainfall associated with MISOs co-occur with deep mixed layer and thick barrier layer conditions. Realistic representation of river freshwater fluxes in a coupled ocean-atmosphere model leads to improved intra-seasonal SST and rainfall variability. Thick barrier layers in the north-western Bay attenuates the entrainment cooling of the mixed layer, and the high mixed layer heat content provides conducive oceanic conditions for the genesis of monsoon low-pressure systems (LPS), thereby affecting rainfall over India. This study has important implications for operation forecasting using coupled models.

Forecast‐ready models to support fisheries' adaptation to global variability and change

AbstractOcean and climate drivers affect the distribution and abundance of marine life on a global scale. Marine ecological forecasting seeks to predict how living marine resources respond to physical variability and change, enabling proactive decision‐making to support climate adaptation. However, the skill of ecological forecasts is constrained by the skill of underlying models of both ocean state and species‐environment relationships. As a test of the skill of data‐driven forecasts for fisheries, we developed predictive models of catch‐per‐unit‐effort (CPUE) of tuna and billfish across the south‐west Pacific Ocean, using a 12‐year time series of catch data and a large ensemble climate reanalysis. Descriptors of water column structure, particularly temperature at depth and upper ocean heat content, emerged as useful predictors of CPUE across species. Enhancing forecast skill over sub‐seasonal to multi‐year timescales in any system is likely to require the inclusion of sub‐surface ocean data and explicit consideration of regional physical dynamics.

Современные особенности температурно-влажностного режима тропосферы в Сибирском секторе в различные циркуляционные периоды

The paper studies the long-term dynamics of air temperature and relative humidity anomaly indices in the surface layer and at different levels of the troposphere in Siberia and neighboring regions (European and Far Eastern sectors). As the main cause of the observed variations in climatic parameters we considered circulation factors, which were taken into account using the typification of macrocirculation processes proposed by B.L. Dzerdzeevsky. Seasonal differences were revealed in the distribution of anomaly indices and the area occupied by anomalies of different signs of annual and monthly mean temperature and relative air humidity, which are most pronounced during circulation periods of increased duration of meridional northern processes in the Siberian sector and in the Northern Hemisphere as a whole. The highest rates of change in the temperature regime in the Siberian sector over recent decades have been observed at the level of the isobaric surface AT–700 hPa (3 km), which affects the advective-dynamic factors of surface cyclo- and frontogenesis, as well as the processes of cloud formation and precipitation. In general, an increase in the heat content of the lower and middle troposphere and a decrease in the relative moisture content near the tropopause can be accompanied by an increase in the amount of the potential energy and convective instability energy reserves and can lead to an increase in climate risks in the Siberian sector.

Современные особенности температурно-влажностного режима тропосферы в Сибирском секторе в различные циркуляционные периоды

The paper studies the long-term dynamics of air temperature and relative humidity anomaly indices in the surface layer and at different levels of the troposphere in Siberia and neighboring regions (European and Far Eastern sectors). As the main cause of the observed variations in climatic parameters we considered circulation factors, which were taken into account using the typification of macrocirculation processes proposed by B.L. Dzerdzeevsky. Seasonal differences were revealed in the distribution of anomaly indices and the area occupied by anomalies of different signs of annual and monthly mean temperature and relative air humidity, which are most pronounced during circulation periods of increased duration of meridional northern processes in the Siberian sector and in the Northern Hemisphere as a whole. The highest rates of change in the temperature regime in the Siberian sector over recent decades have been observed at the level of the isobaric surface AT–700 hPa (3 km), which affects the advective-dynamic factors of surface cyclo- and frontogenesis, as well as the processes of cloud formation and precipitation. In general, an increase in the heat content of the lower and middle troposphere and a decrease in the relative moisture content near the tropopause can be accompanied by an increase in the amount of the potential energy and convective instability energy reserves and can lead to an increase in climate risks in the Siberian sector.

Ocean data assimilation for the initialization of seasonal prediction with the Community Earth System Model

Seasonal prediction highly depends on its initialization scheme. Currently, the operational utilization of advanced data assimilation methods in the oceanic initialization is still relatively less and its benefit is far from being fully unveiled. In this study, the Community Earth System Model (CESM) is configured with an Ensemble Adjustment Kalman Filter (EAKF) to initialize the seasonal prediction. The performance of the established prediction system is assessed by comparing it with a benchmark prediction system, which is based on the same model but with a nudging scheme. Results show that the assimilation of only oceanic observations can not only effectively constrain the oceanic variables, but also improves the atmospheric variables through coupling processes, which helps to produce accurate and compatible initial conditions. With the initial conditions, the current prediction system is better than the benchmark prediction system and can produce skillful predictions for sea surface temperature, ocean heat content, air temperature at 2 m, precipitation and major climate variabilities including El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The current prediction system also shows better ensemble consistency and less prediction drifts, which could contribute to the improvement of prediction skill.