Earth's energy budget

Summary

Earth's energy budget accounts for the balance between the energy that Earth receives from the Sun and the energy the Earth loses back into outer space. Smaller energy sources, such as Earth's internal heat, are taken into consideration, but make a tiny contribution compared to solar energy. The energy budget also accounts for how energy moves through the climate system. Because the Sun heats the equatorial tropics more than the polar regions, received solar irradiance is unevenly distributed. As the energy seeks equilibrium across the planet, it drives interactions in Earth's climate system, i.e., Earth's water, ice, atmosphere, rocky crust, and all living things. The result is Earth's climate. Earth's energy budget depends on many factors, such as atmospheric aerosols, greenhouse gases, the planet's surface albedo (reflectivity), clouds, vegetation, land use patterns, and more. When the incoming and outgoing energy fluxes are in balance, Earth is in radiative equilibrium and the climate system will be relatively stable. Global warming occurs when earth receives more energy than it gives back to space, and global cooling takes place when the outgoing energy is greater. Multiple types of measurements and observations show a warming imbalance since at least year 1970. The rate of heating from this human-caused event is without precedent. When the energy budget changes, there is a delay before average global surface temperature changes significantly. This is due to the thermal inertia of the oceans, land and cryosphere. Accurate quantification of these energy flows and storage amounts is a requirement within most climate models. In spite of the enormous transfers of energy into and from the Earth, it maintains a relatively constant temperature because, as a whole, there is little net gain or loss: Earth emits via atmospheric and terrestrial radiation (shifted to longer electromagnetic wavelengths) to space about the same amount of energy as it receives via solar insolation (all forms of electromagnetic radiation).

Official source

https://en.wikipedia.org/wiki/Earth's_energy_budget

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (3)

Related people (4)

Related units (3)

Related concepts (66)

Related courses (8)

Related lectures (102)

, , , , , ,

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

2022

The energy efficiency of the urban texture relies notably on the buildings’ form, which characterizes its capability to take profit of the solar potential as well as its loss of energy through the envelope. Therefore, the general layout at the district scale has a significant impact on the global energy balance in a dense built environment, where the relative position of the adjacent buildings generate shadowing and inter-reflection on a large part of the incoming solar radiation. In the current work, an urban energy simulator named CitySim is used together with a hybrid evolutionary algorithm. The physical model within CitySim features the computation of shortwave radiation including reflections, longwave radiation and a nodal thermal model for the building energy flows. The complete simulation leads to a rather precise evaluation of the annual heating needs, defined as the objective function to be minimized at the district scale. An existing district in Paris is taken as case study: the Bercy park front. Its buildings are disposed in several blocks surrounding courtyards with openings on the park’s side (southwest). This district is recent (1994-2005) and located in a dense area of seven stories buildings. In its original design, the access to sunlight was taken into account by the planner, thus the initial intuition of the architect is compared with optimized configurations. The paper describes a case of urban form optimization, with the formal description of the variables, constraints and objectives of the problem and the definition of the geometrical case for Bercy Front Park. The optimization variables focus on geometrical properties such as the height of the buildings and glazing ratios. The thermal properties of the building (insulation, glazing type) are set in accordance with the French standards of the thermal regulation (RT2005). The urban layouts resulting of the optimization process are analyzed and discussed.

EPFL Solar Energy and Building Physics Laboratory (LESO-PB)2013

Atmospheric aerosol is defined as a suspension of solid or liquid particles in air. The major concerns about aerosol particles are their adverse health effects and their role in the Earth's climate system. Atmospheric particles influence the Earth's radiation budget in two ways: either directly by scattering and absorbing incoming solar radiation (and to a far less extent longwave radiation emitted from the Earth) or indirectly by their ability to act as cloud condensation nuclei (CCN). With increasing particle concentrations, caused by, e.g., anthropogenic emissions, more CCN are available to form cloud droplets. For a fixed water content in the atmosphere this leads to more but smaller droplets and therefore to enhanced cloud albedos as well as to rain suppression. Both effects have been recognized in recent years to be of great importance for understanding the observed climate change. Nevertheless, they remain poorly understood and quantified. The Jungfraujoch (JFJ, 3580 m asl; 46.548°N, 7.984°E) High Alpine Research Station is equipped with instruments that have for decades performed important Global Climate Observations. A major part of the aerosol instruments perform in-situ measurements. However, due to the harsh weather conditions, they usually cannot be run outdoors. The ambient air has to be inducted into a housing, such that the aerosol is sampled at a temperature (T) and relative humidity (RH) different from the ambient values. Therefore, the measured aerosol properties may considerably differ from the ambient — the climate-relevant — ones. During the first Cloud and Aerosol Characterization Experiment (CLACE) at the JFJ in-situ aerosol size distributions were measured simultaneously indoor at dry conditions (T ≈ 25 °C and RH < 10%) and, for the first time in such an exposed place, outdoor at ambient conditions (T < –5 °C) by means of two scanning mobility particle sizers (SMPS). The data set was completed by measurements of hygroscopic growth factors using a hygroscopicity tandem differential mobility analyzer (H-TDMA). A comparison of dry and ambient size distributions shows two main features: First, the dry total number concentration is often considerably smaller (on average 28%) than the ambient total number concentration. This is most likely due to the evaporation of volatile material at the higher indoor temperature. These particle losses mainly concern small particles (dry diameter Ddry ≤ 100 nm), and therefore have only a minimal affect on the surface and volume concentrations. Second, the dry number size distribution is shifted towards smaller particles, reflecting the hygroscopic behavior of the aerosols. This shift was modeled using a modified Köhler equation adapted to the measured hygroscopic growth factors. The corrected dry surface and volume concentrations are in good agreement with the ambient measurements for the whole RH range, but the correction works best for RH < 80%. The results indicate that size distribution data measured at indoor conditions (i.e. dry and warm) may be successfully corrected to reflect ambient conditions. By combining these results with earlier JFJ aerosol measurements (e.g. chemical composition), it was possible to model dry and ambient optical aerosol properties for a summer and a winter case. The model calculations were based on a total of 496 size distributions representative for the JFJ aerosol, hygroscopic growth parameterizations and the following simplified aerosol structures: The fine mode (Ddry ≤ 1 µm) aerosol was assumed to consist of a water-insoluble spherical core concentrically encased by a coating comprising all water-soluble compounds, and the coarse mode (Ddry > 1 µm) particles were assumed to be water-insoluble homogeneous spheres. Ambient scattering coefficients σsca(RH) were found to be considerably different from the dry scattering coefficients σsca(RH = 0). The scattering enhancement factors ξ(RH) = σsca(RH)/σsca(RH = 0) strongly depend on the particle size. At RH = 85% they vary for example between ≈ 1.2 and ≈ 3.8. It was possible to establish a parameterization of ξ(RH) with the dry Ångström exponent å (based on scattering only). Since å follows directly from the dry scattering measurements, the parameterization allows to derive ambient scattering coefficients from the dry scattering coefficients without the need of any additional measurement other than ambient RH. RH also affects the absorption coefficient σabs. Depending on particle size and wavelength (investigated between 370 nm and 950 nm) absorption enhancement factors χ(RH) = σabs(RH)/σabs(RH = 0) were found to range from 0.84 to 1.78. However, it was possible to demonstrate that, even though the humidity effect on absorption is substantial, its contribution to the humidity effect on extinction and the single scattering albedo is negligible at the JFJ. The EPFL Raman lidar installed at the JFJ provides profiles of extinction and backscattering coefficients at the wavelengths 355 nm, 532 nm and 1064 nm for altitudes between typically 4 km and 15 km asl. These measurements are ambient but afflicted with more uncertainties than the dry in-situ measurements. A method was developed to derive microphysical aerosol properties from optical lidar data. This is a so-called ill-posed problem, i.e., small errors in the lidar data lead to huge errors in the inverted microphysical properties, unless special mathematical tools are applied. Therefore the method makes use of regularization techniques. It is shown that microphysical parameters can be inverted with acceptable accuracy from an optical dataset as it is provided by a lidar of e.g. the EPFL type.

EPFL2004