Earth's Energy Balance Research Articles

Another point of view

Earth Observation Understanding Earth's energy balance is fundamental for understanding climate. The amount of solar energy incident on the top of the atmosphere is well known, but the outgoing radiative flux is more uncertain because traditional ground-based, aircraft, and satellite instruments see only a fraction of Earth at a time, and their data must be extrapolated, interpolated, or combined to create a whole-planet picture. Carlson et al. present measurements made by the instrument NISTAR, which can see all of Earth at once because it is located at the Lagrangian L-1 point 1.6 million miles in the direction of the Sun. This allows them to determine the total outgoing radiation flux and its spectrum at subseasonal resolution. Geophys. Res. Lett. 10.1029/2019GL083736 (2019).

What Drives the Life Cycle of Tropical Anvil Clouds?

AbstractThe net radiative effects of tropical clouds are determined by the evolution of thick, freshly detrained anvil clouds into thin anvil clouds. Thick anvil clouds reduce Earth's energy balance and cool the climate, while thin anvil clouds warm the climate. To determine role of these clouds in climate change we need to understand how interactions of their microphysical and macrophysical properties control their radiative properties. We explore anvil cloud evolution using a cloud‐resolving model in three‐simulation setups of increasing complexity to disentangle the impacts of the various components of diabatic heating and their interaction with cloud‐scale motions. The first phase of evolution and rapid cloud spreading is dominated by latent heating within convective updrafts. After the convective detrainment stops, most of the spreading and thinning of the anvil cloud is driven by cloud radiative processes and latent heating. The combination of radiative cooling at cloud top, latent cooling due to sublimation at cloud base, latent heating due to deposition and radiative heating in between leads to a sandwich‐like, cooling‐heating‐cooling structure. The heating sandwich promotes the development of two within‐anvil convective layers and a double cell circulation, dominated by strong outflow at 12‐km altitude with inflow above and below. Our study reveals how small‐scale processes including convective, microphysical processes, latent and radiative heating interact within the anvil cloud system. The absence or a different representation of only one component results in a significantly different cloud evolution with large impacts on cloud radiative effects.

Contrasting Response of Precipitation to Aerosol Perturbation in the Tropics and Extratropics Explained by Energy Budget Considerations.

Precipitation plays a crucial role in the Earth's energy balance, the water cycle, and the global atmospheric circulation. Aerosols, by direct interaction with radiation and by serving as cloud condensation nuclei, may affect clouds and rain formation. This effect can be examined in terms of energetic constraints, that is, any aerosol‐driven diabatic heating/cooling of the atmosphere will have to be balanced by changes in precipitation, radiative fluxes, or divergence of dry static energy. Using an aqua‐planet general circulation model (GCM), we show that tropical and extratropical precipitation have contrasting responses to aerosol perturbations. This behavior can be explained by contrasting ability of the atmosphere to diverge excess dry static energy in the two different regions. It is shown that atmospheric heating in the tropics leads to large‐scale thermally driven circulation and a large increase in precipitation, while the excess energy from heating in the extratropics is constrained due to the effect of the Coriolis force, causing the precipitation to decrease.

The energy balance of Earth’s tectonosphere

Concentrations of K, U, and Th in rocks of the Earth’s crust and upper mantle of platforms, geosynclines, and oceans have been analyzed. Respective values of radiogenic heat generation in upper mantle rocks of the aforementioned types of regions are 0.04, 0.06, and 0.08 μW/m3. As far as platforms are concerned, heat generation there has been found to correlate with geological history, heat flow, and deep-seated temperatures. The energy preservation law in geological processes has been shown to hold.

Substantial Reductions in Cloud Cover and Moisture Transport by Dynamic Plant Responses

AbstractCumulus clouds make a significant contribution to the Earth's energy balance and hydrological cycle and are a major source of uncertainty in climate projections. Reducing uncertainty by expanding our understanding of the processes that drive cumulus convection is vital to the accurate identification of future global and regional climate impacts. Here we adopt an interdisciplinary approach that integrates interrelated scales from plant physiology to atmospheric turbulence. Our explicit simulations mimic the land‐atmosphere approach implemented in current numerical weather prediction, and global climate models enable us to conclude that neglecting local plant dynamic responses leads to misrepresentations in the cloud cover and midtropospheric moisture convection of up to 21% and 56%, respectively. Our approach offers insights into the key role played by the active vegetation on atmospheric convective mixing that has recently been identified as the source of half of the variance in global warming projections (i.e., equilibrium climate sensitivity).

Detection and interpretation of clouds types using visible and infrared satellite images

One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature differences. The data are taken by (MODIS), (GOES) and (METEOSAT) because these satellites are forecasting in a near lifetime data. The case studied in 24/12/2016 over the area of Iraq.

CloudNet: Ground‐Based Cloud Classification With Deep Convolutional Neural Network

AbstractClouds have an enormous influence on the Earth's energy balance, climate, and weather. Cloud types have different cloud radiative effects, which is an essential indicator of the cloud effect on radiation. Therefore, identifying the cloud type is important in meteorology. In this letter, we propose a new convolutional neural network model, called CloudNet, for accurate ground‐based meteorological cloud classification. We build a ground‐based cloud data set, called Cirrus Cumulus Stratus Nimbus, which consists of 11 categories under meteorological standards. The total number of cloud images is three times that of the previous database. In particular, it is the first time that contrails, a type of cloud generated by human activity, have been taken into account in the ground‐based cloud classification, making the Cirrus Cumulus Stratus Nimbus data set more discriminative and comprehensive than existing ground‐based cloud databases. The evaluation of a large number of experiments demonstrates that the proposed CloudNet model could achieve good performance in meteorological cloud classification.

The cloud-free global energy balance and inferred cloud radiative effects: an assessment based on direct observations and climate models

In recent studies we quantified the global mean Earth energy balance based on direct observations from surface and space. Here we infer complementary reference estimates for its components specifically under cloud-free conditions. While the clear-sky fluxes at the top of atmosphere (TOA) are accurately known from satellite measurements, the corresponding fluxes at the Earth’s surface are not equally well established, as they cannot be directly measured from space. This is also evident in 38 global climate models from CMIP5, which are shown to greatly vary in their clear-sky surface radiation budgets. To better constrain the latter, we established new clear-sky reference climatologies of surface downward shortwave and longwave radiative fluxes from worldwide distributed Baseline Surface Radiation Network sites. 33 out of the 38 CMIP5 models overestimate the clear-sky downward shortwave reference climatologies, whereas both substantial overestimations and underestimations are found in the longwave counterparts in some of the models. From the bias structure of the CMIP5 models we infer best estimates for the global mean surface downward clear-sky shortwave and longwave radiation, at 247 and 314 Wm−2, respectively. With a global mean surface albedo of 13.5% and net shortwave clear-sky flux of 287 Wm−2 at the TOA this results in a global mean clear-sky surface and atmospheric shortwave absorption of 214 and 73 Wm−2, respectively. From the newly-established diagrams of the global energy balance under clear-sky and all-sky conditions, we quantify the cloud radiative effects not only at the TOA, but also within the atmosphere and at the surface.

Global land change from 1982 to 2016.

Land change is a cause and consequence of global environmental change1,2. Changes in land use and land cover considerably alter the Earth's energy balance and biogeochemical cycles, which contributes to climate change and-in turn-affects land surface properties and the provision of ecosystem services1-4. However, quantification of global land change is lacking. Here we analyse 35years' worth of satellite data and provide a comprehensive record of global land-change dynamics during the period 1982-2016. We show that-contrary to the prevailing view that forest area has declined globally5-tree cover has increased by 2.24millionkm2 (+7.1% relative to the 1982 level). This overall net gain is the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16millionkm2 (-3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover. The mapped land changes and the driver attributions reflect a human-dominated Earth system. The dataset we developed may be used to improve the modelling of land-use changes, biogeochemical cycles and vegetation-climate interactions to advance our understanding of global environmental change1-4,6.

Projections of actual evapotranspiration under the 1.5 °C and 2.0 °C global warming scenarios in sandy areas in northern China

Actual evapotranspiration (ETa) is an essential component of Earth's global energy balance and water cycle. The Paris Agreement aspires to limit global mean surface warming to <2 °C and no >1.5 °C relative to preindustrial levels. However, it is uncertain how this global level will impact the shifts in the extents of sandy areas caused by global desertification. Using Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) datasets and advection-aridity models, we investigated the spatiotemporal features of ETa in sandy areas in northern China under global warming scenarios of 1.5 °C and 2.0 °C. The four climate models indicated significant increases in ETa in arid areas across northwestern China. Over time, the ETa value under only the representative concentration pathway 2.6 (RCP2.6) emission scenario increased towards a plateau and significantly increased in the other three emission scenarios (P < 0.01) under global warming of 1.5 °C and 2.0 °C. In terms of the spatial variations, ETa showed an increasing trend in all seasons except winter. The maximum ETa was 84.61 mm, and high values were mainly located in the southeast of the study area. Precipitation and the normalized difference vegetation index (NDVI) showed good correlations with ETa in the sandy areas in northern China. The sandy areas in northern China showed decreasing trends (0.45 km2/a) from 1980 to 2015. Under global warming of 2.0 °C (2040–2059) relative to that of 1.5 °C (2020–2039), the area of sandy land will increase at a rate of 27.04 km2 per decade (P < 0.01); after this period, the sandy land area in northern China may gradually stabilize, with a trend of 0.02 km2/a (2047–2100). Early efforts to achieve the 1.5 °C temperature goal could therefore markedly reduce the likelihood that large regions will face substantial global desertification and the related impacts.

The influence of internal variability on Earth's energy balance framework and implications for estimating climate sensitivity

Abstract. Our climate is constrained by the balance between solar energy absorbed by the Earth and terrestrial energy radiated to space. This energy balance has been widely used to infer equilibrium climate sensitivity (ECS) from observations of 20th-century warming. Such estimates yield lower values than other methods, and these have been influential in pushing down the consensus ECS range in recent assessments. Here we test the method using a 100-member ensemble of the Max Planck Institute Earth System Model (MPI-ESM1.1) simulations of the period 1850–2005 with known forcing. We calculate ECS in each ensemble member using energy balance, yielding values ranging from 2.1 to 3.9 K. The spread in the ensemble is related to the central assumption in the energy budget framework: that global average surface temperature anomalies are indicative of anomalies in outgoing energy (either of terrestrial origin or reflected solar energy). We find that this assumption is not well supported over the historical temperature record in the model ensemble or more recent satellite observations. We find that framing energy balance in terms of 500 hPa tropical temperature better describes the planet's energy balance.

Estimation of atmospheric columnar organic matter (OM) mass concentration from remote sensing measurements of aerosol spectral refractive indices

Aerosols have adverse effects on human health and air quality, changing Earth's energy balance and lead to climate change. The components of aerosol are important because of the different spectral characteristics. Based on the low hygroscopic and high scattering properties of organic matter (OM) in fine modal atmospheric aerosols, we develop an inversion algorithm using remote sensing to obtain aerosol components including black carbon (BC), organic matter (OM), ammonium nitrate-like (AN), dust-like (DU) components and aerosol water content (AW). In the algorithm, the microphysical characteristics (i.e. volume distribution and complex refractive index) of particulates are preliminarily separated to fine and coarse modes, and then aerosol components are retrieved using bimodal parameters. We execute the algorithm using remote sensing measurements of sun-sky radiometer at AERONET site (Beijing RADI) in a period from October of 2014 to January of 2015. The results show a reasonable distribution of aerosol components and a good fit for spectral feature calculations. The mean OM mass concentration in atmospheric column is account for 14.93% of the total and 56.34% of dry and fine-mode aerosol, being a fairly good correlation (R = 0.56) with the in situ observations near the surface layer.

Comparison of methodologies for cloud cover estimation in Brazil - A case study

Clouds are the major modulator of the shortwave and longwave radiation components of the Earth's energy balance and, as such, help to regulate the planet's temperature. In the energy sector, clouds are a source of instability in the generation of energy using solar technologies. This study aims at comparing three approaches to get cloud cover information in the Southeastern region of Brazil during the period of approximately three months. The first method, assumed as reference, uses all-sky camera pictures for the cloud cover estimation. The other two methodologies use downward longwave radiation with surface meteorological data and geostationary satellite data. Both methods presented good agreement with the camera for clear sky and overcast conditions, with probabilities of detection of 92.8% and 80.7% for the longwave method and 93.3% and 87.6% for the satellite method, respectively. The major problem occurs with the broken-clouds sky scenario, with probabilities of detection above 38%, where each method has its own specificity, such as, longwave emissivity of the atmosphere, spatial resolution and view geometry. The long-wave method has the minor R correlation with the camera (87%) when compared with the satellite method (93%) and requires a daily normalization, which make it not usable for instantaneous measurements. Regarding the satellite method, the most important issue is the spatial resolution, which has the major impact on the broken-clouds sky scenarios. The cloud masking works properly for large clouds with, at least, the size comparable to the satellite image pixel. Furthermore, the method using the all-sky camera also needs to be improved, because it presented some deficiencies, like very bright areas around the sun, sometimes identified as clouds, leading to cloud cover overestimation.

Estimating Evapotranspiration From Satellite Using Easily Obtainable Variables: A case study over the Southern Great Plains, U.S.A.

Evapotranspiration (ET) is a critical component of the Earth's water budget, a critical modulator of land-atmosphere (L-A) interactions, and also plays a crucial role in managing the Earth's energy balance. In this study, the feasibility of generating spatially-continuous daily evaporative fraction (EF) and ET from minimal remotely-sensed and meteorological inputs in a trapezoidal framework is demonstrated. A total of four variables, Normalized Difference Vegetation Index (NDVI), Land surface temperature (Ts ), gridded daily average temperature (Ta ) and elevation (z) are required to estimate EF. Then, ET can be estimated with the available soil heat flux (G) and net radiation (Rn) data. Firstly, the crucial model variable, Ts - Ta , is examined how well it characterizes the variation in EF using in situ data recorded at two eddy correlation flux towers in Southern Great Plains, U.S.A in 2011. Next, accuracy of satellite-based Ts are compared to ground-based Ts . Finally, EF and ET estimates are validated. The results reveal that the model performed satisfactorily in modeling EF and ET variation at winter wheat and deciduous forest during the high evaporative months. Even though the model works best with the observed MODIS-Ts as opposed to temporally interpolated Ts , results obtained from interpolated Ts are able to close the gaps with reasonable accuracy. Due to the fact that Ts - Ta , is not a good indicator of EF outside the growing season when deciduous forest is dormant, potential improvements to the model are proposed to improve accuracy in EF and ET estimates at the expense of adding more variables.

A simple model of snow albedo decay using observations from the Community Collaborative Rain, Hail, and Snow-Albedo (CoCoRaHS-Albedo) Network

ABSTRACTThe albedo of seasonal snow cover plays an important role in the global climate system due to its influence on Earth's radiation budget and energy balance. Volunteer Community Collaborative Rain, Hail, and Snow-Albedo (CoCoRaHS-Albedo) observers collected 3249 individual daily albedo, snow depth and density measurements using standardized techniques at dozens of sites across New Hampshire, USA over four winter seasons. The data show that albedo increases rapidly with snow depth up to ~0.14 m. Multiple linear regression models using snowpack age, snow depth or density, and air temperature provide reasonable approximations of surface snow albedo during times of albedo decay. However, the linear models also reveal systematic biases that highlight an important non-linearity in snow albedo decay. Modeled albedo values are reasonably accurate within the range of 0.6–0.9, but exhibit a tendency to overestimate lower albedo values and underestimate higher albedo values. We hypothesize that rapid reduction in high albedo fresh snow results from a decrease in snow specific surface area, while during melt-events the presence of liquid water in the snowpack accelerates metamorphism and grain growth. We conclude that the CoCoRaHS-Albedo volunteer observer network provides useful snow albedo, depth and density measurements and serves as an effective model for future measurement campaigns.

Surface tension prevails over solute effect in organic-influenced cloud droplet activation.

The spontaneous growth of cloud condensation nuclei (CCN) into cloud droplets under supersaturated water vapour conditions is described by classic Köhler theory. This spontaneous activation of CCN depends on the interplay between the Raoult effect, whereby activation potential increases with decreasing water activity or increasing solute concentration, and the Kelvin effect, whereby activation potential decreases with decreasing droplet size or increases with decreasing surface tension, which is sensitive to surfactants. Surface tension lowering caused by organic surfactants, which diminishes the Kelvin effect, is expected to be negated by a concomitant reduction in the Raoult effect, driven by the displacement of surfactant molecules from the droplet bulk to the droplet-vapour interface. Here we present observational and theoretical evidence illustrating that, in ambient air, surface tension lowering can prevail over the reduction in the Raoult effect, leading to substantial increases in cloud droplet concentrations. We suggest that consideration of liquid-liquid phase separation, leading to complete or partial engulfing of a hygroscopic particle core by a hydrophobic organic-rich phase, can explain the lack of concomitant reduction of the Raoult effect, while maintaining substantial lowering of surface tension, even for partial surface coverage. Apart from the importance of particle size and composition in droplet activation, we show by observation and modelling that incorporation of phase-separation effects into activation thermodynamics can lead to a CCN number concentration that is up to ten times what is predicted by climate models, changing the properties of clouds. An adequate representation of the CCN activation process is essential to the prediction of clouds in climate models, and given the effect of clouds on the Earth's energy balance, improved prediction of aerosol-cloud-climate interactions is likely to result in improved assessments of future climate change.

Response of evapotranspiration to changes in land use and land cover and climate in China during 2001–2013

Land surface evapotranspiration (ET) is a central component of the Earth's global energy balance and water cycle. Understanding ET is important in quantifying the impacts of human influences on the hydrological cycle and thus helps improving water use efficiency and strengthening water use planning and watershed management. China has experienced tremendous land use and land cover changes (LUCC) as a result of urbanization and ecological restoration under a broad background of climate change. This study used MODIS data products to analyze how LUCC and climate change affected ET in China in the period 2001–2013. We examined the separate contribution to the estimated ET changes by combining LUCC and climate data. Results showed that the average annual ET in China decreased at a rate of −0.6mm/yr from 2001 to 2013. Areas in which ET decreased significantly were mainly distributed in the northwest China, the central of southwest China, and most regions of south central and east China. The trends of four climatic factors including air temperature, wind speed, sunshine duration, and relative humidity were determined, while the contributions of these four factors to ET were quantified by combining the ET and climate datasets. Among the four climatic factors, sunshine duration and wind speed had the greatest influence on ET. LUCC data from 2001 to 2013 showed that forests, grasslands and croplands in China mutually replaced each other. The reduction of forests had much greater effects on ET than change by other land cover types. Finally, through quantitative separation of the distinct effects of climate change and LUCC on ET, we conclude that climate change was the more significant than LULC change in influencing ET in China during the period 2001–2013. Effective water resource management and vegetation-based ecological restoration efforts in China must consider the effects of climate change on ET and water availability.

Integrative analysis of desert dust size and abundance suggests less dust climate cooling.

Desert dust aerosols affect Earth's global energy balance through interactions with radiation1,2, clouds3,4, and ecosystems5. But the magnitudes of these effects are so uncertain that it remains unclear whether atmospheric dust has a net warming or cooling effect on global climate1,4,6. Consequently, it is still uncertain whether large changes in atmospheric dust loading over the past century have slowed or accelerated anthropogenic climate change4,7-9, and the climate impact of possible future alterations in dust loading is similarly disputed9,10. Here we use an integrative analysis of dust aerosol sizes and abundance to constrain the climatic impact of dust through direct interactions with radiation. Using a combination of observational, experimental, and model data, we find that atmospheric dust is substantially coarser than represented in current climate models. Since coarse dust warms global climate, the dust direct radiative effect (DRE) is likely less cooling than the ~0.4 W/m2 estimated by models in a current ensemble2,11-13. We constrain the dust DRE to - 0.20 (-0.48 to +0.20) W/m2, which suggests that the dust DRE produces only about half the cooling that current models estimate, and raises the possibility that dust DRE is actually net warming the planet.

Light absorption enhancement of black carbon from urban haze in Northern China winter

Atmospheric black carbon (BC) is an important pollutant for both air quality and Earth's energy balance. Estimates of BC climate forcing remain highly uncertain, e.g., due to the mixing with non-absorbing components. Non-absorbing aerosols create a coating on BC and may thereby act as a lens which may enhance the light absorption. However, this absorption enhancement is poorly constrained. To this end a two-step solvent dissolution protocol was employed to remove both organic and inorganic coatings, and then investigate their effects on BC light absorption. Samples were collected at a severely polluted urban area, Jinan, in the North China Plain (NCP) during February 2014. The BC mass absorption cross-section (MAC) was measured for the aerosol samples before and after the solvent-decoating treatment, and the enhancement of MAC (EMAC) from the coating effect was defined as the ratio. A distinct diurnal pattern for the enhancement was observed, with EMAC 1.3 ± 0.3 (1 S.D.) in the morning, increasing to 2.2 ± 1.0 in the afternoon, after that dropping to 1.5 ± 0.8 in the evening-night. The BC absorption enhancement primarily was associated with urban-scale photochemical production of nitrate and sulfate aerosols. In addition to that, regional-scale haze plume with increasing sulfate levels strengthened the absorption enhancement. These observations offer direct evidence for an increased absorption enhancement of BC due to severe air pollution in China.

Collateral transgression of planetary boundaries due to climate engineering by terrestrial carbon dioxide removal

Abstract. The planetary boundaries framework provides guidelines for defining thresholds in environmental variables. Their transgression is likely to result in a shift in Earth system functioning away from the relatively stable Holocene state. As the climate system is approaching critical thresholds of atmospheric carbon, several climate engineering methods are discussed, aiming at a reduction of atmospheric carbon concentrations to control the Earth's energy balance. Terrestrial carbon dioxide removal (tCDR) via afforestation or bioenergy production with carbon capture and storage are part of most climate change mitigation scenarios that limit global warming to less than 2 °C. We analyse the co-evolutionary interaction of societal interventions via tCDR and the natural dynamics of the Earth's carbon cycle. Applying a conceptual modelling framework, we analyse how the degree of anticipation of the climate problem and the intensity of tCDR efforts with the aim of staying within a "safe" level of global warming might influence the state of the Earth system with respect to other carbon-related planetary boundaries. Within the scope of our approach, we show that societal management of atmospheric carbon via tCDR can lead to a collateral transgression of the planetary boundary of land system change. Our analysis indicates that the opportunities to remain in a desirable region within carbon-related planetary boundaries only exist for a small range of anticipation levels and depend critically on the underlying emission pathway. While tCDR has the potential to ensure the Earth system's persistence within a carbon-safe operating space under low-emission pathways, it is unlikely to succeed in a business-as-usual scenario.