Terrestrial Albedo Research Articles

Small reduction in land surface albedo due to solar panel expansion worldwide

Photovoltaic (PV) panel deployment for decarbonization may reduce local terrestrial albedo, triggering a positive radiative forcing that counteracts the desired negative radiative forcing from carbon emission reductions. Yet, this potential adverse impact remains uncertain due to limited observations at PV sites. Herein we employ a robust linear parameterization method to quantify PV-induced albedo changes based on satellite data globally. We find an overall albedo decrease of −1.28 (−1.80, −0.90) × 10−2 (median and interquartile range), specific for land-cover types and climate regimes. However, the extent of albedo reduction is markedly lower than simplistic assumed values in simulating climate feedback for solar farming in Earth system models. Moreover, the albedo-induced positive radiative forcing can be offset by negative radiative forcing from clean solar generation in most PV farms within one year. Our findings underscore PV’s potential in mitigating global warming and stress the need for more accurate model estimations.

Application of the novel satellite calibrated method “Radiative Forcing Meter” on a high albedo test facility for CO2 compensation

The increase of terrestrial albedo may be considered a key strategy to mitigate global warming, since it produces a reduction of the radiative forcing (RF). The RF concept, as defined by IPCC, is used in literature for calculations of the CO2 compensation due to albedo increase, which can be achieved by the development of high-albedo solutions (cool materials, retro-reflective materials, green infrastructures, etc.). The authors have previously proposed a new procedure, called RF-meter, to measure the continuous time history of the RF due to an albedo increase (RFΔα) and so to calculate the related CO2 offset potential by high-albedo solutions. RF-meter procedure is based on the continuous albedo measurements at ground level and discrete satellite calibration. The proposed method is tested on a high-albedo surface (HAS) of 900 m2 treated with a high-reflective paint installed on the roof of CIRIAF building, University of Perugia, Italy. The experimental field is equipped with an albedometer, a weather station and a Calculus Unit. The measured data are elaborated by the Calculus Unit to calculate the RF time history and the compensated CO2. Data from albedo monitoring exhibited that albedo of HAS was always higher than albedo before the treatment (α0) and the average Δα is equal to 0.3. The calibration procedure allows to reduce the errors on RFΔα calculation. The maximum difference between albedo values from albedometer and satellite measurements resulted equal to 3.9%. Results from the Calculus Unit showed an amount of CO2 compensated by HAS equal to 73 kgCO2eq/m2.

A Novel Measurement-Based Method for Assessing Global Warming Mitigation via High-Albedo Solutions

Global warming mitigation via terrestrial albedo increase has been widely investigated in literature; the proposed methodologies relate CO2 compensation to albedo increase generally via the concept of Radiative Forcing (RF). However, literature methods calculate RF by averaged input data, without considering RF variation due to many local and temporal phenomena. For instance, an average value of compensated effect of albedo change (Δα = 0.01) is 3 kg CO2eq/m2, which has been introduced no matter the position and climatic condition of the site. In our study, we propose a novel procedure to measure RF continuous time history by means of ground measurements, astronomical equations, and satellite calibration. The procedure is called RF-meter. In this way, a more accurate assessment of compensated CO2 may be achieved. A test facility is also designed and proposed to double check the procedure, and preliminary results are reported in order to show and test the calibration procedure. It is expected that albedo-increased surfaces as well as cool roofs and/or other technical solutions will be eligible to obtain Emission Credits (EC). The proposed procedure will aid in the assignment of EC to High-Albedo Solutions (HAS), as it could represent an objective and accurate method to relate the albedo increase to a corresponding CO2 offset.

Earth's Albedo 1998–2017 as Measured From Earthshine

AbstractThe reflectance of the Earth is a fundamental climate parameter that we measured from Big Bear Solar Observatory between 1998 and 2017 by observing the earthshine using modern photometric techniques to precisely determine daily, monthly, seasonal, yearly and decadal changes in terrestrial albedo from earthshine. We find the inter‐annual fluctuations in albedo to be global, while the large variations in albedo within individual nights and seasonal wanderings tend to average out over each year. We measure a gradual, but climatologically significant 0.5 decline in the global albedo over the two decades of data. We found no correlation between the changes in the terrestrial albedo and measures of solar activity. The inter‐annual pattern of earthshine fluctuations are in good agreement with those measured by CERES (data began in 2001) even though the satellite observations are sensitive to retroflected light while earthshine is sensitive to wide‐angle reflectivity. The CERES decline is about twice that of earthshine.

ESTIMATION OF LAND SURFACE ALBEDO FROM GCOM-C/SGLI SURFACE REFLECTANCE

Abstract. This paper examines algorithms for estimating terrestrial albedo from the products of the Global Change Observation Mission – Climate (GCOM-C) / Second-generation Global Imager (SGLI), which was launched in December 2017 by the Japan Aerospace Exploration Agency. We selected two algorithms: one based on a bidirectional reflectance distribution function (BRDF) model and one based on multi-regression models. The former determines kernel-driven BRDF model parameters from multiple sets of reflectance and estimates the land surface albedo from those parameters. The latter estimates the land surface albedo from a single set of reflectance with multi-regression models. The multi-regression models are derived for an arbitrary geometry from datasets of simulated albedo and multi-angular reflectance. In experiments using in situ multi-temporal data for barren land, deciduous broadleaf forests, and paddy fields, the albedos estimated by the BRDF-based and multi-regression-based algorithms achieve reasonable root-mean-square errors. However, the latter algorithm requires information about the land cover of the pixel of interest, and the variance of its estimated albedo is sensitive to the observation geometry. We therefore conclude that the BRDF-based algorithm is more robust and can be applied to SGLI operational albedo products for various applications, including climate-change research.

Alternatives for Managing Atmospheric Warming

AbstractThe current discussion regarding global warming (or “climate change”) centers on managing the contribution of carbon dioxide (CO2) to incremental warming due to enhanced absorption of infrared radiation. If we are concerned about the warming, what is most important is the atmospheric heating regardless of cause. The incremental effect of CO2 may enhance this, but it is not the dominant mechanism of atmospheric warming, which is solar irradiance and the net absorption compared with reflection. This paper analyzes the large energy flows from the sun, human‐generated heat and CO2 emissions, several alternative energy conversion and generation strategies, and the resulting contributions to atmospheric heating. It is shown that increasing terrestrial albedo can offset the effects of fossil fuel combustion on both direct heating and incremental heating from CO2 emissions, and represents a viable alternative to replacing fossil‐fuel combustion with solar power.

EXAMINATION OF THE TERRAIN EFFECT FOR TERRESTRIAL ALBEDO ESTIMATION VIA BRDF MODEL PARAMETERS

Abstract. In this paper, we examine the effect of terrain on terrestrial albedo estimation. Terrestrial albedo is one of the most important parameters for understanding the global heat balance. The existing approach for estimating terrestrial albedo involves the estimation of model parameters of the bidirectional reflectance distribution function (BRDF) based on measurements obtained at different geometries. Then, narrowband albedos are estimated from the BRDF model parameters and the broadband albedo is finally estimated by narrowband-tobroadband conversion. Previous studies have not considered the terrain effect for generating the terrestrial albedo. Experiments using in situ measurements showed that the BRDF model, which transforms the geocoordinate of the reflectance of the shadowed terrain, generates the best accuracy. The improvement in the accuracy by the terrain effect correction is limited, and therefore further investigations using more in situ and simulated data are necessary for operational products.

Estimation of terrestrial albedo via BRDF model considering terrain effect

Estimation of terrestrial albedo via BRDF model considering terrain effect

Modification of the terrestrial albedo following the absorption of the solar radiation by the dark artificial surfaces and its influence on the green house effect

In this article, it is implicated another factor other than that greenhouse gases in global warming. Indeed, CO2 and its equivalents retain only infrared radiation of long wavelengths. These are issued naturally by the earth at all times, but recently under the pretext of prestige or fashion, in hot countries is added the paintings of buildings in dark color, black in this case. These colors affect the albedo coefficient by the absorption of solar radiation and the emission of far infrared radiation that cannot cross the greenhouse gases, so partly reflected towards the earth causing global warming. Global action on reducing greenhouse gas emissions should therefore be complemented by a reduction in the dark color areas created by man.

Earth's albedo variations 1998–2014 as measured from ground‐based earthshine observations

AbstractThe Earth's albedo is a fundamental climate parameter for understanding the radiation budget of the atmosphere. It has been traditionally measured not only from space platforms but also from the ground for 16 years from Big Bear Solar Observatory by observing the Moon. The photometric ratio of the dark (earthshine) to the bright (moonshine) sides of the Moon is used to determine nightly anomalies in the terrestrial albedo, with the aim of quantifying sustained monthly, annual, and/or decadal changes. We find two modest decadal scale cycles in the albedo, but with no significant net change over the 16 years of accumulated data. Within the evolution of the two cycles, we find periods of sustained annual increases, followed by comparable sustained decreases in albedo. The evolution of the earthshine albedo is in remarkable agreement with that from the Clouds and the Earth's Radiant Energy System instruments, although each method measures different slices of the Earth's Bond albedo.

Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.

Bacteria increase arid-land soil surface temperature through the production of sunscreens.

Soil surface temperature, an important driver of terrestrial biogeochemical processes, depends strongly on soil albedo, which can be significantly modified by factors such as plant cover. In sparsely vegetated lands, the soil surface can be colonized by photosynthetic microbes that build biocrust communities. Here we use concurrent physical, biochemical and microbiological analyses to show that mature biocrusts can increase surface soil temperature by as much as 10 °C through the accumulation of large quantities of a secondary metabolite, the microbial sunscreen scytonemin, produced by a group of late-successional cyanobacteria. Scytonemin accumulation decreases soil albedo significantly. Such localized warming has apparent and immediate consequences for the soil microbiome, inducing the replacement of thermosensitive bacterial species with more thermotolerant forms. These results reveal that not only vegetation but also microorganisms are a factor in modifying terrestrial albedo, potentially impacting biosphere feedbacks on past and future climate, and call for a direct assessment of such effects at larger scales.

Influence of tree species on continental differences in boreal fires and climate feedbacks

Wildfires are common in boreal forests around the globe and strongly influence ecosystem processes. However, North American forests support more high-intensity crown fires than Eurasia, where lower-intensity surface fires are common. These two types of fire can result in different net effects on climate as a consequence of their contrasting impacts on terrestrial albedo and carbon stocks. Here we use remote-sensing imagery, climate reanalysis data and forest inventories to evaluate differences in boreal fire dynamics between North America and Eurasia and their key drivers. Eurasian fires were less intense, destroyed less live vegetation, killed fewer trees and generated a smaller negative shortwave forcing. As fire weather conditions were similar across continents, we suggest that different fire dynamics between the two continents resulted from their dominant tree species. In particular, species that have evolved to spread and be consumed by crown fires as part of their life cycle dominate North American boreal forests. In contrast, tree species that have evolved to resist and suppress crown fires dominate Eurasian boreal forests. We conclude that species-level traits must be considered in global evaluations of the effects of fire on emissions and climate. Boreal forest wildfires in North America are more intense and destructive than in Eurasia. Differences in species-level adaptations to fire are primary drivers of these differences in fire regimes.

Influence of celestial light on lunar surface brightness determinations: Application to earthshine studies

Aims. We consider the influence of celestial-sphere brightness on determinations of terrestrial albedo from earthshine intensity measurements. In particular, the contributions from zodiacal light and starlight are considered. Methods. Using published data for the zodiacal light (ZL) and stellar brightness distribution across the sky, we calculate the expected contribution to the sky at the position of the Moon in typical earthshine observations, and the magnitude relative to typical earthshine intensities. We derive terrestrial albedo with and without the ZL correction in order to gauge the magnitude of the e ect. Results. We find that celestial-sphere surface brightness can be so large that a considerable and unacceptable error level would have an impact on half of typical earthshine-based albedo-determinations if left unaccounted for. Considering the empirical uncertainty on ZL, we show that almost all our earthshine data can be used if a sky correction is made. In real observations we find up to a 1% e ect on albedo results of correcting for the celestial brightness. Conclusions. Correction for ZL and starlight brightness is essential to earthshine measurements if climate-science relevant levels of terrestrial albedo accuracy are to be achieved, something that has not yet been realized. With ZL and starlight corrections the earthshine method can potentially yield accurate terrestrial albedo values.

Determining hematite content from NUV/Vis/NIR spectra: Limits of detection

Hematite occurs in various geologic settings including igneous, metamorphic, and sedimentary rocks as well as in soils. However, it frequently occurs at low concentrations, especially in soils, where it may be <1% by weight. Because hematite has the potential to be an indicator of oxidizing and climatic conditions in soils and paleosols, it is important to understand its limit of detection. In this paper we examine the limits of detection of hematite visually and with diffuse reflectance spectrophotometry (DRS) and X‑ray diffraction (XRD). To accomplish this we used a sample set consisting of “knowns” or calibration samples. These known samples consisted of 15 different matrices of varying mineral composition into which hematite in 7 different concentrations ranging from 0.01 to 4% by weight were mixed. Including the 0% hematite, our calibration data set consisted of 120 samples. Visually, hematite can be detected at a concentration of 0.01% by weight in a light matrix and 0.5% in the darkest of our matrices. However, because of metamerism, visual techniques cannot specifically identify hematite. We find that for both DRS and XRD the limit of detection is also dependent on the matrix. For XRD the limit of detection for hematite in bulk samples is about 1%. For DRS the limit of detection depends on the data reduction technique used. The commonly used Kubelka‑Munk remission function and its first and second deriva tives can easily identify hematite at the 0.5% level. However, the first derivative of the percent reflectance curve can detect hematite at 0.01% by weight in a light matrix and 0.05% in a dark matrix. We suggest that the first derivative of DRS curves is the best currently available method for qualitatively detecting the mineral hematite at low concentrations found in soils, sediments, and rocks. Work described in this paper may be applied in several situations. Our study of visual limits of hematite detection should aid field geologists in assessing hematite content. Analysis of color wave length bands may also have application in remote sensing by indicating which bands are most sensitive to hematite, reported to be an important constituent of the martian surface. Furthermore, this study could help clarify remotely sensed terrestrial albedo changes, especially the Sahara/Sahel transition where the sediments change from light, quartz-dominated to dark, hematite-dominated. Our study also points out that with laboratory‑based spectra the first derivative of the reflectance curve is the most sensitive transform for processing spectral data for hematite, thereby allowing concentrations as low as 0.01% to be detected.

Fighting global warming by climate engineering: Is the Earth radiation management and the solar radiation management any option for fighting climate change?

Abstract The best way to reduce global warming is, without any doubt, cutting down our anthropogenic emissions of greenhouse gases. But the world economy is addict to energy, which is mainly produced by fossil carbon fuels. As economic growth and increasing world population require more and more energy, we cannot stop using fossil fuels quickly, nor in a short term. On the one hand, replacing this addiction with carbon dioxide-free renewable energies, and energy efficiency will be long, expensive and difficult. On the other hand, meanwhile effective solutions are developed (i.e. fusion energy), global warming can be alleviated by other methods. Some geoengineering schemes propose solar radiation management technologies that modify terrestrial albedo or reflect incoming shortwave solar radiation back to space. In this paper we analyze the physical and technical potential of several disrupting technologies that could combat climate change by enhancing outgoing longwave radiation and cooling down the Earth. The technologies proposed are power-generating systems that are able to transfer heat from the Earth surface to the upper layers of the troposphere and then to the space. The economical potential of some of these technologies is analyzed as they can at the same time produce renewable energy, thus reduce and prevent future greenhouse gases emissions, and also present a better societal acceptance comparatively to geoengineering.

Estimating wetland vegetation abundance based on spectral mixture analysis: a comparison between LSMA and FCM classification methods

Vegetation abundance is a critical indicator for measuring the status of vegetation. It is also important for evaluating the eco-environment of wetland. In this article, linear spectral mixture analysis (LSMA) and fuzzy c-means (FCM) classification methods were applied to estimate vegetation abundance in Wild Duck Lake Wetland, one of the typical freshwater wetlands in North China, based on Landsat Thematic Mapper (TM) data acquired on 27 June 2011. Due to its effectiveness in characterizing vegetation activity and greenness, the normalized difference vegetation index (NDVI) was incorporated into the six reflective bands of the Landsat TM image to provide enough dimensionality to support the use of the a five-endmember LSMA model, which includes terrestrial plants, aquatic plants, high albedo, low albedo, and bare soil. Then, a fully constrained LSMA algorithm was performed to obtain vegetation abundance in our study area. An FCM classification algorithm was also used to generate vegetation abundance. Finally, both results were modified using the extracted water area of Wild Duck Lake Wetland, which was obtained with the combination of NDVI and normalized difference water index. The root mean square error (RMSE) and the coefficient of determination (R2) were calculated to assess the accuracy of vegetation abundance by using a WorldView-2 multispectral image. Validation showed that although there were slight differences between the vegetation abundance images, they shared similar spatial patterns of vegetation distribution: high vegetation abundance values in agricultural areas and riparian areas, moderate in grassland areas, and low in residential areas. The FCM classification generated an R2 of 0.791, while the LSMA yielded a result with an R2 of 0.672. Additionally, the RMSE also indicated that the FCM classification can obtain a much better result than LSMA: the former’s RMSE is 0.091 and the latter is 0.172. The result suggests that the FCM classification based on the nonlinear assumption can handle mixed pixels more effectively than LSMA.

Global change-type drought-induced tree mortality: vapor pressure deficit is more important than temperature per se in causing decline in tree health.

Drought-induced tree mortality is occurring across all forested continents and is expected to increase worldwide during the coming century. Regional-scale forest die-off influences terrestrial albedo, carbon and water budgets, and land-surface energy partitioning. Although increased temperatures during drought are widely identified as a critical contributor to exacerbated tree mortality associated with “global-change-type drought”, corresponding changes in vapor pressure deficit (D) have rarely been considered explicitly and have not been disaggregated from that of temperature per se. Here, we apply a detailed mechanistic soil–plant–atmosphere model to examine the impacts of drought, increased air temperature (+2°C or +5°C), and increased vapor pressure deficit (D; +1 kPa or +2.5 kPa), singly and in combination, on net primary productivity (NPP) and transpiration and forest responses, especially soil moisture content, leaf water potential, and stomatal conductance. We show that increased D exerts a larger detrimental effect on transpiration and NPP, than increased temperature alone, with or without the imposition of a 3-month drought. Combined with drought, the effect of increased D on NPP was substantially larger than that of drought plus increased temperature. Thus, the number of days when NPP was zero across the 2-year simulation was 13 or 14 days in the control and increased temperature scenarios, but increased to approximately 200 days when D was increased. Drought alone increased the number of days of zero NPP to 88, but drought plus increased temperature did not increase the number of days. In contrast, drought and increased D resulted in the number of days when NPP = 0 increasing to 235 (+1 kPa) or 304 days (+2.5 kPa). We conclude that correct identification of the causes of global change-type mortality events requires explicit consideration of the influence of D as well as its interaction with drought and temperature.This study disaggregates the influence of temperature and vapour pressure deficit on net primary productivity of an Australian woodland and their interactions with drought as potential causal agents in recent widespread forest mortality.

Is There an Existing Healthy Threshold for Carbon Storage in the Ecosystem?

I the United Nations Climate Change Conference held in December 2009, China, ranking second as the leading source of greenhouse gas emissions in the world following the U.S., advanced its reduction of CO2 emission intensity by 40−45% below the 2005 levels by 2020. To decrease CO2 emission and combat climate change, China initiated six large forestation projects to enhance carbon (C) storage by 16−30 billion tons of C every year starting from 2006 to 2050. These projects were conducted by increasing the country’s forested area by 40 million ha. The people and the government have paid much attention to C sequestration for a long time. However, they have neglected to determine whether C sequestration has negative effects on the health of the ecosystem. For example, although C sequestration as a result of China’s large-scale forestation projects is a good goal, Wang and Cao considered C sequestration engineering to have negative effects on the health of the ecosystem. Therefore, we advance the concept of a C-healthy threshold in the ecosystem. Mastering the Chealthy thresholds for different ecosystems is important in combating climate change and making appropriate climate policies in the future. Climate change can affect forest growth because plant growth depends on the health of the ecosystem and the availability of C, nitrogen (N), and water, all of which can be influenced by climate change as well. The effects of climate change on evaporation and precipitation accelerate water cycles. The reason is that the strong coupling relationships between C, N, and water cycles in the ecosystem exist mostly through the water fluxes that connect these cycles physically. The C and N transport at a soil−water interface is largely controlled by the C and N inputs and flow rate. Soil mobilizes N and soluble C during intense rainfall. Then, they are transported to the deeper layers, which results in increased substrate availability for the decomposer community and improved nutrient conditions for vegetation. N availability affects the terrestrial albedo, energy and water fluxes, plant C production, respiration, and soil organic matter decay (Figure 1). N limitation occurs when the ecosystem’s C productivity is limited by N availability. N fixation reduces the extent of N limitation when C availability is increased, and it may synergistically lead to an increased C storage. Precipitation, one of the most important factors affecting soil erosion, can cause C transport through runoff and leaching. Soil erosion affects C dynamics in the ecosystem through its effect on the following: slaking or disruption of aggregates; preferential removal of C in runoff water; mineralization of soil organic matter on site; mineralization, displacement, and redistribution of soil organic C over the landscape and transportation in rivers; reaggregation of soil through the formation of organo−mineral complexes in the depositional/protected sites; and deep burial of C-enriched sediments in the depositional sites. Most soils may lose one-half to two-thirds of their soil organic C pool within 5 and 50 years in the tropics and temperate regions, respectively. The new equilibrium may be attained after losing 20 Mg C.ha−1 to 50 Mg C·ha−1. Based on the coupling relationships between C, N, and water, we discuss different conditions to understand the Chealthy threshold in the ecosystem. If C storage by forestation is increased, the C productivity of plants will need an adequate nutrient and water supply. However, if C storage exceeds the nutrient and water supply limit, either plant life will die or C will be transported through soil erosion or other pathways because of the balanced relationships between C, N, and water in the ecosystem. Thus, there is an existing balance threshold for C, nutrients, and water. The other condition is that an increase in precipitant leads to a large amount of nutrient and C loss by soil erosion. When the remaining C in soil cannot maintain the normal C cycle in a terrestrial system, either the plants will die or the ecosystem will be in a subhealth state. We can conclude that, if the C storage in the ecosystem is not controlled under normal fluctuation ranges and is not

Evaluation of the Terrestrial Albedo Applied to Some Scientific Missions

Using the Earth albedo model and the orbital dynamics model developed as part of the First Look Project (Fast Initial In-Orbit Identification of Scientific Satellites) the terrestrial albedo is evaluated considering the orbits of some scientific missions as Gravity Probe B, MICROSCOPE and STEP. The model of the Earth albedo is based on the reflectivity data measured by NASA’s Earth Probe satellite, which is part of the TOMS project (Total Ozone Mapping Spectrometer). The reflectivity data are available daily, on line at the TOMS website, and they fluctuate because of changes in clouds and ice coverage and seasonal changes. The data resolution partitions the Earth surface into a number of cells. The incident irradiance on each cell is used to calculate total radiant flux from the cell. With the radiant flux from each cell, the irradiance at the satellite is calculated.