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Kiran, Mariam, and Anthony Simons. "Testing Software Services in Cloud Ecosystems." International Journal of Cloud Applications and Computing 6, no. 1 (January 2016): 42–58. http://dx.doi.org/10.4018/ijcac.2016010103.
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Testing in the Cloud is far more challenging than testing individual software services. A multitude of factors affect testing, including variations across platforms and infrastructure. Architectural issues include differences between private, public Clouds, multi-Clouds and Cloud-bursting. Platform issues include cross-vendor incompatibility, and diverse locales of service deployment and consumption. Software issues include integration with third-party services, the desire to validate competing service offerings to similar standards and need to re-validate services at different stages of service lifecycle. A complete approach to testing whole Cloud ecosystems should involve all relevant stakeholders, such as service provider, consumer and broker. When testing Clouds, the methodologies used should not hinder the advantages Cloud usage brings to the users or programmers and more importantly be simple and cost effective. However, these testing methodologies differ according to the various kinds of Cloud ecosystems and the different user perspectives of the actors involved such as the end-user, the infrastructures, or the different software (i.e. web services). This paper also studies the state-of-the-art in Cloud testing where most research focuses predominantly on web services, functional testing and quality-of-service, usually being considered separately. The authors suggest a framework, Quality-as-a-Service (QaaS) which integrates quality issues such as functional behaviour and performance monitoring with lifecycle governance and security of the service. This paper maps out the themes in the contemporary research literature and links them with the service lifecycle process for validating future Cloud services. Along the way, the authors identify important research questions that the future Cloud service testing agenda should seek to address.
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Xu, Hang, Zhiqiang Zhang, Jiquan Chen, Mengxun Zhu, and Manchun Kang. "Cloudiness regulates gross primary productivity of a poplar plantation under different environmental conditions." Canadian Journal of Forest Research 47, no. 5 (May 2017): 648–58. http://dx.doi.org/10.1139/cjfr-2016-0413.
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Cloud cover regulates the gross primary productivity (GPP) of forest ecosystems by changing the radiation component and other environmental factors. In this study, we used an open-path eddy covariance system and microclimate sensors installed over a poplar plantation in northern China to measure the carbon exchange and climate variables during the mid-growing seasons (June to August) in 2014 and 2015. The results indicated that the GPP of the plantation peaked when the clearness index (CI) was between 0.45 and 0.65, at which point diffuse photosynthetically active radiation (PARdif) had reached its maximum. Cloudy skies increased the maximum ecosystem photosynthetic capacity (Pmax) by 28% compared with clear skies. PARdif and soil moisture were the most and the least crucial drivers for photosynthetic productivity of the plantation under cloudy skies, respectively. The ecosystem photosynthetic potential was higher under lower vapor pressure deficit (VPD < 1.5 kPa), lower air temperature (Ta < 30 °C), and nonstressed conditions (REW > 0.4) for cloudy skies due to effects of Ta and VPD on stoma. Overall, our research highlighted the importance of cloud-induced radiation component change and environmental variation in quantifying the GPP of forest ecosystems.
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Duarte, Bruno Muniz, and José Ricardo de Almeida França. "Estrutura microfísica das nuvens em diferentes ecossistemas da América do Sul." Anuário do Instituto de Geociências 32, no. 2 (December 1, 2009): 33–41. http://dx.doi.org/10.11137/2009_2_33-41.
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Clouds directly affect meteorological conditions of the planet, by interacting with electromagnetic radiation from the sun, the earth's surface and the atmosphere. Each cloud type interacts in a particular way, being extremely important that the total set of clouds at any location is well represented in atmospheric models, in order to generate more accurate results. The purpose of this paper is to initiate a characterization of cloud types as a function of their microphysical properties and evaluate the dependence on ecosystem and synoptic condition. The data were obtained through remote sensing, using the MODIS sensor and the variables: cloud particle effective radius, optical thickness, pressure and temperature of the cloud top. Several forms of distributions were found for six different ecosystems for the four seasons. It was noted that narrow and concentrated effective radius spectra are linked to deep convection clouds, while broader distributions can be usually associated to cold frontal systems. The amount of events analyzed was not enough to show clear patterns, although the results can lead to other directions in a future and more focused work.
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Zhang, B. C., J. J. Cao, Y. F. Bai, S. J. Yang, L. Hu, and Z. G. Ning. "Effects of cloudiness on carbon dioxide exchange over an irrigated maize cropland in northwestern China." Biogeosciences Discussions 8, no. 1 (February 23, 2011): 1669–91. http://dx.doi.org/10.5194/bgd-8-1669-2011.
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Abstract. Clouds can strongly influence solar radiation and affects other microclimatic factors (such as air temperature and vapour pressure deficit), and those changed environmental conditions may exert strong effects on carbon exchange between terrestrial ecosystems and the atmosphere. In this study, we analyzed how canopy photosynthesis and ecosystem respiration respond to changes in cloudy conditions, based on two years of eddy-covariance and meteorological data from an irrigated maize cropland in Yingke oasis of northwestern China. The results showed that net carbon uptake was more negative under cloudy than under clear conditions, it indicates that net carbon uptake increased under cloudy days. The rate of ecosystem respiration (Re) decreased under cloudy conditions due to decreased air temperature. However, photosynthesis was suppressed by the decreasing air temperature and vapour pressure deficit (VPD) under cloudy skies. Thus, the enhancement of net carbon uptake under cloudy skies mainly contributed from increasing photosynthesis with diffuse radiation. Those results improve our understanding of the effects of cloud cover on carbon exchange process in maize (C4) cropland, and improve our understanding of the driver improving net carbon uptake under cloudy conditions.
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Fernandez, Eduardo, Nobukazu Yoshioka, Hironori Washizaki, and Madiha Syed. "Modeling and Security in Cloud Ecosystems." Future Internet 8, no. 4 (April 20, 2016): 13. http://dx.doi.org/10.3390/fi8020013.
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Werdell, P. Jeremy, Michael J. Behrenfeld, Paula S. Bontempi, Emmanuel Boss, Brian Cairns, Gary T. Davis, Bryan A. Franz, et al. "The Plankton, Aerosol, Cloud, Ocean Ecosystem Mission: Status, Science, Advances." Bulletin of the American Meteorological Society 100, no. 9 (September 2019): 1775–94. http://dx.doi.org/10.1175/bams-d-18-0056.1.
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AbstractThe Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) mission represents the National Aeronautics and Space Administration’s (NASA) next investment in satellite ocean color and the study of Earth’s ocean–atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth’s changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food-web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave-infrared wavelengths, with a ground sample distance of 1 km at nadir. This payload is complemented by two multiangle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022 to early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean–atmosphere–land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products.
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Gotsch, Sybil G., Heidi Asbjornsen, and Gregory R. Goldsmith. "Plant carbon and water fluxes in tropical montane cloud forests." Journal of Tropical Ecology 32, no. 5 (July 15, 2016): 404–20. http://dx.doi.org/10.1017/s0266467416000341.
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Abstract:Tropical montane cloud forests (TMCFs) are dynamic ecosystems defined by frequent, but intermittent, contact with fog. The resultant microclimate can vary considerably over short spatial and temporal scales, affecting the ecophysiology of TMCF plants. We synthesized research to date on TMCF carbon and water fluxes at the scale of the leaf, plant and ecosystem and then contextualized this synthesis with tropical lowland forest ecosystems. Mean light-saturated photosynthesis was lower than that of lowland forests, probably due to the effects of persistent reduced radiation leading to shade acclimation. Scaled to the ecosystem, measures of annual net primary productivity were also lower. Mean rates of transpiration, from the scale of the leaf to the ecosystem, were also lower than in lowland sites, likely due to lower atmospheric water demand, although there was considerable overlap in range. Lastly, although carbon use efficiency appears relatively invariant, limited evidence indicates that water use efficiency generally increases with altitude, perhaps due to increased cloudiness exerting a stronger effect on vapour pressure deficit than photosynthesis. The results reveal clear differences in carbon and water balance between TMCFs and their lowland counterparts and suggest many outstanding questions for understanding TMCF ecophysiology now and in the future.
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Scholl, Martha A., Maoya Bassiouni, and Angel J. Torres-Sánchez. "Drought stress and hurricane defoliation influence mountain clouds and moisture recycling in a tropical forest." Proceedings of the National Academy of Sciences 118, no. 7 (February 9, 2021): e2021646118. http://dx.doi.org/10.1073/pnas.2021646118.
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Mountain ranges generate clouds, precipitation, and perennial streamflow for water supplies, but the role of forest cover in mountain hydrometeorology and cloud formation is not well understood. In the Luquillo Experimental Forest of Puerto Rico, mountains are immersed in clouds nightly, providing a steady precipitation source to support the tropical forest ecosystems and human uses. A severe drought in 2015 and the removal of forest canopy (defoliation) by Hurricane Maria in 2017 created natural experiments to examine interactions between the living forest and hydroclimatic processes. These unprecedented land-based observations over 4.5 y revealed that the orographic cloud system was highly responsive to local land-surface moisture and energy balances moderated by the forest. Cloud layer thickness and immersion frequency on the mountain slope correlated with antecedent rainfall, linking recycled terrestrial moisture to the formation of mountain clouds; and cloud-base altitude rose during drought stress and posthurricane defoliation. Changes in diurnal cycles of temperature and vapor-pressure deficit and an increase in sensible versus latent heat flux quantified local meteorological response to forest disturbances. Temperature and water vapor anomalies along the mountain slope persisted for at least 12 mo posthurricane, showing that understory recovery did not replace intact forest canopy function. In many similar settings around the world, prolonged drought, increasing temperatures, and deforestation could affect orographic cloud precipitation and the humans and ecosystems that depend on it.
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Helmy, Yehia, Mona Nasr, and Shimaa Ouf. "A Proposed Model for Using Cloud Computing and Web2.0 in Deploying E-Learning Ecosystem (ELES)." International Journal of Cloud Applications and Computing 3, no. 4 (October 2013): 51–80. http://dx.doi.org/10.4018/ijcac.2013100105.
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Research community has believed that an e-learning ecosystem is the next generation of e-learning but has faced challenges in optimizing resource allocations, dealing with dynamic demands on getting information and knowledge anywhere and anytime, handling rapid storage growth requirements, cost controlling and greater flexibility. So, flourish, growing, scalable, available, up to date and strong infrastructure e-learning ecosystems in a productive and cost effective way will be needed to face challenges and rapidly changing in learning environment. This paper work focused on an e-learning ecosystem (ELES) which supports new technologies is introduced and implemented. An integration between cloud computing and Web 2.0 technologies and services used to support the development of e-learning ecosystems. Cloud computing an adaptable technology for many of the universities with its dynamic scalability and usage of virtualized resources as a service through the Internet and Web 2.0 brings new instruments help building dynamic e-learning ecosystem on the web.
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Shvaiko, Valerii, Olena Bandurka, Vadym Shpuryk, and Yevhen V. Havrylko. "METHODS FOR DETECTING FIRES IN ECOSYSTEMS USING LOW-RESOLUTION SPACE IMAGES." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 11, no. 1 (March 31, 2021): 15–19. http://dx.doi.org/10.35784/iapgos.2576.
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The paper presents the methods for fire identification using low-resolution space images obtained from Terra Modis and NOAA satellites. There are lots of algorithms to identify potentially "fire pixels" (PF). They are based on the assessment of temperature in spectral ranges from 3.5–4 to 10.5–11.5 microns. One of the problematic aspects in the Fire Detection Method using low-resolution space images is "Cloud and Water Masking". To identify "fire pixels", it is important to exclude from the analysis fragments of images that are covered with clouds and occupied by water objects. Identification of pixels in which one or more fires are actively burning at the time of passing over the Earth is the basis of the algorithm for detecting potentially "fire pixels". The algorithm requires a significant increase in radiation in the range of 4 micrometers, as well as on the observed radiation in the range of 11 micrometers. The algorithm investigates each pixel in a scene that is assigned one of the following classes as a result: lack of data, cloud, water, potentially fire or uncertain. The pixels that lack actual data are immediately classified as "missing data (NULL)" and excluded from further consideration. Cloud and water pixels, defined by the cloud masking technique and water objects, belong to cloud and water classes, respectively. The fire detection algorithm investigates only those pixels of the Earth's surface that are classified as potentially fire or uncertain. The method was implemented using the Visual Programming Tool PowerBuilder in the data processing system of Erdas Imaging. As a result of the use of the identification method, fires in the Chornobyl exclusion zone, steppe fires and fires at gas wells were detected. Using the method of satellite fire identification is essential for the prompt detection of fires for remote forests or steppes that are poorly controlled by ground monitoring methods.
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Ahammad, Ishtiaq, Ashikur Rahman Khan, and Zayed Us Salehin. "A Review on Cloud, Fog, Roof, and Dew Computing." International Journal of Cloud Applications and Computing 11, no. 4 (October 2021): 14–41. http://dx.doi.org/10.4018/ijcac.2021100102.
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The internet of things (IoT) offers a range of benefits for its users, ranging from quicker and more precise perception of our ecosystem to more cost-effective monitoring of manufacturing applications, by taking internet access to the things. Due to the ubiquitous existence of the internet, there's been an increasing pace in the IoT. Such a growing pace has brought about the term of IoT ecosystem. This exponential growing IoT ecosystem will encounter several challenges in its path. Computing domains were used from very initial stage to assist the IoT ecosystem and mitigate those challenges. To understand the impact of computing domains in IoT ecosystem, this paper performs the elaborative study on cloud, fog, roof, and dew computing including their interaction, benefits, and limitations in IoT ecosystem. The brief comparative analysis on these four computing domains are then performed. The impact of internet and offline computing on these computing domains are then analyzed in depth. Finally, this paper presents the suggestions of potential appropriate computing domain strategies for IoT ecosystems.
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Mattia, Santoro, Mazzetti Paolo, and Nativi Stefano. "Virtual earth cloud: a multi-cloud framework for enabling geosciences digital ecosystems." International Journal of Digital Earth 16, no. 1 (January 3, 2023): 43–65. http://dx.doi.org/10.1080/17538947.2022.2162986.
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Lyons, Walter. "Cloud Forests of Costa Rica: Ecosystems in Peril." Weatherwise 72, no. 3 (April 11, 2019): 32–37. http://dx.doi.org/10.1080/00431672.2019.1586505.
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Braaten, Justin D., Warren B. Cohen, and Zhiqiang Yang. "Automated cloud and cloud shadow identification in Landsat MSS imagery for temperate ecosystems." Remote Sensing of Environment 169 (November 2015): 128–38. http://dx.doi.org/10.1016/j.rse.2015.08.006.
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Shah, Viral, Daniel J. Jacob, Jonathan M. Moch, Xuan Wang, and Shixian Zhai. "Global modeling of cloud water acidity, precipitation acidity, and acid inputs to ecosystems." Atmospheric Chemistry and Physics 20, no. 20 (October 28, 2020): 12223–45. http://dx.doi.org/10.5194/acp-20-12223-2020.
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Abstract. Cloud water acidity affects the atmospheric chemistry of sulfate and organic aerosol formation, halogen radical cycling, and trace metal speciation. Precipitation acidity including post-depositional inputs adversely affects soil and freshwater ecosystems. Here, we use the GEOS-Chem model of atmospheric chemistry to simulate the global distributions of cloud water and precipitation acidity as well as the total acid inputs to ecosystems from wet deposition. The model accounts for strong acids (H2SO4, HNO3, and HCl), weak acids (HCOOH, CH3COOH, CO2, and SO2), and weak bases (NH3 as well as dust and sea salt aerosol alkalinity). We compile a global data set of cloud water pH measurements for comparison with the model. The global mean observed cloud water pH is 5.2±0.9, compared to 5.0±0.8 in the model, with a range from 3 to 8 depending on the region. The lowest values are over East Asia, and the highest values are over deserts. Cloud water pH over East Asia is low because of large acid inputs (H2SO4 and HNO3), despite NH3 and dust neutralizing 70 % of these inputs. Cloud water pH is typically 4–5 over the US and Europe. Carboxylic acids account for less than 25 % of cloud water H+ in the Northern Hemisphere on an annual basis but 25 %–50 % in the Southern Hemisphere and over 50 % in the southern tropical continents, where they push the cloud water pH below 4.5. Anthropogenic emissions of SO2 and NOx (precursors of H2SO4 and HNO3) are decreasing at northern midlatitudes, but the effect on cloud water pH is strongly buffered by NH4+ and carboxylic acids. The global mean precipitation pH is 5.5 in GEOS-Chem, which is higher than the cloud water pH because of dilution and below-cloud scavenging of NH3 and dust. GEOS-Chem successfully reproduces the annual mean precipitation pH observations in North America, Europe, and eastern Asia. Carboxylic acids, which are undetected in routine observations due to biodegradation, lower the annual mean precipitation pH in these areas by 0.2 units. The acid wet deposition flux to terrestrial ecosystems taking into account the acidifying potential of NO3- and NH4+ in N-saturated ecosystems exceeds 50 meqm-2a-1 in East Asia and the Americas, which would affect sensitive ecosystems. NH4+ is the dominant acidifying species in wet deposition, contributing 41 % of the global acid flux to continents under N-saturated conditions.
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Janzen, Daniel H., and Winnie Hallwachs. "To us insectometers, it is clear that insect decline in our Costa Rican tropics is real, so let’s be kind to the survivors." Proceedings of the National Academy of Sciences 118, no. 2 (January 11, 2021): e2002546117. http://dx.doi.org/10.1073/pnas.2002546117.
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We have been field observers of tropical insects on four continents and, since 1978, intense observers of caterpillars, their parasites, and their associates in the 1,260 km2 of dry, cloud, and rain forests of Área de Conservación Guanacaste (ACG) in northwestern Costa Rica. ACG’s natural ecosystem restoration began with its national park designation in 1971. As human biomonitors, or “insectometers,” we see that ACG’s insect species richness and density have gradually declined since the late 1970s, and more intensely since about 2005. The overarching perturbation is climate change. It has caused increasing ambient temperatures for all ecosystems; more erratic seasonal cues; reduced, erratic, and asynchronous rainfall; heated air masses sliding up the volcanoes and burning off the cloud forest; and dwindling biodiversity in all ACG terrestrial ecosystems. What then is the next step as climate change descends on ACG’s many small-scale successes in sustainable biodevelopment? Be kind to the survivors by stimulating and facilitating their owner societies to value them as legitimate members of a green sustainable nation. Encourage national bioliteracy, BioAlfa.
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Ficco, Massimo, Christian Esposito, Yang Xiang, and Francesco Palmieri. "Pseudo-Dynamic Testing of Realistic Edge-Fog Cloud Ecosystems." IEEE Communications Magazine 55, no. 11 (November 2017): 98–104. http://dx.doi.org/10.1109/mcom.2017.1700328.
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Karakonstantis, Georgios, Dimitrios S. Nikolopoulos, Dimitris Gizopoulos, Pedro Trancoso, Yiannakis Sazeides, Christos D. Antonopoulos, Srikumar Venugopal, and Shidhartha Das. "Error-Resilient Server Ecosystems for Edge and Cloud Datacenters." Computer 50, no. 12 (December 2017): 78–81. http://dx.doi.org/10.1109/mc.2017.4451208.
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Torres-Delgado, Elvis, Darrel Baumgardner, and Olga L. Mayol-Bracero. "Measurement report: Impact of African aerosol particles on cloud evolution in a tropical montane cloud forest in the Caribbean." Atmospheric Chemistry and Physics 21, no. 23 (December 9, 2021): 18011–27. http://dx.doi.org/10.5194/acp-21-18011-2021.
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Abstract. African aerosol particles, traveling thousands of kilometers before reaching the Americas and the Caribbean, directly scatter and absorb solar radiation and indirectly impact climate by serving as cloud condensation nuclei (CCN) or ice-nucleating particles (INPs) that form clouds. These particles can also affect the water budget by altering precipitation patterns that subsequently affect ecosystems. As part of the NSF-funded Luquillo Critical Zone Observatory, field campaigns were conducted during the summers of 2013 (23 d), 2014 (11 d), and 2015 (92 d) at Pico del Este, a site in a tropical montane cloud forest on the Caribbean Island of Puerto Rico. Cloud microphysical properties, which included liquid water content, droplet number concentration, and droplet size, were measured. Using products from models and satellites, as well as in situ measurements of aerosol optical properties, periods of high- and low-dust influence were identified. The results from this study suggest that meteorology and air mass history have a more important effect on cloud processes than aerosols transported from Africa. In contrast, air masses that arrived after passing over the inhabited islands to the southeast led to clouds with much higher droplet concentrations, presumably due to aerosols formed from anthropogenic emissions.
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Junior, Warley, Bruno Silva, and Kelvin Dias. "A systematic mapping study on mobility mechanisms for cloud service provisioning in mobile cloud ecosystems." Computers & Electrical Engineering 69 (July 2018): 256–73. http://dx.doi.org/10.1016/j.compeleceng.2018.01.030.
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Werdell, Jeremy, and Annette deCharon. "PACE: How One NASA Mission Aligns With the United Nations Decade of Ocean Science for Sustainable Development (OceanShot #1)." Marine Technology Society Journal 56, no. 3 (June 8, 2022): 118–21. http://dx.doi.org/10.4031/mtsj.56.3.30.
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Abstract The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE; <ext-link ext-link-type="uri" xlink:href="https://pace.gsfc.nasa.gov">https://pace.gsfc.nasa.gov</ext-link>) mission, scheduled for launch in January 2024, will extend the continuous high-quality ocean color, atmospheric aerosol, and cloud data records begun by NASA in the late 1990s, building on the heritage of the Coastal Zone Color Scanner (CZCS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) (Figure 1). PACE's global hyperspectral imaging radiometer design concept will enable new discoveries in Earth's living ocean (Figure 2), such as the diversity of organisms fueling marine food webs and how aquatic ecosystems respond to environmental change. Its instrument payload (Figure 3) will also observe Earth's atmosphere to study clouds, airborne aerosol particles, and the interactions between the two. Looking at the ocean, clouds, and aerosols together will improve our knowledge of the roles each plays in our evolving planet. Other applications of PACE science data records—from identifying the frequency, extent, and duration of aquatic harmful algal blooms to improving our understanding of air quality—will result in direct economic, recreational, and societal benefits. Ultimately, by extending and expanding NASA's long record of global Earth satellite observations, the PACE mission will monitor our home planet in new and advanced ways in the coming decade.
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Likhoshway, E. V. "Actual trends in water ecosystem biology development." Marine Biological Journal 2, no. 4 (December 29, 2017): 3–14. http://dx.doi.org/10.21072/mbj.2017.02.4.01.
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This synopsis characterizes new trends in oceanology arising for the last some years as a result of practical application of actual methods in data obtaining and processing. First of all, these are methods of massive parallel sequencing, “-omics” and bioinformatics methods of data storage and analysis. Identifying biologically active substances in water environment and results of laboratory-based experiments show the existence of molecular signal transduction both at the level of population and interspecies relations between microorganisms and at the level of their trophic connections. “From molecules to ecosystem” – is an actual trend in biology of marine ecosystems. Unification and analysis of large databases including space imagery and “cloud” technologies created a new trend of research in ecoinformatics; this allows to understand structural-functional organization of water ecosystems as a whole.
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Fouladinejad, F., A. Matkan, M. Hajeb, and F. Brakhasi. "HISTORY AND APPLICATIONS OF SPACE-BORNE LIDARS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 407–14. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-407-2019.
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Abstract. LIDAR (Light Detection and Ranging) is a laser altimeter system that determines the distance by measuring pulse travel time. The data from the LIDAR systems provide unique information on the vertical structure of land covers. Compared to ground-based and airborne LIDARs providing a high-resolution digital surface model, space-borne LIDARs can provide important information about the vertical profile of the atmosphere in a global scale. The overall objective of these satellites is to study the elevation changes and the vertical distribution of clouds and aerosols. In this paper an overview on the space-borne laser scanner satellites are accomplished and their applications are introduced. The first space-borne LIDAR is the ICESat (Ice, Cloud and land Elevation Satellite) satellite carrying the GLAS instrument which was launched in January 2003. The CALIPSO (the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, 2006), CATS-ISS (the Cloud-Aerosol Transport System, 2015), ADM-Aeolus (Atmospheric Dynamics Mission, 2018), and ICESat-2 (Ice, Cloud and land Elevation Satellite-2, 2018) satellites were respectively lunched and began to receive information about the vertical structure of the atmosphere and land cover. In addition, two ACE (The Aerosol-Cloud-Ecosystems, 2022) and EarthCARE (Earth Clouds, Aerosols and Radiation Explorer, 2021) space-borne satellites were planned for future. The data of the satellites are increasingly utilized to improve the numerical weather predictions (NWP) and climate modeling.
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Fast, Jerome D., Larry K. Berg, Lizbeth Alexander, David Bell, Emma D’Ambro, John Hubbe, Chongai Kuang, et al. "Overview of the HI-SCALE Field Campaign: A New Perspective on Shallow Convective Clouds." Bulletin of the American Meteorological Society 100, no. 5 (May 2019): 821–40. http://dx.doi.org/10.1175/bams-d-18-0030.1.
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AbstractShallow convective clouds are common, occurring over many areas of the world, and are an important component in the atmospheric radiation budget. In addition to synoptic and mesoscale meteorological conditions, land–atmosphere interactions and aerosol–radiation–cloud interactions can influence the formation of shallow clouds and their properties. These processes exhibit large spatial and temporal variability and occur at the subgrid scale for all current climate, operational forecast, and cloud-system-resolving models; therefore, they must be represented by parameterizations. Uncertainties in shallow cloud parameterization predictions arise from many sources, including insufficient coincident data needed to adequately represent the coupling of cloud macrophysical and microphysical properties with inhomogeneity in the surface-layer, boundary layer, and aerosol properties. Predictions of the transition of shallow to deep convection and the onset of precipitation are also affected by errors in simulated shallow clouds. Coincident data are a key factor needed to achieve a more complete understanding of the life cycle of shallow convective clouds and to develop improved model parameterizations. To address these issues, the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the Atmospheric Radiation Measurement (ARM) Southern Great Plains site in north-central Oklahoma during the spring and summer of 2016. We describe the scientific objectives of HI-SCALE as well as the experimental approach, overall weather conditions during the campaign, and preliminary findings from the measurements. Finally, we discuss scientific gaps in our understanding of shallow clouds that can be addressed by analysis and modeling studies that use HI-SCALE data.
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Kremser, Stefanie, Mike Harvey, Peter Kuma, Sean Hartery, Alexia Saint-Macary, John McGregor, Alex Schuddeboom, et al. "Southern Ocean cloud and aerosol data: a compilation of measurements from the 2018 Southern Ocean Ross Sea Marine Ecosystems and Environment voyage." Earth System Science Data 13, no. 7 (July 2, 2021): 3115–53. http://dx.doi.org/10.5194/essd-13-3115-2021.
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Abstract. Due to its remote location and extreme weather conditions, atmospheric in situ measurements are rare in the Southern Ocean. As a result, aerosol–cloud interactions in this region are poorly understood and remain a major source of uncertainty in climate models. This, in turn, contributes substantially to persistent biases in climate model simulations such as the well-known positive shortwave radiation bias at the surface, as well as biases in numerical weather prediction models and reanalyses. It has been shown in previous studies that in situ and ground-based remote sensing measurements across the Southern Ocean are critical for complementing satellite data sets due to the importance of boundary layer and low-level cloud processes. These processes are poorly sampled by satellite-based measurements and are often obscured by multiple overlying cloud layers. Satellite measurements also do not constrain the aerosol–cloud processes very well with imprecise estimation of cloud condensation nuclei. In this work, we present a comprehensive set of ship-based aerosol and meteorological observations collected on the 6-week Southern Ocean Ross Sea Marine Ecosystem and Environment voyage (TAN1802) voyage of RV Tangaroa across the Southern Ocean, from Wellington, New Zealand, to the Ross Sea, Antarctica. The voyage was carried out from 8 February to 21 March 2018. Many distinct, but contemporaneous, data sets were collected throughout the voyage. The compiled data sets include measurements from a range of instruments, such as (i) meteorological conditions at the sea surface and profile measurements; (ii) the size and concentration of particles; (iii) trace gases dissolved in the ocean surface such as dimethyl sulfide and carbonyl sulfide; (iv) and remotely sensed observations of low clouds. Here, we describe the voyage, the instruments, and data processing, and provide a brief overview of some of the data products available. We encourage the scientific community to use these measurements for further analysis and model evaluation studies, in particular, for studies of Southern Ocean clouds, aerosol, and their interaction. The data sets presented in this study are publicly available at https://doi.org/10.5281/zenodo.4060237 (Kremser et al., 2020).
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MacGregor-Fors, Ian, Ina Falfán, Michelle García-Arroyo, Richard Lemoine-Rodríguez, Miguel A. Gómez-Martínez, Oscar H. Marín-Gómez, Octavio Pérez-Maqueo, and Miguel Equihua. "A Novel Approach for the Assessment of Cities through Ecosystem Integrity." Land 11, no. 1 (December 21, 2021): 3. http://dx.doi.org/10.3390/land11010003.
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To tackle urban heterogeneity and complexity, several indices have been proposed, commonly aiming to provide information for decision-makers. In this study, we propose a novel and customizable procedure for quantifying urban ecosystem integrity. Based on a citywide approach, we developed an easy-to-use index that contrasts physical and biological variables of urban ecosystems with a given reference system. The Urban Ecosystem Integrity Index (UEII) is the sum of the averages from the variables that make up its intensity of urbanization and biological components. We applied the UEII in a Mexican tropical city using land surface temperature, built cover, and the richness of native plants and birds. The overall ecosystem integrity of the city, having montane cloud, tropical dry, and temperate forests as reference systems, was low (−0.34 ± SD 0.32), showing that, beyond its biodiverse greenspace network, the built-up structure highly differs from the ecosystems of reference. The UEII showed to be a flexible and easy-to-calculate tool to evaluate ecosystem integrity for cities, allowing for comparisons between or among cities, as well as the sectors/regions within cities. If used properly, the index could become a useful tool for decision making and resource allocation at a city level.
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Chang, Yunhua, Yan-Lin Zhang, Jiarong Li, Chongguo Tian, Linlin Song, Xiaoyao Zhai, Wenqi Zhang, et al. "Isotopic constraints on the atmospheric sources and formation of nitrogenous species in clouds influenced by biomass burning." Atmospheric Chemistry and Physics 19, no. 19 (October 2, 2019): 12221–34. http://dx.doi.org/10.5194/acp-19-12221-2019.
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Abstract. Predicting tropospheric cloud formation and subsequent nutrient deposition relies on understanding the sources and processes affecting aerosol constituents of the atmosphere that are preserved in cloud water. However, this challenge is difficult to address quantitatively based on the sole use of bulk chemical properties. Nitrogenous aerosols, mainly ammonium (NH4+) and nitrate (NO3-), play a particularly important role in tropospheric cloud formation. While dry and wet (mainly rainfall) deposition of NH4+ and NO3- are regularly assessed, cloud water deposition is often underappreciated. Here we collected cloud water samples at the summit of Mt. Tai (1545 m above sea level) in eastern China during a long-lasting biomass burning (BB) event and simultaneously measured for the first time the isotopic compositions (mean ±1σ) of cloud water nitrogen species (δ15N-NH4+ = −6.53 ‰ ± 4.96 ‰, δ15N-NO3- = −2.35 ‰ ± 2.00 ‰, δ18O-NO3- = 57.80 ‰ ± 4.23 ‰), allowing insights into their sources and potential transformation mechanism within the clouds. Large contributions of BB to the cloud water NH4+ (32.9 % ± 4.6 %) and NO3- (28.2 % ± 2.7 %) inventories were confirmed through a Bayesian isotopic mixing model, coupled with our newly developed computational quantum chemistry module. Despite an overall reduction in total anthropogenic NOx emission due to effective emission control actions and stricter emission standards for vehicles, the observed cloud δ15N-NO3- values suggest that NOx emissions from transportation may have exceeded emissions from coal combustion. δ18O-NO3- values imply that the reaction of OH with NO2 is the dominant pathway of NO3- formation (57 % ± 11 %), yet the contribution of heterogeneous hydrolysis of dinitrogen pentoxide was almost as important (43 % ± 11 %). Although the limited sample set used here results in a relatively large uncertainty with regards to the origin of cloud-associated nitrogen deposition, the high concentrations of inorganic nitrogen imply that clouds represent an important source of nitrogen, especially for nitrogen-limited ecosystems in remote areas. Further simultaneous and long-term sampling of aerosol, rainfall, and cloud water is vital for understanding the anthropogenic influence on nitrogen deposition in the study region.
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Susanto, Heru, Fang-Yie Leu, Wahyu Caesarendra, Fahmi Ibrahim, Parastou Khodaparast Haghi, Uus Khusni, and Adam Glowacz. "Managing Cloud Intelligent Systems over Digital Ecosystems: Revealing Emerging App Technology in the Time of the COVID19 Pandemic." Applied System Innovation 3, no. 3 (September 7, 2020): 37. http://dx.doi.org/10.3390/asi3030037.
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The COVID19 pandemic has indirectly changed the landscape of the business environment system through cloud intelligence within the digital ecosystem that has as a goal increasing the access, efficiency, effectiveness, equity and quality of business processes through cloud intelligent systems. Cloud intelligent systems are becoming revolutionary in today’s world pandemic causing a complete and drastic change to a variety of industries, including, security, transportation, business, logistics and manufacturing. The main purpose of cloud intelligence systems is to facilitate the ease of access from any location and the management of practical computing resources. One of the challenges faced by cloud technology today is scheduling. The role of scheduling algorithms is very important, since tasks are executed by orders that may need more attention. Here, scheduling algorithms intended to minimize monetary cost and minimize makespan time to execute the workflow are presented. This study proposes cloud intelligent systems apps through an approach to cloud computing scheduling that may lead to great benefits and efficiency. The result is very promising. It showed that there are numerous applications of intelligent systems due to the more advanced hardware being built nowadays, plus business processes advancing to become smarter and more efficient in growing profitably over a destructive digital ecosystem during the COVID19 pandemic. The results indicate that intelligent systems over the cloud play a big role not just for interacting with the world helping businesses grow, but as well as in the advancement for a better tomorrow.
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Knippertz, Peter, Hugh Coe, J. Christine Chiu, Mat J. Evans, Andreas H. Fink, Norbert Kalthoff, Catherine Liousse, et al. "The DACCIWA Project: Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa." Bulletin of the American Meteorological Society 96, no. 9 (September 1, 2015): 1451–60. http://dx.doi.org/10.1175/bams-d-14-00108.1.
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Abstract Massive economic and population growth, and urbanization are expected to lead to a tripling of anthropogenic emissions in southern West Africa (SWA) between 2000 and 2030. However, the impacts of this on human health, ecosystems, food security, and the regional climate are largely unknown. An integrated assessment is challenging due to (a) a superposition of regional effects with global climate change; (b) a strong dependence on the variable West African monsoon; (c) incomplete scientific understanding of interactions between emissions, clouds, radiation, precipitation, and regional circulations; and (d) a lack of observations. This article provides an overview of the DACCIWA (Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa) project. DACCIWA will conduct extensive fieldwork in SWA to collect high-quality observations, spanning the entire process chain from surface-based natural and anthropogenic emissions to impacts on health, ecosystems, and climate. Combining the resulting benchmark dataset with a wide range of modeling activities will allow (a) assessment of relevant physical, chemical, and biological processes; (b) improvement of the monitoring of climate and atmospheric composition from space; and (c) development of the next generation of weather and climate models capable of representing coupled cloud–aerosol interactions. The latter will ultimately contribute to reduce uncertainties in climate predictions. DACCIWA collaborates closely with operational centers, international programs, policymakers, and users to actively guide sustainable future planning for West Africa. It is hoped that some of DACCIWA’s scientific findings and technical developments will be applicable to other monsoon regions.
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Hilker, Thomas, Alexei I. Lyapustin, Compton J. Tucker, Piers J. Sellers, Forrest G. Hall, and Yujie Wang. "Remote sensing of tropical ecosystems: Atmospheric correction and cloud masking matter." Remote Sensing of Environment 127 (December 2012): 370–84. http://dx.doi.org/10.1016/j.rse.2012.08.035.
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Weathers, Kathleen C. "The importance of cloud and fog in the maintenance of ecosystems." Trends in Ecology & Evolution 14, no. 6 (June 1999): 214–15. http://dx.doi.org/10.1016/s0169-5347(99)01635-3.
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Sequeiros, João B. F., Francisco T. Chimuco, Musa G. Samaila, Mário M. Freire, and Pedro R. M. Inácio. "Attack and System Modeling Applied to IoT, Cloud, and Mobile Ecosystems." ACM Computing Surveys 53, no. 2 (July 2020): 1–32. http://dx.doi.org/10.1145/3376123.
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Pym, David, and Martin Sadler. "Information Stewardship in Cloud Computing." International Journal of Service Science, Management, Engineering, and Technology 1, no. 1 (January 2010): 50–67. http://dx.doi.org/10.4018/jssmet.2010010104.
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Cloud computing ecosystems of service providers and consumers will become a significant part of the way information services are provided, allowing more agile coalitions, cost savings and improved service delivery. Existing approaches to information security do not readily extend to this complex multi-party world. The authors argue for a mathematical model-based framework for the analysis and management of information stewardship that makes explicit both the expectations and responsibilities of cloud stakeholders and the design assumptions of systems. Such a framework supports integrated economic, technology, and behavioural analyses, so providing a basis for a better understanding of the interplay between preferences, policies, system design, regulations, and Service Level Agreements. The authors suggest approaches to constructing economic, technology, and behavioural models and discuss the challenges in integrating them.
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Abril, Adriana B., and Enrique H. Bucher. "Variation in soil biological characteristics on an elevational gradient in the montane forest of north-west Argentina." Journal of Tropical Ecology 24, no. 4 (July 2008): 457–61. http://dx.doi.org/10.1017/s0266467408005154.
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Montane tropical and subtropical rain forests are complex ecosystems, characterized by marked rainfall and temperature gradients with altitude, which in turn control the vegetation altitudinal zones (Hueck 1978). Montane forests are often referred to as cloud forests in recognition of the important influence of a dense and frequent cloud cover that conditions forest structure and functioning (Bautista-Cruz & del Castillo 2005, Holder 2004).
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Gaw, Yee, and Richards. "A High-Resolution Map of Singapore’s Terrestrial Ecosystems." Data 4, no. 3 (August 1, 2019): 116. http://dx.doi.org/10.3390/data4030116.
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The natural and semi-natural areas within cities provide important refuges for biodiversity, as well as many benefits to people. To study urban ecology and quantify the benefits of urban ecosystems, we need to understand the spatial extent and configuration of different types of vegetated cover within a city. It is challenging to map urban ecosystems because they are typically small and highly fragmented; thus requiring high resolution satellite images. This article describes a new high-resolution map of land cover for the tropical city-state of Singapore. We used images from WorldView and QuickBird satellites, and classified these images using random forest machine learning and supplementary datasets into 12 terrestrial land classes. Close to 50 % of Singapore’s land cover is vegetated while freshwater fills about 6 %, and the rest is bare or built up. The overall accuracy of the map was 79 % and the class-specific errors are described in detail. Tropical regions such as Singapore have a lot of cloud cover year-round, complicating the process of mapping using satellite imagery. The land cover map provided here will have applications for urban biodiversity studies, ecosystem service quantification, and natural capital assessment.
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Manekar, Amitkumar, and Dr Pradeepini Gera. "Studying Cloud as IaaS for Big Data Analytics : Opportunity, Challenges." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 909. http://dx.doi.org/10.14419/ijet.v7i2.7.11094.
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James Watt steam engine revolution was greatest revolution in mankind history in 20th century. In 1776, the first steam engines were installed and working in commercial enterprises. This revolution minimize and make world smaller for human being, now world is connected seamlessly. “Big Data Analytics and Cloud” these two words are second numerous revolutions in 21st century. We are living in an era of information explosion. These two magical terms are nothing but relatively very new and fortunately diverted all market trends to a new era of computation in last decade. As these two emerging technology are their early childhood, many people were confused with its relevancy and applicability. Cloud Computing is Infrastructure based solution for managing data and computational framework. 2016 was a significantly more important year for this volumes data technology or Big Data eco system as large number of enterprises, and organizations are generating data, storing that data and worried about future aspect of that data. In 2017, corporate world take cognizance of their large volumes structured and unstructured data as these enterprises and organizations continuously generating large volumes data. The term big data doesn’t just refer to the massive amounts of data existing today, it also refers to the whole ecosystem of Storing or gathering data, Different types of data and analyzing that data. In traditional data ecosystem all leverages are with legacy system. Transforming or migration of these traditional ecosystems to the cloud is full of great challenges and benefits. Cloud computing is an agile and scalable resource access computation paradigm, provides heterogeneous platform seamlessly with infrastructure of internet, exclusively for the trapped and work on pre and post process of big data. Now the challenges are finding opportunity and challenges for managing, migrating and abstracting cloud based big data using cloud infrastructure for future eco system of Big Data Analysis. This paper is basically focused on this issue. We try to reevaluate the facts of existing Cloud Infrastructure as IaaS for tomorrow’s big data analytics.
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Sanchez, Kevin J., Bo Zhang, Hongyu Liu, Matthew D. Brown, Ewan C. Crosbie, Francesca Gallo, Johnathan W. Hair, et al. "North Atlantic Ocean SST-gradient-driven variations in aerosol and cloud evolution along Lagrangian cold-air outbreak trajectories." Atmospheric Chemistry and Physics 22, no. 4 (March 2, 2022): 2795–815. http://dx.doi.org/10.5194/acp-22-2795-2022.
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Abstract. Atmospheric marine particle concentrations impact cloud properties, which strongly impact the amount of solar radiation reflected back into space or absorbed by the ocean surface. While satellites can provide a snapshot of current conditions at the overpass time, models are necessary to simulate temporal variations in both particle and cloud properties. However, poor model accuracy limits the reliability with which these tools can be used to predict future climate. Here, we leverage the comprehensive ocean ecosystem and atmospheric aerosol–cloud dataset obtained during the third deployment of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES3). Airborne and ship-based measurements were collected in and around a cold-air outbreak during a 3 d (where d stands for day) intensive operations period from 17–19 September 2017. Cold-air outbreaks are of keen interest for model validation because they are challenging to accurately simulate, which is due, in part, to the numerous feedbacks and sub-grid-scale processes that influence aerosol and cloud evolution. The NAAMES observations are particularly valuable because the flight plans were tailored to lie along Lagrangian trajectories, making it possible to spatiotemporally connect upwind and downwind measurements with the state-of-the-art FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model and then calculate a rate of change in particle properties. Initial aerosol conditions spanning an east–west, closed-cell-to-clear-air transition region of the cold-air outbreak indicate similar particle concentrations and properties. However, despite the similarities in the aerosol fields, the cloud properties downwind of each region evolved quite differently. One trajectory carried particles through a cold-air outbreak, resulting in a decrease in accumulation mode particle concentration (−42 %) and cloud droplet concentrations, while the other remained outside of the cold-air outbreak and experienced an increase in accumulation mode particle concentrations (+62 %). The variable meteorological conditions between these two adjacent trajectories result from differences in the local sea surface temperature in the Labrador Current and surrounding waters, altering the stability of the marine atmospheric boundary layer. Further comparisons of historical satellite observations indicate that the observed pattern occurs annually in the region, making it an ideal location for future airborne Lagrangian studies tracking the evolution of aerosols and clouds over time under cold-air outbreak conditions.
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Yoon, Younghan, and Sang Leen Yun. "Methodology for Topographic Survey of Carbon Absorption Sources in Stream Wetland Using Industrial Drone." Journal of Korean Society of Environmental Engineers 44, no. 12 (December 31, 2022): 616–26. http://dx.doi.org/10.4491/ksee.2022.44.12.616.
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As the increase of carbon dioxide in atmospheric accelerates climate change, various efforts have been performed to reduce carbon worldwide. Recently, as the concept of green carbon stored and sequestrated through photosynthesis by land plants has been emphasized to reduce carbon content from environments, the importance of carbon absorption survey for plant groups analysis of terrestrial ecosystems such as forests and river wetlands is increasing. Carbon absorption sources in terrestrial ecosystems exist in various forms of plant, soil, and topography, and represent various carbon absorption through physical, chemical and biological reactions between each other depending on the location and height of the plant groups. In this study, an industrial RTK drone capable of taking high-resolution images was used for efficient carbon absorption survey in Damyang stream wetland. Based on the global navigation satellite system by RTK, the location could be corrected in real time, and ecosystem surveys could be conducted on the height of the terrain with RTK drone. The point cloud technique of the high-density surface model was used to analyze the three-dimensional topography of areas that are difficult to access. Using the photo survey function of the RTK drone, it is expected to play an important role in understanding the total amount of green carbon of terrestrial ecosystems and carbon circulation of the land ecosystem by enabling the creation of topographic maps of stream wetlands, and riparian vegetation with complex terrain.
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Basole, Rahul C., and Hyunwoo Park. "Interfirm Collaboration and Firm Value in Software Ecosystems: Evidence From Cloud Computing." IEEE Transactions on Engineering Management 66, no. 3 (August 2019): 368–80. http://dx.doi.org/10.1109/tem.2018.2855401.
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Ferrández-Pastor, Francisco Javier, Juan Manuel García-Chamizo, Sergio Gomez-Trillo, Rafael Valdivieso-Sarabia, and Mario Nieto-Hidalgo. "Smart Management Consumption in Renewable Energy Fed Ecosystems." Sensors 19, no. 13 (July 5, 2019): 2967. http://dx.doi.org/10.3390/s19132967.
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Advances in embedded electronic systems, the development of new communication protocols, and the application of artificial intelligence paradigms have enabled the improvement of current automation systems of energy management. Embedded devices integrate different sensors with connectivity, computing resources, and reduced cost. Communication and cloud services increase their performance; however, there are limitations in the implementation of these technologies. If the cloud is used as the main source of services and resources, overload problems will occur. There are no models that facilitate the complete integration and interoperability in the facilities already created. This article proposes a model for the integration of smart energy management systems in new and already created facilities, using local embedded devices, Internet of Things communication protocols and services based on artificial intelligence paradigms. All services are distributed in the new smart grid network using edge and fog computing techniques. The model proposes an architecture both to be used as support for the development of smart services and for energy management control systems adapted to the installation: a group of buildings and/or houses that shares energy management and energy generation. Machine learning to predict consumption and energy generation, electric load classification, energy distribution control, and predictive maintenance are the main utilities integrated. As an experimental case, a facility that incorporates wind and solar generation is used for development and testing. Smart grid facilities, designed with artificial intelligence algorithms, implemented with Internet of Things protocols, and embedded control devices facilitate the development, cost reduction, and the integration of new services. In this work, a method to design, develop, and install smart services in self-consumption facilities is proposed. New smart services with reduced costs are installed and tested, confirming the advantages of the proposed model.
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Burrows, S. M., T. Butler, P. Jöckel, H. Tost, A. Kerkweg, U. Pöschl, and M. G. Lawrence. "Bacteria in the global atmosphere – Part 2: Modelling of emissions and transport between different ecosystems." Atmospheric Chemistry and Physics Discussions 9, no. 3 (May 4, 2009): 10829–81. http://dx.doi.org/10.5194/acpd-9-10829-2009.
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Abstract. Bacteria are constantly being transported through the atmosphere, which may have implications for human health, agriculture, cloud formation, and the dispersal of bacterial species. We simulated the global transport of bacterial cells, represented as 1μm diameter spherical solid particle tracers, in a chemistry-climate model. We investigated the factors influencing residence time and distribution of the particles, including emission region, CCN activity and removal by ice-phase precipitation. The global distribution depends strongly on the assumptions made about uptake into cloud droplets and ice. The transport is also affected, to a lesser extent, by the emission region and by season. We examine the potential for exchange of bacteria between ecosystems and obtain rough estimates of the flux from each ecosystem by using an optimal estimation technique, together with a new compilation of available observations described in a companion paper. Globally, we estimate the total emissions of bacteria to the atmosphere to be 1400 Gg per year with an upper bound of 4600 Gg per year, originating mainly from grasslands, shrubs and crops. In order to improve understanding of this topic, more measurements of the bacterial content of the air will be necessary. Future measurements in wetlands, sandy deserts, tundra, remote glacial and coastal regions and over oceans will be of particular interest.
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Kavzoglu, Taskin, and Merve Goral. "Google Earth Engine for Monitoring Marine Mucilage: Izmit Bay in Spring 2021." Hydrology 9, no. 8 (July 28, 2022): 135. http://dx.doi.org/10.3390/hydrology9080135.
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Global warming together with environmental pollution threatens marine habitats and causes an increasing number of environmental disasters. Periodic monitoring of coastal water quality is of critical importance for the effective management of water resources and the sustainability of marine ecosystems. The use of remote sensing technologies provides significant benefits for detecting, monitoring, and analyzing rapidly occurring and displaced natural phenomena, including mucilage events. In this study, five water indices estimated from cloud-free and partly cloudy Sentinel-2 images acquired from May to July 2021 were employed to effectively map mucilage aggregates on the sea surface in the Izmit Bay using the cloud-based Google Earth Engine (GEE) platform. Results showed that mucilage aggregates started with the coverage of about 6 km² sea surface on 14 May, reached the highest level on 24 May and diminished at the end of July. Among the applied indices, the Adjusted Floating Algae Index (AFAI) was superior for producing the mucilage maps even for the partly cloudy image, followed by Normalized Difference Turbidity Index (NDTI) and Mucilage Index (MI). To be more specific, indices using green channel were found to be inferior for extracting mucilage information from the satellite images.
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Fahey, Timothy J., Ruth E. Sherman, and Edmund V. J. Tanner. "Tropical montane cloud forest: environmental drivers of vegetation structure and ecosystem function." Journal of Tropical Ecology 32, no. 5 (November 9, 2015): 355–67. http://dx.doi.org/10.1017/s0266467415000176.
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Abstract:Tropical montane cloud forests (TMCF) are characterized by short trees, often twisted with multiple stems, with many stems per ground area, a large stem diameter to height ratio, and small, often thick leaves. These forests exhibit high root to shoot ratio, with a moderate leaf area index, low above-ground production, low leaf nutrient concentrations and often with luxuriant epiphytic growth. These traits of TMCF are caused by climatic conditions not geological substrate, and are particularly associated with frequent or persistent fog and low cloud. There are several reasons why fog might result in these features. Firstly, the fog and clouds reduce the amount of light received per unit area of ground and as closed-canopy forests absorb most of the light that reaches them the reduction in the total amount of light reduces growth. Secondly, the rate of photosynthesis per leaf area declines in comparison with that in the lowlands, which leads to less carbon fixation. Nitrogen supply limits growth in several of the few TMCFs where it has been investigated experimentally. High root : shoot biomass and production ratios are common in TMCF, and soils are often wet which may contribute to N limitation. Further study is needed to clarify the causes of several key features of TMCF ecosystems including high tree diameter : height ratio.
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Abhilasha, Abhilasha, and Dr Anupama Gupta. "POWER EFFICIENT TASK SCHEDULING MECHANISM IN CLOUD ENVIRONMENT: A REVIEW." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 15, no. 11 (August 26, 2016): 7253–57. http://dx.doi.org/10.24297/ijct.v15i11.4349.
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Cloud Computing is being used widely all over the world by many IT companies as it provides various benefits to the users like cost saving and ease of use. However, with the growing demands of users for computing services, cloud providers are encouraged to deploy large datacenters which consume very high amount of energy and also contribute to the increase in carbon dioxide emission in the environment. Therefore, we require to develop techniques which will help to get more environment friendly computing i.e. Green Cloud Computing. In this paper, we have reviewed the existing mechanisms and a new strategy to reduce the carbon dioxide emissions in federated Cloud ecosystems. More specifically, we propose a solution that allows providers to determine the best green destination to reduce the carbon dioxide emissions of the whole federated environment.
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Álvarez-Castañón, Lorena del Carmen. "Technology transfer 4.0 in Latin American innovation ecosystems." Teuken Bidikay - Revista Latinoamericana de Investigación en Organizaciones, Ambiente y Sociedad 11, no. 17 (December 2020): 181–96. http://dx.doi.org/10.33571/teuken.v11n17a10.
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This paper analysed the processes of technology transfer 4.0, its conditions and the main transferable technological trends in Latin America. The complexity approach in the ecosystem allowed to explain how the actors or subsystems are (re)adapted or (re)learned based on their interaction without being managed by any specific entity or component. The methodological process consisted of a scientometric analysis, a thematic analysis based on the projects financed with public resources from 2002 to 2018, and an analysis of the innovation ecosystem in the emerging region of the Mexican Bajío. The findings showed the relevance of intermediate organisms in social leadership for technology transfer; big data, IoT and cloud computing are the main technologies 4.0 that are potentially transferable to respond to territorial heterogeneous conditions.
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Pérez-Irineo, Gabriela, Alejandro Hernández-Sánchez, and Antonio Santos-Moreno. "Effect of anthropogenic activity on mammal activity patterns in two ecosystems." Mammalia 85, no. 4 (April 5, 2021): 336–44. http://dx.doi.org/10.1515/mammalia-2020-0084.
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Abstract Adaptations in species activity patterns allow animals to avoid risks generated by human activities and domestic and feral species. We aimed to evaluate the effect of anthropogenic activity on mammal activity patterns in two tropical ecosystems -semi-evergreen forest and cloud forest-, and its temporal variation in the Sierra Norte of Oaxaca, Mexico. We expected mammal activity patterns to show significant differences from activity patterns of humans and domestic species. From July 2014 to June 2015, we placed camera traps in 23 sites in a semi-evergreen forest and 23 sites in a cloud forest. We estimated the activity level of each species and calculated the activity overlap between wild species and humans and domestic species in each season. We recorded a total of 16 species of wild mammals, four domestic species, and obtained 738 human records. We found no evidence of an effect of anthropogenic activity on the activity patterns of wild mammals: we found similar activity levels between seasons and ecosystems, and moderate to high overlap between the activity patterns of some wild mammal species and of humans and domestic species. Low human population density, human activity temporal dynamics, and the plasticity of wild species could explain the results of our study.
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Burrows, S. M., T. Butler, P. Jöckel, H. Tost, A. Kerkweg, U. Pöschl, and M. G. Lawrence. "Bacteria in the global atmosphere – Part 2: Modeling of emissions and transport between different ecosystems." Atmospheric Chemistry and Physics 9, no. 23 (December 10, 2009): 9281–97. http://dx.doi.org/10.5194/acp-9-9281-2009.
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Abstract. Bacteria are constantly being transported through the atmosphere, which may have implications for human health, agriculture, cloud formation, and the dispersal of bacterial species. We simulate the global transport of bacteria, represented as 1 μm and 3 μm diameter spherical solid particle tracers in a general circulation model. We investigate factors influencing residence time and distribution of the particles, including emission region, cloud condensation nucleus activity and removal by ice-phase precipitation. The global distribution depends strongly on the assumptions made about uptake into cloud droplets and ice. The transport is also affected, to a lesser extent, by the emission region, particulate diameter, and season. We find that the seasonal variation in atmospheric residence time is insufficient to explain by itself the observed seasonal variation in concentrations of particulate airborne culturable bacteria, indicating that this variability is mainly driven by seasonal variations in culturability and/or emission strength. We examine the potential for exchange of bacteria between ecosystems and obtain rough estimates of the flux from each ecosystem by using a maximum likelihood estimation technique, together with a new compilation of available observations described in a companion paper. Globally, we estimate the total emissions of bacteria-containing particles to the atmosphere to be 7.6×1023–3.5×1024 a−1, originating mainly from grasslands, shrubs and crops. We estimate the mass of emitted bacteria- to be 40–1800 Gg a−1, depending on the mass fraction of bacterial cells in the particles. In order to improve understanding of this topic, more measurements of the bacterial content of the air and of the rate of surface-atmosphere exchange of bacteria will be necessary. Future observations in wetlands, hot deserts, tundra, remote glacial and coastal regions and over oceans will be of particular interest.
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Ghorbanian, Arsalan, Soheil Zaghian, Reza Mohammadi Asiyabi, Meisam Amani, Ali Mohammadzadeh, and Sadegh Jamali. "Mangrove Ecosystem Mapping Using Sentinel-1 and Sentinel-2 Satellite Images and Random Forest Algorithm in Google Earth Engine." Remote Sensing 13, no. 13 (June 30, 2021): 2565. http://dx.doi.org/10.3390/rs13132565.
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Mangroves are among the most productive ecosystems in existence, with many ecological benefits. Therefore, generating accurate thematic maps from mangrove ecosystems is crucial for protecting, conserving, and reforestation planning for these valuable natural resources. In this paper, Sentinel-1 and Sentinel-2 satellite images were used in synergy to produce a detailed mangrove ecosystem map of the Hara protected area, Qeshm, Iran, at 10 m spatial resolution within the Google Earth Engine (GEE) cloud computing platform. In this regard, 86 Sentinel-1 and 41 Sentinel-2 data, acquired in 2019, were employed to generate seasonal optical and synthetic aperture radar (SAR) features. Afterward, seasonal features were inserted into a pixel-based random forest (RF) classifier, resulting in an accurate mangrove ecosystem map with average overall accuracy (OA) and Kappa coefficient (KC) of 93.23% and 0.92, respectively, wherein all classes (except aerial roots) achieved high producer and user accuracies of over 90%. Furthermore, comprehensive quantitative and qualitative assessments were performed to investigate the robustness of the proposed approach, and the accurate and stable results achieved through cross-validation and consistency checks confirmed its robustness and applicability. It was revealed that seasonal features and the integration of multi-source remote sensing data contributed towards obtaining a more reliable mangrove ecosystem map. The proposed approach relies on a straightforward yet effective workflow for mangrove ecosystem mapping, with a high rate of automation that can be easily implemented for frequent and precise mapping in other parts of the world. Overall, the proposed workflow can further improve the conservation and sustainable management of these valuable natural resources.
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Jing, Yinghong, Xinghua Li, and Huanfeng Shen. "STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China." Earth System Science Data 14, no. 7 (July 11, 2022): 3137–56. http://dx.doi.org/10.5194/essd-14-3137-2022.
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Abstract. Snow dynamics are crucial in ecosystems, affecting radiation balance, hydrological cycles, biodiversity, and human activities. Snow areas with notably diverse characteristics are extensively distributed in China, mainly including Northern Xinjiang (NX), Northeast China (NC), and the Qinghai–Tibet Plateau (QTP). Spatiotemporal continuous snow monitoring is indispensable for ecosystem maintenance. Nevertheless, the formidable challenge of cloud obscuration severely impedes data collection. In the past decades, abundant binary snow cover area (SCA) maps have been retrieved from moderate resolution imaging spectroradiometer (MODIS) datasets. However, the integrated normalized difference snow index (NDSI) maps containing additional details on snow cover extent are still extremely scarce. In this study, a recent 20-year stretch seamless Terra–Aqua MODIS NDSI collection in China is generated using a Spatio-Temporal Adaptive fusion method with erroR correction (STAR), which comprehensively considers spatial and temporal contextual information. Evaluation tests confirm that the cloud-free STAR NDSI collection is superior to the two baseline datasets. The omission error decreased by 10 % in NX compared to the snow cover extent product, and the average correlation coefficient increased by 0.11 compared to the global cloud-gap-filled MODIS NDSI product. Consequently, this collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues in China. This collection is available from https://doi.org/10.5281/zenodo.5644386 (Jing et al., 2021).
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Galí, Martí, Emmanuel Devred, Marcel Babin, and Maurice Levasseur. "Decadal increase in Arctic dimethylsulfide emission." Proceedings of the National Academy of Sciences 116, no. 39 (September 9, 2019): 19311–17. http://dx.doi.org/10.1073/pnas.1904378116.
Full textAbstract:
Dimethylsulfide (DMS), a gas produced by marine microbial food webs, promotes aerosol formation in pristine atmospheres, altering cloud radiative forcing and precipitation. Recent studies suggest that DMS controls aerosol formation in the summertime Arctic atmosphere and call for an assessment of pan-Arctic DMS emission (EDMS) in a context of dramatic ecosystem changes. Using a remote sensing algorithm, we show that summertime EDMS from ice-free waters increased at a mean rate of 13.3 ± 6.7 Gg S decade−1 (∼33% decade−1) north of 70°N between 1998 and 2016. This trend, mostly explained by the reduction in sea-ice extent, is consistent with independent atmospheric measurements showing an increasing trend of methane sulfonic acid, a DMS oxidation product. Extrapolation to an ice-free Arctic summer could imply a 2.4-fold (±1.2) increase in EDMS compared to present emission. However, unexpected regime shifts in Arctic geo- and ecosystems could result in future EDMS departure from the predicted range. Superimposed on the positive trend, EDMS shows substantial interannual changes and nonmonotonic multiyear trends, reflecting the interplay between physical forcing, ice retreat patterns, and phytoplankton productivity. Our results provide key constraints to determine whether increasing marine sulfur emissions, and resulting aerosol–cloud interactions, will moderate or accelerate Arctic warming in the context of sea-ice retreat and increasing low-level cloud cover.