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Global Climate Monitoring with Microwave Measurements

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Microwave Remote Sensing Tools in Environmental Science

Abstract

The rising cost of global climate change is partly due to natural disasters that will lead to potential negative impacts for many areas. There are problems encountered by many experts whose forecasts vary considerably. Maarten (2006) provides an overview of current knowledge about climate change and its effects on climate variability and extreme weather conditions that could lead to natural disasters, with particular attention to the applicability of information on disaster risk reduction. Extreme events may accompany a gradual rise in average global temperatures due to rising CO2 concentrations. First, the variability of the global climate appears in extreme weather. It is sufficient here to cite such extreme events of November 2018 as multiple wildfires in northern and southern California with tragic consequences. The phenomenon of extreme weather has occurred in the summer of May and June 2018 in almost all European countries, when nature provided events from flood droughts. Table 9.1 lists some of them.

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References

  • Abrahamson DE (1989) Challenge of global warming. Island Press, Washington

    Google Scholar 

  • Bilham R (2005) A flying start, then a slow slip. Science 308:1126–1127

    Article  Google Scholar 

  • Blowers A, Hinchliffe S (2003) Environmental responses. John Wiley & Sons, London

    Google Scholar 

  • Burkhart HE, Tomê M (2012) Modeling forest trees and stands. Springer Netherlands.

    Book  Google Scholar 

  • Butler JH, Montzka SA (2016) The NOAA annual greenhouse gas index (AGGI). NOAA Earth System Research Laboratory, Boulder. http://www.erst.noaa.gov/gmd/aggi.html

    Google Scholar 

  • Campbell JL, Rustad L, Boyer EW, Christopher S (2009) Consequences of climate change for biogeochemical cycling in forests of northeastern North America. Can J For Res 39:264–284

    Article  Google Scholar 

  • Chen X, Zhang X (2016) How environmental uncertainty moderated of relative advantage and perceived credibility on the adoption of mobile health services by Chinese organizations in the big data era. Int J Telemed Appl 2016:1–11. https://doi.org/10.1155/2016/3618402

    Article  Google Scholar 

  • Chernavsky DS (ed) (2004) Recognition, autodiagnostics, thinking: synergetics and human science. Radiotekhnika Publ, Moscow. [in Russian]

    Google Scholar 

  • Condie KC (2005) Earth as an evolving planetary system. Elsevier Academic, Burlington, MA

    Google Scholar 

  • Debertin DL (2012) Agricultural production economics. Macmillan Publishing Company, London

    Google Scholar 

  • Degermendzhi AG (2009) New directions in biophysical ecology. In: Cracknell AP, Krapivin VF, Varotsos CA (eds) Global climatology and Ecodynamics. Springer/Praxis, Chichester, pp 379–396

    Chapter  Google Scholar 

  • FAO (2001) Global forest resources assessment 2000. Main Report. FAO Forestry Paper, Rome, 140

    Google Scholar 

  • Field CB, Raupach MR (eds) (2004) Global carbon cycle: integrating humans, climate, and the natural world. Island Press, Washington

    Google Scholar 

  • Field JG, Hempel G, Summerhayer CP (eds) (2002) Oceans 2020: science trends and the challenge of sustainability. Island Press, Washington

    Google Scholar 

  • Forrester JW (1971) World dynamics. Wright - Allen Press, Cambridge, MA.

    Google Scholar 

  • Gardner JS (2002) Natural hazards risk in the Kullu District, Himachal Pradesh, India. Geogr Rev 92:172–177

    Article  Google Scholar 

  • Goldner J (2002) Messages from space. Michael Wiese Production, Suite

    Google Scholar 

  • Grigoryev AA, Kondratyev KYA (2001) Ecological catastrophes. The St.-Petersburg Scientific Centre of RAS, St.-Petersburg. [in Russian]

    Google Scholar 

  • Gyde LH (2012) Definitions of Forest, deforestation, afforestation, and reforestation. Forest Information Services, Gainesville

    Google Scholar 

  • Hales B, Takahashi T, Bandstra L (2005) Atmospheric CO2 uptake by a coastal upwelling system. Glob Biogeochem Cycles 19(GB1009):1–11

    Google Scholar 

  • Hardy JT (2003) Climate change. Wiley, Washington

    Google Scholar 

  • Hasenauer H (2006) Sustainable Forest management: growth models for Europe. Springer, Berlin

    Book  Google Scholar 

  • Hinchliffe S, Blowers A, Freeland J (2002) Understanding environmental issues. Wiley, London

    Google Scholar 

  • Ji Y, Stocker E (2002) Seasonal, intraseasonal, and interannual variability of global land fires and their effects on atmospheric aerosol distribution. J Geophys Res 107(D23):4697

    Article  Google Scholar 

  • Jönsson AM, Linderson M-L, Stjernquist I, Scglyter P, Bärring L (2004) Climate change and the effect of temperature backlashes causing frost damage in Picea abies. Glob Planet Chang 44(1–4):195–207

    Article  Google Scholar 

  • Kendrick TD (1957) The Lisbon earthquake. Lippincott, Philadelphia

    Google Scholar 

  • Kondratyev KYA, Krapivin VF, Phillips GW (2002) Global environmental change: modelling and monitoring. Springer, Berlin

    Book  Google Scholar 

  • Kondratyev KYA, Krapivin VF, Savinykh VP, Varotsos CA (2004) Global ecodynamics: a multidimensional analysis. Springer-Praxis, Chichester

    Book  Google Scholar 

  • Kondratyev KYA, Krapivin VF, Varotsos CA (2006) Natural disasters as interactive components of global ecodynamics. Springer/Praxis, Chichester

    Google Scholar 

  • Krapivin VF (1993) Mathematical model for global ecological investigations. Ecol Model 67(204):103–127

    Article  Google Scholar 

  • Krapivin VF, Kelley JJ (2009) Model-based method for the assessment of global change in a nature-society system. In: Cracknell AP, Krapivin VF, Varotsos CA (eds) Problems of global climatology and ecodynamics. Springer/Praxis, Chichester, pp 133–184

    Chapter  Google Scholar 

  • Krapivin VF, Shutko AM (2012) Information technologies for remote monitoring of the environment. Springer/Praxis, Chichester

    Book  Google Scholar 

  • Krapivin VF, Varotsos CA (2007) Globalization and sustainable development. Springer/Praxis, Chichester

    Google Scholar 

  • Krapivin VF, Varotsos CA (2008) Biogeochemical cycles in globalization and sustainable development. Springer/Praxis, Chichester

    Google Scholar 

  • Krapivin VF, Mkrtchyan FA, Ivanov MV (2005) Expert system for the operative environmental diagnostics. The 26th Asian conference on remote sensing (ACRS2005). Hanoi. 7–11 November 2005. Vietnam. Asian Association on Remote Sensing – 26th Asian conference on remote sensing and 2nd Asian space conference, ACRS 2005, 3, pp 1967–1975.

    Google Scholar 

  • Krapivin VF, Varotsos CA, Soldatov VY (2015a) New ecoinformatics tools in environmental science: applications and decision-making. Springer, London

    Book  Google Scholar 

  • Krapivin VF, Varotsos CA, Soldatov VY (2015b) New ecoinformatics tools in environmental science: applications and decision-making. Springer, London

    Book  Google Scholar 

  • Krapivin VF, Varotsos CA, Soldatov VY (2017a) The Earth’s population can reach 14 billion in the 23rd century without significant adverse effects on survivability. Int J Environ Res Public Health 14(8):3–18

    Article  Google Scholar 

  • Krapivin VF, Varotsos CA, Nghia BQ (2017b) A modeling system for monitoring water quality in lagoons. Water Air Soil Pollut 228(397):1–12

    Google Scholar 

  • Krapivin VF, Nitu C, Varotsos CA (2019) Microwave remote sensing tools and ecoinformatics. Matrix Rom, Bucharest

    Google Scholar 

  • Li J, Mao J (2016) Changes in the boreal summer intraseasonal oscillation projected by the CNRM-CM5 model under the RCP 8.5 scenario. Clim Dyn 47(12):3713–3736

    Article  Google Scholar 

  • Lindenmayer DB, Foster DR, Franklin JF, Hunter ML, Noss RF, Schmiegelow FA, Perry D (2004) Salvage harvesting policies after natural disturbance. Science 303(5662):1303

    Article  Google Scholar 

  • Lomborg B (2001) The skeptical environmentalist – measuring the real state of the world. Cambridge University Press, Cambridge

    Google Scholar 

  • Lucas JS, Southgate PC (2012) Aquaculture: farming aquatic animals and plants. Wiley, New York

    Book  Google Scholar 

  • Maarten KA (2006) The impacts of climate change on the risk of natural disasters. Disasters 30(1):5–18

    Article  Google Scholar 

  • McConnel WJ (2004) Forest cover change – tales of the unexpected. Global Change Newsl 57:8–11

    Google Scholar 

  • McNulty SG (2002) Hurricane impacts on US forest carbon sequestration. Environ Pollut 116:S17–S25

    Article  Google Scholar 

  • Milne A (2004) Doomsday: the science of catastrophic events. Praeger Publisher, Westport

    Google Scholar 

  • Moisseev NN (1979) Mathematics produces an experiment. Science Publ, Moscow. [in Russian]

    Google Scholar 

  • Monin AS, Shishkov YA (1991) The warming dilemmas in the 20th century. In: Monin AS (ed) Man and Chaos. Hydrometeoizdat, St. Petersburg, pp 47–49. [in Russian]

    Google Scholar 

  • Morris D, Freeland J, Hinchcliffe S, Smith S (2003) Changing environments. Wiley, London

    Google Scholar 

  • Nilsson K, Sangster M, Gallis C, Hartig T, de Vries S, Seeland K, Schipperijn J (eds) (2011) Forests, trees and human health. Springer, Dordrecht

    Google Scholar 

  • Nitu C, Krapivin VF, Bruno A (2000a) Intelligent techniques in ecology. Printech, Bucharest

    Google Scholar 

  • Nitu C, Krapivin VF, Bruno A (2000b) System modelling in ecology. Printech, Bucharest

    Google Scholar 

  • Nitu C, Krapivin VF, Pruteanu E (2004) Ecoinformatics: intelligent systems in ecology. – magic print. Onesti, Bucharest

    Google Scholar 

  • Nitu C, Krapivin VF, Soldatov VY (2013) Information-modeling technology for environmental investigations. Matrix ROM, Bucharest

    Google Scholar 

  • Oppenheimer C (1996) Volcanism. Geography 81(1):65–81

    Google Scholar 

  • Perrie W, Ren X, Zhang W, Long Z (2004) Simulation of extratropical Hurricane Gustav using a coupled atmosphere-ocean-sea spray model. Geophys Res Lett 31(3):L03110

    Article  Google Scholar 

  • Riahi K, Krey V, Rao S, Chirkov V, Fischer G, Kolp P, Kindermann G, Nakicenovic N, Rafai P (2011) RCP-8.5: exploring the consequence of high emission trajectories. Clim Chang 109(33). https://doi.org/10.1007/s10584-011-0149-y

  • Richter CF (1969) Earthquakes. Nat Hist 78:37–45

    Google Scholar 

  • Saavedra-Rivano N (1979) A critical analysis of the Mesarovic-Pestel world model. Appl Math Model 3(5):384–390

    Article  Google Scholar 

  • Sarlis NV, Skordas ES, Varotsos PA, Ramírez-Rojas A, Flores-Márquez EL (2018) Natural time analysis: on the deadly Mexico M8.2 earthquake on 7 September 2017. Physicol A 506:625–634

    Article  Google Scholar 

  • Sarlis NV, Skordas ES, Varotsos PA, Ramírez-Rojas A, Flores-Márquez EL (2019) Investigation of the temporal correlations between earthquake magnitudes before the Mexico M8.2 earthquake on 7 September 2017. Physicol A 517:475–483

    Article  Google Scholar 

  • Sellers PJ, Randall DA, Collotz GJ, Berry JA, Field CB, Dazlich DA, Zhang C, Collelo GD, Bounoua L (1996) A revised land surface parametrization (SiB2) for atmospheric GCMs. Part 1: model formulation. J Clim 9(4):676–705

    Article  Google Scholar 

  • Shi W, Zhang A, Zhou X, Min Z (2018) Challenges and prospects of uncertainties in spatial big data analysis. Ann Am Assoc Geogr 108(6):1513–1520

    Google Scholar 

  • Silver D (1998) Tropical rain Forest. McGraw-Hill, New York

    Google Scholar 

  • Sudarshana P, Nageswara M, Soneji JR (2012) Tropical forests. InTech, New York

    Book  Google Scholar 

  • Tarko AM (2003) Analysis of global and regional changes in biogeochemical carbon cycle: a spatially distributed model. Interim report, IR-03-041. IIASA, Laxenburg

    Google Scholar 

  • Varotsos P (2005) The physics of seismic electric signals. TerraPub, Tokyo

    Google Scholar 

  • Varotsos P, Alexopoulos K (1984a) Physical properties of the variations of the electric field of the earth preceding earthquakes, I. Tectonophysics 110:73–98

    Article  Google Scholar 

  • Varotsos P, Alexopoulos K (1984b) Physical properties of the variations of the electric field of the earth preceding earthquakes. II. Determination of epicenter and magnitude. Tectonophysics 110:99–125

    Article  Google Scholar 

  • Varotsos CA, Krapivin VF (2017) A new big data approach based on geoecological information-modeling system. Big Earth Data 1(1–2):47–63

    Article  Google Scholar 

  • Varotsos PA, Sarlis NV, Skordas ES (2002) Long-range correlations in the electric signals that precede rupture. Phys Rev E 66:011902

    Article  Google Scholar 

  • Varotsos PA, Sarlis NV, Skordas ES (2011) Natural time analysis: the new view of time. Precursory seismic electric signals, earthquakes and other complex time series. Springer, Berlin/Heidelberg

    Book  Google Scholar 

  • Varotsos PA, Sarlis NV, Skordas ES (2019) Phenomena preceding major earthquakes interconnected through a physical model. Ann Geophys 37:315–324

    Article  Google Scholar 

  • Vernadsky VI (1944) Several words about the noosphere. Successes Present Biol 18(2):49–93. [in Russian]

    Google Scholar 

  • Victor DG (2001) The collapse of the Kyoto Protokol and the struggle to slow global warming. Princeton Univ. Press, Princeton

    Google Scholar 

  • Victor DG (2004) Climate change. debating America’s policy options. The Council of Foreign Relations, New York

    Google Scholar 

  • Walker G (2003) Snowball earth: the story of the great global catastrophe that spawned life as we know it. Crown Publishers, New York

    Google Scholar 

  • Waring R, Running S (2007) Forest ecosystems. Analysis at multiple scales. Academic Press, Orlando

    Google Scholar 

  • Wayne GP (2013) The beginner’s guide to representative concentration pathways. Sceptical Science, p 24

    Google Scholar 

  • Wright EL, Erickson JD (2003) Incorporating catastrophes into integrated assessment: science, impacts, and adaptation. Clim Chang 57:265–286

    Article  Google Scholar 

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Varotsos, C.A., Krapivin, V.F. (2020). Global Climate Monitoring with Microwave Measurements. In: Microwave Remote Sensing Tools in Environmental Science . Springer, Cham. https://doi.org/10.1007/978-3-030-45767-9_9

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