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Jonathan Haxell

STUDY NOTES:AR246 Dr. Haxell Examination Date: Wed 16/3:30PM/University Stadium CLIMATE: -pattern of climate variables -characteristics over a period of time Characteristics of Climate: •Varies across space & time •Occurs on different scales – spatial & temporal scales -large scale process •Highly dynamic system -large # of internal & external variables -variables are mutually influential •Dependant on historical events -impact of a variable depends on pre-existing conditions •Can only be understood by Proxy data Implications for reconstructing climate: •Must specify temporal/spatial scale of analysis ○determined by research hypothesis (mega/meso/microscales) ○Scale of analysis will determine data required -ie. Not all data sets are of equal valuable at all scales: -Eg. Megascale – Imp. Variables largely non-biological -not all data sets are available at all scales •Past climate difficult to reconstruct: ○extremely complex systems – highly interconnected ○Nature of effect on climate is obscured due to impact of all variables Climate Reconstructed through two related approaches: 1) Theoretical climate modeling 2)Through proxy data Climate Models: •GCM – general circulation models GOAL – use understanding of modern climate systems -To generate a computer model that can be applied to past Application of uniformitarian assumption – identify natural principles active in the present Not the same thing as analogy – use of a specific modern climate to model the past Methods: •Select # of well-understood climate variables – expressed mathematically •Used to generate a computer simulation – used to calculate the combined effects of all selected variables •Simulation tests with modern climate •Ultimately applied to ancient climate – data for past climate input – model calculates outcome -Eg. CLIMAP (1970's-80's) -Incorporated data: -average temperature -areas of oceans ice free/covered for each -area of glaciation -area's of different vegetation zones\ -calculate combined effects (all variables working together) -model is compared to known outcome -modern dates are then replaced by ancient values (same variables) -GCM provide mega/macroscale perspective -able to model global to continental scale of processes -external variables (independent) – Eg.Amount of solar radiation that reaches the surface of the earth -internal variables (mutually influential) – eg. Interaction of the 5 spheres External Variables: •Astronomical Variables: ○Variation in solar output - Eg. Sunspots: Magnetic disturbance in photosphere results in solar radiation reaching Earth -Eg. Maunder Minimum (1645-1715) ---Little IceAge ○Obliquity – Change in angle of rotational axis vs. Orbital plane -Alters intensity of sunlight – Northern/Southern Hemisphers (governs seasons) ○Orbital Eccentricity – change in shape of earths orbit around the sun •Climate effects of astronomical variables: ○influence distribution/intensity of insolation -Eg. Measure of solar radiation, which in turn influences patterns of air movement and therefor global distribution of heat/moisture ○Creates cycles of mega-scale climate: -Eg. Cyclical in nature & generates distinct climate conditions -Eg. Milankovitch cycles (purposed by Milutin Milankovic -Serbian Mathematician) -calculated combined effect: Obliquity, pression, eccentricity -Demonstrated interactions responsible for cyclical ice ages -Ice age results – low summer temperatures that are not warm enough to melt all winter snow -Estimated northern-hemisphere insolation through Pleistocene -Resulted pattern matched knwon record -Precession (24,000yrs), Obliquity (41,000yrs), Eccentricity (413,000yrs) •ReconstructingAstronomical Variables for the past: ○knowledge of astronomical motion, highly predictable -can reconstruct state of system for other points in time -Eg. Establishes locations of sun/earth -Allows calculation of insolation on monthly basis -Impact varies by latitude/altitude/local conditions •Tectonic Variables: Climate effects of tectonic processes: -Longterm modifications of latitude of continental land masses -Adjustment of ocean/atmospheric currents – affects patterns – global distribution of heat -Volcanic ash – increases atmospheric albedo -Orogenesis (mountain blding) – affects global wind patters •Reconstructing past tectonic states: ○position/size – past continents established by geomagnetic data -ie. Earth's magnetic field aligns ferrous particles in molten rock ○Matched fossil/lithic structure across modern continents -common sequences of strata identify anicent continental breaks ○past Orogenesis understood – geomorphological approaches Internal Variables: •lithosphere: Effects on climate -Direct impact – Eg.Albedo of exposed regolith – influence local/global temperature -Elevation – impact on ambient air temperature -Affects climate influencing distribution of other variables: -landscape features affect wind patterns -altitude/latitude – impact on cryosphere -Relief/regolith – Location/morphology/courses of hydrosphere -soil types effect distribution of plant populations •Reconstructing past lithospheric variables: -geomorphological/sedimentological analysis: -Eg. Geomorphology – past relief: reconstruction via. Hydrography of extinct water bodies -Eg. Sedimentology – Identification of: -Source, transport agents, depositional environment, transformations •Atmosphere: -Effect on climate -Determined by patterns of air movement -redistributed heat/moisture -imp. Determi
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