GEO 130 Earth’s Physical Environments

1. GEO 130 Earth’s Physical Environments

2. Introduction to Physical Geography • Define physical geography • Explain how we study physical geography • List several types of models • Describe and define models • List the factors that complicate the study of pattern and process and provide examples • Give examples of how scale influence the perception of pattern and process • Explain how contingent historic events complicate the interpretation of pattern and process • Explain the difference between non-linear and linear change • Explain why models are limited in describing patterns in the environment • Define and give examples of positive and negative feedback • Define/explain: steady state, dynamic equilibrium, phase shifts, and transient states

3. What is Physical Geography? • Integrated study of three subdisciplines • Climatology • Biogeography • Geomorphology

4. What is Physical Geography? • Includes the role of humans and their influence on natural processes

5. Why study physical geography? • The natural world is as complex as the human world • Consider these facets of the Earth’s surface • Its extent (size) and resolution (detail) • History and time since origin (4.5 billion years)

6. Why study physical geography? • To understand human-environment interaction, you need to understand how the non-human world works.

7. How do we do physical geography? • We document pattern and process

11. We use models to study pattern and process • Models are a simplified, often idealized representation of reality. • Intent of a model is to recreate patterns by capturing the underlying explanatory processes • Your role is to learn models, recognize they are idealized, and try to identify why they are incomplete.

12. What are the types of models? • Graphical conceptual models

13. Types of models • Maps

14. Types of models • Data visualizations and simulations • Mathematical in essence, but enhanced through computational power of the computer.

15. Types of models • Dynamical models • Use field-derived conditions to model the behavior of a phenomena • Can be used to predict or forecast the future

16. http://moe.met.fsu.edu/tcgengifs/

17. Types of models • Dynamical models can also be used to hindcast the past and study events that have already happened

18. Types of models • Statistical models • Use the record of the past to predict the future

19. What complicates the study of pattern-process?

20. 1. Multiple driving variables • Driving variables are most directly responsible for the observed patterns. • They have to be identified, but are not always readily apparent or easily separated from each other

21. Proximate and ultimate causation • A proximate cause is an event which is closest, or immediately responsible, for causing some observed result. • This exists in contrast to a higher-level ultimate cause which is usually thought of as the "real" reason something occurred.

22. Why did the ship hit the rock? • Proximate cause: Because the ship failed to change course to avoid it. • Ultimate cause: Because the ship was under autopilot and the autopilot received bad data from the GPS. • Separating proximate from ultimate causations frequently leads to better understandings of multiple driving variables

23. 2. Contingent events • What contingencies complicate the prediction of wildfires?

24. 3. Feedbacks • Feedbacks make prediction of the outcome of interactions difficult • Positive feedback: externally generated change is reinforced • Negative feedback: externally generated change is minimized

25. Example of positive and negative feedbacks associated with global warming

27. 4. Spatial and temporal scale • Scale determines how we understand pattern and process • Example: controls on temperature: what makes it warm or cold?

28. Answer depends upon temporal and spatial scale • Cloud cover and humidity (minutes to hours) • Diurnal (day-night) cycles • Seasonal cycles (1 year) • Cyclical fluctuations due to sunspots (10-50 years) • Anthropogenic contribution of greenhouse gases (10-100 years) • Milankovitch orbital cycles (10,000 yrs)

30. 5. Thresholds and time lags • Melting of ice sheets and glaciers

32. 6. Teleconnections

34. 7. The earth is constantly changing • Earth is an open system • Change is the norm • Change itself, however, has different types • Steady state equilibrium • Dynamic equilibrium • Phase shift once tipping point (threshold) is reached • Transitional states

35. Steady state equilibrium

36. Dynamic equilibrium

38. Phase shifts • Systems may shift to another state once a threshold is reached • Can be natural or caused by humans

40. No analog states

41. Transitory states • Systems do not settle down to any dynamical equilibrium.