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Do Physicists Belong in the Real World?. Disclaimer: A highly Idiosyncratic Presentation for First Year Graduate Students in Physics. Brief Examples of Physicist Journeys into other domains. Finance, Renewable Energy, Climate Change, Balloon Boys:.
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Do Physicists Belong in the Real World? Disclaimer: A highly Idiosyncratic Presentation for First Year Graduate Students in Physics
Brief Examples of Physicist Journeys into other domains Finance, Renewable Energy, Climate Change, Balloon Boys: Or, What we are not gonna teach you in Graduate School
Questions to Ask • Are we giving you tools and techniques that can be broadly applied to real world problems? • Are we teaching you material that is relevant to the rapidly changing real world? • Are we giving you value added to find a meaningful career? • Do we, as faculty, even care about that?
Balloon Boy Physics A simple calculation would show that the volume of helium in that balloon was 10 times too low to have a 40 lb payload in it.
Non-Linear and Noisy Time Series • Applicable to financial markets • Applicable to all climate systems • Chaotic dynamics apply as well Log-periodic representation of data; June 23, 2008 to predict world oil market collapse starting July 11, 2008
Physicists Toy Boxes • With various tools, one can construct toy models of most any phenomena. The value of that is much larger than people realize because it generally leads to discovery of new dimensions of the problem.
Financial Markets and Relativity • Set risk to be The Geometry of Space (e.g. its dangerous to be near a black hole) • Set Risk-Reward to be the Geometry of SpaceTime The risk-return cone; Note that sigma is the radius of the risk-return cone at the particular security
The Role of the Improbable: A much different way to view the world • Traditional risk analysis, such as Monte Carlo Analysis is excellent at predicting probability in terms of uncertainty, except for one thing…. it completely misses Black Swans. So we continue to invest our money with money managers who predict statistical regular growth but then a Black Swan event occurs, sub-prime deflation or whatever, and wipes out a significant portion of the nation’s wealth. The impact of Black Swans was not included in the financial analysis. • Or airplanes crash into the World Trade Towers. And the world changes forever. • The behavior of world does not regress to the mean
Energy Issues: My Two Most Scientifically Important Publications in the last 5 years
Need Estimates of Potential Yield: Always probe the assumptions! This number is way wrong; 72 TW @80m land; at least 1000 TW oceans Requires 2000 watts per square meter incoming @16.5% efficiency (24 hrs a day)
Example Consulting Report on Solar PV Yield in the Real World Note That First Solar is Greatly Tellurium Limited
Real World Rates Matter • World wide, there are ~450 Solar PV Fab plants • 2008 Production = 7 GW(p); Cumulative installed =15 GW(p). Production not = net generation. Peak not = average. • Average power generated (over the course of a year is 5-10 times lower than the rated peak power) • This means that 15 GW(p) installed is closer to 1.5-3 GW delivered in a world where 2TW are used (.1%)
Real World continued • Assume Global PV production doubles every 3 years (forever) • Assume Global electricity demand increases 5% per year • When does PV reach just 10% of total consumed global electricity? • 28 years at which time GW(p) produced annually is 100 times the current value!
Climate Change and Chaotic Dynamics: Two Examples • What is Climate? • How do you detect real climate change? • Data samples are biased and incomplete A climate must be defined by measureable parameters in such a way that change in those measureable parameters can be detected. Not a single policy maker understands this.
Climate Indexing and Climate change detection. • Works just like the stock market Red Curve is our unbiased model Purple curve is a selected, biased curve. What baseline do you use to measure change?
Climate Change and Chaotic Dynamics: Hurricane Example • Naive expectation is that steadily rising sea surface temperatures (SST) should produce increasingly strong hurricanes • After 2005 Katrina, Rita and Wilma there was a rash of papers on how increasing hurricane strength was now a manifestation of global climate change • Needs reality check
Hurricane Energetics • Total amount of energy release as latent heat (condensation of water droplets) • The amount of kinetic energy needed to maintain the hurricane wind field (and overall movement)
Latent Heat • Hurricane produces 2 cm per day averaged over a radius of 600 km • Volume of rain = 10^16 cm^3/day = 10^16 grams per day • Latent heat of vaporization is 2475 KJ/Kg (at typical hurricane temperature) • Gives 2.5 x 10^16 Joules/per day or 3 x 10^14 Watts (300 TW !!!)
Kinetic Energy • KE generated = amount dissipated due to friction • Dissipation Rate per unit area = air density * drag coefficient * velocity^3 Ro is some characteristic outer radius which is largely unknown for pre-satellite hurricanes.
Energetics • Suitable averages over wind velocities (90 mph over a scale of 60 km) yields 1.5 TW of “kinetic” power • The total energy output of the world in all forms is 14 TW • 14 is bigger than 1.5 but not bigger than 300 • Which energy scale is most relevant for hurricane formation and evolution? If 300 then humans are doing squat.
Physical Root of the Problem • Cyclogenesis is the hardest aspect of this problem. Once a hurricane has spun up, the physics is slightly better understood. This is somewhat similar to the problem of tornadogenesis – why do some supercells produce tornadoes and others do not? Provide physically plausible arguments! • What makes this difficult? Why do some african waves evolve to hurricanes and others do not? • Does global climate change effect the probability of hurricane formation or only the strength of the formed hurricane or neither (yet) • The coupled atmosphere-ocean system is one of the hardest problems in all of physics to deal with, both experimentally and theoretically. • Cyclogenesis or tornadogensis are examples of critical phenomena. Physics students should be well trained in critical phenomena. For cyclogenesis the most likely source of critical phenomean is the interaction of moist convection with large scale circulations that produces a self sustained circulation.
Simple Picture not so Simple Determining the #2 to #4 interaction is where all the physics is
What does Data Tell us? • A Central Pressure • A hurricane wind radius (quite variable) • A duration • A location (time dependent) • An evolutionary timescale (spin up times) • Category X at landfall
Decadal Location Analysis – only 1 region shows upward systematic trend in counts per decade per cell
Counting is always noisy Yellow = raw data Red = corrected RADAR in the 1950s
But strongest storms may be increasing Note that 2009 was weakest Atlantic Basic Hurricane Season over the last 20 years; 2005 was the strongest
Strong Decadal Location Variability on spatial scale of 3x3 degrees
Spin up Times getting faster This is a Physical Signature associated with change in convection rates but data has to support this conjecture.
