lecture 1 : the computational and data sciences

48
Lecture 1 : The Computational and Data Sciences Connecting Theory and Experiments

Upload: elsie

Post on 23-Jan-2016

22 views

Category:

Documents


0 download

DESCRIPTION

Lecture 1 : The Computational and Data Sciences. Connecting Theory and Experiments. Science: Old style. Theory. Experiment. Science: New style. Theory. Experiment. Computational Science. Computational Science a blend of disciplines. Data Science connecting experiments back to theory. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Lecture 1 : The Computational and Data Sciences

Lecture 1 : The Computational and Data Sciences

Connecting Theory and Experiments

Page 2: Lecture 1 : The Computational and Data Sciences

Science: Old style

Theory Experiment

Page 3: Lecture 1 : The Computational and Data Sciences

Science: New style

Theory Experiment

ComputationalScience

Page 4: Lecture 1 : The Computational and Data Sciences

Computational Sciencea blend of disciplines

Page 5: Lecture 1 : The Computational and Data Sciences

Data Scienceconnecting experiments back to theory

Theory Experiment

ComputationalScience

Page 6: Lecture 1 : The Computational and Data Sciences

Data Scienceconnecting experiments back to theory

Theory Experiment

ComputationalScience

DataScience

Page 7: Lecture 1 : The Computational and Data Sciences

Data Scienceconnecting experiments back to theory

Theory Experiment

ComputationalScience

DataScience

Page 8: Lecture 1 : The Computational and Data Sciences

Data Sciencea blend of disciplines

Page 9: Lecture 1 : The Computational and Data Sciences

Simulation movie

Page 10: Lecture 1 : The Computational and Data Sciences

What is Science?In-class problem 1

• On a piece of paper, write down if you believe in global warming and why.

• Write down something that would change your mind.

Page 11: Lecture 1 : The Computational and Data Sciences

What is Science?

a) A set of facts that tells us how nature works

b) The product of research and analysis by professional scientists

c) The underlying Truth about the Universe

d) The collection of data an formation of a hypothesis

e) None of the above

Page 12: Lecture 1 : The Computational and Data Sciences

What is Science?a) A set of facts?

• We are constantly making new discoveries and collecting new data

• Technology and experiments are changing

• Old Theories are replaced by new Theories

• Scientific ``Facts''

Page 13: Lecture 1 : The Computational and Data Sciences

What is Science?b) The product of research and analysis by

professional scientists?

• What is a scientist?

• Do you need a PhD?

• Amateur Scientists play an important role in discovery

• Being scientific DOES NOT required a Union Card

Page 14: Lecture 1 : The Computational and Data Sciences

What is Science?c) The underlying Truth about the Universe?

Truth or no truth. There is no universe

Page 15: Lecture 1 : The Computational and Data Sciences

What is Science?c) The collection of data an formation of a hypothesis

• Getting closer

Page 16: Lecture 1 : The Computational and Data Sciences

What is Science?

a) the state of knowing : knowledge as distinguished from ignorance or misunderstanding

b) a: a department of systematized knowledge as an object of study <the science of theology> b: something (as a sport or technique) that may be studied or learned like systematized knowledge <have it down to a science>

c) 3 a: knowledge or a system of knowledge covering general truths or the operation of general laws especially as obtained and tested through scientific method b: such knowledge or such a system of knowledge concerned with the physical world and its phenomena : natural science

d) 4: a system or method reconciling practical ends with scientific laws <cooking is both a science and an art>

http://www.merriam-webster.com/dictionary/science

Page 17: Lecture 1 : The Computational and Data Sciences

What is Science?the basics

• Science - A study that uses the Scientific Method

• Natural Science – “A rational approach to the study of the universe‘” - Wikipedia

Page 18: Lecture 1 : The Computational and Data Sciences

The Scientific Methoda definition

• Scientific method is a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. It is based on gathering observable, empirical and measurable evidence subject to specific principles of reasoning. A scientific method consists of the collection of data through observation and experimentation, and the formulation and testing of hypotheses.

http://en.wikipedia.org/wiki/Scientific_method

Page 19: Lecture 1 : The Computational and Data Sciences

The Scientific Methodthe process

• characterization of existing data

• formulation of a hypothesis

• deduction - formulation of a predictive test

• experimental testing

• error elimination and characterization

• validate or revise hypothesis

Page 20: Lecture 1 : The Computational and Data Sciences

The Scientific MethodIn-class problem 2

• Based on the collective memory of the students in this class, we will try to reconstruct the process of the scientific method involving the issue of whether Earth orbits the Sun. Take a few minutes to write down everything you remember about this. Then think about how the elements you remember relates to the elements of the scientific process that were mentioned on the slides.

• After 5-minutes, we will discuss your answers as a group.

Page 21: Lecture 1 : The Computational and Data Sciences

Experimental Error

• What time is it?

• Not everyone's clock is perfectly synchronized

• Error is an intrinsic part of measurement

• Statistics are need to characterize error

Page 22: Lecture 1 : The Computational and Data Sciences

The Scientific Methodclimate change – a case study

• characterization of existing data

• formulation of a hypothesis

• deduction - formulation of a predictive test

• experimental testing

• error elimination and characterization

• validate or revise hypothesis

Page 23: Lecture 1 : The Computational and Data Sciences

Existing Data

Photo credit: Professor L. Thompsonhttp://scrippsnews.ucsd.edu/Releases/?releaseID=703

Qouri Kalis Glacier, Peru 1978-2002

Page 24: Lecture 1 : The Computational and Data Sciences

Existing Data

1903 taken by G.K. Gilbert

2003 taken by Hassan Basagic.http://web.pdx.edu/~basagic/snglac.html

Lyell Glacier, Yosemite National Park 1903-2003

Page 25: Lecture 1 : The Computational and Data Sciences

Discuss the following

• Glacier data are strong evidence for global warming

• Glacier data are strong evidence for anthropogenic global warming

• Glacier data are strong evidence for Earth being at its warmest level

Page 26: Lecture 1 : The Computational and Data Sciences

Existing Data

Temperature of Lake Superior

http://www.d.umn.edu/~jaustin/ICE.html

Page 27: Lecture 1 : The Computational and Data Sciences

Existing Data

Atmospheric CO2

Page 28: Lecture 1 : The Computational and Data Sciences

Existing Dataquestions based on study

• Is the climate of Earth changing?

• If the climate is changing, what are the causes?

Page 29: Lecture 1 : The Computational and Data Sciences

Climate Changehypothesis and deduction

• Hypothesis: Global Temperatures are increasing– Deduction: Historical records of temperatures will show this

increase

• Hypothesis: Increases in CO2 are caused by human activity– Long term data from ice cores will show rapid changes in the

CO2 levels over the last few hundred years

• Hypothesis: increases in CO2 caused by human activities play the dominant role in the global average temperature– Deduction: Detailed physical models of the climate will show that

the increases in CO2 will cause increases in the average temperature on Earth

• Natural effects may reinforce the human factors

Page 30: Lecture 1 : The Computational and Data Sciences

Climate Changehow does the climate work?

• Complex equations-– radiant heat from the Sun– energy loss to space– advection of material through winds– evaporation and changing reflectivity from clouds and

ice– ocean and land differences in specific heat– weather

• Way to complicated to calculate by pencil and paper!

Page 31: Lecture 1 : The Computational and Data Sciences

Moving from Equations to Predictionscomputational science!

http://celebrating200years.noaa.gov/breakthroughs/climate_model/welcome.html

Page 32: Lecture 1 : The Computational and Data Sciences

ConclusionsIPCC Fourth Working Group

“Warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global average sea level...‘”

Page 33: Lecture 1 : The Computational and Data Sciences

Conclusions IPCC Fourth Working Group

``Global atmospheric concentrations of CO2, CH4 and N2O have increased markedly as a result of human activities since 1750 and now far exceed pre-industrial values determined from ice cores spanning many thousands of years....Global increases in CO2 concentrations are due primarily to fossil fuel use...''

Page 34: Lecture 1 : The Computational and Data Sciences

Conclusions IPCC Fourth Working Group

Page 35: Lecture 1 : The Computational and Data Sciences

Reducing and Characterizing Error

• A single model usually doesn't tell you enough about the uncertainty of a model

• We need to explore these assumptions of the model

• Multiple runs are needed

• Sometimes multiple models are needed

• Changes in the outcomes show the sensitivity of the model

Page 36: Lecture 1 : The Computational and Data Sciences

Reducing and Characterizing Error IPCC 2001, Climate Change, The Scientific Basis

Page 37: Lecture 1 : The Computational and Data Sciences

Conclusionsclimate forcing through CO2

• ``Most of the observed increase in globally-averaged temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic GHG concentrations....”

• “The observed widespread warming of the atmosphere and ocean, together with ice mass loss, support the conclusion that it is extremely unlikely that global climate change of the past 50 years can be explained without external forcing, and very likely that it is not due to known natural causes alone.''

Conclusion of IPCC Fourth Working Group

Page 38: Lecture 1 : The Computational and Data Sciences

Summary of Climate Data

• Hypothesis: Global Temperatures are increasing

• Hypothesis: Increases in CO2 are caused by human activity

• Hypothesis: increases in CO2 caused by human activities are the dominant source in the global average temperature increases

Page 39: Lecture 1 : The Computational and Data Sciences

Are we certain our results are correct?

• All three of our hypotheses are now supported by very strong evidence

• With enough evidence, a hypothesis becomes a theory

• However - NO scientific conclusion is ever more than a theory, no matter how strong the evidence is!

• Scientific theories can and should still be tested and refined.

Page 40: Lecture 1 : The Computational and Data Sciences

Revised Hypothesiscomputer predictions

• Existing data: Detailed computer models should that polar regions being more affected by climate change, especially in the arctic because of ocean warming

• Hypothesis: Polar regions will experience rapid changes in climate

• Deduction: We should be able to see changes in polar ice cover in satellite data

• Experiment: Examine historical satellite data of polar ice cap data

Page 41: Lecture 1 : The Computational and Data Sciences

The Data Sciencessatellite measurements of sea ice

• Collect huge amounts of satellite images of arctic sea ice using multi-spectral scanners

• Process the raw signals from the detectors into file records

• Archive the records in a database • Convert the records into images• Process the images to determine the area

covered by ice• Use statistics to determine any trends in the data

Gigabytes or Terabytes are changed into a single plot.Data is transformed into understanding.

Page 42: Lecture 1 : The Computational and Data Sciences

Artic Ice CapTERRA satellite

[http://terra.nasa.gov/]

Image from oceanmotion.org

Page 43: Lecture 1 : The Computational and Data Sciences

Artic Ice Capdata sciences

Satellite Data - 1979-2003 SSMI Composite Data

See http://www.everybodysweather.com/Static_Media/Polar_Ice_Cap_Melter/index.htm

Page 44: Lecture 1 : The Computational and Data Sciences

More Sea Ice Data

Page 45: Lecture 1 : The Computational and Data Sciences

More Sea Ice Data

http://nsidc.org/news/press/2007_seaiceminimum/20071001_pressrelease.html

Page 46: Lecture 1 : The Computational and Data Sciences

Conclusions

• ``Arctic sea ice during the 2007 melt season plummeted to the lowest levels since satellite measurements began in 1979. The average sea ice extent for the month of September was 4.28 million square kilometers (1.65 million square miles), the lowest September on record, shattering the previous record for the month, set in 2005, by 23 percent (see Figure 1). At the end of the melt season, September 2007 sea ice was 39 percent below the long-term average from 1979 to 2000. If ship and aircraft records from before the satellite era are taken into account, sea ice may have fallen by as much as 50 percent from the 1950s. The September rate of sea ice decline since 1979 is now approximately 10 percent per decade, or 72,000 square kilometers (28,000 square miles) per year.''

http://nsidc.org/news/press/2007_seaiceminimum/20071001_pressrelease.html

Page 47: Lecture 1 : The Computational and Data Sciences

Global Warmingscientific method

• Existing data– Detailed computer models should that polar regions being more affected

by climate change, especially in the arctic because of ocean warming• Hypothesis:

– Polar regions will experience rapid changes in climate• Deduction:

– We should be able to see changes in polar ice cover in satellite data• Experiment

– Examine historical satellite data of polar ice cap data• Conclusions:

– Satellite data supports our hypothesis– This is additional evidence that our models are correct– The original theory of global warming is to be supported by this data

Page 48: Lecture 1 : The Computational and Data Sciences

Climate Changeare we done now?

• NO! Science is a process - NOT a set of conclusions.

• The process goes on as

• new experiments and new data become available

• better theories and models develop

• Computing is ESSENTIAL in connecting Theory to Experimental Data