1. How will the earth’s temperature change?

2. Let’s start with what we know.
We know that …
The global climate has changed in the past.
There are natural and (more recently) anthropogenic reasons for change.
Humans are changing the environment with increasing GHG concentrations and land use change.
The global mean temperature has increased about 1°F (0.6°C) over the last century.
We have good climate data for the past 150 years.

3. Let’s start with what we know.
We know that …
We have good proxy climate data for the last hundreds of thousands of years.
We can simulate the atmosphere well enough for weather forecasts.
We understand the basic processes and principle equations in the climate system.
We have the computing power to simulate the climate future.

4. Climate Models 101
3/22/10
> What is a GCM? global climate model general circulation model > History of GCM’s and how they work > Types of GCM’s

5. Why are Climate Models Important?
Simulations Running scenarios that you cannot test in the real world - Doubling of current CO2 levels
Sensitivity testing … the what if questions What would happen if all the sea ice in the Arctic melted? What if there were more aerosols in the atmosphere? What if the ocean-atmosphere heat exchange in the North Atlantic slowed?
Guidance Ability to provide some outlook on what the future will hold

6. How do you model something so complex?
The earth climate system
atmosphere processes
land processes
Interactions
Feedbacks
ocean processes
snow/ice
processes

7. How do you model something so complex?
Start out simple.
Start from what we know.

8. Weather Forecast Models give rise to Climate Prediction Models

9. Pre-History of Global Climate Models: Bjerknes
Vilhelm Bjerknes ( ) proposed the procedure known as numerical weather prediction.
He developed a set of equations to predict large scale motion.
He used graphical methods on weather maps to solve these equations.
These methods were used into the 1950’s, but
it was not very successful due to: a) lack of observations and b) calculation time

10. Early Weather Maps (1900)

11. Pre-History of Global Climate Models: Richardson
Lewis Richardson developed first Numerical Weather Prediction system.
Divided space into grid and simplified the equations.
An 8-hr weather forecast took 6 weeks! Plus the forecast was a bust.
Envisioned Forecast Factory, 64,000 ‘computers’ (people with mechanical calculators) with a central leader coordinating by using a beam of light.
Only in the 1940’s did this become reality with the advent of digital computers.

12. Mid-Century Weather Maps

13. Early modelling efforts - weather forecasting
Use of mathematical models to predict the atmosphere
Simulates physics and dynamics of atmosphere
Non-linear equations solved for increments of time
Based on meteorological observations (initialization)
Various scales of models (regional, global)
Early days of NWP
Present day technology

14. Early modelling efforts - climate prediction
Use of mathematical models to predict the atmosphere
Simulates physics and dynamics of atmosphere
Non-linear equations solved for increments of time
Assume a radiative equilibrium of earth
(1-a)S0r2 = 4r2 T4
incoming solar = outgoing thermal

15. (1-a)S0r2 = 4r2 T4 + atmosphere
Simple climate models
One-dimensional models - radiative-convective model
incoming solar = outgoing thermal
(1-a)S0r2 = 4r2 T atmosphere

16. (1-a)S0r2 = 4r2 T4 + atmosphere + advection
Simple climate models
Three-dimensional models - radiative-convective model with horizontal transport
incoming solar = outgoing thermal
(1-a)S0r2 = 4r2 T atmosphere + advection

17. Complex climate models: equations
Solving physics equations:
East-West Wind
North-South Wind
Temperature
Moisture
Pressure

18. Complex climate models: 3 components
atmosphere
ocean
land

19. Complex climate models: coupling
atmosphere
ocean
land

20. Complex climate models: parameterizations
atmosphere
clouds
land type
ice
ocean
land

21. Complex climate models: solving the equations
T is a function of time
time
temperature
How do we solve this in time?
Temperature

22. Complex climate models: solving the equations
What are the coordinates?
Computation time goes up as resolution increases.
[Washington & Parkinson, 1986]

23. Complex climate models: solving the equations
Use pressure coordinates, not altitude. Help deal with terrain.

24. Complex climate models: solving the equations

25. Who runs these models?
By the 1960’s, separate groups evolved to build primitive equation GCMs independently.
GFDL Geophysical Fluid Dynamics Laboratory
UCLA Univ of California, Los Angeles
Livermore Lawrence Livermore National Laboratory
NCAR National Center for Atmospheric Research
UKMO United Kingdom Meteorological Office

26. Who runs these models now?
• European Center (Reading, UK) (1970’s built from scratch)
• Max Planck Institute (Hamburg, Germany)
• NASA Goddard Laboratory for Atmospheric Sciences
• Colorado State University
• Oregon State University
• National Meteorological Centre (Australia)

27. Who runs these models? [

28. Computational Demands for GCMs
GCMs demand enormous computational power.
The first GCMs => 24 hours of computer time for 1 day
By mid-1970s, ~ 12 hours per simulated year
For a typical run of 20 simulated years, a GCM still required as much as 10days of expensive supercomputer time.
Trade-off between resolution and time
Because of these computational needs, weather and climate modeling groups were among the earliest major users of supercomputers.

29. Simulating the Climate System: Climate Models
Use of mathematical models to predict the atmosphere
Simulates physics and dynamics of atmosphere
Non-linear equations solved for increments of time
model calculations
input (data)
output (prediction)

30. Simulating the Climate System: Climate Models
model calculations
input (data)
output (prediction)
station
many stations
gridded dataset
Factors: grid and model resolution missing / bad data

31. Simulating the Climate System: Climate Models
model calculations
input (data)
output (prediction)
East-West Wind
land
ocean
atmosphere
Moisture
Temperature
Pressure
North-South Wind

32. Simulating the Climate System: Climate Models
model calculations
input (data)
output (prediction)
different models have different resolutions assumptions physics schemes biases drawbacks strengths
Parameterizations for: clouds topography ocean-atmos. interaction sea ice

33. Simulating the Climate System: Climate Models
model calculations
input (data)
output (prediction)
Models are run for various time and space scales: Space Time
global short-term
regional long-term

34. Climate Predictions - short term
1-month temperature and precipitation outlook

35. Climate Predictions - short term
3-month temperature and precipitation outlook

36. Climate Predictions - regional

37. Climate Predictions - global

38. Climate Models Grew from weather forecast models
Solve physical equations on a 3-dimensional space - the more grids, the more time it takes
Are run by several different agencies
Have their strengths and weaknesses
Are good to find out answers to the “What if … ?” question