The Philosophy of Climate Modeling Jeffrey T. Kiehl Climate Change Research Section NCAR Jeffrey T. Kiehl Climate Change Research Section NCAR

Outline  Philosophy & Climate Modeling  Climate Science  Finding a Research Problem  Why Model the Climate System?  The Way of Climate Modeling  Summary  Philosophy & Climate Modeling  Climate Science  Finding a Research Problem  Why Model the Climate System?  The Way of Climate Modeling  Summary

Philosophy & Climate Modeling  Epistemology - What can we know?  Models as representations  Metaphysics - What is?  How real are the representations?  Ethics - What is Good/Evil?  What do we choose to present?  Aesthetics - What is Beauty?  How do we present our results?  Politics - Ethics of Groups  What are the social implications of our results?  Epistemology - What can we know?  Models as representations  Metaphysics - What is?  How real are the representations?  Ethics - What is Good/Evil?  What do we choose to present?  Aesthetics - What is Beauty?  How do we present our results?  Politics - Ethics of Groups  What are the social implications of our results?

Climate Science ForcingFeedbacksResponse Variability We all fit in here somewhere!

Finding a Research Problem  Something that Really Grabs You (Follow Your Bliss)  Tractable (be aware of timescales involved, complexity of system)  Affordable (can you pay for it?)  Valuable (to whom?)  Something that Really Grabs You (Follow Your Bliss)  Tractable (be aware of timescales involved, complexity of system)  Affordable (can you pay for it?)  Valuable (to whom?)

Why Model the Climate System?  Develop a fundamental understanding of Earth’s climate system (What Ifs)  To look at mechanisms in the system  To look at interactions within the system  To replicate reality (past, present, future)  To provide information for policy decisions  Can you think of others?  Develop a fundamental understanding of Earth’s climate system (What Ifs)  To look at mechanisms in the system  To look at interactions within the system  To replicate reality (past, present, future)  To provide information for policy decisions  Can you think of others?

Climate What Ifs  What if the solar output decreased?  What if there were no mountains?  What if Earth rotated twice as fast?  What if aerosol loading doubled?  What if cloud drop size decreased?  What if tropical forests disappeared?  What if the solar output decreased?  What if there were no mountains?  What if Earth rotated twice as fast?  What if aerosol loading doubled?  What if cloud drop size decreased?  What if tropical forests disappeared?

The Way of Climate Modeling  Forming a Question  Setting up a simulation  Simulation Strategy  What do you look for?  What can you explain, or not?  Looking at the process level  Forming a new question  Forming a Question  Setting up a simulation  Simulation Strategy  What do you look for?  What can you explain, or not?  Looking at the process level  Forming a new question

Forming a Question  Decides the Model Configuration  Individual or Group Needed?  Decides the Model Configuration  Individual or Group Needed? Don’t get involved in partial problems, but always take flight to where there is a free view over the whole single great problem, even is the view is still not a clear one. Ludwig Wittgenstein

Setting up a Simulation  Boundary Conditions  Initial Conditions  Model Spin up  Defining the control simulation  To tune or not to tune  Boundary Conditions  Initial Conditions  Model Spin up  Defining the control simulation  To tune or not to tune

Energy Balance Surface Temperature Sea Ice Area Spin-up ~100 yr CCSM3 T31X3 Control

To Tune or Not? ocean atmosphere The great Way is easy, yet people prefer the side paths. Be aware when things are out of balance. Tao Te Ching 53 ocean atmosphere

Net Energy Flux into Earth System

Net Energy Flux into Ocean

Simulation Strategy  Length of simulation  Transient  Steady State  Time scales of problem  When do you stop the simulation?  Length of simulation  Transient  Steady State  Time scales of problem  When do you stop the simulation?

What do you look for?  Are there optimal metrics?  Model versus data  Model versus control  Don’t be narrowly focused on a few metrics  Global  Regional  Mean state  Variability  How to display your metrics?  Are there optimal metrics?  Model versus data  Model versus control  Don’t be narrowly focused on a few metrics  Global  Regional  Mean state  Variability  How to display your metrics?

What can(‘t) you explain?  Where to look?  Budgets and Causality (the chicken and the egg)  What tools are available?  Process studies  Sensitivity studies  Temporal evolution  Where to look?  Budgets and Causality (the chicken and the egg)  What tools are available?  Process studies  Sensitivity studies  Temporal evolution

Kiehl and Shields (2005) Inefficient mixing in Permian ocean indicative of anoxia

10XCO 2 1XCO 2

Process Studies  Temporal Evolution and Correlation  Regional Analysis  Sensitivity of Parameterizations  Single Column Model  Data Assimilation  CAPT: A CAM Forecast Model  Temporal Evolution and Correlation  Regional Analysis  Sensitivity of Parameterizations  Single Column Model  Data Assimilation  CAPT: A CAM Forecast Model

CCPP ARM Parameterization Testbed (CAPT) Hannay, Williamson, Kiehl

Summary  Big challenges in model biases:  Tropical mean state  Tropical variability (e.g. ENSO)  Cold polar tropopause  Continental precipitation  High latitude continental temperatures  Big challenges in model biases:  Tropical mean state  Tropical variability (e.g. ENSO)  Cold polar tropopause  Continental precipitation  High latitude continental temperatures

Summary  Big Challenges Model Processes  Fully interactive biogeochemical, atmospheric chemical system model  Regional Simulation of the 20th century climate  Aerosol indirect effect  Big Challenges Model Processes  Fully interactive biogeochemical, atmospheric chemical system model  Regional Simulation of the 20th century climate  Aerosol indirect effect

In the beginner’s mind there are many possibilities,but in the expert’s mind there are few. Shunryu Suzuki