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Removing the Mystery of Predicting Climate Change Duane Waliser JPL 101 Lecture Series July 19, 2006 Your connections to climate change predictions Today’s Lecture Boo - Includes Physics/Math •Bad News •Good News - Only ONE Test Question!! _____________________________________________________________________________ Boo 1. What does he mean by “climate change”? • Observations 2. Build a Simple Climate Model • Greenhouse Gases • Climate Feedback; “What If”? • Model Predictions 3. State of the Art Climate Models • Computation Challenges • Do They Work? 4. Reducing the Uncertainties • Faster Computers • More/Better Satellite Data What Kind of Climate Change Are We talking about? Natural Variations Geological Changes - Ice Ages - No El Nino <-> La Nina - No Volcanic Induced - No… Solar Variations - No… The Kind in “Day After Tomorrow” - Definitely Not Anthropogenic = Man-Made CFCs & Ozone Destruction - No Enhanced Greenhouse Gases (e.g., CO2) - Yes Why All The Concern? Rarely If Ever So Warm Rarely if Ever So Fast “Hockey Stick” What MIGHT be causing this warming? Industrial Age Extended Using Far and Proxy Away Data One of e.g.Most The Ice Cores Important Climate Data Sets So, How is the Warming & CO2 Connected? What about the Future? Past Experience Suggests Starting with a Simple Model Yes, this is where the physics and Math come in Simple Climate Model Observations Stefan-Boltzmann Law: 1884 Physics + Math Solar “constant” 4 TET 4 ~335 W/m2 Emitted Radiation Total Solar Radiation Radiation 101=- Total TakeTerrestrial Away Message Temperature ↑ (aka Infrared, Thermal) Emitted Radiation ↑↑↑↑ Earth Emits Radiation to Cool Sun Heats the Earth Simple Climate Model TE4 Earth Surface Solve For TE => 277 K = 4 C ~ 40 F Real Global Average Temperature = 288 K = 15 C ~ 59 F Not Bad - But We Missed Two Really Important Things Clouds, Ice, Snow, Desert and Dust Reflects Sunlight Back to Space Improve Our Simple Climate Model Ice/Snow Clouds Deserts TE4 A = “Albedo” ~ 0.30 Earth Surface Now Solve For TE => 254 K = -19 C ~ -2 F Freezing Cold!!! Pretty Bad - But We Still Have Something Very Important to Include Greenhouse Earth Gases such as H2O, CO2, CH4 Are Known As Greenhouse Gases Greenhouse Analogy More Improvements to our Climate Model 90% Solar 20% Terrestrial Atmosphere Passes Passes Thru; Rest Cools As TA4 Thru Heats the Atmosphere Ice/Snow Clouds Deserts Greenhouse Gases, H2O, CO2 Atmosphere, TA Surface, TE Back the Math & Physics Now, Weto Balance Energy (i.e. & ) at the Top of the Atmosphere and at the Surface - 2 Equations & 2 Unknowns. Lets Spare the Details….. Now Solve For T => 286 K = 13 C ~ 55 F Pretty Good! . The GH’effect Changes This To This . So Why The “Global Warming”? Ice/Snow Clouds Deserts Greenhouse Gases, H2O, CO2 Atmosphere, TA Surface, TE Recall, CO2 Has Been Increasing So Why The “Global Warming”? Ice/Snow Clouds Deserts Greenhouse Greenhouse Gases, Gases, H H22O, O, CO CO22 Atmosphere, TA TE Surface, TE More GHGs, More Trapping, Higher Temperatures This Part is Well Established So Why Are We Uncertain? Climate Feedbacks!! Ice/Snow-Albedo Feedback Water Vapor Feedback Cloud Feedback Climate Feedbacks Positive or Negative Ice/Snow Clouds Deserts Greenhouse Gases, H2O, CO2 Atmosphere, TA Surface, TE Te : Ice/Snow Melt : Reflection : Te + Te : Water Vapor : GHG : Te + Water Vapor : ?Clouds : Reflection : Te Depends on the type of cloud, its height, ice/water, etc.! The balance of these feedbacks, and MANY others, have to be properly represented In Climate Models Ice/Snow-Albedo Feedback Water Vapor Feedback Cloud Feedback How do We Do this in State-ofthe-Art Climate Modeling? _____________________________________________________________________________ •Divide the Atmosphere Into Boxes (How many - as many as possible) •Do the type of calculations for each Box like we did in our simple model. •Use Conservation of Mass, Energy, and Test Question Momentum and the Gas Law. Did our model useIdeal Conservation of 1) Mass 2) Energy 3) Momentum Climate Model Computer “Grid” Similar for Ocean, Land & Ice Systems Scope of numerical problem in Excel terms Temperature <- Longitude -> Other files for q, U, V, W, P, etc. <- Latitude -> <- Height -> 360 Longitude * 180 Latitude * 30 in Height * 20+ Variables (e.g., Temp, Water Vapor, Wind, Clouds, Radiation, etc) = ~40 Million; Then make a calculation of these to step forward in time for 20 minutes until you get to 100 years. That’s Why We Need Super-Computers JPL Dell Xeon Cluster cosmos.jpl.nasa.gov What Can These Climate Models Do? Natural & Man-Made Induced Changes Volcanoes Solar Greenhouse Ozone Model Hindsight Pretty Good Predicting the Future Science, Politics & Society Plausible “Scenarios” For CO2 Emissions Climate Model Projections Intergovernmental Panel on Climate Change (IPCC, 2001) While there is considerable disagreement, ALL models predict WARMING for ALL plausible scenarios. Where does the warming occur? IPCC, 4th (newest) Assessment Report Projected Temperature Change In 2100 2099-2070 Minus 1999-1970 How About Our Backyard? IPCC, 4th (newest) Assessment Report Systematic Warming 1.5 - 3.0 C 2.7 - 5.4 F Relatively Agreeable +/- 20% Much Less Certain Why do the Model Predictions Differ? Estimating “Unresolved” and Complex Processes Difficulty with Clouds, Climate and Computer Grids Consider drawing a picture of this cloud We would like to Have a sharp pencil For most clouds we have a BIG CRAYON Clouds - and other features - have very fine scales How do you Realistically Represent this with ONE number? 1) Get More Numbers 2) Make Sure it is a Good Number 10km Grid Our Excel ~ 100 km 1000 X More Work Longest Simulations A Few Months 1) Get More Numbers “Nesting” Or “Downscaling” Get More Numbers Where You Most Need Them 2) Make Sure it is a Good Number That’s where satellite data are crucial ICE ICE ICE SNOW MIXED LIQUID LIQUID RAIN Cloud Feedback cccc bbc ccmm cccr r cccc aat t 4 ccmm 477 aat t 663 ccnn 3 rm rm ccss i ggff iroro ddl l 2 ggff 200 d dl l ggi i 2211 ssss ee ggi i hh ssss eer r inin iaiapp mm ccmm 0.09 0.08 0.20 0.07 0.15 0.06 0.05 0.10 0.04 0.03 0.05 0.02 0.01 0.00 0.00 Model m ipipss m irir l l m oocchh m iriroo r r ccmm rr mm ppi i mm rr uukk nn i i m ccaar r uukk m oo m m ccmm oogg 33 eemm 11 Cloud Path (kg/m^2) (kg/m^2) Cloud Ice Ice Path Cloud Ice Strong Influence on Climate IPCC Models: GlobalAverage Average Ice Water PathIce IPCC Models: Global Total Cloud 0.10 0.25 Factor of ~20 Difference Factor of ~7 Difference Cloud Ice: Models vs Observations Li et al. 2005 Observations? AURA/MLS provides the first vertical profiles of Cloud Ice in the upper troposphere -> Extremely Valuable Information to Improve Climate Models. Climate Models And The MJO Day 0 Day 10 Influence Weather Hurricanes,Monsoons & El Nino Day 20 Day 30 Models Do Poorly Simulating & Predicting the MJO Day 40 NCEP/NCAR ~ Observations Tian et al. 2006 AIRS Tropical Thunderstorms / Convective Clouds • Produce The Cloud Ice • Big Temperature Variations • Very Important for Water & Energy Cycles • Hardest to Get Right in Climate Models • Need more information on composition & Structure ICE ICE ICE SNOW MIXED LIQUID LIQUID RAIN CloudSat : Fabulous! In Summary • Warming is Evident in the Observations • The Result of Incorporating our Scientific Knowledge (Theory+Data), and in some cases our Intuition, into Climate “Models”, Unequivocally Indicates the Warming is Anthropogenic in Nature and Likely to Continue • How Much? 1. Depends on Interplay of Society, Economics and Politics (Highly Uncertain). 2. Model Predictions Are Our Most Objective Guide (Better Means to Establish & Reduce Uncertainty). Reducing Remaining Uncertainties •Better/More Measurements •Faster/Better Computers & Infrastructure •Continued Focus