1 / 48

Climate Models

Climate Models. Primary Source: IPCC WG-I Chapter 8 - Climate Models and Their Evaluation. Part 1: Model Structure. The Climate System. How do we simulate this?. Starting Point: Fundamental Laws of Physics. 1. Conservation of Mass. But - these are complex differential equations!

prudence-bender
Download Presentation

Climate Models

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Climate Models Primary Source: IPCC WG-I Chapter 8 - Climate Models and Their Evaluation

  2. Part 1: Model Structure

  3. The Climate System How do we simulate this?

  4. Starting Point: Fundamental Laws of Physics 1. Conservation of Mass But - these are complex differential equations! How can we use them? 2. First Law of Thermodynamics By solving them on a grid. 3. Newton’s Second Law Plus conservation of water vapor, chemical species, …

  5. Global Climate Models: Structure (Bradley, 1999)

  6. Resolution Increases over Time Computing demand increases inversely with cube of horizontal resolution. Increased computing power has allowed increased resolution

  7. Development of Global Climate Models (GCMs) … and increasing complexity. Which should be favored?

  8. Global Climate Models: Land-Atmosphere Link Differing scales: distributed surface properties

  9. Global Climate Models: Development of Ocean Models (Bradley, 1999)

  10. Global Climate Models: Parameterization Important processes smaller than a grid box: e.g., thunderstorms (atmospheric convection) few km (www.physicalgeography.net) What’s a model to do? Parameterization: Represent the effects of the unresolved processes on the grid. Assume that unresolved processes are at least partly driven by the resolved climate. (www.physicalgeography.net)

  11. Higher Resolution Can Help Part of a Global Climate Model 2.5˚ (lat) x 3.75˚ (lon) Regional (limited-area) Climate Model ~ 0.5˚ (lat) x ~ 0.5˚ (lon)

  12. Higher Resolution Can Help Part of a Global Climate Model 2.5˚ (lat) x 3.75˚ (lon) Regional (limited-area) Climate Model ~ 0.5˚ (lat) x ~ 0.5˚ (lon)

  13. EndPart 1: Model Structure

  14. Part 2: Model Evaluation

  15. How Are Models Evaluated? • Testing against observations (present and past) • Comparison with other models • Metrics of reliability • Comparison with numerical weather prediction

  16. What Limits Evaluation? • Unforced (internal) variability • Availability of Observations • Accuracy of Observations • Accuracy of Boundary Conditions (Forcing) These help determine what is “good simulation”.

  17. GCM Simulations of Global T 58 simulations, 14 GCMs ~ 5-95% confidence limits (obs) Ensemble Average

  18. Time Average Surface Temperature (1980-1999) ˚C Mean Model: Average of 23 GCMs

  19. Errors in Simulated Surface Temperature (1980-1999) Lines: Observed mean Colors (top): Ensemble mean - obs. Spatial pattern correlation: ~ 98% (individual models) Colors (bottom): RMS differences in simulated-observed time series (i.e., typical error)

  20. Annual Variability (Seasons) Lines: Observed Standard Deviation (of monthly means) Colors: Ensemble mean - observations

  21. Diurnal Temperature Range (1980-1999) ˚C Mean Model: Average of 23 GCMs Tendency to be smaller than observed Problems with clouds? Boundary layer?

  22. Atmospheric Zonal Average (1980-1999) K Mean Model: Average of 20 GCMs Vertical Axes: Left - Pressure (millibars) Right - Elevation (kilometers) Tendency for cool polar tropopause. Persistent feature of GCMs, though now smaller

  23. Mean Reflected Solar Radiation (1985-1989) Average of 23 GCMs (dashed) Colors: Individual Models Satellite Observations (solid)

  24. Mean Emitted Infrared Radiation (1985-1989) Satellite Observations (solid) Average of 23 GCMs (dashed) Colors: Individual Models

  25. Zonal Average Precipitation (1980-1999) Observations (solid) Average of 23 GCMs (dashed) Colors: Individual Models

  26. Annual Mean Precipitation(1980-1999) Observations Average of 23 GCMs

  27. Atmospheric Specific Humidity (1980-1999) g/kg Mean Model: Average of 20 GCMs Vertical Axes: Left - Pressure (millibars) Right - Elevation (km) (bias) Moist bias in tropical troposphere - 40% + 40%

  28. Ocean (Potential) Temperature (1957-1990) Mean Model: Average of 18 GCMs

  29. Ocean Salinity (1957-1990) PSU Vertical Axes: Depth (m) Mean Model: Average of 18 GCMs PSU = “practical salinity units” • based on conductivity of electricity in water • PSU = 35  water is 3.5% salt

  30. Ocean Heat Transport (Feb 85 - Apr 89) Models: 1980-1999

  31. September March Sea Ice Simulation 14 GCMs (1980-1999) “Number of Models” = models with ice cover > 15% in the 2.5˚ x 2.5˚ region. Red lines: Observed 15% concentration boundaries

  32. El Niño - Southern Oscillation (ENSO) Recent GCMs (~ 2000-2005) “Power” = amount of variability occurring for a cycle length (period) Previous generation GCMs (~ 1995-2000)

  33. Are Models Improving? - 1 “Normalized” = RMS error / observed space-time variability

  34. Are Models Improving? - 2 (Reichler and Kim, 2007) “Performance Index” combines error estimates of Sea level pressure Temperature Winds Humidity Precipitation Snow/Ice Ocean salinity Heat flux

  35. End Part 2: Model Evaluation

  36. Part 3: Model Feedbacks

  37. Positive Feedback: Example How does Earth’s temperature get established and maintained?

  38. Greenhouse Effect - 1 IR radiation absorbed & re-emitted, partially toward surface Solar radiation penetrates

  39. Greenhouse Effect - 2 IR radiation absorbed & re-emitted, partially toward surface Net IR: ~25-100 W-m Emitted IR: ~200-500 W-m

  40. Greenhouse Effect - 3 Cooler atmosphere: - Less water vapor - Less IR radiation absorbed & re-emitted Solar radiation penetrates

  41. Greenhouse Effect - 4 Cooler atmosphere: - thus less surface warming - cooler surface temperature Solar radiation penetrates

  42. Positive Feedback Perturb climate system Positive feedback moves climate away from starting point A destabilizing factor Other examples: - ice-albedo feedback - CO2-ocean temperature feedback

  43. Negative Feedback Perturb climate system Negative feedback moves climate back toward starting point A stabilizing factor Example: Decrease Earth’s temperature Cooler Earth emits less radiation (energy) Outgoing radiation < solar input Net positive energy input Earth warms up from net energy input

  44. Key Feedbacks - 1 • Water Vapor: • Warmer atmosphere can contain more water vapor • Increased water vapor increases greenhouse effect • Atmosphere warms further 2. Clouds: • Clouds cool the climate (reflect sunlight) and warm the climate (block outgoing infrared radiation) • Changes in cloud distribution can thus amplify or reduce the warming

  45. Key Feedbacks - 2 • Snow-ice albedo: • Warmer climate has reduced snow and ice • Surface reflects less and absorbs more solar radiation • Climate warms further 2. Lapse rate (decrease of T with height): • In warmer climate, especially tropics, temperature decreases less with height • Upper troposphere warms more than surface • Upper troposphere emits energy to space (infrared radiation) more effectively than surface, countering the greenhouse effect.

  46. Feedback Strengths

  47. End Part 3: Model Feedbacks

  48. END Climate Models

More Related