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Using observations to reduce uncertainties in climate model predictions

Using observations to reduce uncertainties in climate model predictions. Maryland Climate Change Workshop Prof. Daniel Kirk-Davidoff. You guys can’t event predict the weather next week, what makes you think you can predict the climate 50 years from now?.

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Using observations to reduce uncertainties in climate model predictions

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  1. Using observations to reduce uncertainties in climate model predictions Maryland Climate Change Workshop Prof. Daniel Kirk-Davidoff

  2. You guys can’t event predict the weather next week, what makes you think you can predict the climate 50 years from now?

  3. Change in temperature and precipitation for a doubling of CO2, for a number of different models (From the IPCC third assesment report).

  4. Model differences in mean cloud heating of the earth.

  5. Not only does the treatment of clouds vary from model to model, • It’s very difficult to attribute a difference in “cloud forcing” to a particular difference in model code. • Experiments in hybridizing two models show that no one part of the model code is a dominant source of difference in model sensitivity. • As a general rule, there’s no good way to predict how a change in a model will influence the model’s climate sensitivity, except to run the whole model over again. (Keeps modelers honest!)

  6. Although the models have quite a bit of scatter (!), direct analysis of the data is somewhat reassuring.

  7. Temperature and CO2 for the last 500,000 years, derived from Antarctic ice core. (From Petit et al. 1999, Nature 399:429-436).

  8. “Paleocalibration” X Cretaceous ~ 2 K warming for a doubling of CO2 Temperature X Eocene Radiative Forcing X Last Glacial Maximum (After a plot by Covey et al., 1996, Climatic Change)

  9. Figure 12.1: Global mean surface air temperature anomalies from 1,000-year control simulations with three different climate models, HadCM2, GFDL R15 and ECHAM3/LSG (labelled HAM3L), compared to the recent instrumental record (Stouffer et al., 2000). No model control simulation shows a trend in surface air temperature as large as the observed trend. If internal variability is correct in these models, the recent warming is likely not due to variability produced within the climate system alone. - From the IPCC 3rd Assesment Report

  10. So, observations have a lot of potential to help us figure out climate sensitivity. • What observations do we need? • How can we put them to use? • Needed: • Very accurate measurements of the flux of radiation to from the earth to space over a broad frequency range. • Observations of temperature, water vapor, and cloud water and ice throughout the atmosphere What do we do with them? Use climate model experiments to devise tests that are very specific for climate sensitvity, and then apply these tests to actual data.

  11. A first step: Let’s figure out how to monitor climate to very high accuracy (0.1 K?)

  12. A first step: Let’s figure out how to monitor climate to very high accuracy (0.1 K?)

  13. Satellite Sampling Errors by Orbit

  14. Climate model testing using spectrally resolved radiances

  15. Downscaling climate model predictions Combine climate model predictions of large scale Climate patterns with statistical associations of Maryland weather with large patterns to predict Maryland weather in the future!

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