1. The Water Cycle - Kickoff by Kevin Trenberth -Wide Ranging Discussion -Vapor -Precip/Clouds -Surface Hydrology (Land and Ocean) -Observations and scales - Results: Integrating Themes Convection as an example

2. Who Are we? GlobalRegionalLocalMicro Scale7/615/712/33/1 Type9/214/1212/5 ModelersAnalystsObservers

3. Integrating Themes Transport & Transformation Integration of Models & Observations Integrating Scales –Spatial –Temporal Weather & Climate Operations & Research, Observations Where can we make progress?

4. Critical Pathway: Convection Key Transformation & Transport process Transport of Vapor Precipitation (though not all precip) Effects on Land Surface, Feedbacks Observational and Conceptual Challenges

5. Predict this Predict / Understand This! Simple Case: SH, Clean Air, Open Ocean Try it with: Polluted air, variable land surface! Okay: now model a whole planet of these!

6. Observational Challenges Microscale and Local Organization Global distribution –3D structure, overlaps, clouds over ocean Forcings and feedbacks at all scales –Effects on energy budget –Moisture transport, recycling Aersosol and Cloud Interactions

7. Organization of Convection Radar observations of warm season continental precip (US) -Highly organized, -Diurnal variations (difficult to model)

8. Spatial Scales of Precipitation 10 May 2003: ~200km x 200km One CGM Grid Box (pick a number!)

9. --> small D e large D e <-- Ice size in tropical Cb tops Effects of Microphysics

10. Modeling Challenges Processes –Microphysics very important –Still gaps in understanding Parameterization –How to we best improve parameterizations Prediction –How well can we predict clouds, precip –QPF from convection & verification

11. Mean Observed vs GCM Precip (DJF) “Observed” CAM2.0.1

12. Day 169 Measured T b Day 178 Day 184 Estimated T b (after update) 180 200 220 240 260 180 200 220 240 260 200 220 240 260 280 Assimilation of Microwave Radiobrightness Observations into NOAH Land Surface Model for Regional Scale Soil Moisture and Land Surface Flux Estimates Integrating Models & Obs

13. Scales Integration of spatial scales –Work upscale and downscale Temporal scales too –Climate and weather are the extremes –Move between the two Framework for integrating models and observations

14. Observing Networks New Opportunities –Example: Radar maps of near surface precip –Challenge: 3D structure of clouds (obs & model) Research v. Operations? –One off sensors v. long term monitoring. –Where are improvements to forecasting Need to consider Climate in obs systems –Are we doing this?

15. Interesting Results: QPF & QPE important Semi-Arid regions important Droughts and lack of moisture significant Struggle with convective parameterization Moore’s Law is not the answer Observations limit understanding, models help, but don’t have all answers Need to integrate scales