1. First results from the Aqua-Planet Experiment intercomparison Mike Blackburn, Brian Hoskins University of Reading David Williamson National Center for Atmospheric Research Peter Gleckler Program for Climate Model Diagnosis and Intercomparison Richard Neale NOAA-CIRES Climate Diagnostics Center APE Modelling Groups http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE

2. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE APE Modelling Groups GroupLocationModelResolnFeatures AGU for APE Japan (consortium)AFES v.1.15T39 L48Spectral, eulerian CGAM Reading, UKHadAM3N48 L303.75º x 2.5º grid CSIRO Aspendale, AustraliaCCAM-4-12C48 L18~220km conformal cubic grid DWD Mainz, GermanyGME 29.1.1ni=64 L31~1º icosahedral-hexagonal grid ECMWF Reading, UKIFS Cycle 29r2T L 159 L60Spectral, semi-lagrangian FRCGC Yokohama, JapanNICAM7km L54icosahedral grid, non-hydro. GSFC Maryland, USANSIPP-1N48 L343.75º x 3º grid K1-Japan Japan (collaboration)CCSR/NIES 5.7T42 L20s-l moisture and cloud LASG Beijing, ChinaSAMILR42 L9Spectral, eulerian MGO St. Petersburg, RussiaMGO-gcmT30 L14Spectral MIT Cambridge, USAMIT-gcmC32 L40~280km cubed sphere NCAR Boulder, USACCSM-CAM3T42 L26Spectral, eulerian UKMO Exeter, UKpre-HadGAM1N96 L381.875º x 1.25º grid, s-lagrangian

3. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE The Experiment Complete GCMs but idealised planet More constrained experiment than real-world benchmark (AMIP) Facilitate understanding of model differences and sensitivities No land / orography 8 idealised sea surface temperature (SST) distributions 5 symmetric SSTs span a range of tropical climates Local and global-scale SST anomalies 3-year climate (following spin-up) Following Neale & Hoskins (2000) Symmetric SST profiles Latitude SST (degC) SST anomaly experiments 3KW1 1KEQ 3KEQ

4. Zonal Average Hydrological Cycle Precipitation (mm/day) Evaporation (mm/day) different scale http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE

5. Hydrological Cycle: NCAR model Courtesy of David Williamson, NCAR Precipitation: contributions to resolution dependence, T42 / T85 params. timestepgrid Trunc n.diffusion params. at T42 Working Group on Numerical Experimentation - WGNE

6. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE Inter-tropical Convergence Zone When does convection break through the trade-wind inversion? Many interacting processes ITCZ location sensitive to all these processes in models Emanuel (1994) [ Evap – Precip ] Surface Wind ECMWF - APE control (time average) (mm/day) Cool 30º lat. SST Eq. Warm SST

7. Tropical Variability (precipitation) average 5º N -5º S http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE (mm/day)

8. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE Observations + Theory Observed variability (OLR) Hierarchy of convective organisation Time Time-longitude section of transient OLR averaged between the equator and 5N from May to July in 1980. (Nakazawa, 1988) Zonal Wavenumber Frequency (CPD) UKMO_n96 sym. spectrum (precip) Observed sym. spectrum (OLR) Images from Yoshi-Yuki Hayashi; Yukiko Yamada; NOAA CDC

9. Wider SST maximum in tropics Stronger SST gradient : displaced poleward Response of zonal climate to SST qobs-control Working Group on Numerical Experimentation - WGNEhttp://www.met.reading.ac.uk/~mike/APE/ cntl qobs latitude SST (degC)

14. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE Storm-track statistics Tracking of storm features using 6 hourly sea-level pressure NCAR model for all 8 SSTs Courtesy of Kevin Hodges, ESSC, Reading Mean Intensity latitude Pressure anomaly (hPa) Track Density latitude Number per month in 5º radius peak cntl qobs flat cntl5n 1keq 3keq 3kw1 Zonal speed Zonal speed (ms -1 ) latitude

15. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE Storm-track statistics Tracking of storm features using 6 hourly sea-level pressure 6 models for flat SST Courtesy of Kevin Hodges, ESSC, Reading Track Density latitude Number per month in 5º radius Mean Intensity latitude Pressure anomaly (hPa)

16. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE Low Frequency Variability Significant zonal wavenumber m=5 in 3-year means Slow propagation, c = 1.7ms -1 Significant correlation with annular mode variability Courtesy of Masahiro Watanabe, Hokkaido University. GRL 32, L05701. (2005) 1-point correlation maps: 10-day low-pass surf. pressure EOFs of 10-day low-pass streamfunction =0.3 Ref 51.6N

17. Global Energy Balance APE control experiment: 3 year averages + temporal variability Net flux (toa; surface) sw_dn TOA sw_up sw TOA lw http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE

18. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE Summary APE is useful to test model changes Complex, difficult to understand - despite constrained setup Documenting a wide variety of model behaviours (not converged?) Attempts to understand sensitivities in individual models Additional experiments needed to understand model differences (eg fixed radiation to remove feedbacks) Diagnostic focus: Mean state: model/SST differences; tropical theory; maintenance Tropical wave activity Diurnal cycle Mid-latitude variability & storm-tracks Issues: Reference solution is unknown Expect resolution convergence with parameterizations?

19. http://www.met.reading.ac.uk/~mike/APE/Working Group on Numerical Experimentation - WGNE Blank text