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Recent Results with RRTMG and CAM3.5 Michael J. Iacono

Recent Results with RRTMG and CAM3.5 Michael J. Iacono Atmospheric and Environmental Research, Inc., Lexington, MA William D. Collins Lawrence Berkeley National Laboratory Andrew Conley, Phil Rasch NCAR NCAR Atmospheric Model Working Group Meeting 13 February 2008. Overview

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Recent Results with RRTMG and CAM3.5 Michael J. Iacono

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  1. Recent Results with RRTMG and CAM3.5 Michael J. Iacono Atmospheric and Environmental Research, Inc., Lexington, MA William D. Collins Lawrence Berkeley National Laboratory Andrew Conley, Phil Rasch NCAR NCAR Atmospheric Model Working Group Meeting 13 February 2008

  2. Overview • Radiation Implementation • CAM3.5.18 • Latest RRTMG_LW and RRTMG_SW • Work to be completed • RTMIP Forcing Calculations with AER models • Collins et al., JGR, (2006) - AR4 GCM and LBL models • RRTMG_LW and SW, LBLRTM (LW), CHARTS (SW) CAM3.5_RRTMG simulations • Using CAM cloud optics, but differences in SW • McICA with maximum-random cloud overlap • Aerosols turned off • No retuning yet applied

  3. Radiation Implementation • Codes • RRTMG_LW_v4.4 and RRTMG_SW_v3.4 • Using McICA, statistical technique for sub-grid cloud variability • RRTMG well suited for McICA: 140 LW and 112 SW sub-columns • Fully reformatted for F90 coding • Added ‘IRADAE’ option to calculate optical depths less frequently • Memory requirement: LW and SW about 20 Mb each • Model development and evaluation funded by DOE ARM Program • More info and codes: www.rtweb.aer.com • Work Remaining • Rebuild CAM aerosol database for RRTMG SW bands (NCAR) • Cloud optics and cloud overlap for CAM4 (NCAR) • Convert absorption coefficient data to netCDF (Pincus, Iacono) • Further timing improvement (NCAR, Iacono)

  4. Radiation Implementation Present Timing: On ‘blueice’, over one month, T42L26, in seconds CAM with RRTMG for now 50% slower, but down from 80% slower Potential for enhancing performance further: e.g. McICA, F90 software engineering, vertical layering

  5. RTMIP Calculations Clear Sky Radiative Forcing Cases: Based on MLS profile Iacono et al. (2008) being submitted soon to JGR

  6. RTMIP Calculations with AER models (Longwave) Clear Sky Radiative Forcing (Wm-2) for LBLRTM, RRTM, RRTMG

  7. RTMIP Calculations with AER models (Shortwave) Clear Sky Radiative Forcing (Wm-2) for CHARTS, RRTM, RRTMG

  8. RTMIP Calculations with AER models Clear Sky Heating Rate Forcing (K/d) Case 2b-1a: Doubled CO2

  9. RTMIP Calculations with AER models Clear Sky Heating Rate Forcing (K/d) Case 3b-3a: GHG 1860  2000

  10. RTMIP Calculations with AER models Clear Sky Heating Rate Forcing (K/d) Case 4a-2b: H2O x 1.2

  11. Initial CAM3.5/RRTMG Simulations • 1) CAM3.5 (aer195) • 2) CAM3.5_RRTMG/McICA (aer202) • Both T42/L26, FV, climo SST, CAM cloud optics, no aerosols • Differences: • Spectral mapping of SW cloud optics • 4 bands used in CAM don’t directly translate to RRTMG bands 2) Cloud overlap? 3) Retuning not yet attempted for simulation with RRTMG • CAUTION: Too preliminary to establish climate impact; • Runs show some change to radiative balance, but impact in general is not large except on SW cloud fluxes; • Awaiting NCAR decisions on cloud optics and overlap for CAM4

  12. Temperature CAM3.5 - ECMWF CAM3.5_RRTMG - ECMWF

  13. Surface Temperature CAM3.5 - ECMWF Model Differences

  14. Specific Humidity CAM3.5 - ECMWF Model Differences

  15. Total Cloud CAM3.5 - ISCCP Model Differences

  16. Global Annual Mean Fluxes (Wm-2) aer195: CAM3.5 aer202: CAM3.5_RRTMG

  17. Next Steps Additional timing improvements • Software engineering • Efficiency of SW 2-stream and sub-column generator • More vertical layers (benefits RRTMG relative to CAM) Diagnose reason(s) for SW cloudy flux differences • Likely due to spectral mapping of cloud optics and/or cloud overlap differences (McICA) • Single column calculations in progress Retuning CAM3 with new radiation • Necessary due to impact on radiative balance • Required anyway for other planned changes: • Mitchell ice cloud optics • New liquid water cloud optics

  18. Extra Slides Evaluating CAM water vapor with AIRS radiance spectra • AIRS L3 retrieved water compared to CAM water vapor • Observed AIRS spectra compared to brightness temperature spectra modeled with OSS in CAM_RRTMG/McICA • Work funded by NASA

  19. Evaluating CAM Water Vapor with AIRS: 500 mb: January 2004 and July 2004 [specific humidity (g/kg)] AIRS CAM3_ RRTMG CAM3

  20. Water Vapor Differences (percent): 500 mb: January 2004 and July 2004 CAM3_ RRTMG - AIRS CAM3 - AIRS Positive: Models too moist relative to AIRS

  21. Water Vapor and Mean Spectral BT Differences: 500 mb: July 2004 CAM3_ RRTMG - AIRS CAM3 - AIRS Spectral BT differences negative: Models too moist

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