1. Potential of Simulator Assessments led by GRP H IRO M ASUNAGA Hydrospheric Atmospheric Research Center, Nagoya University ?

2. Satellite data simulator Sep 1, 2011GRP 22nd meeting, Tokyo  Satellite data simulators  Simulate satellite data, of course.  T, q v, q r, … → satellite measured radiance  Radiative transfer code + user interfaces  Sub-grid cloud generator (COSP)  Antenna pattern convolution, PSD library (SDSU)  Growing need for multiple sensor package  TRMM/GPM: PR/DPR + TMI/GMI (+ VIRS)  A-Train: CPR + CALIOP + MODIS + AMSR-E + AMSU + AIRS …  Applications  Climate/Cloud-resolving model evaluation  Retrieval algorithm development for future missions  Radiance based data assimilation  …

3. Multi-sensor simulator packages Sep 1, 2011GRP 22nd meeting, Tokyo  COSP: CFMIP Observation Simulator Package  CFMIP (http://cfmip.metoffice.com/COSP.html)  CRTM: Community Radiative Transfer Model  NOAA (http://www.star.nesdis.noaa.gov/smcd/spb/CRTM/)  ECSIM: EarthCARE Simulator  ESA (Voors et al, 2007)  J-simulator: Joint Simulator for Satellite Sensors  JAXA/U Tokyo (http://www22.atwiki.jp/j-simulator/pages/14.html)  RTTOV: Radiative Transfer Model for TOVS  UK MetOffice/ECMWF (Matricardi et al. 2004; Bauer et al., 2006)  SDSU: Satellite Data Simulator Unit  Nagoya U (http://precip.hyarc.nagoya-u.ac.jp/sdsu/)  Goddard SDSU  NASA GSFC (http://atmospheres.gsfc.nasa.gov/cloud_modeling/sdsu.html)  ISSARS: Instrument Simulator Suite for Atmos Remote Sensing  JPL (under development)

4. Who would need it? Sep 1, 2011GRP 22nd meeting, Tokyo  Algorithm developers?  Most likely have their own RT codes already.  GCM/CRM developers  Would be happy if user-friendly simulators are available.  Best (or least?) motivated to diagnose and refine model performance.  GCM/CRM users  Would be also happy with simulators.  Best available to spend time on model assessment. Satellite simulators have potential user demands primarily from the modeling communities.

5. Why do we need it? Sep 1, 2011GRP 22nd meeting, Tokyo N(D), ρ p,… Masunaga et al., BAMS (2010)

6. Sep 1, 2011GRP 22nd meeting, Tokyo Goddard SDSU applied to a WRF simulation - AMSR-E 36.5 GHz V (top) - MODIS 11 m (middle) - CloudSat dBZ (bottom) Masunaga et al., BAMS (2010)

7. Cloud and Precip Top Heights (CTH and PTH) Sep 1, 2011GRP 22nd meeting, Tokyo MJO wet MJO dry ??  CloudSat CPR  NICAM+SDSU CPR 10-dBZ height CPR echo-top height PTH CTH  TRMM PR&VIRS  NICAM+SDSU PR echo-top height Infrared T b PTH CTH Too much snow In the cloud model

8. Missing 94-GHz Echoes above 8 km Sep 1, 2011GRP 22nd meeting, Tokyo The 94-GHz back-scattering coefficient begins to be saturated due to non-Rayleigh scattering as snow content increases. 94-GHz

9. Sep 1, 2011GRP 22nd meeting, Tokyo Rayleigh regime Wavelength >> 2 π r Geometric optics regime Wavelength << 2 πr 2r

10. A Modification to snow microphysics Sep 1, 2011GRP 22nd meeting, Tokyo Snowflake mass spectrum = m(D)n(D)=aD b N 0 exp(- D) where a=2.5x10 -2 kg m -2 and b=2 (original=Grabowski, 1998) a=5x10 -4 kg m -1 and b=1 (modified) SWC=1g/m 3 0.1 g/m 3 Smaller snowflakes Less saturated

11. PSD Impact on the CTH/PTH Histogram Sep 1, 2011GRP 22nd meeting, Tokyo TRMM NICAM MJO wet MJO dry Original MJO wet MJO dry Modified

12. Model Grid resolution, PBL schemes,… Model Grid resolution, PBL schemes,… Model assessment with simulators Sep 1, 2011GRP 22nd meeting, Tokyo GCM cumulus/cloud parameterizations, … CRM cloud microphysics, … Satellite data simulator Particle Scattering Size distribution, Crystal habit, … Measuring principles Vis, IR, or Microwave Passive or active

13. Tasks Sep 1, 2011GRP 22nd meeting, Tokyo  Close communication is crucial among scientists with different background (modeling vs. remote sensing) to foster new ideas to develop assessment metrics.  Simulator-related sessions in int’l conferences  ex.) AGU fall meetings in a past few years.  GRP led efforts for simulator-based assessment  …