1. Roger A. Stocker 1 Jason E. Nachamkin 2 An overview of operational FNMOC mesoscale cloud forecast support 1 FNMOC: Fleet Numerical Meteorology & Oceanography Center 2 Naval Research Lab (Monterey, CA)

2.  Mission  Current FNMOC COAMPS regional forecasts  Satellite cloud verification (GOES vs. CloudSat)  COAMPS E_PAC cloud verification (GOES)  Conclusions

3.  We provide high quality, relevant, and timely meteorological and oceanographic support to the Fleet.  Numerical Weather Prediction is the core of our business.  Global and Regional Operational Models  Assimilate meteorological and oceanographic data worldwide  Scheduled and on-demand products – 0 to 240 hour forecasts  Specific to Fleet and Joint operations  24x7 Operational Reachback Center  Provide Support to Naval, Joint, Coalition, and National missions  Direct Support for Global Submarine Weather  Data fusion for planning and operations

5. Current Operational Run ATMOSPHERIC MODELS REAL TIME  180 PRELIM 2  009 PRELIM  132 POST TIME  015 OFF TIME  144 00010203040506070809101112 12131415161718192021222300 |||||||||||||||||||||||||||||||||||||||||||||||||| PRELIM  132 NAVDAS NCODA AMS 4 AMS 3 AMS5 E PAC  48 (Nest 2) W ATL  72 (Nest 2) EUROPE  72 (Nest 2) 18km N. INDIAN OCN  48 (Nest 2) W PAC  48 (Nest 2) CENT AM  48 (Nest 2) SW ASIA  78 (Nest 2 & 3) COAMPS NOGAPS NOGAPS Ensemble NAAPS  144 FAROP  144 1/25/08, OPSRUN SW ASIA  12 E PAC  12 W ATL  12 EUROPE  12 CENT AM  12 N INDIAN  12 W PAC  12 OFF TIME RUNS Core Time

6. case study comparison – dots=GOES Cloud top ht. Slide Courtesy of Dr. Steve Miller, Dr. Cristian Mitrescu, and Dr. Rob Wade

7. Slide Courtesy of Dr. Steve Miller, Dr. Cristian Mitrescu, and Dr. Rob Wade GOES Underestimates Cirrus Heights Goes Cloud Top Heights are Currently Used in our Model Validation Study Recent Comparisons with CloudSat Reveal a Potential Bias in the Goes Cloud Top Estimates These results suggest validating against more fundamental satellite measurements (such as radiance) LWC/IWC Validation Issues: Observational Bias

8. Liquid Water Path 2300 UTC0000 UTC Retrievals are based on reflectance. Homogeneous, plane-parallel clouds assumed. Convective (lumpy) cloud LWP underestimated. Measured magnitude fluctuates with solar angle. Best results are at high solar angles (1800-2100 UTC).

9.  30 levels  6-hour data assimilation cycle using NAVDAS 3-D Var  Microphysics based on Rutledge and Hobbs  Kain-Fritsch cumulus parameterization Operational COAMPS ®* Forecasts Observations GOES satellite retrievals –Cloud top temperature –Cloud top height (based on NOGAPS) temperature profile –Liquid (includes ice) water path (daylight hours only) –Cloud type Subset area of forecast grid 4 km footprint interpolated to forecast grid Bias calibration performed Scores derived for Feb-May 2007 *COAMPS ® is a registered trademark of the Naval Research Laboratory. 27 km Nest Observation Domain

10. Satellite-Derived Cloud Top Height (km) 2100 UTC 1 Feb 2007 NRL NexSat Image Satellite Domain Sub-set of FNMOC Operational COAMPS ® EPAC Domain Satellite Data Interpolated to EPAC Operational Domain Averaging Box Methodology for COAMPS ® LWC/IWC Validation Validation Technique: 2-D NRL-derived Satellite Fields Archived for Analysis Satellite fields Interpolated to COAMPS ® Operational Grid RMS statistics Computed (LWP & Cloud Top Height)

11.  COAMPS ® predicts extensive upper atmospheric ice clouds.  Otherwise cloud masses are well placed. Extensive cirrus GOES visible

12. Liquid Water Path COAMPS GOES General features well positioned Positive model bias Spatial error correlation not measured How to quantify this? LWP (g m -2 ) 12-h FCST Point-to-Point Comparison COAMPS GOES

13.  +3 hr lag Fcst almost as good as 0 hr due to phase errors  Model beats persistence after ~ 6-9 hours

14.  More thin cirrus  Less stratus  More deep, thick clouds Fractional cvg LWP (g m -2 )

15.  Model able to differentiate between clear and disturbed periods. 21 hr FCST Corr=0.87

16.  Positive COAMPS cirrus bias  Negative GOES height bias  Overall positive model bias

17.  Values generally stable with lead time.  Reflect performance at synoptic scales. Correlation Forecast hour GOES – COAMPS ® Correlations

18.  Verification of model cloud fields restricted operationally to GOES verification as “truth” which themselves have a negative height bias for clouds and possible LWP errors up to a factor of 2 (CloudSat comparison).  COAMPS predicts synoptic scale events well with good correlations for observations of LWP > 500g/m2  COAMPS has a positive overall cloud bias over the domain which is especially pronounced at upper levels (Cirrus forecasts).  Statistical point-to-point comparisons lead to overall correlations with observations of < 50% even at the analysis time. However, skill can be found over persistence beyond tau=9.