1. NAME Climate Process and Modeling Team/ Issues for Warm Season Prediction J. Schemm and D. Gutzler CPC/NCEP/NWS/NOAA University of New Mexico The 30th Climate Diagnostics and Prediction workshop The Pennsylvania State University October 24-28, 2005 Acknowledgements: Myong-In Lee, Soo-Hyun Yoo and Lindsey Williams

2. NAME Climate Process and Modeling Team - supported by NOAA/OGP CPPA program Team members : David Gutzler, University of New Mexico Wayne Higgins, CPC/NCEP/NWS/NOAA Brian Mapes, University of Miami Kingtse Mo, CPC/NCEP/NWS/NOAA Shrinivas Moorthi, EMC/NCEP/NWS/NOAA Jae-Kyung Schemm, CPC/NCEP/NWS/NOAA Siegfried Schubert, GMAO/GSFC/NASA Glenn White, EMC/NCEP/NWS/NOAA

3. Project Objectives: 1.Implementation of the second phase of NAME Model Assessment Project (NAMAP2) focused on the 2004 season. 2.Coordinated efforts with the current NAME Diurnal Cycle Experiment Project in GCM diagnostics. 3.Implementation of their findings to the NCEP GFS/CFS operational forecast system - NOAA Climate Test Bed. 4.Serve as a primary mechanism for collaboration and technology transfer between research communities and operational centers.

4. NAMAP Analysis: Metrics for model development Improved simulation of monsoon onset, especially in global models Goals for improvement of precipitation (total amount and diurnal variability) and surface flux simulations, tied to improvements in ground truth to be achieved from NAME 2004 field observations Questions regarding the structure of low-level jet circulations and their importance for proper precipitation simulation

5. NAMAP2 -A coordinated exercise in global and regional atmospheric modeling of NAMS. -Summer 2004 is the simulation target. -Simulation protocols have been developed and announced among potential participants. -Focus on uncertainties identified in NAMAP, with additional emphasis on verification using enhanced observations from the NAME 2004 field campaign. -Results based on the first NAMAP published in BAMS, Oct. 2005.

6. NAMAP2 -Will re-examine the metrics proposed by the first NAMAP. -For proper specification of SSTs in the Gulf of California, a new SST analysis has been developed by W. Wang and P. Xie of CPC.

7. NAMAP2 Protocols

8. a) For spatial analysis: Archive lat-lon fields covering the NAMAP2 domain every 3 hours (8/day) during simulation period. Fields to archive: Output Archiving Protocols

9. b) For high-resolution temporal analysis: Archive "MOLTS"-style time series (at least hourly in time and full vertical resolution). We will consider surface fluxes and profiles of humidity, T, u, v, w, p, resolved and convective precipitation, cloud fraction, radiation, and turbulence at model grid points corresponding to the following NAME sounding sites: Output Archiving Protocols

10. A Multi-Platform-Merged (MPM) SST Analysis over the NAME Domain Wanqiu Wang and Pingping Xie Climate Prediction Center NCEP/NWS/NOAA

11.  To create a fine-resolution SST analysis with desirable resolutions and accuracy for NAME Projects  Resolution: 0.25 o in space, 3-hour in time  Domain: 180 o – 30 o W, 30 o S – 60 o N  Target Period: 2001 – present

12.  Input data: All available in-situ and advanced satellite observations  Quality control: Cross verification to ensure data quality  Bias correction: Removal of large-scale/low-frequency bias in satellite observations  OI analysis: Combining SST data from all observations through the Optimal Interpolation (OI)

13. Input Data  In-situ observations Buoys and ships  Satellite Observations GOES: 3-hourly / clear sky TMI: twice daily / all sky AMSR:twice daily / all sky NOAA16: twice daily / clear sky NOAA17: twice daily / clear sky MODIS: Not included yet.

14. Input SST for AMJ 2004 Similar Spatial distribution Pattern; Differences in small-scale features and in magnitude

15. Current Status  Developed prototype algorithm to define the analysis  Produced analysis for 2004  Conducted preliminary comparison with existing analyses (OI and RTG)

16. Some quick analysis statistics OIRTGMPM 0.70 K0.60 K0.48 K OI:Weekly Optimum Interpolation RTG:Real-Time Global analysis (2DVAR) MPM:Multi-Platform-Merged Analysis Magnitude of accuracy : RMS difference in daily mean between analyses and moored buoy (May 15 to Sep 30, 2004) Magnitude of mean bias : RMS difference in seasonal mean between analyses and all in situ (Jun 1 to Aug 31, 2004) OIRTGMPM 0.44 K0.32 K0.19 K

17. Mean difference (K) between analyses and in situ observations (Jun 1 to Aug 31, 2004)  MPM shows smaller bias Note: In situ observations were used in all analyses. However, MPM is probably less dependent on the in situ because the use of much larger amount of satellite observations.

18. Issues involved in warm season predictability over NAME area Model sensitivity on 1. Horizontal resolution 2. Continental boundary conditions 3. Oceanic boundary condition Physical processes 1. Vertical sounding analysis - test for model convection schemes. 2. Surface flux and PBL formulations

19. Coordinated activities with the NAME Diurnal Cycle Experiment Project (S. Schubert, PI) 1.Collaborative effort among NASA, GFDL and NCEP. 2.GCM diagnostics focused on diurnal cycle over NAME domain. 3.Findings of this project to be tested on NCEP GFS and CFS GCMs.

21. Obs GFDL NCEP NASA NARR Figure 1

27. GFS Resolution and Precipitation in the Core Monsoon Region Precipitation (mm day -1 ) Seasonal Cycle (1981-2000) T62 obs T126 month

28. P (JAS) & T2m from observations, AMIP126 and SIMU126 In comparison with observations: The AMIP is too hot (2 C higher) and too dry (2 mm/day less ) over the Great Plains ; The SIMU ensemble means are closer to the observations

29. Area Mean of Climatological Precipitation

30. Anomaly Correlation Scores of 2m Temperature over US Region; RNL2

31. Summary NAMAP2 protocols have been developed and posted at UCAR/JOSS website. A special SST analysis provided by Wang and Xie of CPC Coordinated with the NAME Diurnal Cycle Project, impact of GCM horizontal resolution on warm season precipitation over NA has been examined. Initial soil moisture is important in reducing systematic error and seasonal progression of precipitation and surface temperature. Role of ocean boundary condition will be examined with the new improved SST analysis.