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Climate Test Bed Science Plan

Accelerate evaluation and improvements to the operational Climate Forecast System (CFS) to enhance its skill in providing climate predictions for addressing today's problems and planning for tomorrow.

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Climate Test Bed Science Plan

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  1. CTB Science Plan for the CFS S. Moorthi Jae Schemm Steve Lord Hua-Lu Pan

  2. Vision • To accelerate evaluation of and improvements to the operational Climate Forecast System to enhance its use as a skillful tool in providing NCEP’s climate predictions for users to address today’s problems and plan for tomorrow

  3. Background • The Climate Test Bed (CTB) was organized to enhance the capability of the NCEP Environmental Modeling Center (EMC) to improve the NCEP Climate Forecast System (CFS) and to enhance Climate Prediction Center’s (CPC’s) capability to provide better forecast products to users.

  4. CFS team goal • To accelerate evaluation of and improvements to the operational Climate Forecast System

  5. Current CFS capability • Operational CFS was implemented in 2004. It consisted of • Data assimilation of the atmosphere • Data assimilation of the ocean • Real time coupled 9-month forecasts • 25 years of hindcasts

  6. Next CFS • Currently working on the CFS Reanalysis Reforecast (CFSRR) project: • Coupled (atmosphere-ocean-land-ice) data assimilation in reanalysis mode, 1979-2009 • Coupled reforecasts initialized from the coupled reanalysis, 1981-2009 • Real time forecast to start in 2010

  7. Highlight of the next CFS • High resolution data assimilation to produce better initial conditions for hindcasts and forecasts : allowing for potential products for the monthly forecast • Coupled data assimilation to improve on the spin up character of the forecasts • Consistent analysis-reanalysis and forecast-reforecast for calibration and skill estimates

  8. Strategy • NCEP allocated 1/3 of the NCEP R&D computer to the CTB. Most of the computing resources were and will be used for model experiments • NCPO provides funding to external researchers to work with NCEP scientists to conduct experiments which may lead to model improvements

  9. Science Plan for the CFS (I) • We can not do all the components of the CFS • For Atmospheric data assimilation, we depend on JCSDA to provide improvements • For land data assimilation, we depend on the CPPA funded NCEP land team to provide improvements • For ocean model, we depend on GFDL (and in future HYCOM team) to provide improvements • The EMC Global Climate and Weather Modeling Branch is the team responsible for the GFS and the atmosphere component of the CFS. • We feel that the most effective way to improve the CFS is to improve the GFS/CFS as one package

  10. Science Plan for the CFS (II) • We want to improve weather and climate forecasts by making physically based improvements to the atmospheric model parameterization packages. • We have been successful when we apply rigorous tests to physically based parameterization improvements to both weather and climate models and want to continue along this way.

  11. Science plan for the CFS (III) • Deep and/or shallow convection These processes transport sub-grid scale heat and moisture vertically, which is especially important for climate prediction. • Boundary layer processes As the CFS is a coupled model, the boundary layer is critical for communication of the ocean and land conditions with the atmosphere. • Cloud/radiation/aerosol interaction and feedback Clouds and aerosols modulate the sources and sinks of the thermal energy in to the earth system. This interaction is crucial on climate time scales. • Orographic forcing Orography determines many climate variables through form-drag, mountain blocking, and land/sea contrast.

  12. Science Plan for the CFS (IV) • Gravity wave drag Gravity waves generated by the sub-grid scale orography and/or cumulus convection transport wave energy from the troposphere to the stratosphere and mesosphere and thus control the climate of those regions. • Stochastic forcing Stochastic forcing is not in the CFS at this time, but is important for parameterizing random, unresolved physical forcing. • Cryosphere The cryosphere (glaciers, frozen land, sea ice) plays a crucial role in determining the earth's climate. Modeling of sea-ice and its interaction with the ocean and atmosphere, and modeling frozen land and its interaction with the atmosphere are all important to climate.

  13. Science Plan for the CFS (V) • Testing procedures are key to the road to making model implementations • While transition to operation for MMEs requires only seasonal hindcasts to be evaluated, it is done because we expect the team maintaining the MME models to do their own rigorous tests. • Tests in data assimilation modes and evaluated with forecasts are crucial for weather forecasts. • Tests in multi-year coupled simulations and seasonal hindcasts are crucial for climate forecasts • CTB computer resource is not sufficient and NCEP computer must be used when full-scale testing is needed

  14. Gaps • Insufficient EMC staff to collaborate with external investigators, train their staff (often post-docs) on use of the CFS, and develop new parameterization codes suitable for the CFS for the broad spectrum of possible areas listed above (O2R); • Insufficient computing resources for experimentation and transition changes to the CFS; • Insufficient EMC and NCEP Central Operations (NCO) staff to support the R2O (implementation) process; • Insufficient knowledge within the research community about the tests needed to complete an implementation

  15. We built a new shallow convection scheme a few years ago • Use a bulk mass-flux parameterization • Based on the simplified Arakawa-Shubert (SAS) deep convection scheme, which is being operationally used in the NCEP GFS model • Separation of deep and shallow convection is determined by cloud depth (currently 150 mb) • Main difference between deep and shallow convection is specification of entrainment and detrainment rates • Only precipitating updraft in shallow convection scheme is considered; downdraft is ignored

  16. We build it based on LES studies Siebesma & Cuijpers (1995, JAS) Siebesma et al. (2003, JAS) LES studies

  17. Cloud water cross-section looks better

  18. PBL & Low clouds combined (CFS run) ISCCP Control Cloud cover looks better Revised PBL & new shallow convection

  19. Revised PBL + New shallow (Winter, 2007) 500 hPa Height Anomaly Correlation NH(20N-80N) SH(20S-80S) Skill scores were better

  20. Precipitation skill score over US continent 12-36 hrs 36-60 hrs 60-84 hrs Skill scores were better

  21. Revised PBL + New shallow (Summer, 2005) 500 hPa Height Anomaly Correlation NH(20N-80N) SH(20S-80S) Skill scores were better

  22. Precipitation skill score over US continent 12-36 hrs 36-60 hrs 60-84 hrs Skill scores were slightly better

  23. NINO3.4 OIV2 Observed ENSO signal

  24. NINO3.4 set22 Multi-year simulation of the control looks ok

  25. NINO3.4 set28b The test version showed too weak ENSO in early years and too strong ENSO in later years. RESULTS : no implementation

  26. Srb2 is observation With a VOCALS grant from CPPA, Mechoso worked with us to examine these runs. This is the downward short wave radiation reaching ground for the control

  27. There is too much radiation reaching ground for the new package over western Pacific but too little over central Pacific. More changes will have to be made.

  28. How CTB can help address the GAP • Increasing the number of competitive grants to external researchers to contribute advanced physics packages for the CFS • Provide computational and human resources to expedite tests and evaluations on newly incorporated physical parameterizations • Work to enhance communication with the research community on the requirements for implementing model improvements at NCEP (R2O) • Encouraging researchers to use the operational model (O2R) to identify deficiencies and to develop improvements through a CFS Model Support Facility.

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