1 Coupled Modeling for Seasonal to Interannual Presented By Suru Saha (EMC/NCEP) Contributors: Jack Woollen, Daryl Kleist, Dave Behringer, Steve Penny,

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1 Coupled Modeling for Seasonal to Interannual Presented By Suru Saha (EMC/NCEP) Contributors: Jack Woollen, Daryl Kleist, Dave Behringer, Steve Penny, Xingren Wu, Bob Grumbine, Mike Ek, Jiarui Dong, Shrinivas Moorthi, Xu Li, Sarah Lu, Yu-Tai Hou, Arun Chawla, Henrique Alves (all EMC)

2 Operational System Attribute(s ) System NameAcronymAreal Coverage Horz ResCycle Freq Fcst Length (hr) Climate Forecast System (operational, coupled atmosphere-ocean-sea-ice- land) CFSGlobal110km6hrs45days – seasonal - 9 months SystemAttributes CFSDA: 3DVar for atmosphere (CDAS)+ocean (GODAS)+land (GLDAS)+seaice analysis 4 control (unperturbed) members are out to 9 months, 12 perturbed members per 24 hours are out to 45 or 90 days. System Data Assimilation or Initialization Technique

3 Why System(s) are Operational  Primary stakeholders and requirement drivers The need for seasonal prediction is great, given societal vulnerabilities, such as: the impact of El Nino on the prediction of US temperature and precipitation (especially, since this winter 2015/16 may shape up to be a major event) the drought community, which require accurate predictions for water management purposes industry, such as energy, transportation, etc. Participation in the National and International MME  What products are the models contributing to? At CPC: Global Hazards Assessment, Seasonal Prediction (lead months) of US T&P and global SST, ENSO Diagnostic Discussion, MJO, Drought Outlook, African Desk products, Seasonal Hurricane Outlooks, Arctic Sea-ice prediction. Outside NCEP: Commercial, Regional Climate Centers, etc.  What product aspects are you trying to improve with your development plans? Better guidance through improved forecast skill. Increased availability of products.  Top 3 System Performance Strengths Strength 1: ENSO Prediction (6-month, Nino 3.4 SST) Strength 2: MJO Prediction out to 45 days Strength 3: Prediction of Global SST and oceanic precipitation  Top 3 System Performance Challenges Challenge 1 : Keeping up with constant changes in the observing system Challenge 2 : Keeping up with changing CO2 concentrations in the system Challenge 3 : Keeping up with changing computer systems

4 System Evolution Over the Next 5 Years  Major forcing factors We need a unified approach to global modeling for all spatial and temporal resolutions for better management of modeling activities at NCEP.  Science and development priorities UGCS Unified Global Coupled System Atmosphere-Land-Ocean-Seaice-Waves-Aerosol-Ionosphere interactions Timely Reanalysis and Reforecast for each implementation  What are you top challenges to evolving the system(s) to meet stakeholder requirements? Challenge 1 : Using a unified hybrid ensemble approach to DA of the coupled system Challenge 2 : Testing the following models within the NEMS framework: MOM5.1/MOM6 and/or HYCOM for the ocean SIS2/CICE/KISS for sea-ice WAVEWATCH III for waves Noah-MP for land GOCART for aerosol WAM for ionosphere Challenge 3 : Making the next CFS a community model  Potential opportunities for simplification going forward Unified global modeling allows for better use of resources with respect to core / physics / coupling development, but is can we unified on the different scales involved.

5 Top 3 Things You Need From the UMAC 1.Help with finding the required resources for: Computing Archival Dissemination 2.Where and how should this system be run. 3.Should a focus be on unified global modeling, and how can this e approached as a community modeling effort.