ARCs Contributions to CTB

1. ARCs Contributions to CTB NOAA Climate Test Bed Science Advisory Board 28 August 2007

2. NOAA Applied Research Centers (ARCs) and CTB • The NOAA Applied Research Centers (ARCs) conduct mission-oriented applied R&D with stable funding under five-year renewable institutional awards. Each Center has a unique capability to contribute to the NOAA Climate Program’s objectives. (from CPO: http://www.climate.noaa.gov/cpo_pa/cdep/) • The ARCs collaborate with CTB to accelerate transition of new and improved science-driven climate forecast & analysis products into operations (R2O) with emphasis on specific CPC product ranges (6-10 day, week 2, monthly, seasonal) (from CTB Interim Report 2007) • The ARCs are also beginning a new activity to enable the research community to make use of CTB models (O2R) • ARCs: • Climate Diagnostics ARC (ESRL/PSD; formerly CDC) • COAPS (Florida State U) • COLA • CSES ARC (U Washington) • ECPC (Scripps/U California San Diego) • Affiliated centers (IRI, GFDL, GMAO, NCEP)

3. Example: CTB Seminar Series • CFS as a Prediction System and Research Tool • Initially being established by NCEP and COLA • Will expand to include the broader climate community • 12 scheduled through Feb’08 (6 at COLA, 6 at NCEP) • Seminars at NCEP will be coordinated with CTB “Test and Evaluation Team” meetings • Future Foci: • Multi-Model Ensembles • Climate forecast product improvements

4. Position NOAA to proactively deliver research products and experimental services that provide explanations of current and evolving climate and predictions of future climate and extreme events with drought-related research and applications in support of NIDIS as the near-term priority. Research is coordinated around five foci that contribute to CDEP objectives. Reforecasts and Weather-Climate: develop reliable and improve probabilistic short term climate forecast products Historical Reanalysis: produce a 100-year global climate reanalysis based on surface pressure data using ensemble data assimilation techniques Climate Attribution: improve climate attribution capabilities to meet policy and decision maker needs for explanations of the climate system. Climate System Diagnosis: improve understanding of dynamical processes and predictability of the the climate system Regional Applications and Services: improve delivery of regional climate products and services needed to manage climate-related risks. Climate Diagnostics ARC http://www.cdc.noaa.gov Courtesy - Robin Webb

5. Infuse research findings into weekly US Hazards Assessment discussions, monthly US Seasonal Outlooks discussions, ENSO Diagnostics discussions, Drought Monitoring Assessments Develop advanced techniques for 6-10 day and 8-14 day temperature and precipitation outlooks Develop new tools for NOAA Drought Outlooks Partner with NOAA RISAs (e.g., WWA, CLIMAS, CIG, & CAP) to develop and deliver experimental regional climate products and services Created and maintain a web portal where researchers can download the latest operational source code of the National Center for Environmental Prediction's Global Forecast System (GFS) model modified to run in Linux cluster environments.http://code.google.com/p/ncepgfs/Sciences_Division The Climate Diagnostics ARC complements the Climate Test Bed through scientific advances that improve NOAA climate forecast products and services http://www.cdc.noaa.gov Courtesy - Robin Webb

6. Center for Ocean-Atmospheric Prediction Studies (COAPS) About COAPS COAPS is located at Florida State University and was officially formed in August 1996 by the Florida Board of Regents. COAPS has approximately 45 employees (i.e., faculty, scientists, students, and support staff). Mission Statement To be a center of excellence which promotes interdisciplinary research in air-sea interaction, the coupled ocean-atmosphere-land-ice earth system, and climate prediction on scales of weeks to decades in order to increase our understanding of the physical, social, and economical consequences of coupled ocean-atmospheric variations. Centers/Consortiums within COAPS NOAA Applied Research Center, Research Vessel Data Center, SAMOS Initiative, Florida Climate Center, Southeast Climate Consortium, Northern Gulf of Mexico NOAA Cooperative Institute, HYCOM Consortium Data Serving Florida Climate Data, FSU Winds and Fluxes, Scatterometer Products, Research Vessel Data, . HYCOM Data Products, JMA SST ENSO Index http://www.coaps.fsu.edu Courtesy - Eric Chassignet

7. COAPS Contributions Current • Climate Modeling Activities: Improvement of seasonal surface climate outlooks in the FSU/COAPS atmospheric model to examine its potential for crop yield estimation. Comparison of statistical versus dynamical downscaling. High-resolution Atlantic Basin seasonal hurricane simulations in the FSU/ COAPS atmospheric model. • Refinement and development of climate forecast products: Agriculture, wildfire risk forecast system, variability of extremes and extreme events, etc. (http:///agclimate.org) • Storm Surge Modeling: Collaboration with the NHC/TPC which led to a modification of the surge forecasting techniques for storms in the Gulf of Mexico. Future/Planned • Accelerated development and transfer of applied climate products on time scales of weeks to a season for the Southeast United States. • Collaboration with NCEP on the evaluation of the CFS in the areas of COAPS’ expertise, i.e., seasonal climate prediction (including impact on crop yield), downscaling, El Nino, impact on crop yields, seasonal hurricane activity and prediction, etc. • Evaluation of the CCSM/HYCOM for seasonal prediction. • Evaluation of HYCOM as an ocean component for the CFS. http://www.coaps.fsu.edu Courtesy - Eric Chassignet

8. Center for Ocean-Land-Atmosphere Studies (COLA) • Vision: Global society benefits from use-inspired basic research on climate variability, predictability, & change and free access to research data & tools • Mission: Explore, establish and quantify the predictability of seasonal to decadal variability in a changing climate • Support: COLA is a part of IGES, an independent non-profit institute, and is supported by NSF (lead), NOAA and NASA through a single jointly-peer-reviewed, jointly-funded five-year “omnibus” proposal (current: 2004-2008) • Core Competencies: • Evaluation of and experimentation with Nation’s climate models • Scientific leadership in S-I predictability • Collaboration with PhD program in Climate Dynamics at GMU • GrADS and GDS - highly-valued, widely-used information technology • Accomplishments: • COLA viewed as major interagency program (e.g. US National Research Council report) • Quantified dynamical model seasonal prediction (DSP) capability • Advanced multi-model ensemble • Demonstrated that O-A and L-A interactions, with high-frequency noise and low-frequency climate change, play important roles to enhance predictability • Developed innovative modeling, data analysis and information theory-based strategies for understanding predictability and improving prediction http://www.iges.org Jim Kinter

9. Jan ICs 1982-2000 COLA Contributions to CTB • Current • CFS experiments • 10 COLA scientists, 2 PhD students and 1 summer intern actively using CFS • Diagnose/model initial tendency errors in GFS/CFS (DelSole CTB project) • Potential predictability of intraseasonal variability • ENSO and the ENSO-monsoon relationship • Bias, bias correction & skill in the Atlantic • Multi-model experiments • CCSM proof-of-concept • Planned • Multi-model R2O • CCSM transition to operations (CTB proposal) • GFDL CM2.1 transition to operations (collaboration with GFDL) • GMAO forecast diagnosis (R2O in discussion) • O2R - support for CFS and other models • Initial focus on land surface models (tentative) http://www.iges.org Jim Kinter

10. Center for Science in the Earth System (UW) ARC • Integrated research on the impacts of climate on the U.S. Pacific Northwest by combining and integrating expertise in climate dynamics, ecological dynamics, hydrologic dynamics, and institutional and policy analysis • CSES is partially within the Joint Institute (with NOAA) for Study of Atmosphere and Ocean (JISAO), the UW Regional Integrated Sciences and Assessments (RISA) center, and the UW ARC • Examples of CTB contributions: • Drafting an MOU with CPC/CTB to include National Surface Water Monitor as part of U.S. Drought Monitor • UW West-wide Seasonal Hydrologic Forecast System (see below) • Week-2 NCEP forecast for Pacific Northwest (see below) Courtesy - Dennis Lettenmaier http://www.cses.washington.edu

11. University of Washington West-wide Seasonal Hydrologic Forecast System • A real-time simulation test-bed for • climate forecast use in hydrology and water resources • satellite data assimilation • multi-model approaches • forecast verification • LDAS-era land surface models Courtesy - Dennis Lettenmaier

12. Documenting the skill of the two-week NCEP forecast for early winter in the Pacific Northwest Reforecast 15-day Z500 absolute mean forecast error, OND Motivation: Bond and Vecchi associated Madden and Julian Oscillation (MJO) variability with early-winter warm, wet storms and floods in the PNW. Floods in general are more likely in ENSO neutral and cold conditions (like this year). Approach: Using the Hamill and Whitaker NCEP reforecasts (15-member ensembles, 15-day lead, updated daily 1979-present): Calculate the forecast skill in PNW 500 mbgeopotential height for the early winter. Alsostratify for MJO- and ENSO-phase, andevaluate forecast skill Calculate dominant hemispheric patterns of forecast error and relate to atmospheric flowpatterns and ENSO phase. Identify other regions and seasons whichexhibit predictability at ~2-week leads; evaluateimplications for hydrological (flood) forecasts. Extend analysis to include precipitation as wellas geopotential height. Courtesy - Dennis Lettenmaier

13. Courtesy - John Roads

14. ECPC’s Experimental Prediction System is based on NCEP CFS • 1997: ECPC began making, for the USFS, experimental weekly to seasonal GSM/RSM predictions for the CONUS using the NCEP R1 GSM/RSM • Initial conditions came from the NCEP GDAS 00UTC analysis. Initial persisted SST anomalies provided ocean BCs. Observed precipitation drives initial FDI • 2003: ECPC began making, for IRI/CPC, an ensemble (16) of seasonal (7 months) global predictions using the NCEP SFM • Atmospheric initial conditions came from long term simulations forced by observed SSTs. Ocean BCs came from IRI SST predictions. • 2006: ECPC began making routine ECPM coupled ocean atmosphere predictions for fisheries applications. • The MIT ocean model was coupled to NCEP SFM • The ocean initial conditions came from the JPL analysis • 2006/7: ECPC G-RSM prediction models • GSM and RSM consolidated to a single G-RSM model • Noah LSM replaced RII OSU • Prognostic clouds added to G-RSM • Observed precipitation being used to not only update the FDI but also the soil moisture • Streamflow module under development http://ecpc.ucsd.edu Courtesy - John Roads

15. ECPC’s Past and Future Contributions to CTB PAST • 2005-2008: Member of CST • 2005-2008: ECPC has been diagnosing experimental NCEP CFS/GSM/RSM ensembles for fire danger applications for USFS, NICC • The CFS/GSM/RSM initial conditions and SST boundary conditions came from RII and MOM3 ocean analysis. Observed precipitation used for FDI initial conditions • These experimental forecasts are being provided to NICC as part of its new monthly forecast effort of US fire danger. • Depending on funding, these experimental firedanger forecasts will continue to be provided to NICC. • We also plan to continue these experimental firedanger forecasts at ECPC using models equivalent to CFSnext (e.g. ECPC G-RSM), initialized from GDAS and our own land surface initialization FUTURE ?? • 2007-?: O2R - Provide part time assistance to CTB WWW and help desk. • We are planning for our ECPC Webmaster to work part time at NCEP on the CFS community help desk. • 2008-2010: Analyze multi-RCM downscaling of seasonal CFS forecasts • Depending on funding, we are proposing to develop a pilot multi-RCM model downscaling of NCEP CFS Dec. forecasts • If this Dec. downscaling provides a successful CFS augmentation, additional initial months may be tested. http://ecpc.ucsd.edu Courtesy - John Roads