UMAC data callpage 1 of 16Global Ensemble Forecast System - GEFS Global Ensemble Forecast System Yuejian Zhu Ensemble Team Leader, Environmental Modeling.

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UMAC data callpage 1 of 16Global Ensemble Forecast System - GEFS Global Ensemble Forecast System Yuejian Zhu Ensemble Team Leader, Environmental Modeling Center NOAA / NWS / NCEP

UMAC data callpage 2 of 16Global Ensemble Forecast System - GEFS Whole Atmosphere Model Unified Global Model Application = Ensemble + Reanalysis + Reforecast NGGPS Unified Global Coupled Model “GFS”“GEFS”“CFS” Actionable weather Week 1 through 4-6 Seasonal & annual 1 y2 y4 yUpdate cycle 3 y20-25 y presentReanalysis 6h6-24h???cycling WCOSS WCOSS ?where

UMAC data callpage 3 of 16Global Ensemble Forecast System - GEFS Current Status of GEFS Initial analysis/perturbations –GFS/GSI analysis –BV-ETR (Breeding Vector – Ensemble Transform with Rescaling) Toth, Z., and E. Kalnay, 1997: Ensemble forecasting at NCEP and the breeding method. Mon. Wea. Rev., 125, 3297–3319. Wei, M., Z. Toth, R. Wobus, and Y. Zhu, 2008: "Initial Perturbations Based on the Ensemble Transform (ET) Technique in the NCEP Global Operational Forecast System" Tellus 59A, Model –GFS model (see GFS reforences) Relocation –TS relocation since 2005 Liu, Q., S. J. Lord, N. Surgi, Y. Zhu, R. Wobus, Z. Toth and T. Marchok, 2006: Hurricane Relocation in Global Ensemble Forecast System, Preprints, 27th Conf. on Hurricanes and Tropical Meteorology, Monterey, CA, Amer. Meteor. Soc., P5.13. Stochastic physics –STTP (stochastic total tendency perturbation) since 2010 Hou, D., Z. Toth, Y. Zhu, W. Yang and R. Wobus, 2012: A Stochastic Total Tendency Perturbation Scheme Representing Model- Related Uncertainties in the NCEP Global Ensemble Forecast System, Submitted to Tellus-A (Dec. 2010) Configuration –20+1 members, four times per day, out to 16 days.

UMAC data callpage 4 of 16Global Ensemble Forecast System - GEFS GEFS Upgrade (Q4FY15) V (OPR)V (PARA) GFS ModelEuler, 2012Semi-Lagrangian, 2015 Resolution hT254 (52km) L42 (hybrid)T L 574 (34km) L64 (hybrid) Resolution hT190 (70km) L42 (hybrid)T L 382 (52km) L64 (hybrid) Computational Cost 105 nodes (Integration + post-process) 310 nodes 1 st segment 250 nodes 2 nd segment Execution time55 min 35 min 1 st segment 30 min 2 nd segment Output resolution1 O x 1 O 0.5 O x 0.5 O for 0-8 days 1 O x 1 O the rest Output frequency6h3h the first 8 days; 6h the rest

UMAC data callpage 5 of 16Global Ensemble Forecast System - GEFS GEFS Upgrade (Q4FY15) Moving from BV-ETR approach to EnKF –A major scientific shift Unification DA and Ensemble Generation –Direct link to the hybrid 3D-Var EnKF DA system Perturbations are 6h forecasts EnKF with adjustments: –Tropical Storm Relocation –Centering of the perturbations on the ensemble control analysis Stochastic perturbation (STTP) upgrade –Fine-tune amplitude for changes in model and perturbation method –Turn off surface pressure perturbations for tropical to reduce the spread growing of geopotential height

UMAC data callpage 6 of 16Global Ensemble Forecast System - GEFS GEFS Upgrade (Q4FY15) cases Northern Hemisphere 500hPa Geopotential Height 77% 9.52d 9.20d 75% Summary from nearly 2 years retrospective runs: 1.GEFSv11 improves forecast skill (60%) about 8 hours 2.GEFSv11 enhances AC score from 75% to 77% for day-7 forecast T2m for Northern American With bias correction, GEFSv11 reduces RMS error for all leads Summer precipitation for CONUS Improve reliability

UMAC data callpage 7 of 16Global Ensemble Forecast System - GEFS 00UTC Opr: T254L42 (55km) Opr: T254L42 (55km) Para: T574L64 (33km) Para: T574L64 (33km) 06UTC Thick blue: ensemble mean Bimodality? Sandy Ini: ; Fcst: 8-day Sandy Ini: ; Fcst: 8-day

UMAC data callpage 8 of 16Global Ensemble Forecast System - GEFS GEFS Short-term Plan Initial perturbations –Use EnKF analysis directly, not 6-hour forecasts Model –GFS model with tuning parameters for lower resolution Relocation –TS relocation with tuning TS amplitude of perturbations Stochastic physics –Introduce well-established stochastic tendency perturbations SKEB, SPPT and SHUM Configurations –20+1 members, four times per day, out to 16 days. –Continue to investigate the benefits from different ensemble membership (size)

UMAC data callpage 9 of 16Global Ensemble Forecast System - GEFS GEFS Long-term Plan Toward unified global system –Full coupled system Uniform resolution –Consider uniform resolution after introduce high resolution global ensemble for weather (out to 7-10 days) Ensemble size (or membership) –Continue to investigate the benefits of different ensemble membership Cover week-1, week-2, week 3&4 and monthly forecast –See slides (#10-15) for GEFS extend forecast –Introduce land surface uncertainties (perturbations) –Introduce ocean uncertainties (perturbations) Upgrade every 2 years years reanalysis and GEFS reforecasts for every upgrade.

UMAC data callpage 10 of 16Global Ensemble Forecast System - GEFS Global Ensemble Forecast System Extend to 35 days (experiments) Yuejian Zhu Ensemble Team Leader, Environmental Modeling Center NOAA / NWS / NCEP

UMAC data callpage 11 of 16Global Ensemble Forecast System - GEFS GEFS Extend Forecast Short term plan (1-2 years) –Atmospheric model only –Introduce SST forcing to assimilate MJO and others –Ocean and land surface perturbations In testing – may not include in short-term implementation plan –Stochastic physics Will use the same stochastic physic scheme as GEFS 0-16 day forecast. –Configurations 20+1 members, twice per week, from 16 days to 35 days. Long term plan (3-5 years) –Unified global forecast system –Fully coupled system Atmosphere-Ocean-Land-Ice-Wave-Aerosol –Initial perturbations EnKF DA for atmosphere and ocean –Model uncertainties Stochastic physics –Configurations 20+1 members (?), uniform resolutions, once per day, out to 45 days

UMAC data callpage 12 of 16Global Ensemble Forecast System - GEFS GEFS Extend Forecast Experiments –Period: Sept. 1 st 2013 – Feb. 28 th 2014 (6 months) Weak MJO period –GEFS v11 (2015) 20+1 members, 33km for day 0-8, 50km for day 8-16, 70km for day –Three different configurations have been tested CTL – default GFS/GEFS setting – start with RTG SST analysis, relaxed to climatology (90 days e-folding) RTG – using RTG analysis forcing GEFS every 24 hours (AMIP) CFS – using CFSv2 predictive SST forcing GEFS every 24 hours) –Two additional configurations are on going CFS* - using CFSv2 predictive SST (bias corrected) anomaly forcing GEFS every 24 hours Full coupling with MOM4 (or MOM6) –Evaluations Tropical – MJO, precipitation Extratropical – 500hPa height, surface temperature and precipitation Extreme weather patterns – Blocking, polar vortex

UMAC data callpage 13 of 16Global Ensemble Forecast System - GEFS 1.RTG-SST (AMIP) run has good MJO forecast skills 2.CTL-SST runs has less MJO forecast skills for first 2 weeks WH-MJO fcst skills for GEFS (6 months average)

UMAC data callpage 14 of 16Global Ensemble Forecast System - GEFS Evolution of error difference (500hPa height) 5-day running mean (09/01/2013 – 2/28/2014)

UMAC data callpage 15 of 16Global Ensemble Forecast System - GEFS Lead day = 19 Lead day = 23 RMSESPREAD RMS error and spread distributions for 500hPa height of CTL-SST – (6 months) 5-day running mean For different lead times Uncertainty is Well represented Over dispersion ?

UMAC data callpage 16 of 16Global Ensemble Forecast System - GEFS GEFS Reforecast Consider latest years –Goes with every model upgrade –Goes with new re-analysis –Better to start from 1998 (AMUSU data started) Configurations –Option 1: use “white paper” recommendation –Option 2: consider NWC’s request (current impossible) Real-time or retrospective –Resource dependence Benefits –National centers: WPC, CPC, OPC, NWC –Regions: WFO