Forecast Sensitivity - Observation Impact (FSOI) Inter-comparison Experiment Tom Auligné, Joint Center for Satellite Data Assimilation (JCSDA) Ron Gelaro, NASA, Global Modeling and Assimilation Office (GMAO) Rahul Mahajan, David Groff, NOAA, National Weather Service (NWS) Rolf Langland, Naval Research Laboratory (NRL) Jianjun Liu, NOAA’s Satellite and Information Service ( NESDIS) James Cotton, Larry Morgan, UK Met Office Yoichiro Ota, Japan Meterological Agency (JMA)

Forecast Sensitivity – Observation Impact (FSOI) Fcst Error observations assimilated Langland and Baker (2004) Time -6 h 0 h +24 h Build the illustration in a few steps, click by click.... Adjoint-derived (single outer-loop) observation impact Ensemble-derived observation impact

Motivation Several NWP centers are computing FSOI routinely to monitor/understand/tune their DA system. Are relative impact of various observation types comparable? Can we learn from similarities/differences to improve NWP systems? Multiple NWP Centers expressed interest in this study NRL, GMAO, EMC, Met Office, ECMWF, Meteo-France, KMA, JMA, Env. Canada

Motivation (cont.) Multi-staged and multi-faceted set of experiments. Participants free to contribute commensurate with interests and capability. Initially a narrowly defined FSOI experiment—much in the mold of the previous THORPEX inter-comparison (Gelaro et al. 2010) Original aspects Broader participation of NWP centers (Adjoint & Ensemble-based) Latest global NWP systems Operational (not baseline) observing network Approach centrally collect FSOI output without aggregation of the data Convert into common data structure Flexibility to stratify information.

Experimental Design Time period: 3-month DJF 2014-15 (planned JJA 2014) 00UTC & 06UTC cycles Verification:  24h forecast against self analysis Metric: global total dry energy (surface-100hPa) Adjoint: dry plus moist physics, as available Ensemble: flow-following localization Results shown here are VERY preliminary (only global summary plots of impact at 00UTC will be shown)

Participating NWP Centers NRL GMAO Met Office JMA Adjoint JMA Ensemble EMC Analysis System 3DVar In Observation Space Hybrid 3DVar 4DVar LETKF re-centered via 4DVar EnKF re-centered via 4DEnVar FSOI Technique Adjoint Ensemble Experiment Resolution T119L60 Model: 25km DA: 50km Ens: 100km Model N320 (40km) Adjoint N216 (60km) Model TL959L100 Adjoint TL319L100 Ensemble (x50) TL319L100 Ensemble (x80) T254 Specific Considerations QC = channel selection + dynamical observation error ~30% cycles discarded due to spurious impacts Additional thinning of observations except for aircraft data

COMMON

Observation Impact at 00UTC: Observation Count GMAO NRL Met Office 106 106` 105 JMA Adjoint JMA Ensemble EMC

Observation Impact at 00UTC: Observation Count

Observation Impact at 00UTC: Total Impact 0.35 0.3x2 0.3 0.06 3.0 GMAO NRL Met Office 0.3 0.06 JMA Adjoint JMA Ensemble EMC

Fractional Impact at 00UTC: Satellite Radiances

Fractional Impact at 00UTC: Other Observations

Observation Impact at 00UTC: Fraction of Beneficial Observations Impact < 0  Beneficial Impact > 0  Detrimental ε=10-10 Impact < -ε  Beneficial Impact > ε  Detrimental -ε < Impact < ε  Neutral

Observation Impact at 00UTC: Fraction of Neutral Observations

Total Impact: METOP-B AMSUA Ch. 6 Ensemble Adjoint GSI JMA

Adjoint

Conclusion and Perspectives Confirmation of results from Gelaro et al. (2010), noticeable additional impact from hyperspectral IR sounders Discrepancies between adjoint- and ensemble-based FSOI values. Further investigation needed. Many more composite plots can provide detailed analysis Mean/variance maps (across centers) Time/spatial correlations Ancillary interests not covered so far investigation of different types of norms and verifications methods, more participating NWP centers: global & regional NWP systems. Possibly set up Near-Real-Time multi-agency monitoring capability

Questions?