NASA/GMAO Contributions to GSI OUTLINE • GSI Infrastructure • New Instruments • Methodologies • Closing Remarks Questions/Comments: [email protected]Ricardo Todling Global Modeling and Assimilation Office GSI Workshop, DTC/NCAR, 28 June 2011 Contributions from: A. da Silva, A. El Akkraoui, W. Gu, J.Guo, D. Herdies, W. McCarty, D. Merkova, M. Sienkiewicz, A. Tangborn, Y. Tremolet, K. Wargan, P. Xu, & B. Zhang
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NASA/GMAO Contributions to GSI
OUTLINE• GSI Infrastructure• New Instruments• Methodologies• Closing Remarks
Ricardo TodlingGlobal Modeling and Assimilation OfficeGSI Workshop, DTC/NCAR, 28 June 2011
Contributions from: A. da Silva, A. El Akkraoui, W. Gu, J.Guo, D. Herdies, W. McCarty, D. Merkova, M. Sienkiewicz, A. Tangborn, Y. Tremolet, K. Wargan, P. Xu, & B. Zhang
Ongoing Development• GSI Infrastructure:
– Revisit ChemGuess_Bundle– Introduce MetGuess_Bundle– Generalize Jacobian– Introduce interfaces to GSI-Jacobian/CRTM for Aerosols and Clouds– Revisit interface to TLM and ADM for 4D-Var
• New Observation Types and State-Variables:– MOPITT– SSMI– CrIS and ATMS– OMPS– Doppler Wind Lidar
• Methodologies:– Use of cloud-cleared moisture background to assimilate IR instruments– GMAO-GOCART Aerosols influence on radiance assimilation– Add Bi-CG minimization and corresponding Lanczos pre-conditioning– Estimation of tendency-based Q (system error covariance)
GSI Infrastructure
Revisit ChemGuess_BundleIntroduce MetGuess_BundleGeneralize JacobianIntroduce interfaces to GSI-Jacobian/CRTM for
Aerosols and CloudsRevisit interface to TLM and ADM for 4D-Var
• GSI_Chem_Bundle renamed to ChemGuess_Bundle• Introduce MetGuess_Bundle as a means to ingest
meteorological guesses into GSI: – presently working for clouds-related fields– being extended to work with basic fields (u, v ,tv, etc)
• anavinfo file:– Updates made to chem_guess table– Add met_guess table to control contents for
MetGuess_Bundle• Future work includes:
– Instantiation of ChemGuess and MetGuess Bundles
GSI Infrastructure: ChemGuess and MetGuess Bundles
GSI Infrastructure
Interfaces to Aerosols & Clouds
• Adding aerosols and clouds to Guess Bundle allows for these to be passed to CRTM; parameter in anavinfo tables determines what’s to feed to CRTM and how.
• Add flexible interface to allow for user-specific controls to handle aerosols and clouds (see Tutorial)
Interface to AD/TL models• Revisit to support ESMF• Available interfaces exist
now for at least three global AD/TL models:– GEOS-5 FV-dynamics– GEOS-5 FV-cubed-dynamics– NCEP Perturbation model
New Instruments
MOPITT Carbon MonoxideSSMISCrIS and ATMSOMPS O3 (OSSE-like)Doppler Wind Lidar (OSSE-like)
New Instruments: MOPITT CO
Changes entail:- mild change to obsmod- add usual suspects when handling new observing types, e.g.:
- readCO - setupCO - intCO - stpCO- Estimate and set B(co).
• Four profiles of MOPITT CO are randomly placed on the globe and assimilated using GSI. Preliminary results are consistent with shape of averaging kernel.• Cycling experiments are on the way.
MOPITT - Measurements Of Pollution In The Troposphere
(from Andrew Tangborn)
New Instruments: OMPS O3 (OSSE)OMPS – Ozone Mapping and Profiler Suite
• High Fidelity Measurements:- Total column (like TOMS)- Vertical profiles (like SBUV)
Results show:- Data are ingested into GSI at all levels - QC control works (but rate of rejection can be adjusted)- Analysis works effectively- Penalties are in good range- Time series show fast convergences - OMA and OMF are all very small and OMA are smaller than OMF
(from Philippe Xu)
New Instruments: OMPS O3 (OSSE)OMPS – Ozone Mapping and Profiler Suite
(from Philippe Xu)
a) 5 hPa b) 100 hPa
Analysis error (%) of retrieved ozone assimilation from TRUTH
- At 5 hPa errors are small in most of region; orbit tracks of OMPS analysis are noticeable.
- At 100 hPa errors are large where retrievals are most difficult: Tropics as the ozone value are very small (<0.1ppmv).
New Instruments: OMPS O3 (OSSE)OMPS – Ozone Mapping and Profiler Suite
(from Philippe Xu)
Retrieved vs MLS TRUTH (%) OMPS sampled vs MLS TRUTH (%)
Monthly Zonal Mean analysis errors
• The results show that OMPS data agree well with MLS in the stratosphere and in most of the troposphere.
• In the tropical UT and LS there is large discrepancy (%) between MLS and OMPS, where the ozone mixing ratio are very small (<0.1 ppmv); needs more work.
- Mie impact neutral away from tropics; mildly positive in tropics - Rayleigh impact positive throughout; dominates in tropics
- Lower-troposphere- Mie and Rayleigh give redundant impact: either provides all information
- All-in-all OSSE tends to over-state impact of observing system- Obs error need to be better adjusted (esp. for Mie)
Methodologies
Use of cloud-cleared moisture background to assimilate IR instruments
GOCART Aerosols influence on radianceBi-CG minimization and Lanczos pre-conditioningEstimation of tendency-based Q (model error)
Methodologies: Cloud-cleared q variable for IR
Changes entail:- add cloud frac to guess- cloud frac to crtm_interface
Picture displays mean OmF for AIRS calculated using full q variable (red)and cloud-clear q variable; some reduction in bias is observed when new is used – results are still preliminary.
(water-vapor)
(from Dagmar Merkova & A da Silva)
Methodologies: Aerosol Radiance Contamination
• CRTM allows for the inclusion of (GOCART) aerosols• The GEOS-5 GOCART aerosol species have been
introduced as state variables in GSI– No aerosol analysis for now– Aerosol effects included in the observation operators for IR
instruments: AIRS, HIRS, IASI, etc
• Control Experiment:– Fully interactive GEOS-5 GOCART aerosols– Standard global GSI– ARCTAS period: Summer 2008– Resolution: ½ degree
Plots show horizontal scales for B and prototype Q for stream function, velocity potential, and temperature at 45N obtained over a four-month sample of forecast full fields and tendencies, respectively.
Figure above shows normalized impact of observations within analysis window for SC and no-B WC.
(from Banglin Zhang & Wei Gu)
Closing Remarks
• Completing comparison of SC and WC-4dVar in prototype GEOS-5 4dVar system.
• Making progress in bringing GEOS-5 Cubed-Sphere TLM and ADM to maturity.
• Started working on hybrid ensemble components for GEOS-5 3d- and 4d-Var.
Collaboration with NCEP is ongoing and fundamental for the success of these implementation.
New Instruments: OMPS O3 (OSSE)OMPS – Ozone Mapping and Profiler Suite