Suomi -NPP in NAVDAS-AR

1. Use of Suomi-NPP in NAVDAS-AR*Benjamin Ruston1, Steve Swadley1, Nancy Baker1, Rolf Langland1, Karl Hoppel2,Efren Serra3, and Pedro Tsai31NRL, Monterey, CA2NRL, Washington D.C., CA3SAIC, Monterey, CA*Navy Atmospheric Variational Data Assimilation System – Accelerated Representer

2. Suomi-NPP in NAVDAS-AR • ATMS • Operationally assimilated using JCSDA CRTM • Improved coverage compared to AMSU-A/MHS • Improved performance of water vapor channels compared to MHS, both spectrally and in noise performance • OMPS • Delivered OMPS Nadir Profiler (NP) assimilation methodology to operations; currently pending OPSTEST • First use of passive tracer assimilation capability in NAVDAS-AR • Transferred along with SBUV/2 • CrIS • In experimental assimilation using JCSDA CRTM • Refining cloud detection methodology • Examining innovation and increment statistics to: • Refine observation error • Hollingsworth-Lönnberg and Desrozier techniques • Refine channel selection • Adjoint methods: Forecast sensitivity to observation error

3. Outline • Current ATMS operational performance • How does the impact of ATMS compare with other Microwave (MW) and Infrared (IR) sensors • How has ATMS looked from a stability standpoint • What components could be added for additional ATMS impacts • Ozone in the Navy global model and OMPS assimilation • Navy Global Environmental Model (NAVGEM) Ozone analysis • Passive tracers in NAVGEM and NAVDAS-AR • Impacts of OMPS-NP and SBUV/2 on NAVGEM Ozone field • Current development work with CrIS • Channel selection and questions • Data thinning, current strategy and concepts • Observation errors as diagnosed from innovation statistics • Summary and Future Directions

4. Navy’s Data Assimilation Tools NRL Coupled Ocean Data Assimilation SystemMultivariate Analysis of ocean u,v,T,s,ice,SSH,SWH. Global, Regional, Local Ocean Data Assimilation. NCODA NRL Atmospheric Variational Data Assimilation System3D Variational Analysis, Observation Space. Global, Regional, or Local Application. NAVDAS NAVDAS Accelerated Representer4D Variational Analysis, Weak Constraint, Model Space. Global or Regional Application. High Altitude DA. NAVDAS-AR ADJOINTS NAVDAS(–AR) Adjoints of 3D & 4D Data Assimilation Systems NOGAPS TLM; Moist Adjoint COAMPS®TLM; Moist Adjoint, including explicit moist physics NAVDAS-AdjointOBservation Monitoring System Real-time monitoring of all data assimilated. Identification of observation quality problems. Real-time data selection and data targeting. NAVOBS Ensemble Kalman Filter AlgorithmTesting for COAMPS® using real observations. EnKF/4DVAR Hybrid for the NAVDAS-AR framework. Ensemble DA

5. Operational Use of ATMS • ATMS is treated as a primary sensor and has a first priority weighting along with MetOp-B, DMSP-F18, and NOAA-18. • A 36km Gaussian 100pt filter is used to scene average the data • The ATMS data are thinned to ~135km before assimilation • In addition to quality flags in the data itself; a sea ice, cloud liquid water and scattering index is generated and applied to water vapor and tropospheric temperature channels • Operational bias correction is variational; however, a Harris-Kelley offline type is available

6. Operational Use of ATMS ATMS Spatial Smoothing Effects on OB-BK StDv DTG: 2012070412 Gaussian Average Boxcar Average s: Scan Position, b: Beam position N = 200* pre-computed closest points *note: a 100-point filter is used operationally

7. Operational Use of ATMS • Monitoring of operational data streams at FNMOC • http://www.nrlmry.navy.mil/metoc/ar_monitor/ Zonal Innovation Latitudinal dependence of mean and stdv Radgrams Global mean and stdv of innovation Observation Impact Reduction of NWP error due to observation

8. Monitoring of ATMS

9. OMPS - Ozone Assimilation • Currently, the global NAVGEM model is re-initialized every 6-hours with an external Ozone field • Added capability to assimilate OMPS-NP while maintaining ability to assimilate SBUV/2 • This fully utilized and developed the passive tracer assimilation in NAVDAS-AR • Added diagnostics for passive tracers (increment, etc.) • Passive tracer can be other trace gasses or dust • Shortened the vertical correlation length scale for Ozone • For radiances use the Ozone profile from the model rather than a default profile • Explored assimilation of IASI sounding channel in Ozone band

10. Ozone vertical profile at IASI locations NAVGEM Ozone background is shows well-behaved vertical distributions In the future we may assimilate IASI channels sensitive to Ozone So we examined the Ozone profiles at all IASI locations

11. Ozone Assimilation Tracer Assimilation: Ozone profiles from SBUV/2 and OMPS NEW - With Ozone Assimilation OLD - NOAA Initialization Add Tracer Assimilation capability for passive species. Implemented for Ozone retrievals from SBUV/2 and Suomi NPP-OMPS. Delivery in FY14 will allow removal of dependence on external NOAA field.

12. CrIS Assimilation • CrISis treated as a primary sensor and has a first priority weighting along with MetOp-B, DMSP-F18, and NOAA-18. • Data is selected for only a single FOV of the 9 per “golf ball” • The CrIS data is thinned to ~135km before assimilation • A Hamming apodization is performed on the radiances before conversion to brightness temperature to match coefficients in JCSDA CRTM • In addition to quality flags in the data itself; a cloud screen is applied using the innovation similar to IASI and AIRS, if a cloud is detected water vapor channels will not be assimilated for that pixel • Experimental bias correction is variational; however, a Harris-Kelley offline type will be developed before delivery to operations

13. CrIS Assimilation • CrISperformance continues to meet expectations for the sensor • The large volume of data requires extra care in efficiency and modularity of the code to meet operational time constraints • The current real-time feed is 1317 unapodized channels processed at AFWA and which arrive at FNMOC through a “bent-pipe” from NESDIS • There is some concern that operations may not support archival of the data stream indefinitely

14. CrIS Assimilation

15. Monitoring of CrIS

16. Summary Does ATMS have positive impact to Navy Global NWP? Yes, ATMS has consistently shown a positive impact to global NWP in the NAVGEM/NAVDAS-AR system. The impact is very similar to that of a combined AMSU-A/MHS sensor suite from the NOAA satellite series. Will Ozone from OMPS-NP be used operationally? Yes, the next system NAVGEM v1.2.1 has been delivered to FNMOC and is pending an OPSTEST. It includes Ozone assimilation from OMPS-NP and SBUV/2. This does not have a dramatic impact on the global atmospheric forecasts, particularly in the troposphere. Will CrIS be operationally assimilated? Certainly, the CrIS sensor has shown great promise as an addition to the NAVDAS-AR system. It continues to undergo development, and is slated for release with NAVGEM v1.3.x, and will include both temperature and moisture channel assimilation.

17. Future Directions • Explore more dynamic thinning for ATMS, rather than evenly spaced • Test any striping mitigation strategies which are proposed and provided • Investigate potential “bias” correction between SBUV/2 and OMPS-NP • Examine impact of improved Ozone chemistry with improved diurnal variation on Ozone assimilation and model temperatures and fluxes in mid to upper stratosphere • Continue to bring CrIS assimilation to operational readiness • Add radiance components to land surface assimilation scheme • Begin testing MW (and IR) cloudy assimilation strategies