EMC’s Current and future GSI development

EMC’s Current and future GSI development John C. Derber Environmental Modeling Center NCEP/NWS/NOAA With input from: Many others

Project areas • Advanced assimilation • Use of Satellite Radiance data • Cloud assimilation • Doppler Radar data • NSST analysis • Use of GPS data • Satellite winds • Trace and constituent gases and aerosols • Conventional observations • Other • Code maintenance

Advanced Assimilation • Hybrid GSI/EnKF system (Whitaker …) • Global system – dual resolution (Kleist, Parrish, Treadon) • Parallel tests for implementation in Spring 2012 begun • Results very promising • Presentation by Kleist this afternoon • Regional (Wu, Parrish) • Using global EnKF ensembles? • Initial tests promising, but not as good as global • Hurricane (Tong, HFIP) • Being set up to run this hurricane season • Using global EnKF ensembles • 4D-Var (Rancic, GMAO) • Perturbation model to be used for all systems • Current status, being incorporated into GSI • Balance constraints (Kleist, Parrish, Kim (NESDIS)) • Regional development still stalled • Inclusion of cloud and precip. parameterization underway in global. • Importance once hybrid system developed?

Use of Satellite Radiances • Improved CRTM (vanDelst, Groff, Q. Liu (NESDIS), Han(NESDIS)) • Improved surface emissivity models/libraries • Improved surface information usage • Variable characteristics over FOV • Multi-levels • Improved cloud and aerosol Radiative Transfer • Accuracy and efficiency • Improved characterization of instruments • spectral responses for instruments

Use of Satellite Radiances • Use of NPP data (McCarty(GMAO), Collard, Chen(NESDIS)) • Launch Oct. 2011 • GOES-R and SEVERI (H. Liu, Collard) • SSMIS (Collard, Liang(NESDIS)) • F-16, F-17, F-18 available • Improve use of current satellite data • Improved bias correction (Y. Zhu, Collard) • Improved quality control • Channel selection (Collard, Jung (U. Wisc))

Cloud and precip. assimilation • Forward operator for cloudy radiances • Microwave (CRTM, Kim (NESDIS)) • IR (CRTM, McCarty (GMAO), Auligne (NCAR)) • Analysis variable for clouds (E. Liu) • Total water variable (Met. Office) • Background error covariances (McCarty (GMAO)) • Observation errors (Kim) • Can introduce bias if not specified carefully • Possibly correlated

Doppler Radar data • Use of Tail Doppler Radar for Hurricanes (Tong) • Use of fixed U.S. Doppler Radar network (S. Liu, NSSL) • External Doppler Radar networks (e.g., Canada) (S. Liu)

NSST analysis • Produces analysis of the Near Sea Surface Temperature every analysis time (diurnal cycle) (X. Li) • Involves inclusion of Surface warming and Surface Cooling model in ocean boundary layer • Inclusion of NSST model in forecast model (diurnal cycle in forecast) • Direct use of Radiance

NSST is a T-Profile just below the sea surface. Here, only the vertical thermal structure due to diurnal thermocline layer warming and thermal skin layercooling is resolved Assuming the linear profiles, then, 5 parameters are enough to represent NSST: Diurnal Warming Profile T Mixed Layer z Thermocline Skin Layer Cooling Profile Deeper Ocean z z

SST: Diurnal Variability of NSST at z=0 (05/17/2010 – 06/24/2010)

New New New New New - Old New - Old New / Old New / Old Old Diurnal Variability of Air temperature (05/17/2010 – 06/24/2010)

Validation of analysis: Histogram of O-B. 05/12/2010 – 06/24/2010 Surface Air T AVHRR_N18 Ch-4 OLD (Used) Sea T OLD (Used) OLD (Used) OLD (Used) OLD (Used) OLD (Used) OLD (Used) OLD (Used) OLD (All) OLD (All) OLD (All) OLD (All) OLD (All) OLD (All) NEW (Used) NEW (Used) NEW (Used) NEW (Used) NEW (All) NEW (All)

Time series at drifting buoy locations. Northern Mid-Latitude Atlantic, 05/12/2010 – 06/24/2010 OLD (Used) OLD (All) NEW (Used) NEW (All) NEW - OLD

Use of GPS data • Operational use of Refractivity (Cucurull) • Use of Bending Angle (Cucurull) • Preparation for implementation Spring 2012 • Inclusion of compressibility factors • Use of updated Refractivity coefficients • Use of ground based delay (Cucurull, GSD)

Satellite winds • Ability to read from Dump files rather than Prepbufr files. • Allows more information from data to be retained • Consistent from moving GOES IR sounding channels from PREPBUFR • Improve processing time • Improve quality control of winds • Add use of new satellite wind estimates (e.g., JMA water vapor winds)

Trace and constituent gases and aerosols • Trace and constituent gases • Inclusion of climatological changes in CO2 (and eventually other gases e.g., Methane) (Yang) • Improved Ozone analysis (H. Liu, GMAO) • OMI data • SBUV N-19 • MLS • Aerosols (H-C. Huang, Z. Liu (NCAR)) • Preliminary work completed – lots more to do!

Conventional observations • Improved quality control • Specification of observation error for individual stations • Bias correction • Need historical data base for all conventional obs to do above. • Many continual problems in locating stations, instrument types, and other meta data, etc. • Field experiments

Other Additional analysis variables for RTMA (Wind Gusts, PBL height, visibility, etc.) – (Pondeca, Zhu) Mesonet QC - (Levine) Additional observations in BUFR and PREPBUFR (Keyser). Data mining

Code Maintenance • Testing and evaluation of changes • Preparation for implementation • Optimization (coding, MPI, OPENMP) • Try to maintain simplicity

EMC GSI development • Relies heavily on collaborative development • Many scientific challenges in improving system • Availability of computational resources is a major problem for enhancing data assimilation system so resource neutral changes (or better) will be given priority • Code maintenance extremely important and very happy with role DTC has taken on a bridge to/from operations • Developments need to be coordinated across many projects and many groups

EMC’s Current and future GSI development