13 th JCSDA Workshop Ocean Data Assimilation Development of Data Assimilation Modules for Operational Ocean and Wave Forecasting Systems at NOAA/NCEP Vladimir Osychny 1, Henrique Alves 2, Arun Chawla 3, Hae-Cheol Kim 1, Carlos Lozano 3, Avichal Mehra 3, and Hendrik Tolman 3 1 IMSG at NOAA/NCEP, 2 SRG at NOAA/NCEP, 3 NOAA/NCEP

Two Main Projects: 1. Develop a GSI-based DA interface for operational wave forecasting systems at NOAA/NCEP Main objective: To develop a GSI-based module in WAVEWATCH III for assimilation of total significant wave height (H s ) 2. Develop NCODA-based DA module for operational ocean models at NOAA/NCEP (NCODA: Navy Coupled Ocean Data Assimilation) Main objective: To develop an NCODA-based DA module for RTOFS- Global 2/24

DA interface for wave models  Project main objective: To develop a GSI-based module in WAVEWATCH III for assimilation of total significant wave height (H s )  Intermediate objective: Include wave heights into the RTMA as a part of the next RTMA update (Q4, FY 2015) RTMA: Real-Time Mesoscale Analysis Pondeca et al., 2014: The 2014/2015 projected expansion of NCEP’s RTMA and URMA. (XIX AMS conference on IOAS-AOLS) In collaboration with: Meso Branch & ObsProc Team: Jacob Carley, Geoff DiMego, Steven Levine, Manuel Pondeca and Jeff Whiting Marine Branch: Vera Gerald and Todd Spindler 3/24

What is RTMA?  operational hourly analysis of atmospheric surface data  based on GSI and an atmospheric forecast model 4/24 The four domains in which the RTMA currently runs: CONUS, Alaska, Puerto Rico (PR), and Hawaii (HI) NDFD grids. For illustrative purposes only, the figure shows the temperature (°C) valid at 1800 UTC 19 May From Pondeca et al. (WF 2011)

RTMA is a good choice as a development framework for our purposes because:  similar set up: GSI code, data flow  relatively simpler case to start with: 2DVAR, univariate  substantial existing expertise  opportunity to add a valuable (for forecasters) new analysis variable to an existing operational system (RTMA) while developing a data assimilation module for a wave model 5/24

Major building blocks:  Integrate H s data into RTMA Prepbufr ‒ made assessment of H s satellite and in situ data obtained via GTS and available in data tanks; ‒ developed a quality-control (QC) procedure for Near-Real-Time (NRT) H s data from satellites and in situ platforms (developed and tested in Matlab); ‒ tested the QC procedure for Jason-1/2, SARAL/Altika, CryoSat-2 as well as in situ data ‒ started to prepare procedures that facilitate data transfer from data tanks into RTMA (ready for in situ data; to be completed for satellite data)  RTMA work ‒ added H s as a new variable to GSI code; ‒ prepared input parameters/fields for a single observation test; ‒ ran the test 6/24

Components of the QC procedure: 1. Valid range test 2. Proximity to land test: ETOPO-1 (used in WAVEWATCH) 3. Proximity to ice test: NCEP operational ice coverage (5’ grid) 4. Statistical outliers (de-spiking) based on iterative procedure: A low-pass signal is obtained by using an order-statistic filter: ‒ Approx. 10 sec. (~60 km, ~11 points; 5 minimum) data window ‒ Mean is calculated for values between 20 th and 80 th percentile Estimate STD based on the high-pass residue for the same data window and the same data selection Flag outliers (> 3STD) Additional constraints at each iteration: ‒ test differences between neighboring data values for original data and for high-pass portion ‒ lower limit on RMS 7/24

Jason-2, SARAL/AltiKa and CryoSat-2 data locations September 5, /24 Jason-2 SARAL/AltiKa CryoSat-2

H s data from Jason-2 (and SARAL/AltiKa) are much “cleaner” than those from Jason-1 Jason-1 data: Dec. 6, /24

H s data from Jason-2 (and SARAL/AltiKa) are much “cleaner” than those from Jason-1 Jason-2 data: June 20, /24

H s data from CryoSat-2 are “cleaner” than those from Jason-1, but have “pockets” of noisy data CryoSat-2 data: Jan. 10, /24

Work with GSI (RTMA) code  added H s as a new variable to GSI code  created land-sea mask  set preliminary characteristics for background and observation errors  generated model background fields for a test run  made a test run - single observation (Jacob Carley) 12/24

RTMA single observation test for H s background incrementsanalysis 13/24

Future work:  Work on data flow and QC procedure ‒ Complete transferring of the QC procedure from Matlab to FORTRAN ‒ Integrate satellite H s data into RTMA data stream (in situ data already integrated)  RTMA (GSI) work ‒ prepare input parameters/fields for RTMA tests with realistic data loads (satellite and in situ data) ‒ run RTMA tests with realistic data loads ‒ include H s into operational RTMA update ‒ transition from RTMA to a DA module for a global wave forecast system 14/24

NCODA-based DA module for operational ocean models at NOAA/NCEP  Background: Part of NAVY/NOAA Memorandum of Agreement on implementing NCODA at NCEP operations.*  Project main objective: Port NCODA to WCOSS at NCEP to be used for DA purposes with RTOFS-Global *The agreement is specific to the operational RTOFS system. Further joint research and development are expected to be part of a future agreement. 15/24

Subtasks:  General understanding of NCODA  Understand structure of the code: from very basic to in-depth  Inventory of input parameters  Inventory of input/output data sets (observations, background fields, topography, model output, etc.) that are used in NCODA ─ mandatory and optional data sets in terms of running the code; ─ mapping between NAVY and NOAA data sets:  mapping of RTOFS fields to NCODA formats  assembling and formatting data from NCEP data tanks into NCODA- required form  identifying data sets that are available only to NAVY and finding and mapping proper replacement sets  Understand how data flow through both DA and QC modules as well as between the modules  Make it work: compile and run the system  Understand output 16/24

Preliminary work:  Basic description of NCODA: papers published in scientific literature  Obtained NCODA code from NAVY: ‒ Consists of two stand-alone modules: 1) variational (DA) module; 2) QC module; ‒ Test (toy) projects for the variational module; nothing similar for the QC part  Successfully compiled and run the test projects 17/24

18/24 1)noaa 2)metop 3)metop_lac 4)coms 5)goes 6)ist 7)amsr 8)windsat 9)atsr 10)ship 11)noaa_lac 12)viirs 13)msg 14)mtsat 15)trak 16)altim 17)prof 18)gldr 19)swh 20)amsr_ice 21)ssmi 22)vel 23)sss SST/IR, NOAA Global Area Coverage (GAC) SST/IR, MetOp GAC SST/IR, MetOp Local Area Coverage (LAC) SST/IR, (Comm., Ocean & Met. Satellite; Korea) SST/IR, GOES IST (ice surf temp; MODIS, MetOp, VIIRS) SST/microwave (Aqua, TRMM) SST/microwave (WindSat) SST/IR (ERS, EnviSat) SST (in situ: ship, buoy obs) SST/IR, NOAA LAC SST/IR (Suomi-NPP) SST/IR (MeteoSat 2 nd Generation) SST/IR (MTSAT, Japan) SST/SSS (in situ: track obs) SSH ( altimeters: GFO,TOPEX, Jason, EnviSat,CryoSat, AltiKa ) T,S-profiles (in situ: Argo, BT, etc.) T,S profiles (in situ: gliders) H s (altimeters & in situ) Sea Ice Concentration (Aqua, DMSP) Sea Ice Concentration (DMSP) Current velocity (drifters, ADCP, radars) SSS (Aquarius, SMOS) NCODA data types: model variables, measured parameters, sensors, obs. platforms NCODA

NCODA results for the provided SST tests (bathymetry) 19/24

NCODA results for two provided SST test (SST) NCODA results for the provided SST tests (SST background) 20/24

NCODA results for the provided SST tests (SST analysis increment) 21/24

Basic approach: Try to compile the code: ‒ address the resulting warnings/error messages; ‒ targeted work with the code Study the code (line by line) Communicate with the NAVY to try to resolve the found issues 22/24

Completed work:  Successfully compiled and run all the test examples provided by the NAVY for the variational part of the code  Identified NCODA routines that facilitate obtaining data from a GODAE ftp server and successfully run them as a stand-alone procedure  Identified a need to develop a script facilitating mapping of RTOFS (HYCOM) fields to NCODA grid  Started to prepare work-flow descriptions of the code and its major modules:  sequence of main steps  code components  input parameters  involved data sets  potential improvements  Communicated the found issues and our requests to the NAVY 23/24

Future work  Try to obtain from the NAVY a few working examples for the QC part of the NCODA code  Compile and run the QC part of the code  Evaluate performance of the NCODA QC procedures  Compile and run the variational part of the code  Resolve the issue with the script facilitating mapping of RTOFS (HYCOM) fields to NCODA grid as well as other (?) decoding/transfer scripts  Continue working on work-flow descriptions of the code and of its major modules 24/24