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NRL Overview and Plans
Presented by Dr. Nancy Baker
with contributions by NRL Scientists from the Marine Meteorology, Remote Sensing, Space
Sciences and Oceanography Divisions
13th JCSDA Technical Review Meeting & Science Workshop on Satellite Data Assimilation May 13-15, 2015
NOAA Center for Weather and Climate Prediction (NCWCP), College Park, MD
Six Divisions performing scientific and technological innovation, research and development from the bottom of the sea floor to the top of the atmosphere and into space.
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Flat Surface with Bubbles
Marine Geosciences (MS, 7400)
Acoustics (DC & MS, 7100)
Oceanography (MS, 7300)
Marine Meteorology (CA, 7500)
Remote Sensing (DC, 7200)
Space Sciences (DC, 7600)
Ocean and Atmospheric Science and Technology Directorate (7000)
This Directorate was formed in 1992, when meteorology and oceanography were integrated into NRL with the merger of smaller labs in CA and MS with NRL DC.
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Presentations by NRL Scientists at this workshop
Overview of JCSDA Activities and Plans• Nancy Baker (NRL MRY) “NRL Overview and Plans”Ocean Data Assimilation• Hans Ngodock (NRL SSC) “Assimilation of SSH Altimeter Observations into an
operational 4dvar system”• Matt Carrier (NRL SSC) “Operational Implementation of Altimeter Data Assimilation
using the Navy Coastal Ocean Model 4D-Var”Assimilation of New Sensor Data• Tanya Maurer (NRL MRY) “DMSP F19 SSMIS NAVGEM Assimilation Results and
Cal/Val Progress”Air Composition/Aerosols• Ed Hyer (NRL MRY) “Advances in data and methods for aerosol data assimilation in
the Navy Aerosol Analysis and Prediction System”Improving Atmospheric Data Assimilation• Bill Campbell (NRL MRY) “Accounting for Correlated Satellite Observation Error in
NAVGEM”• Ben Ruston (NRL MRY) “Updates to SNPP Use in Navy NWP”
** Also in attendance Melinda Peng (NRL MRY) and Dave Kuhl (NRL DC)
NAVGEM 1.2.1
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NAVGEM 1.2.1 Operational 08 Jul 2014 at FNMOC
• Added/refined assimilation of …IASI water vapor radiances*Suomi-NPP OMPS, and NOAA SBUV/2 Ozone ProfilesIASI from MetOp-BDMSP-F19 SSMIS capability (radiances and wind/TPW retrievals)
• Revised QC/code stabilityLunar intrusion flag for ATMSGPS-RO tropospheric error updateAdditional QC check for GNSS (background pseudo-RH sanity check)
• Additional diagnosticsVerification against ECMWFFull column error norm for ob impact (except top two levels)
Ben Ruston, Pat Pauley, Nancy Baker, Tanya Maurer, Steve Swadley, Rolf Langland, Dave Kuhl, Liz Satterfield
NAVGEM v1.3
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NAVGEM 1.3 Operational May 2015 at FNMOC
Data Assimilation• SSMIS Upper Atmosphere Sounding (UAS) assimilation (ch. 21)• GPS-RO addition of GRACE-B and TanDEM-X • SNPP VIIRS Atmospheric Motion Vectors
Forecast Model
• T425L60 resolution (31km, top at 0.04 hPa or ~70km) Reduced Gaussian grids
• New stratospheric physics for water vapor photo chemistry, sub-grid-scale non-orographic gravity wave drag, and stratospheric humidity quality control
• New dynamics formulation utilizing perturbation virtual potential temperature to improve numerical stability and reduce semi-implicit decentering
• Convective cloud fraction predicted based on Xu-Randall
• Improved initialization of ground wetness and ground temperature• LIS soil moisture initialization• New snow albedo• WAVEWATCH® III v4.18
Karl Hoppel, Ben Ruston, Nancy Baker, Tanya Maurer, Steve Swadley
High cloud cover: DJF 2013/2014
NAVGEM v1.2.1
ERA-interim analysis
Mean = 20.1%
Mean = 31.7 %
Mean = 37.5 %
NAVGEM v1.3
• The high cloud cover shows perhaps the most notable improvement, particularly in tropical convective regions.
• Significant improvement in the surface solar radiation budget.
Improved Cloud FractionsXu-Randall
Distribution S
tatement A
:A
pproved for Public R
elease
NAVGEM v1.3.1
NAVGEM 1.3.1 September, 2015 at FNMOC
• SNPP CrIS temperature and water vapor radiances• AQUA AIRS water vapor radiances• Geostationary Clear Sky Radiance • Terra MISR Cloud Motion Vectors• MetOp A/B Global AVHRR AMVs
• Stratospheric humidity scaling - paves way for Hölm transform
• TAC => BUFR transition for radisosonde and surface obs
• Revised external digital filter
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Ben Ruston, Pat Pauley, Nancy Baker, Karl Hoppel, Rebecca Stone, Liang Xu
Geostationary Clear Sky Radiance Assimilation
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COMS-1 GOES13 GOES15 MSG-10 MTP-07
Capability brings in 6 sensors MTSAT-2 not shown
Error reduction smaller than traditional sounders
Large bias (2-5°C) Good constraint Tracks NWP improvements
Ben Ruston, Michelle Dai
Plans for 2016
Hybrid 4DVar (NAVGEM v1.4)• New NAVGEM TLM and Adjoint model• Activate Ozone assimilation along with Mesospheric Ozone photochemistry• Redefine humidity analysis variable (Hölm transform)• Revised observation and background error covariances• Activate anchor channel capability for radiances• COMS-1 AMVs• Correlated observation error for ATMS and IASI (and more …)
COAMPS® Mesoscale 4DVar• UAS (Unmanned Aircraft Systems) data assimilation to support experiments• Includes radiance and GNSS-RO assimilation
Data pre-processing and QC• Modernize code – e.g Complex Quality Control (CQC) for radiosondes (NGGPS)• Complete TAC BUFR transition for RAOB, SYNOP
Ben Ruston, Dave Kuhl, Pat Pauley, Nancy Baker, Karl Hoppel, Rebecca Stone, Liang Xu, Liz Satterfield
P0 _Hybridb (1 )P0 _CONV
b P0 _ENSb
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Middle Atmosphere Assimilation
NAVGEM Stratosphere-Mesosphere Development
Changes to the forecast model for assimilation of upper level radiances
o Extension of the model vertical domain up to L74 to 6x10-5 hPa (~116 km)
o New stratospheric-mesospheric ozone photochemistry with diurnal variability in the upper stratosphere and mesosphere
o New parameterized stratospheric-mesospheric water vapor photochemistry and quality control
o New stochastic gravity-wave drag parameterization
Important: Reduce upper-level temperature biases (i.e., improve modeled “climate”)
POC: John McCormack (NRL DC)
KEXP10 - KEXP8
Negative (colder)More water, more IR cooling
Positive (warmer)Less water, less IR cooling
Parameterized H2O Photochemistry: Reducing Forecast Temperature Bias
288-Hour Forecast Temperature Difference: (H2O chem) – (no H2O chem)
John McCormack, Ben Ruston, Steve Eckermann
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8.7 hPa 0.91 hPa 0.096 hPa 0.042 hPa 0.010 hPa 0.0033 hPa
Parameterized Ozone Photochemistry
• NAVGEM currently uses a linearized ozone photochemistry parameterization based on diurnally averaged odd-oxygen (O3+O) production and loss rates in the stratosphere. It does not account for diurnal cycle in ozone present above 1 hPa.
• A new generalized ozone photochemistry parameterization has been developed for NAVGEM, which will allow SNPP OMPS assimilation to be activated.
POC: Steve Eckermann (NRL DC)
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• Extension of NAVGEM model vertical domain past 100 km (left, blue curve) fully resolves atmospheric region sampled by SSMIS UAS channels on operational DMSP platforms (right).
• UAS assimilation needs Community Radiative Transfer Model (CRTM) containing Zeeman Splitting corrections (Han et al. 2010)
Extending Model Top Past 100 km
Zeeman splitting
John McCormack, Steve Swadley, Ben Ruston, Karl Hoppel, Dave Kuhl
15
Looking Ahead
• NAVGEM 2.0; T681L80 19km,0.01hPa~80km) – Upgrade of cloud water/ice prediction– New land surface model – High-order PBL scheme– Coupled CICE (sea-ice) model– Coupled to HYCOM (ocean) model– Coupled to WAVEWATCH® ocean wave model– 4 aerosol constituents prediction Model updates pave the way for coupled assimilation, cloud and
precipitation affected radiance assimilation and 4DVar aerosol assimilation
• Mesoscale 4DVar with radiance and GNSS-RO assimilation
Global Hybrid 4DVar
16Dave Kuhl, Nancy Baker, Craig Bishop, Liz Satterfield, Dan Hodyss, Ben Ruston
“Scorecard” using ECMWFComparison of Hybrid 4DVar vs. 4DVar
Total Score=+9
P0 _Hybridb (1 )P0 _CONV
b P0 _ENSb
COAMPS 4DVarSample Model Domains
COAMPS 4DVar has been tested over many regions with multiple nests, different map projections, and vertical levels. Wallclock ~15m for 45x45 km grid (121x91x30)
Much easier to assimilate radiances and GNSS-RO
CICECICE
NCODA Current Applications
NCODA Current Applications
Ob-Space NCODA 3D-Var
Ob-Space NCODA 3D-Var
NAVGEMNAVGEM
COAMPS®COAMPS®EFSEFSCOAMPS-OS®COAMPS-OS®
COAMPS®-TCCOAMPS®-TC
Coupled COAMPS
Ens.
Coupled COAMPS
Ens.
NAAPSNAAPS
WW3WW3WW3
Ensemble
WW3
Ensemble
NCOMNCOM
HYCOMHYCOM
Aerosol Data Correction
Ocean, Wave, Ice Model Initialization
Ocean, Wave, Ice Model Initialization
Atmospheric Model BC
NCEP, NASA IN
TEREST
NCEP, NASA IN
TEREST
Currnet Funding for Development of Coupled 4DVAR/ Ensemble Hybrid
DA System based on NAVDAS-AR
Currnet Funding for Development of Coupled 4DVAR/ Ensemble Hybrid
DA System based on NAVDAS-AR Advanced
4DDA R&D
Advanced 4DDA R&D
Ensemble Transform
3DVAR – simultaneous analysis of 5 ocean variables: temperature, salinity, geopotential, u,v velocity components
Ocean/Wave Model
Ocean Data QC
3DVAR
Raw Obs
SST:NOAA (GAC, LAC), METOP (GAC, LAC), GOES, MSG, MTSAT-2, AATSR, VIIRS, (AMSR-2) Ship/Buoy in situ Profile Temp/Salt: XBT, CTD, Argo Floats, Fixed/Drifting Buoy, Ocean GlidersAltimeter SSH: Jason, Altika, CryosatSea Ice: SSMIS, (AMSR-2)Velocity: (HF Radar, ADCP, Argo Trajectories, Surface Drifters, Gliders)
Innovations
Increments
Forecast Fields Prediction Errors First Guess
Adaptive Sampling Observation Impact
Sensors NCODA: QC + 3DVAR HYCOM, NCOM, WW3
Navy Coupled Ocean Data Assimilation
Automated QC w/condition flags
NCODA Data Flow
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