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

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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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