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FY14 JCSDA AMV PROJECTCOPC Action Item 2013-1.8: Coordinate an update to be briefed to the next

COPC by the JCSDA describing collaborative efforts to improve the exploitation of atmospheric motion vectors (AMVs).

Update #1: Goal is to optimize the forecast impact from AMVs in the NOAA global forecast system,

leveraging past experiments performed by NRL and GMAO exploring the differential impact of these data.

JCSDA will lead coordination of partner contributions to test advanced processing of AMVs. Partners include NCEP and NESDIS and, likely, NASA/GMAO, NRL/MMD, and U. Wisc/CIMMS. Preliminary discussions have been initiated with NASA and Navy. Tentative plans include:

• GMAO will contribute to the design and evaluation of data impact experiments for measuring effectiveness of new techniques;

• NRL/MMD will contribute techniques for processing, screening, superobing/thinning, and assimilating AMV data, with assistance from U. of Wisc/CIMMS;

• NESDIS will ensure operational availability of upgraded AMV data products using imagery from both polar orbiting and geostationary platforms;

• NCEP/EMC will be responsible for improving assimilation techniques for the AMVs and final testing and maintenance of code upgrades in the NCEP GDAS.

JCSDA will provide supercomputer resources for development and testing of NOAA systems.

CSAB recommends keeping this action opened.1

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Operational monitoring reveals much larger relative impact of AMVs in Navy system.

FNMOC and GMAO Observation Impact Monitoring Operational Data from Spring 2012

http://gmao.gsfc.nasa.gov/products/forecasts/systems/fp/obs_impact/http://www.nrlmry.navy.mil/metoc/ar_monitor/

NRL NAVDAS-AR (4D-Var) Total Observation Sensitivity

24 Hr Fcst Error Norm Reduction (J/kg)

Cloud_WindRadiosonde

LandSfcIASI

SSMIS TPW AMSU-A SSMIS

AMDARAQUA

MHS MDCRSMODIS Wind

ShipSfc GPS

PIBAL LEO GEO Wind

ASCAT Sfc Wind SSMIS Sfc Wind

WindSAT-TPW AVHRR WindWindSAT Sfc Wind

AIREPTC Synthetic

DropsondeAMSU-B

Aus_SyntheticMIL ACARR/S_Wind

WindSAT-PRHSCAT Sfc Wind

SSMI-PRH

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

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Why does FNMOC get such large impact from satellite winds?

• Use of more satellite winds from more sources, some hourly?• More effective treatment of satellite winds …superobing vs.

thinning?• Assimilation of fewer satellite radiances?

FNMOC assimilates far more WV winds, and Vis, IR and WV winds from additional sources…most notably U.Wisc/CIMSS…also AFWA

FNMOC GMAO

Observation Count Observation Count

65-80K obs/anal160-200K obs/anal

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

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A simple joint experiment:Assimilate Navy-prepared satellite winds in the GMAO global forecast system…

NRL SatWinds have roughly double the total impact of GMAO SatWinds.

GMAO Control With NRLAMV

Fractional Impact (%) Fractional Impact (%)

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

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NRL NHEM SUPEROB Horz. Prism Distribution

1. Process AMVs to generate 1 superob per prism 2. Replace each superob by the unrejected ob

closest in space to the superob --- selected from the obs used to form the superob

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

An NRL experiment:Compare NRL superob technique to a thinning approach

prism

Superob

Unrejected Observations

Thinned Ob Replacement

METHOD changes VALUE

• Comparable in terms of 500 mb AC, with superobing having a slight advantage at longer forecast ranges in the Southern Hemisphere.

• Improvement in 200mb wind speed with superobing except in the tropics, where thinning is slightly better.

• Improvement in 850mb wind speed in NHEM with superobing, but thinning slightly better in tropics and SHEM.

NRL experiment produced mixed results, depending on metric and area selected. Overall edge to superobing.

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Satwind AMSU-A Hyps IR All Obs

GMAO 90 520 1220 2500FNMOC 350 350 800 2200

Observation Counts per 6 hr (in thousands)

Notable observing system differences:

Approximate average values for the year ending 15 May 2012

GMAO assimilated far more radiance observations than FNMOC.

Observation mix plays a significant role in modulating the impact of any one data type: the smaller impact of the NRL AMVs in the GMAO system (compared with their impact in the NRL system) is likely due to the larger number of satellite radiances in the GMAO system.

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

• Relative impacts of most AMV types (right) correlate well with data counts (left).

• Beneficial impact of MODIS winds in NRLAMV (versus non-beneficial impact in CONTROL, right) requires other explanation….superobs? More research needed

Global Data Count Total Impact by Data Type

WINDSAT

MODIS IR

MODIS WV

METEOSAT WV

METEOSAT IR/Vis

LeoGeo

JMA WV

JMA IR/Vis

GOES WV

GOES IR

ASCAT

WINDSAT

MODIS IR

MODIS WV

METEOSAT WV

METEOSAT IR/Vis

LeoGeo

JMA WV

JMA IR/Vis

GOES WV

GOES IR

ASCAT

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

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FY14 JCSDA AMV PROJECT

• Compared with the control run with GMAO (NCEP) AMVs, the assimilation of NRL AMVs in the earlier project provided substantially increased beneficial impact, and also appeared to improve forecast skill overall.

• The FY14 JCSDA project will be a follow-on multiagency effort to see if leveraging the NRL and GMAO techniques can improve the utilization of the AMV data in the NCEP system. Improved AMV assimilation important for JPSS Data Gap Mitigation.

• NRL has an in-house project to further investigate and improve assimilation of AMV data, so some collaboration ongoing between NRL, U. Wisc./CIMMS, and GMAO.

• Official JCSDA project will begin once a project plan is developed, SOWs are agreed upon, and “Sandy supplement” funds are distributed to the non-NOAA partners.

• Joint investigation of AMV data assimilation should benefit all JCSDA partners through “lessons learned” using different systems to explore optimum methods for data processing, quality control, scaling/selection, and assimilation of these data.

Aug 15th, 12 UTC through Sept. 30th, 2010, @12 UTCTotal Reduction in the Moist Error Norm

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

When AMV winds are removed from the analysis altogether, the positive impact of the MW and IR satellite sounders does increase significantly. Does NRL have the optimum mix?

AMV wind CONTROL

~17%

~8%

~11%

~48%

~60%

NAVDAS-AR

EXPERIMENT

AMV wind DENIAL

~88%

~61%

~29%

~11%

~17%

Summary of Total Observation Impact – Tropics

Control NRLAMV

• Contributions from CIMSS and non-CIMSS winds (right) are comparable to each other, and to that from GMAO control winds (left).

• Not a data quality difference driving impact volume of AMVs in NRLAMV

10 Dec 2010 – 31 Jan 2011 00z

EARLIER NRL/GMAO AMV STUDIESResults courtesy of Ron Gelaro, GMAO, Nancy Baker and Pat Pauley, NRL

GEOS-5

EXPERIMENT