Impact of the NAME04 Soundings on the NCEP data assimilation systems
Water Vapor Radiance Assimilation in the NCEP Global Data Assimilation System
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Transcript of Water Vapor Radiance Assimilation in the NCEP Global Data Assimilation System
Water Vapor Radiance Assimilation in the NCEP Global Data
Assimilation System
James JungCooperative Institute for Meteorological Satellite Studies
In collaboration with
NCEP/EMC, NASA/GMAO, NESDIS/STAR, NESDIS/JPSS, CAWCR, etc.
12th Annual JCSDA Review
Outline
• Recent Projects Supersaturation removal Using q instead of RH for background error Addition to Baseline Observing System Experiments
• Current Work 2014 Global Data Assimilation System transition
• Future Projects Water Vapor Radiance Assimilation Addition to Baseline Observing System Experiments
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Water Vapor Assimilation
12th Annual JCSDA Review
Background
• May 2012 version of the GDAS/GFS Hybrid (80 ensembles, T254) T574, NCEP operational resolution
• Summer and winter seasons• No changes to observations
Counts / fits differences due to atmosphere changes
• Forecast scores verified against own analysis
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12th Annual JCSDA Review
BackgroundSupersaturation removal
• NCEP Ticket #346 Supersaturation removal experiments
• Subversion branch r29873 with updates
• T574 hybrid (~May 2012 version ported to JIBB)
• No changes to observations
• Perturbations derived from the ensembles used RH
• Namelist variable added (clip_supersaturation=.true.)
• Factqmax=50.0 (penalize minimization for generating supersaturation)
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12th Annual JCSDA Review
Backgroundrelative humidity vs specific humidity
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• NCEP ticket #338 Use q instead of RH perturbations for the moisture component in the ensembles.
• Includes the changes from the supersaturation removal experiment.
• RH background error derived from ensemble specific humidityF RH perturbations are computed from q only (Removes
ΔT)
F From Daryl Kleist
F Namelist variable (q_hyb_ens=.true.)
12th Annual JCSDA Review
Supersaturation counts before each outer loop from the control
SUPERSAT RH COUNT,RMS= 770051 0.118376SUPERSAT RH COUNT,RMS= 1494196 0.103566SUPERSAT RH COUNT,RMS= 1585750 0.101427
Supersaturation counts before each outer loop from the experiment
SUPERSAT RH COUNT,RMS= 0 0.00000SUPERSAT RH COUNT,RMS= 235489 0.266668E-01SUPERSAT RH COUNT,RMS= 160906 0.716671E-02
Supersaturation counts accumulate with each outer loop in the control. Counts and RMS are an order of magnitude higher in the control
Effect on supersaturation counts
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Latitude – Height Analysis DifferencesRelative Humidity
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About equally less relative humidity in both experiments
20120801 - 20120915 20130101 - 20130215
12th Annual JCSDA Review
Latitude – Height Analysis DifferencesCloud Water
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About equally less cloud water in both experiments
20120801 - 20120915 20130101 - 20130215
12th Annual JCSDA Review
Latitude – Height Analysis DifferencesGeopotential Height
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Lower heights in the enkf_q experiment
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Latitude – Height Analysis DifferencesTemperature
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Significantly colder over both poles
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Analysis DifferencesNear Surface Temperature
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Significantly colder over both poles
20120801 - 20120915 20130101 - 20130215
12th Annual JCSDA ReviewCourtesy A. Collard
North Pole Rawinsonde Comparisons
Black = control, green = experiment
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South Pole Rawinsonde Comparisons
Courtesy A. CollardBlack = control, green = experiment
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12th Annual JCSDA Review
Analysis troposphere fit to rawinsondes
Experiment is generally cooler
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Control: solidExperiment: dash
Analysis: black6-hr guess: red
12th Annual JCSDA Review
Analysis troposphere fit to rawinsondes
Experiment generally drier
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Control: solidExperiment: dash
Analysis: black6-hr guess: red
12th Annual JCSDA Review
12 & 36 hr forecast fit to rawinsondes
Experiment remains cooler in troposphere but drifting back to control
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Control: solidExperiment: dash
12-hr: black36-hr: red
12th Annual JCSDA Review
12 & 36 hr forecast fit to rawinsondes
Experiment remains drier
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Control: solidExperiment: dash
12-hr: black36-hr: red
12th Annual JCSDA Review
Anomaly Correlations500 hPa Northern Hemisphere
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20120801 - 20120915 20130101 - 20130215
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Anomaly Correlations500 hPa Southern Hemisphere
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20120801 - 20120915 20130101 - 20130215
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Tropical Wind Vector RMSE
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Summary
• Reduce supersaturation counts and RMS (wrt RH) by an order of magnitude
• Troposphere - drier / stratosphere – wetter
• Troposphere cooler, less drift in stratosphere temperature
• Less clouds at upper levels
• Convergence and penalty marginally worse (factqmax)
• Benchmarks / scores are mixed to postitive. ENKF_Q better than SUPERSAT.
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Addition to baseline Observing System
Experiments
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12th Annual JCSDA Review
Background
• May 2012 version of the GDAS/GFS Hybrid (80 ensembles, T254) T574, NCEP operational resolution
• Summer and winter seasons
• Baseline is conventional data and GPS-RO
• Add single instruments ATMS (SNPP) AMSUA, MHS (NOAA-19) AIRS (Aqua)
• Verified against a control analysis with all operational data (including NOAA-19, SNPP, and Aqua)
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Latitude – HeightAnalysis Differences
All_Data SNPP-ATMS – All_Data
Aqua-AIRS – All_Data N19-AMSU/MHS – All_Data
Base – All_Data
Relative Humidity
00Z20120801 - 20120920
12th Annual JCSDA Review
Latitude – HeightAnalysis Differences
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All_Data SNPP-ATMS – All_Data
Aqua-AIRS – All_Data N19-AMSU/MHS – All_Data
Base – All_Data
Cloud Water
00Z20120801 - 20120920
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Latitude – HeightAnalysis Differences
All_Data SNPP-ATMS – All_Data
Aqua-AIRS – All_Data N19-AMSU/MHS – All_Data
Base – All_Data
Temperature
00Z20120801 - 20120920
12th Annual JCSDA Review
500 hPa AC scores for 00Z 20120801-20120930
Base SNPP-ATMSAll_Data Aqua-AIRSN19-AMSU/MHS
Base SNPP-ATMSAll_Data Aqua-AIRSN19-AMSU/MHS
Northern Hemisphere Southern Hemisphere
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12th Annual JCSDA Review
1000 hPa AC scores for 00Z 20120801 – 20120930
Base SNPP-ATMSAll_Data Aqua-AIRSN19-AMSU/MHS
Base SNPP-ATMSAll_Data Aqua-AIRSN19-AMSU/MHS
Northern Hemisphere Southern Hemisphere
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12th Annual JCSDA Review
Tropical Vector Wind RMSE for 00Z 20120801 - 20120930
Base SNPP-ATMSAll_Data Aqua-AIRSN19-AMSU/MHS
Base SNPP-ATMSAll_Data Aqua-AIRSN19-AMSU/MHS
200 hPa 850 hPa
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Hurricane Statistics20120801 - 20120915
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Summary(WRT the control)
• Increased cloud water in the tropics. Baseline has the most clouds
• Higher geopotential heights at upper levels. Baseline and SNPP-ATMS are the highest
• Greater RH in Southern Hemisphere upper troposphere Except for Aqua-AIRS
• Anomaly correlation scores: SNPP-ATMS and Aqua-AIRS are generally equal N19-AMSU/MHS is slightly lower
• Tropical wind vector RMSE: Aqua-AIRS is best (first 24 hours) Baseline worst throughout
• Aqua-AIRS generally best hurricane stats
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12th Annual JCSDA Review
Future Projects
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12th Annual JCSDA Review
Water Vapor Radiance Assimilation • Build from previous work. Control will including these namelist
changes: clip_supersaturation=.true. factqmax=50.0 q_hyb_ens=.true.
• Due to all of the recent changes in both the analysis and forecast model, a review of the QC procedures for MW and IR water vapor channels currently used by GDAS is in order. Adjust gross error check Adjust assimilation weights
• Review water vapor channel selection for AIRS, IASI, and CrIS. Remove AIRS stratospheric channels ( ~11) Add tropospheric channels for IASI and CrIS.
• Two season impact tests. Operations resolution (T1534?)
• Wiki page for progress updates. Ticket #394 Branch jung_wv_chans
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Observing System ExperimentsData Additions
• Control Lower resolution semi-Lagrangian (T670?) All available data
• Baseline Conventional data only (unless unstable)
• Experiments AIRS IASI CrIS
• If time permits ATMS SSMIS
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