Observing System Experiments Using the NCEP Global Data Assimilation System

Observing System Experiments Using the

NCEP Global Data Assimilation System

James JungCooperative Institute for Meteorological Satellite Studies

Lars Peter RiishojgaardUniversity of Maryland, Baltimore County

Overview

• Background / Experiments

• Anomaly Correlations

• Tropical Wind Vector RMSE

• Summary

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Background

• NCEP Operational GDAS/GFS May 2011 version (non-hybrid)

• T574L64 operational resolution

• Two Seasons 15 Aug – 30 Sept 2010 15 Dec 2010 – 31 Jan 2011

• Cycled experiments

• 7 Day forecast at 00Z

• Control late analysis (GDAS) used for verification

• Not NCEP operations computer

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Experiments

• No Satellite data AMSU-A, MHS, AMVs, GPS-RO, Hyperspectral,

GOES Sounder, HIRS, Scatterometer (WindSat)

• No Conventional data Rawinsondes, Aircraft, Ship/Buoy, Profilers, VAD

winds

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ExperimentsSatellite Instruments

• No AMSU-A NOAA-15, NOAA-18, NOAA-19, MetOp-A, Aqua

• No MHS NOAA-18, NOAA-19, MetOp-A

• No Atmospheric Motion Vectors (AMV) MTSAT, Meteosat-7, Meteosat-9, GOES-E, GOES-W, MODIS

• No GPS-RO (11) CNOFS, COSMIC, GRACE, MetOp-A, SACC, TerraSAR-X

• No Hyperspectral AIRS, IASI

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ExperimentsConventional Instruments

• No Rawinsondes (T, Q, UV) Rawinsondes, Dropsondes, PIBALs

• No Aircraft data AIREP, ASDAR, AIRCAR

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Anomaly Correlations

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500 hPa Anomaly Correlations15 Aug – 30 Sep 2010

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No Satellite / No Conventional Data

Northern Hemisphere Southern Hemisphere

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500 hPa Anomaly Correlations 15 Aug – 30 Sep 2010

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No AMSU-A / No MHS

Northern Hemisphere Southern Hemisphere

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500 hPa Anomaly Correlations 15 Aug – 30 Sep 2010

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No GPS-RO / No AMV

Northern Hemisphere Southern Hemisphere

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500 hPa Anomaly Correlations 15 Aug – 30 Sep 2010

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No Rawinsondes / No Aircraft

Northern Hemisphere Southern Hemisphere

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500 hPa Anomaly Correlations 15 Aug – 30 Sep 2010

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No Hyperspectral Infrared

Northern Hemisphere Southern Hemisphere

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500 hPa, Day 5, Average AC scores

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1000 hPa, Day 5, Average AC scores

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Anomaly Correlation Conclusions

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• No satellite and no conventional data experiments are similar to previous studies. No Satellite has greatest impact, especially in Southern Hemisphere.

• Single instrument scores are much smaller than entire suite denial.

• Few instruments have statistically significant impact at day 5. Rawinsonde, Aircraft (Aug-NH) Rawinsonde, GPS-RO (Aug-SH) Rawinsonde, AMSU-A (Dec-NH) AMSU-A, GPS-RO (Dec-SH)

500 hPa

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Anomaly Correlation Conclusions

• In general, similar (but less) impact as at 500 hPa

• Single instrument scores are much smaller than entire suite denial.

• Less sensors have statistically significant impact at day 5. Rawinsonde (Aug-NH) Rawinsonde (Dec-NH) Rawinsonde, AMSU-A (Dec-SH)

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1000 hPa

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Tropical Vector Wind RMSE

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No Satellite / No Conventional Data15 Aug – 30 Sep 2010

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RED => RMS (exp) > RMS(control)

GREEN => RMS(exp) < RMS(control)

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No AMSU-A / No MHS 15 Aug -30 Sep 2010

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RED => RMS (exp) > RMS(control)

GREEN => RMS(exp) < RMS(control)

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No GPS-RO / No AMV 15 Aug -30 Sep 2010

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RED => RMS (exp) > RMS(control)

GREEN => RMS(exp) < RMS(control)

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No Rawinsondes / No Aircraft 15 Aug -30 Sep 2010

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RED => RMS (exp) > RMS(control)

GREEN => RMS(exp) < RMS(control)

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No Hyperspectral Infrared 15 Aug -30 Sep 2010

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RED => RMS (exp) > RMS(control)

GREEN => RMS(exp) < RMS(control)

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Tropical Wind Statistics Conclusions

• RED implies data has positive effect on tropical winds

• All data types have a positive impact on Vector Wind Statistics in the Tropics

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Summary

• NCEP operations version of the GDAS (May 2011) at the operational resolution (T574L64) was used

• Two season cycled experiment Aug – Sep 2010 Dec 2010 – Jan 2011

• No Satellite / No Conventional data statistics similar to previous studies.

• Impact from individual sensors is less than expected Few individual sensors make statistically significant changes to the

anomaly correlation scores.

• All instrument types have a positive impact on tropical winds AMSU, MHS, AMVs, GPS-RO, Aircraft, Rawinsondes

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