Observational Data Source Impacts In The NCEP GDAS Mr. Kevin Cooley CIO & Director Central Operations, NCEP Sponsored by JCSDA and NPOESS IPO

Introduction Contributors Organizations Dr. Stephen Lord, Director, NCEP Environmental Modeling Center Dr. Tom Zapotocny, University of Wisconsin Tom.Zapotocny@ssec.wisc.edu Dr. James Jung, Joint Center for Satellite Data Assimilation (JCSDA) Jim.Jung@noaa.gov Organizations NCEP Environmental Modeling Center Joint Center for Satellite Data Assimilation

Introduction (Cont.) Evaluation of current observing systems provides An important baseline for observing system assessment and planning Useful information for tuning and improving operational system JCSDA Preparing for future observing systems (METOP, NPP, NPOESS) Assessment of current systems observing system components (at operational resolution) Focus on satellite data Observing System Simulation Experiments (OSSEs) for advanced instruments

Introduction (Cont.) NCEP Global Forecast System (GFS) SSI version scheduled for operational implementation Includes ability to assimilation AIRS data Operational forecast model resolution T254L64 to 84 h T170L42 to 180 h T126L28 to 360 h Forecasts at 00Z only Operational data cutoffs (except for new instruments)

GFS Experimental Setup Two Time Periods 45 day runs 15 Jan 2003 – 15 Feb 2003 15 Aug 2003 – 20 Sep 2003 Control All operational observations Includes 3 AMSU configuration AQUA observations not included Data Denials All AMSU All HIRS AIRS Quikscat GOES Atmospheric Motion Vectors (AMVs) TRMM (August-Sept. 2004 only) Fields archived for further analysis

Winter Case Results Sponsored by JCSDA and NPOESS IPO

Data Assimilation Impacts in the NCEP GDAS (cont) AMSU and “All Conventional” data provide nearly the same amount of improvement to the Northern Hemisphere.

on Global Temperature Forecasts Impact of AMSU and HIRS on Global Temperature Forecasts RMS Forecast Impact

on Global Zonal Wind Forecasts Impact of AMSU and HIRS on Global Zonal Wind Forecasts RMS Forecast Impact

on Global Humidity Forecasts Impact of AMSU and HIRS on Global Humidity Forecasts RMS Forecast Impact

AMSU: 0.5 day improvement at 5 days No HIRS N. Hemisphere 500 mb ht anomaly correlation

AMSU: 0.75 day improvement at 5 days No HIRS S. Hemisphere 500 mb ht anomaly correlation

The REAL problem is Day 1 No AMSU No HIRS Tropics 850 mb Vector (F-A) RMS

The REAL problem is Day 1 No AMSU No HIRS Tropics 200 mb Vector (F-A) RMS

No Quikscat

Summer Case Results Sponsored by JCSDA and NPOESS IPO

Summer vs Winter Impact HIRS Northern Hemisphere Summer vs Winter Impact N. Hemisphere 500 mb ht anomaly correlation NH Summer N. Hemisphere 500 mb ht anomaly correlation NH Winter Larger HIRS impact In Northern Hemisphere in summer than in winter

Summer vs Winter Impact HIRS Northern Hemisphere Summer vs Winter Impact N. Hemisphere 500 mb ht anomaly correlation NH Summer N. Hemisphere 500 mb ht anomaly correlation NH Winter Larger HIRS impact In Northern Hemisphere in summer than in winter

Impact on Hurricane Track Forecasts AMSU HIRS GOES AMV Quikscat TRMM Sponsored by JCSDA and NPOESS IPO

Satellite data ~ 10-15% impact

with AMSU results at 12hours TRMM impact < 5% Inconsistent with AMSU results at 12hours Improved initial position error (1 km)

Summary AMSU impacts dominate all forecast variables Northern Hemisphere, Southern Hemisphere and tropics Up to 12 h in Northern Hemisphere at 5 days Up to 18 h in Southern Hemisphere at 5 days HIRS impacts largest in Northern Hemisphere in summer Moisture field Satellite data cannot correct rapidly growing (24 hours) model errors in tropics