Planned Simulations for New Nature Run G. D. Emmitt, S. Greco, S. A. Wood and C. O’Handley Simpson Weather Associates OSEE meeting November 16, 2006

Objectives Evaluate and adjust (if necessary) Nature Run clouds Apply subgrid scale wind variance algorithm Simulate ACARS and AMDAR wind observations Simulate CMVs; WVMW(?) Simulate MODIS winds Simulate DWL (ISAL concept) winds.

Issues Measurement errors Correlated (systematic) errors Representativeness Cloud effects –All other instruments simulated should use same clouds; satellite perspective algorithm –Cloud “porosity” for lidars should be approximated using results of analyses of GLAS and CALIPSO data

CMVs Competition for DWL upper troposphere wind detection (DD) Use same technique as that used on T213 Provide both CMVs with and without height assignment errors –Height assignments could be improved using space-based lidar altimetry

ACARS and AMDAR Competition for Upper Tropospheric DWL measurements (DD) Use a weekly set of flight paths to simulate ACARS (US) and AMDAR (EU) observations –Simulating likely route adjustments based upon Nature Run weather of the day is too complicated for now.

DWL Observations NASA recent ISAL/IMDC study Hybrid wind lidar Specific instrument parameters ADM alone GWOS alone ADM/GWOS combined ADM follow-ons

Simulating DWL observations Use Doppler Lidar Simulation Model (funded by NASA, NOAA and DoD since Start with Nature Run; calibrate cloud coverage; produce satellite perspective data set; scale grid scale wind variance to sub-grid (Von Karman); distribute backscatter targets by several schemes. Combine many independent samples in the vertical and horizontal to produce an observation representative of the average of the illuminated volumes. This product includes both correlated and random observation errors. DWL observations provided to the OSSE are LOS components with quality flags based upon signal strength and sample numbers.

Systematic errors Direct Detection –Background errors –Multiple scattering –Pointing Coherent –Pointing