1. A Rapid Prototyping Capability Experiment to Evaluate CrIS / ATMS Observations for Urban Modeling Applications July 10, 2007 NASA Review of MRC RPCs Patrick J. Fitzpatrick Valentine G. Anantharaj Christopher M. Hill Lori M. BruceJ. Mark Janus Mississippi State University Lars-Peter Riishojgaard Global Modeling and Assimilation Office / Joint Center for Satellite Data Assimilation Steve Chin Lawrence Livermore National Laboratory

2. General Overview NPOESS to be launched in 2013NPOESS to be launched in 2013 preceding NPOESS Preparatory Project (NPP) to be launched in 2009preceding NPOESS Preparatory Project (NPP) to be launched in 2009 component sensors of NPOESS and NPP to include:component sensors of NPOESS and NPP to include: –Advanced Technology Microwave Sounder (ATMS) –Cross-track Infrared Sounder (CrIS)

3. Sounder Overview ATMS –across track scanning microwave radiometer –cross-track resolution: 1.5 km CrIS –Fourier transform spectrometer –cross-track resolution: 14.0 km –vertical resolution: ~ 3.0 km

4. OSSE Methodology

5. Relatable Modeling Work MM5 simulations of squall line over Mississippi Delta region (April 2005)MM5 simulations of squall line over Mississippi Delta region (April 2005) Visible improvement in model representation of squall line with the assimilation of radar dataVisible improvement in model representation of squall line with the assimilation of radar data

6. Squall line with MM5 : 03-h forecast w/ radarcold start w/ standard obs.observed

7. Squall line with MM5 : 09-h forecast w/ standard obs.observed w/ radarcold start

8. Squall line with MM5 : 12-h forecast w/ radarcold start w/ standard obs.observed

9. Relatable Modeling Work Impact of radar data quantified through analysis of model background errorsImpact of radar data quantified through analysis of model background errors –errors computed between different forecast cycles (Parrish & Derber 1992) 00UTC (Day 1)12h forecast24h forecast error 12UTC12h forecast24h forecast error 00UTC (Day 2)12h forecast within this RPC effort:within this RPC effort: –model background error analysis could be used to calibrate free-running simulations (e.g. with no verifiable boundary conditions) during assimilation of data representing ATMS / CrIS

10. Configuration of Model Runs ECMWF NR grid Run performed by ECMWFRun performed by ECMWF Output administered by NCEPOutput administered by NCEP Global coverageGlobal coverage T799 (∆x ~ 25 km)T799 (∆x ~ 25 km) Integration periods representing:Integration periods representing: –27 September 2005 – 01 November 2005 –10 April 2006 – 03 May 2006 High-resolution Nature Run (HRNR) Image adopted from Shuttle Radar Topography Mission

11. Configuration of Model Runs ECMWF NR grid Regional (MM5) NR grid 135°W 45°W 60°N 0°0°0°0° Images adopted from Shuttle Radar Topography Mission

12. Configuration of Model Runs Regional (MM5) NR grid 135°W 45°W 60°N 0°0°0°0° Run performed with MM5Run performed with MM5 ECMWF HRNR initial conditionsECMWF HRNR initial conditions broad domain centered over Gulfbroad domain centered over Gulf ∆x ~ 9 km or 25 km∆x ~ 9 km or 25 km integration periods as with HRNRintegration periods as with HRNR Regional-Scale Nature Run (RSNR) Image adopted from Shuttle Radar Topography Mission

13. Configuration of Model Runs Image adopted from Shuttle Radar Topography Mission Regional (MM5) NR grid 135°W 45°W 60°N 0°0°0°0° Approximate Nested WRF grid Runs performed with WRFRuns performed with WRF RSNR as initial conditionsRSNR as initial conditions ∆x ~ 3 km or 9 km∆x ~ 3 km or 9 km domain focused on Gulfdomain focused on Gulf integration period of 48 hintegration period of 48 h focus on mesoscale weather systemfocus on mesoscale weather system Sensitivity experiments Houston / Galveston North Central Gulf Coast Tampa Bay region

14. Urban center study candidates Source: U.S. Census 2006 estimates North Central Gulf Coast North Central Gulf Coast Tampa Bay region Tampa Bay region Houston / Galveston Houston / Galveston

15. Current RPC Plan WRF sensitivity experimentsWRF sensitivity experiments –exclusion (or denial) of datasets for assimilation –inclusion of data representing ATMS / CrIS –assess impact of ATMS / CrIS on modeling of urban center Implement urban canopy parameterization (UCP) scheme from Lawrence Livermore National Laboratory (LLNL)Implement urban canopy parameterization (UCP) scheme from Lawrence Livermore National Laboratory (LLNL) –try MODIS and ASTER data in place of USGS land surface data within the UCP scheme Compute maps of aerodynamic roughness within urban environmentCompute maps of aerodynamic roughness within urban environment –use SRTM topography for simulations of large-eddy scale (LES)

16. LLNL UCP scheme allows better representation of urban heat island, other effects of urban infrastructure in mesoscale modelallows better representation of urban heat island, other effects of urban infrastructure in mesoscale model Currently uses USGS emissivity data for input parameters of schemeCurrently uses USGS emissivity data for input parameters of scheme use of MODIS and ASTER data may allow more realistic representation of urban canopyuse of MODIS and ASTER data may allow more realistic representation of urban canopy COAMPS® tracer concentrations (from Chin et al. 2000) Contours – modeled; Shades – observed

17. Aerodynamic Roughness Estimation GoalsGoals –develop robust (general, efficient, accurate) aerodynamic roughness “distribution” estimator –investigate aerodynamic roughness parametric sensitivity –investigate uncertainty propagation Computational ApproachComputational Approach –RANS/LES with 2 nd order turbulence closure (based on SimCenter U 2 NCLE) –discrete roughness elements – Taylor, et al. –parametric sensitivity analysis using complex Taylor series – Newman, III, et al. Investigative Approach (verification and validation)Investigative Approach (verification and validation) –isolated roughness element simulation –roughness element array simulation –random roughness element simulation –urban simulation Current Research by M. Janus