June 2003Yun (Helen) He1 Coupling MM5 with ISOLSM: Development, Testing, and Application W.J. Riley, H.S. Cooley, Y. He*, M.S. Torn Lawrence Berkeley National.

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Presentation transcript:

June 2003Yun (Helen) He1 Coupling MM5 with ISOLSM: Development, Testing, and Application W.J. Riley, H.S. Cooley, Y. He*, M.S. Torn Lawrence Berkeley National Laboratory

June 2003Yun (Helen) He2 Outline Introduction Model Integration Model Configuration Model Testing Simulation and Impacts of Winter Wheat Harvest Conclusions Observations and Future Work

June 2003Yun (Helen) He3 Introduction CO 2 fluxes and other trace-gas exchanges are tightly coupled to the surface water and energy fluxes. Land-use change has strong impact on surface energy fluxes. We coupled MM5 with ISOLSM (Riley et. al 2003), which is based on LSM1 (Bonan, 1995). LSM1, thus ISOLSM, simulates: vegetation response to water vapor, CO 2, and radiation; soil moisture and temperature. ISOLSM also simulates gases and aqueous fluxes within the soil column and 18 O composition of water and CO 2 exchanges between atmosphere and vegetation.

June 2003Yun (Helen) He4 Model Integration New interface between MM5 and ISOLSM based on the current OSULSM interface with MM5 and includes: partitioning shortwave radiation between diffuse and direct components spatially and temporally-dependent vegetation dynamics (i.e., leaf area index). Compiler options changed to accommodate two different source code styles. Automatic script to retrieve and process pregrid data from NCEP NNRP data.

June 2003Yun (Helen) He5 Model Integration (cont’d) Import MM5 to NERSC IBM SP machine. 380 compute nodes, 16 way each  6,656 processors 16 to 64 GB memory per node 375 MHz per CPU  10 Tflop/sec peak speed 44 TB disk space in GPFS Revise MPP library and MPP object files for ISOLSM. Investigate optimization levels to achieve bit-for-bit MPP results with sequential runs. Run scripts with automatic I/O from NERSC HPSS. Speedup with 64 CPUs is about 36. Simulation time: 15 min for domain 1 50 min for domain 2

June 2003Yun (Helen) He6 Model Configuration Model Initialization: First-guess and boundary condition interpolated from NCEP NNRP. Model Grids: Outer Domain 1: Continental USA grid size: 54 x 68, resolution: 100 km x 100 km One-way nestdown Inner Domain 2: FIFE or ARM-CART region grid size: 41 x 41, resolution: 10 km x 10 km Vertical: 18  -layers between 100 mb and surface Physics package used: Grell convective scheme Simple ice microphysics MRF PBL scheme CCM2 radiation package

June 2003Yun (Helen) He7 Model Testing Comparisons between: MM5 coupled with ISOLSM MM5 coupled with OSULSM (Chen and Dudhia, 2001) FIFE dataset: 3-year measured data (Betts and Ball 1998) surface fluxes, soil moisture, soil temperature, etc. spatially averaged over 225 km 2 area of Kansas. June, July, August of ISOLSM performed comparably or better than OSULSM.

June 2003Yun (Helen) He8

June 2003Yun (Helen) He9

June 2003Yun (Helen) He10 Winter Wheat Harvest Simulation MM5-ISOLSM model applied to ARM-CART region from June to July Two scenarios: Early harvest: June 4, 1987 (Julian day 155) Late harvest: July 5, 1987 (Julian day 186) Set harvest area with bare soil. Four distinct time periods are evident in the simulations: JD : large evaporation at harvest area JD : reduced evaporation at harvest area JD : increased precipitation JD : two scenarios converge

June 2003Yun (Helen) He11 ARM-CART Region early harvest – late harvest

June 2003Yun (Helen) He12 ARM-CART Region early harvest - late harvest

June 2003Yun (Helen) He13 early harvest – late harvest

June 2003Yun (Helen) He14 Conclusions Successfully coupled MM5 and ISOLSM. Built and ran the coupled model in parallel. Validated the coupled model against current MM5 model and FIFE dataset. Utilized the coupled model to study the impact of winter wheat harvest. Winter wheat harvest simulation indicates that harvest impacts both regional and local surface fluxes, 2 m air temperature, and soil temperature and moisture.

June 2003Yun (Helen) He15 Observations and Future Work The coupled model allows us to estimate surface fluxes that are consistent with ecosystem CO 2 exchange. The soil advection and diffusion sub-models allow us to simulate the impacts of regional meteorology on other distributed trace-gases. Study the impact of human-induced land-use change on regional climate and predict regionally-distributed estimates of CO 2 exchanges. Investigate the practicality of estimating distributed trace-gas fluxes from atmospheric measurements.