Module 17 MM5: Climate Simulation BREAK

Regional Climate Simulation for the Pan-Arctic using MM5 William J. Gutowski, Jr., Helin Wei, Charles Vörösmarty, Balazs Fekete & Steven Frolking Iowa State University University of New Hampshire

Regional Climate Simulation for the Pan-Arctic using MM5 Focus Land-Atmosphere Coupling in Pan-Arctic Hydrologic Cycle

NCAR/Penn State Non-hydrostatic MM5 (V2) Grell cumulus convection Mixed-phase microphysics CCM2 radiation Blackadar high resolution PBL NCAR Land Surface Model (LSM) Simple Thermodynamic Sea Ice Model Model

Period: 1 Oct Sep Sensitivity runs: Oct 85 or July 86 Computation: DOE/Ames ALICE (32-nodes) NCAR C90 (4-nodes) [2.5 cpu-hr/month] NCAR Blackforest Model domain (grid: 51 x 91; 120 km)

 Historical Arctic Rawinsonde Archive (HARA)  NCEP reanalysis (upper air)  TOVS  sfc. (skin) temperature  vertical temp profile  PBL stratification  Xie-Arkin precipitation  Polar Radiation Flux Project (PRF)  The Arctic 2-Meter Air Temperature data set Observational comparisons

Asian Arctic Watershed North American Arctic Watershed European Arctic Watershed Analysis Sectors = selected HARA sites Central Arctic Ocean

Cloud calibration (Oct & July 1986) ExperimentCC algorithmResult (non-convective) 1RH > 75% (MM5 std.)too much 2RH > 98%too much 3CLW > kg/m 3 too little CIW > kg/m 3 => CC=75% 4CLW > kg/m 3 ~ OK CIW > kg/m 3 => CC=90%

Surface incident solar radiation [W/m 2 ] Polar Rad. Flux Obs. MM5/LSM

Cloud calibration - Precipitation simulation (July 1986)

Cloud calibration - Precipitation simulation (Oct. 1985)

500 hPa Heights (Dec85 - Jan86 - Feb86) NCEPMM5

500 hPa Heights (Mar - Apr - May 86) NCEPMM5

500 hPa Heights (Jun - Jul - Aug 86) NCEPMM5

500 hPa Heights (Oct85 - Nov85 - Sep86) NCEPMM5

latitude 45N 65N 85N RMS Differences (NCEP - simulation) (a) Z(500 hPa) (b) u(850 hPa) (c) v(850 hPa) (a) 45N 65N 85N 45N 65N 85N OCT JAN APR JUL [m/s] (b) (c) [m/s] [m]

500 hPa Heights: RMS Difference vs. Time (MM5-NCEP) [m] OCT 1 NOV

850 hPa Wind: RMS Difference vs. HARA MM5/LSM NCEP U component V component

850 hPa Wind: RMS Difference vs. HARA MM5/LSM NCEP U component V component

Obs. MM5/LSM 2-Meter Air Temperature

Obs. MM5/LSM Stratification Parameter:  (950 hPa) -  (900 hPa)

Precipitatble Water: MM5 vs. NCEP/NCAR Reanalysis & Sat. Obs.

Precipitation: MM5 vs. Xie-Arkin

Global, Composite Runoff  0.5˚ climatology  Composite based on Observed river discharge 0.5˚ river network (STN-30p) Climatology-driven water balance model River Networking & Runoff

Mackenzie River Global, Composite Runoff

Hudson Hope Gauging Station

1. Water Balance Model driven by climatological precip. & temp. computes runoff in 0.5˚ grids 2. Runoff vs. discharge 3. Correct runoff in 0.5˚ grids by discharge

Surface Runoff [mm/month ] ______________ Post-processing assumption: No infiltration over frozen soil UNH-CLIM MM5/LSM

What is error vs. region size? Averaging Grids: Compute average error variance for...

What is error vs. region size? Averaging Grids: Compute average error variance for grids...

What is error vs. region size? Averaging Grids: Compute average error variance for grids of different spacings

What is error vs. region size? Average RMS difference scaled by amplitude of field’s annual cycle

Module 17 MM5: Climate Simulation Examples of MM5 climate simulation:  North America - good near-surface simulation - shortcomings of narrow boundary zone zone - generic errors in precipitation bias - shortcomings of gridded observations  Arctic - benefits of variety of observations - importance of cloud cover to all simulation - shortcomings of reanalyses - scale-dependence of errors