1 / 10

Driving UM-SCM with reanalysis / model data

Driving UM-SCM with reanalysis / model data. Vaughan Barras ACCESS Model Development Group. Dynamically constrained simulations. Previous experience constraining GCMs dynamically with reanalyses, allowing other model components to evolve d 18 O in hydrological cycle

garret
Download Presentation

Driving UM-SCM with reanalysis / model data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Driving UM-SCM with reanalysis / model data Vaughan Barras ACCESS Model Development Group

  2. Dynamically constrained simulations Previous experience constraining GCMs dynamically with reanalyses, allowing other model components to evolve • d18O in hydrological cycle • eg: Melbourne Uni Network of Isotopes in Precipitation 3rd IOP (Jun 11, 2005) • See also: Noone (2006) (WGNE Rep. 36; WMO/TD-No. 1347) Yoshimura et al., 2008 (JGR, 113, D19108) Barras and Simmonds, (submitted to JGR)

  3. Use in SCMs? …yes…provided it is set up carefully and SCM used appropriately. • Idealised cases (equilibrium, constant forcings) • Targeted studies (Intercomparisons) • Intensive Observational Campaigns (IOPs) • TWP-ICE, TOGA-COARE, GABLS, DYCOMS, RICO, Cabauw,… • Alternative namelist generation? • NWP forcings • Useful - depending on what is under investigation • Complicated setup…

  4. genesis Software to create SCM namelists at a user-defined location from reanalyses / model input. Uses: • Testing of parameterisations under a range of scenarios • IOPs can be subjective in the conditions they represent • Based on approximate ‘real-world’ conditions (reanalyses) • Extract model conditions for detailed testing • Efficiency enables creation of ensemble namelists • Variable initial conditions, major forcing fields.

  5. how it works • Download global NetCDF fields of pmsl, F, U, V, T, q for desired period • ERA40 • JRA25 (q > level 12 = 0.0) • NCEP (genesis converts RH to q) • UM • dumps from STASH (sub-periods of longer runs) • Use ‘Trans’ option in xconv to interpolate to P grid. • User specifies lat / lon • Define ‘files.inp’ and ‘dates.dat’ files • Simple list of input file names and dates matching inputs • Command line execution • Can be scripted

  6. genesis --help gale/vjb> genesis Usage: genesis genesis [options] -d verbose, debug mode -h help -t no. of time increments (def=150) -l no. of levels of input data (def=20) -x no. of longitudes (def=29) -y no. of latitudes (def=17) -X user defined longitude (eg: 243.7) -Y user defined latitude (eg: 65.0) -D use date file (def = false) -O use offset file (def = false) -E ERA40 data (def = false) -J JRA data (def = false) -N NCEP data (def = false) -U UM data (def = false) You also need a few files in the run directory for this to work. a) files.inp - a file listing the *.nc file names in order: ps,z,u,v,t,q b) offset.dat (optional) - list of offset parameters from ncdump hdr [scale, add] - if geopotential needs converting only (m2/s2 >> m) then use -O with offset file set to 1 0 for each. c) dates.dat (optional) - a list of dates/times corresponding to data records. [generate using datetraj - yyyymmdd hhhh]

  7. details • Read NetCDF fields • Finds nearest neighbour grid points for interpolation • Calculates advective tendencies (T, q) • Linear interpolation of fields (horizontally) • Could incorporate other interpolation methods if desired • Derivation of geostrophic wind profiles • Assign dates / times to records • Intermediate output field (*.scm) • Initial profiles (P_IN, UI, VI, QI, THETA) • Increments (U_INC, V_INC, T_INC, Q_STAR) • Output ‘namelist.scm’ • Still needs to be checked before running!

  8. Example – CASES 99 NWP forcing profiles compared with hi-res soundings from CASES 99 U T V q

  9. Example – CASES 99 ERA40 forced UM-SCM runs t = 6hr U* Tsfc t = 48hr

  10. however… Still requires user to set up cases carefully. • SCM6.3 has constant Ūg • Restricted to short runs where synoptic circulation isn’t rapidly changing (midlats can be a problem in this regard, tropics ok) • Variable setting in SCM7.1, enables longer simulations • No inclusion of ‘w’ • SCMs sensitive to these settings, best if user defined / derived by model continuity • Not comparable to observations, but… • Genesis can provide framework for parameterisation sensitivity studies, not restricted by IOP location. • Enables targeting of problem regions / conditions [debugging…]

More Related