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ASM Project Update: Atmospheric Component University of Colorado. Mark W. Seefeldt and John J. Cassano University of Colorado at Boulder Cooperative Institute for Research in Environmental Sciences Department of Atmospheric and Oceanic Sciences. Goals for Year 1 of DOE Project.

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asm project update atmospheric component university of colorado

ASM Project Update:Atmospheric ComponentUniversity of Colorado

Mark W. Seefeldt and John J. Cassano

University of Colorado at Boulder

Cooperative Institute for Research in Environmental Sciences

Department of Atmospheric and Oceanic Sciences

goals for year 1 of doe project
Goals for Year 1 of DOE Project
  • Develop and evaluate Polar WRF
    • University of Colorado
    • Iowa State University
    • Sub-contract to Bromwich / Hines - OSU
  • Coupling of WRF to CCSM cpl7
    • Lead by Juanxiong He, UAF
goals after the boulder meeting in may 2008
Goals after the Boulder meeting in May 2008
  • Create and establish the atmosphere/land pan-arctic domain
  • Run a one-month simulation for September 1998 over the pan-arctic domain
  • Continue to develop and evaluate the WRF physics parameterization over the Arctic
  • Evaluate seasonal extremes and impact of fractional sea ice in WRF

Iowa State University (Bill, Justin, Brandon)

  • Continue with coupling of WRF to CCSM cpl7

UAF (Juanxiong He)

  • Pan-arctic atmosphere/land domain
  • Pan-arctic simulation for September 1998
  • WRF Pre-processing System (WPS)
  • Evaluation of global forcing data for WRF
  • WRF polar modifications update
  • Introduction to Model Evaluation Tools (MET)
  • Evaluation of radiation and microphysics parameterizations during the SHEBA year
pan arctic atmosphere land domain
Pan-Arctic Atmosphere/Land Domain
  • Requirements for the atmosphere / land domain:
    • 50 km grid resolution
    • Extend beyond the boundaries of the ocean/sea ice domain
    • Incorporate the entire Arctic watershed basin
pan arctic atmosphere land domain1
Pan-Arctic Atmosphere/Land Domain
  • Extend ~ 10 points beyond the Arctic watershed basin
pan arctic atmosphere land domain2
Pan-Arctic Atmosphere/Land Domain
  • Extend beyond the boundaries of ocean/sea ice domain
pan arctic atmosphere land domain3
Pan-Arctic Atmosphere/Land Domain
  • The combination of the two requirements:
pan arctic atmosphere land domain4
Pan-Arctic Atmosphere/Land Domain
  • The two domains with color shaded topography:
pan arctic atmosphere land domain5
Pan-Arctic Atmosphere/Land Domain
  • The domains with color shaded topography and bathymetry:
pan arctic atmosphere land domain6
Pan-Arctic Atmosphere/Land Domain
  • WPS (WRF Pre-Processing System) settings:
    • s_we = 1, e_we = 276
    • s_sn = 1, e_sn = 206
    • dx = 50000
    • dy = 50000
    • map_proj = ‘polar’
    • ref_lat = 80.5
    • ref_lon = 160.0
    • truelat1 = 80.5
    • stand_lon = -114.0
pan arctic atmosphere land domain7
Pan-Arctic Atmosphere/Land Domain
  • All files related to the pan-arctic atmosphere / land domain can be retrieved from ARSC:
    • namelist.wps.pan_arctic (WPS namelist)
    • (WPS geogrid.exe output)

(a cleaned-up version of the NetCDF output)

    • all domain images in png and ps format
  • Located at:


wrf pan arctic simulation
WRF Pan-Arctic Simulation
  • At the May 2008 meeting it was agreed for all groups to supply data for a one-month simulation
    • month: September 1998
    • data: 6-hourly intervals (preferably NetCDF)
wrf pan arctic simulation1
WRF Pan-Arctic Simulation
  • WRF Configuration:
    • a single continuous run from 00 UTC 31 August through 00 UTC 1 October 1998 (31 days)
    • forcing data: ERA40 – soil / surface values

ECMWF-TOGA – atmosphere

    • using the new pan-arctic domain (50 km res.)
    • physics:

SW: Goddard LW: RRTM

Microphysics: Morrison Cumulus: Grell-Devenyi

PBL: YSU (sfclayer: MM5) Land Surface: Noah LSM

    • output: 6-hour history interval (wrfout NetCDF)
wrf pan arctic simulation2
WRF Pan-Arctic Simulation
  • Initial test – June 2008:
    • run locally on a dual-processor Linux system
    • one day: ~ 6 hours 47 minutes processing time
    • entire month: ~ 8 days
  • Created daily wrfout files: 566 MB / day
  • Sample wrfout NetCDF file provided to NPS
wrf pan arctic simulation3
WRF Pan-Arctic Simulation
  • Second test – December 2008:
    • run on midnight at ARSC
    • same configuration as the June 2008 test
    • 8 CPUs: one day: ~ 28 minutes

entire month: estimated at 14-15 hours

    • 16 CPUs: one day: ~ 19 minutes

entire month: estimated at 10 hours

    • 32 CPUs: have not been able to get a test run
    • the wrfout NetCDF files will be located at:


wrf pre processing system wps
WRF Pre-processing System (WPS)
  • The WPS processes the static terrestrial and the gridded model forcing data into a format to be used by WRF
wrf pre processing system wps1
WRF Pre-processing System (WPS)
  • There are three steps in the WPS process:
    • geogrid.exe – creates the domain and processes the static terrestrial data
    • ungrib.exe – extracts the gridded forcing data and creates ‘intermediate files’
    • metgrid.exe – combines the geogrid data with the intermediate files to create the WRF input files
wrf pre processing system wps2
WRF Pre-processing System (WPS)
  • The interpolation to the model horizontal grid is done in metgrid.exe
  • metgrid.exe checks that all mandatory fields are included (pres, skintemp, T, u, v, ~ psfc)
  • Data from non-GRIB sources can be included if it is in the ‘intermediate file’ format (ex: sea ice from NSIDC)
  • metgrid.exe creates the met_em* files
wrf real exe
WRF – real.exe
  • real.exe creates the initial and boundary condition files to be used by wrf.exe
  • The interpolation to the model vertical levels is done in real.exe
  • If a non-mandatory field is not included in the met_em* files, but it is used by wrf.exe, then real.exe creates the data

Ex: If sea ice is not included in the met_em* files, then real.exe sets all grid points with a SKINTEMP less than 271 K (user specified) as sea ice

  • real.exe has the ability to create psfc, but it is best to have it from the source data
wrf global forcing data
WRF – Global Forcing Data
  • WRF works best with the NCEP Final Analyses
  • Features:
    • 1 x 1 degree global grid every six hours
    • daily 30 July 1999 – present
    • NCAR – DSS: ds083.2
  • It is not a re-analysis – when the model is changed the dataset is not reprocessed
  • The NCEP analyses have been indicated to be relatively poor performing in the arctic
wrf global forcing data1
WRF – Global Forcing Data
  • ERA40 has shown the best performance in the arctic
  • A consistent data set covering a range of years
  • There are different version of ERA40 at the NCAR – DSS (best to use pressure level):
    • model native resolution:

surface / single levels – N80 – (includes psfc) ds117.0

upper air – T159 spectral resolution – ds117.1

Note: WPS ungrib.exe does not support the grid types

    • 2.5 deg lat/lon global grid

surface / single levels (does not include psfc) - ds118.0

upper air – ds118.1

wrf global forcing data2
WRF – Global Forcing Data
  • ECMWF-TOGA has shown good performance in the arctic
  • It is not a re-analysis
  • The supplemental fields have improved over the last 10 years
  • There are two general versions of ECWF:
    • model native resolution:

surface / single levels – N80 – (inc. psfc) ds111.0

upper air – T106 spectral resolution – ds111.1

Note: WPS ungrib.exe supports this n80 grid

    • 2.5 deg lat/lon global grid

global surface and upper level analysis – ds111.2

-does not include soil moisture and temperature

wrf global forcing data3
WRF – Global Forcing Data
  • It has proven to be difficult to select a preferred source of global forcing data
  • ERA40 is the preferred choice
    • has the consistency of a re-analysis
    • does not have psfc in a format usable by WPS
  • ECMWF-TOGA has the psfc values
    • the analyses change over time
    • older analyses are missing some supplemental fields
  • The likely solution for pre-2003 is to use ERA40 and to develop a method to get psfc into the met_em* files
wrf polar modifications
WRF – Polar Modifications
  • Modifications have been made to the native WRF code for polar applications
    • Keith Hines and David Bromwich

Byrd Polar Research Center (OSU)

  • The modifications are currently distributed by BPRC and are not included in WRF releases
    • They may be included in the WRF 3.1 release – Spring 2009
  • The modifications fall into two divisions:
    • fractional sea-ice
    • Noah LSM
  • ifdef compiler flags turn on the two divisions of modifications at compile time
wrf polar modifications1
WRF – Polar Modifications
  • Fractional sea ice:
    • Surface boundary layer routine called separately for ice and liquid
    • Noah or other LSMs can be used
    • Can specify sea ice albedo
  • Noah LSM:
    • Snow/ice emissivity set at 0.98
    • Permanent ice albedo set at 0.8
    • If snowpack depth > 0.05 m, treat snow within the prognostic “soil” layers of Noah
    • Direct summation of surface energy balance terms in diagnostic calculation of surface temperature
    • Penman Equation evapotranspiration calculations updated for ice sublimation

*Information from Hines and Bromwich – 2008 AMOMFW presentation

model evaluation tools met
Model Evaluation Tools (MET)
  • What is it?
    • a set of model evaluation tools for the WRF community
    • developed by scientists, statisticians, and software engineers
    • primary users include WRF developers, university researchers, and operational centers
    • developed and supported by the Development Testbed Center (DTC)
    • support provided by the Air Force Weather Agency (AFWA) and NOAA
met components
MET Components
  • data reformatting modules (ex. ascii2nc)
  • statistics modules:
    • MODE – object based spatial verification
    • Grid-Stat – verification of grids
    • Point-Stat – verification of point data
  • analysis modules (ex. VSDB analysis tool)

Figure and information courtesy of UCAR/DTC

met components grid stat
MET Components – Grid-Stat
  • Compares gridded forecasts to observations (analysis / “truth”)
  • Includes ‘neighborhood methods’
  • Select multiple: variables, levels, thresholds, masking regions, smoothing methods, confidence interval methods (CIs), and alpha values for CIs
  • Output: contingency table counts and statistics with CIs, continuous statistics with CIs, neighborhood methods
met components point stat
MET Components – Point-Stat
  • Compare observation against a user specified region of grid point(s)
    • nearest point
    • 2x2 box around observation point
    • 3x3 box around observation point
  • Select multiple: variables, levels, thresholds, masking regions, matching methods, confidence intervals (CI) methods
  • Several metrics can be used to create matched forecast value (min., max., median, unweighted mean, distance weighted mean)
  • User-defined number of minimum number of valid data points
met statistics discrete variables
MET Statistics – Discrete Variables
  • based on applying a threshold to a continuous variable
  • Number of observations
  • FHO Statistics
  • Contingency table counts
  • Contingency table proportions
  • Accuracy
  • Bias
  • Probability of Detection of Yes
  • Probability of Detection of No
  • False Alarm Ratio
  • Critical Success Index
  • Gilbert Skill Score
  • Hanssen and Kuipers Disciminent
  • Heidke Skill Score
  • Odd Ratio
met statistics continuous variables
MET Statistics – Continuous Variables
  • Mean (fcst./obs.)
  • Standard Deviation (fcst./obs.)
  • Correlation Coefficients (3 types)
  • Mean Error
  • Mean Absolute Error
  • Mean Squared Error
  • Bias-correlated Mean Squared Error
  • Root-Mean Squared Error
  • Error Percentiles (10th, 25th, 50th, 75th, 90th)
  • Partial Sums (1st and 2nd moments of the forecasts, observations, and errors)
    • scalar, anomaly, vector, vector anomaly
wrf evaluation of physics
WRF Evaluation of Physics
  • In May a list of preferred physics parameterizations was selected based on a quick and limited evaluation
    • Land surface: Noah
    • Longwave radiation: RRTM
    • Shortwave radiation: Goddard
    • Boundary layer: YSU or MYJ (MYJ)
    • Microphysics: Morrison or WSM5
    • Cumulus: Kain-Fritsch or Grell-Devenyi
  • 50km ARCMIP domain over the SHEBA field campaign
  • Limited number of combinations were evaluated
  • Two months were evaluated: January 1998, June 1998
  • Results were compared only compared against the SHEBA surface observations
wrf evaluation of physics1
WRF Evaluation of Physics
  • Past studies indicate that atmospheric models have difficulties with the clouds (microphysics) and radiation processes in the polar region
  • Different combinations of parameterizations impact the results of the selected parameterizations
  • Goal: to thoroughly evaluate the WRF microphysics and radiation processes in the arctic
    • test all probable microphysics and radiation parameterizations
    • multiple months through the year
    • multiple observation points
    • test with 10km and 50km resolutions
    • hold all other physics parameterizations constant
wrf clouds and radiation evaluation
WRF Clouds and Radiation Evaluation
  • Domain to cover the SHEBA field campaign and the Barrow ARM observation location
  • 50km and 10km domains to cover both locations
wrf clouds and radiation evaluation1
WRF Clouds and Radiation Evaluation
  • Selected five longwave and shortwave radiation combinations:
  • Selected six realistic microphysics parameterizations:

mp_2 – Lin mp_4 – WSM5 mp_6 – WSM6

mp_7 – Goddard mp_8 – Thompson mp_10 – Morrison

  • All other physics parameterizations are constant

PBL: MYJ Land Surface: Noah LSM Cumulus: Kain-Fritsch

wrf clouds and radiation evaluation2
WRF Clouds and Radiation Evaluation
  • Selected three months during the SHEBA year:

199801 January winter

199803 March seasonal transition

199805 May transition to liquid clouds

199806 June summer

  • Results in: 5 x 6 x 4 = 120 simulations
  • The results will be evaluated with both the10km domain and the 50km domain (one-way nesting)
  • The goal is to identify 2-3 preferred radiation and microphysics combinations