Codes Employed

The components of the end-to-end forecast system used in the Land Information System (LIS) Sensitivity Test included:

    • WRF Preprocessing System (WPS) (v3.4)

    • WRF Data Assimilation (WRFDA) (v3.4)

    • WRF-ARW model (v3.4)

    • Unified Post Processor (UPP) (v1.1)

    • Model Evaluation Tools (MET) (v4.0) *Includes PB2NC error       described here

    • NCAR Command Language (NCL) for graphics generation

    • Statistical programming language, R, to compute confidence        intervals

Domain Configuration

    • Contiguous U.S. (CONUS) domain with 15-km grid spacing

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    • 403 x 302 gridpoints, for a total of 121,706 horizontal gridpoints

    • 56 vertical levels (57 sigma entries); model top at 10 hPa

    • Lambert-Conformal map projection

Sample Namelists

    • namelist.wps

    • namelist.input

AFWA Reference Configuration

    • Sample namelist.input

Other run-time settings

    • Long timestep = 90 s; Acoustic step = 4
    • Calls to the boundary layer and microphysics parameterization        were made every time step
    • Calls to the cumulus parameterization were made every 5        minutes
    • Calls to radiation were made every 30 minutes

Initial and Boundary Conditions

    • Initial conditions (ICs) and Lateral Boundary Conditions
       (LBCs): 0.5 x 0.5 degree Global Forecast System (GFS) model

    • Lower Boundary Conditions (LoBCs): Output from
       the AFWA Land Information System (LIS) utilizing two version
       of the Noah land surface model (v2.7.1 and v3.3)

    • SST Initialization: Fleet Numerical Meteorology and        Oceanography Center (FNMOC) daily, real-time sea surface        temperature (SST) product

Preprocessing Component

The time-invariant component of the lower boundary conditions (topography, soil and vegetation type etc.), using United States Geological Survey (USGS) input data, was generated through the geogrid program of WPS. The avg_tsfc program of WPS was also used to compute the mean surface air temperature in order to provide improved water temperature initialization for lakes and smaller bodies of water in the domain that are further away from an ocean.

Data Assimilation Component

A 6-hour "warm start" spin-up procedure preceded each forecast (see figure below). Data assimilation was conducted using WRFDA at the beginning and the end of the 6-hour warm start window using observation data files provided by AFWA. At the beginning of the data assimilation window, the GFS derived initial conditions were used as the model background, and at the end of the window, the 6-hour WRF forecast initialized by the WRFDA analysis was used. After each WRFDA run, the LBCs derived from GFS were updated and used in the subsequent forecasts.
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Cases Run

• Forecast Dates: 1 July 2011 - 29 June 2012

• Initializations: Every 36 hours, including both 00 and 12 UTC

• Forecast Length: 48 hours; output files generated every 3 hours

The tables below list the forecast initializations that failed to complete the end-to-end process due to the reasons described in the table. All incomplete forecasts were due to missing or bad input data sets, not model crashes.

Verification

The Model Evaluation Tools (MET) package, comprised of:

    • grid-to-point comparisons - utilized for surface and upper air        model data
    • grid-to-grid comparisons - utilized for QPF

was used to generate objective verification statistics, including:

    • Bias-corrected Root Mean Square Error (BCRMSE) and Mean
       Error (Bias) for:
        • Surface: Temperature (2 m), Dew Point Temperature (2 m)            and Winds (10 m)
        • Upper Air: Temperature, Dew Point Temperature and Winds

    • Gilbert Skill Score (GSS) and Frequency Bias (FBias) for:
        • 3-hr and 24-hr Precipiation Accumulation intervals

Each type of verification metric is accompanied by confidence intervals (CIs), at the 99% level, computed using a parametric method for the surface and upper air variables and a boostrapping method for precipitation.

Both configurations were run for the same cases allowing for a pair-wise difference methodology to be applied, as appropriate. The CIs on the pair-wise differences between statistics for the two configurations objectively determines whether the differences are statistically significant (SS).

To establish practical significance (PS) in order to examine SS pair-wise differences that are potentially more meaningful, the data was censored to only look at differences that were greater than the operational measurement uncertainty requirements as defined by the World Meteorological Organization (WMO). The following criteria were applied to determine PS pair-wise differences between the configurations and versions for select variables: i) temperature and dew point temperature differences greater than 0.1K and ii) wind speed differences greater than 0.5 ms^-1.

Area-averaged verification results were computed for the full and CONUS domains, East and West domains, and 14 sub-domains.