Accession Number : ADA595323


Title :   Assessing High-Resolution Weather Research and Forecasting (WRF) Forecasts Using an Object-Based Diagnostic Evaluation


Descriptive Note : Final rept. 1 Oct 2012-30 Sep 2013


Corporate Author : ARMY RESEARCH LAB WHITE SANDS MISSILE RANGE NM COMPUTATIONAL AND INFORMATION SCIENCES DIRECTORATE/BATTLEFIELD ENVIRONMENT DIV


Personal Author(s) : Vaucher, Gail ; Raby, John


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a595323.pdf


Report Date : Feb 2014


Pagination or Media Count : 95


Abstract : The Model Assessment Project conducted an investigation into the applicability of the Model Evaluation Tools (MET), Method for Object-Based Diagnostic Evaluation (MODE) tool, which was designed to perform spatial verification of numerical weather prediction (NWP) model forecasts. The NWP model used during the investigation was a version of the Weather Research and Forecasting-Advanced Research Weather Research and Forecasting (WRF-ARW) model, which is tailored to address Armyscale horizontal spatial resolutions of 1 3 km. This model is called the Weather Running Estimate Nowcast (WRE-N). The WRE-N was run over three nested grids with the 1-km inner nest grid spacing being the study focus. The observations were surface meteorological variables from independent gridded analyses. MODE compared meteorological features or objects defined from the forecast and observed fields for the same valid time on the basis of measureable attributes. It then quantified the differences between corresponding objects as a measure of forecast error. MODE was designed to evaluate errors in precipitation forecasts, but little work had been done with continuous variable fields. The focus of this study was to assess the application of MODE to NWP models and high-resolution meteorological variables over small, Army-relevant domains.


Descriptors :   *NOWCASTING , *STATISTICAL ANALYSIS , *WEATHER FORECASTING , CASE STUDIES , COMPUTER PROGRAMS , FUZZY LOGIC , HIGH RESOLUTION , LESSONS LEARNED , NUMERICAL METHODS AND PROCEDURES


Subject Categories : Meteorology
      Statistics and Probability


Distribution Statement : APPROVED FOR PUBLIC RELEASE