Case, Jonathan L.;
Kumar, Sujay V.;
Srikishen, Jayanthi;
Jedlovec, Gary J.
Improving Numerical Weather Predictions of Summertime Precipitation over the Southeastern United States through a High-Resolution Initialization of the Surface State
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Medientyp:
E-Artikel
Titel:
Improving Numerical Weather Predictions of Summertime Precipitation over the Southeastern United States through a High-Resolution Initialization of the Surface State
Beteiligte:
Case, Jonathan L.;
Kumar, Sujay V.;
Srikishen, Jayanthi;
Jedlovec, Gary J.
Beschreibung:
<jats:title>Abstract</jats:title>
<jats:p>It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high-resolution models. This paper presents model verification results of a case study period from June to August 2008 over the southeastern United States using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the National Aeronautics and Space Administration’s (NASA) Land Information System (LIS) and sea surface temperatures (SSTs) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction’s (NCEP) 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spinup run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS–MODIS data substantially impact surface and boundary layer properties. The Developmental Testbed Center’s Meteorological Evaluation Tools package is employed to produce verification statistics, including traditional gridded precipitation verification and output statistics from the Method for Object-Based Diagnostic Evaluation (MODE) tool. The LIS–MODIS initialization is found to produce small improvements in the skill scores of 1-h accumulated precipitation during the forecast hours of the peak diurnal convective cycle. Because there is very little union in time and space between the forecast and observed precipitation systems, results from the MODE object verification are examined to relax the stringency of traditional gridpoint precipitation verification. The MODE results indicate that the LIS–MODIS-initialized model runs increase the 10 mm h−1 matched object areas (“hits”) while simultaneously decreasing the unmatched object areas (“misses” plus “false alarms”) during most of the peak convective forecast hours, with statistically significant improvements of up to 5%. Simulated 1-h precipitation objects in the LIS–MODIS runs more closely resemble the observed objects, particularly at higher accumulation thresholds. Despite the small improvements, however, the overall low verification scores indicate that much uncertainty still exists in simulating the processes responsible for airmass-type convective precipitation systems in convection-allowing models.</jats:p>