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Approximately 400 Automated Surface Observing System (ASOS) observations of convective cloud-base heights at 2300 UTC were collected from April through August of 2001. These observations were compared with lifting condensation level (LCL) heights above ground level determined by 0000 UTC rawinsonde soundings from collocated upper-air sites. The LCL heights were calculated using both surface-based parcels (SBLCL) and mean-layer parcels (MLLCL-using mean temperature and dewpoint in lowest 100 hPa). The results show that the mean error for the MLLCL heights was substantially less than for SBLCL heights, with SBLCL heights consistently lower than observed cloud bases. These findings suggest that the mean-layer parcel is likely more representative of the actual parcel associated with convective cloud development, which has implications for calculations of thermodynamic parameters such as convective available potential energy (CAPE) and convective inhibition. In addition, the median value of surface-based CAPE (SBCAPE) was more than 2 times that of the mean-layer CAPE (MLCAPE). Thus, caution is advised when considering surface-based thermodynamic indices, despite the assumed presence of a well-mixed afternoon boundary layer.

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The National Blend of Models (NBM) is the culmination of an effort to develop a nationally consistent set of foundational gridded guidance products based on well-calibrated National Weather Service (NWS) and non-NWS model information. These guidance products are made available to the National Centers for Environmental Prediction centers and NWS Weather Forecast Offices for use in their forecast process. As the NWS continues to shift emphasis from production of forecast products to impact-based decision support services for core partners, the deterministic and probabilistic output from the NBM will become increasingly important as a starting point to the forecast process. The purpose of this manuscript is to document the progress of NBM versions 3.1 and 3.2 and what techniques are used to blend roughly 30 individual models and ensembles for a number of forecast elements and regions. Focus will be on the core elements such as (1) temperature and dew point temperature, (2) winter weather, fire weather, thunderstorm probabilities, and (3) wind speed and gusts.