Weather Forecast Model Evaluation Using METplus and the New York State Mesonet Flux Network

Established in 2017, the New York State Mesonet (NYSM) is a comprehensive network of 126 standard meteorological sites, 17 profiler sites (3D scanning lidar and microwave radiometer), 17 snow sites, and 18 flux sites (momentum, heat, moisture, and CO2) that spans the complex terrain of New York State. The NYSM operates within the University at Albany’s Atmospheric Sciences Research Center (ASRC) and was conceived as a monitoring/early warning detection network; however, it also provides a unique observational data set for evaluating the accuracy and process representation of numerical weather prediction (forecast) models. A collaborative project between ASRC and the National Center for Atmospheric Research (NCAR) aims to combine high-resolution forecast model output (an experimental version of the high-resolution Unified Forecast System) with NYSM observations using the enhanced Model Evaluation Tools (METplus), a versatile verification and visualization system developed by NCAR, the National Oceanic and Atmospheric Administration (NOAA), and the broader community. METplus includes a suite of tools for calculation of statistics between model outputs and in situ observations across spatiotemporal scales, as well as ingest of non-standard observations and model output fields via Python embedding capabilities (e.g., using Python to easily ingest widely varying data formats and passing data structures to MET statistical tools). We are developing METplus workflows and use cases to ingest both standard meteorological variables (e.g., 2-m temperature), as well as land-atmosphere fluxes and flux-derived measures of land-atmosphere coupling (e.g., Bowen Ratio) to test physically-based parameterization schemes and provide insight into forecast model biases. We will provide an overview of our METplus workflows and use cases, as well as discuss some preliminary model evaluation results.