Development of fine‐resolution analyses and expanded large‐scale forcing properties: 1. Methodology and evaluation

Abstract

AbstractWe produce fine‐resolution, three‐dimensional fields of meteorological and other variables for the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS‐DA) framework that is used within the Weather Research and Forecasting model at a cloud‐resolving resolution of 2 km. The MS‐DA algorithm uses existing reanalysis products and constrains fine‐scale atmospheric properties by assimilating high‐resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system. Evaluations also show that the large‐scale forcing derived from the fine‐resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine‐resolution fields are used to characterize the contribution of subgrid variability to the large‐scale forcing and to derive hydrometeor forcing, which are presented in companion papers.