Effect of Boundary Conditions on Adjoint-Based Forecast Sensitivity Observation Impact in a Regional Model

Abstract

In this study, the effect of boundary condition configurations in the regional Weather Research and Forecasting (WRF) model on the adjoint-based forecast sensitivity observation impact (FSOI) for 24 h forecast error reduction was evaluated. The FSOI has been used to diagnose the impact of observations on the forecast performance in several global and regional models. Different from the global model, in the regional model, the lateral boundaries affect forecasts and FSOI results. Several experiments with different lateral boundary conditions were conducted. The experimental period was from 1 to 14 June 2015. With or without data assimilation, the larger the buffer size in lateral boundary conditions, the smaller the forecast error. The nonlinear and linear forecast error reduction (i.e., observation impact) decreased as the buffer size increased, implying larger impact of lateral boundaries and smaller observation impact on the forecast error. In all experiments, in terms of observation types (variables), upper-air radiosonde observations (brightness temperature) exhibited the greatest observation impact. The ranking of observation impacts was consistent for observation types and variables among experiments with a constraint in the response function at the upper boundary. The fractions of beneficial observations were approximately 60%, and did not considerably vary depending on the boundary conditions specified when calculating the FSOI in the regional modeling framework.

Effect of atmospheric conditions and VPRM parameters on high-resolution regional CO2 simulations over East Asia

“…In previous studies that simulated CO 2 concentrations using WRF-Chem, various atmospheric fields were used as the initial and boundary conditions of the model. As WRF-Chem is a regional model, initial atmospheric conditions and atmospheric boundary conditions greatly affect the simulation results and forecast error (Kim and Kim 2021). To simulate CO 2 concentrations using WRF-Chem in the US, Hu et al (2020) used the National Center for Environmental Prediction-Department of Energy (NCEP/DOE) R2 data (Kanamitsu et al 2002); Chen et al (2019) and Feng et al (2019) used the European Center for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim; Dee et al 2011);and Martin et al (2019) conducted an experiment using NCEP North American Regional Reanalysis (NARR; Mesinger et al 2006).…”