Sensitivity of the National Oceanic and Atmospheric Administration multilayer model to instrument error and parameterization uncertainty

The response of the National Oceanic and Atmospheric Administration multila yer inferential dry deposition velocity model (NOAA-MLM) to error in meteor ological inputs and model parameterization is reported. Monte Carlo simulat ions were performed to assess the uncertainty in NOAA-MLM deposition veloci ty V-d estimates for ozone (O-3), sulfur dioxide (SO2), and nitric acid (HN O3) associated with measurements of meteorological variables (including tem perature, humidity, radiation, wind speed, wind direction, and leaf area in dex). Summer daylight scenarios for grass, corn, soybean, oak, and pine wer e considered. Model sensitivity to uncertainty in the leaf area index (LAI) , minimum stomatal resistance, and soil moisture parameterizations was expl ored. For SO2 and HNO3, instrument error associated with the measurement of wind speed and direction resulted in the greatest V-d error. Depending On vegetation type, the most important source of uncertainty due to instrument error for the V-d of O-3 was LAI. Of the model parameterizations studied, accurate estimation of temporal aspects of the annual LAI profile and the c haracterization of soil moisture supply and demand are most important to mo del-estimated V-d uncertainty. Considered individually, these factors can r esult in SO2 and HNO3 V-d estimate uncertainty of +/-25% and O-3 estimate u ncertainty greater than 60%. For single plant species settings, reductions in estimate uncertainty should be possible with minor algorithmic modificat ion, inclusion of more species-appropriate LAI profiles, and careful applic ation of remote sensing technology.