Distribution of reactive nitrogen species in the remote free troposphere: data and model comparisons

Abstract

The available reactive nitrogen measurements from the global free troposphere obtained during the period of 1985–1995 have been compiled and analyzed. The species of interest are NO, NO x (NO+NO 2), NO y, PAN, HNO 3 and O 3. Data extending to 13 km have been gridded with a 5°×5° horizontal and 1 km vertical resolution. The data have been divided into two seasons, namely “Winter” and “Summer” depending upon the time and location of the observations. Data described here as well as additional analysis have also been archived and are accessible on-line through the World Wide Web at: http://george.arc.nasa.gov/∼athakur. Global maps of the reactive nitrogen species distribution are produced in a form that would be most useful for the test and evaluation of models of tropospheric transport and chemistry. Limited comparisons of the observed reactive nitrogen species data with predictions by 3-D global models were performed using three selected models. Significant model to model as well as data to model differences were frequently observed. During summer, models tended to underpredict NO (−25 to −60%) while significantly overpredicting HNO 3 (+250 to +400%) especially in the upper troposphere. Similarly, the seasonal HNO 3 variations predicted by some models were opposite to those observed. PAN was generally overpredicted, especially in the upper troposphere, while NO y was underpredicted. Ozone on average was better simulated but significant deviations at specific locations were evident. By comparing model predictions with observations, an overall quantitative assessment of the accuracy with which these three models describe the global distribution of measured reactive nitrogen species is provided. No reliable trend information for any of the reactive nitrogen species was possible based on the presently available data set. The reactive nitrogen data currently offer only a limited spatial and temporal coverage for the validation of global models.