| Popis: |
We assess the quality of regional or global ozone reanalysis data for biome modeling and ozone (O3) risk mapping over subarctic Europe where monitoring is sparse. Reanalysis data can be subject to systematic errors originating from, e.g., quality of assimilated data, distribution and strength of precursor sources, incomprehensive atmospheric chemistry or land-atmosphere exchange, and spatiotemporal resolution. Here, we evaluate three selected global and regional ozone reanalysis products. Our analysis suggests that global reanalysis products do not reproduce observed ground-level ozone well in the subarctic region. Only the Copernicus Atmosphere Monitoring Service Regional Air Quality (CAMSRAQ) reanalysis ensemble sufficiently captures the observed seasonal cycle. We computed the root mean square error (RMSE) by season. The RMSE variation between (2.6–6.6) ppb suggests inherent challenges even for the best reanalysis product (CAMSRAQ). O3 concentrations in the region are systematically underestimated by (2–6) ppb compared to the tropospheric background ozone concentrations derived from observations. Furthermore, we explore the suitability of the CAMSRAQ for gap-filling at one site in northern Norway with a long-term record but not belonging to the observational network. We devise a reconstruction method based on Reynolds decomposition and adhere to recommendations by the United Nations Economic Commission for Europe (UNECE) Long Range Transboundary Air Pollution (LRTAP) convention. The thus reconstructed data for two weeks in July 2018 are compared with CAMSRAQ evaluated at the nearest neighboring grid point. Our reconstruction method performs better (78 % accuracy) than CAMSRAQ (73 % accuracy) but diurnal extremes are underestimated by both. |
