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. Eastern China (27–41 ∘  N,110–123 ∘  E) is heavily polluted bynitrogen dioxide ( NO2 ), particulate matter with aerodynamic diameterbelow 2.5  µ m (PM 2.5 ), and other air pollutants. These pollutantsvary on a variety of temporal and spatial scales, with many temporal scalesthat are nonperiodic and nonstationary, challenging proper quantitativecharacterization and visualization. This study uses a newly compiledEOF–EEMD analysis visualization package to evaluate the spatiotemporalvariability of ground-level NO2 , PM 2.5 , and their associationswith meteorological processes over Eastern China in fall–winter 2013.Applying the package to observed hourly pollutant data reveals a primaryspatial pattern representing Eastern China synchronous variation intime, which is dominated by diurnal variability with a much weakerday-to-day signal. A secondary spatial mode, representing north–southopposing changes in time with no constant period, is characterized bywind-related dilution or a buildup of pollutants from one day to another. We further evaluate simulations of nested GEOS-Chem v9-02 andWRF/CMAQ v5.0.1 in capturing thespatiotemporal variability of pollutants. GEOS-Chem underestimates NO2 by about 17  µ g m −3 and PM 2.5 by35  µ g m −3 on average over fall–winter 2013. It reproduces the diurnalvariability for both pollutants. For the day-to-day variation, GEOS-Chemreproduces the observed north–south contrasting mode for both pollutants butnot the Eastern China synchronous mode (especially for NO2 ). Themodel errors are due to a first model layer too thick (about 130 m) tocapture the near-surface vertical gradient, deficiencies in the nighttimenitrogen chemistry in the first layer, and missing secondary organic aerosolsand anthropogenic dust. CMAQ overestimates the diurnal cycle of pollutantsdue to too-weak boundary layer mixing, especially in the nighttime, andoverestimates NO2 by about 30  µ g m −3 and PM 2.5 by 60  µ g m −3 . For the day-to-day variability, CMAQ reproducesthe observed Eastern China synchronous mode but not the north–south opposingmode of NO2 . Both models capture the day-to-day variability ofPM 2.5 better than that of NO2 . These results shed light onmodel improvement. The EOF–EEMD package is freelyavailable for noncommercial uses.

atmospheric chemistry and physics

Spatiotemporal variability of NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; and PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; over Eastern China: observational and model analyses with a novel statistical method