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. To improve the operational air quality forecasting over China, a newaerosol or gas-phase pollutants assimilation capability is developed within theWRFDA system using the three-dimensional variational (3DVAR) algorithm. In this first application, the interfacefor the MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) aerosol scheme is built with the potential for flexible extension. Basedon the new WRFDA-Chem system, five experiments assimilating differentsurface observations, including PM 2.5 , PM 10 , SO2 , NO2 , O3 , and CO, areconducted for January 2017 along with a control experiment without data assimilation (DA).Results show that the WRFDA-Chem system evidently improves the airquality forecasting. From the analysis aspect, the assimilation of surfaceobservations reduces the bias and RMSE in the initial condition (IC)remarkably; from the forecast aspect, better forecast performances areacquired up to 24 h, in which the experiment assimilating the six pollutantssimultaneously displays the best forecast skill overall. With respect to theimpact of the DA cycling frequency, the responses toward IC updating are found to be different among the pollutants. For PM 2.5 , PM 10 , SO2 , and CO, theforecast skills increase with the DA frequency. For O3 , althoughimprovements are acquired at the 6 h cycling frequency, the advantage ofmore frequent DA could be consumed by the disadvantages of the unbalancedphotochemistry (due to inaccurate precursor NOx ∕  VOC (volatile organic compound) ratios) or the changedtitration process (due to changed NO2 concentrations but not NO) fromassimilating the existing observations (only O3 and NO2 , but no VOC and NO). As yet the finding is based on the 00:00 UTC forecast for this winter season only,and O3 has strong diurnal and seasonal variations. More experiments shouldbe conducted to draw further conclusions. In addition, considering oneaspect (IC) in the model is corrected by DA, the deficiencies of otheraspects (e.g., chemical reactions) could be more evident. This studyexplores the model deficiencies by investigating the effects of assimilatinggaseous precursors on the forecast of related aerosols. Results show thatthe parameterization (uptake coefficients) in the newly addedsulfate–nitrate–ammonium (SNA)-relevant heterogeneous reactions in the model is not fully appropriate although it best simulates observed SNA aerosolswithout DA; since the uptake coefficients were originally tuned under theinaccurate gaseous precursor scenarios without DA, the biases from the twoaspects (SNA reactions and IC DA) were just compensated. In futurechemistry development, parameterizations (such as uptake coefficients) fordifferent gaseous precursor scenarios should be adjusted and verified withthe help of the DA technique. According to these results, DA ameliorates certainaspects by using observations as constraints and thus provides anopportunity to identify and diagnose the model deficiencies; it is usefulespecially when the uncertainties of various aspects are mixed up and thereaction paths are not clearly revealed. In the future, besides being usedto improve the forecast through updating IC, DA could be treated as anotherapproach to explore necessary developments in the model.

atmospheric chemistry and physics

Development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: aiming to improve air quality forecasting and diagnose model deficiencies