Regional evaluation of the performance of the global CAMS chemical modeling system over the United States (IFS cycle 47r1)

The Copernicus Atmosphere Monitoring Service (CAMS) provides routine analyses and forecasts of trace gases and aerosols on a global scale. The core is ECMWF’s Integrated Forecast System (IFS), where modules for atmospheric chemistry and aerosols have been introduced, and which allows data-assimilation of satellite retrievals of composition. We have updated both the homogeneous and heterogeneous NOx chemistry applied in the three independent tropospheric-stratospheric chemistry modules maintained within CAMS, referred to as IFS(CB05BASCOE), IFS(MOCAGE) and IFS(MOZART). Here we focus on the evaluation of main trace gas products from these modules that are of interest as markers of air quality, namely lower tropospheric O3, NO2 and CO, with a regional focus over the contiguous United States without data assimilation. Evaluation against lower tropospheric composition reveals overall good performance, with chemically induced biases within 10 ppb across species across regions within the US with respect to a range of observations. The versions show overall equal or better performance than the CAMS Reanalysis. Evaluation of surface air quality aspects shows that annual cycles are captured well, albeit with variable seasonal biases. During wintertime conditions there is a large model spread between chemistry schemes in lower-tropospheric O3 (~10–35 %) and, in turn, oxidative capacity related to NOx lifetime differences. Analysis of differences in the HNO3 and PAN formation, which act as reservoirs for reactive nitrogen, revealed a general underestimate in PAN formation over polluted regions likely due to too low organic precursors. Particularly during wintertime, the fraction of NO2 sequestered into PAN has a variability of 100 % across chemistry modules indicating the need for further constraints. Notably a considerable uncertainty in HNO3 formation associated with wintertime N2O5 conversion on wet particle surfaces remains. In summary this study has indicated that the chemically induced differences in the quality of CAMS forecast products over the United States depends on season, trace gas, altitude and region. Whilst analysis of the three chemistry modules in CAMS provide a strong handle on uncertainties associated with chemistry modeling, the further improvement of operational products additionally requires coordinated development involving emissions handling, chemistry and aerosol modeling, complemented with data-assimilation efforts.

Introducing the MISR level 2 near real-time aerosol product

Atmospheric aerosols are an important element of Earth's climate system and have significant impacts on the environment and on human health. Global aerosol modeling has been increasingly used for operational forecasting and as support for decision making. For example, aerosol analyses and forecasts are routinely used to provide air quality information and alerts in both civilian and military applications. The growing demand for operational aerosol forecasting calls for additional observational data that can be assimilated into models to improve model accuracy and predictive skill. These factors have motivated the development, testing, and release of a new near real-time (NRT) level 2 (L2) aerosol product from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra platform. The NRT product capitalizes on the unique attributes of the MISR aerosol retrieval approach and product contents, such as reliable aerosol optical depth as well as aerosol microphysical information. Several modifications are described that allow for rapid product generation within a 3 h window following acquisition of the satellite observations. Implications for the product quality and consistency are discussed and compared to the current operational L2 MISR aerosol product. Several ways of implementing additional use-specific retrieval screenings are also highlighted.

Evaluation and Bias Correction of the Secondary Inorganic Aerosol Modeling over North China Plain in Autumn and Winter

Secondary inorganic aerosol (SIA) is the key driving factor of fine-particle explosive growth (FPEG) events, which are frequently observed in North China Plain. However, the SIA simulations remain highly uncertain over East Asia. To further investigate this issue, SIA modeling over North China Plain with the 15 km resolution Nested Air Quality Prediction Model System (NAQPMS) was performed from October 2017 to March 2018. Surface observations of SIA at 28 sites were obtained to evaluate the model, which confirmed the biases in the SIA modeling. To identify the source of these biases and reduce them, uncertainty analysis was performed by evaluating the heterogeneous chemical reactions in the model and conducting sensitivity tests on the different reactions. The results suggest that the omission of the SO2 heterogeneous chemical reaction involving anthropogenic aerosols in the model is probably the key reason for the systematic underestimation of sulfate during the winter season. The uptake coefficient of the “renoxification” reaction is a key source of uncertainty in nitrate simulations, and it is likely to be overestimated by the NAQPMS. Consideration of the SO2 heterogeneous reaction involving anthropogenic aerosols and optimization of the uptake coefficient of the “renoxification” reaction in the model suitably reproduced the temporal and spatial variations in sulfate, nitrate and ammonium over North China Plain. The biases in the simulations of sulfate, nitrate, ammonium, and particulate matter smaller than 2.5 μm (PM2.5) were reduced by 84.2%, 54.8%, 81.8%, and 80.9%, respectively. The results of this study provide a reference for the reduction in the model bias of SIA and PM2.5 and improvement of the simulation of heterogeneous chemical processes.

Air Quality in East Asia during the heavy haze event period of 10 to 15 January 2013

A prolonged heavy haze event that has caused for the Environmental Protection Bureau (EPB) in Beijing to take emergency measures for the protection of the public health and the reduction of air pollution damages in China has been analyzed with the use of the Aerosol modeling System (AMS) to identify causes of this event. It is found that the heavy haze event is associated with high aerosols and water droplets concentrations. These high aerosol concentrations are mainly composed of anthropogenic aerosols, especially secondary inorganic aerosols formed by gas-to-particle conversion of gaseous pollutants in the eastern part of China whereas those in the northeastern parts of China are composed of the mixture of the anthropogenic aerosols and the Asian dust aerosol originated from the dust source regions of northern China and Mongolia. These high aerosol concentrations are found to be subsequently transported to the downwind regions of the Korean Peninsula and Japan causing a prolonged haze event there. It is also found that the Asian dust aerosol originated from northern China and Mongolia and the anthropogenic aerosols produced by chemical reactions of pollutants in the high emissions region of eastern China can cause significantly adverse environmental impacts in the whole Asian region by increased atmospheric aerosol loadings that may cause respiration diseases and visibility reduction and by excess deposition of aerosols causing adverse impacts on terrestrial and marine eco-systems.

Introducing the MISR Level 2 Near Real-Time Aerosol Product

Atmospheric aerosols are an important element of Earth’s climate system, and have significant impacts on the environment and on human health. Global aerosol modeling has been increasingly used for operational forecasting and as support to decision making. For example, aerosol analyses and forecasts are routinely used to provide air quality information and alerts in both civilian and military applications. The growing demand for operational aerosol forecasting calls for additional observational data that can be assimilated into models to improve model accuracy and predictive skill. These factors have motivated the development, testing, and release of a new near real-time (NRT) level 2 (L2) aerosol product from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA’s Terra platform. The NRT product capitalizes on the unique attributes of the MISR aerosol retrieval approach and product contents, such as reliable aerosol optical depth as well as aerosol microphysical information. Several modifications are described that allow for rapid product generation within a three-hour window following acquisition of the satellite observations. Implications for the product quality and consistency are discussed as compared to the current operational L2 MISR aerosol product. Several ways of implementing additional use-specific retrieval screenings are also highlighted.

Stratospheric chemistry and aerosol modeling in CAMS with the IFS-CB05-BASCOE-GLOMAP (ICBG) system: evaluation in quiescent conditions and in a volcanic eruption.

<p>We present interactive stratospheric aerosol simulations with the ICBG system, a  global tropospheric-stratospheric combined aerosol-chemistry model which is an extension to the ECMWF Integrated Forecasting System (IFS), and is developed as part of the Copernicus Atmosphere Monitoring Service (CAMS). ICBG is the result of the merging of two existing CAMS configurations of the IFS:</p><ul><li>The IFS-GLOMAP tropospheric-stratospheric aerosol microphysics system, which has the GLOMAP-mode aerosol scheme configured for forecast-cycling experiments within the IFS,</li> <li>The IFS-CB05-BASCOE tropospheric (CB05) – stratospheric (BASCOE) chemistry scheme, which is also an established configuration of the IFS within CAMS.</li> </ul><p>During the first phase of CAMS, the stratospheric chemistry scheme IFS-BASCOE was extended to include the stratospheric sulphur chemistry from the UM-UKCA model, with sulphuric acid production rates from IFS-BASCOE passed each timestep to the aerosol scheme IFS-GLOMAP for aerosol particle nucleation and condensation. The aerosol surface area densities (SAD) simulated by IFS-GLOMAP simulated are similarly passed each timestep to the stratospheric chemistry scheme IFS-BASCOE for  heterogeneous reactions. In a recent progression of this strato-tropospheric modelling system, the climatology for meteoric smoke particles (MSP) used in UM-UKCA has also been implemented. Thus the simulated stratospheric aerosol layer comprises not only pure sulphuric particles nucleated homogeneously but also meteoric-sulphuric particles formed from the MSPs.</p><p>We  evaluate the simulated stratosphere aerosol layer in quiescent conditions, comparing it to SAGE-II measurements from the 1998-2002 period. The simulated stratospheric sulfate burden, aerosol extinction, stratospheric aerosol optical depth (sAOD) and surface area density (SAD) agree well with the SAGE-II retrievals. We also show results from ICBG simulations of the volcanic aerosol cloud from a large-magnitude tropical eruption (Pinatubo, June 1991, VEI6) and a medium-magnitude eruption at a northern mid-latitude (Raikoke, June 2019, VEI4).</p>

Evaluation of multi-component ensemble simulation of PM2.5 in the Pearl River Delta region

<p>Sulfate, nitrate, ammonium, organic carbon and black carbon are the key components of PM<sub>2.5</sub>, but their simulations are still facing high uncertainty. Exploring the sources of such uncertainty is important for the modeling of PM<sub>2.5</sub> and the understanding of atmospheric chemical processes. This study aims to evaluate and investigate the modeling uncertainty of these aerosols over Pearl River Delta (PRD) region based on Monte Carlo simulations of a Nested Air Quality Prediction Modeling System (NAQPMS) during 2015. Emission inventory as one of the most important uncertainty sources are perturbed according to their uncertainties to derive 50 ensemble simulations of NAQPMS with 15km horizontal resolution. The surface observations of sulfate, nitrate, ammonium, OC and BC from 10 sites in PRD region for one year are used to evaluation the performance of the ensemble mean estimation of the simulations. The results suggested that the ensemble mean could well reproduce the spatial and temporal variations of nitrate, ammonium, OC and BC with the correlation coefficients above 0.74 and their mean bias less than 2μg·m<sup>-3</sup> . However, the model has poor skills in the sulfate modeling with the correlation coefficients 0.26 and remarkable underestimation in winter. Further analysis for such modeling uncertainties suggested that the uncertainties in emissions can explain most of modeling uncertainties for BC and OC. However, the biases in sulfate and ammonium modeling especially during the wintertime are probably caused by the uncertainty in heterogeneous reaction modeling. The above results provide an overall assessment of the uncertainty in inorganic aerosol modeling over PRD region and can serve a basis for its simulation improvement.</p>

Development of Ensemble-based Assimilation System for Aerosol Forecasting and Reanalysis at NOAA

<p>In 2016 NOAA chose the FV3 (Finite Volume) dynamical core as a basis for its future global modeling system. For aerosol modeling this dynamical core was supplemented with GFS (Global Forecast System) physics and coupled through an interface with GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) parameterization. The assimilation methodology relies on a hybrid variational-ensemble approach within the newly developed model-agnostic JEDI (Joint Effort for Data assimilation Integration) framework. Observations include 550 nm AOD retrievals from VIIRS (Visible Infrared Imaging Radiometer Suite) instruments on polar-orbiting  SNPP and NOAA-20 satellites. The system is under development and early its results are compared with NASA'a MERRA-2 and ECMWF's CAMSiRA reanalyses.  </p><p> </p>