AS1.6
PICO: Fri, 28 Apr | PICO spot 5
AQ-WATCH (Air Quality: Worldwide Analysis and Forecasting of Atmospheric Composition for Health) is an international consortium, which co-develops and co-produces tailored products and services derived from space and in situ observational data for improving air quality forecasts and attribution. For this purpose, AQ-WATCH develops a supply chain leading to innovative downstream products and services for providing air quality information tailored to the identified needs of international users. This presentation will focus on one of the AQ-WATCH products, the AQ-WATCH air quality forecast system. Air quality forecast models provided by the AQ-WATCH consortium are set up for the focus regions in Asia and the Americas, based on the templates of Copernicus European and MarcoPolo-Panda Asian ensembles, but with much higher resolution and reliance on regional emission and observational information. The models are established over the focus regions using the meteorological and emission data taken from Copernicus repositories and other national archives and refined with local information wherever available. Each forecast model is then evaluated using local observational datasets and with the needs of the stakeholders. Machine learning workflows are being incorporated into the forecast system to improve both results from individual models and the model ensembles based on bias correction from observation data. Lessons learnt from model comparison in the focus regions will be presented. At last, the potential application of the system prototype, as well as the other AQ-WATCH products, namely the global and regional air quality atlas, the air quality attribution & mitigation, the dust and fire forecasts, and the fracking analysis tool, to other regions of the world will be discussed.
How to cite: Li, C. W. Y., Sofiev, M., Timmermans, R., Kranenburg, R., Pfister, G., Kumar, R., Deroubaix, A., Huneeus, N., Opazo, M., Caballero, T., Mo, D., Zhang, X., Leufen, L. H., Kleinert, F., Schultz, M., Granier, C., Basart, S., Salvi, O., Caillard, B., and Brasseur, G.: Introduction to the AQ-WATCH multi-model air quality forecast system, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15547, https://doi.org/10.5194/egusphere-egu23-15547, 2023.
While overall global warming with the causes and global processes connected to well-mixed CO2, and its impacts on global to continental scales are well understood with a high level of confidence, there are knowledge gaps concerning the impact of many other non-CO2radiative forcers leading to low confidence in the conclusions. This relates mainly to specific anthropogenic and natural precursor emissions of short-lived GHGs and aerosols and their precursors. These gaps and uncertainties also exist in their subsequent effects on atmospheric chemistry and climate, through direct emissions dependent on changes in e.g., agriculture production and technologies based on scenarios for future development as well as feedback of global warming on emissions, e.g., permafrost thaw. In addition to the atmospheric radiative forcing (gaseous or aerosols), albedo changes connected to land use and land cover can play a role, depending on the adaptation or mitigation measures included in different scenarios.
The main goal of the EC Horizon Europe project FOCI (from the call HORIZON-CL5-2021-D1-01-0 Improved understanding of greenhouse gas fluxes and radiative forcers, including carbon dioxide removal technologies), is to assess the impact of key radiative forcers, where and how they arise, the processes of their impact on the climate system, to find and test an efficient implementation of these processes into global Earth System Models and into Regional Climate Models, eventually coupled with CTMs, and finally to use the tools developed to investigate mitigation and/or adaptation policies incorporated in selected scenarios of future development targeted at Europe and other regions of the world. We will develop new regionally tuned scenarios based on improved emissions to assess the effects of non-CO2 forcers. Mutual interactions of the results and climate services producers and other end-users will provide feedback for the specific scenarios preparation and potential application to support the decision-making, including climate policy.
How to cite: Halenka, T. and Sokhi, R.: Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13739, https://doi.org/10.5194/egusphere-egu23-13739, 2023.
Including prognostic atmospheric composition (AC) simulations in numerical weather predication or climate modelling application to exploit AC – weather feedbacks is often prohibited by the high computational cost of adding complex AC simulation to the weather or climate model. There are in principle two approaches to solve this problem: (i) drastically reduce the complexity of the aerosol and chemistry simulations in the weather model, or (ii) safe cost by reducing the spatial resolution of the model components simulating the AC processes and implement a coupling mechanism.
At ECMWF a dual configuration forecast (dcfc) approach for the of the Integrated Forecasting System (IFS) has been developed based on the infrastructure for Object-Oriented Prediction System (OOPS). It enables the coupled simulation of a high-resolution application and a low-resolution application of the IFS and a coupling mechanism. The low-resolution model instance simulates the aerosol and chemistry-processes as activated for the operational AC forecasts by the Copernicus Atmosphere Monitoring Service (CAMS)
We show first scientific results of this dual configuration forecast (dcfc) for a sever dust storm event in Europe in March 2022. We will discuss to what extent and at what computational cost the dcfc application can forecast the meteorological impact of the dust on radiation and 2m temperatures. We will compare the dcfc result to the more expensive integrated IFS-CAMS configuration as well as to NWP forecast using the aerosol climatology as currently applied in the ECMWF operational weather forecasts.
How to cite: Flemming, J. and Hamrud, M.: A multiple gird approach for atmospheric composition - aware NWP forecasts with the ECMWF forecast system, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17501, https://doi.org/10.5194/egusphere-egu23-17501, 2023.
In this study, a global variable-resolution modeling framework of atmospheric dust and its radiative feedback is introduced and evaluated. In this model, atmospheric dust is simulated simultaneously with the meteorological fields, and dust-radiation interaction is included. Five configurations of global mesh with the refinement at different resolutions and over different regions of interest are used to explore the impacts of regional refinement on modeling dust lifecycle at regional and global scales. The model produces reasonably the overall magnitudes and spatial variabilities of global dust metrics such as surface mass concentration, total deposition, AOD, and radiative forcing compared to observations and previous modeling results. Two global variable-resolution simulations with mesh refinement over major deserts of North Africa (V16km-NA) and East Asia (V16km-EA) simulates less dust emissions and smaller dry deposition rate inside the refined regions due to the weakend near-surface wind speed caused by better resolved topographic complexity at higher resolution. Dust mass loading over North Africa is close to each other between V16km-NA and U120km, while over East Asia, V16km-EA simulates higher dust mass loading. Over the non-refined areas with the same resolution, the difference between global variable-resolution and uniform-resolution experiments also exist, which is partly related to their difference in dynamic time-step and the coefficient for horizontal diffusion. Refinement at convection-permitting resolution around the Tibet Plateau (TP) leads to significantly different dust and precipitation around the TP against coarse resolution, which implies that dust-precipitation interaction over this area deserves further investigation with this global variable-resolution modeling framework in future.
How to cite: Zhao, C., Feng, J., Du, Q., Xu, M., Gu, J., and Hu, Z.: Simulating atmospheric dust and its radiative impact with a global variable-resolution model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3730, https://doi.org/10.5194/egusphere-egu23-3730, 2023.
The Chinese Meteorology Administration chemistry model CUACE is online integrated into the mesoscale operational weather prediction (NWP) model (GRAPES_Meso5.1) and aerosol-cloud-radiation interaction is achieved to establish the first version (V1) of chemistry-weather (CW) interacted model GRAPES-Meso5.1/CUACE CW V1. The most polluted winter 2016-2017 is selected to study the meteorology impacts on haze/fog prediction, the impact of aerosol-radiation, aerosol-cloud and CW interaction (ARI, ACI, CWI) on haze/fog prediction and NWP. Single way model without CWI displays reasonable PM 2.5 and visibility prediction in general. However, modeled PM2.5 peaks are underestimated and visibility valleys are overestimated during haze/fog pollution, the underestimation of relative humidity (RH) contributes major to this misestimation; CWI model cut the negative bias of PM 2.5 peaks and the positive bias of visibility valleys. The improvement of 5km and 3km low visibility by CWI during severe haze/fog period is more obvious than that of 10 km, which just compensates for the largest deficiency in low visibility prediction related with severe haze/fog by single way model; The NWP including sea level pressures, relative humidity(RH), temperature, wind speed are also improved by CWI from surface to upper troposphere; ARI contributes larger to the predicted PM2.5 ,visibility and NWP improvement than that of ACI, their relative contributions varies with model vertical height and the overlapping condition of cloud and aerosols. Due to the joint contribution of RH and PM2.5, CWI’s improving on visibility is larger than PM2.5. This study illustrates the importance of including CWI in air quality prediction model.
How to cite: Wang, H.: Chemistry-Weather Interacted Model System GRAPES_Meso5.1/CUACE CW V1.0: Development, Evaluation and Application in Better Haze/fog Prediction in China, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4025, https://doi.org/10.5194/egusphere-egu23-4025, 2023.
Aerosols play a significant role in the radiation and atmospheric precipitation physics of microphysics and convection, and have a significant impact on air quality, visibility, public health, aviation, and climate. A physics suite, which includes the aerosol-aware double momentum Thompson-Eidhammer microphysics scheme (TH-E MP), the scale-aware and aerosol-aware Grell-Freitas (GF) convection scheme, and the MYNN-EDMF boundary layer and shallow cloud scheme, was developed at NOAA Global System Laboratory (GSL). The GSL physics suite is applied in the FV3GFS global model and the Rapid Refresh Forecast System (RRFS) regional model. We also developed the RRFS – Smoke and Dust model (RRFS-SD) at NOAA GSL with the Common Community Physics Package (CCPP), which is designed to facilitate a host-model agnostic implementation of physics parameterizations. Because of the interactive and strongly coupled nature of chemistry and physics, it is natural to allow for the smoke, dust and other chemical modules to be called directly from the physics suite. Here we embedded the plume rise modules for wildfire, sea-salt, dust, and anthropogenic emission modules into the regional model of RRFS and global UFS model using CCPP as subroutines of physics. The prognostic emissions of sea-salt, and organic carbon are combined to represent the “water friendly” aerosol emission, while the prognostic emission of dust is used to represent “ice friendly” aerosol emission for TH-E MP. With this implementation, we examined the aerosol indirect feedback when using the TH-E scheme in the global FV3GFS forecast with C768 (~13km) horizontal resolution and 127 vertical levels. There are significant cloud-radiation responses to the aerosol differences, and the severely positive precipitation bias over Europe and North America is significantly alleviated when applying this aerosol emission method for indirect feedback. We also examined the smoke direct feedback to the radiation in the RRFS-SD with 3km horizontal resolution and 64 vertical layers for September, 2020 during which the western US experienced extreme wildfires. The aerosol direct feedback run significantly improves the forecast of aerosol optical depth, surface 2m air temperature, 10m wind speed, and radiation fluxes.
How to cite: Li, H., Grell, G., Ahmadov, R., Romero-Alvarez, J., Zhang, L., James, E., Baker, B., Olson, J., Sun, S., Schnell, J., and Wang, N.: Indirect and direct aerosol feedback in the global and regional scale NOAA UFS Weather Model , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3983, https://doi.org/10.5194/egusphere-egu23-3983, 2023.
How to cite: Zhang, W., Wang, H., and Zhang, X.: Aerosol–cloud interaction in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on mesoscale numerical weather prediction under haze pollution conditions in Jing–Jin–Ji in China , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4146, https://doi.org/10.5194/egusphere-egu23-4146, 2023.
We investigate the aerosol direct and semi-direct effect on subseasonal prediction using NOAA’s fully coupled Unified Forecast System (UFS) model, which includes the atmospheric model FV3 with the Global Forecast System (GFS) physics package V17, MOM6 ocean model, WW3 wave model and CICE6 sea ice model. A systematic twin experiment is carried out: (i) UFS with prescribed aerosol climatology and (ii) UFS coupled to interactive aerosols from the GOCART aerosol module. Both experiments are deterministic 32-day hindcasts with monthly initialization over multiple years.
The modeled aerosol optical depth (AOD) in both experiments is in good agreement with the MODIS satellite observations. The AOD from the experiments with interactive aerosols captured the interannual variability seen in the observations. The estimated radiative forcing from the aerosol radiation interaction in these two sets of experiments is similar in the multi-year average. However, the advantage in the experiments with interactive aerosols can be seen clearly when simulating radiative forcing in the extreme dust storm and biomass burning events. Changes in cloud and precipitation are small between these two sets of experiments.
How to cite: Sun, S., Frost, G., Grell, G., Zhang, L., Baker, B., Meixner, J., and Cheng, A.: Simulating direct and semi-direct effect of aerosols on subseasonal prediction: climatology versus interactive aerosols in the UFS model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11392, https://doi.org/10.5194/egusphere-egu23-11392, 2023.
The Integrated Forecasting System (IFS) of ECMWF is core of the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including reactive gases, as well as aerosol and greenhouse gases. The CAMS global model consists of the aerosol model of the IFS, IFS-AER, which is a sectional-bulk scheme, while the chemistry scheme is based on a CB05-based carbon-bond mechanism, with the option to couple this to BASCOE-based stratospheric chemistry. The composition model is updated regularly, aligned with updates of ECMWF’s operational meteorological model. Here we report on updates planned for the operational version after next, referred to as CY49R1. This concerns revisions on a large range of topics, as developed over the recent years, and therefore impacting many aspects of chemistry and aerosol composition in troposphere and stratosphere. Main aspects concern:
- A review of the representation of polar stratospheric clouds and of their impact on stratospheric ozone,
- An extension of IFS-AER to represent stratospheric sulfate aerosols, coupled with CB05 and BASCOE precursor gases,
- An upgrade of gas-particle partitioning through the implementation of EQSAM4Clim in the IFS,
- Computation of aerosol, cloud and rain pH, and use of the update pH values in aqueous chemistry,
- A combined representation of aerosols and chemistry deposition processes (wet and dry),
- Update of aerosol optics, including a simple representation of dust asphericity and hygroscopic growth,
- Update of PM diagnostic output
In this contribution we provide an overview of expected changes with emphasis on changes in composition modeling aspects. We will present their expected impact on key atmospheric composition aspects, including air quality performance across major pollution regions across the world, aerosol optical depth, dust, and stratospheric composition products.
How to cite: Remy, S., Huijnen, V., Simon, C., Metzger, S., Williams, J., Minganti, D., Bingen, C., Alexe, M., and Flemming, J.: Changes to the IFS atmospheric composition model in support to the CAMS update for CY49R1., EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15355, https://doi.org/10.5194/egusphere-egu23-15355, 2023.
The ECMWF’s Integrated Forecast System (IFS) is the global atmospheric model used by the Copernicus Atmospheric Monitoring Service (CAMS) to provide analyses and forecasts on atmospheric composition. Currently, the CAMS global model includes the aerosol model of the IFS, the aerosol module IFS-AER making use of a sectional-bulk scheme, and the chemistry scheme based on a CB05-based carbon-bond mechanism, with the option to couple this to stratospheric chemistry module BASCOE. The combined BASCOE will be used operationally in the CAMS global system starting from the upgrade to cycle 48R1 planned in June 2023. This abstract focuses on further developments related to stratospheric chemistry and aerosols that are to be implemented in the future operational cycle 49R1, as well as on a first evaluation of IFS’ performances in representing stratospheric aerosols and chemistry against different datasets.
Initially focussing on the troposphere, IFS-AER has been extended to include and represent stratospheric sulfate aerosol processes, keeping the existing tracers. The extended IFS-AER(strato) has been coupled to IFS(BASCOE) through the gaseous sulphuric acid tracer, to the IFS radiation scheme, and to the 4Dvar assimilation scheme. The evaluation of aerosol aspects makes use of aerosol datasets (aerosol extinction, AOD, …) from the Global Ozone Monitoring by Occultation of Stars (GOMOS, onboard Envisat), and the Global Space-based Stratospheric Aerosol Climatology (GloSSAC), based on different cases studies including quiescent and (highly) volcanic periods. It has also been tested against reference simulations from WACCM-CARMA. These intercomparisons show a reasonable agreement against retrieval datasets such as GloSSAC and reference simulations from WACCM-CARMA. In quiescent conditions, the new system showed a decreasing trend with respect to the reference datasets.
BASCOE includes a simple PSC parameterization, which has been updated and tuned in cycle 49R1. In order to assess the impact of this upgrade, we evaluate the composition of the polar lower stratosphere during the winter-spring seasons ("ozone hole" events) of 2008, 2009 and 2020 above the Antarctic and 2009, 2011, 2012 and 2020 above the Arctic, with a focus on 5 key species observed by Aura-MLS. This evaluation demonstrates the capacity of IFS(BASCOE) to forecast the chemical composition of the polar lower stratosphere above both the Arctic and the Antarctic for several years with very different evolution of the polar vortex. While further improvements are desirable and will require an overhaul of the PSC parameterization, the current performance allows us to study the interannual variability of ozone hole episodes.
How to cite: Bingen, C., Chabrillat, S., Errera, Q., Huijnen, V., Metzger, S., Minganti, D., Rémy, S., Williams, J., and Flemming, J.: Extension and evaluation of the Integrated Forecast System (IFS) cycle 49R1 to stratospheric aerosols and chemistry for the global Copernicus Atmospheric Monitoring Service (CAMS), EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15869, https://doi.org/10.5194/egusphere-egu23-15869, 2023.
Southeastern Brazil is the most developed and populous region with 89.5 million of inhabitants, according to the Instituto Brasileiro de Geografia e Estatística (IBGE) for 2021. The main metropolitan and industrialized areas are concentrated in its four states (São Paulo, Minas Gerais, Rio de Janeiro and Espírito Santo). One of them comprises the Metropolitan Area of São Paulo (MASP) with 7.3 million vehicles that releases air pollutant -gas and ultrafine particles- to the atmosphere due to the use of different fuel types; light-duty vehicles consume ethanol, gasohol (85% gasoline and 25% hydrous ethanol) or natural gas, and heavy vehicles (i.e., buses and trucks) run on diesel. So, frequently high concentrations of air pollutants (ozone and fine particles) in urban areas are above the recommended limits suggested by the World Health Organization (WHO) with high health risk mainly for children and elderly. The biggest concern is the high health risk of exposing the population to ultrafine particles, also called nanoparticles. Consequently, it is important to understand the formation of ultrafine particles, whether they are emitted directly or formed in the atmosphere.
We study the formation processes of ultrafine particles in the scenario of fuel change in the road transport sector, including a greater use of biofuels. The air quality modeling system will analyze the impact of different scenarios in urban areas in southeastern Brazil. We begin with the air quality simulation for the current conditions as the base case scenario using the WRF-Chem model. As the main data input, we use emission data with two temporal profile distributions (monthly and hourly time average). First, we use available monthly anthropogenic emission's data processed by the European Copernicus Atmosphere Service (CAMS). Secondly, we added hourly road transport emission calculated with the LAPAT model, which use emission factors derived from measurements in experimental campaigns in tunnels where light and heavy vehicles circulate within the MASP. This simulation test with the WRF-Chem model considers the MOZART-MOSAIC mechanism and additional emissions from other sources such as biomass burning and chemical initial and boundary conditions from the CAM-Chem model. Experimental data and measurements of meteorological and air quality parameters will support the work to evaluate the performance of the model’s results.
How to cite: Delgado Peralta, A. H. and Andrade, M. D. F.: Impact of the use of biofuels on the formation of ultrafine particles in southeastern Brazil, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16081, https://doi.org/10.5194/egusphere-egu23-16081, 2023.
The Integrated Forecasting System (IFS) of ECMWF is used within the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including aerosols as well as reactive trace gases and greenhouse gases. Inorganic gas/aerosol equilibrium involving the major sulphate and nitrate anions, i.e., H2SO4/HSO4-/SO42- and HNO3/NO3-, largely determines the aerosol acidity, while the gas/liquid/solid phase partitioning of semi-volatile cations, NH3/NH4+, and the liquid/solid partitioning of non-volatile mineral cations, particularly Ca2+, Mg2+, and K+, overall control the gas-liquid-solid aerosol equilibrium partitioning of reactive nitrogen compounds. For the NO3- and NH4+ equilibrium, our recent developments have focused on EQSAM4Clim, which has been recently integrated into the IFS as a computationally efficient means of describing aerosol pH in a global modeling system.
EQSAM4Clim is used in the IFS to estimate gas-liquid-solid partitioning and the aerosol associated liquid water content, which is subsequently used to estimate the associated aerosol, cloud and rain acidity. The aerosol, cloud and rain pH is computed by considering the liquid water (H2O) content in the respective liquid water phase using either the aerosol associated water computed by EQSAM4clim, and if present, the cloud and/or rain water of the IFS. The pH is coupled to the aqueous phase chemistry in IFS(CB05) and in the wet deposition of SO2 and NH3, which in-turn affects the aerosol composition through changes in the SO2/SO42-, NH3/NH4+and HNO3/NO3- partitioning, the aerosol associated liquid water content and solution pH.
Here we present first results of the of the impact of improved aerosol acidity in the solution (aerosol/cloud/rain water) on PM2.5 forecasts simulated in the IFS which are subject to gas-particle partitioning. In particular, the NH4+, NO3- and SO42- concentrations have been compared against observational datasets at the surface, showing promising improvements as a direct result of the new pH computations. When coupling the EQSAMClim pH into the aqueous phase chemistry routine, the surface concentrations of SO42- and the SO2 + SO42- wet deposition fluxes are improved over most of Europe, but degraded over parts of US. The relative impact of the improved pH appears generally small as compared to other related changes such as updates in aqueous chemistry rates. In the pH coupling, the aqueous chemistry component dominates the impact on the wet deposition of SO2/NH3. All of these results are highly dependent on the emissions input (SO2/NOx/NH3).
How to cite: Metzger, S., Rémy, S., Huijnen, V., Williams, J., Chabrillat, S., Bingen, C., and Flemming, J.: Impact of pH computation from EQSAM4Clim on inorganic aerosols in the CAMS system, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16085, https://doi.org/10.5194/egusphere-egu23-16085, 2023.
A global aerosol data assimilation (DA) system based on the ensemble-variational (EnVar) application in the Joint Efforts for Data assimilation Integration (JEDI) was recently developed for the Global Ensemble Forecast System - Aerosols (GEFS-Aerosols) in operations at NOAA/NWS/NCEP. The aerosol optical depth (AOD) retrievals at 550 nm are assimilated to improve the GEFS-Aerosols initial conditions and its subsequent forecasts. To account for aerosol emission uncertainty in the ensemble forecasts and thus enhance AOD assimilation, a stochastically-perturbed emission (SPE) approach was implemented in the Common Community Physics Package (CCPP)-based GEFS-Aerosols. The performance of this JEDI-based EnVar aerosol DA system has been evaluated using the CCPP-based GEFS-Aerosols in the near-real time (NRT) experiments at NOAA/OAR/GSL and the global aerosol reanalysis products that assimilate 550 nm AOD retrievals from the the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, respectively. The NRT experiment results are displayed on the GSL website (https://ruc.noaa.gov/projects/nrt/Aerosol-DA/). Both the NRT experiment results and global aerosol reanalyses demonstrate that compared to the six-hour forecasts without AOD assimilation, the analyses and subsequent six-hour forecasts resulting from AOD assimilation show significantly improved agreement with AOD retrievals from VIIRS, MODIS and the Aerosol Robotic NETwork (AERONET), and AOD analyses/reanalyses from NASA and ECMWF. Although AOD retrievals, due to their column-integral nature, provide limited information regarding aerosol compositions and vertical profiles, AOD assimilation in our experiments generally contributes to improved aerosol analyses and forecasts verified against those from NASA and ECMWF.
One of the ongoing Unified Forecast System (UFS)-Research to Operations (R2O) efforts aims to integrate and improve aerosol prediction within UFS (hereafter referred to as UFS-Aerosols). UFS-Aerosols will eventually replace the standalone GEFS-Aerosols for operations at NOAA/NWS/NCEP. Compared to GEFS-Aerosols, UFS-Aerosols is coupled with NASA's second-generation Goddard Chemistry Aerosol Radiation and Transport (GOCART) model including additional nitrate aerosol species, adopts improved biomass burning and dust emissions, and allows for aerosol-radiation interactions. Motivated by the promising results of assimilating AOD for GEFS-Aerosols and to advance aerosol assimilation and prediction in UFS, we are extending and improving this JEDI-based EnVar aerosol DA system for UFS-Aerosols. It requires further development of AOD forward operator, its tangent linear and adjoint models in JEDI’s Unified Forward Operator (UFO) to accommodate additional nitrate aerosol species in UFS-Aerosols. Enhancements to this DA system for UFS-Aerosols include implementing SPE within UFS-Aerosols to improve background ensemble and implementing assimilation of log-transformed AOD within JEDI to better satisfy the Gaussian assumptions in the DA update. To evaluate these new developments for UFS-Aerosols, cycled DA experiments will be performed to assimilate 550 nm AOD retrievals from VIIRS instruments on board NOAA’s satellites, and verified against various aerosol observations and reanalyses. Results will be presented.
How to cite: Huang, B., Pagowski, M., Martin, C., Tangborn, A., Abdi-Oskouei, M., E. Barré, J., Kondragunta, S., Grell, G., and Frost, G.: Extending and Improving JEDI-based Global Aerosol Data Assimilation System for UFS-Aerosols, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17426, https://doi.org/10.5194/egusphere-egu23-17426, 2023.
Through a NERC/MOES funded project, PROMOTE, analysis based on WRF and CMAQ models has been conducted to understand the impact of road transport emissions on air quality over Delhi. NCEP/FNL 1 data was used to drive WRF with four nested domains over India with resolutions of 45km, 15 km, 5 km, and 1.6 km for 2018. EDGAR v5.0 emission inventory (for 2015) 2 and Cam-Chem initial and boundary condition data 3 were used to drive the CMAQ model. In the baseline runs, all domains were considered without any change in emissions, while in Scenario 1, road transport sector was removed in the third domain (5km) covering Delhi region. Model performance for NOx, NO2, PM10, PM2.5 and O3 was evaluated with available observations, recognising that air quality and meteorological datasets were limited for the period analysed. In the later part of the study, OSCAR model 4 was used to predict the high-resolution air quality over Delhi and estimate the contributions from road transport emissions. Relative contributions to Delhi's air quality from local and regional long range transport sources are discussed.
As part of a NERC funded COP26 project on Climate Adaptation for India, an overarching goal of this study is to quantify how air quality changes in South Asia in a changing climate under SSP245 (middle-of-the-road scenario) 5. A dynamical downscaling process was implemented and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) data 6 was used to drive Weather Research and Forecasting (WRF) model simulations. Simulations have been conducted for the South Asia-Cordex domain for 2015 (representative of 2011-2020 years) and 2050 (representative of 2046-2055 years) with a 27 km grid resolution. The Community Multiscale Air Quality (CMAQ) model was driven with an average of ten years meteorology with future land use land cover, initial and boundary conditions, and future emissions 7 for India. To assess the impact of averaged meteorology on the CMAQ performance, the CMAQ model was run with both ten years' averaged meteorology around 2015 (2011-2020) and only 2015 meteorology.
Although averaging ten years around the desired year suppresses the diurnal variations, it provides an indication of monthly changes in climate and air quality variables. Under the selected SSP245 scenario, the CMAQ model predicted monthly means of PM2.5 anomalies (2050-2015) range over India between 8 to 41 μg/m3. Significant change is PM2.5, PM10, NOx, and O3 anomalies, especially in the urban regions of India, such as Delhi, before and after the Monsoon months (June to October) have been observed.
Financial Support: We acknowledge funding from NERC/MOES (Reference: NE/P016391/1) for the PROMOTE project and NERC funding (Reference: 2021COPA&R48Sokhi) for the COP26 Improving adaptation strategies for climate extremes and air pollution affecting India project.
References
1 NCEP/NOAA/U.S. 2015, https://doi.org/10.5065/D65Q4T4Z.
2 Crippa M. et al. (2019): http://data.europa.eu/89h/377801af-b094-4943-8fdc-f79a7c0c2d19
3 Buchholz, R. R. et al, (2019). https://doi.org/10.5065/NMP7-EP60
4 Singh V, et al. (2020) Environmental Pollution, 257, 113623
5 van Vuuren, D.P. et al. (2011). Climatic Change 109, 5. https://doi.org/10.1007/s10584-011-0148-z
6 Xu, Z. et al. (2021). Sci Data 8, 293. https://doi.org/10.1038/s41597-021-01079-3
7 SMoG-India v1 2015 and 2050 emissions dataset, NERC project.
How to cite: Alyuz, U., Sokhi, R., Momoh, K., Singh, V., Venkataraman, C., Sharma, A., Gupta, G., Tibrewal, K., Khaiwal, R., Mor, S., and Beig, G. and the PROMOTE Team: High-resolution dynamical downscaling of present and future air quality over the South Asia-Cordex domain with a focus on the megacity Delhi, India, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17561, https://doi.org/10.5194/egusphere-egu23-17561, 2023.
