AS3.18 | Atmospheric Composition and Numerical Weather Forecasting
Atmospheric Composition and Numerical Weather Forecasting
Co-sponsored by WMO and CAMS
Convener: Johannes Flemming | Co-conveners: Georg Grell, Lu Ren, Alexander Baklanov
| Tue, 16 Apr, 16:15–18:00 (CEST)
Room M1
Posters on site
| Attendance Wed, 17 Apr, 10:45–12:30 (CEST) | Display Wed, 17 Apr, 08:30–12:30
Hall X5
Posters virtual
| Attendance Wed, 17 Apr, 14:00–15:45 (CEST) | Display Wed, 17 Apr, 08:30–18:00
vHall X5
Orals |
Tue, 16:15
Wed, 10:45
Wed, 14:00
The weather and atmospheric composition (AC) are closely related. Still, Numerical Weather Prediction (NWP) and AC forecasts are often operated independently. However, recognizing the scientific and operational benefits of combining NWP and AC forecasting and data assimilation, integrated AC-NWP systems for global, regional, and local applications have been developed.

We invite contributions on all aspects of forecasting and data assimilation of aerosols, reactive gases, greenhouse gases, and weather or stratospheric dynamics across different time scales. Our focus is on the scientific, computational, and societal advantages of such integrated approaches. Specifically, but not exclusively, we invite papers addressing the following topics:

a) Improved NWP from short timescales to seasonal scales due to feedbacks between aerosols, chemistry and radiation and cloud physics,

b) Parameterization of weather-composition feedbacks in radiation and cloud physics,

c) Impact of the uncertainty of meteorological simulations on AC predictions,

d) Advancements in designing and developing operational coupled NWP-AC prediction systems,

e) Satellite retrievals of meteorological variables in the presence of aerosols,

f) Data assimilation developments for AC and NWP,

g) Forecasting of stratospheric composition and dynamics after large volcanic eruptions such as the Hunga-Tonga,

h) Combined impact of environmental hazards on society, such as air pollution and high-impact weather, wildfires, dust storms and the underlying meteorological factors,

i) Evaluation, validation, and applications of NWP-AC predication systems.

This Session is organized in cooperation with the Copernicus Atmosphere Monitoring Service (CAMS) and the Global Air Quality Forecasting and Information Systems (GAFIS) initiative and the Modeling Applications Science Advisory Group (SAG-APP) of the WMO Global Atmosphere Watch (GAW) Program.

Orals: Tue, 16 Apr | Room M1

Chairpersons: Johannes Flemming, Georg Grell, Alexander Baklanov
On-site presentation
Raffaele Montuoro, Bing Fu, Neil Barton, Partha Bhattacharjee, Li Pan, Barry Baker, Kate Zhang, Jeffery McQueen, Avichal Mehra, Fanglin Yang, Ivanka Stajner, Gregory Frost, Vijay Tallapragada, and Yuejian Zhu

Ongoing efforts at the National Oceanic and Atmospheric Administration (NOAA), National Weather Service (NWS) are aimed at increasing the realism of the physical processes represented in both global and regional operational numerical weather prediction systems. These efforts include enhancing the description of atmospheric composition and its impact on the atmosphere by incorporating prognostic aerosols and aerosol radiative feedback in each member of the NOAA Global Ensemble Forecast System (GEFS).

Modern Earth system prototypes, built upon the community-based Unified Forecast System (UFS) framework and coupling atmosphere, land, ocean, sea ice, waves, and prognostic aerosols components are being developed and evaluated at the Environmental Modeling Center (EMC) in the process of identifying candidates for the planned operational upgrade of GEFS to version 13.

Prognostic aerosols are integrated in GEFS through the coupled UFS-Aerosols component, developed at EMC in collaboration with the National Aeronautics and Space Administration (NASA) Global Modeling and Assimilation Office (GMAO). UFS-Aerosols embeds NASA's 2nd-generation Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and incorporates updates to the dust scheme and anthropogenic and biogenic emissions from NOAA’s Air Resources Laboratory (ARL), along with wildfire emissions provided by NOAA's National Environmental Satellite, Data, and Information Service (NESDIS).

The impact of radiative feedback from prognostic aerosols on atmospheric predictions in preliminary experiments with GEFS version 13 prototypes will be reviewed. 

How to cite: Montuoro, R., Fu, B., Barton, N., Bhattacharjee, P., Pan, L., Baker, B., Zhang, K., McQueen, J., Mehra, A., Yang, F., Stajner, I., Frost, G., Tallapragada, V., and Zhu, Y.: Advancing NOAA's Global Ensemble Forecast System (GEFS) through the Integration of Prognostic Aerosols, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13049,, 2024.

On-site presentation
Rebecca Schwantes, Barry Baker, Ravan Ahmadov, Larry Horowitz, Lori Bruhwiler, Jian He, Zachary Moon, Jordan Schnell, Andrew Schuh, Li Zhang, Arthur Mizzi, Georg Grell, Vaishali Naik, David Fillmore, Matthew Dawson, Mary Barth, Havala Pye, Benjamin Murphy, Ligia Bernardet, and Brian McDonald and the UFS-Chem Developers

NOAA’s Unified Forecasting System (UFS) is a community-based Earth modeling system that plans to provide a framework to efficiently incorporate research advances into NOAA’s operational forecasts. Currently, chemistry related code for different applications including weather, climate, air quality, and smoke and dust forecasting is incorporated into the UFS through different methods. This non-unified framework is inefficient, difficult for developers to maintain, and not conducive for adding capabilities within the UFS for research applications. Through this work, we plan to unify atmospheric chemistry and composition within the UFS by creating CATChem or the Configurable ATmospheric Chemistry module ( CATChem will be flexible such that users can select the correct level of chemical complexity for their research or operational application. CATChem will include the following processes: passive tracers, chemical kinetics, aerosols, photolysis, wet deposition, dry deposition, connections to emissions, and connection to physics schemes. We will link CATChem to the UFS to create UFS-Chem or the Unified Forecasting System with chemistry. When possible, we will use tools already developed or being developed by the research community like the Model Independent Chemistry Module (MICM), which is a component of the MUlti-Scale Infrastructure for Chemistry and Aerosols (MUSICA), led by NCAR.

We will also add enhanced research capabilities into UFS-Chem, which will include: 

  • Options to use gas and aerosol chemical mechanisms of varying complexity.
  • Options for passive tracers, i.e. long lived greenhouse gases, which will also allow benchmark verification of mass conservation across UFS-Chem.
  • Ability to easily couple different mechanisms to different physics options. 
  • Development of a more flexible emissions processing system.
  • Interfacing with state-of-science atmospheric composition data assimilation capabilities. 
  • Further investment of model evaluation tools like MELODIES-MONET ( that efficiently compare model results against a variety of observations.

UFS-Chem will increase efficiency in code development, reduce costs for code maintenance, reduce time and effort for transitions to operations, and enhance collaborations with the research community. Continued engagement with the atmospheric chemistry and carbon cycle research communities are critical to ensure that research advances are efficiently and promptly included within the UFS, so that NOAA continues to provide state-of-the-art forecasts and monitoring of atmospheric composition to inform key societal challenges and policy. Here we present plans for UFS-Chem development and results for the first version of the global UFS configuration that includes full gas-phase tropospheric and stratospheric chemistry, which has been made possible through CATChem development.

How to cite: Schwantes, R., Baker, B., Ahmadov, R., Horowitz, L., Bruhwiler, L., He, J., Moon, Z., Schnell, J., Schuh, A., Zhang, L., Mizzi, A., Grell, G., Naik, V., Fillmore, D., Dawson, M., Barth, M., Pye, H., Murphy, B., Bernardet, L., and McDonald, B. and the UFS-Chem Developers: Unifying Atmospheric Composition in the Unified Forecasting System Through UFS-Chem Development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12625,, 2024.

On-site presentation
Haiqin Li, Georg Grell, Saulo Freitas, Li Zhang, and Ravan Ahmadov

A physics suite, which includes the aerosol-aware double moment Thompson-Eidhammer microphysics scheme (TH-E MP), the scale-aware and aerosol-aware Community Convective Cloud (C3) parameterization, and the MYNN-EDMF boundary layer and shallow cloud scheme, is under development at NOAA. We recently implemented a simple approach to improve the aerosol representation in the UFS. Sea salt, dust, biomass burning, and anthropogenic aerosol emissions have been embedded as CCPP-compliant subroutines. The prognostic emissions of sea-salt, and organic carbon are combined to represent the “water friendly” aerosol emission, while the prognostic emissions of dust are used to represent “ice friendly” aerosol emission for TH-E MP. With this implementation, we previously examined the aerosol indirect feedback when using the TH-E scheme in the global UFS 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 was significantly alleviated when applying this aerosol emission method for indirect feedback. Here we add the indirect feedback using the C3 convective parameterization. C3 is a new collaborative development which adds several features from the currently operational SAS scheme to the Grell-Freitas parameterization. This study indicates that aerosol-physics interactions using a very simple and computationally highly efficient approach have significant impacts on the numerical weather prediction in the global UFS applications.

How to cite: Li, H., Grell, G., Freitas, S., Zhang, L., and Ahmadov, R.: The Impacts of Aerosol-physics Interactions on Numerical Weather Prediction in NOAA’s  Global Unified Forecast System (UFS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6971,, 2024.

On-site presentation
Ariane Frassoni, Frederic Vitart, Angela Benedetti, and Andrea Molod

Subseasonal forecasts have been fundamental in bridging the gap between numerical weather predictions and seasonal forecasts, offering a wide range of products and services, particularly within the intraseasonal timescale. Despite the unprecedented opportunities to provide relevant information on key climate characteristics within the Subseasonal to Seasonal (S2S) timescale, there remains room for improvement in the predictive skill of S2S forecasts.

One potential avenue for enhancement is the numerical representation of two-way aerosol-climate interactions. Atmospheric aerosols play a crucial role as climate forcing due to their interactions with radiation (direct effect) and influences on cloud life cycle and precipitation (indirect effect).

Recognizing the significance of atmospheric composition in enhancing weather and climate prediction capabilities for the global climate system, the World Climate Research Programme Core Project Earth System Modeling and Observations-Working Group on Numerical Experimentation (WGNE), the WCRP and World Weather Research Programme (WWRP) S2S Steering Group (S2S-SG) and the Global Atmosphere Watch Programme Scientific Advisory Group on Applications (SAG APPs) have collaboratively led the WGNE Aerosol Project. This initiative aims to gain a deeper understanding of the role of aerosols in the predictive skill of models within the S2S timescale.

The WGNE Aerosol Project involves operational meteorological centers worldwide, contributing their state-of-the-art climate-chemistry-aerosol-cloud-radiation coupled modeling systems. Modeling groups participants contributed with an ensemble of retrospective predictions (hindcasts) considering distinct model configurations, taking into account the feedback between radiation/microphysics parametrization and aerosols. No-feedback between radiation/microphysics and aerosols experiments were considered as reference experiments. These reference experiments serve as a baseline to evaluate and understand the impact of incorporating feedback mechanisms in the modeling systems.

We propose to assess the performance of the WGNE Aerosol project modeling contributions, specifically focusing on the global domain within the S2S timescale. This work will present the results of the assessment, focusing on the main atmospheric variables near the surface, and aerosol optical depth from both deterministic and probabilistic perspectives, using common statistical metrics.

The WGNE Aerosol Project offers an opportunity to comprehend the feedback represented in current climate-chemistry-aerosol-cloud-radiation coupled systems and their impact on predicting climate variability, air quality, and extreme meteorological events within the S2S timescale. Moreover, it aims to identify the uncertainties associated with model predictions of feedback, providing insights for future developments and addressing the complexities of coupled modeling systems that impact predictive skill within the S2S timescale.

How to cite: Frassoni, A., Vitart, F., Benedetti, A., and Molod, A.: Quantifying the impact of aerosols on the predictive skill of subseasonal global atmospheric simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20883,, 2024.

On-site presentation
Valentin Hanft, Roland Ruhnke, Axel Seifert, and Peter Braesicke

Stratospheric ozone (O3) absorbs biologically harmful solar ultraviolet (UV) radiation, mainly in the UV-B and UV-C spectral range. At the surface, enhanced UV radiation poses a well documented hazard to human health. In order to quantify the amount of UV radiation and to make warnings easily understandable, the World Health Organization (WHO) has defined an UV Index[1]. It is calculated using a weighted integral of the incoming solar irradiance at surface level between 250 and 400 nanometers and scaling the result to values that generally range between 1 to 10, surpassing 10 for excessive UV exposure.

Implementing UV Index forecasts in numerical weather prediction (NWP) models allows to alert the public in time if special care for sun protection needs to be taken. The German Weather Service (DWD) uses its NWP model ICON (ICOsahedral Nonhydrostatic Model)[2] to offer such a forecast for Germany[3] using external data such as ozone forecasts by the Royal Netherlands Meteorological Institute (KNMI) and radiation lookup tables[4].

Here, we extend the capability of ICON such as to provide a self-consistent UV Index forecasts that do not require external/auxiliary data. For this, we use ICON-ART[5],[6] with a linearized prognostic (stratospheric) ozone scheme (LINOZ)[7] and couple the prognostic ozone (and other model variables) to the atmospheric radiation scheme Solar-J[8]. To validate this new ICON-ART setup, we study the model performance in a selected reference time frame in comparison to CERES[9] satellite data and find generally a good agreement. This is an indication for the suitability of the model system to forecast the UV Index.


[1] World Health Organization. Global solar uv index : a practical guide,2002.

[2] Günther Zängl et al.. The icon (icosahedral non-hydrostatic) modelling framework of dwd and mpi-m: Description of the non-hydrostatic dynamical core. Quarterly Journal of the Royal Meteorological Society, 2015.


[4] Henning Staiger and Peter Koepke. Uv index forecasting on a global scale. Meteorologische Zeitschrift, 2005.

[5] D. Rieger et al.. Icon–art 1.0 – a new online-coupled model system from the global to regional scale. Geoscientific Model Development, 2015.

[6] J. Schröter et al.. Icon-art 2.1: a flexible tracer framework and its application for composition studies in numerical weather forecasting and climate simulations. Geoscientific Model Development, 2018.

[7] C. A. McLinden et al. Stratospheric ozone in 3-d models: A simple chemistry and the cross-tropopause flux. Journal of Geophysical Research: Atmospheres, 2000

[8] J. Hsu, M. J. Prather et al.. A radiative transfer module for calculating photolysis rates and solar heating in climate models: Solar-j v7.5. Geoscientific Model Development, 2017.

[9] NASA/LARC/SD/ASDC. (2017). CERES and GEO-Enhanced TOA, Clouds and Aerosols 1-Hourly Terra-Aqua Edition4A [Data set]. NASA Langley Atmospheric Science Data Center DAAC.

How to cite: Hanft, V., Ruhnke, R., Seifert, A., and Braesicke, P.: Prognostic Ozone For ICON: Enabling UV Forecasts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17068,, 2024.

On-site presentation
Paolo Andreozzi, Mark Fielding, Richard Forbes, and Robin Hogan

For many years, aerosol-cloud-radiation interactions (ACI) have been incorporated in climate models, due to the high sensitivity of the Earth’s climate to changes in cloud microphysical properties. Despite this, such representations are still fraught with uncertainty, strongly limiting the capacity of such models to precisely predict climate change. For numerical weather prediction (NWP), the impact of ACI on forecast skill is controversial, though regional radiative fluxes can be affected significantly. Their representation in NWP models has therefore usually been neglected. We will present early results from an ongoing investigation to calculate the number of droplets (Nd) in liquid-phase clouds online from global aerosol fields in the ECMWF global Integrated Forecasting System (IFS), i.e. the first indirect radiative effect of aerosols. Our ACI scheme uses a lookup table, produced from offline cloud parcel model simulations, to estimate the number of aerosol particles activated into cloud droplets. This approach allows the effect of large sea salt to suppress the activation of sulfate aerosols to be included. We will then constrain the representation of ACI by verifying weather forecast against available satellite and station-based observations. Ultimately, the impact of such simulated processes on the model can be assessed in different configurations of the IFS, spanning from the NWP medium range (10-15 days) to seasonal forecasts to climate projections. We will show how such a computationally inexpensive approach can effectively increase realism of the simulated liquid-phase cloud microphysics in the model, resulting in improved representation of global and regional top-of-the-atmosphere radiative fluxes. We can apply the same approach both to the climatological and prognostic aerosol representations supported by the IFS (the latter being used operationally for air quality forecasts by the Copernicus Atmospheric Monitoring Service, CAMS), allowing sensitive comparison between different configurations of the model. We will conclude by showing advantages of the new ACI scheme when aerosols are prognostic variables, and how such experiments could inform our work towards introducing ACI into the operational IFS forecasts, where currently a climatological representation of aerosols is used.

How to cite: Andreozzi, P., Fielding, M., Forbes, R., and Hogan, R.: Implementing the first indirect radiative effect of aerosols in the ECMWF model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17697,, 2024.

On-site presentation
Towards a 16-year surface reanalysis of air quality over North America using EnOI
Richard Ménard, Jean-Francois Cossette, James Abu, Martin Deshaies-Jacques, and Nedka Pentcheva
On-site presentation
Gaël Descombes, Augustin Colette, and Anthony Ung

The quantity and accuracy of satellite data is constantly growing up for air quality monitoring. They are already widely used to perform better forecast and analysis for global modeling. Even if, high resolution modeling at regional scale has been relying on surface observation for a long time, we will focus on data assimilation over Europe looking especially for satellite data assimilation.In this study, the Chemistry model transport CHIMERE is associated to the Data Assimilation Research Testbed (DART from the National Center Atmospheric Research) to simulate recent events of pollution using for the Sentinel 5P data. Preliminary results coming from the CAMs EvOlution (CAMEO) project will be presented for the Sentinel 5P data. Special emphasis will be made on the regional set-up of the Adjustment Ensemble Kalman Filter (AEKF) ensemble data assimilation system used and future developments

How to cite: Descombes, G., Colette, A., and Ung, A.: Satellite data assimilation at regional scale using the Chimere model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9296,, 2024.

On-site presentation
Vincent Huijnen, Katerina Sindelarova, Miró van der Worp, Jason Williams, and Samuel Rémy


Biogenic volatile organic compounds (BVOCs) are important contributors to atmospheric chemistry and act as precursors of secondary organic aerosol, formaldehyde (HCHO) and carbon monoxide. In presence of high NOx the emitted isoprene may also contribute significantly to the production of tropospheric ozone. As such, having a good handle on BVOC emissions is important for global air quality analyses and forecasts, as produced operationally as part of the Copernicus Atmosphere Monitoring Service (CAMS). Currently, analyses and forecasts as generated using ECMWF’s Integrated Forecasting System for atmospheric composition (IFS-COMPO), use offline monthly datasets for biogenic emissions based on CAMS-GLOB-BIO. However, this approach lacks the ability to capture the daily variability in biogenic VOC emissions, while also the near-real time forecasts have to rely on climatological emissions.

This has motivated the implementation of an online parameterization for the description of BVOC emissions based on the MEGAN scheme, as part of the ECLand module. Having the BVOC emissions as an integral part of the IFS allows the use of the latest parameterization of soil and vegetation properties, together with accurate description of meteorological quantities, which are both important drivers with respect to biogenic emissions. Also, the resulting emissions can be directly used in the atmospheric chemistry module, which has recently been updated with respect to isoprene chemistry. This also enables an indirect evaluation of the emissions using TROPOMI observations of HCHO.

In this contribution we present the current status of the implementation of the online biogenic VOC emissions module into the IFS and provide a first assessment by comparing these emissions to a reference CAMS-GLOB-BIO dataset. Also we evaluate the resulting isoprene emissions in terms of HCHO columns using TROPOMI retrievals, along with its impact on surface ozone and secondary organic aerosol. We highlight uncertainties in different aspects along the parameterization and evaluation chain.


How to cite: Huijnen, V., Sindelarova, K., van der Worp, M., Williams, J., and Rémy, S.: An online parameterization of biogenic VOC emission fluxes in the Integrated Forecasting System for atmospheric composition, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10683,, 2024.

On-site presentation
Christine Bingen, Samuel Rémy, Simon Chabrillat, Daniele Minganti, Quentin Errera, Vincent Huijnen, Swen Metzger, Jason Williams, and Johannes Flemming

ECMWF’s Integrated Forecasting System, extended with modules for atmospheric composition (IFS-COMPO) is used to provide global forecasts and analyses of the atmospheric composition in the framework of the Copernicus Atmosphere Monitoring Service (CAMS). In the last years intensive work has been dedicated to an improved representation of stratospheric composition in IFS-COMPO. Progresses concern both chemistry through the implementation and use of BASCOE in IFS-COMPO since cycle 48R1, and the extension of IFS-AER to also represent stratospheric sulfate and the associated processes, planned for cycle 49R1. In cycle 49R1, IFS-COMPO will have the capacity to forecast different aerosol parameters of importance for the stratospheric heterogeneous chemistry, such as the surface area density (SAD).

The BASCOE module considers full stratospheric chemistry including heterogeneous reactions on the surfaces of polar stratospheric clouds (PSC) that control the extent and depth of ozone depletion events. To date BASCOE makes use of a combination of fixed information (particle number concentration, modal radius and the standard deviation of the aerosol particle size distribution), using a prescribed monthly SAD dataset to describe the aerosol contribution to stratospheric heterogeneous chemical processes. Here we present a further coupling of IFS-AER with BASCOE whereby online aerosol information from IFS-AER is used as an input to the BASCOE heterogeneous chemistry routines.

Two possible coupling mechanisms have been implemented and tested for different test cases representative for high volcanic load (Pinatubo period), moderate volcanic load (2008-2009 period), and low, “background” aerosol load (1997-1998 period). Making use of different reference datasets like GloSSAC (for aerosols) and the BRAM-MLS reanalysis (for ozone and ozone-depleting chemical species), we evaluate the impact of these new coupling mechanisms between IFS-AER and BASCOE on aerosol transport and microphysics during the considered periods, and on simulated stratospheric atmospheric composition, focusing on several ozone-depletion events (“ozone holes”) in both Antarctic and Arctic winter.

How to cite: Bingen, C., Rémy, S., Chabrillat, S., Minganti, D., Errera, Q., Huijnen, V., Metzger, S., Williams, J., and Flemming, J.: Coupling of stratospheric aerosol and chemistry in IFS-COMPO: use of online aerosol information in the stratospheric heterogeneous chemistry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12780,, 2024.

Posters on site: Wed, 17 Apr, 10:45–12:30 | Hall X5

Display time: Wed, 17 Apr 08:30–Wed, 17 Apr 12:30
Chairpersons: Johannes Flemming, Georg Grell, Alexander Baklanov
Mykhailo Savenets, Alexander Mahura, Roman Nuterman, and Tuukka Petäjä

Wildfires, while disastrous for ecosystems, also contribute significantly to pollution impacting human health. They also affect meteorological conditions at both local and regional scales by emitting aerosols into the atmosphere, which have both direct and indirect effects. In Ukraine, forest fires are common in the spring, coinciding with the season of agricultural open burning.

The wildfire episode in April 2020 was among the most severe and especially difficult to extinguish because of its origin and spreading in the abandoned Chornobyl Exclusion Zone (CEZ). Applying the seamless online-integrated Enviro-HIRLAM modeling system, we aimed to study aerosol contamination and how its elevated levels affected regional near-surface meteorology. To achieve this, the model was run in 4 modes: reference (REF) run and runs to simulate direct (DAE), indirect (IDAE) and combined (COMB) aerosol effects. These runs were performed at 15 km horizontal resolution (covering large European territory to consider atmospheric circulation) with downscaling to 5 (focusing on Ukraine) and 2 km (focusing on the CEZ).

Elevated black and organic carbon content accounted for 80% of all aerosol species with the prevailing mass concentration in the accumulation mode in the CEZ. The observed meteorology, driven by aerosol effects, was more intensified in these synoptic conditions, and especially at the edges of the fronts. When aerosol effects were included, the wind speed changed up to ±4 m/s and caused spatial shifts in patterns of cloudiness and precipitation. Moreover, verification showed better results for modelling with IDAE, whereas DAE effects can overestimate changes in near-surface meteorology. This aerosol composition led to noticeable cooling and drying effects. The 2-m air temperature decreased by 3℃ and a specific humidity dropped by 1 g/kg at a local scale. However, these effects varied with atmospheric conditions. In particular, when fronts, especially cold fronts, passed through the CEZ, stronger changes in meteorological parameters were observed as expected. As presence of aerosols influences a humidity regime in the boundary layer (including formation and development of cloudiness and precipitation), the spatial positioning of modeled fronts may be shifted leading to changes of opposite signs.

This study was supported by the grant of HPC-Europa3 Transnational Access Programme for projects “Integrated modelling for assessment of potential pollution regional atmospheric transport as result of accidental wildfires” (IMA-WFires, HPC17TRLGW) & “Research and development for integrated meteorology – atmospheric composition multi-scales and – processes modelling” (Enviro-PEEX(Plus) on ECMWF; SPFIMAHU-2021). The CSC – IT Center for Science Computing (Finland) is acknowledged for computational resources.

How to cite: Savenets, M., Mahura, A., Nuterman, R., and Petäjä, T.: Near-surface meteorology changes driven by aerosol effects during the April 2020 wildfires in the Chornobyl Exclusion Zone, Ukraine, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-303,, 2024.

Johannes Flemming, Melanie Ades, Enza Di Tomaso, Antje Inness, Vincent Huijnen, Luke Jones, Zoi Paschalidi, Miha Razinger, and Samuel Remy

Surface air pollution is a major hazard for society because of its negative impact on human health, crops yield and on other aspects of the economy. Monitoring the air quality with in-situ instruments is routinely carried out in many countries. These air quality networks have limited coverage. They  are often very sparse or are not even present in many parts of the world, that suffer from the worst air quality.  Satellite observations of atmospheric composition provide the unique prospect to contribute to a more spatially complete monitoring of surface air pollution. However, among several other limitations, only vertically integrated measures of the pollution concentration can usually be retrieved from satellites, and not the surface concentration.  The relation between total column information and surface concentrations depends on the shape of the vertical profile. The correlation may be especially poor in the case of lofted air pollution plumes originating from long range transport.   

Data driven methods (machine learning, statistic etc.) are used to infer surface concentrations from satellite observations based on in-situ surface observations. An alternative approach is data assimilation of satellite retrievals in an atmospheric model, a method which has been developed for numerical weather forecasting.  The global forecasting system of atmospheric composition of the Copernicus Atmosphere Monitoring Service (CAMS) applies 4D-VAR data assimilation to satellite retrievals of Aerosol optical depth (AOD), Ozone, Carbon Monoxide and Nitrogen Dioxide (NO2) to correct the model initial conditions and consequently also the PM2.5 and PM10 surface concentrations.  In our presentation, we will give an overview of the usefulness of atmospheric composition (AC) satellite data assimilation for monitoring of surface air quality with the global CAMS system. We will specifically show to what extent AOD assimilation improves the analysis and forecast of surface PM2.5 for different regions and at different temporal and spatial scales. In particular we will discuss the correlation between AOD and PM2.5 in the observations and in the model. We will also discuss the influence of the model performance and aspects of the data assimilation procedure on the impact of AC satellite data assimilation on surface concentrations.

How to cite: Flemming, J., Ades, M., Di Tomaso, E., Inness, A., Huijnen, V., Jones, L., Paschalidi, Z., Razinger, M., and Remy, S.: The impact of AOD assimilation on surface PM analysis and forecast with the global CAMS system. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11437,, 2024.

Shan Sun, Georg Grell, Li Zhang, Judy Henderson, and Haiqin Li

This study examines the impact of aerosol-radiation interation on subseasonal prediction using the Unified Forecast System (UFS) coupled to an ocean and an aerosol component. The aerosol component is from the current NOAA operational GEFS-Aerosols model, which includes the GOCART aerosol modules, simulating sulfate, dust, black carbon, organic carbon, and sea-salt aerosols. The modeled aerosol optical depth (AOD) is compared to reanalysis from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) and observations from Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite. Despite AOD bias primarily in dust and sea salt, good AOD agreement is achieved. The simulated radiative forcing (RF) from the total aerosol at the top of the atmosphere is approximately -2.5 W/m2 or -16 W/m2 per unit AOD globally. This is consistent with previous studies.

In parallel simulations, the dynamic prognostic aerosols are replaced with modeled climatological aerosol concentrations in the UFS. While regional differences in RF are noticeable in some special events between these twin experiments, the resulting RF, surface temperature, precipitation and geopotential height at 500 hPa, show similarity over multi-years in subseasonal applications. This suggests that replacing the costly chemistry module with the modeled aerosol concentration climatology is a possible alternative in the subseasonal applications.

How to cite: Sun, S., Grell, G., Zhang, L., Henderson, J., and Li, H.: Simulating aerosol-radiation effect on subseasonal prediction in a coupled Unified Forecast System and CCPP-Chem: prescribed aerosol climatology versus dynamic aerosol model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4896,, 2024.

Daniele Minganti, Simon Chabrillat, Christine Bingen, Vincent Huijnen, Samuel Remy, Swen Metzger, Jason Williams, and Johannes Flemming

The Integrated Forecasting System (IFS-COMPO) at ECMWF is the global model used by the Copernicus Atmosphere Monitoring Service (CAMS) to provide forecasts and analyses of atmospheric composition, including greenhouse gases, aerosols and reactive gases. Within CAMS, the default configuration of IFS-COMPO relies on the CB05 chemistry scheme for the troposphere and the Belgian Assimilation System for Chemical ObsErvations (BASCOE) module for the stratospheric chemistry.

Currently, the photodissociation rates (Js) in IFS-COMPO can be computed with two methods: Joffline (computationally efficient but inaccurate) and Jonline (more accurate but computationally very expensive). In this work, we implement and evaluate an optimized method for the calculations of the Js in the stratosphere that is as accurate as Jonline and as computationally efficient as Joffline. This method (Jvint) computes the Js using Jonline but on a coarser stratospheric vertical grid (L23) compared to the native vertical grid and will be available in the future cycle 49R1.

We compare three IFS-COMPO simulations using the Jvint, Jonline and Joffline methods with the BASCOE Reanalysis of Aura MLS version 3 (BRAM3) for ozone and with observations from the TROPOspheric Monitoring Instrument (TROPOMI) for nitrous dioxide (NO2). For ozone, the Jvint method significantly reduces the bias with respect to BRAM3 compared to the Joffline method in the upper stratosphere. In the mid-lower stratosphere, however, the Jvint configuration delivers slightly larger bias with respect to BRAM3 when compared to the Joffline method, especially over the Arctic. This bias is consistent with the results from the Jonline method and with the bias reduction in the upper stratosphere. For NO2, the Jvint method also reduces the bias with respect to TROPOMI stratospheric columns compared to the Joffline method at all latitudes.

Concerning the computational cost, it increases in the Jvint method compared to the Joffline method by 5% in December, 16% in July and 12% in November, while the Jonline method is two to three times as computationally expensive compared to Joffline. In addition, the Jvint method improves the seasonal variations of the ozone and NO2 columns compared to the Joffline method, and the differences between the Jvint and Jonline methods are insignificant for most of the stratospheric regions.

We demonstrate the capability of the Jvint method to deliver improved stratospheric columns for ozone and NO2 compared to the Joffline method and significantly reduce the computational cost compared to the Jonline method. The Jvint configuration also includes the time-dependence of the solar flux, ensuring a physically consistent representation of the stratospheric photochemistry.

How to cite: Minganti, D., Chabrillat, S., Bingen, C., Huijnen, V., Remy, S., Metzger, S., Williams, J., and Flemming, J.: Optimization of the calculation of the photodissociation rates in the stratosphere in the BASCOE module of the IFS-COMPO, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11188,, 2024.

Samuel Remy, Swen Metzger, Vincent Huijnen, Jason Williams, and Johannes Flemming

The atmospheric composition forecasting system used to produce the CAMS forecasts of global aerosol and trace gases distributions, IFS-COMPO, undergoes periodic upgrades. In this presentation we describe the development of the future operational cycle 49R1, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12 for describing gas-aerosol partitioning processes for nitrate and ammonium and for providing diagnostic aerosol, cloud and precipitation pH values at global scale. This information on aerosol acidity influences tropospheric chemistry processes associated with aqueous phase chemistry and wet deposition. The other updates to cycle 49R1 include modifications to the description of Desert Dust, Sea-salt aerosols, Carbonaceous aerosols and the size description for the calculation of aerosol optics.


The implementation of EQSAM4Clim significantly improves the partitioning of reactive nitrogen compounds decreasing surface concentrations of both nitrate and ammonium, which reduces PM2.5 biases for Europe, U.S. and China, especially during summertime. For aerosol optical depth there is generally a decrease in the simulated biases for wintertime, and for some regions an increase in the bias for summertime. Improvements in the simulated Ångström exponent is noted for almost all regions, resulting in generally a good agreement with observations.


 The diagnostic aerosol and precipitation pH calculated by EQSAM4Clim have been compared against results from previous simulations (for aerosol pH) and against ground observations (for precipitation pH), with the temporal distribution in the annual mean values showing good agreement against the regional observational datasets. The use of aerosol acidity only has a relatively smaller impact on the aqueous-phase production of sulphate when compared to the changes in gas-to-particle partitioning brought by the use of EQSAM4Clim.


Metzger, S., Rémy, S., Williams, J. E., Huijnen, V., and Flemming, J.: A revised parameterization for aerosol, cloud and precipitation pH for use in chemical forecasting systems (EQSAM4Clim-v12), EGUsphere [preprint],, 2023.

How to cite: Remy, S., Metzger, S., Huijnen, V., Williams, J., and Flemming, J.: Improved representation of aerosol acidity in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Clim., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12250,, 2024.

Ravan Ahmadov, Haiqin Li, Johana Romero-Alvarez, Jordan Schnell, Sudheer Bhimireddy, Eric James, Ka Yee Wong, Ming Hu, Jacob Carley, Partha Bhattacharjee, Barry Baker, Georg Grell, Chuanyu Xu, Shobha Kondragunta, Fangjun Li, Samuel Trahan, and Margaret Marvin

NOAA’s Global Systems Laboratory (GSL), in collaboration with other laboratories, is developing and testing a new high-resolution weather model known as the Rapid-Refresh Forecasting System (RRFS). This model, which uses the Finite Volume Cubed-Sphere Dynamical Core, features a grid covering all of North and Central America at 3 km horizontal resolution, with 65 vertical layers. 

The RRFS is initialized every hour through assimilation of the latest weather observations. It incorporates primary aerosol emissions from wildland fires and dust sources. The coupled RRFS-Smoke-Dust (RRFS-SD) model simulates 3D concentrations of smoke, fine and coarse dust aerosol species concurrently with the meteorology, and includes the aerosol radiative feedback. Hourly fire radiative power data from the Regional ABI and VIIRS fire Emissions (RAVE) product is ingested into RRFS to estimate biomass burning emissions and fire heat fluxes. Windblown dust emissions are parameterized by using the FENGSHA scheme. An experimental version of the RRFS-SD model is being tested by NOAA Environmental Modeling Center (EMC) in real time:

We will present an evaluation of the RRFS-SD model  for several fire and dust case studies. Ground and aircraft-based in-situ and remote sensing data are extensively utilized to evaluate the model simulations of meteorology, smoke and dust fields. Additionally, we will present the radiative feedback of smoke and dust on the meteorological simulations in RRFS. The challenges and uncertainties affecting the smoke and dust forecasting will be discussed as well. 

How to cite: Ahmadov, R., Li, H., Romero-Alvarez, J., Schnell, J., Bhimireddy, S., James, E., Wong, K. Y., Hu, M., Carley, J., Bhattacharjee, P., Baker, B., Grell, G., Xu, C., Kondragunta, S., Li, F., Trahan, S., and Marvin, M.: Forecasting smoke and dust in NOAA’s next-generation high-resolution coupled numerical weather prediction model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12702,, 2024.

Larysa Pysarenko, Alexander Mahura, Roman Nuterman, and Svitlana Krakovska

Aerosol effects play a significant role in Earth’s radiative balance, cloud formation and thus redistribution and change of meteorological characteristics. This study focuses on the case of heat wave event during July-August 2010 accompanied with wildfires, modeled using the seamless online-integrated Enviro-HIRLAM modeling system. We used reference (REF) run and running modes to simulate direct (DAE), indirect (IDAE) and combined (DAE+IDAE) aerosol effects. These runs fulfilled for domain at 15 km horizontal resolution (includes European territory), with downscaling to 5 km (includes the territory of Ukraine).

During the heat wave event, aerosol effects caused the overall 2-m air temperature nighttime cooling and daytime warming being stronger for DAE. Locally, there were observed reversed dependencies reaching up to 5℃ differences compared to REF runs. Specific humidity changes were consistent with air temperature fluctuations showing a decrease at night and increase during midday hours without heterogeneous spatial distribution. IDAE effects caused homogeneously distributed slight decrease in 2-m air temperature, with no sharp changes in specific humidity. At midday, homogeneity disappeared for 2-m air temperature, whereas aerosol effects had no significant impact on specific humidity. DAE+IDAE caused mostly warming effect during night time, with local increase and decrease for specific humidity. For all running modes, there were no significant changes in grid-scale precipitation driven by aerosol effects.

Occasionally, the heat wave event was accompanied with weather fronts. In comparison to anticyclonic synoptic conditions, the role of aerosol effects significantly increased during these weather fronts passage. In the case of a cold front, DAE showed a decrease in 2-m air temperature by -1,2℃ following the cold front areas, and warming on some distance up to +1,4℃ at midnight.

IDAE effects resulted in significant warming before front and cooling after it. Specific humidity falls after cold front up to -4 g/m3. DAE+IDAE affected 2-m air temperature rise before cold front and cooling after during midday. Specific humidity changes unevenly and increases after cold front. Grid-scale precipitation amounts decreased during the cold front passage due to the impact of aerosol effects for all running modes.

This study was supported by the grant of HPC-Europa3 Transnational Access Programme for projects “Integrated Modelling and Analysis of Influence of Land Cover Changes on Regional Weather Conditions/ Patterns” (MALAWE, HPC17ENAVF) & “Research and development for integrated meteorology – atmospheric composition multi-scales and – processes modelling” (Enviro-PEEX(Plus) on ECMWF; SPFIMAHU-2021). The CSC – IT Center for Science Computing (Finland) is acknowledged for computational resources.

How to cite: Pysarenko, L., Mahura, A., Nuterman, R., and Krakovska, S.: A case study of aerosol effects impact on key meteorological characteristics in Ukraine during heat wave event in July-August 2010, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17895,, 2024.

Flora Kluge, Johannes Flemming, Vincent Huijnen, Antje Inness, Christopher Kelly, Jean-François Müller, Glenn-Michael Oomen, Klaus Pfeilsticker, Trissevgeni Stavrakou, Roberto Ribas, Meike Rotermund, Ben Weyland, and Miró Van der Worp

We report on an extensive analysis of CAMS (Copernicus Atmospheric Monitoring Service) formaldehyde (HCHO) simulations in different tropospheric regions, seasons, altitudes and air masses using a comprehensive data set of airborne measured HCHO vertical column densities and mixing ratios. The observations are derived from measurements of the HALO mini-DOAS instrument operated from aboard the German research aircraft DLR HALO during six international research missions in the years 2017 to 2019. In addition, measurements over the South American tropical rain forest in 2014 are included, as this region is of particular interest in the analysis of global biogenic emissions. The analysis of airborne measured and CAMS CY48R1 simulated HCHO vertical profiles shows an overestimation of planetary boundary layer HCHO over the Amazon rain forest by the model on average by 70%. Restricting the comparison to measurements outside of identified anthropogenic emission events (e.g. biomass burning plumes) increases this overestimation of boundary layer HCHO to a factor of five. This finding is further investigated by additionally also including vertical column density measurements of the mini-DOAS instrument to the analysis. This allows the comparison of simulated and airborne derived HCHO with respective TROPOMI satellite observations (for all airborne measurements from May 2018 onwards), hence enabling a comprehensive assessment of tropospheric HCHO. The above findings are included in ongoing research of work package 2.3 of the Horizon Europe CAMEO (CAMS EvOlution) project, which aims to develop an inversion of biogenic emissions within ECMWF’s Integrated Forecasting System (IFS). As a first step towards a successful implementation of HCHO assimilation and inversion capability within the IFS, a simplified HCHO chemistry scheme has been developed and is currently analyzed with a particular focus on its impact on other atmospheric reactive trace gases, such as isoprene and ozone, and on aerosols.

How to cite: Kluge, F., Flemming, J., Huijnen, V., Inness, A., Kelly, C., Müller, J.-F., Oomen, G.-M., Pfeilsticker, K., Stavrakou, T., Ribas, R., Rotermund, M., Weyland, B., and Van der Worp, M.: Initial steps towards an inversion system for biogenic isoprene emissions in CAMS: Verification using HALO mini-DOAS and TROPOMI observations and simplified chemistry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18181,, 2024.

Dirceu Herdies, Andre Reis, Janaina Nascimento, and Angel Vara-Vela

In addition to dynamic and thermodynamic processes, aerosols' chemical and aerodynamic characteristics play a significant role in cloud microphysics and convective development. The region surrounding Manaus, located in the Northern region of Brazil, constitutes a unique environment worldwide for studying the impact of anthropogenic and biogenic emissions on aerosol concentration and, consequently, cloud microphysics. This study investigates chemical-aerosol-cloud interactions during the wet season, employing the Weather Research and Forecasting model with coupled chemistry (WRF-Chem) version and observed data from the GoAmazon2014/5 experiment. The model was configured with a 3 km grid, utilizing the Regional Atmospheric Chemistry Mechanism (RACM) for gas-phase chemistry, and adopting the Modal Aerosol Dynamics Model for Europe (MADE) with parameterization for Secondary Organic Aerosol (SOA) production based on the Volatility Basis Set (VBS) approach for aerosol treatment. The Abdul-Razzak and Ghan option was employed to relate aerosol properties to the 2-moment Morrison cloud microphysics parameterization. The model is initialized with ERA5 and Copernicus Atmosphere Monitoring Service (CAMS) data, incorporating anthropogenic emissions from a regional inventory and biogenic emissions using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). Results indicate that the model effectively represents meteorology and chemistry in the Manaus region. The fully coupled model successfully reproduces plume dispersion and aging. The aerosol concentration peak in the accumulation mode is observed approximately 100 km from Manaus, returning to background concentrations beyond 300 km. The increase in aerosol concentrations is associated with the formation of biogenic and anthropogenic Secondary Organic Aerosol (SOA) and sulfate-derived aerosols with mass peaks at 4, 100, and 1.4 times the background concentration. This aerosol concentration increase significantly correlates with Cloud Condensation Nuclei (CCN) concentration at 0.5% supersaturation. Despite the elevated aerosol concentration in the plume and higher CCN concentration, the CCN/aerosol ratio decreases to 0.02, in contrast to 0.3 in the background region. The distinct chemical and aerodynamic characteristics of aerosols in the background and urban plume regions modulate the Droplet Number Concentration (DNC), Liquid Water Content (LWC), and Effective Radius (Re). Clouds in the plume exhibit higher DNC and LWC, and lower Re. Approximately 40% of clouds in the plume have LWC above 2.5 g/m³, compared to only 10% in background regions. The average Re is 8 and 13 μm in the plume and background regions, respectively. Sensitivity simulations also show that both anthropogenic and biogenic emissions influence cloud processes in the Amazon region. Our results suggest that a more accurate representation of aerosols, often simplified in numerical models, is necessary for enhanced weather and climate modeling.

How to cite: Herdies, D., Reis, A., Nascimento, J., and Vara-Vela, A.: Impact of the Manaus Plume on the Amazon Green Ocean Atmosphere: Aerosol-Cloud Interaction during the Wet Season with fully coupled online chemistry in the WRF model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19415,, 2024.

Swen Metzger, Samuel Rémy, Jason E. Williams, Vincent Huijnen, Christine Bingen, Daniele Minganti, Simon Chabrillat, and Johannes Flemming

The ECMWF’s Integrated Forecasting System (IFS-COMPO) is the European global atmospheric model used to provide global analyses and forecasts of atmospheric composition, including aerosols as well as reactive trace gases and greenhouse gases in both the troposphere and stratosphere within the framework of the Copernicus Atmosphere Monitoring Service (CAMS).

Recently the Equilibrium Simplified Aerosol Model for Climate version 12 (EQSAM4Clim-v12) has been implemented in IFS-COMPO and will be used in cycle 49R1 to compute the inorganic gas/aerosol equilibrium partitioning involving major ammonium, sulphate and nitrate compounds, i.e., NH3/NH4+, H2SO4/HSO4-/SO42- and HNO3/NO3-, as well as the non-volatile mineral cations Ca2+, Mg2+, Na+, and K+. The composition and aerosol water mass (AW) is calculated by EQSAM4Clim through the neutralization of anions by cations, which yields numerous salt compounds. In EQSAM4Clim, all salt compounds (except CaSO4) can partition between the liquid and solid aerosol phase, depending on temperature (T), relative humidity (RH), AW and the T-dependent RH of Deliquescence of (a) single solute compound solutions (RHD) and (b) of mixed salt solutions (MRHD).

The possibility to store the speciated AW from each EQSAM4Clim salt compound has been implemented in IFS-COMPO in an experimental version. Additionally, the associated compound’s growth factors (GF) and various aerosol properties have been added to the IFS-COMPO output diagnostics. Here, we show that results related to the speciated AW and GFs as computed by EQSAM4Clim-v12 in IFS-COMPO based on RHD compare well with the corresponding lookup table values of IFS-COMPO that are currently used operationally. The speciated aerosol water diagnostics based on MRHD will be used to improve the aerosol optical depth (AOD) calculations. Differences between an AW and GF based AOD coupling will be discussed.

How to cite: Metzger, S., Rémy, S., Williams, J. E., Huijnen, V., Bingen, C., Minganti, D., Chabrillat, S., and Flemming, J.: Speciated aerosol water diagnostics in the global Copernicus Atmospheric Monitoring Service (CAMS) Integrated Forecast System (IFS-COMPO), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19784,, 2024.

Lewis Blake, Peter Wind, Hilde Fagerli, Alvaro Valdebenito, Ingrid Super, and Jeroen Kuenen

We present a methodology and first results for analytical propagation of emissions uncertainties
through the EMEP MSC-W chemical transport model (CTM) and an application of these uncertainty
estimates to policy products provided by the Copernicus Atmosphere Monitoring Service
(CAMS) for European cities. CTMs are widely employed in atmospheric modeling to simulate
the transport and transformation of pollutants, but uncertainties in emission estimates can
significantly impact the accuracy of air quality predictions. Our study systematically analyzes
the propagation of uncertainties arising from emissions. The emissions’ uncertainties are consistent
with the CAMS regional emissions product and are calculated using detailed, countryspecific
uncertainty estimates in activity data and generic emission factor uncertainties. The
uncertainties are calculated per source sector and country. The Local Fractions/Sensibilities [1]
methodology available in the EMEP MSC-W model is a tool that allows computation of sourcereceptor
relationships more efficiently. In conjunction with analytical methods for uncertainty
propagation, we deliver air quality predictions with uncertainty estimates at a fraction of the
computational cost and with increased traceability compared to modern surrogate modeling
techniques. In our study we focus on PM2.5 and PM10, and first results will be presented for the
impact of emission uncertainties on forecasted PM concentrations in European cities, as well as
uncertainties in contributions from different source sectors and countries. By integrating emission
uncertainty propagation, our study aims to provide decision-makers with a more accurate
assessment of the reliability of CAMS policy products under various atmospheric conditions
and in the future provide these estimates as part of their operational delivery.




[1] P. Wind, B. Rolstad Denby, and M. Gauss, “Local fractions – a method for the calculation
of local source contributions to air pollution, illustrated by examples using the emep
msc-w model (rv4 33),” Geoscientific Model Development, vol. 13, no. 3, pp. 1623–1634,
2020. [Online]. Available:

How to cite: Blake, L., Wind, P., Fagerli, H., Valdebenito, A., Super, I., and Kuenen, J.: Analytical Propagation of Emission Uncertainties into CAMS Policy Products, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21289,, 2024.

Li Zhang, Georg Grell, Partha Bhattacharjee, Shan Sun, Anders Jensen, Jordan Schnell, Haiqin Li, Yunyao Li, Barry Baker, Judy Henderson, Ravan Ahmadov, Ligia Bernardet, Daniel Tong, Ziheng Sun, Li Pan, Bing Fu, Raffaele Montuoro, Jian He, Rebecca Schwantes, and Siyuan Wang and the NOAA team

Recognizing the uncertainties associated with fire emission, a crucial factor influencing the fire aerosol prediction, we have initiated studies to improve fire emission for subseasonal to seasonal (S2S) forecasts. Two global aerosol/chemistry forecast models are currently under development and have been fully coupled with the Unified Forecast System (UFS), encompassing ocean, sea ice, wave and land surface components for S2S forecasts at NOAA. One is UFS-Aerosols: the second-generation UFS coupled aerosol system, which embeds NASA’s 2nd-generation GOCART model in a National Unified Operational Prediction Capability (NUOPC) infrastructure, has been collaboratively developed by NOAA and NASA since 2021. It is planned to be implemented into the Global Ensemble Forecast System (GEFS) v13.0 for ensemble prototype 5 (EP5) experiments early this year. The other one is UFS-Chem: an innovative community model of chemistry online coupled with UFS, developed collaboratively between NOAA Oceanic and Atmospheric Research (OAR) laboratories and NCAR. The aerosol component implemented into UFS-Chem is based on the current operational GEFS-Aerosols v12.3 and utilizes the Common Community Physics Package (CCPP) infrastructure with updates to wet deposition, dust and fire emission, etc. Both these two global aerosols forecast models include the direct and semi-direct radiative feedback from online aerosols prediction. Various global fire emission data, as well as their ensemble product, are employed to quantify the uncertainties associated with fire aerosol prediction. The capabilities of UFS-Aerosols and UFS-Chem in medium-range and S2S predictions of fire aerosol are assessed and compared using observations from reanalysis data, ground-based measurements, and satellite data. Additionally, preliminary blending and machine learning methods have been developed to predict fire emission and improve the S2S prediction. 

How to cite: Zhang, L., Grell, G., Bhattacharjee, P., Sun, S., Jensen, A., Schnell, J., Li, H., Li, Y., Baker, B., Henderson, J., Ahmadov, R., Bernardet, L., Tong, D., Sun, Z., Pan, L., Fu, B., Montuoro, R., He, J., Schwantes, R., and Wang, S. and the NOAA team: Predicting Fire Aerosols and their Impact on Subseasonal to Seasonal Weather Forecasts in NOAA’s Global Aerosol Forecast Systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6827,, 2024.

Henk Eskes and Thanos Tsikerdekis and the CAMS global developers and validation team

The Copernicus Atmosphere Monitoring Service (CAMS) is providing daily analyses and forecasts of the composition of the atmosphere, including the reactive gases such as ozone, CO, NO2, HCHO, SO2, aerosol species and greenhouse gases. The global CAMS analysis system (IFS-COMPO) is based on the ECMWF Integrated Forecast System (IFS) for numerical weather prediction (NWP), and assimilates a large number of composition satellite products on top of the meteorological observations ingested in IFS. 

The global CAMS system is regularly upgraded, and the upgrades are simultaneous with the upgrades of NWP-IFS. The upgrade to Cy48R1, operational since 27 June 2023, introduced a large number of code changes and improvements, both for COMPO and for NWP. The COMPO innovations include the introduction of full stratospheric chemistry, a major update of the emissions, of the aerosol model, including the representation of secondary organic aerosol, several updates of the dust life cycle and optics, and inorganic chemistry in the troposphere. Concering data assimilation, the assimilation of VIIRS AOD and TROPOMI CO were implemented in 2023. 

The CAMS Cy48R1 upgrade was evaluated using a large number of independent measurement datasets, including surface in situ, surface remote sensing, routine aircraft and balloon and satellite observations. In our contribution we present the validation results for Cy48R1. The new cycle is compared with the previous operational system (Cy47R3), with the independent observations as reference. Results are provided for the period October 2022 to June 2023 for which daily forecasts from both cycles are available. 

Major improvements in skill are found for the ozone profile in the lower-middle stratosphere and for stratospheric NO2 due to the inclusion of full stratospheric chemistry. Stratospheric trace gases compare well with ACE-FTS observations between 10-200 hPa, with larger deviations between 1-10 hPa. The impact of the updated emissions is especially visible over East Asia and is beneficial for the trace gases O3, NO2, and SO2. The CO column assimilation is now anchored by IASI instead of MOPITT which is beneficial for most of the CO comparisons, and the assimilation of TROPOMI CO data improves the model CO field in the troposphere. In general the aerosol optical depth has improved globally, but the dust evaluation shows more mixed results. 

In summary, 83% of the evaluation datasets show a neutral or improved performance of Cy48R1 compared to the previous operational CAMS system, while 17% indicate a (slight) degradation, which shows the overall success of this upgrade. 

This presentation summarises the results achieved by a large consortium of scientists working on CAMS, including the ECMWF staff, the developers of the global CAMS modelling system, the data assimilation team at ECMWF, and the CAMS validation teams. We acknowledge their contributions to this work.

How to cite: Eskes, H. and Tsikerdekis, T. and the CAMS global developers and validation team: Evaluation of the Copernicus Atmosphere Monitoring Service Cy48R1 upgrade of June 2023, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8447,, 2024.

Advancements made to NOAA’s FENGSHA dust emission scheme within the Unified Forecast System with applications to regional air quality and subseasonal to seasonal forecasting
(withdrawn after no-show)
Barry Baker, Margaret Marvin, Wei-Ting Hung, Ivanka Stajner, Jeff McQueen, Raffaele Montuoro, Cory Martin, Jianping Huang, Patrick Campbell, Youhua Tang, Georg Grell, Li Zhang, Ravan Ahmadov, and Partha Bhattacharjee
Fanglin Yang and Anning Cheng

NOAA is collaborating with the US weather and climate science community to develop the fully coupled Unified Forecast System (UFS) for both research and operations across different temporal and spatial scales.  Active development and evaluation are underway to improve the representation of aerosols and its interaction with radiation and clouds in UFS applications.  Aerosols, acting as cloud condensation nuclei and ice nuclei,  affect cloud droplet number concentration and size, cloud lifetime and consequently cloud radiative properties.   Up to now, the impact of aerosols on clouds has not been included in UFS global applications for operation.  In this study we activate the interactions of aerosols with clouds in the Thompson double moment microphysics scheme used by the UFS-based  Global Forecast System (GFS) application.  MERRA2 aerosol climatologies instead of prognostic aerosols are employed for this study to reduce the complexity and uncertainty in aerosol prediction itself.  GFS free forecasts at the 13-km horizontal resolution for the summer of 2020 were conducted to investigate the uncertainty of the representation of aerosol-cloud interaction and the associated impact on GFS medium-range weather forecasts.   The experiment with aerosol-cloud interaction produced an overall larger number concentration of cloud droplets and cloud liquid mixing ratio, and larger number concentration of cloud ice and ice mixing ratio in the low-middle troposphere, but less above the upper troposphere.  The relationships between aerosol optical depth and cloud droplet number concentration were analyzed and compared with MODIS retrievals. In addition, the relationships between aerosol loading and optical properties with liquid water path, shortwave and long wave radiation were examined.  CCPP single column model was also used to help understand the uncertainty of aerosol-cloud interaction algorithms employed by the UFS.  

How to cite: Yang, F. and Cheng, A.: Uncertainty and Impact of Aerosol-Cloud Interaction in the Unified Forecast System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12973,, 2024.

Posters virtual: Wed, 17 Apr, 14:00–15:45 | vHall X5

Display time: Wed, 17 Apr 08:30–Wed, 17 Apr 18:00
Chairperson: Lu Ren
Towards radiatively interactive prognostic aerosol in ECMWF NWP forecasts
(withdrawn after no-show)
Ramiro Checa-Garcia, Robin Hogan, Tim Stockdale, Johannes Flemming, and Retish Senan