The purpose of this special issue is the compilation of modelling and observational studies on the role of atmospheric aerosols in the life cycle and composition of fog and low clouds in southern Africa as well as their mutual links with climate and biogeochemistry.

The special issue is motivated by new results from the AeroFog project, focusing on the hyperarid coastal deserts of Namibia, on the western coast of southern Africa. AeroFog is based on two intensive, ground-based field deployments, which took place in May and September 2024 along the coast and in the desert, and the long-term monitoring and analysis of remote-sensing products. Observations, satellite measurements, and modelling address the aerosol radiative, chemical, and microphysical interactions relevant to fog as well as the meteorological fields and dynamical processes that influence aerosol emission, transport, and deposition. Building on the diverse expertise of scientists in both the Northern and the Southern hemispheres, AeroFog aims to develop a holistic understanding of the mechanisms by which nutrients and pollutants are found in fog and the effect of fog on the biogeochemistry of regional ecosystems. The special issue comprises papers with complementary goals so as to encourage the exchange of ideas among previous, current, and planned large-scale projects and activities in the region.

The natural and anthropogenic climate drivers that impact Earth’s radiation balance, influencing climate states and forcing climate change are termed climate forcing agents. Globally representative forcing estimates are needed to drive Earth system models to simulate past and project future climate states. The Coupled Model Intercomparison Project (CMIP) Forcing Task Team aims to identify, develop, document, and deliver forcings for next-generation models participating in the seventh phase of CMIP (CMIP7). This next phase is likely to be a core contribution to the IPCC seventh assessment cycle (AR7). The special issue welcomes papers documenting forcing data development and evaluation, along with those describing CMIP7 forcing characteristics (in contrast to previous versions). We also invite papers that quantify and assess uncertainties in the spatial and temporal forcing distributions and the influence of forcing on the evolution of climate states across Earth system model configurations.

This ESSD special issue aims to provide access to datasets collected during the Pallas Cloud Experiment (PaCE) that took place in the subarctic region of Finnish Lapland between 12 September and 15 December 2022. The campaign was hosted by the Finnish Meteorological Institute (FMI) and utilized several different approaches to collect extensive datasets on atmospheric properties: a concurrent ground and airborne in situ approach and remote-sensing measurements. The intensive part of the campaign lasted 1 month, from 15 September to 15 October, and focused on vertical profiling of atmospheric properties. Several European institutes contributed to the PaCE campaign by deploying different instrumentation and platforms. Sammaltunturi station (67°58' N, 24°07' E;560 m a.s.l.), a part of the Pallas Atmosphere–Ecosystem Supersite and Global Atmospheric Watch (GAW) programme, located 170 km north of the Arctic Circle, was utilized as a reference point for all measurements. Sammaltunturi station sits on top of a treeless hill (565 m a.s.l.) and is inside a cloud about 50 % of the time during autumn; thus, it is an ideal place for in situ cloud measurements. The station is equipped with various aerosol, cloud, reactive gas, and meteorology instrumentation. Additionally, a square of reserved airspace, TEMPO D area Pallas, with a side length of 7 km and a ceiling height of 2 km a.g.l. centred on Sammaltunturi station provided a safe playground for uncrewed airborne platforms. Remote-sensing instruments, namely a Doppler lidar HALO StreamLine XR (HALO Photonics), ceilometers (models CL31 and CL61, Vaisala Oyj), and a cloud radar (model RPG FMCW 94 GHz,RPG Radiometric Physics), were deployed around Kenttarova station (67°59' N, 24°14' E; 347 m a.s.l.), which is surrounded by coniferous forest. These instruments operated continuously for the whole campaign (15 September–15 December), although with short technical and maintenance breaks.

The Max Planck Institute (MPI) deployed their Helikite with a payload focused on cloud microphysics and atmospheric turbulence measurements. The Swiss Federal Institute of Technology (EPFL) used another Helikite to measure aerosol physical and optical properties. The Karlsruhe Institute of Technology (KIT) provided their mobile cloud chamber for the investigation of ice-nucleating particles (INPs), a Portable Ice Nucleation Experiment (PINE) unit, at the Sammaltunturi station and also collected INPs on filters using a fixed-wing UAV at different altitudes. The TU Wien (TUW) provided a single-particle Wideband Integrated Bioaerosol Sensor (WIBS-5) for measurements of bacteria, moulds, and other biogenic aerosols at Sammaltunturi station. The University of Hertfordshire provided their Universal Cloud and Aerosol Sounding System (UCASS) for the physical characterization of aerosol and clouds in vertical column using a small fixed-wing UAV. FMI deployed two types of small UAVs: multi-rotor profilers to measure meteorological parameters and particulate matter up to 500 m a.g.l and fixed-wing profilers to measure the aerosol and cloud physical properties and meteorological parameters up to 2000 m a.g.l. Also, the FMI tethered balloon system was deployed for aerosol and cloud measurements.

For this SI we welcome manuscripts on activities such as MIIPs – Model Intercomparison and Improvement Projects that target long-standing issues in the representation of small-scale processes in numerical weather prediction and climate models. The initiatives may have been taken during the 10-year Polar Prediction Project (PPP) that finished at the end of 2022 or during the Polar Coupled Analysis and Prediction for Services (PCAPS) both part of the WMO World Weather Research Program. These programs suggest an emphasis on processes that are especially important for the polar regions, but contributions that are relevant and important for model performance in other regions of the world are also welcome. Specific targets are the representation of stably stratified boundary layers, mixed-phase clouds and atmospheric coupling with snow and or ice-covered surfaces, sea-ice, ocean mixing etc.

The intention of this SI is to publish results from MIIPs that establish new and improved workflows to facilitate a more efficient path to improved process representation. This includes research-grade observations that are packaged in an easy-to-use format which combine high-frequency observations of the surface and the atmosphere above to be able to directly compare with the parameterizations used in models using time-step data. The Merged Data File (MDF) format that is defined for both observations and model output come with a series of tools that is transferable between models and observational data collections for both file production and analysis. The SI especially welcome contributions that build on, or further develop the MDF concept including new variables, types of data, sites or new analysis tools such as process-oriented diagnostics or insights in models using the targeted files.

The purpose of this special issue is the compilation of modelling and observational studies on the role of atmospheric aerosols in the life cycle and composition of fog and low clouds in southern Africa as well as their mutual links with climate and biogeochemistry.

The special issue is motivated by new results from the AeroFog project, focusing on the hyperarid coastal deserts of Namibia, on the western coast of southern Africa. AeroFog is based on two intensive, ground-based field deployments, which took place in May and September 2024 along the coast and in the desert, and the long-term monitoring and analysis of remote-sensing products. Observations, satellite measurements, and modelling address the aerosol radiative, chemical, and microphysical interactions relevant to fog as well as the meteorological fields and dynamical processes that influence aerosol emission, transport, and deposition. Building on the diverse expertise of scientists in both the Northern and the Southern hemispheres, AeroFog aims to develop a holistic understanding of the mechanisms by which nutrients and pollutants are found in fog and the effect of fog on the biogeochemistry of regional ecosystems. The special issue comprises papers with complementary goals so as to encourage the exchange of ideas among previous, current, and planned large-scale projects and activities in the region.

The natural and anthropogenic climate drivers that impact Earth’s radiation balance, influencing climate states and forcing climate change are termed climate forcing agents. Globally representative forcing estimates are needed to drive Earth system models to simulate past and project future climate states. The Coupled Model Intercomparison Project (CMIP) Forcing Task Team aims to identify, develop, document, and deliver forcings for next-generation models participating in the seventh phase of CMIP (CMIP7). This next phase is likely to be a core contribution to the IPCC seventh assessment cycle (AR7). The special issue welcomes papers documenting forcing data development and evaluation, along with those describing CMIP7 forcing characteristics (in contrast to previous versions). We also invite papers that quantify and assess uncertainties in the spatial and temporal forcing distributions and the influence of forcing on the evolution of climate states across Earth system model configurations.

This ESSD special issue aims to provide access to datasets collected during the Pallas Cloud Experiment (PaCE) that took place in the subarctic region of Finnish Lapland between 12 September and 15 December 2022. The campaign was hosted by the Finnish Meteorological Institute (FMI) and utilized several different approaches to collect extensive datasets on atmospheric properties: a concurrent ground and airborne in situ approach and remote-sensing measurements. The intensive part of the campaign lasted 1 month, from 15 September to 15 October, and focused on vertical profiling of atmospheric properties. Several European institutes contributed to the PaCE campaign by deploying different instrumentation and platforms. Sammaltunturi station (67°58' N, 24°07' E;560 m a.s.l.), a part of the Pallas Atmosphere–Ecosystem Supersite and Global Atmospheric Watch (GAW) programme, located 170 km north of the Arctic Circle, was utilized as a reference point for all measurements. Sammaltunturi station sits on top of a treeless hill (565 m a.s.l.) and is inside a cloud about 50 % of the time during autumn; thus, it is an ideal place for in situ cloud measurements. The station is equipped with various aerosol, cloud, reactive gas, and meteorology instrumentation. Additionally, a square of reserved airspace, TEMPO D area Pallas, with a side length of 7 km and a ceiling height of 2 km a.g.l. centred on Sammaltunturi station provided a safe playground for uncrewed airborne platforms. Remote-sensing instruments, namely a Doppler lidar HALO StreamLine XR (HALO Photonics), ceilometers (models CL31 and CL61, Vaisala Oyj), and a cloud radar (model RPG FMCW 94 GHz,RPG Radiometric Physics), were deployed around Kenttarova station (67°59' N, 24°14' E; 347 m a.s.l.), which is surrounded by coniferous forest. These instruments operated continuously for the whole campaign (15 September–15 December), although with short technical and maintenance breaks.

The Max Planck Institute (MPI) deployed their Helikite with a payload focused on cloud microphysics and atmospheric turbulence measurements. The Swiss Federal Institute of Technology (EPFL) used another Helikite to measure aerosol physical and optical properties. The Karlsruhe Institute of Technology (KIT) provided their mobile cloud chamber for the investigation of ice-nucleating particles (INPs), a Portable Ice Nucleation Experiment (PINE) unit, at the Sammaltunturi station and also collected INPs on filters using a fixed-wing UAV at different altitudes. The TU Wien (TUW) provided a single-particle Wideband Integrated Bioaerosol Sensor (WIBS-5) for measurements of bacteria, moulds, and other biogenic aerosols at Sammaltunturi station. The University of Hertfordshire provided their Universal Cloud and Aerosol Sounding System (UCASS) for the physical characterization of aerosol and clouds in vertical column using a small fixed-wing UAV. FMI deployed two types of small UAVs: multi-rotor profilers to measure meteorological parameters and particulate matter up to 500 m a.g.l and fixed-wing profilers to measure the aerosol and cloud physical properties and meteorological parameters up to 2000 m a.g.l. Also, the FMI tethered balloon system was deployed for aerosol and cloud measurements.

For this SI we welcome manuscripts on activities such as MIIPs – Model Intercomparison and Improvement Projects that target long-standing issues in the representation of small-scale processes in numerical weather prediction and climate models. The initiatives may have been taken during the 10-year Polar Prediction Project (PPP) that finished at the end of 2022 or during the Polar Coupled Analysis and Prediction for Services (PCAPS) both part of the WMO World Weather Research Program. These programs suggest an emphasis on processes that are especially important for the polar regions, but contributions that are relevant and important for model performance in other regions of the world are also welcome. Specific targets are the representation of stably stratified boundary layers, mixed-phase clouds and atmospheric coupling with snow and or ice-covered surfaces, sea-ice, ocean mixing etc.

The intention of this SI is to publish results from MIIPs that establish new and improved workflows to facilitate a more efficient path to improved process representation. This includes research-grade observations that are packaged in an easy-to-use format which combine high-frequency observations of the surface and the atmosphere above to be able to directly compare with the parameterizations used in models using time-step data. The Merged Data File (MDF) format that is defined for both observations and model output come with a series of tools that is transferable between models and observational data collections for both file production and analysis. The SI especially welcome contributions that build on, or further develop the MDF concept including new variables, types of data, sites or new analysis tools such as process-oriented diagnostics or insights in models using the targeted files.