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.

This ESSD special issue responds to an international need to improve the understanding and modelling of mountain snow and ice hydrological processes. Data sets contributed to the special issue should support and promote research on the effects of mountain snowpacks and glaciers on water supply as well as study of variations in energy and water exchange amongst different high-altitude regions. This initiative arises from a new GEWEX Hydroclimatology Panel cross-cut project – INARCH, the International Network for Alpine Research Catchment Hydrology (www.usask.ca/inarch ). The guest editors invite contributions of openly available detailed meteorological and hydrological observational archives from long-term research catchments at high temporal resolution (at least 5 years of continuous data with hourly sampling intervals for meteorological data, daily precipitation and streamflow, and regular snow and/or glacier mass balance surveys) in well-instrumented mountain regions around the world. Contributors and researchers will use this mountain hydrology data publication special issue for the benefit of global alpine hydrological research.

This special issue aims to (1) provide a high-quality collection of papers showcasing methodological advances in compound- and multi-risk analysis and management, (2) consolidate and foster learning across the compound-risk and (multi-hazard) multi-risk research fields, and (3) identify future research avenues.

Recent years have demonstrated the immense challenges faced by society as a result of the increasing complexity of disaster risk and due to climate change. Societies impacted by multiple natural hazards (either in sequence or at the same time) face different challenges than when impacted by a single hazard that occurs in isolation (AghaKouchak et al., 2020; Hillier and Dixon, 2020; Raymond et al., 2020a). The impacts of compound- and multi-hazard disasters are complex and may be driven by the consecutive nature of the (drivers of) hazards themselves (Hillier et al., 2020; Mora et al., 2018; Ridder et al., 2020; Zscheischler et al., 2018), the spatiotemporal dynamics in exposure and vulnerability caused by earlier events (de Ruiter et al., 2020; de Ruiter and Van Loon, 2022; Reichstein et al., 2021), or the influences of risk management on the dynamics of risk (Simpson et al., 2022). This makes managing compound- and multi-risk disasters especially complex, and several studies have noted that their management may require more comprehensive approaches than single-hazard disasters (Simpson et al., 2023; De Ruiter et al., 2021; Schippers, 2020).

In recent years, international agreements such as the Paris Agreement (2015) and the UN’s Sendai Framework for Disaster Risk Reduction (SFDRR) (UNDRR, 2015) have called upon the disaster risk science community to move away from siloed hazard thinking (i.e. assessing the risk from hazards one by one) and toward improving our understanding of these spatiotemporal complexities of disaster risk. Similarly, the latest series of Intergovernmental Panel on Climate Change (IPCC) reports recognizes the importance of accounting for multiple and complex risks. In a recent survey of members of the natural hazard research community, respondents noted that multi-hazards and resulting risks remain one of the core scientific challenges to be tackled (Sakic Trogrlic et al., 2022).

Subsequently, the past years have seen a rise in compound- and multi-risk (multi-hazard) studies that try to capture some of these complexities through advanced statistical methods (e.g. Zscheischler, 2017; Bevacqua et al., 2022; Couasnon et al., 2020), physically based models (Eilander et al., 2023; Couasnon et al., 2022), and multi-risk system analysis (e.g. Simpson et al., 2022; De Angeli et al., 2022; Van Westen and Greiving, 2017; Gill and Malamud, 2017; Ward et al., 2022). As a result, the compound- and multi-risk communities have developed largely in parallel with each other, and only in recent months have significant efforts been made to bring these two communities together, for example, as demonstrated by the American Geophysical Union (AGU) 2022 session focusing specifically on breaking silos between the two communities.

However, there is some interesting methodological and conceptual overlap between these communities and thus strong potential for catalyzing learning and innovation for (advancing) risk studies. The call from the international community has resulted in a proliferation of innovative methodological approaches across different disciplines, offering a vast array of possible options for multi- and systemic-risk reduction in practice. The importance of this topic is also apparent in recently funded research and networking projects including Damocles, The HuT, MIRACA, MYRIAD-EU, MEDiate, PARATUS, RECEIPT, CLIMAAX, Tomorrow’s Cities, Risk KAN, and NOAA’s Climate Adaptation Partnerships (formerly RISA), among others.

As early career researchers from both fields, we have contributed to shaping these two communities, and we perceive the need to bring them together to assess solutions for the future. However, despite these advances, there is still no single collection of high-quality scientific research papers focusing on methodological innovations for the analysis and management of both compound and multiple risks.

References:

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Eilander, D., Couasnon, A., Leijnse, T., Ikeuchi, H., Yamazaki, D., Muis, S., Dullaart, J., Haag, A., Winsemius, H. C., and Ward, P. J.: A globally applicable framework for compound flood hazard modeling, Nat. Hazards Earth Syst. Sci., 23, 823-846, https://doi.org/10.5194/nhess-23-823-2023, 2023.

Gill, J. C. and Malamud, B. D.: Hazard interactions and interaction networks (cascades) within multi-hazard methodologies, Earth Syst. Dynam., 7, 659-679, https://doi.org/10.5194/esd-7-659-2016, 2016.

Hillier, J. K. and Dixon, R. S.: Seasonal impact-based mapping of compound hazards, Environ. Res. Lett., 15, 114013, https://doi.org/10.1088/1748-9326/abbc3d, 2020.

Mora, C., Spirandelli, D., Franklin, E. C., Lynham, J., Kantar, M. B., Miles, W., Smith, C. Z., Freel, K., Moy, J., Louis, L. V., Barba, E. W., Bettinger, K., Frazier, A. G., Colburn IX, J. F., Hanasaki, N., Hawkins, E., Hirabayashi, Y., Knorr, W., Little, C. M., Emanuel, K., Sheffield, J., Patz, J. A., and Hunter, C. L.: Broad threat to humanity from cumulative climate hazards intensified by greenhouse gas emissions, Nat. Clim. Change, 8, 1062-1071, https://doi.org/10.1038/s41558-018-0315-6, 2018.

Raymond, C., Horton, R. M., Zscheischler, J., Martius, O., AghaKouchak, A., Balch, J., Bowen, S. G., Camargo, S. J., Hess, J., Kornhuber, K., Oppenheimer, M., Ruane, A. C., Wahl, T., and White, K.: Understanding and managing connected extreme events, Nat. Clim. Change, 10, 611-621, https://doi.org/10.1038/s41558-020-0790-4, 2020.

Reichstein, M., Riede, F., and Frank, D.: More floods, fires and cyclones—plan for domino effects on sustainability goals, Nature, 592, 347-349, https://doi.org/10.1038/d41586-021-00927-x, 2021.

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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.

This special issue will serve as a collection point for articles describing datasets associated with field campaigns taking place across the East River Watershed of Colorado over the last few years. This includes the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH), the Surface Atmosphere Integrated Field Laboratory (SAIL), the Sublimation of Snow (SOS) Project, and activities associated with the Watershed Function Science Focus Area (SFA) program. These projects have jointly supported the development of one of the most heavily observed mountainous watersheds in North America by collaboratively collecting observations of atmospheric and surface processes that influence mountainous hydrology in the Upper Colorado River Basin. These projects, primarily sponsored by the National Oceanic and Atmospheric Administration (NOAA), the U.S. Department of Energy (DOE), and the National Science Foundation (NSF), deployed a wide variety of instruments focused on a ~30 km transect around Crested Butte, Colorado, including surface based in situ and remote sensors, as well as mobile sensor systems on aircraft and surface vehicles. Additional data were collected across the broader region using aircraft to offer context for the observations collected in the East River watershed. Instrumentation was deployed by numerous groups, including four different NOAA laboratories, the DOE Atmospheric Radiation Measurement (ARM) program, the National Center for Atmospheric Research (NCAR) Earth Observing Laboratory (EOL), Lawrence Berkeley National Laboratory, US and international university partners, and private industry. In addition, several groups have completed numerical simulations over the operational area in connection with these projects. Informal collaborations have been additionally supported by the formation of a SPLASH–SAIL–SOS (S3) research community to advance atmospheric and surface science with these datasets. This S3 group has already undertaken an initial workshop, held in Boulder, Colorado, in November 2023, to plan scientific research that can leverage data from these different projects. This proposed Earth System Science Data special issue would enable a comprehensive survey of the diverse set of observations, datasets, and modeling results that have already been produced and is timely and necessary to serve as a central reference for both project participants and the international mountain hydrology and hydrometeorology research communities. The special issue is envisioned to include invited and contributed papers related to datasets collected and developed as part of the projects listed above.

Gijs de Boer is the PI for the recently-completed Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) project. SPLASH took place in the East River Watershed and is a significant source of data in this region. Dr. de Boer has an extensive scientific publication record on lower atmospheric processes, including over 80 peer-reviewed publications and several data papers. Additionally, he has previously served as a guest editor for two other ESSD special issues, and has extensive experience with the collection, curation, and publication of data.

Jessica Lundquist is the PI for the NSF-funded Sublimation of Snow (SOS) field campaign in the East River Watershed, and is currently working on two Department of Energy projects in the same location. Professor Lundquist is the author of over 110 peer-reviewed publications, with an h-index of 50. She has served as an Editor of Water Resources Research, during which time she was lead editor on a special issue on snow, and as an Associate Editor for the Journal of Hydrometeorology, for which she was awarded the Editor's award for the quality of her reviews. Professor Lundquist has extensive experience with data papers, through both publishing her own datasets and as the editor in charge of reviewing others' datasets.

Daniel Feldman is the PI for the DOE-funded Surface Atmosphere Integrated field Laboratory (SAIL) field campaign in the East River Watershed, and is currently working with the Department of Energy's Atmospheric System Research (ASR) and the Atmospheric Radiation Measurement (ARM) Programs on advancing science using a wide variety of the SAIL datasets. Dr. Feldman is the author of over 30 peer-reviewed publications He has served as an Associate Editor of the Journal of the Atmospheric Sciences, a Guest Editor for Remote Sensing, and currently serves on the Editorial Board in Frontiers in Environmental Science. Dr. Feldman has written and participated in data papers, and he works closely with and advises the Department of Energy's ARM Data Center that provides data, metadata, and resources to analyze those data to the public. He also works with the Department of Energy's Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) and other agencies, including NASA, NOAA, and NSF to support the dissemination of data and the provision of information on those data in peer-reviewed publication.

Charuleka Varadharajan is the PI for U.S. Department of Energy's data repository, the Environmental Systems Science Data Infrastructure for a Virtual Environment (ESS-DIVE). She also leads the hydrology and data management components for the DOE's Watershed Function SFA, which has collected extensive, interdisciplinary measurements in the region since 2015 and produced several public datasets. Dr. Varadharajan has published extensively on topics related to hydrology, biogeochemistry and data sciences, and specifically has published a data paper on some of the measurements in the region. As PI of a data repository and lead of large DOE project data science and management teams, she has extensive experience with the curation, and publication of data.

This special issue will serve as a collection point for articles describing datasets associated with field campaigns taking place across the East River Watershed of Colorado over the last few years. This includes the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH), the Surface Atmosphere Integrated Field Laboratory (SAIL), the Sublimation of Snow (SOS) Project, and activities associated with the Watershed Function Science Focus Area (SFA) program. These projects have jointly supported the development of one of the most heavily observed mountainous watersheds in North America by collaboratively collecting observations of atmospheric and surface processes that influence mountainous hydrology in the Upper Colorado River Basin. These projects, primarily sponsored by the National Oceanic and Atmospheric Administration (NOAA), the U.S. Department of Energy (DOE), and the National Science Foundation (NSF), deployed a wide variety of instruments focused on a ~30 km transect around Crested Butte, Colorado, including surface based in situ and remote sensors, as well as mobile sensor systems on aircraft and surface vehicles. Additional data were collected across the broader region using aircraft to offer context for the observations collected in the East River watershed. Instrumentation was deployed by numerous groups, including four different NOAA laboratories, the DOE Atmospheric Radiation Measurement (ARM) program, the National Center for Atmospheric Research (NCAR) Earth Observing Laboratory (EOL), Lawrence Berkeley National Laboratory, US and international university partners, and private industry. In addition, several groups have completed numerical simulations over the operational area in connection with these projects. Informal collaborations have been additionally supported by the formation of a SPLASH–SAIL–SOS (S3) research community to advance atmospheric and surface science with these datasets. This S3 group has already undertaken an initial workshop, held in Boulder, Colorado, in November 2023, to plan scientific research that can leverage data from these different projects. This proposed Earth System Science Data special issue would enable a comprehensive survey of the diverse set of observations, datasets, and modeling results that have already been produced and is timely and necessary to serve as a central reference for both project participants and the international mountain hydrology and hydrometeorology research communities. The special issue is envisioned to include invited and contributed papers related to datasets collected and developed as part of the projects listed above.

Gijs de Boer is the PI for the recently-completed Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) project. SPLASH took place in the East River Watershed and is a significant source of data in this region. Dr. de Boer has an extensive scientific publication record on lower atmospheric processes, including over 80 peer-reviewed publications and several data papers. Additionally, he has previously served as a guest editor for two other ESSD special issues, and has extensive experience with the collection, curation, and publication of data.

Jessica Lundquist is the PI for the NSF-funded Sublimation of Snow (SOS) field campaign in the East River Watershed, and is currently working on two Department of Energy projects in the same location. Professor Lundquist is the author of over 110 peer-reviewed publications, with an h-index of 50. She has served as an Editor of Water Resources Research, during which time she was lead editor on a special issue on snow, and as an Associate Editor for the Journal of Hydrometeorology, for which she was awarded the Editor's award for the quality of her reviews. Professor Lundquist has extensive experience with data papers, through both publishing her own datasets and as the editor in charge of reviewing others' datasets.

Daniel Feldman is the PI for the DOE-funded Surface Atmosphere Integrated field Laboratory (SAIL) field campaign in the East River Watershed, and is currently working with the Department of Energy's Atmospheric System Research (ASR) and the Atmospheric Radiation Measurement (ARM) Programs on advancing science using a wide variety of the SAIL datasets. Dr. Feldman is the author of over 30 peer-reviewed publications He has served as an Associate Editor of the Journal of the Atmospheric Sciences, a Guest Editor for Remote Sensing, and currently serves on the Editorial Board in Frontiers in Environmental Science. Dr. Feldman has written and participated in data papers, and he works closely with and advises the Department of Energy's ARM Data Center that provides data, metadata, and resources to analyze those data to the public. He also works with the Department of Energy's Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) and other agencies, including NASA, NOAA, and NSF to support the dissemination of data and the provision of information on those data in peer-reviewed publication.

Charuleka Varadharajan is the PI for U.S. Department of Energy's data repository, the Environmental Systems Science Data Infrastructure for a Virtual Environment (ESS-DIVE). She also leads the hydrology and data management components for the DOE's Watershed Function SFA, which has collected extensive, interdisciplinary measurements in the region since 2015 and produced several public datasets. Dr. Varadharajan has published extensively on topics related to hydrology, biogeochemistry and data sciences, and specifically has published a data paper on some of the measurements in the region. As PI of a data repository and lead of large DOE project data science and management teams, she has extensive experience with the curation, and publication of data.

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.

This special issue aims to (1) provide a high-quality collection of papers showcasing methodological advances in compound- and multi-risk analysis and management, (2) consolidate and foster learning across the compound-risk and (multi-hazard) multi-risk research fields, and (3) identify future research avenues.

Recent years have demonstrated the immense challenges faced by society as a result of the increasing complexity of disaster risk and due to climate change. Societies impacted by multiple natural hazards (either in sequence or at the same time) face different challenges than when impacted by a single hazard that occurs in isolation (AghaKouchak et al., 2020; Hillier and Dixon, 2020; Raymond et al., 2020a). The impacts of compound- and multi-hazard disasters are complex and may be driven by the consecutive nature of the (drivers of) hazards themselves (Hillier et al., 2020; Mora et al., 2018; Ridder et al., 2020; Zscheischler et al., 2018), the spatiotemporal dynamics in exposure and vulnerability caused by earlier events (de Ruiter et al., 2020; de Ruiter and Van Loon, 2022; Reichstein et al., 2021), or the influences of risk management on the dynamics of risk (Simpson et al., 2022). This makes managing compound- and multi-risk disasters especially complex, and several studies have noted that their management may require more comprehensive approaches than single-hazard disasters (Simpson et al., 2023; De Ruiter et al., 2021; Schippers, 2020).

In recent years, international agreements such as the Paris Agreement (2015) and the UN’s Sendai Framework for Disaster Risk Reduction (SFDRR) (UNDRR, 2015) have called upon the disaster risk science community to move away from siloed hazard thinking (i.e. assessing the risk from hazards one by one) and toward improving our understanding of these spatiotemporal complexities of disaster risk. Similarly, the latest series of Intergovernmental Panel on Climate Change (IPCC) reports recognizes the importance of accounting for multiple and complex risks. In a recent survey of members of the natural hazard research community, respondents noted that multi-hazards and resulting risks remain one of the core scientific challenges to be tackled (Sakic Trogrlic et al., 2022).

Subsequently, the past years have seen a rise in compound- and multi-risk (multi-hazard) studies that try to capture some of these complexities through advanced statistical methods (e.g. Zscheischler, 2017; Bevacqua et al., 2022; Couasnon et al., 2020), physically based models (Eilander et al., 2023; Couasnon et al., 2022), and multi-risk system analysis (e.g. Simpson et al., 2022; De Angeli et al., 2022; Van Westen and Greiving, 2017; Gill and Malamud, 2017; Ward et al., 2022). As a result, the compound- and multi-risk communities have developed largely in parallel with each other, and only in recent months have significant efforts been made to bring these two communities together, for example, as demonstrated by the American Geophysical Union (AGU) 2022 session focusing specifically on breaking silos between the two communities.

However, there is some interesting methodological and conceptual overlap between these communities and thus strong potential for catalyzing learning and innovation for (advancing) risk studies. The call from the international community has resulted in a proliferation of innovative methodological approaches across different disciplines, offering a vast array of possible options for multi- and systemic-risk reduction in practice. The importance of this topic is also apparent in recently funded research and networking projects including Damocles, The HuT, MIRACA, MYRIAD-EU, MEDiate, PARATUS, RECEIPT, CLIMAAX, Tomorrow’s Cities, Risk KAN, and NOAA’s Climate Adaptation Partnerships (formerly RISA), among others.

As early career researchers from both fields, we have contributed to shaping these two communities, and we perceive the need to bring them together to assess solutions for the future. However, despite these advances, there is still no single collection of high-quality scientific research papers focusing on methodological innovations for the analysis and management of both compound and multiple risks.

References:

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Hillier, J. K. and Dixon, R. S.: Seasonal impact-based mapping of compound hazards, Environ. Res. Lett., 15, 114013, https://doi.org/10.1088/1748-9326/abbc3d, 2020.

Mora, C., Spirandelli, D., Franklin, E. C., Lynham, J., Kantar, M. B., Miles, W., Smith, C. Z., Freel, K., Moy, J., Louis, L. V., Barba, E. W., Bettinger, K., Frazier, A. G., Colburn IX, J. F., Hanasaki, N., Hawkins, E., Hirabayashi, Y., Knorr, W., Little, C. M., Emanuel, K., Sheffield, J., Patz, J. A., and Hunter, C. L.: Broad threat to humanity from cumulative climate hazards intensified by greenhouse gas emissions, Nat. Clim. Change, 8, 1062-1071, https://doi.org/10.1038/s41558-018-0315-6, 2018.

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This ESSD special issue responds to an international need to improve the understanding and modelling of mountain snow and ice hydrological processes. Data sets contributed to the special issue should support and promote research on the effects of mountain snowpacks and glaciers on water supply as well as study of variations in energy and water exchange amongst different high-altitude regions. This initiative arises from a new GEWEX Hydroclimatology Panel cross-cut project – INARCH, the International Network for Alpine Research Catchment Hydrology (www.usask.ca/inarch ). The guest editors invite contributions of openly available detailed meteorological and hydrological observational archives from long-term research catchments at high temporal resolution (at least 5 years of continuous data with hourly sampling intervals for meteorological data, daily precipitation and streamflow, and regular snow and/or glacier mass balance surveys) in well-instrumented mountain regions around the world. Contributors and researchers will use this mountain hydrology data publication special issue for the benefit of global alpine hydrological research.