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From a weather forecasting perspective, the Arctic poses particular challenges for mainly two reasons: 1) The observational data are sparse and 2) the weather phenomena responsible for severe weather, such as polar lows, Arctic fronts, and orographic influences on airflow, are poorly resolved and described by the operational numerical weather prediction (NWP) models. The Norwegian International Polar Year (IPY)– The Observing System Research and Predictability Experiment (THORPEX) project (2007–10) sought to significantly improve weather forecasts of these phenomena through a combined modeling and observational effort. The crux of the observational effort was a 3-week international field campaign out of northern Norway in early 2008, combining airborne and surface-based observations. The main platform of the field campaign was the Deutsches Zentrum für Luft- und Raumfahrt (DLR) research aircraft Falcon, equipped with lidar systems for profiling of aerosols, humidity, and wind, in addition to in situ measurements and dropsondes. A total of 12 missions were flown, yielding detailed observations of polar lows, Arctic fronts, and orographic low-level jets near Spitsbergen, the coast of northern Norway, and the east coast of Greenland. The lidar systems enabled exceptionally detailed measurements of orographic jets caused by the orography of Spitsbergen. Two major polar low developments over the Norwegian Sea were captured during the campaign. In the first polar low case, three f lights were carried out, providing a first-ever probing of the full life cycle of a polar low. Targeting observations by the aircraft in sensitive areas led to improvements in predicted track and intensity of the polar low. Here highlights from the field campaign, as well as from ongoing follow-up investigations, are presented. Highlights from the development of a new limitedarea model ensemble prediction system for the Arctic, as well as an exploitation of new satellite data [Infrared Atmospheric Sounding Interferometer (IASI) data], are also included.
From a weather forecasting perspective, the Arctic poses particular challenges for mainly two reasons: 1) The observational data are sparse and 2) the weather phenomena responsible for severe weather, such as polar lows, Arctic fronts, and orographic influences on airflow, are poorly resolved and described by the operational numerical weather prediction (NWP) models. The Norwegian International Polar Year (IPY)– The Observing System Research and Predictability Experiment (THORPEX) project (2007–10) sought to significantly improve weather forecasts of these phenomena through a combined modeling and observational effort. The crux of the observational effort was a 3-week international field campaign out of northern Norway in early 2008, combining airborne and surface-based observations. The main platform of the field campaign was the Deutsches Zentrum für Luft- und Raumfahrt (DLR) research aircraft Falcon, equipped with lidar systems for profiling of aerosols, humidity, and wind, in addition to in situ measurements and dropsondes. A total of 12 missions were flown, yielding detailed observations of polar lows, Arctic fronts, and orographic low-level jets near Spitsbergen, the coast of northern Norway, and the east coast of Greenland. The lidar systems enabled exceptionally detailed measurements of orographic jets caused by the orography of Spitsbergen. Two major polar low developments over the Norwegian Sea were captured during the campaign. In the first polar low case, three f lights were carried out, providing a first-ever probing of the full life cycle of a polar low. Targeting observations by the aircraft in sensitive areas led to improvements in predicted track and intensity of the polar low. Here highlights from the field campaign, as well as from ongoing follow-up investigations, are presented. Highlights from the development of a new limitedarea model ensemble prediction system for the Arctic, as well as an exploitation of new satellite data [Infrared Atmospheric Sounding Interferometer (IASI) data], are also included.
Abstract
Climate change yields both challenges and opportunities. In both cases, costly adaptations and transformations are necessary and desirable, and these must be based on realistic and relevant climate information. However, it is often difficult for climate scientists to communicate this information to decision-makers and stakeholders, and it can be equally difficult for such actors to interpret and put the information to use. In this essay, we discuss experiences and present recommendations for scientists producing climate services. The basis is our work in several climate service projects. One of them aimed to provide local-scale climate data for municipalities in western Norway and to explore how the data were interpreted and implemented. The project was first based solely on climate science expertise, and the participants did not have sufficient competence on coproduction and knowledge about the regulatory and political landscape in which municipalities operate. Initially, we also subscribed to an outdated idea of climate services, where knowledge providers (climate scientists) “deliver” their information to knowledge users (e.g., municipal planners). Increasingly, as stressed in the literature on coproduction of knowledge, we learned that climate service should be an iterative process where actionable information is coproduced through two-way dialogue. On the basis of these and other lessons learned the hard way, we provide a set of concrete recommendations on how to embed the idea of coproduction from the preproposal stage to beyond the end of climate service projects.
Abstract
Climate change yields both challenges and opportunities. In both cases, costly adaptations and transformations are necessary and desirable, and these must be based on realistic and relevant climate information. However, it is often difficult for climate scientists to communicate this information to decision-makers and stakeholders, and it can be equally difficult for such actors to interpret and put the information to use. In this essay, we discuss experiences and present recommendations for scientists producing climate services. The basis is our work in several climate service projects. One of them aimed to provide local-scale climate data for municipalities in western Norway and to explore how the data were interpreted and implemented. The project was first based solely on climate science expertise, and the participants did not have sufficient competence on coproduction and knowledge about the regulatory and political landscape in which municipalities operate. Initially, we also subscribed to an outdated idea of climate services, where knowledge providers (climate scientists) “deliver” their information to knowledge users (e.g., municipal planners). Increasingly, as stressed in the literature on coproduction of knowledge, we learned that climate service should be an iterative process where actionable information is coproduced through two-way dialogue. On the basis of these and other lessons learned the hard way, we provide a set of concrete recommendations on how to embed the idea of coproduction from the preproposal stage to beyond the end of climate service projects.
Abstract
The Iceland Greenland Seas Project (IGP) is a coordinated atmosphere–ocean research program investigating climate processes in the source region of the densest waters of the Atlantic meridional overturning circulation. During February and March 2018, a field campaign was executed over the Iceland and southern Greenland Seas that utilized a range of observing platforms to investigate critical processes in the region, including a research vessel, a research aircraft, moorings, sea gliders, floats, and a meteorological buoy. A remarkable feature of the field campaign was the highly coordinated deployment of the observing platforms, whereby the research vessel and aircraft tracks were planned in concert to allow simultaneous sampling of the atmosphere, the ocean, and their interactions. This joint planning was supported by tailor-made convection-permitting weather forecasts and novel diagnostics from an ensemble prediction system. The scientific aims of the IGP are to characterize the atmospheric forcing and the ocean response of coupled processes; in particular, cold-air outbreaks in the vicinity of the marginal ice zone and their triggering of oceanic heat loss, and the role of freshwater in the generation of dense water masses. The campaign observed the life cycle of a long-lasting cold-air outbreak over the Iceland Sea and the development of a cold-air outbreak over the Greenland Sea. Repeated profiling revealed the immediate impact on the ocean, while a comprehensive hydrographic survey provided a rare picture of these subpolar seas in winter. A joint atmosphere–ocean approach is also being used in the analysis phase, with coupled observational analysis and coordinated numerical modeling activities underway.
Abstract
The Iceland Greenland Seas Project (IGP) is a coordinated atmosphere–ocean research program investigating climate processes in the source region of the densest waters of the Atlantic meridional overturning circulation. During February and March 2018, a field campaign was executed over the Iceland and southern Greenland Seas that utilized a range of observing platforms to investigate critical processes in the region, including a research vessel, a research aircraft, moorings, sea gliders, floats, and a meteorological buoy. A remarkable feature of the field campaign was the highly coordinated deployment of the observing platforms, whereby the research vessel and aircraft tracks were planned in concert to allow simultaneous sampling of the atmosphere, the ocean, and their interactions. This joint planning was supported by tailor-made convection-permitting weather forecasts and novel diagnostics from an ensemble prediction system. The scientific aims of the IGP are to characterize the atmospheric forcing and the ocean response of coupled processes; in particular, cold-air outbreaks in the vicinity of the marginal ice zone and their triggering of oceanic heat loss, and the role of freshwater in the generation of dense water masses. The campaign observed the life cycle of a long-lasting cold-air outbreak over the Iceland Sea and the development of a cold-air outbreak over the Greenland Sea. Repeated profiling revealed the immediate impact on the ocean, while a comprehensive hydrographic survey provided a rare picture of these subpolar seas in winter. A joint atmosphere–ocean approach is also being used in the analysis phase, with coupled observational analysis and coordinated numerical modeling activities underway.
Abstract
Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction on time scales of several weeks for many extreme events. Here we provide an overview of subseasonal predictability for case studies of some of the most prominent extreme events across the globe using the ECMWF S2S prediction system: heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. The considered heatwaves exhibit predictability on time scales of 3–4 weeks, while this time scale is 2–3 weeks for cold spells. Precipitation extremes are the least predictable among the considered case studies. Tropical cyclones, on the other hand, can exhibit probabilistic predictability on time scales of up to 3 weeks, which in the presented cases was aided by remote precursors such as the Madden–Julian oscillation. For extratropical cyclones, lead times are found to be shorter. These case studies clearly illustrate the potential for event-dependent advance warnings for a wide range of extreme events. The subseasonal predictability of extreme events demonstrated here allows for an extension of warning horizons, provides advance information to impact modelers, and informs communities and stakeholders affected by the impacts of extreme weather events.
Abstract
Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction on time scales of several weeks for many extreme events. Here we provide an overview of subseasonal predictability for case studies of some of the most prominent extreme events across the globe using the ECMWF S2S prediction system: heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. The considered heatwaves exhibit predictability on time scales of 3–4 weeks, while this time scale is 2–3 weeks for cold spells. Precipitation extremes are the least predictable among the considered case studies. Tropical cyclones, on the other hand, can exhibit probabilistic predictability on time scales of up to 3 weeks, which in the presented cases was aided by remote precursors such as the Madden–Julian oscillation. For extratropical cyclones, lead times are found to be shorter. These case studies clearly illustrate the potential for event-dependent advance warnings for a wide range of extreme events. The subseasonal predictability of extreme events demonstrated here allows for an extension of warning horizons, provides advance information to impact modelers, and informs communities and stakeholders affected by the impacts of extreme weather events.
