Periodic Reporting for period 1 - LAWINE (Links between warming Arctic and climate extremes in northern Eurasia)
Período documentado: 2017-02-01 hasta 2019-01-31
The Arctic is experiencing unprecedented climate change, including rapid warming of the lowest portion of Earth's atmosphere, troposphere, and dramatic loss of sea ice, land ice and snow cover. Because the Arctic is an integral part of the global climate system, an open question is to what extent its warming impacts the climates of mid-latitudes. Although an understanding of complex processes linking Arctic amplification with mid-latitude climate extremes is emerging, this understanding is incomplete and important issues remain unclear due to imperfect models and sparse observational records. To address this shortcoming our main objective is to identify remote regions that generate teleconnections affecting the occurrence, intensity and duration of extreme climate events in northern Eurasia. We aim to analyse how well state-of-the-science weather, ocean and climate models simulate the identified associations and to identify physical mechanisms of the teleconnections affecting the northern Eurasian climate extremes.
The project had three specific science objectives to improve the understanding of teleconnections affecting northern Eurasia. Results have been published or submitted to peer-reviewed journals and presented in scientific conferences and workshops. During the latter part of the project, the beneficiary was increasingly involved in teaching and tuition of hydrosphere geophysics due to his appointment as a university professor.
Objective 1 was to identify remote regions that generate teleconnections affecting the occurrence, intensity and duration of extreme climate events in northern Eurasia with the work carried out in Work Package 1. Related to this objective, Vihma et al. (2019b) studied factors influencing European winter temperatures with the focus on Arctic warming. They identified that European winter temperatures were primarily linked to the Atlantic and Scandinavian large-scale weather conditions. In addition, Nygård et al. (2019) used the Self-Organizing Maps method to obtain a comprehensive picture on how large-scale atmospheric circulation is related to moisture transport over northern mid-to-high latitudes. They found that much of the moisture provided by the evaporation in the Arctic is actually transported southwards and that the positive phase of the Arctic Oscillation increases moisture and clouds in northern Eurasia. Tyrrell et al. (2019) studied a case occurred in October 2016 when anomalous Siberian forcing generated a response in atmospheric circulation over northern Europe and Atlantic. In summary, these results highlight that regional combinations and interactions in air-ice-ocean systems surrounding the northern Eurasia play crucial roles in determining its weather, including extreme events.
Objective 2 was to analyse how well state-of-the-science climate models simulate the identified associations and the work was carried out in Work Package 2. Fox-Kemper et al. (2019) reviewed recent progress in the development of ocean and sea-ice modelling. They summarized new developments, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations. Benestad et al. (2017) addressed the problem of climate model experiment design and questioned whether climate model information could be used more effectively to design ‘smarter’ ensemble experiments, improving the distillation of information from ensembles, and helping interpret the relative merits of additional simulations. Uotila et al. (2019) assessed physical environmental states derived from an ensemble of ocean reanalysis products in the polar regions which are used as initial conditions for climate models. They identified large variability between individual products, but also found that their mean state is a useful estimate for the state of the polar oceans. Jonassen et al. (2019) used independent observations from the Antarctic to assess the performance of global atmospheric reanalyses, which meteorological models are also used in climate modelling. They identified a common warm bias which has persisted over decades. Vihma et al. (2019) called for the establishment of a marine Arctic component of the Pan-Eurasian Experiment (MA-PEEX) as a component of the PEEX research infrastructure to best utilize the existing and future observations and to further develop the atmosphere-ocean reanalysis products. It is important that MA-PEEX will promote international collaboration and multidisciplinary research on the marine Arctic, and its interaction with the Eurasian continent. Finally, Norling et al. (2019) carried out climate model simulations to quantify impacts of aerosols on global climate dynamics. Their results indicate that climate models do not agree well in terms of regional responses. In summary these studies were able to, despite some good progress, identify issues decrease the performance of climate models when simulating teleconnections that affect the northern Eurasian weather and climate.
Objective 3 was to identify physical mechanisms of the teleconnections affecting the northern Eurasian climate extremes in Work Packages 3 and 4. Important findings related to the physical mechanisms were uncovered. Vihma et al. (2019b) studied teleconnections influencing European winter temperatures and found that the divergence of dry static energy transport was related to winter cold spells, while warm anomalies were associated with convergence of latent heat transport. Significant cooling has occurred in northern Eurasia owing to a decrease in adiabatic subsidence heating air masses arriving from southeast. Tyrrell et al. (2019) discovered that the record strong warm Arctic - cold Siberian continent pattern led to weak polar vortex and negative North Atlantic Oscillation, which in turn affected the weather conditions over northern Eurasia. Nygård et al. (2019) revealed a strong, causal dependence of moisture, clouds and longwave radiation on atmospheric pressure fields. Kämäräinen et al. (2019) explored importance of various factors affecting near surface air temperature over northern Europe. They found that the decadal scale variability of leading principal components of sea-surface temperature, most importantly the Atlantic Multidecadal Oscillation, and geopotential height are good predictors over seasonal scales, especially in summer and autumn. Importantly, these relationships could be utilised in long-term prediction applications. In summary, Objective 3 was addressed by studies which explained physical mechanisms behind teleconnections of air-ice-ocean systems and demonstrated applicability of these mechanisms for forecasting purposes.
Objective 1 was to identify remote regions that generate teleconnections affecting the occurrence, intensity and duration of extreme climate events in northern Eurasia with the work carried out in Work Package 1. Related to this objective, Vihma et al. (2019b) studied factors influencing European winter temperatures with the focus on Arctic warming. They identified that European winter temperatures were primarily linked to the Atlantic and Scandinavian large-scale weather conditions. In addition, Nygård et al. (2019) used the Self-Organizing Maps method to obtain a comprehensive picture on how large-scale atmospheric circulation is related to moisture transport over northern mid-to-high latitudes. They found that much of the moisture provided by the evaporation in the Arctic is actually transported southwards and that the positive phase of the Arctic Oscillation increases moisture and clouds in northern Eurasia. Tyrrell et al. (2019) studied a case occurred in October 2016 when anomalous Siberian forcing generated a response in atmospheric circulation over northern Europe and Atlantic. In summary, these results highlight that regional combinations and interactions in air-ice-ocean systems surrounding the northern Eurasia play crucial roles in determining its weather, including extreme events.
Objective 2 was to analyse how well state-of-the-science climate models simulate the identified associations and the work was carried out in Work Package 2. Fox-Kemper et al. (2019) reviewed recent progress in the development of ocean and sea-ice modelling. They summarized new developments, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations. Benestad et al. (2017) addressed the problem of climate model experiment design and questioned whether climate model information could be used more effectively to design ‘smarter’ ensemble experiments, improving the distillation of information from ensembles, and helping interpret the relative merits of additional simulations. Uotila et al. (2019) assessed physical environmental states derived from an ensemble of ocean reanalysis products in the polar regions which are used as initial conditions for climate models. They identified large variability between individual products, but also found that their mean state is a useful estimate for the state of the polar oceans. Jonassen et al. (2019) used independent observations from the Antarctic to assess the performance of global atmospheric reanalyses, which meteorological models are also used in climate modelling. They identified a common warm bias which has persisted over decades. Vihma et al. (2019) called for the establishment of a marine Arctic component of the Pan-Eurasian Experiment (MA-PEEX) as a component of the PEEX research infrastructure to best utilize the existing and future observations and to further develop the atmosphere-ocean reanalysis products. It is important that MA-PEEX will promote international collaboration and multidisciplinary research on the marine Arctic, and its interaction with the Eurasian continent. Finally, Norling et al. (2019) carried out climate model simulations to quantify impacts of aerosols on global climate dynamics. Their results indicate that climate models do not agree well in terms of regional responses. In summary these studies were able to, despite some good progress, identify issues decrease the performance of climate models when simulating teleconnections that affect the northern Eurasian weather and climate.
Objective 3 was to identify physical mechanisms of the teleconnections affecting the northern Eurasian climate extremes in Work Packages 3 and 4. Important findings related to the physical mechanisms were uncovered. Vihma et al. (2019b) studied teleconnections influencing European winter temperatures and found that the divergence of dry static energy transport was related to winter cold spells, while warm anomalies were associated with convergence of latent heat transport. Significant cooling has occurred in northern Eurasia owing to a decrease in adiabatic subsidence heating air masses arriving from southeast. Tyrrell et al. (2019) discovered that the record strong warm Arctic - cold Siberian continent pattern led to weak polar vortex and negative North Atlantic Oscillation, which in turn affected the weather conditions over northern Eurasia. Nygård et al. (2019) revealed a strong, causal dependence of moisture, clouds and longwave radiation on atmospheric pressure fields. Kämäräinen et al. (2019) explored importance of various factors affecting near surface air temperature over northern Europe. They found that the decadal scale variability of leading principal components of sea-surface temperature, most importantly the Atlantic Multidecadal Oscillation, and geopotential height are good predictors over seasonal scales, especially in summer and autumn. Importantly, these relationships could be utilised in long-term prediction applications. In summary, Objective 3 was addressed by studies which explained physical mechanisms behind teleconnections of air-ice-ocean systems and demonstrated applicability of these mechanisms for forecasting purposes.
Identification of mechanisms linking Arctic warming and north Eurasian weather patterns improves our capability to predict the evolutions of weather and climate, which are important for the society. Also, better knowledge of the Arctic Ocean state and past changes improves the initial states for long-term atmosphere-ocean forecasts. Finally, a new statistical method for seasonal prediction of north European air temperatures is likely to become a useful tool. As the society increasingly relies on information based on environmental predictions, the findings of the project will have many positive societal implications.