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Abstract
Our goal is to tie climate-scale meteorology to regional physics and ecosystem changes and demonstrate a few resulting impacts to which regional peoples are having to respond in the Alaskan Bering Strait region. The sea ice loss events in the winters of 2017/18 and 2018/19 initiated a series of marine environmental, ecological, and industrial changes through a chain of connected events from jet-stream meanders, storms, southerly winds, warmer sea temperatures, and minimum sea ice cover. Resulting impacts continue as coastal communities respond to ongoing nutritional, cultural, and economic challenges. Global warming potentially initiated these events through a weakened atmospheric Arctic Front. Ecological shifts included a transition/reorganization of the Bering Strait regional marine ecosystem. Subsequent changes included shifts in zooplankton species, increases in large-bodied, predatory fish species moving northward, an ice seal unusual mortality event, and seven consecutive years of multispecies seabird die-offs. These changes in the marine ecosystem create a serious food security concern. Ongoing impacts include large, toxic harmful algal blooms and coastal erosion. Recent changes to the maritime industries of the transboundary waters of the Bering Strait include increased industrial ship traffic, planned development of the Port of Nome, and northward proximity of foreign fishing activity. Projections for the next decades are for an increasing frequency of low sea ice years and continuing ecosystem and industrial transitions that contribute to increasing economic and food security concerns for the 16 coastal communities that compose the Bering Strait region.
Significance Statement
Extreme events in the atmosphere/oceans and resultant record sea ice minimums in 2018 and 2019 were manifested in marine ecosystem transitions and maritime industry impacts. This led to ongoing concerns over the food safety and food security of marine resources essential to the nutritional, cultural, and economic well-being of Alaskan coastal communities of the Bering Strait region. Persistent weakening of the Arctic Front may signal an increased frequency of low sea ice events into the next decades.
Abstract
Our goal is to tie climate-scale meteorology to regional physics and ecosystem changes and demonstrate a few resulting impacts to which regional peoples are having to respond in the Alaskan Bering Strait region. The sea ice loss events in the winters of 2017/18 and 2018/19 initiated a series of marine environmental, ecological, and industrial changes through a chain of connected events from jet-stream meanders, storms, southerly winds, warmer sea temperatures, and minimum sea ice cover. Resulting impacts continue as coastal communities respond to ongoing nutritional, cultural, and economic challenges. Global warming potentially initiated these events through a weakened atmospheric Arctic Front. Ecological shifts included a transition/reorganization of the Bering Strait regional marine ecosystem. Subsequent changes included shifts in zooplankton species, increases in large-bodied, predatory fish species moving northward, an ice seal unusual mortality event, and seven consecutive years of multispecies seabird die-offs. These changes in the marine ecosystem create a serious food security concern. Ongoing impacts include large, toxic harmful algal blooms and coastal erosion. Recent changes to the maritime industries of the transboundary waters of the Bering Strait include increased industrial ship traffic, planned development of the Port of Nome, and northward proximity of foreign fishing activity. Projections for the next decades are for an increasing frequency of low sea ice years and continuing ecosystem and industrial transitions that contribute to increasing economic and food security concerns for the 16 coastal communities that compose the Bering Strait region.
Significance Statement
Extreme events in the atmosphere/oceans and resultant record sea ice minimums in 2018 and 2019 were manifested in marine ecosystem transitions and maritime industry impacts. This led to ongoing concerns over the food safety and food security of marine resources essential to the nutritional, cultural, and economic well-being of Alaskan coastal communities of the Bering Strait region. Persistent weakening of the Arctic Front may signal an increased frequency of low sea ice events into the next decades.
Abstract
This study describes winter climate during the last 500 yr for the greater Baltic Sea region through an examination of well-documented time series of ice cover, sea level pressure, and winter surface air temperatures. These time series have been the focus of previous studies, but here their covariation over different time scales is analyzed based on two modern descriptive statistical techniques, matching pursuit and wavelet analysis. Independently, 15 time periods were found during the last 500 yr with different climatic signatures with respect to winter severity, circulation patterns, and interannual variability. The onsets of these periods are presumably caused largely by perturbations within the system, although correspondences with solar and volcanic activity can be identified for certain of the periods. The Baltic region climate has changes on both centennial and decadal time scales, often with rapid transitions. Major warmer periods were the first half of the eighteenth century and the twentieth century. A common feature for warm (cold) periods is low (high) variability on shorter time scales. Century-scale variability and the modulation of interannual and decadal signals are quite diverse in the temporal records and do not suggest strong periodicities. An “event” type conceptual model therefore appears adequate for characterizing Baltic climate variability.
Abstract
This study describes winter climate during the last 500 yr for the greater Baltic Sea region through an examination of well-documented time series of ice cover, sea level pressure, and winter surface air temperatures. These time series have been the focus of previous studies, but here their covariation over different time scales is analyzed based on two modern descriptive statistical techniques, matching pursuit and wavelet analysis. Independently, 15 time periods were found during the last 500 yr with different climatic signatures with respect to winter severity, circulation patterns, and interannual variability. The onsets of these periods are presumably caused largely by perturbations within the system, although correspondences with solar and volcanic activity can be identified for certain of the periods. The Baltic region climate has changes on both centennial and decadal time scales, often with rapid transitions. Major warmer periods were the first half of the eighteenth century and the twentieth century. A common feature for warm (cold) periods is low (high) variability on shorter time scales. Century-scale variability and the modulation of interannual and decadal signals are quite diverse in the temporal records and do not suggest strong periodicities. An “event” type conceptual model therefore appears adequate for characterizing Baltic climate variability.
Abstract
Instrumental surface air temperature (SAT) records beginning in the late 1800s from 59 Arctic stations north of 64°N show monthly mean anomalies of several degrees and large spatial teleconnectivity, yet there are systematic seasonal and regional differences. Analyses are based on time–longitude plots of SAT anomalies and principal component analysis (PCA). Using monthly station data rather than gridded fields for this analysis highlights the importance of considering record length in calculating reliable Arctic change estimates; for example, the contrast of PCA performed on 11 stations beginning in 1886, 20 stations beginning in 1912, and 45 stations beginning in 1936 is illustrated. While often there is a well-known interdecadal negative covariability in winter between northern Europe and Baffin Bay, long-term changes in the remainder of the Arctic are most evident in spring, with cool temperature anomalies before 1920 and Arctic-wide warm temperatures in the 1990s. Summer anomalies are generally weaker than spring or winter but tend to mirror spring conditions before 1920 and in recent decades. Temperature advection in the trough–ridge structure in the positive phase of the Arctic Oscillation (AO) in the North Atlantic establishes wintertime temperature anomalies in adjacent regions, while the zonal/annular nature of the AO in the remainder of the Arctic must break down in spring to promote meridional temperature advection. There were regional/decadal warm events during winter and spring in the 1930s to 1950s, but meteorological analysis suggests that these SAT anomalies are the result of intrinsic variability in regional flow patterns. These midcentury events contrast with the recent Arctic-wide AO influence in the 1990s. The preponderance of evidence supports the conclusion that warm SAT anomalies in spring for the recent decade are unique in the instrumental record, both in having the greatest longitudinal extent and in their associated patterns of warm air advection.
Abstract
Instrumental surface air temperature (SAT) records beginning in the late 1800s from 59 Arctic stations north of 64°N show monthly mean anomalies of several degrees and large spatial teleconnectivity, yet there are systematic seasonal and regional differences. Analyses are based on time–longitude plots of SAT anomalies and principal component analysis (PCA). Using monthly station data rather than gridded fields for this analysis highlights the importance of considering record length in calculating reliable Arctic change estimates; for example, the contrast of PCA performed on 11 stations beginning in 1886, 20 stations beginning in 1912, and 45 stations beginning in 1936 is illustrated. While often there is a well-known interdecadal negative covariability in winter between northern Europe and Baffin Bay, long-term changes in the remainder of the Arctic are most evident in spring, with cool temperature anomalies before 1920 and Arctic-wide warm temperatures in the 1990s. Summer anomalies are generally weaker than spring or winter but tend to mirror spring conditions before 1920 and in recent decades. Temperature advection in the trough–ridge structure in the positive phase of the Arctic Oscillation (AO) in the North Atlantic establishes wintertime temperature anomalies in adjacent regions, while the zonal/annular nature of the AO in the remainder of the Arctic must break down in spring to promote meridional temperature advection. There were regional/decadal warm events during winter and spring in the 1930s to 1950s, but meteorological analysis suggests that these SAT anomalies are the result of intrinsic variability in regional flow patterns. These midcentury events contrast with the recent Arctic-wide AO influence in the 1990s. The preponderance of evidence supports the conclusion that warm SAT anomalies in spring for the recent decade are unique in the instrumental record, both in having the greatest longitudinal extent and in their associated patterns of warm air advection.
Abstract
The impacts of model physics and initial sea ice thickness on seasonal forecasts of surface energy budget and air temperature in the Arctic during summer were investigated based on Climate Forecast System, version 2 (CFSv2), simulations. The model physics changes include the enabling of a marine stratus cloud scheme and the removal of the artificial upper limit on the bottom heat flux from ocean to sea ice. The impact of initial sea ice thickness was examined by initializing the model with relatively realistic sea ice thickness generated by the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Model outputs were compared to that from a control run that did not impose physics changes and used Climate Forecast System Reanalysis (CFSR) sea ice thickness. After applying the physics modification to either sea ice thickness initialization, the simulated total cloud cover more closely resembled the observed monthly variations of total cloud cover except for the midsummer reduction. Over the Chukchi–Bering Seas, the model physics modification reduced the seasonal forecast bias in surface air temperature by 24%. However, the use of initial PIOMAS sea ice thickness alone worsened the surface air temperature predictions. The experiment with physics modifications and initial PIOMAS sea ice thickness achieves the best surface air temperature improvement over the Chukchi–Bering Seas where the area-weighted forecast bias was reduced by 71% from 1.05 K down to −0.3 K compared with the control run. This study supports other results that surface temperatures and sea ice characteristics are highly sensitive to the Arctic cloud and radiation formulations in models and need priority in model formulation and validation.
Abstract
The impacts of model physics and initial sea ice thickness on seasonal forecasts of surface energy budget and air temperature in the Arctic during summer were investigated based on Climate Forecast System, version 2 (CFSv2), simulations. The model physics changes include the enabling of a marine stratus cloud scheme and the removal of the artificial upper limit on the bottom heat flux from ocean to sea ice. The impact of initial sea ice thickness was examined by initializing the model with relatively realistic sea ice thickness generated by the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Model outputs were compared to that from a control run that did not impose physics changes and used Climate Forecast System Reanalysis (CFSR) sea ice thickness. After applying the physics modification to either sea ice thickness initialization, the simulated total cloud cover more closely resembled the observed monthly variations of total cloud cover except for the midsummer reduction. Over the Chukchi–Bering Seas, the model physics modification reduced the seasonal forecast bias in surface air temperature by 24%. However, the use of initial PIOMAS sea ice thickness alone worsened the surface air temperature predictions. The experiment with physics modifications and initial PIOMAS sea ice thickness achieves the best surface air temperature improvement over the Chukchi–Bering Seas where the area-weighted forecast bias was reduced by 71% from 1.05 K down to −0.3 K compared with the control run. This study supports other results that surface temperatures and sea ice characteristics are highly sensitive to the Arctic cloud and radiation formulations in models and need priority in model formulation and validation.
Abstract
Climate projections at regional scales are in increased demand from management agencies and other stakeholders. While global atmosphere–ocean climate models provide credible quantitative estimates of future climate at continental scales and above, individual model performance varies for different regions, variables, and evaluation metrics—a less than satisfying situation. Using the high-latitude Northern Hemisphere as a focus, the authors assess strategies for providing regional projections based on global climate models. Starting with a set of model results obtained from an “ensemble of opportunity,” the core of this procedure is to retain a subset of models through comparisons of model simulations with observations at both continental and regional scales. The exercise is more one of model culling than model selection. The continental-scale evaluation is a check on the large-scale climate physics of the models, and the regional-scale evaluation emphasizes variables of ecological or societal relevance. An additional consideration is given to the comprehensiveness of processes included in the models. In many but not all applications, different results are obtained from a reduced set of models compared to relying on the simple mean of all available models. For example, in the Arctic the top-performing models tend to be more sensitive to greenhouse forcing than the poorer-performing models. Because of the mostly unexplained inconsistencies in model performance under different selection criteria, simple and transparent evaluation methods are favored. The use of a single model is not recommended. For some applications, no model may be able to provide a suitable regional projection. The use of model evaluation strategies, as opposed to relying on simple averages of ensembles of opportunity, should be part of future synthesis activities such as the upcoming Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
Abstract
Climate projections at regional scales are in increased demand from management agencies and other stakeholders. While global atmosphere–ocean climate models provide credible quantitative estimates of future climate at continental scales and above, individual model performance varies for different regions, variables, and evaluation metrics—a less than satisfying situation. Using the high-latitude Northern Hemisphere as a focus, the authors assess strategies for providing regional projections based on global climate models. Starting with a set of model results obtained from an “ensemble of opportunity,” the core of this procedure is to retain a subset of models through comparisons of model simulations with observations at both continental and regional scales. The exercise is more one of model culling than model selection. The continental-scale evaluation is a check on the large-scale climate physics of the models, and the regional-scale evaluation emphasizes variables of ecological or societal relevance. An additional consideration is given to the comprehensiveness of processes included in the models. In many but not all applications, different results are obtained from a reduced set of models compared to relying on the simple mean of all available models. For example, in the Arctic the top-performing models tend to be more sensitive to greenhouse forcing than the poorer-performing models. Because of the mostly unexplained inconsistencies in model performance under different selection criteria, simple and transparent evaluation methods are favored. The use of a single model is not recommended. For some applications, no model may be able to provide a suitable regional projection. The use of model evaluation strategies, as opposed to relying on simple averages of ensembles of opportunity, should be part of future synthesis activities such as the upcoming Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
Abstract
Seasonally ice-covered marginal seas are among the most difficult regions in the Arctic to study. Physical constraints imposed by the variable presence of sea ice in all stages of growth and melt make the upper water column and air–sea ice interface especially challenging to observe. At the same time, the flow of solar energy through Alaska’s marginal seas is one of the most important regulators of their weather and climate, sea ice cover, and ecosystems. The deficiency of observing systems in these areas hampers forecast services in the region and is a major contributor to large uncertainties in modeling and related climate projections. The Arctic Heat Open Science Experiment strives to fill this observation gap with an array of innovative autonomous floats and other near-real-time weather and ocean sensing systems. These capabilities allow continuous monitoring of the seasonally evolving state of the Chukchi Sea, including its heat content. Data collected by this project are distributed in near–real time on project websites and on the Global Telecommunications System (GTS), with the objectives of (i) providing timely delivery of observations for use in weather and sea ice forecasts, for model, and for reanalysis applications and (ii) supporting ongoing research activities across disciplines. This research supports improved forecast services that protect and enhance the safety and economic viability of maritime and coastal community activities in Alaska. Data are free and open to all (see www.pmel.noaa.gov/arctic-heat/).
Abstract
Seasonally ice-covered marginal seas are among the most difficult regions in the Arctic to study. Physical constraints imposed by the variable presence of sea ice in all stages of growth and melt make the upper water column and air–sea ice interface especially challenging to observe. At the same time, the flow of solar energy through Alaska’s marginal seas is one of the most important regulators of their weather and climate, sea ice cover, and ecosystems. The deficiency of observing systems in these areas hampers forecast services in the region and is a major contributor to large uncertainties in modeling and related climate projections. The Arctic Heat Open Science Experiment strives to fill this observation gap with an array of innovative autonomous floats and other near-real-time weather and ocean sensing systems. These capabilities allow continuous monitoring of the seasonally evolving state of the Chukchi Sea, including its heat content. Data collected by this project are distributed in near–real time on project websites and on the Global Telecommunications System (GTS), with the objectives of (i) providing timely delivery of observations for use in weather and sea ice forecasts, for model, and for reanalysis applications and (ii) supporting ongoing research activities across disciplines. This research supports improved forecast services that protect and enhance the safety and economic viability of maritime and coastal community activities in Alaska. Data are free and open to all (see www.pmel.noaa.gov/arctic-heat/).
The Coastal Observation and Simulation with Topography (COAST) program has examined the interaction of both steady-state and transient cool-season synoptic features, such as fronts and cyclones, with the coastal terrain of western North America. Its objectives include better understanding and forecasting of landfalling weather systems and, in particular, the modification and creation of mesoscale structures by coastal orography. In addition, COAST has placed considerable emphasis on the evaluation of mesoscale models in coastal terrain. These goals have been addressed through case studies of storm and frontal landfall along the Pacific Northwest coast using special field observations from a National Oceanic and Atmospheric Administration WP-3D research aircraft and simulations from high-resolution numerical models. The field work was conducted during December 1993 and December 1995. Active weather conditions encompassing a variety of synoptic situations were sampled. This article presents an overview of the program as well as highlights from a sample of completed and ongoing case studies.
The Coastal Observation and Simulation with Topography (COAST) program has examined the interaction of both steady-state and transient cool-season synoptic features, such as fronts and cyclones, with the coastal terrain of western North America. Its objectives include better understanding and forecasting of landfalling weather systems and, in particular, the modification and creation of mesoscale structures by coastal orography. In addition, COAST has placed considerable emphasis on the evaluation of mesoscale models in coastal terrain. These goals have been addressed through case studies of storm and frontal landfall along the Pacific Northwest coast using special field observations from a National Oceanic and Atmospheric Administration WP-3D research aircraft and simulations from high-resolution numerical models. The field work was conducted during December 1993 and December 1995. Active weather conditions encompassing a variety of synoptic situations were sampled. This article presents an overview of the program as well as highlights from a sample of completed and ongoing case studies.
