United States Heat Wave Frequency and Arctic Ocean Marginal Sea Ice Variability

2019 ◽  
Vol 124 (12) ◽  
pp. 6247-6264 ◽  
Author(s):  
Dagmar Budikova ◽  
Trent W. Ford ◽  
Thomas J. Ballinger
Keyword(s):  
United States ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Heat Wave ◽  
Wave Frequency ◽  
Marginal Sea

scholarly journals Shallow methylmercury production in the marginal sea ice zone of the central Arctic Ocean

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Lars-Eric Heimbürger ◽  
Jeroen E. Sonke ◽  
Daniel Cossa ◽  
David Point ◽  
Christelle Lagane ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Central Arctic Ocean ◽  
Marginal Sea ◽  
Methylmercury Production

scholarly journals Daily Autocorrelation and Mean Temperature/Moisture Rise as Determining Factors for Future Heat-Wave Patterns in the United States

2020 ◽  
Vol 59 (10) ◽  
pp. 1735-1754
Author(s):  
Anthony G. Barnston ◽  
Bradfield Lyon ◽  
Ethan D. Coffel ◽  
Radley M. Horton
Keyword(s):  
United States ◽  
Heat Wave ◽  
Well Being ◽  
The United States ◽  
Wave Frequency ◽  
Apparent Temperature ◽  
Cmip5 Models ◽  
Positive Trend ◽  
Recent Past ◽  
Mean Temperature

AbstractThe frequency of heat waves (defined as daily temperature exceeding the local 90th percentile for at least three consecutive days) during summer in the United States is examined for daily maximum and minimum temperature and maximum apparent temperature, in recent observations and in 10 CMIP5 models for recent past and future. The annual average percentage of days participating in a heat wave varied between approximately 2% and 10% in observations and in the model’s historical simulations during 1979–2005. Applying today’s temperature thresholds to future projections, heat-wave frequencies rise to more than 20% by 2035–40. However, given the models’ slight overestimation of frequencies and positive trend rates during 1979–2005, these projected heat-wave frequencies should be regarded cautiously. The models’ overestimations may be associated with their higher daily autocorrelation than is found in observations. Heat-wave frequencies defined using apparent temperature, reflecting both temperature and atmospheric moisture, are projected to increase at a slightly (and statistically significantly) faster rate than for temperature alone. Analyses show little or no changes in the day-to-day variability or persistence (autocorrelation) of extreme temperature between recent past and future, indicating that the future heat-wave frequency will be due predominantly to increases in standardized (using historical period statistics) mean temperature and moisture content, adjusted by the local climatological daily autocorrelation. Using nonparametric methods, the average level and spatial pattern of future heat-wave frequency is shown to be approximately predictable on the basis of only projected mean temperature increases and local autocorrelation. These model-projected changes, even if only approximate, would impact infrastructure, ecology, and human well-being.

scholarly journals Retrieval of Summer Sea Ice Concentration in the Pacific Arctic Ocean from AMSR2 Observations and Numerical Weather Data Using Random Forest Regression

2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Effects ◽  
Sea Ice Concentration ◽  
Air Temperatures ◽  
The Pacific ◽  
Ice Concentration

The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change and important information for the development of a more economically valuable Northern Sea Route. Passive microwave (PM) sensors have provided information on the SIC since the 1970s by observing the brightness temperature (TB) of sea ice and open water. However, the SIC in the Arctic estimated by operational algorithms for PM observations is very inaccurate in summer because the TB values of sea ice and open water become similar due to atmospheric effects. In this study, we developed a summer SIC retrieval model for the Pacific Arctic Ocean using Advanced Microwave Scanning Radiometer 2 (AMSR2) observations and European Reanalysis Agency-5 (ERA-5) reanalysis fields based on Random Forest (RF) regression. SIC values computed from the ice/water maps generated from the Korean Multi-purpose Satellite-5 synthetic aperture radar images from July to September in 2015–2017 were used as a reference dataset. A total of 24 features including the TB values of AMSR2 channels, the ratios of TB values (the polarization ratio and the spectral gradient ratio (GR)), total columnar water vapor (TCWV), wind speed, air temperature at 2 m and 925 hPa, and the 30-day average of the air temperatures from the ERA-5 were used as the input variables for the RF model. The RF model showed greatly superior performance in retrieving summer SIC values in the Pacific Arctic Ocean to the Bootstrap (BT) and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithms under various atmospheric conditions. The root mean square error (RMSE) of the RF SIC values was 7.89% compared to the reference SIC values. The BT and ASI SIC values had three times greater values of RMSE (20.19% and 21.39%, respectively) than the RF SIC values. The air temperatures at 2 m and 925 hPa and their 30-day averages, which indicate the ice surface melting conditions, as well as the GR using the vertically polarized channels at 23 GHz and 18 GHz (GR(23V18V)), TCWV, and GR(36V18V), which accounts for atmospheric water content, were identified as the variables that contributed greatly to the RF model. These important variables allowed the RF model to retrieve unbiased and accurate SIC values by taking into account the changes in TB values of sea ice and open water caused by atmospheric effects.

scholarly journals Response of ocean phytoplankton community structure to climate change over the 21st century: partitioning the effects of nutrients, temperature and light

2010 ◽  
Vol 7 (12) ◽  
pp. 3941-3959 ◽  
Author(s):  
I. Marinov ◽  
S. C. Doney ◽  
I. D. Lima
Keyword(s):  
Climate Change ◽  
Community Structure ◽  
Sea Ice ◽  
Phytoplankton Biomass ◽  
Phytoplankton Community ◽  
Vertical Mixing ◽  
Phytoplankton Community Structure ◽  
Marginal Sea ◽  
Small Phytoplankton ◽  
The Impact

Abstract. The response of ocean phytoplankton community structure to climate change depends, among other factors, upon species competition for nutrients and light, as well as the increase in surface ocean temperature. We propose an analytical framework linking changes in nutrients, temperature and light with changes in phytoplankton growth rates, and we assess our theoretical considerations against model projections (1980–2100) from a global Earth System model. Our proposed "critical nutrient hypothesis" stipulates the existence of a critical nutrient threshold below (above) which a nutrient change will affect small phytoplankton biomass more (less) than diatom biomass, i.e. the phytoplankton with lower half-saturation coefficient K are influenced more strongly in low nutrient environments. This nutrient threshold broadly corresponds to 45° S and 45° N, poleward of which high vertical mixing and inefficient biology maintain higher surface nutrient concentrations and equatorward of which reduced vertical mixing and more efficient biology maintain lower surface nutrients. In the 45° S–45° N low nutrient region, decreases in limiting nutrients – associated with increased stratification under climate change – are predicted analytically to decrease more strongly the specific growth of small phytoplankton than the growth of diatoms. In high latitudes, the impact of nutrient decrease on phytoplankton biomass is more significant for diatoms than small phytoplankton, and contributes to diatom declines in the northern marginal sea ice and subpolar biomes. In the context of our model, climate driven increases in surface temperature and changes in light are predicted to have a stronger impact on small phytoplankton than on diatom biomass in all ocean domains. Our analytical predictions explain reasonably well the shifts in community structure under a modeled climate-warming scenario. Climate driven changes in nutrients, temperature and light have regionally varying and sometimes counterbalancing impacts on phytoplankton biomass and structure, with nutrients and temperature dominant in the 45° S–45° N band and light-temperature effects dominant in the marginal sea-ice and subpolar regions. As predicted, decreases in nutrients inside the 45° S–45° N "critical nutrient" band result in diatom biomass decreasing more than small phytoplankton biomass. Further stratification from global warming could result in geographical shifts in the "critical nutrient" threshold and additional changes in ecology.

scholarly journals Societal implications of a changing Arctic Ocean

AMBIO ◽  
2021 ◽  
Author(s):  
Henry P. Huntington ◽  
Andrey Zagorsky ◽  
Bjørn P. Kaltenborn ◽  
Hyoung Chul Shin ◽  
Jackie Dawson ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Indigenous Peoples ◽  
Global Climate ◽  
Rapid Change ◽  
The Arctic ◽  
Cultural Continuity ◽  
Societal Implications ◽  
Arctic Ecosystems ◽  
The Many

AbstractThe Arctic Ocean is undergoing rapid change: sea ice is being lost, waters are warming, coastlines are eroding, species are moving into new areas, and more. This paper explores the many ways that a changing Arctic Ocean affects societies in the Arctic and around the world. In the Arctic, Indigenous Peoples are again seeing their food security threatened and cultural continuity in danger of disruption. Resource development is increasing as is interest in tourism and possibilities for trans-Arctic maritime trade, creating new opportunities and also new stresses. Beyond the Arctic, changes in sea ice affect mid-latitude weather, and Arctic economic opportunities may re-shape commodities and transportation markets. Rising interest in the Arctic is also raising geopolitical tensions about the region. What happens next depends in large part on the choices made within and beyond the Arctic concerning global climate change and industrial policies and Arctic ecosystems and cultures.

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