scholarly journals Intercomparison of Precipitation Estimates over the Arctic Ocean and Its Peripheral Seas from Reanalyses

2018 ◽  
Vol 31 (20) ◽  
pp. 8441-8462 ◽  
Author(s):  
Linette N. Boisvert ◽  
Melinda A. Webster ◽  
Alek A. Petty ◽  
Thorsten Markus ◽  
David H. Bromwich ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
The Arctic ◽  
Energy Budgets ◽  
Polar Regions ◽  
Basin Scale ◽  
The Arctic Ocean ◽  
Precipitation Estimates ◽  
Microphysical Processes ◽  
Precipitation Events

Precipitation over the Arctic Ocean has a significant impact on the basin-scale freshwater and energy budgets but is one of the most poorly constrained variables in atmospheric reanalyses. Precipitation controls the snow cover on sea ice, which impedes the exchange of energy between the ocean and atmosphere, inhibiting sea ice growth. Thus, accurate precipitation amounts are needed to inform sea ice modeling, especially for the production of thickness estimates from satellite altimetry freeboard data. However, obtaining a quantitative estimate of the precipitation distribution in the Arctic is notoriously difficult because of a number of factors, including a lack of reliable, long-term in situ observations; difficulties in remote sensing over sea ice; and model biases in temperature and moisture fields and associated uncertainty of modeled cloud microphysical processes in the polar regions. Here, we compare precipitation estimates over the Arctic Ocean from eight widely used atmospheric reanalyses over the period 2000–16 (nominally the “new Arctic”). We find that the magnitude, frequency, and phase of precipitation vary drastically, although interannual variability is similar. Reanalysis-derived precipitation does not increase with time as expected; however, an increasing trend of higher fractions of liquid precipitation (rainfall) is found. When compared with drifting ice mass balance buoys, three reanalyses (ERA-Interim, MERRA, and NCEP R2) produce realistic magnitudes and temporal agreement with observed precipitation events, while two products [MERRA, version 2 (MERRA-2), and CFSR] show large, implausible magnitudes in precipitation events. All the reanalyses tend to produce overly frequent Arctic precipitation. Future work needs to be undertaken to determine the specific factors in reanalyses that contribute to these discrepancies in the new Arctic.

The role of sea ice for plastic pollution in the Arctic

2021 ◽  
Author(s):  
Ilka Peeken ◽  
Elisa Bergami ◽  
Ilaria Corsi ◽  
Benedikt Hufnagl ◽  
Christian Katlein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Long Range ◽  
Environmental Concern ◽  
Ice Cores ◽  
Atlantic Water ◽  
The Arctic ◽  
Polar Regions ◽  
Plastic Pollution ◽  
The Arctic Ocean

<p>Marine plastic pollution is a growing worldwide environmental concern as recent reports indicate that increasing quantities of litter disperse into secluded environments, including Polar Regions. Plastic degrades into smaller fragments under the influence of sunlight, temperature changes, mechanic abrasion and wave action resulting in small particles < 5mm called microplastics (MP). Sea ice cores, collected in the Arctic Ocean have so far revealed extremely high concentrations of very small microplastic particles, which might be transferred in the ecosystem with so far unknown consequences for the ice dependant marine food chain.  Sea ice has long been recognised as a transport vehicle for any contaminates entering the Arctic Ocean from various long range and local sources. The Fram Strait is hereby both, a major inflow gateway of warm Atlantic water, with any anthropogenic imprints and the major outflow region of sea ice originating from the Siberian shelves and carried via the Transpolar Drift. The studied sea ice revealed a unique footprint of microplastic pollution, which were related to different water masses and indicating different source regions. Climate change in the Arctic include loss of sea ice, therefore, large fractions of the embedded plastic particles might be released and have an impact on living systems. By combining modeling of sea ice origin and growth, MP particle trajectories in the water column as well as MPs long-range transport via particle tracking and transport models we get first insights  about the sources and pathways of MP in the Arctic Ocean and beyond and how this might affect the Arctic ecosystem.</p>

scholarly journals A satellite-based estimate of aerosol-cloud microphysical effects over the Arctic Ocean

2018 ◽  
Author(s):  
Lauren M. Zamora ◽  
Ralph A. Kahn ◽  
Klaus B. Huebert ◽  
Andreas Stohl ◽  
Sabine Eckhardt
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Transport Model ◽  
Regional Scale ◽  
The Arctic ◽  
Energy Budgets ◽  
Precipitation Frequency ◽  
Aerosol Cloud ◽  
Full Dataset ◽  
The Arctic Ocean

Abstract. Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol-cloud interactions. Here we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify regional-scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (~ 25 W m−2) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain much of this signal – for example, explaining up to 91 % of the CF differences between the full dataset and the clean-condition subset. After normalizing for meteorological regime, aerosol microphysical effects have small but significant regional-scale impacts on CF, CP, and precipitation frequency. These effects indicate that dominant aerosol-cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

scholarly journals A satellite-based estimate of combustion aerosol cloud microphysical effects over the Arctic Ocean

2018 ◽  
Vol 18 (20) ◽  
pp. 14949-14964 ◽  
Author(s):  
Lauren M. Zamora ◽  
Ralph A. Kahn ◽  
Klaus B. Huebert ◽  
Andreas Stohl ◽  
Sabine Eckhardt
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Large Scale ◽  
Transport Model ◽  
The Arctic ◽  
Energy Budgets ◽  
Precipitation Frequency ◽  
Aerosol Cloud ◽  
The Arctic Ocean ◽  
Combustion Aerosols

Abstract. Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large-scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (∼10 W m−2) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40 % of the CF differences between the full dataset and the clean-condition subset, compared to between 57 % and 91 % of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

scholarly journals Effects of Climatic Drivers and Teleconnections on Late 20th Century Trends in Spring Freshet of Four Major Arctic-Draining Rivers

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 179
Author(s):  
Roxanne Ahmed ◽  
Terry Prowse ◽  
Yonas Dibike ◽  
Barrie Bonsal
Keyword(s):  
Arctic Ocean ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rate Of Change ◽  
The Arctic ◽  
Late 20Th Century ◽  
Basin Scale ◽  
The Arctic Ocean ◽  
Spring Freshet ◽  
Climatic Drivers

Spring freshet is the dominant annual discharge event in all major Arctic draining rivers with large contributions to freshwater inflow to the Arctic Ocean. Research has shown that the total freshwater influx to the Arctic Ocean has been increasing, while at the same time, the rate of change in the Arctic climate is significantly higher than in other parts of the globe. This study assesses the large-scale atmospheric and surface climatic conditions affecting the magnitude, timing and regional variability of the spring freshets by analyzing historic daily discharges from sub-basins within the four largest Arctic-draining watersheds (Mackenzie, Ob, Lena and Yenisei). Results reveal that climatic variations closely match the observed regional trends of increasing cold-season flows and earlier freshets. Flow regulation appears to suppress the effects of climatic drivers on freshet volume but does not have a significant impact on peak freshet magnitude or timing measures. Spring freshet characteristics are also influenced by El Niño-Southern Oscillation, the Pacific Decadal Oscillation, the Arctic Oscillation and the North Atlantic Oscillation, particularly in their positive phases. The majority of significant relationships are found in unregulated stations. This study provides a key insight into the climatic drivers of observed trends in freshet characteristics, whilst clarifying the effects of regulation versus climate at the sub-basin scale.

scholarly journals The Influence of Cloud and Surface Properties on the Arctic Ocean Shortwave Radiation Budget in Coupled Models*

2008 ◽  
Vol 21 (5) ◽  
pp. 866-882 ◽  
Author(s):  
Irina V. Gorodetskaya ◽  
L-Bruno Tremblay ◽  
Beate Liepert ◽  
Mark A. Cane ◽  
Richard I. Cullather
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Liquid Water ◽  
Surface Albedo ◽  
Liquid Water Content ◽  
Radiation Budget ◽  
The Arctic ◽  
Coupled Models ◽  
Arctic Clouds ◽  
The Arctic Ocean

Abstract The impact of Arctic sea ice concentrations, surface albedo, cloud fraction, and cloud ice and liquid water paths on the surface shortwave (SW) radiation budget is analyzed in the twentieth-century simulations of three coupled models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The models are the Goddard Institute for Space Studies Model E-R (GISS-ER), the Met Office Third Hadley Centre Coupled Ocean–Atmosphere GCM (UKMO HadCM3), and the National Center for Atmosphere Research Community Climate System Model, version 3 (NCAR CCSM3). In agreement with observations, the models all have high Arctic mean cloud fractions in summer; however, large differences are found in the cloud ice and liquid water contents. The simulated Arctic clouds of CCSM3 have the highest liquid water content, greatly exceeding the values observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. Both GISS-ER and HadCM3 lack liquid water and have excessive ice amounts in Arctic clouds compared to SHEBA observations. In CCSM3, the high surface albedo and strong cloud SW radiative forcing both significantly decrease the amount of SW radiation absorbed by the Arctic Ocean surface during the summer. In the GISS-ER and HadCM3 models, the surface and cloud effects compensate one another: GISS-ER has both a higher summer surface albedo and a larger surface incoming SW flux when compared to HadCM3. Because of the differences in the models’ cloud and surface properties, the Arctic Ocean surface gains about 20% and 40% more solar energy during the melt period in the GISS-ER and HadCM3 models, respectively, compared to CCSM3. In twenty-first-century climate runs, discrepancies in the surface net SW flux partly explain the range in the models’ sea ice area changes. Substantial decrease in sea ice area simulated during the twenty-first century in CCSM3 is associated with a large drop in surface albedo that is only partly compensated by increased cloud SW forcing. In this model, an initially high cloud liquid water content reduces the effect of the increase in cloud fraction and cloud liquid water on the cloud optical thickness, limiting the ability of clouds to compensate for the large surface albedo decrease. In HadCM3 and GISS-ER, the compensation of the surface albedo and cloud SW forcing results in negligible changes in the net SW flux and is one of the factors explaining moderate future sea ice area trends. Thus, model representations of cloud properties for today’s climate determine the ability of clouds to compensate for the effect of surface albedo decrease on the future shortwave radiative budget of the Arctic Ocean and, as a consequence, the sea ice mass balance.

scholarly journals Attribution of the Recent Winter Sea Ice Decline over the Atlantic Sector of the Arctic Ocean*

2015 ◽  
Vol 28 (10) ◽  
pp. 4027-4033 ◽  
Author(s):  
Doo-Sun R. Park ◽  
Sukyoung Lee ◽  
Steven B. Feldstein
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Environmental Changes ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Positive Trend ◽  
Ir Radiation ◽  
Atlantic Sector ◽  
Sea Ice Decline ◽  
The Arctic Ocean

Abstract Wintertime Arctic sea ice extent has been declining since the late twentieth century, particularly over the Atlantic sector that encompasses the Barents–Kara Seas and Baffin Bay. This sea ice decline is attributable to various Arctic environmental changes, such as enhanced downward infrared (IR) radiation, preseason sea ice reduction, enhanced inflow of warm Atlantic water into the Arctic Ocean, and sea ice export. However, their relative contributions are uncertain. Utilizing ERA-Interim and satellite-based data, it is shown here that a positive trend of downward IR radiation accounts for nearly half of the sea ice concentration (SIC) decline during the 1979–2011 winter over the Atlantic sector. Furthermore, the study shows that the Arctic downward IR radiation increase is driven by horizontal atmospheric water flux and warm air advection into the Arctic, not by evaporation from the Arctic Ocean. These findings suggest that most of the winter SIC trends can be attributed to changes in the large-scale atmospheric circulations.

scholarly journals Arctic Sea Ice Retreat in 2007 Follows Thinning Trend

2009 ◽  
Vol 22 (1) ◽  
pp. 165-176 ◽  
Author(s):  
R. W. Lindsay ◽  
J. Zhang ◽  
A. Schweiger ◽  
M. Steele ◽  
H. Stern
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Extent ◽  
Pacific Side ◽  
Arctic Sea ◽  
The Arctic Ocean

Abstract The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice–ocean model is used to determine the state of the ice and ocean over the past 29 yr to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of −0.57 m decade−1. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.

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