scholarly journals Decadal Changes of the Reflected Solar Radiation and the Earth Energy Imbalance

2019 ◽  
Vol 11 (6) ◽  
pp. 663 ◽  
Author(s):  
Steven Dewitte ◽  
Nicolas Clerbaux ◽  
Jan Cornelis
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Time Derivative ◽  
Heat Content ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Energy Imbalance ◽  
Clear Sky ◽  
The Earth

Decadal changes of the Reflected Solar Radiation (RSR) as measured by CERES from 2000 to 2018 are analysed. For both polar regions, changes of the clear-sky RSR correlate well with changes of the Sea Ice Extent. In the Arctic, sea ice is clearly melting, and as a result the earth is becoming darker under clear-sky conditions. However, the correlation between the global all-sky RSR and the polar clear-sky RSR changes is low. Moreover, the RSR and the Outgoing Longwave Radiation (OLR) changes are negatively correlated, so they partly cancel each other. The increase of the OLR is higher then the decrease of the RSR. Also the incoming solar radiation is decreasing. As a result, over the 2000–2018 period the Earth Energy Imbalance (EEI) appears to have a downward trend of −0.16 ± 0.11 W/m2dec. The EEI trend agrees with a trend of the Ocean Heat Content Time Derivative of −0.26 ± 0.06 (1 σ ) W/m2dec.

scholarly journals Ice Concentration Retrieval from the Analysis of Microwaves: A New Methodology Designed for the Copernicus Imaging Microwave Radiometer

2020 ◽  
Vol 12 (7) ◽  
pp. 1060 ◽  
Author(s):  
Lise Kilic ◽  
Catherine Prigent ◽  
Filipe Aires ◽  
Georg Heygster ◽  
Victor Pellet ◽  
...  
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Microwave Radiometer ◽  
Optimal Estimation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Special Focus ◽  
Polar Regions ◽  
Sea Ice Concentration ◽  
Ice Concentration

Over the last 25 years, the Arctic sea ice has seen its extent decline dramatically. Passive microwave observations, with their ability to penetrate clouds and their independency to sunlight, have been used to provide sea ice concentration (SIC) measurements since the 1970s. The Copernicus Imaging Microwave Radiometer (CIMR) is a high priority candidate mission within the European Copernicus Expansion program, with a special focus on the observation of the polar regions. It will observe at 6.9 and 10.65 GHz with 15 km spatial resolution, and at 18.7 and 36.5 GHz with 5 km spatial resolution. SIC algorithms are based on empirical methods, using the difference in radiometric signatures between the ocean and sea ice. Up to now, the existing algorithms have been limited in the number of channels they use. In this study, we proposed a new SIC algorithm called Ice Concentration REtrieval from the Analysis of Microwaves (IceCREAM). It can accommodate a large range of channels, and it is based on the optimal estimation. Linear relationships between the satellite measurements and the SIC are derived from the Round Robin Data Package of the sea ice Climate Change Initiative. The 6 and 10 GHz channels are very sensitive to the sea ice presence, whereas the 18 and 36 GHz channels have a better spatial resolution. A data fusion method is proposed to combine these two estimations. Therefore, IceCREAM will provide SIC estimates with the good accuracy of the 6+10GHz combination, and the high spatial resolution of the 18+36GHz combination.

scholarly journals A Decade of Spaceborne Observations of the Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument

2016 ◽  
Vol 97 (11) ◽  
pp. 2163-2176 ◽  
Author(s):  
Abhay Devasthale ◽  
Joseph Sedlar ◽  
Brian H. Kahn ◽  
Michael Tjernström ◽  
Eric J. Fetzer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Numerical Models ◽  
Lower Troposphere ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Projections ◽  
Polar Regions ◽  
Arctic Atmosphere ◽  
Warming World

Abstract Arctic sea ice is declining rapidly and its annual ice extent minima reached record lows twice during the last decade. Large environmental and socioeconomic implications related to sea ice reduction in a warming world necessitate realistic simulations of the Arctic climate system, not least to formulate relevant environmental policies on an international scale. However, despite considerable progress in the last few decades, future climate projections from numerical models still exhibit the largest uncertainties over the polar regions. The lack of sufficient observations of essential climate variables is partly to blame for the poor representation of key atmospheric processes, and their coupling to the surface, in climate models. Observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) instrument on board the National Aeronautics and Space Administration (NASA)’s Aqua satellite are contributing toward improved understanding of the vertical structure of the atmosphere over the poles since 2002, including the lower troposphere. This part of the atmosphere is especially important in the Arctic, as it directly impacts sea ice and its short-term variability. Although in situ measurements provide invaluable ground truth, they are spatially and temporally inhomogeneous and sporadic over the Arctic. A growing number of studies are exploiting AIRS data to investigate the thermodynamic structure of the Arctic atmosphere, with applications ranging from understanding processes to deriving climatologies—all of which are also useful to test and improve parameterizations in climate models. As the AIRS data record now extends more than a decade, a select few of many such noteworthy applications of AIRS data over this challenging and rapidly changing landscape are highlighted here.

scholarly journals September Arctic Sea Ice minimum prediction – a new skillful statistical approach

2018 ◽  
Author(s):  
Monica Ionita ◽  
Klaus Grosfeld ◽  
Patrick Scholz ◽  
Renate Treffeisen ◽  
Gerrit Lohmann
Keyword(s):  
Sea Ice ◽  
Statistical Model ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Sea Ice Extent ◽  
Important Indicator ◽  
Predictive Skill

Abstract. Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

scholarly journals Arctic sea-ice conditions and the distribution of solar radiation during summer

1997 ◽  
Vol 25 ◽  
pp. 445-450 ◽  
Author(s):  
Donald K. Perovich ◽  
Walter B. Tucker
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Feedback Mechanism ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Melt Ponds ◽  
Arctic Ice ◽  
Median Area

Understanding the interaction of solar radiation with the ice cover is critical in determining the heat and mass balance of the Arctic ice pack, and in assessing potential impacts due to climate change. Because of the importance of the ice-albedo feedback mechanism, information on the surface state of the ice cover is needed. Observations of the surface slate of sea ice were obtained from helicopter photography missions made during the 1994 Arctic Ocean Section cruise. Photographs from one flight, taken during the height of the melt season (31 July 1994) at 76° N, 172° W, were analyzed in detail. Bare ice covered 82% of the total area, melt ponds 12%, and open water 6%, There was considerable variability in these area fractions on scales < 1 km2. Sample areas >2 3 km2gave representative values of ice concentration and pond fraction. Melt ponds were numerous, with a number density of 1800 ponds km-2. The melt ponds had a mean area of 62 m2a median area of 14 m2, and a size distribution that was well lit by a cumulative lognormal distribution. While leads make up only a small portion of the total area, they are the source of virtually all of the solar energy input to the ocean.

scholarly journals A Study of the Technology Used to Distinguish Sea Ice and Seawater on the Haiyang-2A/B (HY-2A/B) Altimeter Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1490 ◽  
Author(s):  
Chengfei Jiang ◽  
Mingsen Lin ◽  
Hao Wei
Keyword(s):  
Sea Ice ◽  
Sea Water ◽  
Automatic Gain Control ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Altimeter Data ◽  
Support Vector ◽  
Polar Regions ◽  
Waveform Data ◽  
Star Network

When the Haiyang-2B (HY-2B) was launched into space to form a star network with the Haiyang-2A (HY-2A), it provided new data sources for the sea ice research of the Earth’s polar regions. The ability of altimeter echoes to distinguish sea ice and sea water is usable in operational ice charting. In this research study, the level 1B (L1B) data of HY-2A/B altimeter from November 2018 was used to analyze the altimeter waveforms from the polar regions. The Suboptimal Maximum Likelihood Estimation (SMLE) and Offset Center of Gravity (OCOG) tracking packages could maintain the waveform characteristics of diffused and quasi-specular surfaces by comparison. Also, they could be utilized to distinguish sea ice from seawater in the polar regions. It was determined that the types of echoes obtained from the seawater were diffuse. Also, some “ocean-like” waveform data had existed for the old ice formations in the Arctic regions during the study period. The types of echoes obtained from Arctic sea ice were found to be mainly quasi-specular. In the present study, three methods (Threshold segmentation, K-nearest-neighbor (KNN), and Lib-Support Vector machine (LIBSVM)) with four waveform parameters (Automatic Gain Control (AGC) and Pulse Peaking (PP) values of the Ku and C Bands) were adopted to distinguish between the sea ice and seawater areas. The accuracy rate of the separation results for the LIBSVM except band Ku from HY-2B ALT was found to be less than 40% in Antarctic. Meanwhile, the other two methods were observed to have maintained the waveforms correctly at accuracy rates of approximately 80% in Antarctic and the Arctic. In addition, the observed distinguishing errors were located in the regions of the old ice of the Arctic region. In addition, due to the summer melting processes, the large number of ice floes and the snow cover had made it difficult to distinguish the seawater and sea ice in the Antarctic regions.

scholarly journals Present-Day Arctic Sea Ice Variability in the Coupled ECHAM5/MPI-OM Model

2010 ◽  
Vol 23 (10) ◽  
pp. 2520-2543 ◽  
Author(s):  
Nikolay V. Koldunov ◽  
Detlef Stammer ◽  
Jochem Marotzke
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Heat Content ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Max Planck ◽  
Arctic Sea

Abstract As a contribution to a detailed evaluation of Intergovernmental Panel on Climate Change (IPCC)-type coupled climate models against observations, this study analyzes Arctic sea ice parameters simulated by the Max-Planck-Institute for Meteorology (MPI-M) fully coupled climate model ECHAM5/Max-Planck-Institute for Meteorology Hamburg Primitive Equation Ocean Model (MPI-OM) for the period from 1980 to 1999 and compares them with observations collected during field programs and by satellites. Results of the coupled run forced by twentieth-century CO2 concentrations show significant discrepancies during summer months with respect to observations of the spatial distribution of the ice concentration and ice thickness. Equally important, the coupled run lacks interannual variability in all ice and Arctic Ocean parameters. Causes for such big discrepancies arise from errors in the ECHAM5/MPI-OM atmosphere and associated errors in surface forcing fields (especially wind stress). This includes mean bias pattern caused by an artificial circulation around the geometric North Pole in its atmosphere, as well as insufficient atmospheric variability in the ECHAM5/MPI-OM model, for example, associated with Arctic Oscillation/North Atlantic Oscillation (AO/NAO). In contrast, the identical coupled ocean–ice model, when driven by NCEP–NCAR reanalysis fields, shows much increased skill in its ice and ocean circulation parameters. However, common to both model runs is too strong an ice export through the Fram Strait and a substantially biased heat content in the interior of the Arctic Ocean, both of which may affect sea ice budgets in centennial projections of the Arctic climate system.

scholarly journals Influence of stochastic sea ice parametrization on climate and the role of atmosphere–sea ice–ocean interaction

2014 ◽  
Vol 372 (2018) ◽  
pp. 20130283 ◽  
Author(s):  
Stephan Juricke ◽  
Thomas Jung
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Stochastic Perturbations ◽  
Arctic Sea ◽  
The Mean ◽  
Mean Climate

The influence of a stochastic sea ice strength parametrization on the mean climate is investigated in a coupled atmosphere–sea ice–ocean model. The results are compared with an uncoupled simulation with a prescribed atmosphere. It is found that the stochastic sea ice parametrization causes an effective weakening of the sea ice. In the uncoupled model this leads to an Arctic sea ice volume increase of about 10–20% after an accumulation period of approximately 20–30 years. In the coupled model, no such increase is found. Rather, the stochastic perturbations lead to a spatial redistribution of the Arctic sea ice thickness field. A mechanism involving a slightly negative atmospheric feedback is proposed that can explain the different responses in the coupled and uncoupled system. Changes in integrated Antarctic sea ice quantities caused by the stochastic parametrization are generally small, as memory is lost during the melting season because of an almost complete loss of sea ice. However, stochastic sea ice perturbations affect regional sea ice characteristics in the Southern Hemisphere, both in the uncoupled and coupled model. Remote impacts of the stochastic sea ice parametrization on the mean climate of non-polar regions were found to be small.

scholarly journals Wintertime Cold Extremes in Northeast China and Their Linkage with Sea Ice in Barents-Kara Seas

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 386
Author(s):  
Yongyue Luo ◽  
Chun Li ◽  
Jian Shi ◽  
Xiadong An ◽  
Yaqing Sun
Keyword(s):  
Low Temperature ◽  
Sea Ice ◽  
Interannual Variability ◽  
Geopotential Height ◽  
Northeast China ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Northerly Wind ◽  
Cold Air

The impacts of Arctic sea ice on the interannual variability of winter extreme low temperature (WELT) in Northeast China (NEC) and the associated atmospheric circulation patterns are explored in this study based on meteorological observation and the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. Results show that WELT in NEC has prominent interannual variability. We further use ±0.8 standard deviation as the threshold to select the years of frequent and rare extreme low temperature anomalies. Using composite analysis, we find that there are significant negative geopotential height anomalies at 500 hPa over NEC and positive geopotential height anomalies along the Arctic region, which represent the intensification of the East Asian trough (EAT) and the negative Arctic Oscillation (AO) phase in the years of more frequent WELT. The opposite characteristics are detected in the years of rare WELT. Furthermore, we determine that the Barents-Kara Seas are key sea ice regions in Arctic area. In the years of frequent WELT, the decrease of autumn Barents-Kara Seas sea ice and the positive sea surface temperature anomaly can last until the following winter, which is conducive to the intensification of anticyclonic anomalies in Ural regions and the northward extension of Ural ridge (UR). The northerly flow in front of UR guides the cold air penetrating southward from polar regions. Moreover, the anomalous cyclone over East Asia deepens the EAT. The northerly wind behind EAT guides the cold air to the NEC region, causing the wintertime low temperature there. The almost opposite situation occurs in the years of rare WELT.

The impact of orbital forcing on the Arctic climate during the Last Interglacial simulated by the IPSL-CM6A-LR model

2020 ◽  
Author(s):  
Marie Sicard ◽  
Masa Kageyama ◽  
Pascale Braconnot ◽  
Sylvie Charbit
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
Arctic Climate ◽  
The Arctic ◽  
Orbital Forcing ◽  
Last Interglacial ◽  
Arctic Sea ◽  
The Impact

<p>The Last Interglacial (129 – 116 ka BP) is a time period with a strong orbital forcing which leads to a different seasonal and latitudinal distribution of insolation compared to the present. In particular, these changes amplify the Arctic climate seasonality. They induce warmer summers and colder winters in the high latitudes of the Northern Hemisphere. Such surface conditions favour a huge retreat of the arctic sea ice cover.<br>In this study, we try to understand how this solar radiation anomaly spreads through the surface and impacts the seasonal arctic sea ice. Using IPSL-CM6A-LR model outputs, we decompose the surface energy budget to identify the role of atmospheric and oceanic key processes beyond 60°N and its changes compared to pre-industrial. We show that solar radiation anomaly is greatly reduced when it reaches the Earth’s surface, which emphasizes the role of clouds and water vapor transport.<br>The results are also compared to other PMIP4-CMIP6 model simulations. We would like to thank PMIP participants for producing and making available their model outputs.</p>

scholarly journals Effect of Wind Speed and Leads on Clear-Sky Cooling over Arctic Sea Ice during Polar Night

2019 ◽  
Vol 76 (8) ◽  
pp. 2481-2503 ◽  
Author(s):  
Dmitry G. Chechin ◽  
Irina A. Makhotina ◽  
Christof Lüpkes ◽  
Alexander P. Makshtas
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Threshold Value ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Strong Impact ◽  
Polar Night ◽  
Sea Ice Concentration ◽  
Clear Sky ◽  
Ice Concentration

Abstract A simple analytical model of the atmospheric boundary layer (ABL) coupled to sea ice is presented. It describes clear-sky cooling over sea ice during polar night in the presence of leads. The model solutions show that the sea ice concentration and wind speed have a strong impact on the thermal regime over sea ice. Leads cause both a warming of the ABL and an increase of stability over sea ice. The model describes a sharp ABL transition from a weakly stable coupled state to a strongly stable decoupled state when wind speed is decreasing. The threshold value of the transition wind speed is a function of sea ice concentration. The decoupled state is characterized by a large air–surface temperature difference over sea ice, which is further increased by leads. In the coupled regime, air and surface temperatures increase almost linearly with wind speed due to warming by leads and also slower cooling of the ABL. The cooling time scale shows a nonmonotonic dependency on wind speed, being lowest for the threshold value of wind speed and increasing for weak and strong winds. Theoretical solutions agree well with results of a more realistic single-column model and with observations performed at the three Russian “North Pole” drifting stations (NP-35, -37, and -39) and at the Surface Heat Budget of the Arctic Ocean ice camp. Both modeling results and observations show a strong implicit dependency of the net longwave radiative flux at the surface on wind speed.

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