scholarly journals Arctic Cloud Characteristics as Derived from MODIS, CALIPSO, and CloudSat

2013 ◽  
Vol 26 (10) ◽  
pp. 3285-3306 ◽  
Author(s):  
Mark Aaron Chan ◽  
Josefino C. Comiso
Keyword(s):  
Sea Ice ◽  
Cloud Cover ◽  
Arctic Region ◽  
The Arctic ◽  
Orthogonal Polarization ◽  
Cloud Detection ◽  
Percentage Difference ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
High Level ◽  
The Arctic Region

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), and CloudSat Cloud Profiling Radar (CPR) set of sensors, all in the Afternoon Constellation (A-Train), has been regarded as among the most powerful tools for characterizing the cloud cover. While providing good complementary information, the authors also observed that, at least for the Arctic region, the different sensors provide significantly different statistics about cloud cover characteristics. Data in 2007 and 2010 were analyzed, and the annual averages of cloud cover in the Arctic region were found to be 66.8%, 78.4%, and 63.3% as derived from MODIS, CALIOP, and CPR, respectively. A large disagreement between MODIS and CALIOP over sea ice and Greenland is observed, with a cloud percentage difference of 30.9% and 31.5%, respectively. In the entire Arctic, the average disagreement between MODIS and CALIOP increased from 13.1% during daytime to 26.7% during nighttime. Furthermore, the MODIS cloud mask accuracy has a high seasonal dependence, in that MODIS–CALIOP disagreement is the lowest during summertime at 10.7% and worst during winter at 28.0%. During nighttime the magnitude of the bias is higher because cloud detection is limited to the use of infrared bands. The clouds not detected by MODIS are typically low-level (top height <2 km) and high-level clouds (top height >6 km) and, especially, those that are geometrically thin (<2 km). Geometrically thin clouds (<2 km) accounted for about 95.5% of all clouds that CPR misses. As reported in a similar study, very low and thin clouds (<0.3 km) over sea ice that are detected by MODIS are sometimes not observed by CPR and misclassified by CALIOP.

scholarly journals The potential of sea ice leads as a predictor for summer Arctic sea ice extent

2018 ◽  
Vol 12 (12) ◽  
pp. 3747-3757 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Jiping Liu ◽  
Fengming Hui
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Strong Relationship ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Leads ◽  
Arctic Sea Ice Extent

Abstract. The Arctic sea ice extent throughout the melt season is closely associated with initial sea ice state in winter and spring. Sea ice leads are important sites of energy fluxes in the Arctic Ocean, which may play an important role in the evolution of Arctic sea ice. In this study, we examine the potential of sea ice leads as a predictor for summer Arctic sea ice extent forecast using a recently developed daily sea ice lead product retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS). Our results show that July pan-Arctic sea ice extent can be predicted from the area of sea ice leads integrated from midwinter to late spring, with a prediction error of 0.28 million km2 that is smaller than the standard deviation of the observed interannual variability. However, the predictive skills for August and September pan-Arctic sea ice extent are very low. When the area of sea ice leads integrated in the Atlantic and central and west Siberian sector of the Arctic is used, it has a significantly strong relationship (high predictability) with both July and August sea ice extent in the Atlantic and central and west Siberian sector of the Arctic. Thus, the realistic representation of sea ice leads (e.g., the areal coverage) in numerical prediction systems might improve the skill of forecast in the Arctic region.

High interannual variability of sea ice thickness in the Arctic region

Nature ◽  
2003 ◽  
Vol 425 (6961) ◽  
pp. 947-950 ◽  
Author(s):  
Seymour Laxon ◽  
Neil Peacock ◽  
Doug Smith
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Arctic Region ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
The Arctic Region

scholarly journals Genome Sequence of Pedobacter arcticus sp. nov., a Sea Ice Bacterium Isolated from Tundra Soil

2012 ◽  
Vol 194 (23) ◽  
pp. 6688-6688 ◽  
Author(s):  
Ye Yin ◽  
Guidong Yue ◽  
Qiang Gao ◽  
Zhiyong Wang ◽  
Fang Peng ◽  
...  
Keyword(s):  
Cell Surface ◽  
Sea Ice ◽  
Genome Sequence ◽  
Arctic Region ◽  
The Arctic ◽  
Tundra Soil ◽  
Negative Bacterium ◽  
Gram Negative ◽  
Content Type ◽  
The Arctic Region

ABSTRACTPedobacter arcticussp. nov. was originally isolated from tundra soil collected from Ny-Ålesund, in the Arctic region of Norway. It is a Gram-negative bacterium which shows bleb-shaped appendages on the cell surface. Here, we report the draft annotated genome sequence ofPedobacter arcticussp. nov., which belongs to the genusPedobacter.

scholarly journals On the Arctic Wintertime Climate in Global Climate Models

2011 ◽  
Vol 24 (22) ◽  
pp. 5757-5771 ◽  
Author(s):  
Gunilla Svensson ◽  
Johannes Karlsson
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Precipitable Water ◽  
Open Ocean ◽  
Global Climate Models ◽  
The Arctic ◽  
Turbulent Heat ◽  
Skin Temperatures ◽  
Longwave Flux ◽  
The Arctic Region

Abstract Energy fluxes important for determining the Arctic surface temperatures during winter in present-day simulations from the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel dataset are investigated. The model results are evaluated over different surfaces using satellite retrievals and ECMWF interim reanalysis (ERA-Interim). The wintertime turbulent heat fluxes vary substantially between models and different surfaces. The monthly median net turbulent heat flux (upward) is in the range 100–200 W m−2 and −15 to 15 W m−2 over open ocean and sea ice, respectively. The simulated net longwave radiative flux at the surface is biased high over both surfaces compared to observations but for different reasons. Over open ocean, most models overestimate the outgoing longwave flux while over sea ice it is rather the downwelling flux that is underestimated. Based on the downwelling longwave flux over sea ice, two categories of models are found. One group of models that shows reasonable downwelling longwave fluxes, compared with observations and ERA-Interim, is also associated with relatively high amounts of precipitable water as well as surface skin temperatures. This group also shows more uniform airmass properties over the Arctic region possibly as a result of more frequent events of warm-air intrusion from lower latitudes. The second group of models underestimates the downwelling longwave radiation and is associated with relatively low surface skin temperatures as well as low amounts of precipitable water. These models also exhibit a larger decrease in the moisture and temperature profiles northward in the Arctic region, which might be indicative of too stagnant conditions in these models.

scholarly journals The Continuity MODIS-VIIRS Cloud Mask

2020 ◽  
Vol 12 (20) ◽  
pp. 3334 ◽  
Author(s):  
Richard A. Frey ◽  
Steven A. Ackerman ◽  
Robert E. Holz ◽  
Steven Dutcher ◽  
Zach Griffith
Keyword(s):  
Infrared Imaging ◽  
Cloud Fraction ◽  
The Arctic ◽  
Orthogonal Polarization ◽  
Cloud Detection ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Hit Rates ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask

This paper introduces the Continuity Moderate Resolution Imaging Spectroradiometer (MODIS)-Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask (MVCM), a cloud detection algorithm designed to facilitate continuity in cloud detection between the MODIS (Moderate Resolution Imaging Spectroradiometer) on the Aqua and Terra platforms and the series of VIIRS (Visible Infrared Imaging Radiometer Suite) instruments, beginning with the Soumi National Polar-orbiting Partnership (SNPP) spacecraft. It is based on the MODIS cloud mask that has been operating since 2000 with the launch of the Terra spacecraft (MOD35) and continuing in 2002 with Aqua (MYD35). The MVCM makes use of fourteen spectral bands that are common to both MODIS and VIIRS so as to create consistent cloud detection between the two instruments and across the years 2000–2020 and beyond. Through comparison data sets, including collocated Aqua MODIS and Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) from the A-Train, this study was designed to assign statistical consistency benchmarks between the MYD35 and MVCM cloud masks. It is shown that the MVCM produces consistent cloud detection results between Aqua MODIS, SNPP VIIRS, and NOAA-20 VIIRS and that the quality is comparable to the standard Aqua MODIS cloud mask. Globally, comparisons with collocated CALIOP lidar show combined clear and cloudy sky hit rates of 88.2%, 87.5%, 86.8%, and 86.8% for MYD35, MVCM Aqua MODIS, MVCM SNPP VIIRS, and MVCM NOAA-20 VIIRS, respectively, for June through until August, 2018. For the same months and in the same order for 60S–60N, hit rates are 90.7%, 90.5%, 90.1%, and 90.3%. From the time series constructed from gridded daily means of 60S–60N cloud fractions, we found that the mean day-to-day cloud fraction differences/standard deviations in percent to be 0.68/0.55, 0.94/0.64, −0.20/0.50, and 0.44/0.82 for MVCM Aqua MODIS-MVCM SNPP VIIRS day and night, and MVCM NOAA-20 VIIRS-MVCM SNPP VIIRS day and night, respectively. It is seen that the MODIS and VIIRS 1.38 µm cirrus detection bands perform similarly but with MODIS detecting slightly more clouds in the middle to high levels of the troposphere and the VIIRS detecting more in the upper troposphere above 16 km. In the Arctic, MVCM Aqua MODIS and SNPP VIIRS reported cloud fraction differences of 0–3% during the mid-summer season and −3–4% during the mid-winter.

Dominant Characteristics of early autumn Arctic sea ice variability and its impact on Winter Eurasian climate

2020 ◽  
pp. 1-67
Author(s):  
Shuoyi Ding ◽  
Bingyi Wu ◽  
Wen Chen
Keyword(s):  
Sea Ice ◽  
Geopotential Height ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Height Anomaly ◽  
Geopotential Height Anomaly ◽  
Arctic Sea ◽  
Westerly Winds ◽  
The Arctic Region

AbstractThe present study investigated dominant characteristics of autumn Arctic sea ice concentration (SIC) interannual variations and impacts of September-October (SO) mean SIC anomalies in the East Siberian-Chukchi-Beaufort (EsCB) Seas on winter Eurasian climate variability. Results showed that the decreased SO EsCB sea ice is favorable for tropospheric warming and positive geopotential height anomaly over the Arctic region one month later through transporting much more heat fluxes to the atmosphere from the open water. When entering the early winter (ND(0)J(1)), enhanced upward propagation of quasi-stationary planetary waves in the mid-high latitudes generates anomalous Eliassen-Palm flux convergence in the upper troposphere, which decelerates the westerly winds and maintains the positive geopotential height anomaly in the Arctic region. This anticyclonic anomaly extends southward into the central-western Eurasia and leads to evident surface cooling there. Two months later, it further develops toward downstream accompanied by a deepened trough, making the northeastern China experience a colder late winter (JFM(1)). Meanwhile, an anticyclonic anomaly over the eastern North Pacific excites a horizontal eastward wave train and contributes to positive (negative) geopotential height anomaly around the Greenland (Europe), favoring negative surface temperature anomaly over western Europe. In addition, the stratospheric polar vortex is also significantly weakened in the wintertime, which is attributed to decreased meridional temperature gradient and decelerated westerly winds provides a favorable condition for much more quasi-stationary planetary waves propagating into the stratosphere. Some major features of atmospheric responses to EsCB sea ice loss are well reproduced in the CAM4 sensitivity experiments.

scholarly journals Sensitivity of Arctic sulfate aerosol and clouds to changes in future surface seawater dimethylsulfide concentrations

2019 ◽  
Vol 19 (9) ◽  
pp. 6419-6435 ◽  
Author(s):  
Rashed Mahmood ◽  
Knut von Salzen ◽  
Ann-Lise Norman ◽  
Martí Galí ◽  
Maurice Levasseur
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Arctic Region ◽  
Sulfate Aerosol ◽  
The Arctic ◽  
Surface Seawater ◽  
Cloud Radiative Forcing ◽  
Future Global Warming ◽  
Arctic Surface ◽  
The Arctic Region

Abstract. Dimethylsulfide (DMS), outgassed from ocean waters, plays an important role in the climate system, as it oxidizes to methane sulfonic acid (MSA) and sulfur dioxide (SO2), which can lead to the formation of sulfate aerosol. Newly formed sulfate aerosol resulting from DMS oxidation may grow by condensation of gases, in-cloud oxidation, and coagulation to sizes where they may act as cloud condensation nuclei (CCN) and influence cloud properties. Under future global warming conditions, sea ice in the Arctic region is expected to decline significantly, which may lead to increased emissions of DMS from the open ocean and changes in cloud regimes. In this study we evaluate impacts of DMS on Arctic sulfate aerosol budget, changes in cloud droplet number concentration (CDNC), and cloud radiative forcing in the Arctic region under current and future sea ice conditions using an atmospheric global climate model. Given that future DMS concentrations are highly uncertain, several simulations with different surface seawater DMS concentrations and spatial distributions in the Arctic were performed in order to determine the sensitivity of sulfate aerosol budgets, CDNC, and cloud radiative forcing to Arctic surface seawater DMS concentrations. For any given amount and distribution of Arctic surface seawater DMS, similar amounts of sulfate are produced by oxidation of DMS in 2000 and 2050 despite large increases in DMS emission in the latter period due to sea ice retreat in the simulations. This relatively low sensitivity of sulfate burden is related to enhanced sulfate wet removal by precipitation in 2050. However simulated aerosol nucleation rates are higher in 2050, which results in an overall increase in CDNC and substantially more negative cloud radiative forcing. Thus potential future reductions in sea ice extent may cause cloud albedos to increase, resulting in a negative climate feedback on radiative forcing in the Arctic associated with ocean DMS emissions.

scholarly journals Future emissions from oil, gas, and shipping activities in the Arctic

2011 ◽  
Vol 11 (2) ◽  
pp. 4913-4951 ◽  
Author(s):  
G. P. Peters ◽  
T. B. Nilssen ◽  
L. Lindholt ◽  
M. S. Eide ◽  
S. Glomsrød ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Oil And Gas ◽  
Arctic Region ◽  
Gas Production ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Emission Inventories ◽  
Oil And Gas Production ◽  
The Arctic Region

Abstract. The Arctic sea-ice is retreating faster than predicted by climate models and could become ice free during summer this century. The reduced sea-ice extent may effectively "unlock" the Arctic Ocean to increased human activities such as transit shipping and expanded oil and gas production. Travel time between Europe and the north Pacific Region can be reduced by up to 50% with low sea-ice levels and the use of this route could increase substantially as the sea-ice retreats. Oil and gas activities already occur in the Arctic region and given the large undiscovered petroleum resources increased activity could be expected with reduced sea-ice. We use a detailed global energy market model and a bottom-up shipping model with a sea-ice module to construct emission inventories of Arctic shipping and petroleum activities in 2030 and 2050. The emission inventories are on a 1× 1 degree grid and cover both short-lived pollutants and ozone pre-cursors (SO2, NOx, CO, NMVOC, BC, OC) and the long-lived greenhouse gases (CO2, CH4, N2O). We find rapid growth in transit shipping due to increased profitability with the shorter transit times compensating for increased costs in traversing areas of sea-ice. Oil and gas production remains relatively stable leading to reduced emissions from emission factor improvements. The location of oil and gas production moves into locations requiring more ship transport relative to pipeline transport, leading to rapid emissions growth from oil and gas transport via ship. Our emission inventories for the Arctic region will be used as input into chemical transport, radiative transfer, and climate models to quantify the role of Arctic activities in climate change compared to similar emissions occurring outside of the Arctic region.

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