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At least 253 records · Page 14

High Latitude Considerations in the Latest GPCP monthly and daily products (V3.1)

The Global Precipitation Climatology Project (GPCP) product is a popular combined satellite-gauge precipitation data set in which the long-term standards of consistency and homogeneity is underlined. Here we discuss various high latitude analysis considered in the recently released GPCP V3.1 monthly and daily products. Satellite data are used over land and ocean and obtained from the Special Sensor Microwave Imager (SSMI), Special Sensor Microwave Imager/Sounder (SSMIS), geostationary imagers and polar orbiting infrared sounders. GPCP uses the Global Precipitation Climatology Centre (GPCC) over land, as its in situ component, but prior to combination with satellite data GPCC estimates are adjusted for gauge undercatch. Advanced sensors aboard the Tropical Rainfall Measuring Mission (TRMM), CloudSat, and Global Precipitation Measurement (GPM) mission have enabled more accurate estimation of rain and snowfall rates in recent years. Started with GPCP V3.1 these observations are integrated into GPCP through the development of the Tropical Combined Climatology (TCC) used at lower latitudes and the Merged CloudSat, TRMM, and GPM (MCTG) climatology used over the extra tropics and higher latitudes. Improved calibrations of Television-Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) and Advanced Infrared Sounder (AIRS) precipitation are used outside 60ºN-S, where inside this zone the Goddard Profiling (GPROF) algorithm retrievals from SSMI/SSMIS is used to calibrate geostationary IR based precipitation estimate at monthly scale. The Gravity Recovery and Climate Experiment (GRACE) mass change observations are used to determine snowfall accumulations over frozen land and arctic basins and to assess gauge undercatch corrections. Observations of snow on sea ice from NASA’s Operation IceBridge (OIB) flights are utilized as an additional tool for snowfall assessment over sea ice. GPCP V3.1 has higher spatial resolution (0.5ox0.5o) than earlier versions (2.5ox2.5o) over both land and ocean, going back to 1983. Version 3 Daily product uses the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) Final Run V06 estimates, where available (initially restricted to 60°N-S), as well as rescaled TOVS/AIRS data in high-latitude areas, all calibrated to the GPCP V3.1 Monthly estimate. GPCP V3.1 shows about 6% increase in global oceanic precipitation and about 4.5% increase over global land and ocean compared to the previous version (V2.3), some major changes occur over the ocean and around 40oS and 60 oS. We will discuss other important changes of GPCP V3.1, compared to the earlier versions, and our future plans. Through this presentation we will also discuss that while ACCP will provide key information about precipitation, synergistic use of other Earth observing systems (e.g., mass change; recognized as a designated mission in 2017 decadal survey) can also help refine precipitation analysis, especially in high latitude and cold regions.

Ali Behrangi↗

Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗

Quantification of Discharge-Specific Effects on Dissolved Organic Matter Export From Major Arctic Rivers From 1982 Through 2019

Long-term increases in Arctic river discharge have been well documented, and observations in the six largest Arctic rivers show strong positive correlations between dissolved organic carbon (DOC) concentration, river discharge, and chromophoric dissolved organic matter (CDOM) content. Here, observations of DOC and CDOM collected from 2009-2019 by the Arctic Great Rivers Observatory were used to estimate chromophoric DOC (CDOC) concentrations in the Kolyma, Lena, Mackenzie, Ob’, Yenisey, and Yukon Rivers. All rivers but the Mackenzie showed significant positive correlations between annual watershed runoff and the proportion of the DOC that is chromophoric. Historical estimates of DOC and CDOC export were calculated for 1982-2019 by extrapolating the DOC and CDOC concentration – discharge relationships from 2009-2019 as a hindcast modeled estimate. For the six rivers combined, modeled DOC and CDOC export increased, but CDOC increased faster than total DOC. The Lena and Ob’ Rivers showed significant increases in DOC export individually, with annual trends of 39.1 and 20.4 Gg C yr -1 respectively. November-April (winter) DOC and CDOC export increased in all rivers but the Yenisey, with the hindcast winter Kolyma export increasing by more than 20% per decade. There were no significant trends in discharge or associated DOC and CDOC fluxes during the observational period from 2009-2019; only when hindcasted values driven by changes in river discharge were analyzed did trends in DOC and CDOC emerge. This demonstrates how shifting seasonal distributions and increases in discharge can drive changes in DOC and CDOC concentrations and export, independent of other environmental factors.

carbon cycle↗

The Temperature of the Arctic and Antarctic Lower Stratosphere

The temperature of the polar lower stratosphere during spring is the key factor in changing the magnitude of ozone loss in the polar vortices. In this talk, we will review the results of Newman et al. [2000] that quantitatively demonstrate that the polar lower stratospheric temperature is primarily controlled by planetary-scale waves. In particular, the tropospheric eddy heat flux in middle to late winter (January--February) is highly correlated with the mean polar stratospheric temperature during March. Strong midwinter planetary wave forcing leads to a warmer spring Arctic lower stratosphere in early spring, while weak midwinter forcing leads to cooler spring Arctic temperatures. In addition, this planetary wave driving also has a strong impact on the strength of the polar vortex. These results from the Northern Hemisphere will be contrasted with the Southern Hemisphere.

Newman, Paul A.↗

Winter Arctic Sea Ice Thickness from ICESat-2 Freeboards

NASA’s ICESat-2 mission was launched in September 2018 with the primary goal of monitoring our rapidly changing polar regions. The sole instrument onboard, the Advanced Topographic Laser Altimeter System (ATLAS), is now providing routine, very high-resolution, surface elevation data across the globe, including the Arctic and Southern Oceans. In this study we demonstrate our new processing chain for converting the along-track ICESat-2 sea ice freeboard product (ATL10) into sea ice thickness, focusing our initial efforts on the Arctic Ocean. For this conversion we primarily make use of snow depth and density data from the NASA Eulerian Snow on Sea Ice Model (NESOSIM). The coarse resolution (~100 km) snow data are redistributed onto the high resolution (~30 - 100 m) ATL10 freeboards using relationships obtained from snow depth and freeboard data collected by NASA’s Operation IceBridge mission. We present regional sea ice thickness distributions and highlight their seasonal evolution through our first winter-season of data collection. We include ice thickness uncertainty estimates, while also acknowledging the limitations of these estimates. We generate a gridded monthly thickness product and compare this with various monthly sea ice thickness estimates obtained from ESA’s CryoSat-2 satellite mission, with ICE 33 Sat-2 showing consistently lower thicknesses. Finally, we compare our February/March 2019 thickness estimates to ICESat February/March (19th February – 21st March) 2008 ice thickness estimates using the same input assumptions, which show a ~0.40 m or ~21% thinning across an inner Arctic Ocean domain in this 11-year time period.

Alek A Petty↗

Does a Relationship Between Arctic Low Clouds and Sea Ice Matter?

Arctic low clouds strongly affect the Arctic surface energy budget. Through this impact Arctic low clouds influence important aspects of the Arctic climate system, namely surface and atmospheric temperature, sea ice extent and thickness, and atmospheric circulation. Arctic clouds are in turn influenced by these elements of the Arctic climate system, and these interactions create the potential for Arctic cloud-climate feedbacks. To further our understanding of potential Arctic cloudclimate feedbacks, the goal of this paper is to quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and its covariation with sea ice concentration (SIC). We build on previous research using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, there is a weak covariation between CRE and SIC for most atmospheric conditions. Third, the results show statistically significant differences in the average surface CRE under different SIC values in fall indicating a 3-5 W m(exp -2) larger LW CRE in 0% versus 100% SIC footprints. Because systematic changes on the order of 1 W m(exp -2) are sufficient to explain the observed long-term reductions in sea ice extent, our results indicate a potentially significant amplifying sea ice-cloud feedback, under certain meteorological conditions, that could delay the fall freeze-up and influence the variability in sea ice extent and volume. Lastly, a small change in the frequency of occurrence of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea ice.

Taylor, Patrick C.↗

Predictability of the Minimum Sea Ice Extent from Late Winter Fram Strait Ice Export: Model vs Observations

Late winter coastal divergence along the Eurasian coastline (referred to as the ice factory) – or the Fram Strait ice export, a proxy for coastal divergence in the ice factory – is a skillful predictor of the minimum sea ice extent (Williams et al., 2016; Brunette et al., 2018; Sesternikov and, 1979). Coastal divergence leads to the formation of coastal polynya where new ice grows but to a thickness that is not large enough to survive the following summer melt. This signal is then amplified by the ice albedo feedback and leads to more open water at the end of the summer melt season. In this thesis project, we will identify if this source of predictive skill in the seasonal forecast of the minimum sea ice extent is present in General Circulation Models, more precisely in the CESM2-LE, GISS-E2.1-G, GFDL FLOR-LE, CNRM-CM6-1 and the CanESM5. Since even small biases in the large-scale atmospheric circulation simulated by a model can short circuit this coupling between dominant modes of atmospheric variability (NAO and AO), coastal divergence along the Eurasian coastline, Fram Strait ice export and therefore seasonal forecasting skill of the model, failure to reproduce this coupling observed in the real Arctic will be used to identify biases in GCM. Preliminary results show that subtle changes in the large-scale atmospheric circulation leads to opposite statistical relationship between Fram Strait ice area export, coastal divergence along the Eurasian coastline, and seasonal predictability of the minimum sea ice extent both in the CESM2-LE and the GISS-E2.1-G models. Differences are linked with the partitioning between recirculation within the Beaufort Gyre, ice exported through Fram Strait and ridging north of the Canadian Arctic Archipelago.

Sea ice↗

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Sellers, Piers↗

Assessing the Tundra-taiga Boundary with Multi-Sensor Satellite Data

Monitoring the dynamics of the circumpolar boreal forest (taiga) and Arctic tundra boundary is important for understanding the causes and consequences of changes observed in these areas. This ecotone, the world's largest, stretches for over 13,400 km and marks the transition between the northern limits of forests and the southern margin of the tundra. Because of the inaccessibility and large extent of this zone, remote sensing data can play an important role for mapping the characteristics and monitoring the dynamics. Basic understanding of the capabilities of existing space borne instruments for these purposes is required. In this study we examined the use of several remote sensing techniques for identifying the existing tundra- taiga ecotone. These include Landsat-7, MISR, MODIS and RADARSAT data. Historical cover maps, recent forest stand measurements and high-resolution IKONOS images were used for local ground truth. It was found that a tundra-taiga transitional area can be characterized using multi- spectral Landsat ETM+ summer images, multi-angle MISR red band reflectance images, RADARSAT images with larger incidence angle, or multi-temporal and multi-spectral MODIS data. Because of different resolutions and spectral regions covered, the transition zone maps derived from different data types were not identical, but the general patterns were consistent.

Ranson, K. J.↗

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Uttal, Taneil↗

Radio Noise Problems in Arctic Regions

Three main types of radio noise should be considered when establishing noise levels for communication purposes or in experiments utilizing radio techniques in Arctic regions. These are atmospheric and man-made noise, and precipitation static. National Bureau of Standards radio noise data obtained hourly at Arctic and Antarctic stations on eight .fixed frequencies between 51 kc and 20 Mc/s are analyzed to show the characteristics of the three types. The diurnal and seasonal variations of atmospheric radio noise at high latitudes are explainable in terms of changes in propagation factors and in the distribution of world thunderstorm activity. In both northern and southern Arctic regions atmospheric noise decreases during polar cap absorption (PCA), most markedly in the h.f. band. The probable magnitude of man-made noise in the h.f. band is estimated from data taken during PCA, when atmospheric noise is absent. At Thule man-made noise on 2.5 and 5 Mc/s appears to be 57 and 49 dB above kTB (where kTB is antenna thermal noise power), respectively, while at Byrd Station the values are about 20 and 12 dB respectively. Precipitation static is generated on exposed antennas during periods of blowing snow (blizzards). The noise power magnitude can be at least 50 dB above man-made and atmospheric levels, but the maximum enhancement cannot be ascertained because of missing data. In winter and spring months at Byrd Station radio data dependent upon exposed antennas may be lost 10-30 per cent of the time due to precipitation static alone.

Radio Noise↗

Melt Pond Conditions on Declining Arctic Sea Ice Over 1979-2016: Model Development, Validation, and Results

A melt pond (MP) distribution equation has been developed and incorporated into the Marginal Ice-Zone Modeling and Assimilation System to simulate Arctic MPs and sea ice over 1979-2016. The equation differs from previous MP models and yet benefits from previous studies for MP parameterizations as well as a range of observations for model calibration. Model results show higher magnitude of MP volume per unit ice area and area fraction in most of the Canada Basin and the East Siberian Sea and lower magnitude in the central Arctic. This is consistent with Moderate Resolution Imaging Spectroradiometer observations, evaluated with Measurements of Earth Data for Environmental Analysis (MEDEA) data, and closely related to top ice melt per unit ice area. The model simulates a decrease in the total Arctic sea ice volume and area, owing to a strong increase in bottom and lateral ice melt. The sea ice decline leads to a strong decrease in the total MP volume and area. However, the Arctic-averaged MP volume per unit ice area and area fraction show weak, statistically insignificant downward trends, which is linked to the fact that MP water drainage per unit ice area is increasing. It is also linked to the fact that MP volume and area decrease relatively faster than ice area. This suggests that overall the actual MP conditions on ice have changed little in the past decades as the ice cover is retreating in response to Arctic warming, thus consistent with the Moderate Resolution Imaging Spectroradiometer observations that show no clear trend in MP area fraction over 2000-2011.

sea ice↗

Icehouse Effect: A Polar Autumn and Winter Cooling Trend

The icehouse effect is a hypothesized polar climate trend toward cooling (or lack of warming) in response to greenhouse warming of adjacent lower latitudes. When greenhouse warmed air from lower latitudes moves over ice and snow, it generates a stronger, more stable, cappino, inversion than in a parallel case without greenhouse warming. Because the degree of decoupling between vertically adjacent air masses is directly dependent on the strength of the inversion, the capping inversion acts somewhat analogously to the walls and roof of the icehouse of generations past. What is inside the icehouse, namely the cold polar atmospheric boundary layer (ABL) air, is preserved by the "insulation" or decoupling, provided by the warm air aloft. Observations over the Arctic Ocean have shown an unexpected lack of any detectable surface warming trend over the past 40 years. This finding strongly contradicts climate model predictions that polar regions should show the strongest effect of greenhouse warming. It also stands in contrast to the consensus reached by the Intergovernmental Panel on Climate Change (IPCC), that human caused greenhouse warming is now detectable globally. One might ask: Are these Arctic observations wrong? Or, if right, is there a plausible physical explanation for them? The published observations mentioned above used about 50,000 soundings over the Arctic Ocean. Here I present a novel analysis of ALL available Arctic rawinsonde data north of 65N--a total of more than 1.1 million soundings. The analysis confirms the previously published result: There is indeed a slight climate-cooling trend in the vast majority of the data. Importantly, there are also select conditions (very strong and very weak stability of the ABL) which show a consistent, strong Arctic warming trend. It is the juxtaposition of these warming and cooling trends which defines a unique "icehouse signature" for which an explanation can be sought.

Wetzel, Peter J.↗

Alaska Ecological Conservation: Using NASA Earth Observations to Identify Recent Changes in River Ice Phenology and Its Impacts on Caribou Migration

Each fall, caribou (Rangifer tarandus) in the Western Arctic Herd migrate hundreds of kilometers across northwestern Alaska to acquire seasonal resources and reach wintering grounds. Various rivers intersect migration paths, and caribou can only cross over open water or high-ice extents but are unable to cross rivers in stages of partial freezing. Recent temperature increases in Alaska can alter the timing and duration of ice formation periods, impeding migratory patterns. The Massachusetts NASA DEVELOP team partnered with the National Park Service in Alaska to detect river ice onset dates and formation periods using Landsat 8 Operational Land Imager and Landsat 9 Operational Land Imager-2, Sentinel-1 C-band Synthetic Aperture Radar and Sentinel-2A/B MultiSpectral Instrument imagery in Google Earth Engine. This feasibility analysis measured ice coverage using the Normalized Difference Infrared Index, Relative Difference River Ice, and Vertical-Vertical/Vertical-Horizontal backscatter values based on the spectral and surface characteristics of rivers. The team produced annual freezing timelines, time series plots, and maps at three river stretches to analyze river ice phenology changes. Radar imagery assessed ice coverage more accurately, while optical imagery better identified ice onset dates. Meanwhile indices were unable to robustly establish ice formation thresholds across the study period. These study results can help the National Park Service to better evaluate spatiotemporal migratory shifts and contextualize recent regional caribou declines.

river phenology↗

Skillful Spring Forecasts of September Arctic Sea Ice Extent Using Passive Microwave Data

In this study, we demonstrate skillful spring forecasts of detrended September Arctic sea ice extent using passive microwave observations of sea ice concentration (SIC) and melt onset (MO). We compare these to forecasts produced using data from a sophisticated melt pond model, and find similar to higher skill values, where the forecast skill is calculated relative to linear trend persistence. The MO forecasts shows the highest skill in March-May, while the SIC forecasts produce the highest skill in June-August, especially when the forecasts are evaluated over recent years (since 2008). The high MO forecast skill in early spring appears to be driven primarily by the presence and timing of open water anomalies, while the high SIC forecast skill appears to be driven by both open water and surface melt processes. Spatial maps of detrended anomalies highlight the drivers of the different forecasts, and enable us to understand regions of predictive importance. Correctly capturing sea ice state anomalies, along with changes in open water coverage appear to be key processes in skillfully forecasting summer Arctic sea ice.

melt onset↗

Heat Pipes For Alyeska

The heat pipes job is to keep the arctic ground frozen. The permafrost soil alternately freezes and thaws with seasonal temperature changes causing surface dislocations and problems for the builders. In winter, a phenomenon called frost-heaving uplifts the soil. It is something like the creation of highway potholes by the freezing of rainwater below the roadbed, but frost-heaving exerts a far greater force. Thawing of the frost in the summer causes the soil to settle unevenly. Therefore it is necessary to keep the soil in a continually frozen state so the pipeline won't rupture. To solve this problem, McDonnell Douglas Corp. applied heat pipe principles in the design of the vertical supports that hold up the pipeline.

Source record↗

Sea Ice and Ice Temperature Variability as Observed by Microwave and Infrared Satellite Data

Recent reports of a retreating and thinning sea ice cover in the Arctic have pointed to a strong suggestion of significant warming in the polar regions. It is especially important to understand what these reports mean in light of the observed global warning and because the polar regions are expected to be most sensitive to changes in climate. To gain insight into this phenomenon, co-registered ice concentrations and surface temperatures derived from two decades of satellite microwave and infrared data have been processed and analyzed. While observations from meteorological stations indicate consistent surface warming in both regions during the last fifty years, the last 20 years of the same data set show warming in the Arctic but a slight cooling in the Antarctic. These results are consistent with the retreat in the Arctic ice cover and the advance in the Antarctic ice cover as revealed by historical satellite passive microwave data. Surface temperatures derived from satellite infrared data are shown to be consistent within 3 K with surface temperature data from the limited number of stations. While not as accurate, the former provides spatially detailed changes over the twenty year period. In the Arctic, for example, much of the warming occurred in the Beaufort Sea and the North American region in 1998 while slight cooling actually happened in parts of the Laptev Sea and Northern Siberia during the same time period. Big warming anomalies are also observed during the last five years but a periodic cycle of about ten years is apparent suggesting a possible influence of the North Atlantic Oscillation. In the Antarctic, large interannual and seasonal changes are also observed in the circumpolar ice cover with regional changes showing good coherence with surface temperature anomalies. However, a mode 3 is observed to be more dominant than the mode 2 wave reported in the literature. Some of these spatial and temporal changes appear to be influenced by the Antarctic Circumpolar Wave (ACW) and changes in coastal polynya activities.

Comiso, Josefino C.↗