Satellite-derived ice data sets no. 2: Arctic monthly average microwave brightness temperatures and sea ice concentrations, 1973-1976

A summary data set for four years (mid 70's) of Arctic sea ice conditions is available on magnetic tape. The data include monthly and yearly averaged Nimbus 5 electrically scanning microwave radiometer (ESMR) brightness temperatures, an ice concentration parameter derived from the brightness temperatures, monthly climatological surface air temperatures, and monthly climatological sea level pressures. All data matrices are applied to 293 by 293 grids that cover a polar stereographic map enclosing the 50 deg N latitude circle. The grid size varies from about 32 X 32 km at the poles to about 28 X 28 km at 50 deg N. The ice concentration parameter is calculated assuming that the field of view contains only open water and first-year ice with an ice emissivity of 0.92. To account for the presence of multiyear ice, a nomogram is provided relating the ice concentration parameter, the total ice concentration, and the fraction of the ice cover which is multiyear ice

Sudden increase in Antarctic sea ice: Fact or artifact?

Copyright © 2011 American Geophysical UnionThree sea ice data sets commonly used for climate research display a large and abrupt increase in Antarctic sea ice area (SIA) in recent years. This unprecedented change of SIA is diagnosed to be primarily caused by an apparent sudden increase in sea ice concentrations within the ice pack, especially in the area of the most-concentrated ice (greater than 95% concentration). A series of alternative satellite-derived records do not display any abnormal sudden SIA changes, but do reveal substantial discrepancies between different satellite sensors and sea ice algorithms. Sea ice concentrations in the central ice pack and SIA values derived from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSRE) are consistently greater than those derived from the Special Sensor Microwave Imager (SSMI). A switch in source data from the SSMI to AMSRE in mid-2009 explains most of the SIA increase in all three affected data sets. If uncorrected for, the discontinuity artificially exaggerates the winter Antarctic SIA increase (1979–2010) by more than a factor of 2 and the spring trend by almost a factor of 4. The discontinuity has a weaker influence on the summer and autumn SIA trends, on calculations of Antarctic sea ice extent, and in the Arctic

Warming of the Antarctic ice-sheet surface since the 1957 International Geophysical Year

Assessments of Antarctic temperature change have emphasized the contrast between strong warming of the Antarctic Peninsula and slight cooling of the Antarctic continental interior in recent decades. This pattern of temperature change has been attributed to the increased strength of the circumpolar westerlies, largely in response to changes in stratospheric ozone. This picture, however, is substantially incomplete owing to the sparseness and short duration of the observations. Here we show that significant warming extends well beyond the Antarctic Peninsula to cover most of West Antarctica, an area of warming much larger than previously reported. West Antarctic warming exceeds 0.1 °C per decade over the past 50 years, and is strongest in winter and spring. Although this is partly offset by autumn cooling in East Antarctica, the continent-wide average near-surface temperature trend is positive. Simulations using a general circulation model reproduce the essential features of the spatial pattern and the long-term trend, and we suggest that neither can be attributed directly to increases in the strength of the westerlies. Instead, regional changes in atmospheric circulation and associated changes in sea surface temperature and sea ice are required to explain the enhanced warming in West Antarctica

Estimating the Thickness of Sea Ice Snow Cover in the Weddell Sea from Passive Microwave Brightness Temperatures

Passive microwave satellite observations have frequently been used to observe changes in sea ice cover and concentration. Comiso et al. showed that there may also be a direct relationship between the thickness of snow cover (h(sub s)) on ice and microwave emissivity at 90 GHz. Because the in situ experiment of experiment of Comiso et al. was limited to a single station, the relationship is re-examined in this paper in a more general context and using more extensive in situ microwave observations and measurements of h from the Weddell Sea 1986 and 1989 winter cruises. Good relationships were found to exist between h(sub s) sand the emissivity at 90 GHz - 10 GHz and the emissivity at 90 GHz - 18.7 GHz when the standard deviation of h(sub s) was less than 50% of the mean and when h(sub s) was less than 0.25 m. The reliance of these relationships on h(sub s) is most likely caused by the limited penetration through the snow of radiation at 90 GHz. When the algorithm was applied to the Special Sensor Microwave/Imager (SSM/I) satellite data from the Weddell Sea, the resulting mean h(sub s) agreed within 5% of the mean calculated from greater than 1400 in situ observations

Twenty-first-century climate impacts from a declining Arctic sea ice cover

A steady decline in Arctic sea ice has been observed over recent decades. General circulation models predict further decreases under increasing greenhouse gas scenarios. Sea ice plays an important role in the climate system in that it influences ocean-to-atmosphere fluxes, surface albedo, and ocean buoyancy. The aim of this study is to isolate the climate impacts of a declining Arctic sea ice cover during the current century. The Hadley Centre Atmospheric Model (HadAM3) is forced with observed sea ice from 1980 to 2000 (obtained from satellite passive microwave radiometer data derived with the Bootstrap algorithm) and predicted sea ice reductions until 2100 under one moderate scenario and one severe scenario of ice decline, with a climatological SST field and increasing SSTs. Significant warming of the Arctic occurs during the twenty-first century (mean increase of between 1.6° and 3.9°C), with positive anomalies of up to 22°C locally. The majority of this is over ocean and limited to high latitudes, in contrast to recent observations of Northern Hemisphere warming. When a climatological SST field is used, statistically significant impacts on climate are only seen in winter, despite prescribing sea ice reductions in all months. When correspondingly increasing SSTs are incorporated, changes in climate are seen in both winter and summer, although the impacts in summer are much smaller. Alterations in atmospheric circulation and precipitation patterns are more widespread than temperature, extending down to midlatitude storm tracks. Results suggest that areas of Arctic land ice may even undergo net accumulation due to increased precipitation that results from loss of sea ice. Intensification of storm tracks implies that parts of Europe may experience higher precipitation rates

Nonlinear mushy-layer convection with chimneys: stability and optimal solute fluxes

We model buoyancy-driven convection with chimneys -- channels of zero solid fraction -- in a mushy layer formed during directional solidification of a binary alloy in two-dimensions. A large suite of numerical simulations is combined with scaling analysis in order to study the parametric dependence of the flow. Stability boundaries are calculated for states of finite-amplitude convection with chimneys, which for a narrow domain can be interpreted in terms of a modified Rayleigh number criterion based on the domain width and mushy-layer permeability. For solidification in a wide domain with multiple chimneys, it has previously been hypothesised that the chimney spacing will adjust to optimise the rate of removal of potential energy from the system. For a wide variety of initial liquid concentration conditions, we consider the detailed flow structure in this optimal state and derive scaling laws for how the flow evolves as the strength of convection increases. For moderate mushy-layer Rayleigh numbers these flow properties support a solute flux that increases linearly with Rayleigh number. This behaviour does not persist indefinitely, however, with porosity-dependent flow saturation resulting in sub-linear growth of the solute flux for sufficiently large Rayleigh numbers. Finally, we consider the influence of the porosity dependence of permeability, with a cubic function and a Carmen-Kozeny permeability yielding qualitatively similar system dynamics and flow profiles for the optimal states.Comment: 20 pages, 10 figures. Changes from previous version correct typos, expand on discussion of the method including new appendix A, and minor changes to the discussion. A modified final version has been accepted for publication in the Journal of Fluid Mechanic

Arctic Ocean Primary Productivity: The Response of Marine Algae to Climate Warming and Sea Ice Decline

Highlights: 1. Satellite estimates of ocean primary productivity (i.e., the rate at which marine algae transform dissolved inorganic carbon into organic material) were higher in 2018 (relative to the 2003-17 mean) for three of the nine investigated regions (the Eurasian Arctic, Bering Sea, and Baffin Bay). 2. All regions continue to exhibit positive trends over the 2003-18 period, with the strongest trends for the Eurasian Arctic, Barents Sea, Greenland Sea, and North Atlantic. 3. The regional distribution of relatively high (low) chlorophyll-a concentrations can often be associated with a relatively early (late) breakup of sea ice cover

Linked trends in the South Pacific sea ice edge and Southern Oscillation Index

Previous work have shown that sea ice variability in the South Pacific is associated with extratropical atmospheric anomalies linked to the Southern Oscillation (SO). Over a 32 year period (1982–2013), our study shows that the trend in Southern Oscillation Index (SOI) is also able to quantitatively explain the trends in sea ice edge, drift, and surface winds in this region. On average two thirds of the winter ice edge trend in this sector, linked to ice drift and surface winds, could be explained by the positive SOI trend, thus subjecting the ice edge to strong decadal SO variability. If this relationship holds, the negative SOI trend prior to the recent satellite era suggests that ice edge trends opposite to that of the recent record over a similar time scale. Significant low-frequency ice edge trends, linked to the natural variability of SO, are superimposed upon any trends expected of anthropogenic forcing

Positive trend in the Antarctic sea ice cover and associated changes in surface temperature

The Antarctic sea ice extent has been slowly increasing contrary to expected trends due to global warming and results from coupled climate models. After a record high extent in 2012 the extent was even higher in 2014 when the magnitude exceeded 20 × 106 km2 for the first time during the satellite era. The positive trend is confirmed with newly reprocessed sea ice data that addressed inconsistency issues in the time series. The variability in sea ice extent and ice area was studied alongside surface ice temperature for the 34-yr period starting in 1981, and the results of the analysis show a strong correlation of −0.94 during the growth season and −0.86 during the melt season. The correlation coefficients are even stronger with a one-month lag in surface temperature at −0.96 during the growth season and −0.98 during the melt season, suggesting that the trend in sea ice cover is strongly influenced by the trend in surface temperature. The correlation with atmospheric circulation as represented by the southern annular mode (SAM) index appears to be relatively weak. A case study comparing the record high in 2014 with a relatively low ice extent in 2015 also shows strong sensitivity to changes in surface temperature. The results suggest that the positive trend is a consequence of the spatial variability of global trends in surface temperature and that the ability of current climate models to forecast sea ice trend can be improved through better performance in reproducing observed surface temperatures in the Antarctic region

Validation of the MODIS "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. First we provide comparisons between Terra and Aqua swath-based ISTs at approximately 14:00 Local Solar Time, reprojected to 12.5 km polar stereographic cells. Results show good correspondence when Terra and Aqua data were acquired within 2 hrs of each other. For example, for a cell centered over Summit Camp (72.58 N, 38.5 W), the average agreement between Terra and Aqua ISTs is 0.74 K (February 2003), 0.47 K (April 2003), 0.7 K (August 2003) and 0.96 K (October 2003) with the Terra ISTs being generally lower than the Aqua ISTs. More precise comparisons will be calculated using pixel data at the swath level, and correspondence between Terra and Aqua IST is expected to be closer. (Because of cloud cover and other considerations, only a few common cloud-free swaths are typically available for each month for comparison.) Additionally, previous work comparing land-surface temperatures (LSTs) from the standard MODIS LST product and in-situ surface-temperature data at Summit Camp on the Greenland Ice Sheet show that Terra MODIS LSTs are about 3 K lower than in-situ temperatures at Summit Camp, during the winter of 2008-09. This work will be repeated using both Terra and Aqua IST pixel data (in place of LST data). In conclusion, we demonstrate that the uncertainties in the CDR will be well characterized as we work through the various facets of its validation