Sea ice-atmosphere interaction. Application of multispectral satellite data in polar surface energy flux estimates

Satellite data for the estimation of radiative and turbulent heat fluxes is becoming an increasingly important tool in large-scale studies of climate. One parameter needed in the estimation of these fluxes is surface temperature. To our knowledge, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic, an area where the first effects of a changing climate are expected to be seen. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol profiles, the microphysical properties of polar clouds, and the spectral characteristics of the wide variety of surface types found there. We have developed a means to correct for the atmospheric attenuation of satellite-measured clear sky brightness temperatures used in the retrieval of ice surface temperature from the split-window thermal channels of the advanced very high resolution radiometer (AVHRR) sensors on-board three of the NOAA series satellites. These corrections are specified for three different 'seasons' and as a function of satellite viewing angle, and are expected to be applicable to the perennial ice pack in the central Arctic Basin

Spatial and Temporal Variations of Surface Characteristics on the Greenland Ice Sheet as Derived from Passive Microwave Observations

The primary goals of this research were to identify and begin to comprehend the spatial and temporal variations in surface characteristics of the Greenland ice sheet using passive microwave observations, physically-based models of the snowpack and field observations of snowpack and firn properties

Studies of the geophysics of sea ice

Thesis (Ph.D.) University of Alaska Fairbanks, 1993A non-linear growth model that solves the surface energy balance and heat conduction equations was developed to estimate thermal and physical properties of sea ice. The model incorporates several mechanisms that affect the salinity profile, including initial brine entrapment, brine expulsion, and gravity drainage, and is a non-linear extension of the model initially developed by Cox and Weeks (1988). Simulations were run to investigate the effects of the non-linear feedbacks which exist between the ice growth velocity and the thermal properties of the resulting ice. A comparison of the growth rate versus accumulated freeze-days was performed on the linear model, the non-linear model, and empirical formulas based on field observations. Allowing the model to run through the summer months with retarded ice growth and making an attempt at modelling summer desalinization processes produced second and third-year ice with proper temperature and salinity profiles. The ice growth model was then coupled to a Lambertian surface backscattering model for radar. By calculating the average dielectric constant of the penetration depth and using this value in the backscattering model, a comparison of the predicted signature variations in first-year sea ice was performed against observed backscattering values from ERS-1 SAR images of Dease Inlet, Alaska. The agreement between calculated and observed backscatter was surprisingly good considering that other factors may also influence radar returns. However, the more surprising result was the rescaling of the predicted first year ice signature by +6 dB produced a remarkable fit to observed backscattering values of multiyear ice. The predicted backscatter values and ice thicknesses were then used in conjunction with ERS-1 SAR imagery of the high Arctic to estimate areal coverage of the three major ice types in a 100 x 100 km\sp2 area. Heat and mass flux calculations were then performed to produce daily estimates of energy loss and salt infusion for the winter months of October 1991 through March 1992

A Multi-Sensor and Modeling Approach for Mapping Light Under Sea Ice During the Ice-Growth Season

Arctic sea ice is shifting from a year-round to a seasonal sea ice cover. This substantial transformation, via a reduction in Arctic sea ice extent and a thinning of its thickness, influences the amount of light entering the upper ocean. This in turn impacts underice algal growth and associated ecosystem dynamics. Field campaigns have provided valuable insights as to how snow and ice properties impact light penetration at fixed locations in the Arctic, but to understand the spatial variability in the under-ice light field there is a need to scale up to the pan-Arctic level. Combining information from satellites with state-of-the-art parameterizations is one means to achieve this. This study combines satellite and modeled data products to map under-ice light on a monthly time-scale from 2011 through 2018. Key limitations pertain to the availability of satellitederived sea ice thickness, which for radar altimetry, is only available during the sea ice growth season. We clearly show that year-to-year variability in snow depth, along with the fraction of thin ice, plays a key role in how much light enters the Arctic Ocean. This is particularly significant in April, which in some regions, coincides with the beginning of the under-ice algal bloom, whereas we find that ice thickness is the main driver of under-ice light availability at the end of the melt season in October. The extension to the melt season due to a warmer Arctic means that snow accumulation has reduced, which is leading to positive trends in light transmission through snow. This, combined with a thinner ice cover, should lead to increased under-ice PAR also in the summer month

Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling

Broad spectral, interdisciplinary investigation of the electromagnetic properties of sea ice

Journal ArticleThis paper highlights the interrelationship of research completed by a team of investigators and presented in the several individual papers comprising this Special Section on the Office of Naval Research (ONR), Arlington, VA, Sponsored Sea Ice Electromagnetics Accelerated Research Initiative (ARI)

Rethinking the relationship between the observed, simulated and real Arctic sea-ice evolution

In this dissertation, I explore the large differences in Arctic sea-ice evolution between climate models and observations, and among individual climate models. First, I investigate the drivers of the long-term Arctic Ocean warming in a multi-model ensemble. I find that there is no consensus between the models about whether the excess energy is gained by the ocean through the net atmospheric surface flux or through the meridional oceanic heat flux. However, all models agree on the magnitude of the projected warming. The warming is small compared to the anomalies in the energy fluxes. This is because most of the energy gained through one energy flux is lost through the other energy flux due to a relationship between the magnitude of the increase in oceanic heat inflow and the increase in turbulent heat loss to the atmosphere. Second, I explore the feasibility of an observation operator for the Arctic Ocean. An observation operator translates the Arctic Ocean climate simulated by a climate model into a brightness temperature. The brightness temperature is the quantity directly measured by satellites from space. Hence, an observation operator enables us to circumvent the observational uncertainty currently inhibiting reliable climate model evaluation. Sea-ice brightness temperatures at 6.9 GHz are driven by the liquid water fraction profile inside the ice and snow, which is not resolved in most climate models. I show that in winter this profile can be described reasonably well by a linear temperature profile and a salinity profile prescribed as a self-similar function of depth. In summer, the melt-pond fraction is more important for the simulation of the brightness temperature than the internal structure of the ice. Third, I develop an Arctic Ocean Observation Operator for 6.9 GHz based on these findings. I compare brightness temperatures simulated from the output of an Earth System Model to brightness temperatures measured by satellites. The differences between simulated and measured brightness temperatures can mainly be explained by the uncertainty in the simulated state of the sea-ice concentration, the assimilation process, and the melt-pond parametrization. Differences attributable to biases in the observation operator itself are small. The operator is therefore a suitable method for climate model evaluation. In summary, I show different perspectives on the large differences in Arctic sea-ice evolution. On the one hand, I point out that the multi-model ensemble mean is not always representative for the simulated Arctic climate and should be interpreted with care. On the other hand, I introduce and develop an unconventional tool providing new opportunities for future climate model evaluation

Variability of Sea Ice Extent Along The East Coast of Greenland

There has been a decrease in sea ice extent and volume in the polar regions during the past decades; this study focuses on the Northern Hemisphere. The variability of the sea ice extent along the east coast of Greenland is examined and the area is divided into three regional zones to be able to study variations in the correlation strength along the coast. The ice extent along the east coast is achieved from highly accurate, manually produced ice charts from the Danish Meteorology Institute (DMI). The data of the ice extent along the east coast of Greenland is compared to SSM/I data of the ice extent of the entire Northern Hemisphere, achieved from passive microwave sensors for the years 2005-2012. The annual maximum and minimum sea ice extent of the different regions are compared. It was expected to see a negative correlation between the extent in the Northern Hemisphere and along the east coast of Greenland but the results showed a clear non correlation, with slightly higher R-squared values for the annual minimum period than for the maximum. The ice extent is mainly dominated by the ice drift, which in turn is controlled by the wind which follows the isobars of the surface pressure systems. It is therefore expected that the sea ice extent along the east coast of Greenland is highly correlated to the pressure difference across the Fram Strait. In this study a linear dependence between the sea ice extent along the east coast of Greenland and the pressure difference across the Fram Strait is sought for the years 2000-2012. The pressure difference is achieved using a new method; by taking the pressure difference between two weather stations on either side of the Fram Strait it is possible to get an approximate strength and direction of the wind in the middle of the strait, and thereby on the dominating force of direction of the ice. The results of the comparisons between the ice extent along the east coast of Greenland and the pressure difference show a correlation, especially for the annual minimum extent with R-squared values around 0,3. It is concluded that the variability of the sea ice extent is not solely predicted by the pressure difference, and that more parameters must be accounted for such as the surface air temperature