Posts Tagged «Remote Sensing»

This investigation’s major goal is to develop and use models constrained by satellite and ground observations to study the controls on fast ice stream flow.

Deeply embayed ice shelves and narrower fringing ice shelves surround much of Antarctica. Recent results indicate that these ice shelves help regulate the flow of upstream glaciers and ice streams (“ice-shelf buttressing”). This investigation focuses on determining the mass balance of Antarctica’s non-Peninsula ice shelves and on improving our knowledge of the processes that control basal melt.

The primary objective of this research is to construct a comprehensive bias-corrected sea ice thickness record and use it to better quantify and understand the dramatic changes that have been observed in the Arctic ice pack. To do this all available Arctic sea ice thickness observations will be integrated, from satellite, aircraft, and subsurface measurements, and used to identify and correct systematic errors through comparisons with a common reference. With the resultant record four science questions will be answered:• What are the systematic differences between different measurement systems for sea ice thickness?• What are the spatial patterns in the trends…

Seasonal Anomaly Maps — each product compred to the ensemble medianSeasonal Trend Maps — seasonal trends of each variableThis work has been published in the Journal of Climate (Lindsay, R., M. Wensnahan, A. Schweiger, and J. Zhang, 2014: Evaluation of seven different atmospheric reanalysis products in the Arctic. J. Climate, DOI: 10.1175/JCLI-D-13-00014.1. )AbstractAtmospheric reanalyses depend on a mix of observations and model forecasts. In data-sparse regions such as the Arctic, the reanalysis solution is more dependent on the model structure, assumptions, and data assimilation methods than in data-rich regions. Applications such as the forcing of ice-ocean models are sensitive to…

Numerous recent studies have revealed rapid change in ice discharge from Greenland’s outlet glaciers. A near doubling in flow speed of many of Greenland’s glaciers substantially increased the rate at which the ice sheet calved icebergs to the ocean over the last five years.

Huck, P., B. Light, H. Eicken, and M. Haller, “Mapping sediment-laden sea ice in the Arctic using AVHRR remote-sensing data: Atmospheric correction and determination of reflectances as a function of ice type and sediment load“, Remote Sensing of Environment, 107, 484-495, 2007.

IceBridge is a NASA project that supports the acquisition of various data from aircraft in both polar regions that will bridge the gap in coverage between the now defunct ICESat satellite and the next generation ICESat II to be launched in 2015 at the earliest. The main focuses of the data acquisition will be laser altimetry and radar measurements of ice sheets (Greenland and Antarctica) and sea ice (Arctic and Antarctica).

Joughin, I., J. L. Bamber, T. Scambos, S. Tulaczyk, M. Fahnestock, and D. R. MacAyeal,’ Integrating satellite observations with modeling: basal shear stress of the Filcher-Ronne ice streams’, Antarctica, Phil. Trans. Roy. Soc., A 364, 1795-1814, 2006.

Joughin, I., S. Tulaczyk, J.L. Bamber, D. Blankenship, J.W. Holt, T. Scambos, and D.G. Vaughan,’ Basal conditions for Pine Island and Thwaites glaciers, West Antarctica, determined using satellite and airborne data’, J. Glaciol., 55, 245-257, 2009.

Kwok, R., and D.A. Rothrock,’ Decline in Arctic sea ice thickness from submarine and ICESat records: 1958-2008′, Geophys. Res. Lett., 36, doi:10.1029/2009GL039035, 2009.

Kwok, R., S. Farrell, R. Forsberg, K. Giles, S. Laxon, D. McAdoo, J. Morison, L. Padman, C. Peralta-Ferriz, A. Proshutinsky, and M. Steele,’ Combining satellite altimetry, time-variable gravity, and bottom pressure observations to understand the Arctic Ocean: A transformative opportunity’, Proceedings of the OceanObs09: Sustained Ocean Observations and Information for Society Conference, Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. and Stammer, D., Eds., 2, ESA Publication WPP-30, 2010.

Larour, E., Rignot, E., Joughin, I. & Aubry, D.,’ Rheology of the Ronne Ice Shelf, Antarctica, inferred from satellite radar interferometry data using an inverse control method’, Geophysical Research Letters, 32, 2005.

Liu, Z., Schweiger, A. (2017), Synoptic conditions, clouds, and sea ice melt-onset in the Beaufort and Chukchi Seasonal Ice Zone, J. Climate, doi: 10.1175/JCLI-D-16-0887.1 .

Morison, J., J. Wahr, R. Kwok, and C. Peralta-Ferriz,’ Recent trends in Arctic Ocean mass distribution revealed by GRACE’, Geophys. Res. Lett., 34, L07602, doi:10.1029/2006GL029016, 2007.

Peralta-Ferriz, C. and J. Morison, “Understanding the annual cycle of the Arctic Ocean bottom pressure”, Geophys. Res. Lett., 37, L10603, doi:10.1029/2010GL042827, 2010.

Three PSC investigators were recently awarded funds to support their participation in NASA’s IceBridge mission. They include Ron Lindsay, Ian Joughin and Ben Smith. IceBridge is conducting the most extensive set of airborne surveys of the polar ice caps and sea ice ever undertaken.

Schweiger, A. J., R. W. Lindsay, J. A. Francis, J. Key, J. M. Intrieri, and M. D. Shupe, “Validation of TOVS Path-P data during SHEBA“, J. Geophys. Res.,C., 107(10), SHE 17-11 – 17-20, 2002.

Smith, B.E., Fricker, H.A., Joughin, I.R.., and S. Tulaczyk, ‘An inventory of active subglacial lakes in Antarctica detected by ICESat (2003-2008)’, J. Glaciology, 55(192), 573-595, 2009.

We are employing new remote sensing methods applied to multiple satellite data sets to measure the total discharge of ice from the grounded Antarctic Ice Sheet. This effort also will provide the most comprehensive mapping ever of the grounding line position, as well as ice thickness and velocity along and in the vicinity of the grounding line. These products are sensitive indicators of changes and will serve as benchmark data sets of the International Polar Year suitable for subsequent comparisons to identify and quantify future changes in the ice sheet.

The purpose of this project is to improve satellite retrievals of atmospheric temperature, humidity and clouds.  Retrievals are based on   the physical-statistical retrieval method of Chedin et al. (1985, Improved Iteration Inversion Algorithm, 3I). The method has been improved for use in sea ice-covered areas (Francis 1994) and the data set has been designed to address the particular needs of the Polar research community. The data set represents the so called Path-P as designated by the TOVS Science Working Group.

Winebrenner, D.P., E.J. Steig and D.P. Schneider,’ Temporal co-variation of surface and microwave brightness temperatures in Antarctica, with implications for the observation of surface-temperature variability using satellite data’, Ann. Glaciology, Vol. 39, 2004.