Andrew W. Bingham

Greenland snow accumulation estimates from satellite radar scatterometer data

Data collected by the C band ERS-2 wind scatterometer (EScat), the Ku band ADEOS-1 NASA scatterometer (NSCAT), and the Ku band SeaWinds on QuikScat (QSCAT) satellite instruments are used to illustrate spatiotemporal variability in snow accumulation on the Greenland ice sheet. Microwave radar backscatter images of Greenland are derived using the scatterometer image reconstruction (SIR) method at 3-day intervals over the periods 1991–1998 and 1996–1997 for EScat and NSCAT, respectively. The backscatter coefficient σ° normalized to 40° incidence, A, and gradient in backscatter, B, in the range 20°–60° are compared with historical snow accumulation data and recent measurements made in the Program for Arctic Regional Climate Assessment (PARCA) shallow snow pits. Empirical relationships derived from these comparisons reveal different exponential relationships between C and Ku band A values and dry snow zone mean annual accumulation, Q. Frequency difference images between overlapping scatterometer images suggest that C band data are more sensitive to snow layering and buried inhomogeneities, whereas Ku band data are more sensitive to volume scattering from recently accumulated snow. Direct comparisons between NSCAT B values and in situ Q measurements show a linear relationship between ln (Q) and B, with a negative rank correlation of R = −0.8. The root-mean-square residual in fitting regression line equation ln (Q) = 3.08 − 17.83B to the data is 0.05-m snow water equivalent. This simple Ku band empirical relationship is exploited to investigate decadal changes in dry snow zone accumulation between Seasat (1978) and NSCAT (1996). Additional comparisons between NSCAT and recent QSCAT (1999) data reveal significant upslope shifts in the dry snow line along the southwestern flank of the ice sheet. Recent acceleration in the increase in intensity of scattering is observed in the percolation zone, suggesting increased melting between 2000- and 3000-m elevation in the southern half of the ice sheet.

Recent changes in the microwave scattering properties of the Antarctic ice sheet

Time series, satellite microwave data are used to monitor and quantify changes in the scattering properties of the Antarctic ice sheet. Daily ERS scatterometer (EScat) and Special Sensor Microwave/Imager (SSM/I) image data, acquired since 1992, are analyzed to understand the seasonal and interannual changes over the ice sheet. For regions of the ice sheet where azimuthal modulation is negligible, seasonal cycles are observed in both the EScat (amplitude /spl sim/0.5 dB) and SSM/I data (amplitude /spl sim/10 K). These cycles are attributed to seasonal changes in surface temperature. Interannual variability in the time series signatures appears to be associated with accumulation. There is also evidence to suggest that shifts in the wind direction can alter the backscatter through azimuthal modulation. Over the period 1992-97, large trends are observed in the EScat( 1 K yr/sup -1/) signatures over several regions in Antarctica. These changes typically occur over ice shelves and at the margins of the ice sheet where previous melt events have occurred, and where accumulation is relatively high (>300 mm yr/sup -1/). It is likely the large changes result from the successive burial of an efficient scattering layer formed by refreezing after a melt event prior to 1992. There is also evidence to suggest that similarly large changes can be observed in the interior of the ice sheet due to the burial of depth hear layers. In order to monitor long term change in the properties of the Antarctic ice sheet, it is necessary to remove the seasonal cycle from time series microwave data. Such anomaly data can then be used to understand the link between EScat and SSM/I with accumulation and wind shifts.

Earth Science Datacasting: Informed Pull and Information Integration

The intent of Datacasting is to empower consumers of Earth science data with the ability to extract from a stream of data granules (or files) precisely those granules that are required to meet a predefined need, for example, ldquoAcquire from a MODIS L2 data stream only the granules that contain information about a wild fire in Southern California.rdquo Our approach to solving this problem has been to take the concept of Really Simple Syndication (RSS) feeds, for delivering regularly changing web content, and extend this to represent a stream of data granules and deliver regularly changing Earth science data content. In essence, this project is doing for Earth science what Podcasting has done for audio and video. Where Podcasting extended RSS to revolutionize how users access audio and video content provided by various media outlets, so Datacasting extends RSS to provide users with the ability to download data granules provided by Earth science data providers as the data are made available. Moreover, we have taken the concept one step further by creating a solution for filtering on the metadata of a feed in order to identify granules of interest based on user-defined criteria. In this paper, we also show how Datacasting feeds can be combined with other RSS-based feeds to identify relationships between information sources and extract new knowledge, as well as aid the development of new geo-based web services not currently envisaged.

Ocean surface topography data products and tools

The Physical Oceanography Distributed Active Archiving Center (PO.DAAC), NASAs primary data center for archiving and distributing oceanographic data, is supporting the Jason and TOPEX/Poseidon satellite tandem missions by providing a variety of data products, tools, and distribution methods to the wider scientific and general community. PO.DAAC has developed several new data products for sea level residual measurements, providing a long-term climate data record from 1992 to the present. These products provide compatible measurements of sea level residuals for the entire time series including the tandem TOPEX/Poseidon and Jason mission. Several data distribution tools are available from NASA PO.DAAC. The Near-Real-Time Image Distribution Server (NEREIDS) provides quick-look browse images and binary data files. The PO.DAAC Ocean ESIP Tool (POET) provides interactive, on-line data subsetting and visualization for several altimetry data products.

Building climatological services on the cloud

The NASA Physical Oceanographic Distributed Active Archive Center (PO.DAAC) at Jet Propulsion Laboratory is funded by the NASA Earth Science Data and Information System (ESDIS) project to conduct a study of cloud services for data management, data access and data processing. The study is to improve our understanding and articulate the cost/benefit of cloud technologies for the NASA Distributed Active Archive Centers (DAACs) and Science Investigator-led Production Systems (SIPs). This demonstration focuses on our experience in developing climatology services using Apache Hadoop to store and analyze temporal and spatial characteristics of scatter-ometer data over Antarctica.

Seasonal and interannual trends in Antarctic ice sheet microwave data

Time-series microwave satellite observations are used to investigate seasonal and interannual changes in the surface characteristics of the Antarctic ice sheet. Enhanced-resolution C-band ERS-1/2 scatterometer (ESCAT) backscatter and DMSP SSMI brightness temperature images of Antarctica, acquired on a 3-day interval between 1992 and 1997, have been analysed. Both ESCAT and SSMI data show a clear seasonal cycle over all areas of the ice sheet. Using multi-layered radiative transfer models the authors demonstrate these cycles result primarily from thermal forcing. They also note significant interannual trends in both data sets. At the margins of the ice sheet, where melting is known to have occurred, backscatter and brightness temperature trends are typically less than -0.25 dB/year and greater than +1 K/year, respectively. It is likely these trends are linked to accumulation of new snow and successive burial of scatterers (formed during the last significant summer melt period). In the interior of the ice sheet, where no melting occurs, there is generally no significant trend in the backscatter and a slight negative trend in the brightness temperatures. However, there are large spatial variations which the authors believe is caused by the presence of depth hoar layers or higher accumulation rates.