The data include the annual total precipitation from 1985 to 1999 and monthly total precipitation from January 1985 to December 1999. The data is derived from a dynamic model using the omega equation which describes vertical atmospheric motion. The data are arrayed in a 67 x 69 grid with a grid length of 50 km.

Two versions of the data are available in separate directories (ver1 and ver2). Data are in ASCII files named yy.sum for annual total precipitation (mm), yymm.sum for monthly total precipitation (mm), and yy1-yy2.mean for annual mean precipitation from yy1 to yy2. Latitude and longitude data for the grid points and topological data are also available. See the readme file or the reference below for more details.

Bromwich, D. H., Q.-S. Chen, L.-S. Bai, E. N. Cassano, and Y. Li, 2001. Modeled precipitation variability over the Greenland Ice Sheet, J. Geophys. Res., 106, 33,891-33,908.

The Greenland Climate Network (GC-NET) currently consists of 18 stations with a distributed coverage over the Greenland ice sheet. Four stations are located on top of the ice sheet (3000 m elevation range) along the north-south direction, ten stations are located along the 2000 m contour line, and four stations were positioned in the ablation region around 300 m elevation. GC-Net AWS are equipped with instruments to measure surface energy and mass balance. So far, the GC-NET archive contains 50+ station years of measurements. These data have been quality controlled and calibrated.

The Greenland Climate Network (GC-Net) was established in spring 1994 with the emphasis to monitor climatological and glaciological parameters at various locations on the ice sheet over a time period of at least 10 years. The objectives of the GC-Net automatic weather station (AWS) network are: (1) Assess daily, annual and interannual variability in accumulation rate, surface climatology and surface energy balance at selected locations on the ice sheet where high sensitivity of the ice sheet mass balance to climate anomalies is predicted from modeling results; (2) Assess accurate surface elevation, location, near-surface density at the AWS location with the option to revisit the locations in order to get temporal information for dynamic ice sheet modeling.

The statistics are based on 12 critical parameters such as: incoming shortwave radiation, reflected shortwave radiation, net radiation, temperature-humidity-wind profile at two levels, wind direction, pressure and surface height. The possible data point count for all AWS and channels is 5.04574 106, whereas 4.72291 106 data were retrieved, resulting in an overall success rate of 93.6%. Recent 6 days of hourly surface meteorological ASCII data and plots are updated hourly on the WWW at: http://cires.colorado.edu/steffen/aws/current_GC-Net_plots.html. The GC-Net sites that are using GOES and ARGOS satellite data links are operationally updating automatically as of September 16 1999.

Potential applications - AVHRR Polar Pathfinder surface albedo, comparison with satellite-derived elevation, ice-core chemical transfer models, comparison with NCAR MM5 GCM, Coastal versus inland climate comparison, blowing snow mass flux, evaporative mass flux, surface energy balance, logistic support for ice camps and Thule AB, operational weather forecast (ECMWF) parameters = Each AWS station measures 32 parameters, such as temperature, humidity, wind speed and wind directions at two levels, shortwave incoming and reflected radiation, net radiation, snow height, pressure, snow temperature profile from 0 to 10 m depth, GPS time and location. The data are sampled at 1 s and 60 s and averaged over an hour, and transmitted hourly via satellite link (ARGOS and GOES).

Mean normalised backscatter coefficient (sigma-naught); backscatter variance; and other associated data files from Seasat SASS (1978); ERS-1/2 (1991-2000); NSCAT (1996-1997); and QuickSCAT (1999-). Global, overlapping swath data are accumulated over a fixed interval of time and then gridded, binned and averaged, and also processed using the Scatterometer Image Reconstruction (SIR) algorithm developed at Brigham Young University.

When using these data please cite the Scatterometer Climate Record Pathfinder, and send several copies of any publications stemming from research undertaken in association with these data to Dr. Drinkwater.

The derived data are estimates of the accumulation rate (in kg/m²/year) on the Greenland ice sheet. The validity of the estimation method is limited to the dry snow zone. The data are derived from dual-polarized observations of microwave emission at 6.6 GHz made by the Scanning Microwave Multichannel Microwave Radiometer between 1979 and 1985 -- specifically, we have averaged brightness temperatures for each 25 km pixel on the SSM/I grid (as provided in the NASA Goddard Space Flight Center SMMR Polar Data collection on CD) over the entire period between the start of data collection in 1979 and the end of calendar year 1985, excluding only brief periods during some summers when brightness temperatures jumped anomalously by approximately 5K. (The latter events are likely to have been surface hoar formation events.)

We have added 6K to the resulting average vertically polarized brightness temperatures for the reason discussed by Winebrenner et al. (JGR 2001), formed a polarization ratio, and used a relationship between polarization and accumulation rate to derive this data set.

Scanning laser altimeters were flown over the Greenland icesheet during late spring or early summer in the years 1993- 1999. Flights spanned the entire icesheet, sampling interior and coastal regions and several outlet glaciers. The data provided here is condensed from the original scanning lidar measurements to roughly one measurement per 75m along the flight track, by fitting a plane to a set of points within a 70meter by 150meter subset. Each record in the resulting data set includes location, ellipsoid elevation, surface slope, and an RMS surface roughness. Flights from 1993 and 1994 were repeated in 1998 and 1999 to provide a measurement of the ice elevation change over a five- year period.

During 1993-1997 a line of stakes about 30-km apart was established completely around the ice sheet approximately along the 2000-m elevation contour except in the south west, where it was higher because of high mountains, nunataks, and crevasses [Thomas et al., 1998 and 2000]. Each station was precisely surveyed by GPS, with resurvey one or two years later, to yield estimates of ice velocity. Station locations were marked by aluminum poles approximately 2 meters long, inserted close to vertically into the snow surface to a depth of about 1 meter. A second and, in areas of very high accumulation, a third pole was added to the lower pole using connecting sections and hose clamps. At each station, a GPS receiver was set atop the lower pole, by attaching a short length of aluminum rod to the base of the receiver and inserting this into the marker pole. Most stations were installed and surveyed via Twin Otter aircraft, during brief (about 10-minute) stops for station installation, and GPS mounting etc. The GPS receivers were left to operate for a minimum of 40 minutes, and more commonly a few hours. Up to 10 stations were visited during a one-day flight from a nearby coastal station. The GPS data from each day were processed by a point-positioning analysis for the longest-occupied station, with differential solutions for the others relative to this. Errors on resulting horizontal locations were about +/- 2 cm for the longest-occupied station, increasing to about +/- 10 cm for the shortest occupancy, with vertical errors approximately double these values. Additional errors were introduced by tilting of the marker poles during the 1-2 year interim between surveys, increasing the uncertainty by perhaps 5 cm. Consequently, derived velocities are accurate to better than +/- 0.2 m/yr.

The main objective of the traverse measurements was to infer the mass balance of central parts of the ice sheet upslope from the traverse, and results from this work have been published in Thomas et al., [1998] and 2000, with comparisons of these results with those from repeat altimetry in Thomas et al. (2001). Ongoing projects using these data include:

• Collaboration with J. Bamber to increase the spatial resolution of our mass-balance estimates in order to identify causes for major imbalance in parts of southern Greenland.
• Use of the ice velocities to infer basal conditions along the traverse.

These data are available from our web site: http://www-bprc.mps.ohio-state.edu/ohglas/parca-traverse.htm. They were acquired with support from NASA's Polar Research Program, and users requesting the data are asked to provide a brief description of their application of the data. This will help provide NASA with an assessment of the scientific benefits resulting from their support of such efforts.

References:

Thomas, R., B. Csatho, S. Gogineni, K. Jezek, and K. Kuivinen. 1998. Thickening of the western part of the GreenlandIice Sheet. Journal of Glaciology 44: 653-658.

Thomas, R., T. Akins, B. Csatho, M. Fahnestock, P. Gogineni, C. Kim, and J. Sonntag. 2000. Mass balance of the Greenland Ice Sheet at high elevations. Science 289: 426-427.

Thomas, R., B. Csatho, C. Davis, C. Kim, W. Krabill, S. Manizade, J. McConnell and J. Sonntag. 2001. Mass balance of higher-elevation parts of the Greenland Ice Sheet. Journal of Geophysical Research - Atmospheres 106 (D24) (December): 33707-33716.

Ice-sheet mass balance can be inferred from comparison between total net accumulation and total ice discharge, and this data set contains results from such a comparison for higher-elevation parts of the Greenland ice sheet. During 1993-1997, velocities were measured at a line of stakes about 30-km apart completely around the ice sheet approximately along the 2000-m elevation contour except in the south west, where it was higher because of high mountains, nunataks, and crevasses [Thomas et al., 2000]. More information on these velocities can be found on our web site. Ice thickness was also measured along the traverse by a low-frequency ice-sounding radar [Gogineni et al., 1998]. Snow accumulation was from existing estimates [Ohmura and Reeh, 1991], supplemented by recent German and PARCA measurements and with estimates of total precipitation at weather stations for coastal accumulation rates. Each estimate refers to the time period over which measurements were made, ranging from years to centuries, but the overall set of results is heavily influenced by results from recent PARCA cores, most of which refer to the past two or three decades. Total snow accumulation within catchment areas corresponding to selected groups of stakes, expressed as a volume flux of ice, was compared to ice discharge between the stake locations. This was calculated as the product of ice thickness and velocity integrated between the stakes, after correcting for the ratio (R) between surface and column-averaged velocity, based on model simulations of the velocity/depth profile [Huybrechts, 1996]. Errors for small catchment areas are quite large because of uncertainties in local accumulation rates, the size of the catchment area, and R [Thomas et al., 1998]. For areas larger than about 100,000 sq km, the random nature of these errors reduces their overall effect to less than 7% of the snow-accumulation rate, and considerably less for the entire region under study [Thomas et al., 2000]. Snow-accumulation rates range from less than 0.1 m of water equivalent per year in the northeast to more than one meter per year in parts of the southeast, with an average value for the entire ice sheet of about 0.3 m/yr [Bales et al., this issue].

The data set presented here is in tabular form, with a listing for individual gates of: station locations forming the gates; velocities, ice thicknesses and R estimates at the gates; total upstream accumulation; and resulting estimates of average ice-thickening rates (dH/dt) for the catchment areas appropriate to the gates.

Because errors in dH/dt are large for single gates, additional Tables are provided giving:

1. Values for larger ice-sheet catchment areas (approximately 30,000 sq km) formed by including several adjacent gates.
2. Values for 12 larger gates (up to >100,000 sq km) that represent regions of the ice sheet with distinctive patterns of dH/dt. These estimates are compared to independent estimates from altimetry measurements in Thomas et al.

Errors in accumulation rates are the largest source of uncertainty in these mass-balance estimates, but they are progressively reduced as more information is acquired. The data presented here were compiled before all PARCA accumulation measurements had been analyzed, so they include different estimates of dH/dt based on accumulation estimates ranging from those in Ohmura and Reeh [1991] to our own attempts to improve these using then available PARCA data, and details of these can be found on our web site. Consequently, the dH/dt estimates provided here will be progressively improved as our estimates of snow accumulation also improve.

Ongoing work with these data include:

• Investigation of the regions that are significantly out of balance, in an attempt to identify causes for the imbalance.
• Progressive updating of the dH/dt estimates using improved accumulation estimates, flow lines based on better maps of ice-sheet topography, and better estimates of R. This will be continued into the GLAS mission, using accumulation estimates from atmospheric analyses, for comparison with GLAS measurements of surface-elevation change.

These data are available from our web site: http://www-bprc.mps.ohio-state.edu/ohglas/parca-traverse.htm. They were acquired with support from NASA's Polar Research Program, and users requesting the data are asked to provide a brief description of their application of the data. This will help provide NASA with an assessment of the scientific benefits resulting from their support of such efforts.

References

Bales, R. C., J. R. McConnell, E. Mosley-Thompson and B. Csatho. (In press). Accumulation map for the Greenland Ice Sheet: 1970-1990. Journal of Geophysical Research - Atmosphere.

Gogineni, S., D. Tammana, D. Braaten, C. Leuschen, T. Akins, J. Legarsky, P. Kanagaratnam, J. Stiles, C. Allen and K. Jezek. 2001. Coherent radar depth sounding of the Greenland Ice Sheet. Journal of Geophysical Research - Atmosphere 106 (D24) (December): 33761-33772.

Huybrechts, P. 1996. Basal temperature conditions of the Greenland Ice Sheet during the glacial cycles. Annals of Glaciology 23: 226-236.

Ohmura, A. and N. Reeh. 1991. New precipitation and accumulation maps for Greenland. Journal of Glaciology 37: 140-148.

Thomas, R., B. Csatho, S. Gogineni, K. Jezek, and K. Kuivinen. 1998. Thickening of the western part of the Greenland Ice Sheet. Journal of Glaciology 44: 653-658.

Thomas, R., T. Akins, B. Csatho, M. Fahnestock, P. Gogineni, C. Kim, and J. Sonntag. 2000. Mass balance of the Greenland Ice Sheet at high elevations. Science 289: 426-427.

Thomas, R., B. Csatho, C. Davis, C. Kim, W. Krabill, S. Manizade, J. McConnell and J. Sonntag. 2001. Mass balance of higher-elevation parts of the Greenland Ice Sheet. Journal of Geophysical Research - Atmosphere 106 (D24) (December): 33707-33716.

Ice velocity data of outlet glaciers in northern Greenland, gridded on a polar stereographic projection with a 70 deg. secant plane, and 150-m posting. Scene size is about 100 x 100 km. Each grid is the combination of interferometric pairs from the ERS-1/2 radar satellites acquired along both descending and ascending tracks. Processing assumes parallel surface flow. In some instances, a radar topography map of the glacier was generated using interferometry data to improve the precision of mapping.