1 Spatial Modelling of the Terrestrial Environment - Georeferencial

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Modelling Ice Sheet Dynamics by Satellite-Derived Topography 31 Another use for high-resolution topography is as an input dataset for modelling the surface mass balance of an ice mass. As mentioned earlier, this is often undertaken using a positive degree day model, with the temperature parameterized as a function of position and elevation, with the latter being the most sensitive parameter due to the effect of the adiabatic lapse rate (the change in temperature as a function of altitude through the atmosphere). Improvements in both the spatial resolution and vertical accuracy of DEMs of the GrIS have had a substantial impact on estimates of mass loss by ablation. In a comparison of the use of two DEMs (an older one derived chiefly from terrestrial measurements and one derived from SRA data), a difference of 20% in ablation was obtained (van de Wal and Ekholm, 1996). In another study resolution was found to influence ablation due to the smoothing effect on valleys where greater ablation takes place due to their lower elevation (Reeh and Starzer, 1996). Although the mean elevation may be the same, due to the binary behaviour of the positive degree day model (melting can only take place if the temperature is above 0 ◦ C), the amount of melt calculated may not be. Thus the desirable DEM resolution must be sufficient to resolve glaciated valleys, typically of about 5–10 km in width. A comparison between a 2.5 km DEM and a more recent 1 km DEM of Greenland indicated that there was no difference in ablation estimated using these two models which suggests that resolution-induced errors in estimating ablation are no longer important for the GrIS at least (Bamber et al., 2001). Vertical accuracy in some marginal areas may still be, however. 2.5 Conclusion Two quite different but complementary approaches to obtaining accurate topography over the large, homogeneous expanses of the Antarctic and Greenland ice sheets have been presented. Some examples of the datasets generated by the two methods and the application of these data to problems in spatial modelling of the ice sheets have been discussed. Accurate topography has been shown to be valuable both directly and indirectly for validating and calibrating several types of numerical ice sheet models. In particular, DEMs have been used to constrain thermo-mechanical models and test the reliability of the ice motion they predict. This latter application resulted from using the DEM directly in a simple finite-difference model, which traced and integrated the ice flux down a flow line to produce, with the benefit of surface accumulation data, an independent, global estimate of the velocity field. Ice sheet scale DEMs have also been used as the key input dataset for modelling the surface mass balance of the Greenland ice sheet, which is crucial for accurately determining its net mass balance and hence its contribution to sea level rise. Limitations still exist in the current generation of satellite-derived DEMs, however. This is particularly true for the Antarctic ice sheet where there are still no accurate data for the central region south of 81.5 ◦ (the latitudinal limit of ERS-1 and -2); one-fifth of the ice sheet is still relatively poorly mapped. There are also areas around the coast of Greenland and along the TransAntarctic mountains where there is sparse radar altimeter and/or InSAR coverage. In January 2003, the first of a series of satellite missions with the primary objective of studying the cryosphere was launched. ICESat is a NASA-funded satellite that carries a dual-frequency laser. The inclination of the orbit, combined with the pointing capability of the laser, should provide valuable data over those parts of Antarctica and Greenland not reached by the current suite of sensors. Further into the future, the European
32 Spatial Modelling of the Terrestrial Environment Space Agency plans to launch CRYOSat. This will be an ‘imaging’ radar altimeter system that will, like ICESat, provide valuable data for the marginal steeper sloping areas of the ice sheets but also for smaller ice masses such as the ice caps of the Russian and Eurasian Arctic. High accuracy and high spatial resolution topography over glacierized terrain looks set to continue to provide valuable information on the form and flow of land ice on the surface of the Earth. References Azuma, N., 1994, A flow law for anisotropic ice and its application to ice sheets, Earth and Planetary Science Letters, 128, 601. Bamber, J.L., 1994a, A digital elevation model of the Antarctic ice sheet derived from ERS-1 altimeter data and comparison with terrestrial measurements, Annals of Glaciology, 20, 48–54. Bamber, J.L., 1994b, Ice sheet altimeter processing scheme, International Journal of Remote Sensing, 14, 925–938. Bamber, J.L. and Bentley, C.R., 1994, A comparison of satellite altimetry and ice thickness measurements of the Ross ice shelf, Antarctica, Annals of Glaciology, 20, 357–364. Bamber, J.L. and Bindschadler, R.A., 1997, An improved elevation data set for climate and ice sheet modelling: validation with satellite imagery, Annals of Glaciology, 25, 439–444. Bamber, J.L., Ekholm, S. and Krabill, W.B., 2001, A new, high-resolution digital elevation model of Greenland fully validated with airborne laser altimeter data, Journal of Geophysical Research, 106, 6733–6745. Bamber, J.L., Hardy, R.J., Huybrechts, P. and Joughin, I., 2000a, A comparison of balance velocities, measured velocities and thermomechanically modelled velocities for the Greenland ice sheet, Annals of Glaciology, 30, 211–216. Bamber, J.L., Hardy, R.J. and Joughin, I., 2000b, An analysis of balance velocities over the Greenland ice sheet and comparison with synthetic aperture radar interferometry, Journal of Glaciology, 46, 67–74. Bamber, J.L. and Huybrechts, P., 1996, Geometric boundary conditions for modelling the velocity field of the Antarctic ice sheet, Annals of Glaciology, 23, 364–373. Bamber, J.L., Vaughan, D.G. and Joughin, I., 2000c, Widespread complex flow in the interior of the Antarctic ice sheet, Science, 287, 1248–1250. Braithwaite, R.J., 1995, Positive degree-day factors for ablation on the Greenland ice-sheet studied by energy-balance modeling, Journal of Glaciology, 41, 153–160. Brenner, A.C., Bindschadler, R.A., Thomas, R.H. and Zwally, H.J., 1983, Slope-induced errors in radar altimetry over continental ice sheets, Journal of Geophysical Research, 88, 1617– 1623. Budd, W.F. and Warner, R.C., 1996, A computer scheme for rapid calculations of balance-flux distributions, Annals of Glaciology, 23, 21–27. Ekholm, S., 1996, A full coverage, high-resolution, topographic model of Greenland computed from a variety of digital elevation data, Journal of Geophysical Research-Solid Earth, 101, 21961–21972. Engelhardt, H. and Kamb, B., 1998, Basal sliding of Ice Stream B, West Antarctica, Journal of Glaciology, 44, 223–230. Fabre, A., Ritz, C. and Ramstein, G., 1997, Modelling of last glacial maximum ice sheets using different accumulation parameterizations, Annals of Glaciology, 24, 223–228. Gladstone, R.M., Bigg, G.R. and Nicholls, K.W., 2001, Iceberg trajectory modeling and meltwater injection in the Southern Ocean, Journal of Geophysical Research, 106, 19,903–19,916. Hardy, R.J., Bamber, J.L. and Orford, S., 2000, The delineation of major drainage basins on the Greenland ice sheet using a combined numerical modelling and GIS approach, Hydrological Processes, 14, 1931–1941. Houghton, J.T., Filho, L.G.M., Callander, B.A., Harris, N., Kattenberg, A. and Maskell, K., 1996, Climate Change 1995: The Science of Climate Change (Cambridge: Cambridge University Press).
Page 2 and 3: Spatial Modelling of the Terrestria
Page 4 and 5: Copyright C○ 2004 John Wiley & So
Page 6 and 7: Contents List of Contributors Prefa
Page 8 and 9: Contributors Jonathan L. Bamber Sch
Page 10 and 11: List of Contributors xi George Perr
Page 12 and 13: xiv Preface in theory and applicati
Page 14 and 15: 2 Spatial Modelling of the Terrestr
Page 20 and 21: Editorial: Spatial Modelling in Hyd
Page 22 and 23: Editorial: Spatial Modelling in Hyd
Page 24 and 25: 2 Modelling Ice Sheet Dynamics with
Page 26 and 27: Modelling Ice Sheet Dynamics by Sat
Page 46 and 47: 36 Spatial Modelling of the Terrest
Page 68 and 69: 4 Using Coupled Land Surface and Mi
Page 70 and 71: Coupled Land Surface and Microwave
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84 Spatial Modelling of the Terrest
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100 Spatial Modelling of the Terres
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Editorial: Terrestrial Sediment and
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Editorial: Terrestrial Sediment and
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6 Remotely Sensed Topographic Data
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Remotely Sensed Topographic Data fo
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7 Modelling Wind Erosion and Dust E
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Modelling Wind Erosion and Dust Emi
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8 Near Real-Time Modelling of Regio
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Near Real-Time Modelling of Regiona
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High Low TSM Concentration Figure 8
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9 Estimation of Energy Emissions, F
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Fireline Intensity and Biomass Cons
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Figure 9.4 The upper row shows EOS
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PART III SPATIAL MODELLING OF URBAN
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11 Modelling the Impact of Traffic
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Modelling the Impact of Traffic Emi
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PART IV CURRENT CHALLENGES AND FUTU
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268 Index Bi-spectral InfraRed Dete
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270 Index floodplain maps, UK 92 fl
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272 Index Long-Term Ecological Rese
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274 Index snow depth measurement ne
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276 Index urban land use in remotel
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1 Spatial Modelling of the Terrestrial Environment - Georeferencial

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