The past decade has seen a rapid increase in the application of high-resolution imagery and geographic-based information systems across every segment of society from security intelligence to product marketing to scientific research. Google Earth has positioned itself at the forefront of this spatial information wave by providing free access to high-resolution imagery through a simple, user-friendly interface. Whereas Google Earth imagery has been widely exploited across the earth sciences for spatial visualization, education, and place-based searches, few studies have utilized the high-resolution imagery to yield quantitative insights about the processes and mechanisms acting at the earth's surface. In this paper, we detail the benefits of the underlying high-resolution imagery available within Google Earth, review the limited published research to date, and utilize this imagery to quantitatively illuminate previously difficult and unresolved questions within the discipline of geomorphology involving: (1) channel-width variability and scaling relations in the tectonically active Himalaya; (2) landslide characteristics related to large magnitude climatic and tectonic events in Haiti; and (3) identification and quantification of laterally offset geomorphic features within eastern California. In each example, we compare analyses using freely available Google Earth imagery with standard imagery and techniques (e.g., Landsat, ASTER, lidar) to demonstrate the potential benefits of using high-spatial resolution Google Earth imagery over established methodologies. In addition, we discuss the potential limitations and problems with using the imagery currently available in Google Earth and propose favorable future applications, namely studies in remote terrains and those requiring high-resolution imagery across a large spatial extent, where purchasing such imagery in an academic environment would be cost-prohibitive. Whether as a supplement, for reconnaissance, or as the primary data set, high-resolution Google Earth imagery, when properly applied, holds great promise for quantitatively tackling previously unresolved problems in the study of earth surface processes.

The extent to which orography may be a product of climate-erosion interactions is largely unknown. One grand challenge is to quantify the precipitation regimes of mountainous regions at the spatial and temporal scales relevant for investigating the interplay of erosion and tectonics in active orogens. In this paper, our objective is to synthesize recent research integrating numerical model simulations, satellite data, and surface observations in the Himalaya to elucidate the role of weather and climate in mountain evolution. We focus on the seasonal and interannual space-time variability of precipitation in the Great Himalayas by studying two preeminent storm regimes in detail—monsoon onsets and depressions in general, and wintertime Western Disturbances (cold season events). High-resolution simulations of heavy precipitation storms for two monsoon onset conditions (1999 and 2001) and one wintertime storm (2000) are used to illustrate the complex patterns of interaction between the mountains and the atmosphere, and to show how these affect the spatial distribution of precipitation. Along with observations from an existing ground-based network, these simulations provide unique insights into the space-time features of seasonal and inter-annual variability of precipitation. Our analysis indicates that the trajectory of monsoon storms during onset events exerts a strong control on the precipitation amounts and rainfall penetration into the rain shadow. Spatial variability of subsequent storm tracks in any given year helps explain the interannual variability of monsoon precipitation. Both observational data and our simulations define striking spatial variability in precipitation on upwind and downwind fianks of ridges that project into obliquely impinging storms. Specifically, as southeasterly monsoon winds encounter north-south oriented ridges, forced lifting of moist air enhances precipitation on the upwind fianks, whereas less precipitation occurs on downwind fianks. This variability is observed at spatial scales as short as ∼10 km—a distance equivalent to the spacing of major ridge crests. Because infrequent, singular storm events appear to control the mass input to glaciers, and may determine the frequency and spatial distribution of landslides, these findings provide physically based insight into decoupling high-frequency (seasonal to interannual time scales) from low-frequency (multidecadal to centennial and longer time scales) signals in the interpretation of climate and erosion records in the Himalayas. Furthermore, this research suggests that integrative studies aimed at unraveling the role of climate in landscape evolution must include consideration of storm frequency and intensity along with spatial variability at scales consistent with regional climate forcing.