Abstract
Abstract. The influence of climate on landform evolution has attracted great interest over the past decades. While many studies aim at determining erosion rates or parameters of erosion models, feedbacks between tectonics, climate, and landform evolution have been discussed but addressed quantitatively only in a few modeling studies. One of the problems in this field is that coupling a large-scale landform evolution model with a regional climate model would dramatically increase the theoretical and numerical complexity. Only a few simple models have been made available so far that allow efficient numerical coupling between topography-controlled precipitation and erosion. This paper fills this gap by introducing a quite simple approach involving two vertically integrated moisture components (vapor and cloud water). The interaction between the two components is linear and depends on altitude. This model structure is in principle the simplest approach that is able to predict both orographic precipitation at small scales and a large-scale decrease in precipitation over continental areas without introducing additional assumptions. Even in combination with transversal dispersion and elevation-dependent evapotranspiration, the model is of linear time complexity and increases the computing effort of efficient large-scale landform evolution models only moderately. Simple numerical experiments applying such a coupled landform evolution model show the strong impact of spatial precipitation gradients on mountain range geometry including steepness and peak elevation, position of the principal drainage divide, and drainage network properties.
Highlights
Feedbacks between topography, precipitation, and erosion may even make it difficult to distinguish between cause and effect (Molnar and England, 1990)
This study presents a new model for orographic precipitation for use in large-scale landform evolution models such as the stream-power incision model (SPIM) or the shared stream-power model
The linear feedback precipitation model (LFPM) developed in this study describes two moisture components, which are interpreted as vapor and cloud water
Summary
The redistribution of moisture from the oceans towards continental domains governs the global erosion engine. As the only nonlocal component of the model, a Gaussian smoothing in the upwind direction was used in order to reduce effects of surface roughness Due to these properties, the model is able to reproduce increased precipitation at the windward side compared to the leeward side of a mountain belt, but it fails to describe the large-scale shadow in a plane behind the mountain range or the decrease in precipitation with increasing distance to the ocean. The model proposed by Smith and Barstad (2004) defines two components, interpreted as cloud water and hydrometeors This model focuses on condensation and fallout at small scales, while it cannot predict transport over long distances Using a quite ingenious approach for describing deviations from equilibrium, it is able to capture the increase in precipitation with elevation as well the slow decrease in precipitation with increasing distance from the ocean It requires an artificial smoothing at small scales, to the model of Roe et al (2003). The linear time complexity (i.e., that the computing effort increases only linearly with the grid size) achieved by contemporary fluvial landform evolution models (Hergarten and Neugebauer, 2001; Braun and Willett, 2013; Yuan et al, 2019; Hergarten, 2020) should be preserved
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