We present evidence that land use practices in the plains of Colorado influence regional climate and vegetation in adjacent natural areas in the Rocky Mountains in predictable ways. Mesoscale climate model simulations using the Colorado State University Regional Atmospheric Modelling System (RAMS) projected that modifications to natural vegetation in the plains, primarily due to agriculture and...

Attaining accurate precipitation data is critical to understanding land surface processes and global climate change. The development of satellite sensors and remote sensing technology has resulted in multi-source precipitation datasets that provide reliable estimates of precipitation over un-gauged areas. However, gaps exist over high latitude areas due to the limited spatial extent of several ...

Climate change due to anthropogenic greenhouse gas emissions is expected to increase the frequency and intensity of precipitation events, which is likely to affect the probability of flooding into the future. In this paper we use river flow simulations from nine global hydrology and land surface models to explore uncertainties in the potential impacts of climate change on flood hazard at global...

Anthropogenic forcings have contributed to global and regional warming in the last few decades and likely affected terrestrial precipitation. Here we examine changes in major Köppen climate classes from gridded observed data and their uncertainties due to internal climate variability using control simulations from Coupled Model Intercomparison Project 5 (CMIP5). About 5.7% of the global total l...

The ‘rain use efficiency’ (RUE) may be defined as the ratio of above-ground net primary productivity (ANPP) to annual precipitation, and it is claimed to be a conservative property of the vegetation cover in drylands, if the vegetation cover is not subject to non-precipitation related land degradation. Consequently, RUE may be regarded as means of normalizing ANPP for the impact of annual preci...

The ‘rain use efficiency’ (RUE) may be defined as the ratio of above-ground net primary productivity (ANPP) to annual precipitation, and it is claimed to be a conservative property of the vegetation cover in drylands, if the vegetation cover is not subject to non-precipitation related land degradation. Consequently, RUE may be regarded as means of normalizing ANPP for the impact of annual preci...

A biased coinflip Ansatz provides a stochastic regional scale land surface climate model of minimum complexity, which represents physical and stochastic properties of an ideal rainfall–runoff chain. The solution yields the empirically derived Schreiber formula as an Arrhenius-type equation of state W = exp(-D). It is associated with two thresholds and combines river runoff Ro, precipitation P a...

This study reports the first assessment of the compounding effects of land-use change and greenhouse gas warming effects on our understanding of projections of future climate. An AGCM simulation of the potential impacts of tropical deforestation and greenhouse warming on climate, employing a version of NCAR Community Climate Model (CCM1-Oz), is presented. The joint impacts of tropical deforesta...

NARCliM (New South Wales and Australian Capital Territory Regional Climate Modelling project) is a climate downscaling project for Australia and the surrounding regions. Present and future climate simulations are performed using a 1-way nested dynamical down scaling approach and span 2 domains. We focus on the inner 10 km domain that extends across south-east Australia. Three regional climate m...

The Community Land Model (CLM3) Dynamic Global Vegetation Model (CLMDGVM) is used diagnostically to identify land and atmospheric model biases that lead to biases in the simulated vegetation. The CLM-DGVM driven with observed atmospheric data (offline simulation) underestimates global forest cover, overestimates grasslands, and underestimates global net primary production. These results are con...