SignificanceNorth American and European countries built many large dams until 1975, after which both started to abandon a significant part of their installed hydropower because of the negative social and environmental impacts. However, there has been a recent trend of new large hydropower dams being built in developing countries, particularly in megabiodiversity river basins, such as the Amazon, the Congo, and the Mekong. The socioeconomic and environmental damages in these river systems are even greater than the early costs in North America and Europe. This paper discusses how the hydropower sector needs to not only focus on energy production but also, include the negative social and environmental externalities caused by dams and recognize the unsustainability of current common practices.

Previous global estimates of the human impact on terrestrial photosynthesis products depended heavily on extrapolation from plot-scale measurements. Here, we estimated this impact with the use of recent data, many of which were collected at global and continental scales. Monte Carlo techniques that incorporate known and estimated error in our parameters provided estimates of uncertainty. We estimate that humans appropriate 10 to 55% of terrestrial photosynthesis products. This broad range reflects uncertainty in key parameters and makes it difficult to ascertain whether we are approaching crisis levels in our use of the planet's resources. Improved estimates will require high-resolution global measures within agricultural lands and tropical forests.

Irrigation’s effects on precipitation during an exceptionally dry summer (June–August 2012) in the United States were quantified by incorporating a novel dynamic irrigation scheme into the Weather Research and Forecasting (WRF) Model. The scheme is designed to represent a typical application strategy for farmlands across the conterminous United States (CONUS) and a satellite-derived irrigation map was incorporated into the WRF-Noah-Mosaic module to realistically trigger the irrigation. Results show that this new irrigation approach can dynamically generate irrigation water amounts that are in close agreement with the actual irrigation water amounts across the high plains (HP), where the prescribed scheme best matches real-world irrigation practices. Surface energy and water budgets have been substantially altered by irrigation, leading to modified large-scale atmospheric circulations. In the studied dry summer, irrigation was found to strengthen the dominant interior high pressure system over the southern and central United States and deepen the trough over the upper Midwest. For the HP and central United States, the rainfall amount is slightly reduced over irrigated areas, likely as a result of a reduction in both local convection and large-scale moisture convergence resulting from interactions and feedbacks between the land surface and atmosphere. In areas downwind of heavily irrigated regions, precipitation is enhanced, resulting in a 20%–100% reduction in the dry biases (relative to the observations) simulated over a large portion of the downwind areas without irrigation in the model. The introduction of irrigation reduces the overall mean biases and root-mean-square errors in the simulated daily precipitation over the CONUS.

The total heat gained by the North Atlantic Ocean over the past 50 years is equivalent to a basinwide increase in the flux of heat across the ocean surface of 0.4 +/- 0.05 watts per square meter. We show, however, that this basin has not warmed uniformly: Although the tropics and subtropics have warmed, the subpolar ocean has cooled. These regional differences require local surface heat flux changes (+/-4 watts per square meter) much larger than the basinwide average. Model investigations show that these regional differences can be explained by large-scale, decadal variability in wind and buoyancy forcing as measured by the North Atlantic Oscillation index. Whether the overall heat gain is due to anthropogenic warming is difficult to confirm because strong natural variability in this ocean basin is potentially masking such input at the present time.

[1] Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.