One way to adapt to and mitigate current and future water scarcity is to manage and store water more efficiently. Reservoirs act as critical buffers to ensure agricultural and municipal water deliveries, mitigate flooding, and generate hydroelectric power, yet they often lose significant amounts of water through evaporation, especially in arid and semiarid regions. Despite this fact, reservoir evaporation has been an inconsistently and inaccurately estimated component of the water cycle within the water resource infrastructure of the arid and semiarid western United States. This paper highlights the increasing importance and challenges of correctly estimating and forecasting reservoir evaporation in the current and future climate, as well as the need to bring new ideas and state-of-the-art practices for the estimation of reservoir evaporation into operational use for modern water resource managers. New ideas and practices include i) improving the estimation of reservoir evaporation using up-to-date knowledge, state-of-the-art instrumentation and numerical models, and innovative experimental designs to diagnose processes and accurately forecast evaporation; ii) improving our understanding of spatial and temporal variations in evaporative water loss from existing reservoirs and transferring this knowledge when expanding reservoirs or siting new ones; and iii) implementing an adaptive management plan that incorporates new knowledge, observations, and forecasts of reservoir evaporation to improve water resource management.

Heat fluxes at the lake surface play an integral part in determining the energy budget and thermal structure in lakes, including regulating how lakes respond to climate change. We explore patterns in turbulent heat fluxes, which vary across temporal and spatial scales, using in situ high‐frequency monitoring data from 45 globally distributed lakes. Our analysis demonstrates that some of the lakes studied follow a marked seasonal cycle in their turbulent surface fluxes and that turbulent heat loss is highest in larger lakes and those situated at low latitude. The Bowen ratio, which is the ratio of mean sensible to mean latent heat fluxes, is smaller at low latitudes and, in turn, the relative contribution of evaporative to total turbulent heat loss increases toward the tropics. Latent heat transfer ranged from ~ 60% to > 90% of total turbulent heat loss in the examined lakes. The Bowen ratio ranged from 0.04 to 0.69 and correlated significantly with latitude. The relative contributions to total turbulent heat loss therefore differ among lakes, and these contributions are influenced greatly by lake location. Our findings have implications for understanding the role of lakes in the climate system, effects on the lake water balance, and temperature‐dependent processes in lakes.

Can we predict long‐term trends of lake surface temperature based on air temperature alone? We explore this question by analyzing the performance of a hybrid model (air2water) as a predictive tool for defining scenarios of lake surface temperature in the framework of climate change studies. Employing Lake Tahoe (U.S.A.) as a case study, we apply the model using different air temperature datasets (in situ measurements, gridded observations, and downscaled General Circulation Models). Through a data‐driven calibration of the model parameters based on surface water temperature records, we show that air2water provides good performance (root mean square error ∼ 0.5°C, on a monthly scale) regardless of the input dataset. The model is able to accurately capture the historical long‐term trend and interannual fluctuations over decades (from 1969 to present), using only 7 yr of monthly measurements of surface water temperature for calibration. Additionally, when used to predict future surface water temperature of the lake, air2water produces the same projections irrespective of the air temperature dataset used to drive the model. This is certainly desirable, but not immediately expected when using a relatively simple model. Overall, the results suggest the high potential and robustness of air2water as a predictive tool for climate change assessment. Lake surface temperature warming of up to 1.1°C (RCP 4.5) and 2.9°C (RCP 8.5) was simulated at the end of the 21st century during summer months in Lake Tahoe. Such a scenario, if realized, would lead to serious consequences on lake water chemistry, primary productivity, plankton community structure, and nutrient cycling.

Open top chambers (OTCs) were adopted as the recommended warming mechanism by the International Tundra Experiment (ITEX) network in the early 1990’s. Since then, OTCs have been deployed across the globe. Hundreds of papers have reported the impacts of OTCs on the abiotic environment and the biota. Here we review the impacts of the OTC on the physical environment, with comments on the appropriateness of using OTCs to characterize the response of biota to warming. The purpose of this review is to guide readers to previously published work and to provide recommendations for continued use of OTCs to understand the implications of warming on low stature ecosystems. In short, the OTC is a useful tool to experimentally manipulate temperature, however the characteristics and magnitude of warming varies greatly in different environments, therefore it is important to document chamber performance to maximize the interpretation of biotic response. When coupled with long-term monitoring, warming experiments are a valuable means to understand the impacts of climate change on natural ecosystems.

Climate change is warming the temperatures and lengthening the Arctic growing season with potentially important effects on plant phenology. The ability of plant species to acclimate to changing climatic conditions will dictate the level to which their spatial coverage and habitat-type dominance is different in the future. While the effect of changes in temperature on phenology and species composition have been observed at the plot and at the regional scale, a systematic assessment at medium spatial scales using new noninvasive sensor techniques has not been performed yet. At four sites across the North Slope of Alaska, changes in the Normalized Difference Vegetation Index (NDVI) signal were observed by Mobile Instrumented Sensor Platforms (MISP) that are suspended over 50 m transects spanning local moisture gradients. The rates of greening (measured in June) and senescence (measured in August) in response to the air temperature was estimated by changes in NDVI measured as the difference between the NDVI on a specific date and three days later. In June, graminoid-and shrub-dominated habitats showed the greatest rates of NDVI increase in response to the high air temperatures, while forb-and lichen-dominated habitats were less responsive. In August, the NDVI was more responsive to variations in the daily average temperature than spring greening at all sites. For graminoid-and shrub-dominated habitats, we observed a delayed decrease of the NDVI, reflecting a prolonged growing season, in response to high August temperatures. Consequently, the annual C assimilation capacity of these habitats is increased, which in turn may be partially responsible for shrub expansion and further increases in net summer CO 2 fixation. Strong interannual differences highlight that long-term and noninvasive measurements of such complex feedback mechanisms in arctic ecosystems are critical to fully articulate the net effects of climate variability and climate change on plant community and ecosystem processes.