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Large riverine systems are diverse and dynamic and are made up of multiple habitat types of lentic and lotic water. They are also heavily modified by humans and today nearly all habitats in many large rivers have been drastically altered. These modifications often include disconnecting lentic habitats either permanently or intermittently from the main channel. The Merwin Preserve at Spunky Bottoms (Merwin) began as a connected backwater that was leveed and drained for agriculture in the 1920s and restored in 1999, with restoration allowing it to become a disconnected backwater habitat. This status changed in 2013 when record flooding on the adjacent Illinois River overtopped and breached the levee creating an unmanaged and intermittent connection allowing the river access at moderately high river stages. During the past 20 years, the fish community at Merwin has undergone several changes that follow three drought events pre-breach, the exchange of fishes from the mainstem following the breach in 2013, and subsequent low water conditions of much of the area as river levels drop. Long term data and more intensive sampling efforts during the drought of 2012 showed relative abundance of sport fishes declined during, or immediately following, pre-breach drought events and post-breach low water conditions while relative abundance of non-sport and non-native fishes remained stable. The unique story of Merwin can provide a case study for other large river restoration projects on the effects of drought, climate change, and impacts of an unmanaged connection of a previously disconnected habitat to an adjacent large river. [ABSTRACT FROM AUTHOR]

The Intergovernmental Panel on Climate Change (IPCC) suggests limiting global warming to 1.5 °C compared to 2 °C would avoid dangerous impacts of anthropogenic climate change and ensure a more sustainable society. As the vulnerability to global warming is regionally dependent, this study assesses the effects of 0.5 °C less global warming on climate extremes in the United States. Eight climate extreme indices are calculated based on Coupled Model Intercomparison Project—phase 5 (CMIP5), and North American—Coordinated Regional Climate Downscaling Experiments (NA-CORDEX) with and without bias correction. We evaluate the projected changes in temperature and precipitation extremes, and examine their differences between the 1.5 and 2 °C warming targets. Under a warming climate, both CMIP5 and NA-CORDEX show intensified heat extremes and reduced cold extremes across the country, intensified and more frequent heavy precipitation in large areas of the North, prolonged dry spells in some regions of the West, South, and Midwest, and more frequent drought events in the West. Results suggest that the 0.5 °C less global warming would avoid the intensification of climate extremes by 32–46% (35–42%) for heat extremes intensity (frequency) across the country and, by 23–41% for heavy precipitation intensity in the North, South, and Southeast. The changes in annual heavy precipitation intensity are mainly contributed by winter and spring. However, impacts of the limited warming on the frequency of heavy precipitation, dry spell, and drought frequency are only evident in a few regions. Although uncertainties are found among the climate models and emission scenarios, our results highlight the benefits of limiting warming at 1.5 °C in order to reduce the risks of climate extremes associated with global warming. [ABSTRACT FROM AUTHOR]

Soil moisture can affect precipitation, however there is significant debate about the sign and strength of land–atmosphere coupling. This may be due to the differences regarding the selection of data sources, the presence of atmospheric persistence, and the spatial and temporal scales of the analysis. This study is a sensitivity analysis that quantifies how each of these factors influences land–atmosphere coupling in the central United States from 2005 to 2007. Four different sources of soil moisture are used to represent soil moisture: in situ measurements and three satellite products. The Thunderstorm Observation by Radar (ThOR) algorithm is used to identify convective events. The results show that warm-season afternoon convection initiates preferentially over dry soil, if in situ measurements are used. However, when satellite data are used the sign and strength of the soil moisture-precipitation coupling varies depending on which satellite dataset is used. This demonstrates that evaluations of land–atmosphere coupling strength are sensitive to the source of soil moisture. Our results also show that accounting for atmospheric persistence tends to weaken apparent land–atmosphere coupling. Changing the spatial scale of the analysis can also influence the sign and coupling strength. Analyses that are performed at a coarser spatial resolution tend to indicate a wet preference because they do not capture the local negative feedbacks. This study demonstrates that contradictions in the literature regarding the sign and strength of soil moisture-precipitation feedbacks can be partly attributed to differences in datasets, methods and scale of the analysis. [ABSTRACT FROM AUTHOR]

We develop an extreme heat validation approach for medium-range forecast models and apply it to the NCEP coupled forecast model, for which we also attempt to diagnose sources of poor forecast skill. A weighting strategy based on the Poisson function is developed to provide a seamless transition from short-term day-by-day weather forecasts to expanding time means across subseasonal timescales. The skill of heat wave forecasts over the conterminous United States is found to be rather insensitive to the choice of skill metric; however, forecast skill does display spatial patterns that vary depending on whether daily mean, minimum, or maximum temperatures are the basis of the heat wave metric. The NCEP model fails to persist heat waves as readily as is observed. This inconsistency worsens with longer forecast lead times. Land–atmosphere feedbacks appear to be a stronger factor for heat wave maintenance at southern latitudes, but the NCEP model seems to misrepresent those feedbacks, particularly over the Southwest United States, leading to poor skill in that region. The NCEP model also has unrealistically weak coupling over agricultural areas of the northern United States, but this does not seem to degrade model skill there. Overall, we find that the Poisson weighting strategy combined with a variety of deterministic and probabilistic skill metrics provides a versatile framework for validation of dynamical model heat wave forecasts at subseasonal timescales. Climate science: evaluating forecasts of extreme heat across subseasonal timescales A validation window that broadens with time is developed to provide seamless verification of extreme heat forecasts from days to weeks. Trent Ford (Southern Illinois University), Paul Dirmeyer (COLA-George Mason University), and David Benson (George Mason University) applied several skill metrics with a Poisson function weighting strategy to verify NOAA coupled forecast system model extreme heat forecasts over the United States. The model fails to persist heat waves as readily as is observed, and this inconsistency worsens with longer forecast lead times. Land surface–atmosphere interactions appear to influence heat wave persistence, but the model misrepresents these interactions, leading to poor skill in the Southwest and Midwest regions. The Poisson weighting strategy provides a versatile framework for verifying forecasts across subseasonal timescales. Continued verification and improvement of model forecasts contributes to reducing the risk of extreme climate events. [ABSTRACT FROM AUTHOR]