Sediment resuspension and transport in Lake Michigan during the unstratified period

Instrumented moorings were deployed during the winter of 1994–95 at three depths (28, 58 and 101 m) in southern Lake Michigan. Storms during the observation period were not unusually severe, so the processes observed are typical of those that occur during an average winter. Time series observations of water temperature, beam attenuation coefficient (a measure of water transparency) and current velocity show that local resuspension of bottom sediment occurred frequently after the breakdown of the thermocline. Resuspension was most frequent close to the shore but was also observed at the 58 m station. Local resuspension did not occur at the 101 m station, but advection to the site of material resuspended at shallower sites was observed. These observations do not support the hypothesis proposed by previous investigators that local resuspension at depths of 100 m or greater occurs during the unstratified period. It is more likely that fine-grained material resuspended by storm action in intermediate water depths (≈ 30–60 m) is transported into the deeper parts of the lake by the general lake circulation.     

Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe

The determination of the depth of daytime and nighttime mixing layers must be known very accurately to relate boundary-layer concentrations of gases or particles to upstream fluxes. The mixing-height is parametrized in numerical weather prediction models, so improving the determination of the mixing height will improve the quality of the estimated gas and particle budgets. Datasets of mixing-height diurnal cycles with high temporal and spatial resolutions are sought by various end users. Lidars and ceilometers provide vertical profiles of backscatter from aerosol particles. As aerosols are predominantly concentrated in the mixing layer, lidar backscatter profiles can be used to trace the depth of the mixing layer. Large numbers of automatic profiling lidars and ceilometers are deployed by meteorological services and other agencies in several European countries providing systems to monitor the mixing height on temporal and spatial scales of unprecedented density. We investigate limitations and capabilities of existing mixing height retrieval algorithms by applying five different retrieval techniques to three different lidars and ceilometers deployed during two 1-month campaigns. We studied three important steps in the mixing height retrieval process, namely the lidar/ceilometer pre-processing to reach sufficient signal-to-noise ratio, gradient detection techniques to find the significant aerosol gradients, and finally quality control and layer attribution to identify the actual mixing height from multiple possible layer detections. We found that layer attribution is by far the most uncertain step. We tested different gradient detection techniques, and found no evidence that the first derivative, wavelet transform, and two-dimensional derivative techniques have different skills to detect one or multiple significant aerosol gradients from lidar and ceilometer attenuated backscatter. However, our study shows that, when mixing height retrievals from a ultraviolet lidar and a near-infrared ceilometer agreed, they were 25?C40% more likely to agree with an independent radiosonde mixing height retrieval than when each lidar or ceilometer was used alone. Furthermore, we point to directions that may assist the layer attribution step, for instance using commonly available surface measurements of radiation and temperature to derive surface sensible heat fluxes as a proxy for the intensity of convective mixing. It is a worthwhile effort to pursue such studies so that within a few years automatic profiling lidar and ceilometer networks can be utilized efficiently to monitor mixing heights at the European scale.     

Preparing for Climatic Change: The Water, Salmon, and Forests of the Pacific Northwest

The impacts of year-to-year and decade-to-decade climatic variations on some of the Pacific Northwest's key natural resources can be quantified to estimate sensitivity to regional climatic changes expected as part of anthropogenic global climatic change. Warmer, drier years, often associated with El Niño events and/or the warm phase of the Pacific Decadal Oscillation, tend to be associated with below-average snowpack, streamflow, and flood risk, below-average salmon survival, below-average forest growth, and above-average risk of forest fire. During the 20th century, the region experienced a warming of 0.8 °C. Using output from eight climate models, we project a further warming of 0.5–2.5 °C (central estimate 1.5 °C) by the 2020s, 1.5–3.2°C (2.3 °C) by the 2040s, and an increase in precipitation except in summer. The foremost impact of a warming climate will be the reduction of regional snowpack, which presently supplies water for ecosystems and human uses during the dry summers. Our understanding of past climate also illustrates the responses of human management systems to climatic stresses, and suggests that a warming of the rate projected would pose significant challenges to the management of natural resources. Resource managers and planners currently have few plans for adapting to or mitigating the ecological and economic effects of climatic change.