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This paper presents the results of a series of idealized cloud resolving simulations of the evolution of moist roll convection observed as part of the Lake-Induced Convection Experiment (Lake-ICE) that took place during the 1997/98 winter over central Lake Michigan. Satellite and radar observations of the roll convection depict striking linear rolls stretching from 10 km off the western shore of the lake, across to the eastern shore, and then continuing across Michigan. The spacing of the primary rolls was observed to be 6 km, giving a ratio of spacing to depth of about 5:1, which is consistent with theory. In addition, a longer wavelength (13 km) of stationary banding was observed parallel to the shoreline. In an earlier study of this case, multiply nested simulations of the convective rolls based on real data variable initialization were successful in producing banded structures with similar spacing and location over the water to those observed using fine grid resolution of about 500 m. Unfortunately, the initial locations of simulated bands were organized primarily by numerical effects of grid interpolation. This suggested that the spacing of the bands was robust, but that their initial location was highly sensitive to subtle systematic forcings. In this paper, a set of idealized model experiments, designed to isolate the role that physically realistic local forcing plays in the organization of the rolls, was performed. Because externally generated upstream turbulence was suppressed in these tests so as not to bias the result, the generation of rolls was delayed until 20–30 km downwind of the observed location and the location simulated in the previous grid nesting experiments. It was shown that the subtle effects of the shoreline geometry were sufficient to spawn a near-surface streamwise vorticity that became the primary seed for roll development at the most efficient mode of roll convection. These results suggest that previous structures evolved in the upstream shear-driven land-based mixed layer were likely also important in determining where the nonlocal overturning was first triggered. It is not clear from these results whether the shear-driven structures that evolved over the land also played a significant role in organizing the structural geometry of the lake rolls. Results also suggested that the shore parallel bands were a robust feature of the atmospheric structure resulting from resonant gravity wave trapping in the frontal layer. [ABSTRACT FROM AUTHOR]

Lakes are a major geologic feature in humid regions, and multiple lake hydrologic types exist with varying physical and chemical characteristics, connections among lakes, and relationships to the landscape. The authors developed a model of water fluxes through major components of groundwater-dominated lake catchments in a region containing thousands of lakes, the Northern Highland Lake District (NHLD) of northern Wisconsin and the Upper Peninsula of Michigan. The model was calibrated with data from widely differing lakes using the same set of simple equations to represent the hydrologic type, water residence time, and amount and timing of stream and groundwater flows of representative lakes in today's climate. The authors investigated the sensitivity of the water balance of a set of three connected representative lakes and their catchments to systematic increases and decreases in the precipitation regime, and contrasted results using lake-specific morphometry to those for a lake having size and shape parameters typical of the region. Results indicate that a common set of equations can successfully represent major water balance characteristics of the three basic lake hydrologic types (hydraulically mounded, groundwater flowthrough, and drainage) in the NHLD. Sensitivity of modeled lakes varied by lake type, with drainage lakes more strongly buffered against substantial hydrologic changes in extreme climate scenarios. Catchment-scale water budgets differed substantially among lakes of different types, yet can be understood along a continuum of relative catchment size. These results suggest that a simple model of lake and catchment water balance can be extended to entire lake districts, where the detailed morphometry of most lakes is not well known. [ABSTRACT FROM AUTHOR]

Gridded climate datasets are used by researchers and practitioners in many disciplines, including forest ecology, agriculture, and entomology. However, such datasets are generally unable to account for microclimatic variability, particularly within sites or among individual trees. One such dataset is a recent climatology of extreme minimum temperatures in the U.S. Great Lakes region, based on the Parameter–Elevation Regressions on Independent Slopes Model (PRISM) gridded temperature dataset. Development of this climatology was motivated by interest in the spatiotemporal variability of winter temperatures potentially lethal to the hemlock woolly adelgid (HWA) (Adelges tsugae Annand) (Hemiptera: Adelgidae), an invasive insect that causes mortality of eastern hemlock (Tsuga canadensis). In this study, cold-season daily minimum temperatures were monitored at six Michigan sites varying in latitude, elevation, Great Lakes proximity, and HWA infestation status, to address two objectives. First, we documented the spatiotemporal variability in daily minimum air temperatures recorded at multiple aspects and heights on selected hemlock trees. Second, this variability was characterized in the context of the PRISM extreme minimum temperature climatology. Tree-sensor air temperatures exhibited minimal relationships with aspect but considerable sensitivity to height. Daily minimum temperatures were higher for some tree sensors positioned ≤ 0.2 m above ground level during some time periods, with overall muted temporal variability, relative to an adjacent ambient sensor. This phenomenon was attributed to the insulating effects of snow cover, because the tree–ambient sensor temperature difference was positively correlated with snow depth. Overall, results indicate that such unresolved variability warrants consideration by gridded climate dataset users. [ABSTRACT FROM AUTHOR]

Presented are four winter seasons of data from an enhanced precipitation instrument suite based at the National Weather Service (NWS) Office in Marquette (MQT), Michigan (250–500 cm of annual snow accumulation). In 2014 the site was augmented with a Micro Rain Radar (MRR) and a Precipitation Imaging Package (PIP). MRR observations are utilized to partition large-scale synoptically driven (deep) and surface-forced (shallow) snow events. Coincident PIP and NWS MQT meteorological surface observations illustrate different characteristics with respect to snow event category. Shallow snow events are often extremely shallow, with MRR-indicated precipitation heights of less than 1500 m above ground level. Large vertical reflectivity gradients indicate efficient particle growth, and increased boundary layer turbulence inferred from observations of spectral width implies increased aggregation in shallow snow events. Shallow snow events occur 2 times as often as deep events; however, both categories contribute approximately equally to estimated annual accumulation. PIP measurements reveal distinct regime-dependent snow microphysical differences, with shallow snow events having broader particle size distributions and comparatively fewer small particles and deep snow events having narrower particle size distributions and comparatively more small particles. In addition, coincident surface meteorological measurements indicate that most shallow snow events are associated with surface winds originating from the northwest (over Lake Superior), cold temperatures, and relatively high surface pressures, which are characteristics that are consistent with cold-air outbreaks. Deep snow events have meteorologically distinct conditions that are accordant with midlatitude cyclones and frontal structures, with mostly southwest surface winds, warmer temperatures approaching freezing, and lower surface pressures. [ABSTRACT FROM AUTHOR]

On an annual basis, heat is the chief cause of weather-related deaths in the United States. Therefore, understanding the temperature structure where people live is important for reducing the health burden imposed by hot weather. This study focused on the air temperatures in the Detroit, Michigan, metropolitan region during the summer of 2009. An observational network was established that included 1) monitors sited in the backyards of residential participants, 2) National Weather Service standard observations, and 3) a network of monitors operated by the State of Michigan. Daily high and low temperatures were analyzed for spatial pattern, magnitude of spatial variability, and relationships with weather conditions. The existence of spatial variability was confirmed specifically during weather that was considered to be dangerous to public health. The relationships between temperature observations and distance to water, distance to city center, and local percent of impervious surface were investigated. The spatial variability during the daily low was typically stronger in magnitude and the spatial pattern was more consistent than were those during the daily high. The largest correlation with land-cover and location attributes was between values of percent of impervious surface and daily low temperatures. Daily high temperatures were most correlated with distance to water. Consistent with previous studies on spatial variability in urban environments, the results suggest a need for sensitivity to the spatially variable nature of exposure to heat events in both public health and urban planning. For example, these results showed that the downtown area experienced elevated temperatures during nights and that the eastern portions of Detroit experienced decreased temperatures during afternoons. [ABSTRACT FROM AUTHOR]

The 2010 Development Test Environment Experiment (DTE10) took place from 28 January to 29 March 2010 in the Detroit, Michigan, metropolitan area for the purposes of collecting and evaluating mobile data from vehicles. To examine the quality of these data, over 239 000 air temperature and atmospheric pressure observations were obtained from nine vehicles and were compared with a weather station set up at the testing site. The observations from the vehicles were first run through the NCAR Vehicle Data Translator (VDT). As part of the VDT, quality-checking (QCh) tests were applied; pass rates from these tests were examined and were stratified by meteorological and nonmeteorological factors. Statistics were then calculated for air temperature and atmospheric pressure in comparison with the weather station, and the effects of different meteorological and nonmeteorological factors on the statistics were examined. Overall, temperature measurements showed consistent agreement with the weather station, and there was little impact from the QCh process or stratifications-a result that demonstrated the feasibility of collecting mobile temperature observations from vehicles. Atmospheric pressure observations were less well matched with surface validation, the degree of which varied with the make and model of vehicle. Therefore, more work must be done to improve the quality of these observations if atmospheric pressure from vehicles is to be useful. [ABSTRACT FROM AUTHOR]

Premodification of the atmosphere by upwind lakes is known to influence lake-effect snowstorm intensity and locations over downwind lakes. This study highlights perhaps the most visible manifestation of the link between convection over two or more of the Great Lakes lake-to-lake (L2L) cloud bands. Emphasis is placed on L2L cloud bands observed in high-resolution satellite imagery on 2 December 2003. These L2L cloud bands developed over Lake Superior and were modified as they passed over Lakes Michigan and Erie and intervening land areas. This event is put into a longer-term context through documentation of the frequency with which lake-effect and, particularly, L2L cloud bands occurred over a 5-yr time period over different areas of the Great Lakes region. [ABSTRACT FROM AUTHOR]

The cold-air outbreak of 13–14 January 1998 during the Lake-Induced Convection Experiment was characterized by large positive buoyancy flux and moderate wind shear. Although theory predicts only cellular organization in these conditions, transient linear organization was observed. Time series of vertical velocity obtained with the Pennsylvania State University 94-GHz vertically pointing cloud radar, which is sensitive to cloud droplets and ice crystals, were used to document the changes in organization that occurred during this wintertime lake-effect event. The cloud radar was deployed on the downwind shore of southern Lake Michigan and measured high-temporal-resolution vertical velocity data at several in-cloud heights. The duration of the event was 18 h, encompassing three cycles of linear organization switching to cellular organization. In Part I of this two-part series the authors document the transient nature of the linearly organized convection and evaluate the role of atmospheric conditions in the mode switching between linear and cellular organization. Within the limits of the available measurements, no correlation was found with mean or low-level shear, surface fluxes, or stability parameters. The mode switching in this case does not appear to be controlled by the atmospheric indicators typically associated with linearly organized convection, suggesting that other factors must have played an important role. [ABSTRACT FROM AUTHOR]

Real-time high-resolution mesoscale predictions using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) over the Great Lakes region are evaluated for the 2002/03 winter and 2003 summer seasons using surface and upper-air observations, with a focus on near-surface and boundary layer properties that are important for applications such as air quality and fire weather predictions. The summer season predictions produce a cold bias in maximum daily temperature and a warm bias in minimum temperature that together lead to a good prediction of daily mean temperature but a smaller-than-observed diurnal temperature cycle. In winter, the predicted near-surface temperatures are lower both day and night, yielding good agreement with the observed amplitude of the diurnal temperature cycle but relatively large cold bias in daily mean temperature. The predicted temperatures in the boundary layer are also systematically lower than the observed temperatures in the two seasons. The cold bias is consistent with the wetter-than-observed lower atmosphere in the model prediction, which in turn can be attributed to an inadequate specification of soil moisture. In both seasons, the model produced substantially more precipitation in all categories, especially in the heavy precipitation category, and the overprediction is primarily associated with more widespread area coverage in the model prediction. The chances of producing a false precipitation forecast are substantially higher than missing an observed precipitation event. Small systematic errors are found in the predictions of low-level winds, but above the boundary layer, the predicted winds are predominantly from the west, while the observed winds are from the west-northwest. The model is able to capture the general development and evolution of the lake–land breezes in areas surrounding Lake Michigan during summer, although errors exist in the strengths of the breezes and the timing of their transition. Predicted early morning inversions are slightly stronger than observed in winter and weaker than observed in summer. The weak summer morning inversion results in a rapid inversion breakup followed by an earlier growth of a mixed layer after sunrise. Despite the head start, the predicted mixed-layer heights in late afternoon are lower than those observed, suggesting that either the predicted surface sensible heat flux may be too low or the boundary layer flux divergence may be too high. Decreasing horizontal grid spacing from 12 to 4 km results in little improvement in the predictions of near-surface and boundary layer properties except for precipitation, for which the model bias is significantly reduced by the increase in horizontal resolution. The cold and wet biases and errors in inversion strengths and mixed-layer development call for extra caution when using products from mesoscale forecasts in applications such as air pollution and fire weather prediction. [ABSTRACT FROM AUTHOR]

Lake-effect snowstorms generally develop within convective boundary layers, which are induced when cold air flows over relatively warm lakes in fall and winter. Mesoscale circulations within the boundary layers largely control which communities near the downwind shores of the lakes receive the most intense snow. The lack of quantitative observations over the lakes during lake-effect storms limits the ability to fully understand and predict these mesoscale circulations. This study provides the first observations of the concurrent spatial and temporal evolution of the thermodynamic and microphysical boundary layer structure and mesoscale convective patterns across Lake Michigan during an intense lake-effect event. Observations analyzed in this study were taken during the Lake-Induced Convection Experiment (Lake-ICE). Aircraft and sounding observations indicate that the lake-effect snows of 13 January 1998 developed within a convective boundary layer that grew rapidly across Lake Michigan. Boundary layer clouds developed within 15 km and snow developed within 30 km of the upwind (western) shoreline. Near the downwind shore, cloud cover was extensive and snow nearly filled the boundary layer. Extensive sea smoke in the surface layer, with disorganized (or cellular) and linear features, was observed visually across the entire lake. Over portions of northern Lake Michigan, where airborne dual-Doppler radar observations were obtained, the mesoscale circulation structure remained disorganized (random or cellular) across the lake. Given observed shear and stability conditions in this region, this structure is consistent with past theoretical and numerical modeling results. To the south, where surface winds were slightly stronger and lake–air temperature differences were less, wind-parallel bands indicative of rolls were often present. The horizontal scale of the observed mesoscale convective structures grew across Lake Michigan, in agreement with most previous... [ABSTRACT FROM AUTHOR]

ABSTRACT The Keweenaw Current, observed along the coast of the Keweenaw Peninsula in Lake Superior during July 1973, was simulated using a 3D, nonorthogonal coordinate transformation, primitive equation coastal ocean model. The model domain covered the entire lake with a high resolution of 250-600 m in the cross-shelf direction and 4-6 km in the alongshelf direction along the peninsula. The model was initialized using the monthly averaged temperature field observed in June 1973 and was run prognostically with synoptic wind forcing plus monthly averaged heat flux. Good agreement was found between model-predicted and observed currents at buoy stations near Eagle Harbon Comparison of the model results with and without inclusion of heat flux suggested that combined wind and heat fluxes played a key role in the intensification of the Keweenaw Current during summer months. The model-predicted relatively strong near-inertial oscillations occurred episodically under conditions... [ABSTRACT FROM AUTHOR]