Changing surface radiation and energy budgets of the Hudson Bay Complex using the North American regional reanalysis (NARR) model

Monthly and annual component fluxes of the surface radiation and energy budgets for the two-decade period from 1997 to 2016 are compared with the climate normal period (1981–2010) for the marine system consisting of James Bay, Hudson Bay, Hudson Strait and Foxe Basin using estimates from the North American regional reanalysis model. Reflected solar radiation has declined unevenly, primarily offshore of major rivers, in polynyas and along shore leads, both during earlier melt and later freeze up. Annually, net radiation increases are driven by albedo decreases during the summer. Over 94% of the increases in ocean heat gain during the melt season are due to increases in absorbed sunlight. Large enhanced oceanic heat losses in the late fall are almost entirely consumed by intensified convective losses of both sensible and latent heat. All the seas within the Hudson Bay Complex show a reduced rate of ocean warming over the past two decades. This outcome can be partially reconciled with the observation that all water bodies are experiencing enhanced losses of energy during extended ice-free winters that exceed enhanced gains of energy during the extended ice-free summers. The implications of seasonal changes in ice cover for future climate are discussed.

Meteorological Differences Characterizing Tornado Outbreak Forecasts of Varying Quality

Tornado outbreaks (TOs) are a major hazard to life and property for locations east of the Rocky Mountains. Improving tornado outbreak (TO) forecasts will help minimize risks associated with these major events. In this study, we present a methodology for quantifying TO forecasts of varying quality, based on Storm Prediction Center convective outlook forecasts, and provide synoptic and mesoscale composite analyses to identify important features characterizing these events. Synoptic-scale composites from the North American Regional Reanalysis (NARR) are presented for TO forecasts at three forecast quality levels, H-class (high quality), M-class (medium quality), and L-class (low quality), as well as false alarm TO forecasts. H-class and false alarm TO forecasts share many meteorological similarities, particularly in the synoptic-scale, though false alarm events show less well-defined low-level synoptic-scale features. M- and L-class TOs present environments dominated by mesoscale thermodynamic processes (particularly dryline structures), contrasting H-class TOs which are clearly synoptically driven. Simulations of these composites reveal higher instability in M- and L-class TOs that lack key kinematic structures that characterize H-class TOs. The results presented offer important forecast feedback that can help inform future TO predictions and ultimately produce improved TO forecast quality.

North American Supercell Environments in Atmospheric Reanalyses and RUC-2

A suite of modern atmospheric reanalyses is analyzed to determine how they represent North American supercell environments. This analysis is performed by comparing a database of Rapid Update Cycle (RUC-2) proximity soundings with profiles derived from the nearest grid point in each reanalysis. Parameters are calculated using the Sounding and Hodograph Analysis and Research Program in Python (SHARPpy), an open-source Python sounding-analysis package. Representation of supercell environments varies across the reanalyses, and the results have ramifications for climatological studies that use these datasets. In particular, thermodynamic parameters such as the convective available potential energy (CAPE) show the widest range in biases, with reanalyses falling into two camps. The North American Regional Reanalysis (NARR) and the Japanese 55-year Reanalysis (JRA-55) are similar to RUC-2, but other reanalyses have a substantial negative bias. The reasons for these biases vary and range from thermodynamic biases at the surface to evidence of convective contamination. Overall, it is found that thermodynamic biases feed back to other convective parameters that incorporate CAPE directly or indirectly via the effective layer. As a result, significant negative biases are found for indices such as the supercell composite parameter. These biases are smallest for NARR and JRA-55. Kinematic parameters are more consistent across the reanalyses. Given the issues with thermodynamic properties, better segregation of soundings by storm type is found for fixed-layer parameters than for effective-layer shear parameters. Although no reanalysis can exactly reproduce the results of earlier RUC-2 studies, many of the reanalyses can broadly distinguish between environments that are significantly tornadic versus nontornadic.

An Evaluation of the North American Regional Reanalysis Simulated Soil Moisture Conditions during the 2011–13 Drought Period

Accurate and timely information on soil moisture conditions is an important component to effectively prepare for the damaging aspects of hydrological extremes. The combination of sparsely dense in situ networks and shallow observation depths of remotely sensed soil moisture conditions often force local and regional decision-makers to rely on numerical methods when assessing the current soil state. In this study, soil moisture from a commonly used, high-resolution reanalysis dataset is compared to observations from the U.S. Climate Reference Network (USCRN). The purpose of this study is to evaluate how well the North American Regional Reanalysis (NARR) captured the evolution, intensity, and spatial extent of the 2012 drought using both raw volumetric values and standardized anomalies of soil moisture. Comparisons revealed that despite a dry precipitation bias of 22% nationally, NARR had predominantly wetter 5-cm volumetric soil conditions over the growing season (April–September) than observed at USCRN sites across the contiguous United States, with differences more pronounced in drier regions. These biases were partially attributed to differences between the dominant soil characteristics assigned to the modeled grid cells and localized soil characteristics at the USCRN stations. However, NARR was able to successfully capture many aspects of the 2012 drought, including the timing, intensity, and spatial extent when using standardized soil moisture anomalies. Standardizing soil moisture conditions reduced the magnitude of systematic biases between NARR and USCRN in many regions and provided a more robust basis for utilizing modeled soil conditions in assessments of hydrological extremes.

Feasibility of small wind turbines in Ontario: Integrating power curves with wind trends

Micro-scale/small wind turbines, unlike larger utility-scale turbines, produce electricity at a rate of 300 W to 10 kW at their rated wind speed and are typically below 30 m in hub-height. These wind turbines have much more flexibility in their costs, maintenance and siting owing to their size and can provided wind energy in areas much less suited for direct supply to the grid system. The small wind industry has been substantially slow to progress in Ontario, Canada, and there is much debate over their viability in a growing energy dependent economy. In an effort to diversify the energy sector in Canada, it is crucial that some preliminary research be conducted in regards to the relevance of changing winds as they impact small wind turbines; this study seeks to demonstrate the performance of two small wind turbines, and speculate on the potential power output and its trend over Ontario historically over the last 33 years using the North American Regional Reanalysis (NARR) data. We assessed the efficiencies of a Skystream 3.7 (2.4 kW) and a Bergey Excel 1 kW wind turbines at the pre-established Kortright Centre for Conservation wind test site, located north of Toronto. We have found that the small turbine-based wind power around the Great Lakes and eastern James Bay have increased during the seasonal months of winter and fall, contributing as much as about 10 % in some regions to the total electricity demand in Ontario.