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R. J. Barthelmie and S. C. Pryor

Abstract

Wind speeds over the oceans are required for a range of applications but are difficult to obtain through in situ methods. Hence, remote sensing tools, which also offer the possibility of describing spatial variability, represent an attractive proposition. However, the uncertainties inherent in application of current remote sensing methodologies have yet to be fully quantified. Aside from known issues regarding absolute accuracy and precision, there are a number of biases inherent in remote retrieval of wind speeds using satellite-borne instrumentation that lead to overestimation of the wind resource and are demonstrated here to be of sufficient magnitude to merit further consideration. As an interim measure, error bounds are proposed for the wind speed probability distribution parameters, which may be applied to sparse datasets such as those likely to be obtained from satellite-borne instrumentation.

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S. C. Pryor and J. T. Schoof

Abstract

Climate science is increasingly using (i) ensembles of climate projections from multiple models derived using different assumptions and/or scenarios and (ii) process-oriented diagnostics of model fidelity. Efforts to assign differential credibility to projections and/or models are also rapidly advancing. A framework to quantify and depict the credibility of statistically downscaled model output is presented and demonstrated. The approach employs transfer functions in the form of robust and resilient generalized linear models applied to downscale daily minimum and maximum temperature anomalies at 10 locations using predictors drawn from ERA-Interim reanalysis and two global climate models (GCM; GFDL-ESM2M and MPI-ESM-LR). The downscaled time series are used to derive several impact-relevant Climate Extreme (CLIMDEX) temperature indices that are assigned credibility based on 1) the reproduction of relevant large-scale predictors by the GCMs (i.e., fraction of regression beta weights derived from predictors that are well reproduced) and 2) the degree of variance in the observations reproduced in the downscaled series following application of a new variance inflation technique. Credibility of the downscaled predictands varies across locations and between the two GCM and is generally higher for minimum temperature than for maximum temperature. The differential credibility assessment framework demonstrated here is easy to use and flexible. It can be applied as is to inform decision-makers about projection confidence and/or can be extended to include other components of the transfer functions, and/or used to weight members of a statistically downscaled ensemble.

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J. T. Schoof and S. C. Pryor

Abstract

Markov chains are widely used tools for modeling daily precipitation occurrence. Given the assumption that the Markov chain model is the right model for daily precipitation occurrence, the choice of Markov model order was examined on a monthly basis for 831 stations in the contiguous United States using long-term data. The model order was first identified using the Bayesian information criteria (BIC). The maximum-likelihood estimates of the Markov transition probabilities were computed from 100 bootstrapped samples and were then used to generate 50-yr precipitation occurrence series. The distributions of dry- and wet-spell lengths in the resulting series were then compared with observations using a two-sample Kolmogorov–Smirnov (K-S) test. The results suggest that the most parsimonious model, as identified by the BIC, usually (in approximately 68% of the cases) reproduced the wet- and dry-spell length distributions. However, the K-S test often indicated a second-order model when the BIC indicated a first-order model. In a smaller number of cases, the BIC indicated a higher-order model than the K-S test. In both cases, the differences were found to be due to the distribution of wet spells rather than dry spells. It is concluded that models chosen on the basis of the BIC may not adequately reproduce the distributions of wet and dry spells for some locations and times of year.

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S. C. Pryor and L. L. Sørensen

Abstract

Many previous studies have indicated the importance of nitric acid (HNO3) reactions on sea salt particles for flux divergence of HNO3 in the marine surface layer. The potential importance of this reaction in determining the spatial and temporal patterns of nitrogen dry deposition to marine ecosystems is investigated using models of sea spray generation and particle- and gas-phase dry deposition. Under horizontally homogeneous conditions with near-neutral stability and for wind speeds between 3.5 and 10 m s−1, transfer of HNO3 to the particle phase to form sodium nitrate may decrease the deposition velocity of nitrogen by over 50%, leading to greater horizontal transport prior to deposition to the sea surface. Conversely, for wind speeds above 10 m s−1, transfer of nitrogen to the particle phase would increase the deposition rate and hence decrease horizontal transport prior to surface removal.

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S. C. Pryor, R. C. Sullivan, and T. Wright

Abstract

Introduction of irrigated agriculture changes the partitioning of the surface energy flux between sensible and latent heat (H vs LE) and alters the albedo α and emissivity ε. In the absence of changes in the radiation components of the surface energy balance, the change in the Bowen ratio due to irrigation typically suppresses the local air temperature T but increases the total near-surface atmospheric heat content (as measured using equivalent potential temperature θ e). While the effect of irrigation on surface energy partitioning due to enhanced surface and subsurface water availability has long been acknowledged, the roles of associated changes in ε and α have received less attention, and the scales and magnitudes of these effects remain uncertain. A new methodology designed for application to in situ and remote sensing data is presented and used to demonstrate that the net impact of irrigation on T and θ e is strongly dependent on the regional climate, land cover in surrounding areas, and the amount of irrigation in the upwind fetch. The results suggest that the impact of the radiative forcing terms on net available energy is not negligible and may amplify or offset the impact from changed energy partitioning on T and θ e depending on the specific regional climate and land cover.

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T. J. Shepherd, R. J. Barthelmie, and S. C. Pryor

Abstract

The Weather Research and Forecasting (WRF) Model has been extensively used for wind energy applications, and current releases include a scheme that can be applied to examine the effects of wind turbine arrays on the atmospheric flow and electricity generation from wind turbines. Herein we present a high-resolution simulation using two different wind farm parameterizations: 1) the “Fitch” parameterization that is included in WRF releases and 2) the recently developed Explicit Wake Parameterization (EWP) scheme. We compare the schemes using a single yearlong simulation for a domain centered on the highest density of current turbine deployments in the contiguous United States (Iowa). Pairwise analyses are applied to diagnose the downstream wake effects and impact of wind turbine arrays on near-surface climate conditions. On average, use of the EWP scheme results in small-magnitude wake effects within wind farm arrays and faster recovery of full WT array wakes. This in turn leads to smaller impacts on near-surface climate variables and reduced array–array interactions, which at a systemwide scale lead to summertime capacity factors (i.e., the electrical power produced relative to nameplate installed capacity) that are 2%–3% higher than those from the more commonly applied Fitch parameterization. It is currently not possible to make recommendations with regard to which wind farm parameterization exhibits higher fidelity or to draw inferences with regard to whether the relative performance may vary with prevailing climate conditions and/or wind turbine deployment configuration. However, the sensitivities documented herein to the wind farm parameterization are of sufficient magnitude to potentially influence wind turbine array siting decisions. Thus, our research findings imply high value in undertaking combined long-term high-fidelity observational studies in support of model validation and verification.

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S. C. Pryor, M. Nielsen, R. J. Barthelmie, and J. Mann

Abstract

Remote sensing tools represent an attractive proposition for measuring wind speeds over the oceans because, in principle, they also offer a mechanism for determining the spatial variability of flow. Presented here is the continuation of research focused on the uncertainties and biases currently present in these data and quantification of the number of independent observations (scenes) required to characterize various parameters of the probability distribution of wind speeds. Theoretical and empirical estimates are derived of the critical number of independent observations (wind speeds derived from analysis of remotely sensed scenes) required to obtain probability distribution parameters with an uncertainty of ±10% and a confidence level of 90% under the assumption of independent samples, and it is found that approximately 250 independent observations are required to fit the Weibull distribution parameters. Also presented is an evaluation of Weibull fitting methods and determination of the fitting method based on the first and third moments to exhibit the “best” performance for pure Weibull distributions. Further examined is the ability to generalize parameter uncertainty bounds presented previously by Barthelmie and Pryor for distribution parameter estimates from sparse datasets; these were found to be robust and hence generally applicable to remotely sensed wind speed data series.

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J. T. Schoof, T. W. Ford, and S. C. Pryor

Abstract

Humidity is a key determinant of heat wave impacts, but studies investigating changes in extreme heat events have not differentiated between events characterized by high temperatures and those characterized by simultaneously elevated temperature and humidity. The authors present a framework, using air temperature (T) and equivalent temperature (T E; a measure combining temperature and specific humidity), to examine changes in local percentile-based extreme heat events characterized by high temperature (T only) and those with high temperature and humidity (T-and-T E events). Application to one observational dataset (PRISM), four reanalysis products (1981–2015), and seven U.S. regions reveals widespread changes in heat wave characteristics over the 35-yr period. Agreement among the datasets employed on several heat wave metrics suggests that many of the findings are robust. With the exception of the northern plains region, all regions experienced increases in both T-only and T-and-T E heat wave day (HWD) frequency in each of the reanalyses. In the northern plains, all datasets have negative trends in T-only HWD frequency and positive trends in T-and-T E HWD frequency. Trends in HWD frequency were generally accompanied by changes in the spatial footprint in heat wave conditions. Temperature has increased significantly during T-only HWDs in the western regions, while increases in T E during T-and-T E HWDs have occurred in the central United States and Northeast region. These findings suggest that equivalent temperature provides an alternative perspective on the evolution of regional heat wave climatology. Studies considering changes in regional heat wave impacts should carefully consider the role of atmospheric moisture.

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S. C. Pryor, I. G. McKendry, and D. G. Steyn

Abstract

The Lower Fraser Valley of British Columbia is currently experiencing rapid population growth and episodically suffers elevated oxidant concentrations, the frequency of which is linked to meteorological conditions on the synoptic scale. This study is a first step toward developing and validating a methodology for “declimatizing” air quality data so that postulated effects of changing emissions patterns can be addressed. Principal component analysis of gridded fields at three atmospheric levels (sea level–reduced surface pressure, 850-mb height, and 500-mb height) yields four principal components (or modes of the atmospheric circulation) that account for over 83% of geophysical dataset variance. Daily component scores from these components are used as independent parameters in a region equation of the daily maximum ozone concentrations at a site (Rocky Point Park) in Vancouver over five summers (1984–88, inclusive). The coefficients in this equation are used to construct another algorithm that is used to predict maximum daily ozone concentrations at this site during the summers of 1989–92 on the basis of synoptic-scale meteorology. The algorithm correctly predicts the low frequency of ozone episodes in the July 1989–July 1992 period but cannot account for the reduction in daily maximum ozone concentrations on nonexceedance days at Rocky Point Park over this period. The implications of these findings are that during the summers of 1989–92 meteorological conditions on the synoptic scale were not conducive to the occurrence of ozone exceedances but that the reduction in average daily maximum ozone concentrations cannot be accounted for on the basis of synoptic-scale meteorological variability as parameterized by the component scores.

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H. Wang, R. J. Barthelmie, A. Clifton, and S. C. Pryor

Abstract

Defining optimal scanning geometries for scanning lidars for wind energy applications remains an active field of research. This paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of its high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. The radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.

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