A range of multi‐year observational data sets are used to characterize the hydroclimate of the Dallas Fort‐Worth area (DFW) and to investigate the impact of urban land cover on daily accumulated ...precipitation, RADAR composite reflectivity (cREF), and cloud top height (CTH) during the warm season. Analyses of observational data indicate rainfall rates (RR) in a 45° annulus sector 50–100 km downwind of the city are enhanced relative to an upwind area of comparable size. Enhancement of mean precipitation intensity in this annulus sector is not observed on days with spatially averaged RR > 6 mm/day. Under some flow directions, the probability of cREF >30 dBZ, occurrence of hail, and the probability of CTH >10,000 geopotential meters are also enhanced up to 200 km downwind of DFW. Two deep convection events that passed over DFW are simulated with the Weather Research and Forecasting model using a range of microphysical schemes and evaluated using RADAR observations. Model configurations that exhibit the highest fidelity in these control simulations are used in a series of perturbation experiments where the areal extent of the city is varied between zero (replacement with grassland) and eight times its current size. These perturbation experiments indicate a non‐linear response of Mesoscale Convective System properties to the urban areal extent and a very strong sensitivity to the microphysical scheme used. The impact on precipitation from the urban area, even when it is expanded to eight‐times the current extent, is much less marked for deep convection with stronger synoptic forcing.
Plain Language Summary
Urban areas are rapidly expanding and have the potential to strongly influence the local and regional climate. Long‐term warm season observations near Dallas‐Fort Worth show higher rainfall intensity and hail frequency 50–100 km downwind of the city, but those days with the heaviest precipitation are not enhanced by the city. Numerical simulations show that atmospheric responses to urbanization are very sensitive to the precise model configuration used which means there are still large uncertainties in projecting how urbanization may influence atmospheric hazards.
Key Points
Mean precipitation and hail frequency are higher downwind of Dallas‐Fort Worth except on the wettest days
Deep convection properties do not respond linearly to urban extent
Microphysical schemes affect the sign of response in metrics of deep convection to urban extent
Wind turbine performance and condition monitoring play vital roles in detecting and diagnosing suboptimal performance and guiding operations and maintenance. Here, a new seismic‐based approach to ...monitoring the health of individual wind turbine components is presented. Transfer functions are developed linking key condition monitoring properties (drivetrain and tower acceleration) to unique, robust, and repeatable seismic signatures. Predictive models for extreme (greater than 99th percentile) drivetrain and tower acceleration based on independent seismic data exhibit higher skill than reference models based on hub‐height wind speed. The seismic models detect extreme drivetrain and tower acceleration with proportions correct of 96% and 93%, hit rates of 91% and 82%, and low false alarm rates of 4% and 6%, respectively. Although new wind turbines incorporate many diagnostic sensors, seismic‐based condition/performance monitoring may be particularly useful in extending the productive lifetime of previous generation wind turbines.
We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in ...complex terrain. We show that the CNN successfully identifies and characterizes wakes in scans with varying resolutions and geometries, and can capture wake characteristics in spatially heterogeneous fields resulting from data quality control procedures and complex background flow fields. The geometry, spatial extent and locations of wakes and wake fragments exhibit close accord with results from visual inspection. The model exhibits a 95% success rate in identifying wakes when they are present in scans and characterizing their shape. To test model robustness to varying image quality, we reduced the scan density to half the original resolution through down-sampling range gates. This causes a reduction in skill, yet 92% of wakes are still successfully identified. When grouping scans by meteorological conditions and utilizing the CNN for wake characterization under full and half resolution, wake characteristics are consistent with a priori expectations for wake behavior in different inflow and stability conditions.
Surface sensible heat fluxes (SH) over Tibetan Plateau (TP) dictate the seasonal conversion, onset and maintenance of the Asian monsoon. Spatiotemproal variability in SH over central and eastern TP ...(CETP) from reanalysis products (i.e., JRA55, ERA‐Interim, NCEP1, and NCEP2) and derived using bulk transfer approximations applied to observations is characterized for all seasons during 1980–2015 and is diagnosed in the context of two important drivers of variability: wind speed and land‐air temperature difference (Tg‐Ta). In the climatological mean, SH from observations increases from east to west and exhibits obvious seasonality with highest value in spring and lowest in winter. Declines in SH prior to 2000 as manifest in the observations appears to have resulted from changes in wind speeds, and the subsequent recovery is attributable to increases in both wind speeds and air‐surface temperature gradients. The intercomparison shows that ERA‐Interim exhibits greatest accord with observations in terms of the climatological distribution and seasonality, and all reanalyses exhibit some aspects of the temporal variability and long‐term trends as manifest in the observations. However, the root causes of the long‐term variability in SH as manifest in the reanalysis products are not consistent with inferences derived from the observations.
Key Points
Evaluation of the ability of the reanalysis to capture the major spatial and seasonal patterns of sensible heat (SH) flux over the central and eastern Tibetan Plateau
Evaluation of the ability of the reanalysis to capture the longer term “trends”/periodicities in SH flux
Decomposition of the causes of the variability of SH flux to two key local drivers ‐ wind speed and thermal gradient (land‐air)
Abstract
Daily expected wind power production from operating wind farms across North America are used to evaluate capacity factors (CF) computed using simulation output from the Weather Research and ...Forecasting (WRF) Model and to condition statistical models linking atmospheric conditions to electricity production. In Parts I and II of this work, we focus on making projections of annual energy production and the occurrence of electrical production drought. Here, we extend evaluation of the CF projections for sites in the Northeast, Midwest, southern Great Plains (SGP), and southwest U.S. coast (SWC) using statewide wind-generated electricity supply to the grid. We then quantify changes in the time scales of CF variability and the seasonality. Currently, wind-generated electricity is lowest in summer in each region except SWC, which causes a substantial mismatch with electricity demand. While electricity of residential heating may shift demand, research presented here suggests that summertime CF are likely to decline, potentially exacerbating the offset between seasonal peak power production and current load. The reduction in summertime CF is manifest for all regions except the SGP and appears to be linked to a reduction in synoptic-scale variability. Using fulfillment of 50% and 90% of annual energy production to quantify interannual variability, it is shown that wind power production exhibits higher (earlier fulfillment) or lower (later fulfillment) production for periods of over 10–30 years as a result of the action of internal climate modes.
Significance Statement
Electrical power system reassessment and redesign may be needed to aid efficient increased use of variable renewables in the generation of electricity. Currently wind-generated electricity in many regions of North America exhibits a minimum in summertime and hence is not well synchronized with electricity demand, which tends to be maximized in summer. Future projections indicate evidence of reductions in wind power during summer that would amplify this offset. However, electrification of heating may lead to increased wintertime demand, which would lead to greater synchronization.
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