Dont Mess with Texas: Getting the Lone Star State to Net-Zero by 2050

The world is decarbonizing. Many countries, companies, and financial institutions have committed to cutting their emissions. Decarbonization commitments have been issued by: 136 countries including Canada, China, and the UK, at least 16 U.S. states including New York, Louisiana, and Virginia, and a third of the largest 2,000 publicly traded companies in the world, including Apple, Amazon, and Walmart, and numerous Texas companies like ExxonMobil, American and Southwest Airlines, Baker Hughes, and AT&T.1–9 These decarbonizing countries, states, cities, and companies are Texas's energy customers. If Texas ignores the challenge to decarbonize its economy, it may eventually face the more difficult challenge of selling carbon-intensive products to customers around the world who do not want them. We are already seeing this scenario beginning to play out with France canceling a liquified natural gas deal from Texas gas producers and both U.S. and international automakers announcing shifts to electric vehicles. Proactive net-zero emissions strategies might allow Texas to maintain energy leadership and grow the economy within a rapidly decarbonizing global marketplace.Thankfully, Texas is uniquely positioned to lead the world in the transition to a carbon-neutral energy economy. With the second highest Gross State Product in the US, the Texas economy is on par with countries like Canada, Italy, or Brazil. Thus, Texas's decisions have global implications. Texas also has an abundant resource of low-carbon energy sources to harness and a world-class workforce with technical capabilities to implement solutions at a large-scale quickly and safely. Texas has a promising opportunity to lead the world towards a better energy system in a way that provides significant economic benefits to the state by leveraging our renewable resources, energy industry expertise, and strong manufacturing and export markets for clean electricity, fuels, and products. The world is moving, with or without Texas, but it is likely to move faster--and Texas will be more prosperous--if Texans lead the way.There are many ways to fully decarbonize the Texas economy across all sectors by 2050. In this analysis, we present a Business as Usual (BAU) scenario and four possible pathways to Texas achieving state-wide net-zero emissions by 2050. Figure ES-1 provides a visual comparison of scenario conditions

Impact of model improvements on 80 m wind speeds during the second Wind Forecast Improvement Project (WFIP2)

During the second Wind Forecast Improvement Project (WFIP2; October 2015&ndash;March 2017, held in the Columbia River Gorge and Basin area of eastern Washington and Oregon states), several improvements to the parameterizations used in the High Resolution Rapid Refresh (HRRR &ndash; 3&thinsp;km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST &ndash; 750&thinsp;m horizontal grid spacing) numerical weather prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configurations, with the EXP configuration including all the improved parameterizations. The impacts of the experimental parameterizations on the forecast of 80&thinsp;m wind speeds (wind turbine hub height) from the HRRR and HRRRNEST models are assessed, using observations collected by 19 sodars and three profiling lidars for comparison. Improvements due to the experimental physics (EXP vs. CNT runs) and those due to finer horizontal grid spacing (HRRRNEST vs. HRRR) and the combination of the two are compared, using standard bulk statistics such as mean absolute error (MAE) and mean bias error (bias). On average, the HRRR 80&thinsp;m wind speed MAE is reduced by 3&thinsp;%&ndash;4&thinsp;% due to the experimental physics. The impact of the finer horizontal grid spacing in the CNT runs also shows a positive improvement of 5&thinsp;% on MAE, which is particularly large at nighttime and during the morning transition. Lastly, the combined impact of the experimental physics and finer horizontal grid spacing produces larger improvements in the 80&thinsp;m wind speed MAE, up to 7&thinsp;%&ndash;8&thinsp;%. The improvements are evaluated as a function of the model's initialization time, forecast horizon, time of the day, season of the year, site elevation, and meteorological phenomena. Causes of model weaknesses are identified. Finally, bias correction methods are applied to the 80&thinsp;m wind speed model outputs to measure their impact on the improvements due to the removal of the systematic component of the errors. </div

Observation of the Urban Wind Island Effect

Urban wind island effect (UWI) is defined as a phenomenon in which boundary layer mean wind speeds in an urban area are noticeably higher than its neighboring rural areas. Unlike urban heat island effect which has been extensively studied, the UWI was only recently observed in a modeling study. Here we study existence of the UWI over Indianapolis, Indiana using wind profile measurements from two Doppler wind lidars (DWL) that were deployed in climatologically upwind and downwind of the city. Under certain atmospheric conditions higher wind speeds and turbulence were observed at the downwind site over the entire urban boundary layer outside the urban canopy layer

Observation of the Urban Wind Island Effect

Urban wind island effect (UWI) is defined as a phenomenon in which boundary layer mean wind speeds in an urban area are noticeably higher than its neighboring rural areas. Unlike urban heat island effect which has been extensively studied, the UWI was only recently observed in a modeling study. Here we study existence of the UWI over Indianapolis, Indiana using wind profile measurements from two Doppler wind lidars (DWL) that were deployed in climatologically upwind and downwind of the city. Under certain atmospheric conditions higher wind speeds and turbulence were observed at the downwind site over the entire urban boundary layer outside the urban canopy layer

Doppler Lidar in the Wind Forecast Improvement Projects

This paper will provide an overview of some projects in support of Wind Energy development involving Doppler lidar measurement of wind flow profiles. The high temporal and vertical resolution of these profiles allows the uncertainty of Numerical Weather Prediction models to be evaluated in forecasting dynamic processes and wind flow phenomena in the layer of rotor-blade operation

Entrainment and Mixing of Transported Ozone Layers: Implications for Surface Air Quality in the Western U.S.

Recently, two air quality campaigns were conducted in the southwestern United States to study the impact of transported ozone, stratospheric intrusions, and fire emissions on ground-level ozone concentrations. The California Baseline Ozone Transport Study (CABOTS) took place in May – August 2016 covering the central California coast and San Joaquin Valley, and the Fires, Asian, and Stratospheric Transport Las Vegas Ozone Study (FAST-LVOS) was conducted in the greater Las Vegas, Nevada area in May – June 2017. During these studies, nearly 1000 hours of ozone and aerosol profile data were collected with the NOAA TOPAZ lidar. A Doppler wind lidar and a radar wind profiler provided continuous observations of atmospheric turbulence, horizontal winds, and mixed layer height. These measurements allowed us to directly observe the degree to which ozone transport layers aloft were entrained into the boundary layer and to quantify the resulting impact on surface ozone levels. Mixed layer heights in the San Joaquin Valley during CABOTS were generally below 1 km above ground level (AGL), while boundary layer heights in Las Vegas during FAST-LVOS routinely exceeded 3 km AGL and occasionally reached up to 4.5 km AGL. Consequently, boundary layer entrainment was more often observed during FAST-LVOS, while most elevated ozone layers passed untapped over the San Joaquin Valley during CABOTS

Entrainment and Mixing of Transported Ozone Layers: Implications for Surface Air Quality in the Western U.S.

Recently, two air quality campaigns were conducted in the southwestern United States to study the impact of transported ozone, stratospheric intrusions, and fire emissions on ground-level ozone concentrations. The California Baseline Ozone Transport Study (CABOTS) took place in May – August 2016 covering the central California coast and San Joaquin Valley, and the Fires, Asian, and Stratospheric Transport Las Vegas Ozone Study (FAST-LVOS) was conducted in the greater Las Vegas, Nevada area in May – June 2017. During these studies, nearly 1000 hours of ozone and aerosol profile data were collected with the NOAA TOPAZ lidar. A Doppler wind lidar and a radar wind profiler provided continuous observations of atmospheric turbulence, horizontal winds, and mixed layer height. These measurements allowed us to directly observe the degree to which ozone transport layers aloft were entrained into the boundary layer and to quantify the resulting impact on surface ozone levels. Mixed layer heights in the San Joaquin Valley during CABOTS were generally below 1 km above ground level (AGL), while boundary layer heights in Las Vegas during FAST-LVOS routinely exceeded 3 km AGL and occasionally reached up to 4.5 km AGL. Consequently, boundary layer entrainment was more often observed during FAST-LVOS, while most elevated ozone layers passed untapped over the San Joaquin Valley during CABOTS

Assessment of virtual towers performed with scanning wind lidars and Ka-band radars during the XPIA experiment

© 2017 The Author(s). During the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign, which was carried out at the Boulder Atmospheric Observatory (BAO) in spring 2015, multiple-Doppler scanning strategies were carried out with scanning wind lidars and Ka-band radars. Specifically, step-stare measurements were collected simultaneously with three scanning Doppler lidars, while two scanning Ka-band radars carried out simultaneous range height indicator (RHI) scans. The XPIA experiment provided the unique opportunity to compare directly virtual-tower measurements performed simultaneously with Ka-band radars and Doppler wind lidars. Furthermore, multiple-Doppler measurements were assessed against sonic anemometer data acquired from the meteorological tower (met-tower) present at the BAO site and a lidar wind profiler. This survey shows that-despite the different technologies, measurement volumes and sampling periods used for the lidar and radar measurements- A very good accuracy is achieved for both remote-sensing techniques for probing horizontal wind speed and wind direction with the virtual-tower scanning technique