A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models.

In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018-2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

Datasets on hub-height wind speed comparisons for wind farms in California.

This article includes the description of data information related to the research article entitled "The future of wind energy in California: Future projections with the Variable-Resolution CESM"[1], with reference number RENE_RENE-D-17-03392. Datasets from the Variable-Resolution CESM, Det Norske Veritas Germanischer Lloyd Virtual Met, MERRA-2, CFSR, NARR, ISD surface observations, and upper air sounding observations were used for calculating and comparing hub-height wind speed at multiple major wind farms across California. Information on hub-height wind speed interpolation and power curves at each wind farm sites are also presented. All datasets, except Det Norske Veritas Germanischer Lloyd Virtual Met, are publicly available for future analysis.

Cool Roofs in Guangzhou, China: Outdoor Air Temperature Reductions during Heat Waves and Typical Summer Conditions.

In this paper, we simulate temperature reductions during heat-wave events and during typical summer conditions from the installation of highly reflective "cool" roofs in the Chinese megacity of Guangzhou. We simulate temperature reductions during six of the strongest historical heat-wave events over the past decade, finding average urban midday temperature reductions of 1.2 °C. In comparison, we simulate 25 typical summer weeks between 2004 and 2008, finding average urban midday temperature reductions of 0.8 °C, indicating that air temperature sensitivity to urban albedo in Guangzhou varies with meteorological conditions. We find that roughly three-fourths of the variance in air temperature reductions across all episodes can be accounted for by a linear regression, including only three basic properties related to the meteorological conditions: mean daytime temperature, humidity, and ventilation to the greater Guangzhou urban area. While these results highlight the potential for cool roofs to mitigate peak temperatures during heat waves, the temperature reductions reported here are based on the upper bound case, which increases albedos of all roofs (but does not modify road albedo or wall albedo).

Spatially explicit methane emissions from petroleum production and the natural gas system in California.

We present a new, spatially resolved inventory of methane (CH4) emissions based on US-EPA emission factors and publically available activity data for 2010 California petroleum production and natural gas production, processing, transmission, and distribution. Compared to official California bottom-up inventories, our initial estimates are 3 to 7 times higher for the petroleum and natural gas production sectors but similar for the natural gas transmission and distribution sectors. Evidence from published "top-down" atmospheric measurement campaigns within Southern California supports our initial emission estimates from production and processing but indicates emission estimates from transmission and distribution are low by a factor of approximately 2. To provide emission maps with more accurate total emissions we scale the spatially resolved inventory by sector-specific results from a Southern California aircraft measurement campaign to all of California. Assuming uncertainties are determined by the uncertainties estimated in the top-down study, our estimated state total CH4 emissions are 541 ± 144 Gg yr(-1) (as compared with 210.7 Gg yr(-1) in California's current official inventory), where the majority of our reported uncertainty is derived from transmission and distribution. We note uncertainties relative to the mean for a given region are likely larger than that for the State total, emphasizing the need for additional measurements in undersampled regions.

Mesoscale climatic simulation of surface air temperature cooling by highly reflective greenhouses in SE Spain.

A long-term local cooling trend in surface air temperature has been monitored at the largest concentration of reflective greenhouses in the world, at the Province of Almeria, SE Spain, associated with a dramatic increase in surface albedo in the area. The availability of reliable long-term climatic field data at this site offers a unique opportunity to test the skill of mesoscale meteorological models describing and predicting the impacts of land use change on local climate. Using the Weather Research and Forecast (WRF) mesoscale model, we have run a sensitivity experiment to simulate the impact of the observed surface albedo change on monthly and annual surface air temperatures. The model output showed a mean annual cooling of 0.25 °C associated with a 0.09 albedo increase, and a reduction of 22.8 W m(-2) of net incoming solar radiation at surface. Mean reduction of summer daily maximum temperatures was 0.49 °C, with the largest single-day decrease equal to 1.3 °C. WRF output was evaluated and compared with observations. A mean annual warm bias (MBE) of 0.42 °C was estimated. High correlation coefficients (R(2) > 0.9) were found between modeled and observed values. This study has particular interest in the assessment of the potential for urban temperature cooling by cool roofs deployment projects, as well as in the evaluation of mesoscale climatic models performance.

Effects of retrofitting emission control systems on in-use heavy diesel vehicles.

Diesel engines are now the largest source of nitrogen oxides (NO(x)) and fine particulate black carbon (soot) emissions in California. The California Air Resources Board recently adopted a rule requiring that by 2014 all in-use heavy trucks and buses meet current (2007) exhaust particulate matter (PM) emission standards. Also by 2023 all in-use heavy-duty vehicles will have to meet current NO(x) emission standards, with significant progress in achieving the requirements for NO(x) control expected by 2014. This will require retrofit or replacement of older in-use engines. Diesel particle filters (DPF) reduce PM emissions but may increase the NO(2)/NO(x) emission ratio to approximately 35%, compared to approximately 5% typical of diesel engines without particle filters. Additionally, DPF with high oxidative capacity reduce CO and hydrocarbon emissions. We evaluate the effects of retrofitting trucks with DPF on air quality in southern California, using an Eulerian photochemical air quality model. Compared to a 2014 reference scenario without the retrofit program, black carbon concentrations decreased by 12 +/- 2% and 14 +/- 2% during summer and fall, respectively, with corresponding increases in ambient ozone concentrations of 3 +/- 2% and 7 +/- 3%. NO(2) concentrations decreased by 2-4% overall despite the increase in primary NO(2) emissions because total NO(x) emissions were reduced as part of the program to retrofit NO(x) control systems on in-use engines. However, in some cases NO(2) concentrations may increase at locations with high diesel truck traffic.