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Trends and meteorological drivers of extreme daily reservoir evaporation events in the western United States
Extreme daily evaporation from reservoir surfaces can lead to significant short-term water losses, affecting water quality, water supply, and reservoir operation strategies. Historical trends in daily reservoir evaporation events have eluded the scientific and operational communities, largely due to a lack of long-term, consistent data record. This study quantifies trends in extreme daily reservoir evaporation events at 165 major reservoirs located in the western U.S. Here, we use the place-based energy balance and aerodynamic Daily Lake Evaporation Model (DLEM) driven by multiple meteorological data products (RTMA, gridMET, Daymet) to estimate daily evaporation rates at these reservoirs from 1981 to 2022. The results—while are based on different meteorological forcing datasets—consistently indicate that the California, Lower Colorado, and Rio Grande hydrologic regions are more prone to higher daily evaporation extremes. Compared to the rest of western U.S, these three regions also experience a more pronounced increasing trend in the annual maximum daily evaporation rate, at about 0.3 mm day -1 decade -1 during 1981-2022. The results show that heat and dryness are the main drivers to the increasing trend of extreme evaporation, while extreme wind speed is the primary contributor to exceptionally high daily evaporation events across all regions. This phenomenon is particularly prominent in the arid Lower Colorado region, but less significant in the cold and humid Pacific Northwest region. We also find that the correlation between extreme wind speed and extreme evaporation degrades as the time scale increases from daily, to monthly and seasonal. Our findings have strong implications for the pattern and distribution of extreme evaporation events at the western U.S. reservoirs, and illustrate how various drivers influence extreme evaporation across different time scales.
Historical and Future Windstorms in the Northeastern United States
Large-scale windstorms represent an important atmospheric hazard in the Northeastern US (NE) and are associated with substantial socioeconomic losses. Regional simulations performed with the Weather Research and Forecasting (WRF) model using lateral boundary conditions from three Earth System Models (ESMs: Geophysical Fluid Dynamics Laboratory (GFDL), Hadley Centre Global Environment Model (HadGEM) and Max Planck Institute (MPI)) are used to quantify possible future changes in windstorm characteristics and/or changes in the parent cyclone types responsible for windstorms. WRF nested within MPI ESM best represents important aspects of historical windstorms and the cyclone types responsible for generating windstorms compared with a reference simulation performed with the ERA-Interim reanalysis for the historical climate. The spatial scale and frequency of the largest windstorms in each simulation defined using the greatest extent of exceedance of local 99.9th percentile wind speeds (U > U999) plus 50-year return period wind speeds (U50,RP) do not exhibit secular trends. Projections of extreme wind speeds and windstorm intensity/frequency/geolocation and dominant parent cyclone type associated with windstorms vary markedly across the simulations. Only the MPI nested simulations indicate statistically significant differences in windstorm spatial scale, frequency and intensity over the NE in the future and historical periods. This model chain, which also exhibits the highest fidelity in the historical climate, yields evidence of future increases in 99.9th percentile 10 m height wind speeds, the frequency of simultaneous U > U999 over a substantial fraction (5–25%) of the NE and the frequency of maximum wind speeds above 22.5 ms−1. These geophysical changes, coupled with a projected doubling of population, leads to a projected tripling of a socioeconomic loss index, and hence risk to human systems, from future windstorms.
Winds aloft statistical analysis in support of day of launch Shuttle systems evaluation
In connection with the development of the Meteorological Interactive Data Display System (MIDDS) for utilization by the Launch Systems Evaluation Advisory Team (LSEAT), requirements have been established to expand the pre-launch analysis of winds aloft for the Space Shuttle. Statistical analyses developed for the system include: comparison of pre-launch wind component profiles to wind component extremes at each altitude calculated from launch site historical data; conditional probability ellipses for wind vectors at a future time given the wind vector at an initial time; comparison of observed extreme wind shear and associated wind speed with launch site historical data utilizing the bivariate extreme value (Gumbel) distribution; estimation of extremes of wind speed or wind shear at a future time given the extremes of either variable at an initial time, utilizing the conditional extreme value distribution; power spectrum analysis for tracking wind perturbation energy in sequential pre-launch Jimsphere wind profiles.
Jimsphere wind and turbulence exceedance statistic
Exceedance statistics of winds and gusts observed over Cape Kennedy with Jimsphere balloon sensors are described. Gust profiles containing positive and negative departures, from smoothed profiles, in the wavelength ranges 100-2500, 100-1900, 100-860, and 100-460 meters were computed from 1578 profiles with four 41 weight digital high pass filters. Extreme values of the square root of gust speed are normally distributed. Monthly and annual exceedance probability distributions of normalized rms gust speeds in three altitude bands (2-7, 6-11, and 9-14 km) are log-normal. The rms gust speeds are largest in the 100-2500 wavelength band between 9 and 14 km in late winter and early spring. A study of monthly and annual exceedance probabilities and the number of occurrences per kilometer of level crossings with positive slope indicates significant variability with season, altitude, and filter configuration. A decile sampling scheme is tested and an optimum approach is suggested for drawing a relatively small random sample that represents the characteristic extreme wind speeds and shears of a large parent population of Jimsphere wind profiles.
Intense windstorms in the northeastern United States
Abstract. Windstorms are a major natural hazard in many countries. The objective of this study is to identify and characterize intense windstorms during the last 4 decades in the US Northeast and determine both the sources of cyclones responsible for these events and the manner in which those cyclones differ from the cyclone climatology. The windstorm detection is based on the spatial extent of locally extreme wind speeds at 100 m height from the ERA5 reanalysis database. During the top 10 windstorms, wind speeds exceed their local 99.9th percentile over at least one-third of land-based ERA5 grid cells in this high-population-density region of the USA. Maximum sustained wind speeds at 100 m during these windstorms range from 26 to over 43 ms−1, with wind speed return periods exceeding 6.5 to 106 years (considering the top 5 % of grid cells during each storm). Property damage associated with these storms, with inflation adjusted to January 2020, ranges from USD 24 million to over USD 29 billion. Two of these windstorms are linked to decaying tropical cyclones, three are Alberta clippers, and the remaining storms are Colorado lows. Two of the 10 re-intensified off the east coast, leading to development of nor'easters. These windstorms followed frequently observed cyclone tracks but exhibit maximum intensities as measured using 700 hPa relative vorticity and mean sea level pressure that is 5–10 times the mean values for cyclones that followed similar tracks over this 40-year period. The time evolution of wind speeds and concurrent precipitation for those windstorms that occurred after the year 2000 exhibit good agreement with in situ ground-based and remote sensing observations, plus storm damage reports, indicating that the ERA5 reanalysis data have a high degree of fidelity for large, damaging windstorms such as these. A larger pool of the top 50 largest windstorms exhibit evidence of only weak serial clustering, which is in contrast to the relatively strong serial clustering of windstorms in Europe.
Wind data for wind driven plant
Simple, averaged wind velocity data provide information on energy availability, facilitate generator site selection and enable appropriate operating ranges to be established for windpowered plants. They also provide a basis for the prediction of extreme wind speeds.
Ascent structural wind loads for the National Space Transportation System (NSTS)
An aerospace vehicle must withstand the design ascent structural load or be within any flight constraint to safely reach orbit. For the NSTS an assessment for flight readiness is made for each mission. This assessment for ascent loads and performance parameters is stated in terms of launch probability derived from samples of Jimsphere wind profiles. For the day of launch operations an allowance is made for the ascent load variability due to the wind profile variability over a 3.5-hour period. This is the current time period required to obtain a Jimsphere measurement and perform a complete load simulation prior to launch time. The load variability is derived from a sample of 3.5-hour Jimsphere wind profile pairs. It is applied as a conditional percentile value given the wind load at 3.5 hours prior to launch time. Probability models are used for these analyses. Application of the univariate, bivariate and conditional forms of the extreme value (Gumbel) probability distribution to the analysis of extreme wind speeds, wind shears and vehicle loads is described.
Predicting Wind Loading and Instability in Solar Tracking PV Arrays
Wind loading and the fluctuating pressure loads it creates on PV panel surfaces are associated with multiple degradation mechanisms and failures. Modest wind speeds create reversing loads that can initiate cell cracks and weather cracked cells. Stronger wind speeds and extreme weather events can lead to larger scale forces and the aerodynamic instability known as torsional galloping. All these effects are dependent on the complex coupling between wind speed, panel orientation, and a myriad of other hardware and site-specific factors. In this work, we present the latest developments from our work to build an open-source, high-performance computing (HPC) fluid dynamics solver to predict and mitigate these effects. This simulation package allows users to easily specify different array layouts, solar-tracking angles, panel geometries, and weather conditions before automatically generating a refined computational mesh and solving for the unsteady loading on each panel surface. Small domains (e.g., a single panel row in isolation) can be solved on a modern laptop, while larger domains or very high-fidelity studies can be solved on distributed or HPC resources with minimal modifications to the underlying problem specification. We present preliminary case studies obtained using this simulation package and highlight how increased wind speeds combined with sub-optimal tracking angles can exacerbate degradation drivers.
Validation of Weather Forecasting Products
Meteorological modeling plays a pivotal role in operational safety and emergency response at the Savannah River Site (SRS). This study focuses on verifying the Regional Atmospheric Modelling System (RAMS) Version 4.3 through Mean Bias Error (MBE) and Root Mean Square Error (RMSE) analyses of temperature, dew point, and wind speed over a decade. Using observed data from SRS, we assessed RAMS' accuracy, revealing seasonal biases and error trends. Results indicate RAMS' strengths in mild weather conditions but challenges during seasonal extremes and wind speed predictions due to measurement disparities. Future research aims to expand verification to other models and parameters, advocating for enhanced forecasting accuracy crucial for safeguarding personnel and community well-being.
Turbulence regimes in the nocturnal roughness sublayer: Interaction with deep convection and tree mortality in the Amazon
We investigated the influence of seasonality and proximity to the forest canopy on nocturnal turbulence regimes in the roughness sublayer of a Central Amazon forest. Since convective systems of different scales are common in this region, we also analyzed the effect of extreme wind gusts (propagated from convective downdrafts) on the organization of the turbulence regimes, and their potential to cause the mortality of canopy trees. Our data include high-frequency winds, temperature and ozone concentration at different heights during the dry and wet seasons of 2014. In addition, we used critical wind-speed data derived from a tree-winching experiment and a modeling study conducted in the same study site. Two different turbulence regimes were identified at three heights above the canopy: a weakly stable (WS) and a very stable regime (VS). The threshold wind speeds that mark the transition between turbulence regimes were larger during the dry season and increased as a function of the height above the canopy. The turbulent fluxes of sensible heat and momentum during the WS accounted for 88% of the entire nighttime flux. Downdrafts occurred only in the WS and favored a fully coupled state of wind flow along the canopy profile. The destructive potential of winds was four times higher than on nights without downdrafts.
WRF-simulated low-level jets over Iowa: characterization and sensitivity studies
Abstract. Output from 6 months of high-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize local low-level jets (LLJs) over Iowa for winter and spring in the contemporary climate. Low-level jets affect rotor plane aerodynamic loading, turbine structural loading and turbine performance, and thus accurate characterization and identification are pertinent. Analyses using a detection algorithm wherein the wind speed above and below the jet maximum must be below 80 % of the jet wind speed within a vertical window of approximately 20–530 m a.g.l. (above ground level) indicate the presence of an LLJ in at least one of the 14 700 4 km×4 km grid cells over Iowa on 98 % of nights. Nocturnal LLJs are most frequently associated with stable stratification and low turbulent kinetic energy (TKE) and hence are more frequent during the winter months. The spatiotemporal mean LLJ maximum (jet core) wind speed is 9.55 m s−1, and the mean height is 182 m. Locations of high LLJ frequency and duration across the state are seasonally varying, with a mean duration of 3.5 h. The highest frequency occurs in the topographically complex northwest of the state in winter and in the flatter northeast of the state in spring. Sensitivity of LLJ characteristics to the (i) LLJ definition and (ii) vertical resolution at which the WRF output is sampled is examined. LLJ definitions commonly used in the literature are considered in the first sensitivity analysis. These sensitivity analyses indicate that LLJ characteristics are highly variable with definition. Use of different definitions identifies both different frequencies of LLJs and different LLJ events. Further, when the model output is down-sampled to lower vertical resolution, the mean jet core wind speed height decreases, but spatial distributions of regions of high frequency and duration are conserved. Implementation of a polynomial interpolation to extrapolate down-sampled output to full-resolution results in reduced sensitivity of LLJ characteristics to down-sampling.
Toward CO 2 Multimeasurement Geophysical Monitoring in the North Dakota CarbonSAFE Project
Paper presented at 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16), October 23–27, 2022, Lyon, France. Overcoming data acquisition challenges associated with a lake in the study area, electrical infrastructure around the plant, noise from mine activities, complex near-surface conditions associated with reclaimed mine land, high wind speed, and extremely cold temperatures, data processing, modeling, and inversion of the baseline geophysical data demonstrated the importance of high-quality data for a CO 2 geophysical monitoring program. Implementing more advanced data acquisition and processing techniques in future monitoring surveys can further improve confidence in interpretations of geophysical survey data.
The maxometer-dynamic and static tests
The ability to withstand extreme environmental conditions, such as the high flow velocities and extreme temperatures associated with the launch of aerospace vehicles, was considered in the developement of two maxometer models which are capable of measuring extremely high wind speeds (130 m/sec) and retaining a record of the peak speed over any given time period. The dynamic and static tests of these models are reported, along with pertinent results.
Mountain winds (revisited)
The prediction of extremely high wind speeds, at ground level on the downstream side of a mountain range, is possible by solving the initial value problem for a two-layered nonlinear shallow water model of the atmosphere. Three different numerical methods are described to find the solutions which may involve shocks: (1) the vonNeumann-Richtmyer artificial viscosity method, (2) a filtering scheme, and (3) a hybrid method.
Evaluation of Nimbus 7 SMMR sensor with airborne radiometers and surface observations in the Norwegian Sea
Measurements made by the Nimbus 7 SMMR are compared with near simultaneous observations using the airborne SMMR simulator and with surface observations. The area of the test is in the Norwegian Sea between Bear Island and Northern Norway. It is noted that during the observation period two low-pressure systems were located in the test area, giving a spatial wind variation from 3-20 m/s. It is shown that the use of the currently available brightness temperatures and algorithms for SMMR does not give universally satisfactory results for SST and wind speed under extreme weather conditions. In addition, the SMMR simulator results are seen as indicating the need for more work on calibration.
Some tests of flat plate photovoltaic module cell temperatures in simulated field conditions
The nominal operating cell temperature (NOCT) of solar photovoltaic (PV) modules is an important characteristic. Typically, the power output of a PV module decreases 0.5% per deg C rise in cell temperature. Several tests were run with artificial sun and wind to study the parametric dependencies of cell temperature on wind speed and direction and ambient temperature. It was found that the cell temperature is extremely sensitive to wind speed, moderately so to wind direction and rather insensitive to ambient temperature. Several suggestions are made to obtain data more typical of field conditions.