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At least 451 records · Page 25

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗

Connecting Global Modes of Variability to Climate in High Mountain Asia

Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.

54 ENVIRONMENTAL SCIENCES↗

Follow-up Studies of Five Cataclysmic Variable Candidates Discovered by LAMOST

We report follow-up observations of five cataclysmic variable candidates from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) published by Hou et al. LAMOST J024048.51+195226.9 is the most unusual of the five; an early-M type secondary star contributes strongly to its spectrum, and its spectral and photometric behavior are strikingly reminiscent of the hitherto-unique propeller system AE Aqr. We confirm that a 7.34 hr period discovered in the Catalina survey data is orbital. Another object, LAMOST J204305.95+341340.6, appears to be a near twin of the novalike variable V795 Her, with an orbital period in the so-called 2–3 hr “gap.” LAMOST J035913.61+405035.0 is evidently an eclipsing, weakly outbursting dwarf nova with a 5.48 hr period. Our spectrum of LAMOST J090150.09+375444.3 is dominated by a late-type secondary and shows weak, narrow Balmer emission moving in phase with the absorption lines, but at lower amplitude; we do not see the He ii λ4686 emission evident in the published discovery spectrum. We again confirm that a period from the Catalina data, in this case 6.80 hr, is orbital. LAMOST J033940.98+414805.7 yields a radial-velocity period of 3.54 hr, and its spectrum appears to be typical of novalike variables in this period range. The spectroscopically selected sample from LAMOST evidently includes some interesting cataclysmic variables that have been unrecognized until now, apparently because of the relatively modest range of their photometric variations.

79 ASTRONOMY AND ASTROPHYSICS↗

Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production

Abstract. The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. We evaluate wake variability and annual energy production with the first yearlong modeling assessment using the Weather Research and Forecasting model, deploying 12 MW turbines across the domain at a density of 3.14 MW km−2, matching the planned density of 3 MW km−2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. We also provide a first step towards uncertainty quantification by testing the amount of added turbulence kinetic energy (TKE) by 0 % and 100 %. We provide a sensitivity analysis by additionally comparing 25 % and 50 % for a short case study period. The strongest wakes, propagating 55 km, occur in summertime stable stratification, just when New England's grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than the diurnal variability of wakes. Overall, yearlong simulated wake impacts reduce power output by a range between 38.2 % and 34.1 % (for 0 %–100 % added TKE). Internal wakes cause greater yearlong power losses, from 29.2 % to 25.7 %, compared to external wakes, from 14.7 % to 13.4 %. The overall impact is different from the linear sum of internal wakes and external wakes due to non-linear processes. Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy from wind turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production to New England grid demand and find that the lease areas can supply 58.8 % to 61.2 % of annual load. We note that the results of this assessment are not intended to make nor are they suitable to make commercial judgments about specific wind projects.

17 WIND ENERGY↗

II. Aerodynamic research relative to variable-sweep multimission aircraft

The development of a multimission military aircraft would be highly desirable both from the standpoint of easing the strain on the national budget by reducing the number of aircraft types and of providing versatility which would increase the effectiveness of the aircraft in the performance of a given mission. Some of the capabilities which might be required of such an aircraft are shown in figure 1 along with their respective aerodynamic and configuration requirements. The first three capabilities are grouped together since they all require good subsonic characteristics. The first, a long loiter capability for combat air patrol and the second, a long ferry range for efficient aircraft deployment both require a high subsonic lift-drag ratio. The third capability, STOL, is desirable for carrier and short-field operation and requires the development of high lift. All three of these capabilities can best be obtained with a high-aspect-ratio wing having a large span and a low-sweep angle. The fourth capability is that of a high-altitude supersonic attack or intercept and requires a high lift-drag ratio at supersonic speeds which dictates a rather slender configuration with a moderate-span wing which is either very thin or highly swept. The fifth capability listed in figure 1 is that of a low-altitude high-speed attack that would increase the probability of long-range penetration of antiaircraft defenses. The high dynamic pressures encountered on the deck at high speeds require a low-lift-curve slope to reduce the gust-induced normal accelerations, and low friction and wave drag (drag due to lift is insignificant at high dynamic pressures) to assure sufficient speed and range. In order to best satisfy these requirements, a slender aircraft having little or no wing is required. It is apparent from figure 1 that these five capabilities are highly incompatible and that an efficient multimission aircraft will require a means of varying its aerodynamic characteristics. This can be best accomplished with some type of variable-wing geometry. There are, of course, several types of variable wing geometry. However, in view of the extremely large variations in wing span desired, variable wing sweep, as indicated In the lower right sketch of figure 1, appears to provide the best method. The Langley Research Center of the National Aeronautics and Space Administration has therefore initiated a research program to provide the aerodynamic information needed for the development of a variable-sweep multimission military aircraft, and it is the purpose of this paper to briefly describe some of the results of this program.

Military aircraft↗

Investigation of North American Vegetation Variability under Recent Climate: A Study Using the SSiB4/TRIFFID Biophysical/Dynamic Vegetation Model

Recent studies have shown that current dynamic vegetation models have serious weaknesses in reproducing the observed vegetation dynamics and contribute to bias in climate simulations. This study intends to identify the major factors that underlie the connections between vegetation dynamics and climate variability and investigates vegetation spatial distribution and temporal variability at seasonal to decadal scales over North America (NA) to assess a 2-D biophysical model/dynamic vegetation model's (Simplified Simple Biosphere Model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID)) ability to simulate these characteristics for the past 60 years (1948 through 2008). Satellite data are employed as constraints for the study and to compare the relationships between vegetation and climate from the observational and the simulation data sets. Trends in NA vegetation over this period are examined. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation, which describes the population dynamics of species competing for some common resource, have been identified as having major impacts on vegetation spatial distribution and obtaining proper initial vegetation conditions in SSiB4/TRIFFID. The finding that vegetation competition coefficients significantly affect vegetation distribution suggests the importance of including biotic effects in dynamical vegetation modeling. The improved SSiB4/TRIFFID can reproduce the main features of the NA distributions of dominant vegetation types, the vegetation fraction, and leaf area index (LAI), including its seasonal, interannual, and decadal variabilities. The simulated NA LAI also shows a general increasing trend after the 1970s in responding to warming. Both simulation and satellite observations reveal that LAI increased substantially in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S. on vegetation are also evident from decreases in the simulated and satellite-derived LAIs. Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental-scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with differentmodels and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.

climate variability↗

Interannual to Decadal Variability of Ocean Evaporation as Viewed from Climate Reanalyses

Questions we'll address: Given the uncoupled framework of "AMIP" (Atmosphere Model Inter-comparison Project) experiments, what can they tell us regarding evaporation variability? Do Reduced Observations Reanalyses (RedObs) using Surface Fluxes and Clouds (SFC) pressure (and wind) provide a more realistic picture of evaporation variability? What signals of interannual variability (e.g. El Nino/Southern Oscillation (ENSO)) and decadal variability (Interdecadal Pacific Oscillation (IPO)) are detectable with this hierarchy of evaporation estimates?

Climate Variability↗

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

uncertainty↗

An Assessment of Multimodel Simulations for the Variability of Western North Pacific Tropical Cyclones and Its Association with ENSO

An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño-Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño-namely, eastern Pacific (EP) and central Pacific (CP) El Niño-and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.

climate models↗

Comparing Proxy and Model Estimates of Hydroclimate Variability and Change over the Common Era

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations.We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

Common Era↗

Interpreting Precession-Driven δ O-18 Variability in the South Asian Monsoon Region

Speleothem records from the South Asian summer monsoon (SASM) region display variability in the ratio of O-18 and O-16 (δ O-18) in calcium carbonate at orbital frequencies. The dominant mode of variability in many of these records reflects cycles of precession. There are several potential explanations for why SASM speleothem records show a strong precession signal, including changes in temperature, precipitation, and circulation. Here we use an Earth system model with water isotope tracers and water-tagging capability to deconstruct the precession signal found in SASM speleothem records. Our results show that cycles of precession-eccentricity produce changes in SASM intensity that correlate with local temperature, precipitation, and δ O-18. However, neither the amount effect nor temperature differences are responsible for the majority of the SASM δ O-18 variability. Instead, changes in the relative moisture contributions from different source regions drive much of the SASM δ O-18 signal, with more nearby moisture sources during Northern Hemisphere summer at aphelion and more distant moisture sources during Northern Hemisphere summer at perihelion. Further, we find that evaporation amplifies the δ O-18 signal of soil water relative to that of precipitation, providing a better match with the SASM speleothem records. This work helps explain a significant portion of the long-term variability found in SASM speleothem records.

paleoclimate↗

Using the Diurnal Variability in GeoNEX TOA Reflectances for Earth Monitoring

Observations from the third-generation geostationary satellite instruments (GOES 16/17 ABI, Himawari 8/9 AHI, and etc.) have spatial resolution and spectral band configurations comparable to flagship LEO sensors (e.g., MODIS/VIIRS). More importantly, these data are acquired at very high temporal resolution, faithfully recording the variations of the full disk of Earth at every 5-10 minutes. They thus provide unique information about Earth’s atmosphere and surface. In order to explore the unique information content of geostationary data, this study systematically analyzes the diurnal variability in the GeoNEX L1G TOA reflectance products and compares them to simulated results by state-of-the-art radiative transfer codes. Our results show that • The smoothness of the TOA reflectance diurnal cycle provides a convenient and reliable way to identify stable atmospheric conditions and filter out passing clouds/shadows. • The diurnal variability of the blue band (0.47µm) reflectance is regulated mainly by atmospheric optical conditions over a majority of land cover types. As such, the diurnal variability of the blue band data allows us to retrieve AOD without invoking the use of spectral band ratios (SRC) as in previous algorithms. • In comparison, the diurnal variability of the short-wave infrared band (2.2µm) BRFs is mainly regulated by surface reflectance and the sun-target-satellite geometry. This information allows us to test and, if suitable, retrieve surface BRDF parameters. • Spectral band ratios, especially those between the 2.2µm and 0.47µm bands, are not constant but vary by locations and sun-target-satellite geometries. Our analysis clearly demonstrates that the information provided in high-frequent geostationary observations is unique and complementary to LEO sensors. Therefore, a synergy of GEO and LEO (and other) sensors has the great potential to improve existing remote sensing models and algorithms for better Earth monitoring.

Diurnal Variability↗

Evaluation of a Variable Facesheet Liner Configuration in Grazing Incidence for Broadband Noise Reduction

Abstract Tests were conducted in the NASA Langley Grazing Flow Impedance Tube (GFIT) to determine the broadband noise reduction capability of a variable facesheet liner. Three uniform liners were designed to achieve sound absorption over distinct frequency regimes at Mach 0.0. Each liner was fabricated and tested in the GFIT at sound pressure levels of 120 and 140 dB, and at tangential flow velocities up to Mach 0.5. A variable facesheet liner was fabricated to combine the geometries of these three liners, such that the facesheet geometry (hole diameter and porosity) was varied across the liner surface. The Prony method was used to educe the impedance of each sample, and these impedances were input to the CHE (Convected Helmholtz Equation) propagation code to predict the acoustic pressure profiles in the GFIT. Comparisons of predicted and measured acoustic pressure profiles were used to confirm the uniformity of all four liners, and to demonstrate the suitability of the CHE code in analysis of the variable facesheet concept. Results showed good comparison at no flow and Mach 0.3, and acceptable comparison at Mach 0.5. The variable facesheet liner provides enhanced broadband noise reduction at the no-flow condition for which it was designed, but further optimization is needed to target flow conditions.

acoustic↗

Evaluation of a Variable Facesheet Liner Configuration in Grazing Incidence for Broadband Noise Reduction

Tests were conducted in the NASA Langley Grazing Flow Impedance Tube (GFIT) to determine the broadband noise reduction capability of a variable facesheet liner. Three uniform liners were designed to achieve sound absorption over distinct frequency regimes at Mach 0.0. Each liner was fabricated and tested in the GFIT at sound pressure levels of 120 and 140 dB, and at tangential flow velocities up to Mach 0.5. A variable facesheet liner was fabricated to combine the geometries of these three liners, such that the facesheet geometry (hole diameter and porosity) was varied across the liner surface. The Prony method was used to educe the impedance of each sample, and these impedances were input to the CHE (Convected Helmholtz Equation) propagation code to predict the acoustic pressure profiles in the GFIT. Comparisons of predicted and measured acoustic pressure profiles were used to confirm the uniformity of all four liners, and to demonstrate the suitability of the CHE code in the analysis of the variable facesheet concept. Results showed good comparison at no flow and at Mach 0.3, and acceptable comparison at Mach 0.5. The variable facesheet liner provided enhanced broadband noise reduction at the no-flow condition for which it was designed, but further optimization is needed to target flow conditions.

acoustic↗

Analysis of Igniter/Promoter Material Effects on Burn Length Variability in Astm G124 Standard Testing

ASTM G124 refers to the “Standard Test Method for Determining the Combustion Behavior of Metallic Materials in Oxygen Enriched Atmospheres”. Major test parameters are well defined in the standard and a detailed description of how to set up and conduct the test is also included. However, one variable - the igniter/promoter system - is not clearly restricted or specified. Due to the fact that this igniter/promoter system is not definitively specified, multiple materials have been used. This lack of specificity in igniter/promoter material was identified as a potential source of variability in test results, and as such has been selected for this study as a parameter to analyze and identify if the igniters/promoters should be standardized. For that purpose, several igniter/promoter systems have been selected (that were currently in use at various laboratories) which would be tested via ASTM G124 with Inconel 718 test rods. Testing was conducted over two phases – the first for screening promoter effects in the transition region of the material, and the second for comparing measured flammability thresholds identified through testing by each igniter/promoter type. The results of this study have found that igniter/promoter material is not a statistically significant factor in the variability of burn length in test samples. Initial results showing variability was likely due to small sample size, as the issue became less pronounced once more samples were tested and more data generated. Each of the igniter/promoter systems tested were effective at determining flammability thresholds and so it is concluded that no specific igniter/promoter needs to be identified in the ASTM G124 test standard.

oxygen compatibility↗

Connecting Global Modes of Variability to Climate in High Mountain Asia

Oscillations in global modes of variability (MoV) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Un-derstanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic Oscillation (AO), Eurasian teleconnection, Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (Nino34), with winter and summer climate in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2-m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and also using a lagged correlation analysis to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and Central China in both winter and summer and a positive correlation in Western China in summer. PRECTOT has a positive correlation with all MoV in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, espe-cially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time-windows and specific regions within HMA that exhibit high correlation between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.

teleconnections↗

Numerical Modelling of a Two-Body Point Absorber Featuring Variable Geometry

This work presents a novel wave energy converter (WEC) device concept that incorporates variable geometry modules into a two-body point absorber type WEC. The variable geometry modules consist of air inflatable bags in the surface float and a water inflatable ring in the reaction body. The variable geometry floats are able to provide greater control over the device hydrodynamics; they can be inflated or deflated to emphasize either power absorption or load shedding. The device geometry is controlled in a quasi-static fashion, while the power take-off (PTO) unit is controlled on a wave-to-wave timescale. The surface float is tethered directly to the submerged reaction body through PTO tether lines. A linear time-domain analysis, conducted using open-source Wave Energy Converter (WEC-Sim) software, was used to estimate the absorbed power of the WEC in sea states defined by the Wave Energy Prize. WEC power performance was weighted against the expected capital cost of building the load bearing structure of the device, providing an estimated ACE value. The inclusion of the variable geometry modules was shown to be effective in altering the device geometry to improve power capture with a near proportional increase in expected costs, providing a nearly constant power-to-cost ratio.

cost of energy↗

Considering the Variability of Soiling in Long-Term PV Performance Forecasting: Preprint

This study presents the development of a methodology for evaluating the variability associated with soiling on long-term PV forecasting. Independent engineering firms typically build P50 forecasts for large PV plants through the use of the PVsyst software, where monthly soiling losses are one of many inputs to the P50 model. Subsequently, long-term performance distributions, or Pvalues, are constructed through a Monte Carlo analysis that includes various factors such as: satellite irradiance modeling uncertainty, uncertainty in the PVsyst model, and long-term irradiance variability. Often the PVsyst model uncertainty is increased to account for sites with significant soiling concerns but no systematic method has been presented in the literature to specifically include soiling variability within Pvalues. In this work soiling information from 16 sites in the U.S. Southwest are combined with 20 years of rainfall data to generate 20 years of energy production with soiling losses and then subsequently generate Pvalues. The results show that the spread of Pvalues (P1-P99) can increase from 0-13% when interannual soiling variability is included.

interannual variability↗