Make the Most of Online Weatherization Training Resources
This presentation provides an overview of federal online training resources available for the weatherization workforce.
48 EE - Weatherization and Intergovernmental Progr↗
SEARCH · Engineering Papers
Results for “Weather”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Climatic effects of irrigation over the Huang-Huai-Hai Plain in China simulated by the weather research and forecasting model: Simulated Irrigation Effects in China
In this study, we apply the Weather Research and Forecasting model coupled with an operational-like irrigation scheme to investigate the climatic effects of irrigation over the Huang-Huai-Hai plain (3HP) in China. Multiple numerical experiments with irrigation off/on during spring, summer and both spring and summer are conducted, respectively. Our results show that the warm bias in surface temperature and dry bias in soil moisture are reduced over the 3HP region during growing seasons when irrigation is turned on in the model. Air temperature during non-growing seasons is also affected by irrigation due to the persistent effects of soil moisture on land-air energy exchanges and ground heat storage. Irrigation can induce a cooler planetary boundary layer (PBL) during growing seasons, causing a wetter PBL with more low-level clouds during spring but relatively dryer PBL in summer. Further analyses indicate that the dryer summer is highly related to the changes in the East Asian summer monsoon (EASM) circulation that is modified by irrigation effect. Spring irrigation may induce a decreased land-ocean thermal contrast, leading to a possible weaker EASM. Summer irrigation, however, evidently cools the atmosphere column and forces a southward shift of the upper-level jet, which results in more precipitation in Yangtze River basin but less over southern and northern China during summer.
3HP↗
Reduced accrual of mineral-associated organic matter after two years of enhanced rock weathering in cropland soils, though no net losses of soil organic carbon
Abstract Enhanced rock weathering (ERW), the application of crushed silicate rock to soil, can remove atmospheric carbon dioxide by converting it to (bi) carbonate ions or solid carbonate minerals. However, few studies have empirically evaluated ERW in field settings. A critical question remains as to whether additions of crushed rock might positively or negatively affect soil organic matter (SOM)—Earth’s largest terrestrial organic carbon (C) pool and a massive reservoir of organic nitrogen (N). Here, in three irrigated cropland field trials in California, USA, we investigated the effect of crushed meta-basalt rock additions on different pools of soil organic carbon and nitrogen (i.e., mineral-associated organic matter, MAOM, and particulate organic matter, POM), active microbial biomass, and microbial community composition. After 2 years of crushed rock additions, MAOM stocks were lower in the upper surface soil (0–10 cm) of plots with crushed rock compared to unamended control plots. At the 2 sites where baseline pre-treatment data were available, neither total SOC nor SON decreased over the 2 years of study in plots with crushed rock or unamended control plots. However, the accrual rate of MAOM-C and MAOM-N at 0–10 cm was lower in plots with crushed rock vs. unamended controls. Before ERW is deployed at large scales, our results suggest that field trials should assess the effects of crushed rock on SOM pools, especially over multi-year time scales and in different environmental contexts, to accurately assess changes in net C and understand the mechanisms driving interactions between ERW and SOM cycling.
58 GEOSCIENCES↗
A case study of the Weather Research and Forecasting model applied to the Joint Urban 2003 tracer field experiment. Part 2: Gas tracer dispersion
Here, the Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The first method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model’s Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.
54 ENVIRONMENTAL SCIENCES↗
Sensitivity of Turbine-Height Wind Speeds to Parameters in the Planetary Boundary-Layer Parametrization Used in the Weather Research and Forecasting Model: Extension to Wintertime Conditions
This work extends the model sensitivity analysis of Yang et al. (Boundary-Layer Meteorology, 2017, Vol. 162, 117-142) to include results for February 2011, in addition to May of the same year. We investigated the sensitivity of simulated hub-height wind speeds to the selection of 26 parameters applied in the Mellor-Yamada-Nakanishi-Niino (MYNN) planetary boundary-layer parameterization in the Weather Research and Forecasting (WRF) model, including parameters used to represent the dissipation of turbulence kinetic energy (TKE), Prandtl number (Pr), and turbulence length scales. Differences in the sensitivity of the ensemble of simulated wind speed to the various parameters can largely be explained by changes in the static stability. The largest monthly differences were found during the day, while the sensitivity to many of the parameters during the night were similar regardless of the month. This finding is consistent with an increased frequency of day-time stable conditions in February compared to May. The spatial variability of the sensitivity to TKE dissipation, Pr, and k can also be attributed to variability in the static stability across the domain at any point in time.
parametrization schemes, Parametric sensitivity, P↗
Silicate weathering in anoxic marine sediment as a requirement for authigenic carbonate burial
We emphasize the importance of marine silicate weathering (MSiW) reactions in anoxic sediment as fundamental in generating alkalinity and cations needed for carbonate precipitation and preservation along continental margins. We use a model that couples thermodynamics with aqueous geochemistry to show that the CO 2 released during methanogenesis results in a drop in pH to 6.0; unless these protons are buffered by MSiW, carbonate minerals will dissolve. We present data from two regions: the India passive margin and the active subduction zone off Japan, where ash and/or rivers supply the reactive silicate phase, as reflected in strontium isotope data. Offshore India and Korea, alteration of continent-derived silicates results in pore water enriched in radiogenic 87 Sr, with 87 Sr/ 86 Sr ratios as high as 0.7095 and 0.7104, respectively. Off Japan, strontium in pore water influenced by ash alteration is depleted in 87 Sr, with 87 Sr/ 86 Sr as low as 0.7065. Carbonate minerals formed by alkalinity and cations generated through MSiW carry these strontium isotopic signals, and are typically dolomite, siderite, and Fe-rich calcite. These contrast with the aragonite and high-magnesium calcite that form during anaerobic oxidation of methane and incorporate the coeval seawater 87 Sr/ 86 Sr signal. We show that MSiW is necessary for authigenic carbonate formation and preservation along continental margins, which remove carbon from Earth’s surface at rates previously estimated to be at least 10 12 mol yr -1 . In addition, these authigenic carbonates are of relevance to studies of the deep biosphere, fluid flow, seismogenesis, slope stability, and reservoir characteristics.
54 ENVIRONMENTAL SCIENCES↗
Microgrid energy scheduling under uncertain extreme weather: Adaptation from parallelized reinforcement learning agents
Microgrids are useful solutions for integrating renewable energy resources and providing seamless green electricity to minimize carbon footprint. In recent years, extreme weather events happened often worldwide and caused significant economic and societal losses. Such events bring uncertainties to the microgrid energy scheduling problems and increase the challenges of microgrid operation. Traditional optimization approaches suffer from the inaccuracy of the uncertain microgrid model and the unseen events. Existing reinforcement learning (RL) - based approaches are also hampered by the limited generalization and the increasing computational burden when stochastic formulations are required to accommodate the uncertainties. This paper proposes a new parallelized reinforcement learning (PRL) method based on the probabilistic events to handle the microgrid energy uncertainties. Specifically, several local learning agents are employed to interact with pertinent microgrid environments in a distributed manner and report outcomes to the global agent, which will optimize microgrid energy resources online during extreme events. The stochastic microgrid energy optimization problem is reformulated to include all possible scenarios with probabilities. The advantage estimate functions of learning agents are designed with a backward sweep to transfer the outcomes to the value function updating process. Two simulation studies, stochastic optimization and online testing, are performed to compare with several existing RL approaches. Results substantiate that the proposed PRL method can achieve up to 20% optimization performance improvement with 4 and 28 times less computation cost than Q-learning with experience replay and multi-agent Q-learning approaches, respectively.
24 POWER TRANSMISSION AND DISTRIBUTION↗
ENSO regimes and the late 1970's climate shift: The role of synoptic weather and South Pacific ocean spiciness
South Pacific subtropical density compensated temperature and salinity (spiciness) anomalies are known to be associated with decadal equatorial variability, however, the mechanisms by which such disturbances are generated, advect and the degree to which they modulate the equatorial thermocline remains controversial. During the late 1970's a climate regime transition preceded a period of strong and sustained El Nino events. Using an ocean general circulation model forced by the constituent mechanical and thermodynamic components of the reanalysed atmosphere we show that the late 1970's transition coincided with the arrival of a large-scale, subsurface cold and fresh water anomaly in the central tropical Pacific. An ocean reanalysis for the period 1990–2007 that assimilates subsurface Argo, XBT and CTD data, reveals that disturbances occur due to the subduction of negative surface salinity anomalies from near 30° S, 100° W which are advected along the σ=25–26 kgm{sup −3} isopycnal surfaces. These anomalies take, on average, seven years to reach the central equatorial Pacific where they may substantially perturb the thermocline before the remnants ultimately ventilate in the region of the western Pacific warm pool. Positive (warm–salty) disturbances, known to occur due to late winter diapycnal mixing and isopycnal outcropping, arise due to both subduction of subtropical mode waters and subsurface injection. On reaching the equatorial band (10° S–0° S) these disturbances tend to deepen the thermocline reducing the model's ENSO. In contrast the emergence of negative (cold–fresh) disturbances at the equator are associated with a shoaling of the thermocline and El Nino events. Process studies are used to show that the generation and advection of anomalous density compensated thermocline disturbances critically depend on stochastic forcing of the intrinsic ocean by weather. We further show that in the absence of the inter-annual component of the atmosphere forcing Central Pacific El Nino events are manifest.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Ferrite grain refinement in low carbon Cu–P–Cr–Ni–Mo weathering steel at various temperatures in the (α + γ) region
Self-designed Cu–P–Cr–Ni–Mo weathering steel was subjected to compression test to determine the mechanism of ferrite grain refinement from 750 °C to 925 °C. Optical microscopic images showed that ferrite grain size declined, whereas the ferrite volume fraction increased with increasing compression temperature. Electron backscatter diffraction patterns revealed that several low-angle boundaries shifted to high-angle boundaries, thereby generating fine ferrite grains surrounded by high-angle boundaries. Numerous low-angle boundaries were observed within ferrite grains at 750 °C, which indicated the existence of pre-eutectoid ferrite. Results showed that ferrite grain refinement could be due to continuous dynamic recrystallization at 750 °C and 775 °C, and deformation-induced ferrite transformation could be the main mechanism at 800 °C and 850 °C. Fine equiaxed ferrite grains with size ranging from 1.77 μm to 2.69 μm were produced in the (α + γ) dual-phase region. - Graphical abstract: There is a close relationship between the microstructure evolution and flow curves during deformation. Fine equiaxed ferrite grains with size ranging from 1.77 μm to 2.69 μm were achieved in the (α + γ) dual-phase region. Ferrite grain refinement could be due to continuous dynamic recrystallization at 750 °C and 775 °C, and deformation-induced ferrite transformation at 800 °C and 850 °C. The occurrence of deformation-induced ferrite transformation and continuous dynamic recrystallization can be monitored by analysis of flow curves and microstructures. Deformation-induced ferrite transformation leads to the dynamic softening in flow curve when temperature just below A{sub r3}, while the dynamic softening in flow curve is ferrite continuous dynamic recrystallization (Special Fig. 5b). - Highlights: • Compression deformation was operated at temperatures from 750 °C to 925 °C at a strain rate of 0.1 s–1, and a strain of 1.2. • Fine equiaxed ferrite grains of ~1.77–2.19 μm were obtained at 750 °C and 775 °C via continuous dynamic recrystallization. • Ferrite grain size of ~2.31–2.69 μm at 800 °C and 850 °C can be obtained by deformation-induced ferrite transformation. • With decreasing deformation temperature the average grain size of ferrite decreased while volume fraction increased. • Ferrite refinement was from deformation-induced ferrite to continuous dynamic recrystallization as temperature reduced.
36 MATERIALS SCIENCE↗
Microphysical Piggybacking in the Weather Research and Forecasting Model
Abstract This paper presents incorporation of the microphysical piggybacking into the Weather Research and Forecasting (WRF) model. Microphysical piggybacking is to run a single simulation applying two microphysical schemes, the first scheme driving the simulation and the second piggybacking this simulated flow. “Driving the simulation” means that the simulated microphysical processes, affect the cloud buoyancy and thus force the simulated flow. In contrast, the piggybacking variables are advected by the simulated flow and undergo microphysical transformation, but they do not affect the simulated flow (like in prescribed flow—kinematic—simulations). The two sets of variables (driver and piggybacker) include temperature, water vapor mixing ratio, and all microphysical variables. We provide details of implementing piggybacking into the WRF model, illustrate its applications, and demonstrate the benefits of this methodology in two idealized three‐dimensional cases: (a) a squall line case applying two microphysics schemes, the Thompson bulk microphysics scheme and the University of Pécs/NCAR bin (UPNB) scheme. The piggybacking simulations revealed that the microphysics‐dynamics interaction plays a more important role than the pure microphysical size sorting effect in the transition zone formation. (b) A case of daytime shallow‐to‐deep convective development over land. This case uses the UPNB scheme and contrasts convection developing in environments with either pristine or polluted cloud condensation nuclei (CCN). The piggybacking results indicated that the increase of cloud cover and decrease of supersaturation are mainly associated with the microphysical effect of increasing CCN while the change of precipitation on the ground is also influenced by microphysics‐dynamics interactions.
54 ENVIRONMENTAL SCIENCES↗
Enhanced Simulation of Atmospheric Blocking in a High‐Resolution Earth System Model: Projected Changes and Implications for Extreme Weather Events
Atmospheric blocking is closely linked to the occurrence of extreme weather events. However, low-resolution Earth system models often underestimate the frequency of blocking, undermining confidence in future projections. Here, in this study, we use the high-resolution Community Earth System Model (CESM-HR; 25 km atm and 10 km ocean) to show that CESM-HR reduces biases in atmospheric blocking for both winter and summer, particularly for events lasting longer than 10 days. This improvement is partly due to reduced sea surface temperature biases at higher resolution. Additionally, applying a bias correction to the 500 hPa geopotential height further enhances blocking frequency simulations, highlighting the crucial role of the mean state. Under the Representative Concentration Pathway 8.5 scenario, CESM-HR projects a decrease in wintertime blocking over regions such as the Euro-Atlantic and Chukchi-Alaska, consistent with previous studies. In contrast, summer blocking is expected to become more frequent and persistent, driven by weakened zonal winds. The blocking center shifts from historical locations over Scandinavia and eastern Russia to central Eurasia, significantly increasing blocking over the Ural region. Summer blocking frequency over the Scandinavia-Ural region may eventually surpass historical winter blocking over the Euro-Atlantic. This increase in summer blocking could exacerbate summer heatwaves in a warming climate, making severe heatwaves, like those observed recently, more common in the future.
Atmospheric blocking↗
Modeling the impact of extreme weather events and future climate on the radiologically contaminated sites of Enewetak Atoll
Enewetak Atoll underwent 43 historical nuclear tests from 1948 to 1958, including the first hydrogen bomb test, resulting in a substantial nuclear material fallout contaminating the Atoll and the lagoon waters. The radionuclide fallout material deposited in lagoon sediments and land soil will remain for decades to come. With intensifying climate and extreme weather events, the possibility of redistribution of deposited radionuclide material has become a great concern. This study uses a numerical modeling approach to estimate the potential elevated radionuclide concentrations that can be distributed during storm events under current and future climates. We simulated three historical storm scenarios that are most likely to impact Atoll’s environment and remobilize the radionuclide-bound sediments. WRF-ARW was used to reconstruct these storm scenarios under current year (2015) and future year (2090) climates. Storm-induced ocean hydrodynamics conditions were generated using FVCOM. FVCOM-ICM was externally coupled to simulate the fate and transport of radionuclides. Given that the 239 Pu is the largest inventory of the lagoon and Atoll islands, the model results show the highest average 239 Pu concentration that an island may be exposed to is 3.25E-4 Bq/m 3 (becquerel per cubic meters), which is an increase of 84 times the average baseline/existing 239 Pu concentration without the storm conditions. The overall increase in 239 Pu average over all the islands of Atoll is about 20 folds relative to the baseline concentration. Despite the high relative increase ratios, the significantly low activity concentrations may not pose an immediate exposure risk. However, due to the limitations of the study and uncertainties/biases in the historical data used, further research supported by field surveys to better characterize the current contamination level may be needed to make more accurate predictions.
54 ENVIRONMENTAL SCIENCES↗
Using stochastic activity networks to study the energy feasibility of automatic weather stations
Automatic Weather Stations (AWSs) are systems equipped with a number of environmental sensors and communication interfaces used to monitor harsh environments, such as glaciers and deserts. Designing such systems is challenging, since designers have to maximize the amount of sampled and transmitted data while considering the energy needs of the system that, in most cases, is powered by rechargeable batteries and exploits energy harvesting, e.g., solar cells and wind turbines. To support designers of AWSs in the definition of the software tasks and of the hardware configuration of the AWS we designed and implemented an energy-aware simulator of such systems. The simulator relies on the Stochastic Activity Networks (SANs) formalism and has been developed using the Möbius tool. In this paper we first show how we used the SAN formalism to model the various components of an AWS, we then report results from an experiment carried out to validate the simulator against a real-world AWS and we finally show some examples of usage of the proposed simulator.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States
Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex “Gigafire” occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.
54 ENVIRONMENTAL SCIENCES↗
WEATHER ON OTHER WORLDS. II. SURVEY RESULTS: SPOTS ARE UBIQUITOUS ON L AND T DWARFS
We present results from the Weather on Other Worlds Spitzer Exploration Science program to investigate photometric variability in L and T dwarfs, usually attributed to patchy clouds. We surveyed 44 L3-T8 dwarfs, spanning a range of J – K{sub s} colors and surface gravities. We find that 14/23 (61%{sub −20%}{sup +17%}, 95% confidence) of our single L3-L9.5 dwarfs are variable with peak-to-peak amplitudes between 0.2% and 1.5%, and 5/16 (31%{sub −17%}{sup +25%}) of our single T0-T8 dwarfs are variable with amplitudes between 0.8% and 4.6%. After correcting for sensitivity, we find that 80%{sub −27%}{sup +20%} of L dwarfs vary by ≥0.2%, and 36%{sub −17%}{sup +26%} of T dwarfs vary by ≥0.4%. Given viewing geometry considerations, we conclude that photospheric heterogeneities causing >0.2% 3-5 μm flux variations are present on virtually all L dwarfs, and probably on most T dwarfs. A third of L dwarf variables show irregular light curves, indicating that L dwarfs may have multiple spots that evolve over a single rotation. Also, approximately a third of the periodicities are on timescales >10 hr, suggesting that slowly rotating brown dwarfs may be common. We observe an increase in the maximum amplitudes over the entire spectral type range, revealing a potential for greater temperature contrasts in T dwarfs than in L dwarfs. We find a tentative association (92% confidence) between low surface gravity and high-amplitude variability among L3-L5.5 dwarfs. Although we can not confirm whether lower gravity is also correlated with a higher incidence of variables, the result is promising for the characterization of directly imaged young extrasolar planets through variability.
79 ASTRONOMY AND ASTROPHYSICS↗
Economic losses from extreme weather in the U.S. Gulf Coast region: spatially differential contributions of climate hazard and socioeconomic exposure and vulnerability
Worldwide economic losses from extreme weather events (EWE) have increased over recent decades, with significant geographic heterogeneity in damages. The IPCC defines the risk from EWE as a function of the climate hazard, socioeconomic exposure, and vulnerability. Although these three drivers vary at fine spatial scales, spatial variability largely has been overlooked in assessments of the drivers of economic loss from EWE. Using cluster analysis, we developed a novel socio-climate hazard typology (SCT) that integrates locally defined climate hazard and socioeconomic exposure and social vulnerability typologies. The results identified 838 unique SCT types impacted by EWE across the Gulf Coastal United States during 1981–2010. We regressed the SCT types and their constituent hazard and socioeconomic components against the cumulative economic loss (1981–2010) from EWE for each SCT type. Across the landscape, economic damages of SCT types were determined by unique, spatially explicit combinations of different risk factors, even in explaining the same level of economic loss. For example, multi-billion-dollar damages in the central Gulf Coast and peninsular Florida were explained by different drivers of risk, with damages in the former explained by additive interaction between climate hazard and multiplicative interaction between climate hazard and socioeconomic exposure and vulnerability, and in the latter explained by socioeconomic exposure and vulnerability. These results highlight the need to diagnose additive and multiplicative interactions among drivers of EWE risk in a spatially explicit context.
54 ENVIRONMENTAL SCIENCES↗
Surrogate Model for Distribution Networks Influenced by Weather
Here, we propose a method for generating reduced representations of time series and for constructing low dimensional surrogate models for time dependent calculations of power and voltage in distribution networks. We employ Fourier polynomials. The surrogate model strategy is aimed at reducing the computational cost of time dependent simulations, albeit, at the expense of fidelity. The reduced representation is achieved by identifying a small and most consequential subset of degrees of freedom. In power and voltage distribution networks dynamics that are heavily influenced by strong cyclic weather events, e.g., the hourly, diurnal and seasonal cycles, the weather/climate time series spectrum exposes these most energetic components. Once the degrees of freedom are identified their amplitudes are optimized using training data. The key challenge in using spectral methods in power network surrogates is addressing the computation of quotients. For this we propose a numerically-stable deconvolution strategy.
Weather events↗
Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development
The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.
17 WIND ENERGY↗