Variable Wind Research Articles

Glacial‐Interglacial Circulation and Climatic Changes in the South Indian Ocean (Kerguelen Plateau Region) Recorded by Detrital and Biogenic Magnetic Minerals

AbstractThe Southern Ocean (SO) plays a fundamental role in global climate due to the presence of the intense eastward‐flowing Antarctic Circumpolar Current (ACC), one of the most important ocean current systems. The configuration of the frontal systems of the ACC is controlled by the orbital‐ and millennial‐scale variations of the Southern Hemisphere westerly winds (SHWW) and the SO upwelling. However, the reconstruction of paleoclimate and paleocurrent in the SO remains controversial possibly because of the complex interpretation of paleo‐proxies and the regional variations. Here, we present results from rock magnetic measurements and electron microscopic analyses on marine core MD11‐3353 over the past 150 Kyr, which is located in the Polar Front Zone, west of the Kerguelen Plateau. Our data sets indicate that magnetic mineral assemblages in the core are dominated by detrital magnetic minerals mixed with biogenic magnetic minerals (i.e., magnetofossils formed by magnetotactic bacteria) during the interglacial periods. Changes in the detrital magnetic mineral content indicate a strong modulation of the ACC intensity and the SHWW stress at the orbital scale over the last climatic cycle with an enhanced activity during the glacial periods. The increase in magnetofossils content during the interglacial periods indicates an enhanced nutrient supply from the SO upwelling resulting from the southward migration of the Antarctic Polar Front. Our results suggest that the variations of concentration and assemblage of magnetic minerals can be used as faithful proxies for reconstructing ocean circulation and upwelling changes in the South Indian Ocean over the past 150 Kyr.

Rethinking the Role of Financial Transmission Rights in Wind-Rich Electricity Markets in the Central U.S.

Transmission congestion can cause a divergence between wholesale power prices at the individual pricing nodes where power is generated and the more-liquid trading hubs where that power is often delivered and sold. This nodal price difference is commonly referred to as the “locational basis” (or just “basis”). Because the basis varies over time, it can—if not hedged—unpredictably affect a wind plant’s revenue and/or value, which increases investor risk and potentially slows deployment. We find wind plants typically face a larger and more-negative basis than do thermal generators, and hence are more-negatively impacted by congestion. Moreover, while most thermal generators can effectively hedge basis risk by purchasing conventional fixed-volume financial transmission rights (FTRs), these fixed-volume FTRs do not effectively hedge basis risk for variable wind generation. More-effective hedging mechanisms may be required to support those generators most-impacted by congestion, and to promote continued investment in variable generation resources in congested markets.

Unique Combinations of Differently Shaped Equatorial Plasma Bubbles Occurring Within a Small Longitude Range

AbstractOn 12 October 2020 and 26 December 2021, NASA's Global‐scale Observations of the Limb and Disk (GOLD) mission observed differently shaped equatorial plasma bubbles (EPBs) simultaneously within ∼10° longitude, near the subsatellite point and over the Atlantic, respectively which is unusual. On 12 October 2020, three EPBs with differing curvatures were observed in a ∼12° longitude sector. The westside EPB was curved toward the east, in a C‐shape. The middle was straight. The eastside EPB was curved westward, in a reversed C‐shape. In the second case, 26 December 2021, in a smaller longitude range of ∼6° adjacent C‐shaped and reversed C‐shaped EPBs were observed. EPBs' zonal drift velocities at the magnetic equator and both equatorial ionization anomaly crests were compared. These occurrences of oppositely shaped EPBs simultaneously in a narrow longitude may indicate that small‐scale longitudinal variations in the E‐region density, electric field, neutral wind variations, or a combination of them were present.

Radio Refractivity Impact on Signal Strength of Mobile Communication

This research investigated radio refractivity impact on signal strength of mobile communication. The mobile communication signal strengths of two popular networks in Nigeria, 9Mobile and MTN, were considered. In the 2100 MHz-3 G band, 9Mobile transmits in the downlink spectrum of 2130.00–2140.00 MHz, while MTN transmits in the downlink spectrum of 2110.00–2120.00 MHz. Also, 9Mobile transmits in the downlink spectrum of 791–821 MHz in the 800 MHz band and 1805–1880 MHz in the 1800 MHz, while MTN transmits in the downlink spectrums of 2620–2690 MHz in the 2600 MHz band; all in the 4 G band. Using the instrument of a mobile station in each station (location) in some selected cities in southern Nigeria, the signal strengths were measured. A cell signal monitor (version 5.1.1) mobile application installed in an Android (transceiver) device (having two SIM slots) constituted the mobile station. To achieve high accuracy, there was a restriction in measuring transmission from specific cells. Hourly measurement of signal strengths was carried out and instantaneously corresponding weather parameters were recorded. Weather parameters for this investigation; atmospheric temperature and pressure; and relative humidity were excerpted online from the Nigeria Meteorological Agency (NIMET) hourly weather report for the various cities where the stations were situated. The hourly radio refractivity was computed using the 2015 International Telecommunication Union–Radio-communication sector (ITU-R) recommended model. Overall, the results indicate that there was no established linear relationship between signal strength and radio refractivity since the overall average R value is 0.0123691 and the overall average standard deviation of R values is 0.1112165. The inconsistencies in the linear relationships obtained from different locations and cells could be due to variations in topography, antenna properties, seasonal variations, wind and position, and distance of the receiver from the transmitter.

Multi-objective optimization strategy for parallel tuning of multiple fractional order controllers in a PMSG based WECS

In this paper, a novel multi-objective optimization strategy is proposed for the parallel tuning of six fractional order controllers used in regulation loops of a PMSG based wind energy conversion system connected to the electric grid. The nonlinear nature of the WECS components has made controllers design challenging. To enhance the transient response of system variables, Fractional Order Proportional Integral (FOPI) controllers are considered as they are more suitable for such nonlinear physical systems. The additional parameters introduced by FOPI are normally tuned using a single objective, multi-dimensional particle swarm optimization algorithm. However, the inter-dependence of regulation loops introduces additional complexity that is solved in this work using a multi-objective optimization strategy based on a succession of Single-Objective PSO and Multi-Objective PSO. A simulation study has been conducted in order to demonstrate the higher performance and superior tracking accuracy of the proposed multi-objective optimization strategy in variable wind speed operating conditions.

Wind Power Deviation Charge Reduction using Machine Learning

High penetration of wind power plants in power systems resulted in various challenges such as frequent system imbalances due to highly uncertain and variable wind generation. Additional spinning reserves and specific balancing products such as flexible ramp products are used to handle such frequent imbalances. Incorporation of these ancillary services leads to increased total operational costs. Increased operational costs should be transferred to wind power producers as it is caused by wind power plants. This leads to penalizing the wind power producers for the deviation of power generation from forecasts, called deviation charges. These deviation charges can be reduced by improving the forecasting accuracy. Existing forecasting models show performance in terms of error matrices. Such error matrices do not indicate the financial loss associated with it. This can be overcome by expressing forecasting performance in terms of deviation charge and it will directly encourage wind power producers to improve forecasting accuracy or arrange reserves to accommodate the error. This paper proposes a backpropagation-based artificial neural network model for reducing deviation charges in this context. An analysis is conducted on the data collected from the Bonneville Power Administration (BPA) Balancing Area. Seasonal analysis (Spring, Summer, Fall, and Winter) is conducted to show the performance of the proposed model throughout the year. The proposed model performance is compared with linear regression and ARIMA models. The comparison shows that the proposed ANN model gives the least deviation charges in the Spring, Summer, and Winter seasons and deviation charges in the Fall season are higher than the ARIMA model.

Incorporating Stochastic Wind Vectors in Wildfire Spread Prediction

The stochastic nature of environmental factors that govern the behavior of fire, such as wind and fuel, exposes wildfire modeling to a degree of uncertainty. In order to produce more realistic wildfire predictions, it is, therefore, necessary to incorporate these uncertainties within wildfire models in a way that reflects the influence of environmental stochasticity on wildfire propagation. Otherwise, the risks of the potential danger of a given wildfire may be under-represented. Specifically, environmental stochasticity in the form of wind variability results in considerable uncertainty in the output of fire spread models. Here, we consider two stochastic wind models and their implementation in the spark fire simulator framework to capture the environmental uncertainty related to wind variability. The results are compared with the output from purely deterministic wildfire spread models and are discussed in the context of the potential ramifications for wildfire risk management.

Offshore Wind Power Resource Assessment in the Gulf of North Suez

Growing population, industrialization, and power requirements are adversely affecting the environment through increased greenhouse gases resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led nations to promote clean and self-renewable sources of energy to address this environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting an offshore wind power resource assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above mean sea level (AMSL), as well as temperature and pressure data near the surface, are used. The data is obtained from ERA5 (fifth generation global climate reanalysis) at six (L1–L6) chosen offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL, while temperature and pressure are available near water-surface level. At the L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m2, 6.37 m/s and 225 W/m2, 6.91 m/s and 281 W/m2, 5.48 m/s and 142 W/m2, 4.30 m/s and 77 W/m2, and 5.03 and 115 W/m2 and at 100 m AMSL, respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at the L1 and L3 sites, and generally lower values of wind variability indices, are indicative of a favorable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at the L5 and L1 sites, corresponding to wind turbines WT1 and WT4. Based on this analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifier indices introduced will help decision-makers in targeting potential windy sites with more confidence.

Combined Coastal Sea Level Estimation Considering Astronomical Tide and Storm Surge Effects: Model Development and Its Application in Thermaikos Gulf, Greece

Tide gauge recordings furnish the longest and almost the most continuous data source of sea level monitoring. Traditionally, they are collected using tide gauge instrumentation fixed at seaport locations to provide a time series of sea level estimates relative to a local geodetic benchmark. Sea level tidal observables are distinguished in the astronomical tide component originating from the attraction of the Earth–Moon–Sun gravitational system, and the storm surges ought to have meteorological effects due to wind and atmospheric air pressure variation. This study provides a comprehensive methodological approach and software to compute sea level considering astronomical tides enhanced by storm surge effects. The model is realized and assessed using a long-standing set of 21 consecutive years of tidal and meteorological measurements originating from Thermaikos Gulf, Greece. Analyses show model verification and conclusions about the tidal behavior of the test area, suggesting a satisfactory agreement (86% Willmott Skill factor, 9 cm standard deviation) between predicted and observed sea level estimates, accounting for amplitude and the time shift of skew surges.

Stratospherically induced circulation changes under the extreme conditions of the no-Montreal-Protocol scenario

Abstract. The Montreal Protocol and its amendments (MPA) have been a huge success in preserving the stratospheric ozone layer from being destroyed by unabated chlorofluorocarbon (CFC) emissions. The phaseout of CFCs has not only prevented serious impacts on our health and climate, but also avoided strong alterations of atmospheric circulation patterns. With the Earth system model SOCOLv4, we study the dynamical and climatic impacts of a scenario with unabated CFC emissions by 2100, disentangling radiative and chemical (ozone-mediated) effects of CFCs. In the stratosphere, chemical effects of CFCs (i.e., the resulting ozone loss) are the main drivers of circulation changes, weakening wintertime polar vortices and speeding up the Brewer–Dobson circulation. These dynamical impacts during wintertime are due to low-latitude ozone depletion and the resulting reduction in the Equator-to-pole temperature gradient. Westerly winds in the lower stratosphere strengthen, which is for the Southern Hemisphere (SH) similar to the effects of the Antarctic ozone hole over the second half of the 20th century. Furthermore, the winter and spring stratospheric wind variability increases in the SH, whereas it decreases in summer and fall. This seasonal variation in wind speed in the stratosphere has substantial implications for the major modes of variability in the tropospheric circulation in the scenario without the MPA (No-MPA). We find coherent changes in the troposphere, such as patterns that are reminiscent of negative Southern and Northern Annular modes (SAM and NAM) and North Atlantic Oscillation (NAO) anomalies during seasons with a weakened vortex (winter and spring); the opposite occurs during seasons with strengthened westerlies in the lower stratosphere and troposphere (summer). In the troposphere, radiative heating by CFCs prevails throughout the year, shifting the SAM into a positive phase and canceling out the ozone-induced effects on the NAO, whereas the North Pacific sector shows an increase in the meridional sea-level pressure gradient as both CFC heating and ozone-induced effects reinforce each other there. Furthermore, global warming is amplified by 1.7 K with regionally up to a 12 K increase over eastern Canada and the western Arctic. Our study sheds light on the adverse effects of a non-adherence to the MPA on the global atmospheric circulation, uncovering the roles of the underlying physical mechanisms. In so doing, our study emphasizes the importance of the MPA for Earth's climate to avoid regional amplifications of negative climate impacts.

Assessment of the onshore storage capacity of hydrogen in Argentina’s natural gas fields

Increasing the proportion of electricity from renewable energy sources is critical for the reduction of CO 2 emissions required to meet the commitments of the Paris Agreement. However, intermittency in energy generation due to the daily and seasonal variability of wind and solar radiation is a major challenge. Addressing this issue requires the development of large-scale energy storage systems. Low-carbon hydrogen production and storage in geological reservoirs offers a potential seasonal energy storage solution. Here, we provide the first assessment of the underground storage capacity for hydrogen in Argentina and identify sites where future clusters of low-carbon hydrogen production could be co-located with suitable geological storage sites. We outline a production-based methodology that couples historical hydrocarbon production with remaining reserves to provide a reliable estimation of the amount of hydrogen that can be stored in each reservoir. Assuming a cushion gas requirement of 50%, our results show that a combined storage capacity of 2860 TWh of hydrogen exists. This far exceeds the requirements to meet the seasonal electricity demand for residential consumption in the country. The results of our sensitivity analysis show that the two most sensitive variables are temperature and compressibility, suggesting that high-pressure shallow reservoirs are most suitable for underground hydrogen storage. We additionally propose locations for two H 2 production and storage hubs that would permit the integration of storage sites with renewable developments and natural gas reserves that could be combined with carbon capture and storage to produce low-carbon hydrogen. Thematic collection: This article is part of the Hydrogen as a future energy source collection available at: https://www.lyellcollection.org/topic/collections/hydrogen

Characteristics and rarity of the strong 1940s westerly wind event over the Amundsen Sea, West Antarctica

Abstract. Glaciers in the Amundsen Sea Embayment of West Antarctica are rapidly retreating and contributing to sea level rise. Ice loss is occurring primarily via exposure to warm ocean water, which varies in response to local wind variability. There is evidence that retreat was initiated in the mid-20th century, but the perturbation that may have triggered retreat remains unknown. A leading hypothesis is that large pressure and wind anomalies in the 1940s drove exceptionally strong oceanic ice-shelf melting. However, the characteristics, drivers, and rarity of the atmospheric event remain poorly constrained. We investigate the 1940s atmospheric event using paleoclimate reconstructions and climate model simulations. The reconstructions show that large westerly wind anomalies occurred from ∼1938–1942, a combined response to the very large El Niño event from 1940–1942 and other variability beginning years earlier. Climate model simulations provide evidence that events of similar magnitude and duration may occur tens to hundreds of times per 10 kyr of internal climate variability (∼0.2 to 2.5 occurrences per century). Our results suggest that the 1940s westerly event is unlikely to have been exceptional enough to be the sole explanation for the initiation of Amundsen Sea glacier retreat. Additional factors are likely needed to explain the onset of retreat in West Antarctica, such as naturally arising variability in ocean conditions prior to the 1940s or anthropogenically driven trends since the 1940s.

Nonlinear modelling of the association between winter weather severity and maintenance expenditures

The winter weather severity plays a crucial role in determining the resources required for winter maintenance activities. This study utilized nonlinear models to examine the relationship between winter weather variables (temperature, wind speed, and snowfall) and winter maintenance expenditures (labor, material, and equipment) based on data from the state of Illinois. The data were collected and aggregated by year and district to align with the expenditure data, and the state was divided into three climatic zones, with separate models developed for each. The ROUT method was employed to identify and eliminate outliers before conducting nonlinear modelling. The best-fitting model was selected using cross-validation and R2 evaluation. The results demonstrate that the chosen nonlinear models effectively depict the connection between winter weather and winter maintenance expenses. These findings can aid agencies in efficiently allocating resources for winter maintenance.

Comparative Study and Dynamic Performance Analysis of DFIG based Wind Energy Conversion System

This paper presents a novel control strategy for wind energy conversion system for improving the dynamic stability of the system. In off-grid applications, the load voltage and frequency should be managed in steady-state and transient circumstances. For rural areas with unpredictable wind and load circumstances, electricity quality and control are crucial tasks. In order to improve power quality, dynamic stability and power management in direct drive standalone wind energy systems, this research provides a coordinated proportional resonant (PR) controller. Under different operating situations, such as variable wind with step increases and decreases in wind velocity, balanced and unbalanced load conditions, the dynamic performance of a doubly-fed induction generator (DFIG) is evaluated. In order to meet the load requirement, the suggested PR control technique with battery energy controller also provides efficient power balancing between the wind and battery sources. A fair performance comparison is made between the proposed control strategy and conventional vector control strategy by using the MATLAB/SIMULINK platform under varying wind and load circumstances. The proposed control approach shown better dynamic stability, improving the power quality of the system and better synchronization.

Mechanisms for Abrupt Summertime Circumpolar Surface Warming in the Southern Ocean

Abstract In recent years, the Southern Ocean has experienced unprecedented surface warming and sea ice loss—a stark reversal of the sea ice expansion and surface cooling that prevailed over the preceding decades. Here, we examine the mechanisms that led to the abrupt circumpolar surface warming events that occurred in late 2016 and 2019 and assess the role of internal climate variability. A mixed layer heat budget analysis reveals that these recent circumpolar surface warming events were triggered by a weakening of the circumpolar westerlies, which decreased northward Ekman transport and accelerated the seasonal shoaling of the mixed layer. We emphasize the underappreciated effect of the latter mechanism, which played a dominant role and amplified the warming effect of air–sea heat fluxes during months of peak solar insolation. An examination of the CESM1 large ensemble demonstrates that these recent circumpolar warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM), whereby negative SAM in austral spring favors shallower mixed layers and anomalously high summertime SST. A key insight from this analysis is that the seasonal phasing of springtime mixed layer depth shoaling is an important contributor to summertime SST variability in the Southern Ocean. Thus, future Southern Ocean summertime SST extremes will depend on the coevolution of mixed layer depth and surface wind variability. Significance Statement This study examines how reductions in the strength of the circumpolar westerlies can produce abrupt and extreme surface warming across the Southern Ocean. A key insight is that the mixed layer temperature is most sensitive to surface wind perturbations in late austral spring, when the regional mixed layer depth and solar insolation approach their respective seasonal minimum and maximum. This heightened surface temperature response to surface wind variability was realized during the austral spring of 2016 and 2019, when a dramatic weakening of the circumpolar westerlies triggered unprecedented warming across the Southern Ocean. In both cases, the anomalously weak circumpolar winds reduced the northward Ekman transport of cool subpolar waters and caused the mixed layer to shoal more rapidly in the spring, with the latter mechanism being more dominant. Using results from an ensemble of coupled climate simulations, we demonstrate that the 2016 and 2019 Southern Ocean warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM). These results suggest that future Southern Ocean surface warming extremes will depend on both the evolution of regional mixed layer depths and interannual wind variability.

Diurnal variation of monsoon winds during the onset, active-break and withdrawal phases observed at its gateway in India: A case study of 2021

Diurnal variation of the low-level jet (LLJ) and tropical easterly jet stream (TEJ) over Cochin – the gateway of Indian summer monsoon – was investigated during the monsoon onset over Kerala (MOK), active-break, and withdrawal phases in the year 2021. Horizontal wind profiles obtained from the 205 MHz wind profiling radar at Cochin University of Science and Technology, India, were analyzed to delineate the core speed and core heights of the LLJ and TEJ. Distinct diurnal variability in wind patterns was observed during various monsoon phases. The LLJ and TEJ core speed and heights exhibited significant diurnal variations, with the LLJ reaching maximum diurnal amplitudes between 2.5 m s−1 (onset phase) and 0.5 m s−1 (break phase). Notably, the LLJ core speed during the break phase was approximately half of that during the active phase. The ratios of the diurnal range to the time mean LLJ core speed varied between 0.19 (active phase) and 1.33 (onset phase). Moreover, the LLJ core height is higher during active compared to break. Similarly, the TEJ core height at Cochin is marginally higher during active compared to that during break. Interestingly, an enhanced TEJ core speed and weakened LLJ were observed during the break phases. The variation of moisture flux exhibited positive correlation with the core speed with 2–3 h lag, significantly influencing the diurnal variability of rainfall. The causative factors behind the diurnal oscillations during various phases of the monsoon are discussed.

Enhancement of a Grid-Connected DFIG Wind Turbine System Using Fractional Order PI Controllers

The wind velocities are unpredictable, and generating power with persistent speed is difficult which comprises mechanical stress at the rotor that leads to poor efficiency. So, variable wind power speed generation has ample significance with the Doubly Fed Induction Generator (DFIG). For a grid-connected DFIG, the governing of power is done conventionally by employing vector-controlled PI regulators. Yet, the performance of PI regulators depends on system parameters, which motivates the adoption of Fractional Order PI (FOPI) regulators. Presently FOPI regulators are seizing a lot of applications with the assistance of additional tuning parameters. However, tuning FOPI regulators by conventional methods is challenging. So, initially, the Particle Swarm Optimization (PSO) method was used for tuning FOPI regulators, but the disadvantages are low convergence rate, falling into local elucidation, entailing more variables to attune, and requiring a large number of iterations. Thus, this motivates introducing the Ant Lion Optimization (ALO) algorithm in this article due to its better performance and eligibility to overcome the limitations of conventional methods. Furthermore, in the validation of the proposed algorithm, the performance parameters like DC coupling capacitor voltage, rotor Speed, active power, and reactive power with PI, FOPI, PSO-FOPI, and ALO-FOPI regulators are compared and analysed using the bode plot are presented. The time response analysis of all the controllers with PI, FOPI, PSO-FOPI, and ALO-FOPI controllers were also observed with a voltage dip. Finally, the fractional order controllers with frequency response and time response analysis show superior performance in distributed generation with advanced heuristic controllers when compared to conventional controllers. The complete work has been simulated via MATLAB/ Simulation platform.

Fractional-order neural control of a DFIG supplied by a two-level PWM inverter for dual-rotor wind turbine system

Energy ripples are among the common problems in renewable energies as a result of using less efficient strategies. In this work, a new technique is suggested to control a doubly-fed induction generator (DFIG) using the pulse width modulation (PWM). The new technique is based on the combination of neural networks and fractional-order control to minimize the reactive and active power ripples of the DFIG-based variable speed dual-rotor wind turbine system. The suggested fractional-order neural control (FONC) with the PWM is a simple, robust and a high-performance strategy. Simulation is performed using Matlab software to validate the effectiveness of the designed control of 1.5 MW DFIG and the obtained results are compared with the traditional direct power control (DPC) in different working conditions. In addition, the comparison between the suggested control and the DPC is performed in the cases of changing or not changing the device parameters in terms of ripple ratio, dynamic response, steady-state error, current quality, and overshoot of active and reactive power of the DFIG. As compared to the DPC, the proposed FONC technique improves the active and reactive power ripples by 65.71% and 84.74%, respectively. Also, improves the overshoot of the active and reactive power by 71.33% and 91.72%, respectively. The simulation results demonstrate the high performance and robustness of the FONC technique for the parametric variations of the DFIG-based variable speed dual-rotor wind turbine system compared to the DPC control.

Estimation of the Eddy Viscosity Profile in the Sea Surface Boundary Layer from Underway ADCP Observations

Abstract A method of assessing the mean eddy viscosity profile (EVP) in the sea surface boundary layer (SBL) under variable wind conditions is proposed. Performance of the method is tested using observations by an ADCP-equipped platform in the coastal environment of the northwestern Mediterranean Sea under variable (3–12 m s−1) wind conditions. EVP retrievals are made by a variational method strongly constrained by the Ekman dynamics, with the wind and velocity observations assumed to be uncertain within the prescribed error bars. Results demonstrate a reasonable agreement of the EVPs with KPP shape functions for stronger (8–12 m s−1) wind conditions and appear to be consistent with the classical Pacanowski–Philander parameterization of the viscosity profile based on the Richardson number. For weaker (3–5 m s−1) winds, the EVP retrievals turn out to be less accurate, which is primarily attributed to the decay of the wind-driven turbulence energy in the SBL. Feasibility and prospects of the retrieval technique are discussed in the context of uncertainties in the structure of the background flow and limitations of the microstructure and ADCP profiling.

Robustness of the Stochastic Parameterization of Subgrid-Scale Wind Variability in Sea Surface Fluxes

Abstract High-resolution numerical models have been used to develop statistical models of the enhancement of sea surface fluxes resulting from spatial variability of sea surface wind. In particular, studies have shown that flux enhancement is not a deterministic function of the resolved state. Previous studies focused on single geographical areas or used a single high-resolution numerical model. This study extends the development of such statistical models by considering six different high-resolution models, four different geographical regions, and three different 10-day periods, allowing for a systematic investigation of the robustness of both the deterministic and stochastic parts of the data-driven parameterization. Results indicate that the deterministic part, based on regressing the unresolved normalized flux onto resolved-scale normalized flux and precipitation, is broadly robust across different models, regions, and time periods. The statistical features of the stochastic part of the model (spatial and temporal autocorrelation and parameters of a Gaussian process fit to the regression residual) are also found to be robust and not strongly sensitive to the underlying model, modeled geographical region, or time period studied. Best-fit Gaussian process parameters display robust spatial heterogeneity across models, indicating potential for improvements to the statistical model. These results illustrate the potential for the development of a generic, explicitly stochastic parameterization of sea surface flux enhancements dependent on wind variability.