Reanalysis Wind Research Articles

Assessment of Wind Energy Potential in Kolaka Using Era5-land Reanalysis Data

This research aims to evaluate the potential for wind energy in Kolaka Regency using ERA5-Land reanalysis data from the output of the European Center for Medium-Range Weather Forecasts (ECMWF) model, which has a spatial resolution of 9 km with hourly temporal resolution for the period of 2001 to 2020. This research also compared the quality of ERA5-Land reanalysis wind speed data on data from nearby meteorological stations using statistical assessment methods. The analysis results reveal that the highest average wind speed is discovered at a height of 80 to 150 meters with a range of 4.99 to 5.93 m/s. The spatial distribution map of wind power density indicates that the energy potential at a height of 80 to 150 meters can reach 60 to 170 W/m2. The largest wind energy potential in Kolaka Regency can be generated in the DJF period (December-January-February) with the highest average monthly wind power density in January and the JJA period (June-July-August) with the highest average in July. In general, Kolaka Regency can be classified as an area with first-class wind energy potential, so it tends to be more suitable for the development of small-scale power plants. The suitable locations for developing small-scale wind power plants in Kolaka Regency are the southern Pomalaa coast and the Tanggetada coast because both locations have better wind energy sources than other areas.

Analysis of rain effects on China-France oceanography satellite scatterometer backscatter measurements

ABSTRACT The rotating fan beam scanning observation mechanism of China-France oceanography satellite (CFOSAT) scatterometer provides more comprehensive ocean measurements. However, its data quality is often impacted by rain contamination. In this study, we analysed the effect of rain on CFOSAT SCATterometer (CSCAT) backscatter measurements by collocating CSCAT data, the Integrated Multi-satellitE Retrievals (IMERG) rain data, and the wind reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF). The research findings indicate that, rain exhibits an intensification effect on backscatter at low wind speeds, but this effect gradually diminishes with increasing wind speeds, eventually transitioning to an attenuation effect at a wind speed between 10–20 m·s−1. At extremely high wind speeds above 20 m·s−1, the rain initially increases and then decreases CSCAT normalized radar cross section (σ 0) as the rain rate increases. The sensitivity of CSCAT σ 0 to rain rate decreases as the incidence angle increases. Its sensitivity to wind speed decreases as the rain rate increases. The azimuthal modulation becomes more pronounced with higher wind speeds and smaller incidence angles. However, rain weakens the asymmetry and anisotropy. Furthermore, the HH polarization exhibits a more pronounced susceptibility to rain compared to the VV polarization.

Towards sustainable energy: integrating ERA5 data for offshore wind farm planning in India

India’s pursuit of offshore wind energy development, particularly along the Tamil Nadu coastline within its Exclusive Economic Zone (EEZ), faces significant spatial and economic challenges due to existing industrial activities and water depth limitations. Motivated by the need to optimize offshore wind resources and bridge the gap between onshore and offshore wind energy achievements, this study hypothesizes that ERA5 reanalysis wind data can be relied upon for assessing offshore wind resources and optimizing wind farm layouts, especially in the absence of measured data. The research employs methods such as comparing ERA5 data with empirical wind measurements, generating wind rose diagrams for layout optimization, and conducting a comprehensive financial analysis to estimate the Levelized Cost of Energy (LCoE). The results confirm the efficacy of ERA5 data, identifying an optimal wind farm layout with a capacity density of 5.17 MW per square kilometer, turbine spacing of 7.22 meters, and an LCoE of Rs. 8.84 per kWh. The study concludes that significant financial support and strategic policy interventions are essential for minimizing wake losses, optimizing capacity density, and fostering the long-term growth of India’s offshore wind energy sector, providing critical insights for policymakers, developers, and investors. The novelty of this research lies in its detailed exploration of spatial optimization and cost-effective strategies to enhance the techno-economic viability of offshore wind projects in India.

Integrated assessment of offshore wind and wave power resources in mainland Portugal

This study presents a comprehensive analysis of offshore wind and wave energy resources in mainland Portugal, aiming to facilitate sustainable energy exploitation. The study integrates the spatial distribution and temporal variability of those energy resources, as well as the interplay between wind and wave patterns and co-location feasibility. A 44-year dataset (1979–2022), derived from ERA5 reanalysis wind and SWAN wave model across the concession zones designated by the Portuguese government (labelled as P1 to P6) are utilised. The results indicate promising prospects for wind and wave power densities in these zones, emphasising the suitability of the offshore renewable energy extraction. Additionally, analysis revealed fluctuations in wind and wave power variability among the selected locations, with concession zone P3 (Leixões) emerging as a promising candidate due to its relatively lower variability and stable distribution patterns of both resources. The analysis on co-location feasibility demonstrated the potential for efficient energy extraction in location P5 proving to be the most favourable in wind-wave resource integration. Moreover, time lag analysis highlighted opportunities for optimising energy capture efficiency. Overall, this study provides valuable insights into the sustainable exploitation of wind and wave power resources, contributing to deliver informed decision-making for renewable energy investment.

Proposal and application of a convective wind gustiness parameterization based on convective available potential energy

Wind gustiness is an effective approach for addressing mesoscale enhancement in estimating air-sea interface fluxes. In this study, an improved convective gustiness parameterization scheme based on convective available potential energy (CAPE) is formulated utilizing reanalysis data and wind observations from moored buoys. This new parameterization was examined by implementing it in the air-sea flux transfer scheme within the National Center for Atmospheric Research Community Earth System Model (NCAR CESM) version 2.1.3 and contrasting it with a previously proposed scheme based on convective precipitation rate. The results indicate a significant reduction in negative biases of surface winds and latent heat fluxes over the tropical Indian Ocean and western Pacific during summer with the implementation of either gustiness scheme, resulting in an average increase in latent heat flux of approximately 9 W·m− 2. Specifically, the CAPE-based scheme shows a more favorable impact in the Indo-Pacific Warm Pool region, whereas the precipitation-based scheme exhibits inferior performance in the western Pacific Intertropical Convergence Zone. Further analysis reveals that the inclusion of the gustiness scheme distinctly alters surface evaporation and latent heat flux, influencing vertical motion in the area with active convective activity and effectively improving precipitation simulations by up to 18%. Moreover, the CAPE-based scheme reduces the bias in summer precipitation simulations by approximately 5% more than the precipitation-based scheme.

Synchronicity of the Gulf Stream path downstream of Cape Hatteras and the region of maximum wind stress curl

The Gulf Stream, a major ocean current in the North Atlantic ocean is a key component in the global redistribution of heat and is important for marine ecosystems. Based on 27 years (1993–2019) of wind reanalysis and satellite altimetry measurements, we present observational evidence that the path of this freely meandering jet after its separation from the continental slope at Cape Hatteras, aligns with the region of maximum cyclonic vorticity of the wind stress field known as the positive vorticity pool. This synchronicity between the wind stress curl maximum region and the Gulf Stream path is observed at multiple time-scales ranging from months to decades, spanning a distance of 1500 km between 70 and 55W. The wind stress curl in the positive vorticity pool is estimated to drive persistent upward vertical velocities ranging from 5 to 17 cm day−1 over its ~ 400,000 km2 area; this upwelling may supply a steady source of deep nutrients to the Slope Sea region, and can explain as much as a quarter of estimated primary productivity there.

The Coastal Sea‐Level Response to Wind Stress in the Middle Atlantic Bight

AbstractAnalysis of 40 years of tide gauge data and reanalysis wind stresses from the Middle Atlantic Bight (MAB) indicate that along‐shelf wind stresses are a dominant driver of coastal dynamic sea level (sea level plus atmospheric pressure) variability at daily to yearly time scales. The sea‐level response to along‐shelf wind stress varies substantially along the coast and is accurately reproduced by a steady, barotropic, depth‐averaged model (Csanady, 1978, https://doi.org/10.1175/1520‐0485(1978)008<0047:tatw>2.0.co;2, Arrested Topographic Wave). The model indicates that the sea‐level response in the MAB depends primarily on the along‐shelf distribution of the along‐shelf wind stress, the Coriolis frequency, the bottom drag coefficient, and the cross‐shelf bottom slope. The along‐shelf wind stress varies along the MAB shelf due primarily to changes in the shelf orientation. The sea‐level response depends on both the local and upstream (in the sense of Kelvin wave propagation) along‐shelf wind stresses. Consequently, sea‐level variability at daily, monthly and yearly time scales along much of the central MAB coast is more strongly driven by upstream winds along the southern New England shelf than by local winds along the central MAB shelf. The residual coastal sea‐level variability, after removing the wind‐driven response and the trend, is roughly uniform along the MAB coast. The along‐coast average of the residual sea level at monthly and yearly time scales is caused by variations in shelf water densities primarily associated with the large annual cycle in water temperature and interannual variations in salinity.

Response of the low latitude mesosphere and lower thermosphere to the recent sudden stratospheric warming events of 2017–18 and 2019

Upper mesospheric wind data acquired by the medium frequency radar at Kolhapur (16.7oN, 74.2oE) and Modern–Era Retrospective analysis for Research and Application version 2 (MERRA-2) temperature and wind reanalysis datasets are used to investigate the dynamical response of the low-latitude middle atmosphere to the sudden stratospheric warming (SSW) events that occurred during the 2017–18 and 2018–19 winters. When the amplitude of the high-latitude stratospheric planetary wave (PW) of zonal wavenumber one reduces considerably with the onset of the SSW event, the low-latitude mesospheric PW over Kolhapur also shows a considerable reduction in the PW activity. It is noteworthy that the upper mesospheric winds are eastward for approximately 3 weeks after the onset of SSW. The reduced PW activity is associated with the enhanced gravity wave activity in the meridional wind during the SSW 2018–19 event. The plane of propagation of gravity waves obtained from the perturbation ellipse method suggests that their predominant plane of propagation is in the north–south direction. The persistence of the eastward winds is suggested to be due to the interaction of the northward propagating gravity waves with the mean flow, leading to the eastward acceleration due to the Coriolis force.

Explanations for the positive storm surges on the left side of landfall typhoons in China

The coastal regions of Southeast China frequently experience unusual positive storm surges on the left side of landfalling typhoons, a phenomenon historically overlooked and inadequately explained by conventional circular wind field models. In this study, a high resolution, two-dimensional storm surge model based on ADCIRC along with tide gauge data were used to investigate the spatiotemporal distribution of these surges and proposes underlying mechanisms, informed by a comparative analysis of circular and ERA5 reanalysis wind fields during typical typhoon event 9711 Winnie. Analyzing tide gauge data spanning from 1986 to 2016, the study uncovers a distinct pattern of left-side positive storm surges along the southeastern coast, notably on the Fujian coast and within the Taiwan Strait, which are found to be comparable to those on the cyclone’s right side. The research also documents a significant escalation in both the frequency and intensity of these left-side surges over the past three decades. Simulation results highlights the inadequacies of circular wind field models in operational forecasting and emphasizes the necessity of accounting for topographic influences and the structural complexity of wind fields in storm surge predictions. This is particularly pertinent in semi-enclosed seas with intricate hydrodynamics, such as the Taiwan Strait. The insights gleaned from this study are pivotal for enhancing the real-time simulation and prediction of storm surges, which are vital for coastal safety and disaster prevention measures.

The Importance of Contemporaneous Wind and pCO2 Measurements for Regional Air‐Sea CO2 Flux Estimates

AbstractFew observational platforms are able to sustain direct measurements of all the key variables needed in the bulk calculation of air‐sea carbon dioxide (CO2) exchange, a capability newly established for some Uncrewed Surface Vehicles (USVs). Western boundary currents are particularly challenging observational regions due to strong variability and dangerous sea states but are also known hot spots for CO2 uptake, making air‐sea exchange quantification in this region both difficult and important. Here, we present new observations collected by Saildrone USVs in the Gulf Stream during the winters of 2019 and 2022. We compared Saildrone data across co‐located vehicles and against the Pioneer Array moorings to validate the data quality. We explored how CO2 flux estimates differ when all variables needed to calculate fluxes from the bulk formulas are simultaneously measured on the same platform, relative to the situation where in situ observations must be combined with publicly‐available data products. We systematically replaced variables in the bulk formula with those often used for local and regional flux estimates. The analysis revealed that when using the ERA‐5 reanalysis wind speed in place of in situ observations, the ocean uptake of CO2 is underestimated by 8%; this underestimate grows to 9% if the NOAA Marine Boundary Layer atmospheric CO2 product and ERA‐5 significant wave height are also used in place of in situ observations. Overall our findings point to the importance of collecting contemporaneous observations of wind speed and ocean pCO2 to reduce biases in estimates of regional CO2 flux, especially during high wind events.

Trends of extreme waves around Hainan Island during typhoon processes

Extreme waves mostly occur during typhoon processes in China Seas. This study statistically shows the trends of extreme wave height over the past several decades around Hainan Island, based on the reconstruction of historical wave processes during the typhoon events from 1949 to 2022. Totally 807 events in the tropical cyclone (TC) best track datasets are numerically simulated by the widely used wave model SWAN. The driving wind fields are reconstructed as a combination of an empirical cyclone wind model with the reanalysis wind field data, in order to better simulate waves near cyclone centers with higher spatial resolution. Based on the reconstructed wave data, the spatial distribution of wave characteristics around Hainan Island has been provided. The Mann-Kendall test shows a descending trend of extreme wave height in the southeast side of Hainan Island, where the maximum descending rate could reach up to 5 cm/yr. The influence of the long-term trend on the design extreme wave height is also discussed. Comparing to the variation of the design extreme wave height with sampling period, the long-term trend is also a significant impact factor.

Impact of Satellite Wind on Improving Simulation of the Upper Ocean Response to Tropical Cyclones

Accurate modeling of the ocean response to tropical cyclones (TCs) requires high-quality wind fields to force ocean models. In this study, blended wind fields are generated using multi-source satellite data and the Climate Forecast System Reanalysis (CFSR) wind data. We utilize the hybrid wind fields to drive the Regional Ocean Modeling System (ROMS) for simulating oceanic dynamic and thermodynamic parameters. The model’s simulated ocean surface and sub-surface temperatures, as well as current speeds, are generally consistent with satellite and in situ observations collected during TC Winston and Freddy. The results are significantly better than those simulated by ROMS using wind forcing from CFSR alone. These results suggest that incorporating satellite wind data into the atmospheric forcing has the potential to enhance vertical mixing and improve simulations of the upper ocean response to TCs.

Just How River‐Like Are Atmospheric Rivers?

AbstractAtmospheric Rivers (ARs) are synoptic‐scale conduits for poleward transport of heat and water, often associated with extreme rainfall. Using NASA surface heat flux observations and climate model simulations, we assess whether ARs are “rivers”, transporting heat and moisture over longer distances, or mostly local convergence. The observations indicate that ARs reduce extratropical surface energy fluxes, even during early development. This damping of surface fluxes during ARs is also simulated in the Goddard Institute for Space Studies ModelE, 2.1 (GISS‐E2.1) nudged to (MERRA2) reanalysis winds. Furthermore, water provenance tracers in GISS‐E2.1 identify the moisture source for ∼7,500 ARs globally during 2018–2022 as farther upstream and equatorward compared to climatology. These results quantitatively show that ARs source relatively less moisture from the surface beneath them and more from a greater distance than during non‐AR times.

Multi-scale simulation of typhoon wind field at building scale utilizing mesoscale model with nested large eddy simulation

Based on the mesoscale WRF (Weather Research Forecast) and LES (Large Eddy Simulation), an integrated numerical simulation framework aiming to resolve typhoon wind fields around urban building blocks has been developed. The holistic multi-scale simulation spans four scales: macroscale (∼1000 km), mesoscale (∼100 km), microscale (∼1 km), and building scale (0.1–100m). By interactively sharing the meteorological data among different scales, this simulation framework addressed the challenge of downscaling typhoon effects in urban environments. Typhoon weather reanalysis and urban wind field simulation were conducted by the WRF model with nested computational domains incorporating high-resolution topography data. For the downscaled LES model with urban buildings, the wind profiles produced by the WRF model were used at the interface with provided turbulent fluctuations in the flow. K11 building is a 270-m-tall building located in a densely built-up area of Hong Kong. Wind velocity and pressure fields surrounding the K11 building in Hong Kong during Typhoon Kammuri were obtained by the proposed framework, and the simulation results were validated by comparing with the meteorological data and full-scale measurements at the top of the K11 building. The interactions of the wind fields and building clusters resulting in vortex shedding, separation, and channeling effects have been resolved at high resolutions. Probabilistic distributions and higher-order statistics of wind pressure, i.e., skewness and kurtosis, were presented to highlight non-Gaussian characteristics of the simulated local wind pressure on the K11 building. Based on the simulated wind pressure, wind-induced vibration of the K11 building during the typhoon was analyzed and compared to the measurements.

What Is the Contribution of Convergence Zones to Global Precipitation? Assessing Observations and Climate Models Biases

AbstractConvergence zones (CZs) are known drivers of precipitation regimes from regional to planetary scales. However, there is a scarcity of accounts of the contribution of CZs to the global precipitation. In this study, we build upon a recently developed Lagrangian diagnostic to attribute precipitation to CZ events in observations and simulations submitted to the Coupled Model Intercomparison Project 6 (CMIP6). Observed CZs are identified using ERA5 reanalysis wind and attributed precipitation from observational products based on satellite estimates and rain gauges. We estimate that approximately 54% (51%–59%, depending on the precipitation product) of global precipitation falls over CZs; in some regions, such as the Intertropical Convergence Zone (ITCZ) and subtropical monsoon regions, this proportion is greater than 60%. All CMIP6 simulations analyzed here attribute about 10% more precipitation to CZ events than what the observations suggest. To investigate this overestimation, we decompose the precipitation error in terms of frequency and intensity of CZ precipitation and find that all models present a substantial positive bias in the frequency of CZ precipitation, suggesting that climate models trigger precipitation too easily in regions of airmass confluence; such positive frequency biases in CZ precipitation help explaining well‐known biases in climate models, such as the double‐ITCZ in the Pacific. We also find that models with better mass conservation present an apportionment of CZ precipitation closest to the observational estimates, demonstrating the relevance of mass conservation in advection schemes.

Enhanced Typhoon-Induced Design Wave Height Estimation for Ocean Engineering Applications Using High Performance Computing

Coastal construction heavily depends on accurately estimating design wave parameters. This paper presents a technique for calculating ocean engineering design wave heights that addresses the challenges of inadequate wind speed and measured wave data in the field using High Performance Computing (HPC). The proposed method combines the Simulating WAves Nearshore (SWAN) wave model driven by wind with two different wind field models: the NCEP/NCAR reanalysis wind field and the Jelesnianski typhoon model wind field. By combining these models, the study reduces the underestimation of wind speed and inaccurate depiction of typhoon-related details. The method's effectiveness is demonstrated by applying it to calculate the design wave elements of the deep-sea breeding platform in Dongluo Island, Fujian. The study results show that the platform can experience a maximum wave height of 9.42 m during a 50-year recurrence period. The research shows that the platform's southwest corner is the most vulnerable location. This new calculation method is a significant improvement in ocean engineering design since it overcomes the limitations that come with the lack of wind speed and measured waves. By utilizing multiple wind field models, the calculated wave heights' accuracy and reliability is considerably enhanced. The application of this method to the breeding platform in Dongluo Island has yielded valuable insights for designing resilient structures in similar oceanic environments. This study demonstrates the important application of computational numerical simulations in the field of ocean engineering, providing high-precision predictive capabilities for structural design and risk assessment.

Extraction of persistent lagrangian coherent structures for the pollutant transport prediction in the Bay of Bengal

Lagrangian Coherent Structures (LCS) are the hidden fluid flow skeletons that provide meaningful information about the Lagrangian circulation. In this study, we computed the monthly climatological LCSs (cLCS) maps utilizing 24 years (1994–2017) of HYbrid Coordinate Ocean Model (HYCOM) currents and ECMWF re-analysis winds in the Bay of Bengal (BoB). The seasonal reversal of winds and associated reversal of currents makes the BoB dynamic. Therefore, we primarily aim to reveal the cLCSs associated with seasonal monsoon currents and mesoscale (eddies) processes over BoB. The simulated cLCS were augmented with the complex empirical orthogonal functions to confirm the dominant lagrangian transport pattern features better. The constructed cLCS patterns show a seasonal accumulation zone and the transport pattern of freshwater plumes along the coastal region of the BoB. We further validated with the satellite imagery of real-time oil spill dispersion and modelled oil spill trajectories that match well with the LCS patterns. In addition, the application of cLCSs to study the transport of hypothetical oil spills occurring at one of the active oil exploration sites (Krishna-Godavari basin) was described. Thus, demonstrated the accumulation zones in the BoB and confirmed that the persistent monthly cLCS maps are reasonably performing well for the trajectory prediction of pollutants such as oil spills. These maps will help to initiate mitigation measures in case of any occurrence of oil spills in the future.

Long-Term Assessment of Morocco’s Offshore Wind Energy Potential Using ERA5 and IFREMER Wind Data

Offshore wind energy is a promising resource for renewable energy development. Reanalysed wind data are unmatched by other wind data sources in providing a long-term assessment of wind power potential. In this study, 10 of the selected offshore locations close to the Moroccan coast were used to evaluate the ERA5 wind reanalysis dataset against the IFREMER-blended observational dataset covering the years 1993–2016. The ERA5 wind data’s capacity to represent wind variability in the area was confirmed by the results of the statistical methodologies used. All the reanalysed data scored better at capturing the observed wind variability at the southern sites than at the northern ones, where the wind variability was more complex. In a long-term evaluation from 1981 to 2020, the wind power potential in the Moroccan Atlantic coast was found to be very stable except in the northern sites and between Agadir and Bou Arich. Seven of the 10 sites considered were ranked as promising sites for offshore wind power generation, with wind power densities above 420 W/m2 at 100 m in height. Additionally, the change in signs in the variability toward the middle of the ERA5 record, which was seen at all locations and was also evident in the observations, did not significantly affect the yearly wind power density. However, the seasonal distribution of the latter was modified according to the local features of the seasonal variability.

Definition of springtime easterly wind bursts in the Indian Ocean and their roles in triggering positive IOD events

Using wind reanalysis dataset, we propose a definition for easterly wind bursts (EWBs) occurring in the Indian Ocean and analyze their effects on positive Indian Ocean Dipole (pIOD) events. It was found that there were eight pIOD events during the period from 1980–2020, all of which were accompanied by EWBs occurrence in spring except 2015. The significant impact of EWBs on pIOD events is through the Bjerkness feedback process, strengthening upwelling in the Eastern Indian Ocean (EIO) and triggering a westward zonal current in the equatorial Indian Ocean, both cooling the EIO and in turn strengthening the easterly wind anomalies. Further analysis reveals that the negative upper ocean heat content (OHC) anomalies in EIO, acting as a trigger of Bjerkness feedback process, also plays a critical role in the development of pIOD. Thus, the simultaneous occurrence of EWBs and negative OHC anomalies in spring is an important precursor to pIOD occurrence, although there are possible other triggers.

Three-Parameter Weibull for Offshore Wind Speed Distribution in Malaysia

It is usual practice to employ the probability density function in order to ascertain the wind energy potential. In this paper, the three-parameter Weibull model was suggested to distribute the low wind speed data at a site off the coast of Kijal, Terengganu. The maximum likelihood approach was used to determine the value of the distribution parameters. The Matrix Laboratory (MATLAB), better known for its user-friendly programming language, is used to carry out all of the analysis. The three-parameter Weibull was compared with the two-parameter Weibull and Rayleigh using the R-squared and the root mean square error (RMSE). These three distributions statistically model hourly ERA-5 reanalysis wind speeds. The three-parameter Weibull has a good performance, since it appears between the best R2 closest to 1 and RMSE the closest to 0. The R2 for the three-parameter Weibull is 0.9898, the two-parameter Weibull is 0.9874, and Rayleigh is 0.5153. While the RMSE Three-parameter Weibull is 0.0070, the two-parameter Weibull is 0.0082, and Rayleigh is 0.0677.