Wind Mixing Research Articles

Hurricane Arthur and its effect on the short-term variability of <i>p</i>CO<sub>2</sub> on the Scotian Shelf, NW Atlantic

Abstract. The understanding of the seasonal variability of carbon cycling on the Scotian Shelf in the NW Atlantic Ocean has improved in recent years; however, very little information is available regarding its short-term variability. In order to shed light on this aspect of carbon cycling on the Scotian Shelf we investigate the effects of Hurricane Arthur, which passed the region on 5 July 2014. The hurricane caused a substantial decline in the surface water partial pressure of CO2 (pCO2), even though the Scotian Shelf possesses CO2-rich deep waters. High-temporal-resolution data of moored autonomous instruments demonstrate that there is a distinct layer of relatively cold water with low dissolved inorganic carbon (DIC) slightly above the thermocline, presumably due to a sustained population of phytoplankton. Strong storm-related wind mixing caused this cold intermediate layer with high phytoplankton biomass to be entrained into the surface mixed layer. At the surface, phytoplankton begin to grow more rapidly due to increased light. The combination of growth and the mixing of low DIC water led to a short-term reduction in the partial pressure of CO2 until wind speeds relaxed and allowed for the restratification of the upper water column. These hurricane-related processes caused a (net) CO2 uptake by the Scotian Shelf region that is comparable to the spring bloom, thus exerting a major impact on the annual CO2 flux budget.

Comparison of WRF local and nonlocal boundary layer Physics in Greater Kuala Lumpur, Malaysia

The urban boundary layer (UBL) is the internal advection layer of atmosphere above urban region which determines the exchanges of momentum, water and other atmospheric constituents between the urban land surface and the free troposphere. This paper tested the performance of three planetary boundary layer (PBL) physics schemes of Weather Research and Forecast (WRF) software to ensure the appropriate representation of vertical structure of UBL in Greater Kuala Lumpur (GKL). Comparison was conducted on the performance of respective PBL schemes to generate vertical and near-surface weather profile and rainfall. Mellor-Yamada- Janjíc (MYJ) local PBL scheme coupled with Eta MM5 surface layer scheme was found to predict the near-surface temperature and wind profile and mixing height better than the nonlocal schemes during the intermonsoonal period with least influences of the synoptic background weather.

Low <i>p</i>CO<sub>2</sub> under sea-ice melt in the Canada Basin of the western Arctic Ocean

Abstract. In September 2013, we observed an expanse of surface water with low CO2 partial pressure (pCO2sea) (< 200 µatm) in the Chukchi Sea of the western Arctic Ocean. The large undersaturation of CO2 in this region was the result of massive primary production after the sea-ice retreat in June and July. In the surface of the Canada Basin, salinity was low (< 27) and pCO2sea was closer to the air–sea CO2 equilibrium (∼ 360 µatm). From the relationships between salinity and total alkalinity, we confirmed that the low salinity in the Canada Basin was due to the larger fraction of meltwater input (∼ 0.16) rather than the riverine discharge (∼ 0.1). Such an increase in pCO2sea was not so clear in the coastal region near Point Barrow, where the fraction of riverine discharge was larger than that of sea-ice melt. We also identified low pCO2sea (< 250 µatm) in the depth of 30–50 m under the halocline of the Canada Basin. This subsurface low pCO2sea was attributed to the advection of Pacific-origin water, in which dissolved inorganic carbon is relatively low, through the Chukchi Sea where net primary production is high. Oxygen supersaturation (> 20 µmol kg−1) in the subsurface low pCO2sea layer in the Canada Basin indicated significant net primary production undersea and/or in preformed condition. If these low pCO2sea layers surface by wind mixing, they will act as additional CO2 sinks; however, this is unlikely because intensification of stratification by sea-ice melt inhibits mixing across the halocline.

Modeling the optimal mix and location of wind and solar with transmission and carbon pricing considerations

Abstract This study develops a model for calculating the optimal amount of transmission, wind, and solar capacity that should be built in a grid's different regions. It also presents a framework for choosing CO2 prices by balancing increasing system cost and flexibility requirements with CO2 emissions reductions. In a simulation of the ERCOT grid, the model suggests a 60 $/ton CO2 price and an optimal investment of 27.0 GW of transmission capacity to five different regions. These regions install a total of 26.6 GW of wind and 11.1 GW of solar, representing a grid with about 60% thermal and 40% renewable capacity. This renewable mix produces 110 TWh of energy per year, 34% of the total electricity demand. The grid emits 82.2 million tons of CO2 per year under this scenario, a 65% reduction from the 237 million tons produced when no renewable capacity is installed. At the optimal renewable development solution, all coal and natural gas boiler generators have capacity factors less than 20% with many of them not being dispatched at all. While these results are specific to ERCOT, the methods and model can be used by any grid with an aim for renewable energy capacity expansion.

Response of water temperatures and stratification to changing climate in three lakes with different morphometry

Abstract. Water temperatures and stratification are important drivers for ecological and water quality processes within lake systems, and changes in these with increases in air temperature and changes to wind speeds may have significant ecological consequences. To properly manage these systems under changing climate, it is important to understand the effects of increasing air temperatures and wind speed changes in lakes of different depths and surface areas. In this study, we simulate three lakes that vary in depth and surface area to elucidate the effects of the observed increasing air temperatures and decreasing wind speeds on lake thermal variables (water temperature, stratification dates, strength of stratification, and surface heat fluxes) over a century (1911–2014). For all three lakes, simulations showed that epilimnetic temperatures increased, hypolimnetic temperatures decreased, the length of the stratified season increased due to earlier stratification onset and later fall overturn, stability increased, and longwave and sensible heat fluxes at the surface increased. Overall, lake depth influences the presence of stratification, Schmidt stability, and differences in surface heat flux, while lake surface area influences differences in hypolimnion temperature, hypolimnetic heating, variability of Schmidt stability, and stratification onset and fall overturn dates. Larger surface area lakes have greater wind mixing due to increased surface momentum. Climate perturbations indicate that our larger study lakes have more variability in temperature and stratification variables than the smaller lakes, and this variability increases with larger wind speeds. For all study lakes, Pearson correlations and climate perturbation scenarios indicate that wind speed has a large effect on temperature and stratification variables, sometimes greater than changes in air temperature, and wind can act to either amplify or mitigate the effect of warmer air temperatures on lake thermal structure depending on the direction of local wind speed changes.

Reservoir-type hydropower equivalent model based on a future cost piecewise approximation

The long-term (LT) scheduling of reservoir-type hydropower plants is a multistage stochastic dynamic problem that has been traditionally solved using the stochastic dual dynamic programming (SDDP) approach. This LT schedule of releases should be met through short-term (ST) scheduling decisions obtained from a hydro-thermal scheduling that considers uncertainties. Both time scales can be linked if the ST problem considers as input the future cost function (FCF) obtained from LT studies. Known the piecewise-linear FCF, the hydro-scheduling can be solved as a one-stage problem. Under certain considerations a single segment of the FCF can be used to solve the schedule. From this formulation an equivalent model for the hydropower plant can be derived and used in ST studies. This model behaves accordingly to LT conditions to be met, and provides a marginal cost for dispatching the plant. A generation company (GENCO) owning a mix of hydro, wind, and thermal power will be the subject of study where the model will be implemented. The GENCO faces the problem of scheduling the hydraulic resource under uncertainties from e.g. wind and load while determining the market bids that maximize its profit under uncertainties from market prices. A two-stage stochastic unit commitment (SUC) for the ST scheduling implementing the equivalent hydro model will be solved.

Delay-Doppler characteristics of surface interacting underwater sound

The interaction of underwater sound with the ocean surface is investigated. Laboratory measurements of the delay-Doppler structure of the surface multipath at a transmission frequency of 300 kHz are compared to physics based analytic predictions. Channel impulse responses and channel scattering functions are measured when the surface is characterized by wind generated roughness, swell-like roughness, and a mix of wind and swell. The distribution of surface scattered energy across delay time and Doppler shift is presented as a function of wind speed ranging from 0.5 m/s to 11.0 m/s. The effect of wave shape and nominal out-of-plane grazing angle on the delay time spread and Doppler spread of the surface multipath are also considered. Proper characterization of surface interacting acoustic energy has direct application to the improved performance of shallow water and near surface underwater acoustic communications systems.

Preparation and catalytic performance of activated carbon non-woven fabric Pt-based catalyst

For the purpose of systematically characterizing the ambient volatile organic compound (VOC) levels and their emission sources in the Pearl River Delta (PRD) of China, a grid study with VOC samples simultaneously taken at 84 sites over the PRD was conducted in summer and winter of 2008 and 2009. Positive Matrix Factorization (PMF) model was applied to identify the major VOC contributing sources and their temporal and spatial variations. Nine sources were identified, with gasoline exhaust, industrial emission and LPG leakage & propellant emission the top three significant sources. They accounted for 23%, 16% and 13% of the ambient VOC levels, respectively. Control measures should be therefore targeted on mitigating the VOC emissions from the traffic-related and industrial-related sources. The total VOC level did not show strong increase from 5 a.m. to 10 a.m. during all the four sampling campaigns, which may result from stronger wind and higher mixing height at 10 a.m. Three hotspot areas with significant VOC contributions were identified by source apportionment analysis: (1) the Pearl River Estuary; (2) an area from Central Dongguan to North Shenzhen; and (3) the Zhuhai–Zhongshan–Jiangmen area. For better characterizing the roles of VOC and NOx in producing the secondary pollutants and to identify specific sources emitting excessive concentrations of precursors, the emission-oriented Photochemical Assessment Monitoring Station (PAMS) network is recommended to be established in the PRD. Three PAMS networks are suggested in correspondence to the three identified hotspot areas.

Measurement of scattering and absorption properties of dust aerosol in a Gobi farmland region of northwestern China – a potential anthropogenic influence

Abstract. We conducted a comprehensive field campaign to explore the optical characteristics of mineral dust in Dunhuang farmland near the Gobi Desert of northwest China during spring of 2012. The day-to-day and diurnal variations of dust aerosol showed prominent features throughout the experiment, primarily attributable to frequent dust events and local anthropogenic emissions. The overall average mass concentrations of the particulate matter with an aerodynamic diameter less than 10 µm (PM10), light scattering coefficient (σsp, 670), absorption coefficient (σap, 670), and single-scattering albedo (SSA670) were 113 ± 169 µg m−3, 53.3 ± 74.8 Mm−1, 3.2 ± 2.4 Mm−1, and 0.913 ± 0.05, respectively, which were comparable to the background levels in the southern United States but smaller than those in the eastern and other northwestern Chinese cities. The anthropogenic dust produced by agricultural cultivations (e.g., land planning, plowing, and disking) exerted a significant superimposed effect on high dust concentrations in Dunhuang farmland prior to the growing season (i.e., from 1 April to 10 May). Strong south valley wind and vertical mixing in daytime scavenged the pollution, and the weak northeast mountain wind and stable inversion layer at night favorably accumulated the air pollutants near the surface. In the afternoon (13:00–18:00 LT, local time), mean SSA670 was 0.945 ± 0.04 predominantly from dust particles, whereas finer particles and lower SSA670 values ( ∼ 0.90–0.92) were measured at night, suggesting the potential influence by the mixed dust pollutants. During a typical biomass burning event on 4 April 2012, σap, 670 increased from ∼ 2.0 to 4.75 Mm−1 and SSA670 changed from ∼ 0.90 to ∼ 0.83, implying remarkable modification of aerosol absorptive properties induced by human activities. The findings of this study would help to advance an in-depth understanding of the interaction among dust aerosol, atmospheric chemistry, and climate change in a desert source region.

Threshold in North Atlantic-Arctic Ocean circulation controlled by the subsidence of the Greenland-Scotland Ridge

High latitude ocean gateway changes are thought to play a key role in Cenozoic climate evolution. However, the underlying ocean dynamics are poorly understood. Here we use a fully coupled atmosphere-ocean model to investigate the effect of ocean gateway formation that is associated with the subsidence of the Greenland–Scotland Ridge. We find a threshold in sill depth (∼50 m) that is linked to the influence of wind mixing. Sill depth changes within the wind mixed layer establish lagoonal and estuarine conditions with limited exchange across the sill resulting in brackish or even fresher Arctic conditions. Close to the threshold the ocean regime is highly sensitive to changes in atmospheric CO2 and the associated modulation in the hydrological cycle. For larger sill depths a bi-directional flow regime across the ridge develops, providing a baseline for the final step towards the establishment of a modern prototype North Atlantic-Arctic water exchange.

Multi-objective pinch analysis for power system planning

Given the rising levels of greenhouse gases and the dependence of power generation on fossil fuels, power system planning with emission constraint is of crucial importance. The objective of emission constrained power sector planning is to identify an optimal energy mix, capable of supplying the required amount of electrical energy while simultaneously keeping emissions within a predefined limit. Cost minimisation is the common objective in power sector planning. Additionally, the choice of one power plant over another involves considering a large number of social, environmental, and economic factors. A multi-objective approach is better suited to address such a complex problem. In this paper, Pinch Analysis, a single objective optimisation method, is modified to address multi-objective problems. It is then applied to simultaneously minimise the land footprint, water footprint, and capital cost associated with energy generation for the Indian power sector. A graphical solution space containing all Pareto optimal solutions for a three-objective problem is also presented. It is seen that for India, the energy mix is dominated by photovoltaic and carbon capture enabled coal power plants. The energy mix for least water footprint contains only photovoltaic power plants while that for least land footprint has a mix of wind, nuclear, small hydel, photovoltaic and biomass. Capital investment is the minimum when biomass and nuclear power plants, along with carbon capture enabled coal plants supply the demand, making biomass the only renewable to feature in the cost optimal mix. Existing coal power plants continue to supply over 35% of the energy requirements for the entire solution space. The overall results highlight the importance of solar PV and carbon capture technology.

Sensitivity of the overturning circulation of the Baltic Sea to climate change, a numerical experiment

An ocean model covering the Baltic Sea area is forced by several climate scenarios for a period extending from 1961 to 2100. The Baltic Sea overturning circulation is then analyzed. The analysis shows that this circulation decreases between the end of the 20th century and the end of the 21st century, and that the decrease is amplified in the case of the strongest greenhouse gas emission scenarios, which corresponds with the highest warming cases. The reasons behind this decrease in overturning circulation are investigated. A strong increase of thermal stratification is noticed at the level of the Baltic Sea mixed layer. Based on buoyancy flux considerations, we demonstrate that the decrease in overturning circulation coincides with the increase of thermal stratification. Evidence shows that the underlying process is linked to a smaller erosion of the halocline due to a higher shielding, itself linked with a stronger and longer seasonal thermocline. This theory works if surface wind mixing is not taken into account directly in the computation of buoyancy fluxes.

SMART-Invest: a stochastic, dynamic planning for optimizing investments in wind, solar, and storage in the presence of fossil fuels. The case of the PJM electricity market

In this paper, we present a stochastic dynamic planning model called SMART-Invest, which is capable of optimizing investment decisions in different electricity generation technologies. SMART-Invest consists of two layers: an optimization outer layer and an operational core layer. The operational model captures hourly variations of wind and solar over an entire year, with detailed modeling of day-ahead commitments, forecast uncertainties and ramping constraints. The outer layer requires optimizing an unknown, non-convex, non-smooth, and expensive-to-evaluate function. We present a stochastic search algorithm with an adaptive stepsize rule that can find the optimal investment decisions quickly and reliably. By properly capturing the marginal cost of investments in wind, solar and storage, we feel that SMART-Invest produces a more realistic picture of an optimal mix of wind, solar and storage, resulting in a tool that can provide more accurate guidance for policy makers.

Merging gauge data and models with satellite data from multiple sources to aid the understanding of long-term trends in chlorophyll-a concentrations

ABSTRACTSeveral studies have analysed the long-term trends of chlorophyll-a (chl-a) concentration and related its intensity to sea surface temperature (SST) and wind forcing. In this article, we present trends of chl-a concentrations for the period 1997–2016 derived from multi-merged satellite data and analysed the role of SST, wind mixing (WM) and surface incoming short wave flux (SISF) and river discharges in the distribution of chl-a in the coastal waters of southwest India. The results show decreasing trend of anomalies for chl-a. Chl-a shows negative trend, though not significant, with all other variables, i.e., WM, SISF and river discharge over the last two decades in the study area. Whereas, an increasing trend of SST has recorded for the region during the same period. Our results suggest that the warming of sea surface as observed from SST, decreased river input, weakening of winds and reduced solar radiation are among the most prominent reasons for decline in chl-a concentration for the study region. Further, the positive relation between chl-a with WM and SISF and negative correlation with SSTs suggest that these trends are driven by enhanced ocean stratification due to rapid warming in the Indian Ocean, which suppresses nutrient mixing from subsurface layers.

On the spatial–temporal variations in the chlorophyll-a concentration on the Peter the Great Bay shelf during the winter–spring phytoplankton bloom according to satellite and subsatellite data

Chlorophyll-a concentration (Cchl) variations in the cross section within and outside the Peter the Great Bay shelf during different stages of the winter–spring phytoplankton bloom in 2003–2005 has been considered based on a ship (obtained during the R/V Akademik M.A. Lavrent’ev voyage of February 26 to March 9, 2003) and MODIS-Aqua spectroradiometer and the SeaWiFS color-scanner satellite data. A comparison of the Cchl variability obtained from the ship and satellite data indicates that these data are inconsistent. According to satellite data obtained at the MUMM atmospheric correction, the Cchl variability is distorted less than the NIR-correction data. Studying the variations in the coefficients of light absorption by the detritus and yellow substance (adg) and light backscattering by suspended particles (bbp), Cchl, chlorophyll-a fluorescence (Fchl) according to the satellite data allow us to state that the variations in the discrepancy between the satellite and ship Cchl values are mainly caused by the variations in the content of the detritus and yellow substance in water. Based on the satellite data, it has been revealed that the adg values increase with increasing wind mixing after the phytoplankton bloom (about 2–5 km areas where the adg, Cchl, Fchl, and bbp values abruptly increased in 2005, apparently due to eddy formation). It has been indicated that the Fchl characteristic, which is close to Cchl, increases when the favorable conditions for the phytoplankton bloom deteriorate. Therefore, this characteristic cannot be used to identify Cchl under the indicated conditions.

Testing quantitative pollen dispersal models in animal-pollinated vegetation mosaics: An example from temperate Tasmania, Australia

Reconstructing past vegetation abundance and land-cover changes through time has important implications in land management and climate modelling. To date palaeovegetation reconstructions in Australia have been limited to qualitative or semi-quantitative inferences from pollen data. Testing pollen dispersal models constitutes a crucial step in developing quantitative past vegetation and land cover reconstructions. Thus far, the application of quantitative pollen dispersal models has been restricted to regions dominated by wind-pollinated plants (e.g. Europe) and their performance in a landscape dominated by animal-pollinated plant taxa is still unexplored. Here we test, for the first time in Australia, two well-known pollen dispersal models to assess their performance in the wind- and animal-pollinated vegetation mosaics of western Tasmania. We focus on a mix of wind- (6 taxa) and animal- (7 taxa) pollinated species that comprise the most common pollen types and key representatives of the dominant vegetation formations. Pollen Productivity Estimates and Relevant Source Area of Pollen obtained using Lagrangian Stochastic turbulent simulations appear to be more realistic when compared to the results from the widely used Gaussian Plume Model.

The Demand Side Management Potential to Balance a Highly Renewable European Power System

Shares of renewables continue to grow in the European power system. A fully renewable European power system will primarily depend on the renewable power sources of wind and photovoltaics (PV), which are not dispatchable but intermittent and therefore pose a challenge to the balancing of the power system. To overcome this issue, several solutions have been proposed and investigated in the past, including storage, backup power, reinforcement of the transmission grid, and demand side management (DSM). In this paper, we investigate the potential of DSM to balance a simplified, fully renewable European power system. For this purpose, we use ten years of weather and historical load data, a power-flow model and the implementation of demand side management as a storage equivalent, to investigate the impact of DSM on the need for backup energy. We show that DSM has the potential to reduce the need for backup energy in Europe by up to one third and can cover the need for backup up to a renewable share of 67%. Finally, it is demonstrated that the optimal mix of wind and PV is shifted by the utilisation of DSM towards a higher share of PV, from 19% to 36%.

Physical drivers of chlorophyll variability in the open South China Sea

AbstractThe variability of chlorophyll a concentration (Chl a) in the open South China Sea (SCS) was examined using observations from two Bio‐Argo floats. During the period of September 2014 to August 2015, there was a permanent subsurface Chl a maximum (SCM) in the depth range of 48 to 96 m in the central basin of the SCS. In the northern basin, the SCM disappeared in winter, replaced by enhanced surface layer phytoplankton with high Chl a. The values of the SCM were influenced by the vertical displacement of isotherms. Strong wind forcing and surface cooling were the main physical drivers of high surface Chl a in winter. In the north, stronger wind than in the center, lower sea surface temperature (SST) than in the center, and Kuroshio water intrusion were more favorable for the upward transport of nutrient‐rich deep water. A large amount of nitrate could be advected from the Taiwan Strait and shallow continental shelf to the northern basin in winter. A combination of strong wind mixing, surface cooling, Kuroshio water intrusion, and horizontal advection caused the winter surface phytoplankton bloom in the north.

Determination of ocean surface wave shape from forward scattered sound.

Forward scattered sound from the ocean surface is inverted for wave shape during three periods: low wind, mix of wind and swell, and stormy. Derived wave profiles are spatially limited to a Fresnel region at or near the nominal surface specular reflection point. In some cases, the surface wave profiles exhibit unrealistic temporal and spatial properties. To remedy this, the spatial gradient of inverted waves is constrained to a maximum slope of 0.88. Under this global constraint, only surface waves during low wind conditions result in a modeled surface multipath that accurately matches data. The power spectral density of the inverted surface wave field saturates around a frequency of 8 Hz while upward looking SONAR saturates at 1 Hz. Each shows a high frequency spectral slope of -4 that is in agreement with various empirical ocean wave spectra. The improved high frequency resolution provided by the scattering inversion indicates that it is possible to remotely gain information about high frequency components of ocean waves. The inability of the inversion algorithm to determine physically realistic surface waves in periods of high wind indicates that bubbles and out of plane scattering become important in those operating scenarios.

Level versus Variability Trade-offs in Wind and Solar Generation Investments: The Case of California

Hourly plant-level wind and solar generation output and real-time price data for one year from the California ISO control area is used to estimate the vector of means and the contemporaneous covariance matrix of hourly output and revenues across all wind and solar locations in the state. Annual hourly output and annual hourly revenues mean/standard deviation efficient frontiers for wind and solar resource locations are computed from this information. For both efficient frontiers, economically meaningful differences between portfolios on the efficient frontier and the actual wind and solar generation capacity mix are found. The relative difference is significantly larger for aggregate hourly output relative to aggregate hourly revenues, consistent with expected profit-maximizing unilateral entry decisions by renewable resource owners. Most of the hourly output and hourly revenue risk-reducing benefits from the optimal choice of locational generation capacities is captured by a small number of wind resource locations, with the addition of a small number of solar resource locations only slightly increasing the set of feasible portfolio mean and standard deviation combinations. Measures of non-diversifiable wind and solar energy output and revenue risk are computed using the actual market portfolio and the risk-adjusted expected hourly output or hourly revenue maximizing portfolios.