Control Run Research Articles

Cannabis and exercise: Effects of Δ9-tetrahydrocannabinol on preference and motivation for wheel-running in mice

Recent surveys have revealed close links between cannabis and exercise. Specifically, cannabis usage before and/or after exercise is an increasingly common habit primarily aimed at boosting exercise pleasure, motivation, and performance whilst facilitating post-exercise recovery. However, whether these beliefs reflect the true impact of cannabis on these aspects of exercise is unknown. This study has thus examined the effects of cannabis' main psychoactive ingredient, namely Δ9-tetrahydrocannabinol (THC), on (i) mouse wheel-running preference and performance and (ii) running motivation and seeking behaviour. Wheel-running preference and performance were investigated using a T-maze with free and locked wheels located at the extremity of either arm. Running motivation and seeking were assessed by a cued-running operant task wherein wheel-running was conditioned by nose poking. Moreover, because THC targets cannabinoid type 1 (CB1) receptors, i.e. receptors previously documented to control running motivation, this study also assessed the role of these receptors in running preference, performance, and craving-like behaviour. Whilst acute blockade or genetic deletion of CB1 receptors decreased running preference and performance in the T-maze, THC proved ineffective on either variable. The failure of THC to affect running variables in the T-maze extended to running motivation, as assessed by cued-running under a progressive ratio (PR) reinforcement schedule. This ineffectiveness of THC was not related to the treatment protocol because it successfully increased motivation for palatable food. Although craving-like behaviour, as indexed by a cue-induced reinstatement of running seeking, was found to depend on CB1 receptors, THC again proved ineffective. Neither running motivation nor running seeking were affected when CB1 receptors were further stimulated by increasing the levels of the endocannabinoid 2-arachidonoylglycerol. These results, which suggest that the drive for running is insensitive to the acute stimulation of CB1 receptors, raise the hypothesis that cannabis is devoid of effect on exercise motivation. Future investigation using chronic administration of THC, with and without other cannabis ingredients (e.g. cannabidiol), is however required before conclusions can be drawn.

Activated sludge community and flocs morphology in response to aluminum oxide particles in the wastewater treatment system

This work aims at comparing the response of activated sludge on the exposure either to aluminum oxide microparticles (Al2O3 MPs) or aluminum oxide nanoparticles (Al2O3 NPs) in the activated sludge system operating in the continuous mode. It was for the first time made with regard to three issues: composition of the microbial community, morphology of activated sludge flocs and settling properties of the sludge. It occurred that the addition of Al2O3 MPs or NPs to activated sludge did not reduce either richness or diversity of the bacterial community. Proteobacteria was the dominant phylum in each activated sludge system studied, however the presence of Al2O3 MPs or NPs caused to the decrease of Betaproteobacteria and the increase of Alphaproteobacteria. The most abundant genera identified in the control run, i.e. without addition of Al2O3 particles, were KD1-23, Caldilinea, Dechloromonas and Pseudomonas, whereas in the runs with Al2O3 MPs or NPs these were Caldilinea, Pseudomonas, Brevundimonas, Terracoccus or Caldilinea, Rhodobacter, Dokdonella, Terracocus, respectively. It was found that Al2O3 MPs or NPs contributed to the reduction of the denitrifying bacteria representing the genera Dechloromonas and KD1-23. Regarding the flocs morphology it occurred that Al2O3 NPs influenced it stronger than Al2O3 MPs did. Al2O3 NPs made the activated sludge flocs bigger and more circular compared to those exposed to Al2O3 MPs or not exposed to any Al2O3 particles. These changes of flocs morphology influenced positively the settling properties of activated sludge and contributed to the limitation of sludge bulking.

A Robust Control Strategy With Perturbation Estimation for the Parrot Mambo Platform

This article addresses theoretical and practical challenges associated with a commercially available and ready-to-fly small-scale unmanned aircraft system (UAS) developed by Parrot SA: the Mambo quad rotorcraft. The dynamic model and the structure of the controller running onboard the UAS autopilot are not disclosed by its manufacturers. For this reason, a novel robust controller for discrete-time systems under time delays and input saturation is first developed for this platform. Then, three fundamental estimation and control challenges are addressed. The first challenge is the system identification of the X and Y translational dynamics of the UAS. To accomplish this goal, input-output data pairs are collected from different UAS platforms during real-time experimental flights. A group of dynamic models are identified from the data pairs through an extended least-squares algorithm. The obtained models are similar in nature but exhibit parametrical variations due to uncertainties in the fabrication process and different levels of wear and tear. Using a time-varying modeling approach, the second challenge addresses the development of a robust controller, which guarantees the stability of all the identified dynamic models. The third challenge addresses the development of a nonlinear controller enhanced with a perturbation estimation, which can reject, from the nominal model, the effects of model uncertainties and perturbations. These theoretical developments are presented in the form of two original theorems. The proposed strategies are ultimately validated in a set of real-time experiments, demonstrating their effectiveness and applicability.

Protective effect of multi-row HDPE board sand fences: A wind tunnel study

Recently, sand fences, made of high density polyethylene (HDPE) board, which is resistant against harsh plateau environmental conditions, could possibly be used to control the wind-blown sand along the Qinghai section of the Golmud-Korla Railway. In this paper, wind tunnel simulation was performed on the protective effect of multiple rows of HDPE board sand fences on wind-blown sand. Two parameters have been used to reflect the protective effect of sand fences, that is, windproof efficiency and sand control efficiency, referring to the reduction rates of wind speed at a height of 0.04 m and sand flux in a run of test with the fence compared those in the control run of test without it, respectively. The test results showed that when the porosity was 30%, the single-row sand fence had the best wind proof and sand control efficiency with respective values of 46% and 65.3%. The windproof efficiencies of double-row and triple-row sand fences at 20H were 59% and 62%, respectively. Compared with the windproof efficiency of the single-row sand fence, those of the two-row and three-row fences increased by 13% and 16%, respectively; The maximum sand control efficiency of the double-row and triple-row sand fences were 92.1% and 96.5%, increased by 26.8% and 31.2%, respectively, compared with that of the single-row sand fence. This study indicates that the sand control efficiency after adding one or two rows was not double or triple that of the single-row fence, while the first-row sand fence played a major protective role. Compared with the double-row sand fences, the effect of the third row sand fence in triple-row sand fences is limited, and thus double-row HDPE board sand fences with the porosity of 30% are recommended to control wind-blown sand along the Qinghai section of the Golmud-Korla Railway.

Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

Lagrangian modelling of a person lost at sea during the Adriatic scirocco storm of 29 October 2018

Abstract. On 29 October 2018 a windsurfer's mast broke about 1 km offshore from Istria during a severe scirocco storm in the northern Adriatic Sea. He drifted in severe marine conditions until he eventually beached alive and well in Sistiana (Italy) 24 h later. We conducted an interview with the survivor to reconstruct his trajectory and to gain insight into his swimming and paddling strategy. Part of survivor's trajectory was verified using high-frequency radar surface current observations as inputs for Lagrangian temporal back-propagation from the beaching site. Back-propagation simulations were found to be largely consistent with the survivor's reconstruction. We then attempted a Lagrangian forward-propagation simulation of his trajectory by performing a leeway simulation using the OpenDrift tracking code using two object types: (i) person in water in unknown state and (ii) person with a surfboard. In both cases a high-resolution (1 km) setup of the NEMO v3.6 circulation model was employed for the surface current component, and a 4.4 km operational setup of the ALADIN atmospheric model was used for wind forcing. The best performance is obtained using the person-with-a-surfboard object type, giving the highest percentage of particles stranded within 5 km of the beaching site. Accumulation of particles stranded within 5 km of the beaching site saturates 6 h after the actual beaching time for all drifting-particle types. This time lag most likely occurs due to poor NEMO model representation of surface currents, especially in the final hours of the drift. A control run of wind-only forcing shows the poorest performance of all simulations. This indicates the importance of topographically constrained ocean currents in semi-enclosed basins even in seemingly wind-dominated situations for determining the trajectory of a person lost at sea.

Sensitivity of snow models to the accuracy of meteorological forcings in mountain environments

Abstract. Snow models are usually evaluated at sites providing high-quality meteorological data, so that the uncertainty in the meteorological input data can be neglected when assessing model performances. However, high-quality input data are rarely available in mountain areas and, in practical applications, the meteorological forcing used to drive snow models is typically derived from spatial interpolation of the available in situ data or from reanalyses, whose accuracy can be considerably lower. In order to fully characterize the performances of a snow model, the model sensitivity to errors in the input data should be quantified. In this study we test the ability of six snow models to reproduce snow water equivalent, snow density and snow depth when they are forced by meteorological input data with gradually lower accuracy. The SNOWPACK, GEOTOP, HTESSEL, UTOPIA, SMASH and S3M snow models are forced, first, with high-quality measurements performed at the experimental site of Torgnon, located at 2160 m a.s.l. in the Italian Alps (control run). Then, the models are forced by data at gradually lower temporal and/or spatial resolution, obtained by (i) sampling the original Torgnon 30 min time series at 3, 6, and 12 h, (ii) spatially interpolating neighbouring in situ station measurements and (iii) extracting information from GLDAS, ERA5 and ERA-Interim reanalyses at the grid point closest to the Torgnon site. Since the selected models are characterized by different degrees of complexity, from highly sophisticated multi-layer snow models to simple, empirical, single-layer snow schemes, we also discuss the results of these experiments in relation to the model complexity. The results show that, when forced by accurate 30 min resolution weather station data, the single-layer, intermediate-complexity snow models HTESSEL and UTOPIA provide similar skills to the more sophisticated multi-layer model SNOWPACK, and these three models show better agreement with observations and more robust performances over different seasons compared to the lower-complexity models SMASH and S3M. All models forced by 3-hourly data provide similar skills to the control run, while the use of 6- and 12-hourly temporal resolution forcings may lead to a reduction in model performances if the incoming shortwave radiation is not properly represented. The SMASH model generally shows low sensitivity to the temporal degradation of the input data. Spatially interpolated data from neighbouring stations and reanalyses are found to be adequate forcings, provided that temperature and precipitation variables are not affected by large biases over the considered period. However, a simple bias-adjustment technique applied to ERA-Interim temperatures allowed all models to achieve similar performances to the control run. Regardless of their complexity, all models show weaknesses in the representation of the snow density.

Hurricane Dorian Outer Rain Band Observations and 1D Particle Model Simulations: A Case Study

The availability of high quality surface observations of precipitation and volume observations by polarimetric operational radars make it possible to constrain, evaluate, and validate numerical models with a wide variety of microphysical schemes. In this article, a novel particle-based Monte-Carlo microphysical model (called McSnow) is used to simulate the outer rain bands of Hurricane Dorian which traversed the densely instrumented precipitation research facility operated by NASA at Wallops Island, Virginia. The rain bands showed steady stratiform vertical profiles with radar signature of dendritic growth layers near −15 °C and peak reflectivity in the bright band of 55 dBZ along with polarimetric signatures of wet snow with sizes inferred to exceed 15 mm. A 2D-video disdrometer measured frequent occurrences of large drops >5 mm and combined with an optical array probe the drop size distribution was well-documented in spite of uncertainty for drops <0.5 mm due to high wind gusts and turbulence. The 1D McSnow control run and four numerical experiments were conducted and compared with observations. One of the main findings is that even at the moderate rain rate of 10 mm/h collisional breakup is essential for the shape of the drop size distribution.

Evaluation of Two Initialization Schemes for Simulating the Rapid Intensification of Typhoon Lekima (2019)

Two different initialization schemes for tropical cyclone (TC) prediction in numerical models are evaluated based on a case study of Typhoon Lekima (2019). The first is a dynamical initialization (DI) scheme where the axisymmetric TC vortex in the initial conditions is spun up through the 6-h cycle runs before the initial forecast time. The second scheme is a bogussing scheme where the analysis TC vortex is replaced by a synthetic Rankine vortex. Results show that although both initialization schemes can help improve the simulated rapid intensification (RI) of Lekima, the simulation employing the DI scheme (DIS) reproduces better the RI onset and intensification rate than that employing the bogussing scheme (BOG). Further analyses show the cycle runs of DI help establish a realistic TC structure with stronger secondary circulation than those in the control run and BOG, leading to fast vortex spinup and contraction of the radius of maximum wind (RMW). The resultant strong inner-core primary circulation favors precession of the midlevel vortex under the moderate vertical wind shear (VWS) and thus helps vortex alignment, contributing to an earlier RI onset. Afterwards, the decreased vertical shear and the stronger convection inside the RMW support the persistent RI of Lekima in DIS. In contrast, the reduced VWS is not well captured and the inner-core convection is weaker and resides farther away from the TC center in BOG, leading to slower intensification. The results imply that the DI effectively improves the prediction of the inner-core process, which is crucial to the RI forecast.

On the role of increased CO2 concentrations in enhancing the temporal clustering of heavy precipitation events across Europe

This study examines the response of the clustering behavior in heavy precipitation events across Europe to increasing atmospheric CO2 concentrations. We focus on four large-scale climate modes [Arctic Oscillation (AO), North Atlantic Oscillation (NAO), East Atlantic (EA) pattern, and Scandinavia pattern (SCAND)] that have been found to play a significant role in controlling the occurrence of these events. We use a peak over threshold (POT) method to define daily heavy precipitation events and Cox regression as the modeling framework. We consider three experiments from the Coupled Model Intercomparison Project Phase 5 (CMIP5): (1) pre-industrial control run experiments (PI-control); (2) a 1%/year increase in CO2 from the CO2 concentration in PI control to quadrupling (1pctCO2); and (3) an instantaneous quadrupling of CO2, then holding it fixed (abrupt4 × CO2). We measure the effects of CO2 by examining whether the Cox regression coefficients in the CO2 experiments are significantly different from those in the PI control. We find that (1) the increases in CO2 are unlikely to lead to changes in the spatial patterns of relationships between climate modes and heavy precipitation; (2) the increases in CO2 are likely to lead to a strengthening of the relationship between the AO/SCAND and the occurrence of heavy precipitation events, while increases in CO2 have weaker effects on the role of NAO and EA; (3) the response to an abrupt increase in CO2 is generally stronger compared to a more gradual one; (4) the responses of the integrated vapor transport and 500-mb geopotential height to increasing CO2 provide a physical mechanism to explain the enhanced relationship between climate modes and clustering of heavy precipitation events.

The control chart with practical importance for linear profile

In recent years, linear profile monitoring has become one of the popular research directions in SPC. Although the linear profile model is simple and widely applicable, it is too sensitive to small parameter changes, leading to an increase in false alarm rates. This paper presents a new control chart with the practical importance for linear profile. The control chart can be more tolerant for the small shifts comparing the conventional control chart with considering the practical importance, so as to ensure that the really important changes are detected. The simulation study shows that the new control chart can be used to detect the change of intercept and slope efficiently. Based on control chart provided by Kim (2003), we obtain the threshold for the control chart with tolerance under null hypothesis with nominal in control run length (ARL 0) and also yield run length for the situations of out of control (ARL 1).

Analyzing the impact of CryoSat-2 ice thickness initialization on seasonal Arctic Sea Ice prediction

AbstractTwin 5-month seasonal forecast experiments are performed to predict the September 2018 mean and minimum ice extent using the fully coupled Navy Earth System Prediction Capability (ESPC). In the control run, ensemble forecasts are initialized from the operational US Navy Global Ocean Forecasting System (GOFS) 3.1 but do not assimilate ice thickness data. Another set of forecasts are initialized from the same GOFS 3.1 fields but with sea ice thickness derived from CryoSat-2 (CS2). The Navy ESPC ensemble mean September 2018 minimum sea ice extent initialized with GOFS 3.1 ice thickness was over-predicted by 0.68 M km2 (5.27 M km2) vs the ensemble forecasts initialized with CS2 ice thickness that had an error of 0.40 M km2 (4.99 M km2), a 43% reduction in error. The September mean integrated ice edge error shows a 18% improvement for the Pan-Arctic with the CS2 data vs the control forecasts. Comparison against upward looking sonar ice thickness in the Beaufort Sea reveals a lower bias and RMSE with the CS2 forecasts at all three moorings. Ice concentration at these locations is also improved, but neither set of forecasts show ice free conditions as observed at moorings A and D.

Effects of Semistochastic Westerly Wind Bursts on ENSO Predictability

AbstractWesterly wind bursts (WWBs) occurring over the tropical Pacific play an important role on El Niño‐Southern Oscillation (ENSO) dynamics. Currently, climate models have significant biases in their representation of WWBs, which may limit their ability to predict ENSO. In this study, we explore the possibility of improving ENSO prediction by introducing a semistochastic WWBs parameterization scheme into the Community Earth System Model (CESM). Three ensemble hindcasts, namely, the control run with the original CESM, the WWB run with parameterized WWBs, and the Non_WWB run with built‐in WWBs removed, are conducted for the period 1982–2016. We find that CESM with parameterized WWBs enables better ENSO prediction, especially for both amplitude and spatial distribution of eastern Pacific and central Pacific El Niño events. This improvement is related to more realistic representation of WWBs which leads to better prediction of surface wind stress anomalies and thermocline depth anomalies.

The impacts of climate change on the winter water cycle of the western Himalaya

Some 180 million people depend on the Indus River as a key water resource, fed largely by precipitation falling over the western Himalaya. However, the projected response of western Himalayan precipitation to climate change is currently not well constrained: CMIP5 GCMs project a reduced frequency and vorticity of synoptic-scale systems impacting the area, but such systems would exist in a considerably moister atmosphere. In this study, a convection-permitting (4 km horizontal resolution) setup of the Weather Research and Forecasting (WRF) model is used to examine 40 cases of these synoptic-scale systems, known as western disturbances (WDs), as they interact with the western Himalaya. In addition to a present-day control run, three experiments are performed by perturbing the boundary and initial conditions to reflect pre-industrial, RCP4.5 and RCP8.5 background climates respectively. It is found that in spite of the weakening intensity of WDs, net precipitation associated with them in future climate scenarios increases significantly; conversely there is no net change in precipitation between the pre-industrial and control experiments despite a significant conversion of snowfall in the pre-industrial experiment to rainfall in the control experiment, consistent with the changes seen in historical observations. This shift from snowfall to rainfall has profound consequences on water resource management in the Indus Valley, where irrigation is dependent on spring meltwater. Flux decomposition shows that the increase in future precipitation follows directly from the projected moistening of the tropical atmosphere (which increases the moisture flux incident on the western Himalaya by 28%) overpowering the weakened dynamics (which decreases it by 20%). Changes to extreme rainfall events are also examined: it is found that such events may increase significantly in frequency in both future scenarios examined. Two-hour maxima rainfall events that currently occur in 1-in-8 WDs are projected to increase tenfold in frequency in the RCP8.5 scenario; more prolonged (1-week maxima) events are projected to increase fiftyfold.

Warm‐season precipitation drivers in northeastern Argentina: Diurnal cycle of the atmospheric moisture balance and land–atmosphere coupling

AbstractSoutheastern South America is influenced by moisture transport from lower latitudes, sustains intense convective storms and is a land–atmosphere coupling hotspot, but the interconnection between these processes is still not well understood. We present the warm‐season diurnal cycle climatology of the atmospheric water balance components in the South American Low‐Level Jet (SALLJ) exit region in northeastern Argentina during 1998–2012. Different precipitation‐based types of events (clear‐sky and rainy days) were explored together with processes tied to the land–atmosphere coupling at the daily scale. Our research was based on simulations with and without soil moisture–atmosphere coupling with the RCA4 regional climate model. A control simulation was compared with a sensitivity simulation where the soil moisture was prescribed with the daily climatological values from the control run. The ERA5 reanalysis and the satellite precipitation products TRMM‐3B42 v7 and CMORPH v1.0 bias‐corrected were used for comparative purposes. From the diurnal water balance analysis, we found that moisture flux convergence in the region is the main driver for nocturnal precipitation while local evapotranspiration feeds afternoon rain events. Rainy afternoons do not show differences between simulations, but rainy nights seem to be affected. Moreover, daily correlations between surface and boundary‐layer variables showed that the local coupling is weaker during rainy days than during clear‐sky days. Therefore, we suggest that changes in non‐local drivers, such as the moisture flux through the SALLJ, are more relevant for rainy nights than the local coupling.

Effect of Breaking Waves on Near-Surface Mixing in an Ocean-Wave Coupling System under Calm Wind Conditions

Estimating wave effects on vertical mixing is a necessary step toward improving the accuracy and reliability of upper-ocean forecasts. In this study, we evaluate the wave effects on upper-ocean mixing in the northern East China Sea in summer by analyzing the results of comparative experiments: a stand-alone ocean model as a control run and two ocean–wave coupled models that include the effect of the breaking waves (BW) and of the wave–current interaction (WCI) with a vortex-force formalism. The comparison exhibits that under weak wind conditions, the BW effect prescribed by wave dissipation energy significantly enhances near-surface mixing because of increased downward turbulent kinetic energy (TKE), whereas the WCI has little effect on vertical mixing. Increased TKE results in a mixed-layer depth deepened by ~46% relative to the control run, which provides better agreement with the observed surface thermal structure. An additional experiment with local wind–based BW parameterization confirms the importance of nonlocally generated waves that propagated into the study area upon near-surface mixing. This suggests that under calm wind conditions, waves propagated over distances can largely affect surface vertical mixing; thus, ocean–wave coupling is capable of improving the surface thermal structure.

Hydropower Potential in the Alps under Climate Change Scenarios. The Chavonne Plant, Val D’Aosta

Present and prospective climate change will likely affect the hydrological cycle in sensitive areas, such as the Alps, thus impacting water-based activities. A most representative example is hydropower production, i.e., exploitation of water to produce energy. In the Italian Alps hydropower is strictly dependent upon water from snow and ice melt, and both are decreasing in response to global warming. Here, we study the effects of potential climate change scenarios at 2100 upon hydropower production from the Chavonne plant, in Valle d’Aosta region of Italy, a run-of-the-river (ROR) plant taking water from two high altitude glacierized catchments of Val di Cogne, and Valsavarenche. We use Poli-Hydro, a state-of-the-art hydrological model to mimic the hydrological budget of the area, including ice and snow melt share. Projections of the hydrological budget were built until 2100 by means of selected climate change scenarios, under proper downscaling. We used runs of three General Circulation Models (GCMs), EC-Earth, CCSM4, and ECHAM6.0 under three Representative Concentration Pathways RCP 2.6, RCP 4.5, and RCP 8.5 from AR5 of IPCC, and of their updated version under four Shared Socio-Economic Pathways SSP1 2.6, SSP2 4.5, SSP3 7.0, and SSP5 8.5 from AR6. We then assessed hydropower production changes against a recent control run CR period (2005–2015). Mean annual flow is estimated at 14.33 m3 s−1 during CR, with ice melt contribution ca. 2%, and snow melt contribution ca. 44%. Ice cover in 2005 was estimated as 19.2 km2, reaching in 2015, 9.93 km2. Mean hydropower production was estimated at 153.72 GWh during the CR. Temperature would largely increase throughout the century (+0.93 °C on average at the half century, +2.45 °C at the end of the century). The ice covered area would be largely depleted (ca. −86%, −94% respectively), with reduced contribution of ice melt (0.23%, <0.1%, respectively) and snow melt (ca. 37%, 33%, respectively). Precipitation would show uncertain patterns, and hence incoming discharge at the plant would erratically vary (−29% to +24% half century, −27% to +59% end of century). Hydropower production displays a large dependence upon monthly discharge patterns, with mostly positive variations (+2.90% on average at half century, +6.95% on average at end of century), with its change driven by exceedance of plant’s capacity.

PDO-Related Wintertime Atmospheric Anomalies over the Midlatitude North Pacific: Local versus Remote SST Forcing

AbstractObserved wintertime atmospheric anomalies over the central North Pacific associated with the Pacific decadal oscillation (PDO) are characterized by a cold/trough (warm/ridge) structure, that is, an anomalous equivalent barotropic low (high) over a negative (positive) sea surface temperature (SST) anomaly. While the midlatitude atmosphere has its own strong internal variabilities, to what degree local SST anomalies can affect the midlatitude atmospheric variability remains unclear. To identify such an impact, three atmospheric general circulation model experiments each having a 63-yr-long simulation are conducted. The control run forced by observed global SST reproduces well the observed PDO-related cold/trough (warm/ridge) structure. However, the removal of the midlatitude North Pacific SST variabilities in the first sensitivity run reduces the atmospheric response by roughly one-third. In the second sensitivity run in which large-scale North Pacific SST variabilities are mostly kept, but their frontal-scale meridional gradients are sharply smoothed, simulated PDO-related cold/trough (warm/ridge) anomalies are also reduced by nearly one-third. Dynamical diagnoses exhibit that such a reduction is primarily due to the weakened transient eddy activities that are induced by weakened meridional SST gradient anomalies, in which the transient eddy vorticity forcing plays a crucial role. Therefore, it is suggested that midlatitude North Pacific SST anomalies make a considerable (approximately one-third) contribution to the observed PDO-related cold/trough (warm/ridge) anomalies in which the frontal-scale meridional SST gradient (oceanic front) is a key player, although most of those atmospheric anomalies are determined by the SST variabilities outside of the midlatitude North Pacific.

Ferric oxide/date seed activated carbon nanocomposites mediated dark fermentation of date fruit wastes for enriched biohydrogen production

Biohydrogen production from biomass waste, not only addresses the energy demand in a renewable manner but also resolves the safe disposal issues associated with these biowastes. Also, scalable and low-cost techniques to enhance biohydrogen production have gained more attraction and are highly explored. In this research work, date-palm fruit wastes have been studied for their biohydrogen production potential using Enterobacter aerogenes by dark fermentation. Hydrogen yield and productivity were improved through the addition of iron oxide nanoparticles (Fe3O4 NPs) and its date seed activated carbon nanocomposites (Fe3O4/DSAC) to the fermentation media. Studies on discrete inclusions of these NPs showed that the appropriate dosage of NPs promoted, while higher dosages repressed the hydrogen production performance. Optimal dosage and fermentation time was observed as 150 mg/L and 24 h for both the additives. Fe3O4/DSAC nanocomposites showed better hydrogen production enhancement than Fe3O4 NPs. Maximum hydrogen yield of 238.7 mL/g was obtained for the 150 mg/L nanocomposites, which was 65.7% higher than that of the standalone Fe3O4 NPs and three folds higher than the yield of the control run without any NPs inclusion (78.4 mL/g). Metabolites analysis showed that the hydrogen evolution followed the ethanol-acetate pathway. Formation levels of longer chain propionate and butyrate co-metabolites were significantly low in the presence of Fe3O4/DSAC than Fe3O4. The carbon support in the nanocomposites acted as an adsorbent-buffer, which favored the medium pH in-addition to the stimulatory effects of Fe3O4 NPs. Cell growth and specific hydrogenase activity analysis were also performed to supplement the hydrogen production results. Gompertz and modified Logistic kinetic models were employed for kinetic modeling of experimental hydrogen production values. The Fe3O4/DSAC nanocomposites exhibited significant application potential for the production of biohydrogen from date fruit wastes.

Assessing the Impact of Different Ocean Analysis Schemes on Oceanic and Underwater Acoustic Predictions

AbstractAssimilating oceanic observations into prediction systems is an advantageous approach for real‐time ocean environment characterization. However, its benefits to underwater acoustic predictions are not trivial due to the nonlinearity and sensitivity of underwater acoustic propagation to small‐scale oceanic features. In order to assess the potential of oceanic data assimilation, integrated ocean‐acoustic Observing System Simulation Experiments are conducted. Synthetic altimetry and in situ data were assimilated through a variational oceanographic data assimilation system. The predicted sound speed fields are then ingested in a range‐dependent acoustic model for transmission loss (TL) predictions. The predicted TLs are analyzed for the purpose of (i) evaluating the contributions of different sources to the uncertainties of oceanic and acoustic forecasts and (ii) comparing the impact of different oceanic analysis schemes on the TL prediction accuracy. Using ensemble member clustering techniques, the contributions of boundary conditions, ocean parameterizations, and geoacoustic characterization to acoustic prediction uncertainties are addressed. Subsequently, the impact of three‐dimensional variational (3DVAR), 4DVAR, and hybrid ensemble‐3DVAR data assimilation on acoustic TL prediction at two signal frequencies (75 and 2,500 Hz) and different ranges (30 and 60 km) are compared. 3DVAR significantly improves the predicted TL accuracy compared to the control run. Promisingly, 4DVAR and hybrid data assimilation further improve the TL forecasts, the hybrid scheme achieving the highest skill scores for all cases, while being the most computationally intensive scheme. The optimal scheme choice thus depends on requirements on the accuracy and computational constraints. These findings foster developments of coupled data assimilation for operational underwater acoustic propagation.