Simple Empirical Approach Research Articles

Global Estimates of Particulate Organic Carbon Concentration From the Surface Ocean to the Base of the Mesopelagic

AbstractThe gravitational settling of organic particles from the surface to the deep ocean is an important export pathway and one of the largest components of the ocean carbon pump. The strength and efficiency of the gravitational pump are often measured using metrics reliant on reference depths and empirical formulations that parameterize the relationship between depth and the flux or concentration of particulate organic carbon (POC). Here, BGC‐Argo profiles were used to identify the isolume where POC concentration, [POC], starts to decline, revealing attenuation trends below this isolume that are remarkably consistent across the global ocean. We developed a simple empirical approach that uses observations from the first optical depth to predict [POC] from the surface ocean to the base of the mesopelagic (1,000 m), allowing assessments of spatial and temporal variability in gravitational pump efficiencies. We find that rates of [POC] attenuation are high in areas of high biomass and low in areas of low biomass, supporting the view that bloom events sometimes result in a relatively weak deep biological pump that is characterized by low transfer efficiency to the base of the mesopelagic. Our isolume‐based attenuation model was applied to satellite data to yield the first remote sensing‐based estimate of integrated global POC stock of 3.02 Pg C over the top 1,000 m, with an uncertainty of 0.69 Pg C. Of this total stock, approximately 1.02 Pg was located above the reference isolume where [POC] begins to attenuate.

Quantification of error sources in wave runup estimates on two Mediterranean sandy beaches

Projected future sea level rise and marine storminess is a serious threat for beaches as they induce beach flooding and erosion. Among other factors, wave runup play an important role in beach evolution and must be robustly assessed. However, little attention has been paid to the uncertainties associated to its characterization and how do they compare to other sources of uncertainty. We have quantified the impact of several sources of error in the estimation of wave runup on sandy beaches. Understanding what factors are more influential in the accuracy of the results will help to determine the main sources of uncertainty in beach flooding projections. A calibrated state-of-the-art numerical modelling system has been setup for two beaches in the Mallorca islands (NW Mediterranean). The system has been forced with the best available information of nearshore incoming waves and has been validated against observations to define the benchmark accuracy. To determine the key factors affecting the accuracy of the system's results, different systems configurations have been tested with different degrees of complexity.Our results show that using the most sophisticated modelling system with the best information on boundary conditions, bottom bathymetry, and submerged vegetation leads to a swash RMSE comparable to the standard deviation of the observed swash. We have also found that the choice of lateral boundary conditions (i.e., source of information for the incoming waves) can double the RMSE and induce large biases. Our results also show that using a simple empirical approach usually underestimates the wave runup. However, in locations with vegetated seabed there is a compensation error, and the empirical approach can lead to acceptable results if forced by nearshore waves. In addition, we have compared the error estimates obtained with uncertainties associated to projected sea level rise. Our findings suggest that the uncertainty associated with wave runup modelling should be considered in the assessment of the total uncertainty of future beach flooding, since the analysis performed indicates that this uncertainty can account for between 16% and 60% of the uncertainties linked to mean sea level projections.

International production chains and the pollution offshoring hypothesis: An empirical investigation

Most analyses of the impact of heterogeneous environmental policy stringency on the location of industrial firms have considered the relocation of entire activities – the well-known pollution haven hypothesis. Yet international enterprises may decide to only offshore a subset of their production chain – the so-called pollution offshoring hypothesis (POH). We introduce a simple empirical approach to test the POH combining a comprehensive industrial mergers and acquisitions dataset, a measure of sectoral linkages based on input-output tables and an index score of environmental policy stringency. Our results confirm the impact of relative environmental policy stringency on firms’ decisions to engage in cross-country M&As. Our findings also indicate that environmental taxation have a stronger impact on international investment decisions than standards-based policies. Further, we find that transactions involving a target firm operating in a sector upstream of the acquirer are more sensitive to environmental policy stringency, especially when that sector is highly pollution-intensive. This empirical evidence is consistent with the pollution offshoring hypothesis.

Modeling Isoprene Emission Response to Drought and Heatwaves Within MEGAN Using Evapotranspiration Data and by Coupling With the Community Land Model.

We introduce two new drought stress algorithms designed to simulate isoprene emission with the Model of Emissions of Gases and Aerosols from Nature (MEGAN) model. The two approaches include the representation of the impact of drought on isoprene emission with a simple empirical approach for offline MEGAN applications and a more process-based approach for online MEGAN in Community Land Model (CLM) simulations. The two versions differ in their implementation of leaf-temperature impacts of mild drought. For the online version of MEGAN that is coupled to CLM, the impact of drought on leaf temperature is simulated directly and the calculated leaf temperature is considered for the estimation of isoprene emission. For the offline version, we apply an empirical algorithm derived from whole-canopy flux measurements for simulating the impact of drought ranging from mild to severe stage. In addition, the offline approach adopts the ratio (f PET) of actual evapotranspiration to potential evapotranspiration to quantify the severity of drought instead of using soil moisture. We applied the two algorithms in the CLM-CAM-chem (the Community Atmosphere Model with Chemistry) model to simulate the impact of drought on isoprene emission and found that drought can decrease isoprene emission globally by 11% in 2012. We further compared the formaldehyde (HCHO) vertical column density simulated by CAM-chem to satellite HCHO observations. We found that the proposed drought algorithm can improve the match with the HCHO observations during droughts, but the performance of the drought algorithm is limited by the capacity of the model to capture the severity of drought.

A correction procedure for self-induced velocity of a finite-sized particle in two-way coupled Euler–Lagrange simulations

The importance of incorporating a correction to undo the self-induced perturbation velocity of a particle, when its size becomes comparable to the Eulerian grid, in a two-way coupled Euler–Lagrange (EL) simulation is now well appreciated. The present work improves upon the prior correction procedures in a few important ways. First, the past correction procedures have been scalar-based with the assumption that the quasi-steady force is the source of self-induced velocity perturbation. Here we generalize to a vector correction procedure and thereby the directions of feedback force and relative velocity can be different. This allows the correction procedure to be used even in the presence of added-mass, history, and lift forces. Second, the effect of a nearby wall has been systematically included in the correction procedure. The correction procedure depends on fundamental Oseen solutions of streamwise and transverse regularized feedback forces. We present a Fourier transform-based analytical approach to obtaining these regularized Oseen solutions. We also present a step-by-step numerical procedure for obtaining the Oseen solutions in any EL code. With the analytical or numerical Oseen functions, the correction procedure can be easily implemented in any EL code. Iterations are required in solving the implicit correction equations and it is demonstrated that the correction procedure converges rapidly within three or four iterations. A simple empirical approach is also presented to account for unsteady effects in the correction procedure.

Common and idiosyncratic movements in Latin-American exchange rates

We propose a simple theoretical and empirical approach to differentiate between common and idiosyncratic exchange rate movements in 5 Latin-American economies: Brazil, Chile, Colombia, Mexico, and Peru. Our approach allows us to distinguish the effects of a regional exchange rate common factor and macroeconomic fundamentals differentials on exchange rates. The methodology and estimation strategy are suitable for both low- and high-frequency settings. We provide evidence that the regional common factor is important to assess the dynamics of the Latin-American exchange rates. In our estimations, the relation between exchange rates and the common factor is contemporaneous and stable during the studied period.

On the effect of reference periods on trends in percentile-based extreme temperature indices

A number of studies have noted that the use of distinct reference periods when comparing indices measuring the frequency of days exceeding a particular temperature percentile threshold leads to apparently different behaviour. We show that these differences arise because of the interplay between the increasing temperatures and the choice of reference period. The time series of the indicators calculated using the different reference periods are offset, as expected, but also diverge. Linear trends calculated over the same period from the same underlying data but where different reference periods have been used are substantially different if a change in climatological conditions has occurred between the two reference periods. We show this not only occurs in our simple empirical approach, but also for the averages of gridded observational and reanalysis datasets and also at a station level. This has implications for data set comparisons using trends in temperature percentile indices that are based on different reference periods. It also has implications for updates to standard reference periods used to monitor the climate.

Linking different drought types in a small catchment from a statistical perspective – Case study of the Wernersbach catchment, Germany

Drought is a complex natural phenomenon, which is challenging to define and to describe quantitatively. Canonical drought propagation scheme ‘meteorological → agricultural (or soil related) → hydrological’ does not always reflect the reality in a catchment. Thus it is necessary to include compound or cascading effects of precipitation, soil moisture and discharge interactions on different time scales to get a comprehensive picture on the drought characteristics, as well as on its development and recovery.We studied the linkage between droughts over multiply temporal scales and severity levels using various statistical methods for a case study of a small forested catchment in Germany. It was found that indeed different types of droughts are highly interconnected and their behavior can significantly differ from the classical scheme.A simple empirical approach gives frequencies, seasonality and trends of various combinations of droughts. It showed that among all types the test site is mostly exposed to a light hydro-meteorological one especially in autumn months with an increasing trend. Multivariate distributions can be used to evaluate joint probabilities and return periods of drought components. It was revealed that the well-known European drought in 2018 was also presented as an extreme case of a joint hydro-meteo-soil drought in the examined catchment. By Markov chains one can analyze the transition and persistence between droughts. Well-established propagation pathways between different types and severity levels of droughts with high persistence for longer droughts were found for the study area.

Binding free energies for the SAMPL8 CB8 \u201cDrugs of Abuse\u201d challenge from umbrella sampling combined with Hamiltonian replica exchange

Umbrella sampling along a one-dimensional order parameter in combination with Hamiltonian replica exchange was employed to calculate the binding free energy of five guest molecules with known affinity to cucurbit[8]uril. A simple empirical approach correcting for the overestimation of the affinity by the GAFF force field was proposed and subsequently applied to the seven guest molecules of the “Drugs of Abuse” SAMPL8 challenge. Compared to the uncorrected binding free energies, the systematic error decreased but quantitative agreement with experiment was only reached for a few compounds. From a retrospective analysis a weak point of the correction term was identified.

Empirically classifying network mechanisms

Network data are often explained by assuming a generating mechanism and estimating related parameters. Without a way to test the relevance of assumed mechanisms, conclusions from such models may be misleading. Here we introduce a simple empirical approach to mechanistically classify arbitrary network data as originating from any of a set of candidate mechanisms or none of them. We tested our approach on simulated data from five of the most widely studied network mechanisms, and found it to be highly accurate. We then tested 1284 empirical networks spanning 17 different kinds of systems against these five widely studied mechanisms. We found that 387 (30%) of these empirical networks were classified as unlike any of the mechanisms, and only 1% or fewer of the networks classified as each of the mechanisms for which our approach was most sensitive. Based on this, we use Bayes’ theorem to show that most of the 70% of empirical networks our approach classified as a mechanism could be false positives, because of the high sensitivity required of a test to detect rarely occurring mechanisms. Thus, it is possible that very few of our empirical networks are described by any of these five widely studied mechanisms. Additionally, 93 networks (7%) were classified as plausibly being governed by each of multiple mechanisms. This raises the possibility that some systems are governed by mixtures of mechanisms. We show that mixtures are often unidentifiable because different mixtures can produce structurally equivalent networks, but that we can still accurately predict out-of-sample functional properties.

Linear Relationship of a Soil Total Water Potential Function and Relative Yield—A Technique to Control Salinity and Water Stress on Golf Courses and Other Irrigated Fields

A simple empirical approach is proposed for the determination of crop relative yield (%) through the soil total water potential (kPa). Recurring to decimal logarithms, from analytical exponential expressions, a linear simple relationship of soil total water potential Ψt (matric Ψm + potential Ψo) function and crop relative yield was studied and developed. The combination of the salinity model, the soil water retention model and the matric potential approach were used to reach this objective. The representation of turfgrass crop relative yield (%) versus a function of soil total water potential f(Ψt) values was shown through a log-normal graph (y = a + mx); the log scale axis “y” (ordinates) defines relative yield Yr, being two the origin ordinate “a” and “m” the slope; the normal decimal scale axis “x” (abscissa) is the function of soil total water potential f(Ψt). Hence, it is possible, using only two experimental points, to define a simple linear relation between a function of soil total water potential and crop relative yield, for a soil matric potential value lower than −20 kPa. This approach was first tested on golf courses (perennial turfgrass fields), but it was further decided to extend it to other annual crop fields, focused on the model generalization. The experimental plots were established, respectively, in Algarve, Alentejo and Oeiras (Portugal) and in the North Negev (Israel). Sprinkler and trickle irrigation systems, under randomized blocks and/or water and salt gradient techniques, were used for water application with a precise irrigation water and salt distribution. Results indicated that there is a high agreement between the experimental and the prediction values (R2 = 0.92). Moreover, the precision of this very simple and easy tool applied to turfgrass fields and other irrigated soils, including their crop yields, under several different sites and climatic conditions, can contribute to its generalization.

Reanalysis of Soil Moisture Used for Rainfall Thresholds for Rainfall-Induced Landslides: The Italian Case Study

Landslides are one of the most frequent natural disasters that can endanger human lives and property. Therefore, prediction of landslides is essential to reduce economic damage and save human lives. Numerous methods have been developed for the prediction of landslides triggering, ranging from simple methods that include empirical rainfall thresholds, to more complex ones that use sophisticated physically- or conceptually-based models. Reanalysis of soil moisture data could be one option to improve landslide forecasting accuracy. This study used the publicly available FraneItalia database hat contains almost 9000 landslide events that occurred in the 2010–2017 period in Italy. The Copernicus Uncertainties in Ensembles of Regional Reanalyses (UERRA) dataset was used to obtain precipitation and volumetric soil moisture data. The results of this study indicated that precipitation information is still a much better predictor of landslides triggering compared to the reanalyzed (i.e., not very detailed) soil moisture data. This conclusion is valid both for local (i.e., grid) and regional (i.e., catchment-based) scales. Additionally, at the regional scale, soil moisture data can only predict a few landslide events (i.e., on average around one) that are not otherwise predicted by the simple empirical rainfall threshold approach; however, this approach on average, predicted around 18 events (i.e., 55% of all events). Despite this, additional investigation is needed using other (more complete) landslide databases and other (more detailed) soil moisture products.

Evaluating the applicability of a screen diffraction approximation to local volcano infrasound

Atmospheric acoustic waves from volcanoes at infrasonic frequencies (0.01–20 Hz) can be used to estimate source parameters for hazard modeling, but signals are often distorted by wavefield interactions with topography, even at local recording distances (<15 km). We present new developments toward a simple empirical approach to estimate attenuation by topographic diffraction at reduced computational cost. We investigate the applicability of a thin screen diffraction relationship developed by Maekawa [1968, doi: https://doi.org/10.1016/0003-682X(68)90020- 0]. We use a 2D axisymmetric finite-difference method to show that this relationship accurately predicts power losses for infrasound diffraction over an idealized kilometer-scale screen; thus validating the scaling to infrasonic wavelengths. However, the Maekawa relationship overestimates attenuation for realistic volcano topography (using Sakurajima Volcano as an example). The attenuating effect of diffraction may be counteracted by constructive interference of multiple reflections along concave volcano slopes. We conclude that the Maekawa relationship is insufficient as formulated for volcano infrasound, and suggest modifications that may improve the prediction capability.

Estimation of Lifetime Distribution with Missing Censoring

This paper considers the estimation of lifetime distribution based on missing-censoring data. Using the simple empirical approach rather than the maximum likelihood argument, we obtain the parametric estimations of lifetime distribution under the assumption that the failure time follows exponential or gamma distribution. We also derive the nonparametric estimation for both continuous and discrete failure distributions under the assumption that the censoring distribution is known. The loss of efficiency due to missing-censoring is shown to be generally small if the data model is specified correctly. Identifiability issue of the lifetime distribution with missing-censoring data is also addressed.

Probabilistic seismic hazard mapping of National Capital Region of India using a modified gridded seismicity model

This is the first comprehensive study for a seismic macro-zonation of the National Capital Region of India by using the probabilistic seismic hazard analysis approach. A modified gridded seismicity model is used for this purpose, in which the earthquake occurrence rates obtained using the Gutenberg-Richter's (G-R) relationships for conventional area type seismic sources are distributed non-uniformly among a grid of cells. This provides a more robust approach than the commonly used weighted sum of area sources of homogeneous seismicity and the zone-free smoothed gridded seismicity. Other distinguishing features of the present analysis include: detailed seismotectonic evaluation of the region to identify seven area type seismic sources, compilation of a comprehensive earthquake catalogue for the estimation of seismicity recurrence parameters, selection of the most appropriate ground motion prediction equation by using a database of 71 strong motion accelerograms recorded in the region, and estimation of the compatible distance parameters by associating a fictitious fault rupture plane to each grid cell with appropriate strike and dip angles. Hazards maps are prepared for the hard rock site condition in terms of the peak ground acceleration and the 5%-damping acceleration response spectrum amplitudes for several combinations of natural periods and return periods. A simple empirical approach is also developed to obtain amplification factors for modifying the uniform hazard response spectra for the rock sites to those for the soil sites with a given VS30 value. The hazard estimates from this study are found to be somewhat higher with greater site-to-site variations as compared to those from the earlier studies.

Dielectric Spectroscopy and Application of Mixing Models Describing Dielectric Dispersion in Clay Minerals and Clayey Soils.

The number of sensors, ground-based and remote, exploiting the relationship between soil dielectric response and soil water content continues to grow. Empirical expressions for this relationship generally work well in coarse-textured soils but can break down for high-surface area and intricate materials such as clayey soils. Dielectric mixing models are helpful for exploring mechanisms and developing new understanding of the dielectric response in porous media that do not conform to a simple empirical approach, such as clayey soils. Here, we explore the dielectric response of clay minerals and clayey soils using the mixing model approach in the frequency domain. Our modeling focuses on the use of mixing models to explore geometrical effects. New spectroscopic data are presented for clay minerals (talc, kaolinite, illite and montmorillonite) and soils dominated by these clay minerals in the 1 MHz–6 GHz bandwidth. We also present a new typology for the way water is held in soils that we hope will act as a framework for furthering discussion on sensor design. We found that the frequency-domain response can be mostly accounted for by adjusting model structural parameters, which needs to be conducted to describe the Maxwell–Wagner (MW) relaxation effects. The work supports the importance of accounting for soil structural properties to understand and predict soil dielectric response and ultimately to find models that can describe the dielectric–water content relationship in fine-textured soils measured with sensors.

Computation of absolute radii of 103 elements of the periodic table in terms of nucleophilicity index

The size of an atom is a very significant parameter in associating and understanding a wide range of atomic or molecular physico-chemical properties. Considering importance of the size descriptor, an ansatz to compute absolute radius (r) in terms of nucleophilicity index (N) is proposed in the present work for atoms of 103 elements of periodic table. We have followed a very simple empirical approach to compute the absolute radii of the elements invoking regression analysis the new set of radii satisfy all the sine qua non of periodic properties. Relativistic effects are pronounced in the computed radii. A close agreement is noted on comparing the computed data with the existing scales. A strong quantitative correlation is observed with ionization potential and electronegativity for the computed data. Moreover, the absolute radius calculated in the present effort is employed in calculating internuclear bond distance, a real field descriptor, for several heteronuclear diatomic molecules. A significant agreement between the theoretically computed and experimentally determined internuclear bond distances is observed, thus corroborating the consistency of our proposed model.

Soil temperature modeling in topsoil with plastic film mulching and low spring temperatures

ABSTRACT Mulching has been widely used to increase soil temperature and promote seedling emergence in areas with cold springs. However, soil temperature regulation with mulching is not well controlled, which often leads to failure in crop establishment. A two-year field study was conducted to determine and simulate the effect of transparent plastic film mulching on soil temperatures at 5 cm depth (T5) using the Denitrification-Decomposition (DNDC) model in the cold Hetao Irrigation District in north-western China. Four treatments were used: no mulch (CK), full mulching with plastic film at 140 cm width (PMF), and partial plastic film mulching at 60 cm width (PM60) and 30 cm width (PM30). Mulching did not result in a sinusoidal phase change in diurnal air temperature (Ta) between mulch and the soil surface (Tms). Tms decreased with a decrease in film width. Values of the daily averaged Tms and T5 were significantly correlated (R2 > 0.70). Simulated T5 matched the observed T5 well, with marginal overestimation in both no-mulch and mulch conditions (NSE > 0.7). Embedding a simple empirical approach for Tms calculation can reduce parameter input into the DNDC model, and result in acceptable T5 simulation.

A Quick-Look Method for Initial Evaluation of Gas Hydrate Stability below Subaqueous Permafrost

Many studies demonstrated the coexistence of subaqueous permafrost and gas hydrate. Subaqueous permafrost could be a factor affecting the formation/dissociation of gas hydrate. Here, we propose a simple empirical approach that allows estimating the steady-state conditions for gas hydrate stability in the presence of subaqueous permafrost. This approach was derived for pressure, temperature, and salinity conditions typical of subaqueous permafrost in marine (brine) and lacustrine (freshwater) environments.

Catalytic effect of capital transfers in a federal context: the case of Spanish regions

Abstract There is a broad theoretical consensus on the effects of transfers (desired incentive impacts and induced adverse effects). But, as the literature review shows, there is not an accepted methodology for the empirical evaluation of these effects. The authors suggest a simple but rigorous empirical approach to quantify the catalytic effect of conditioned transfers for investment and their asymmetric impact across regions in Spain. To identify this behaviour, they have applied different empirical approaches with frontier techniques that let them consider the frontier as a proxy for potential investment. The results show that the conditioned transfers received by the regions from higher levels of government have a stimulus effect for investments, especially in the poor regions. The authors identify several factors explaining this unbalanced catalytic effect: the political cost of tax collection, political factors, inadequate management of debt, and other variables such as the level of economic development, population density, and the economic cycle.