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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products.

Wolff, David B.↗
NASA NTRS2011

Scale Dependence of Spatiotemporal Intermittence of Rain

It is a common experience that rainfall is intermittent in space and time. This is reflected by the fact that the statistics of area- and/or time-averaged rain rate is described by a mixed distribution with a nonzero probability of having a sharp value zero. In this paper we have explored the dependence of the probability of zero rain on the averaging space and time scales in large multiyear data sets based on radar and rain gauge observations. A stretched exponential fannula fits the observed scale dependence of the zero-rain probability. The proposed formula makes it apparent that the space-time support of the rain field is not quite a set of measure zero as is sometimes supposed. We also give an ex.planation of the observed behavior in tenus of a simple probabilistic model based on the premise that rainfall process has an intrinsic memory.

Kundu, Prasun K.↗
NASA NTRS2014

Drop Size Distribution - Based Separation of Stratiform and Convective Rain

For applications in hydrology and meteorology, it is often desirable to separate regions of stratiform and convective rain from meteorological radar observations, both from ground-based polarimetric radars and from space-based dual frequency radars. In a previous study by Bringi et al. (2009), dual frequency profiler and dual polarization radar (C-POL) observations in Darwin, Australia, had shown that stratiform and convective rain could be separated in the log10(Nw) versus Do domain, where Do is the mean volume diameter and Nw is the scaling parameter which is proportional to the ratio of water content to the mass weighted mean diameter. Note, Nw and Do are two of the main drop size distribution (DSD) parameters. In a later study, Thurai et al (2010) confirmed that both the dual-frequency profiler based stratiform-convective rain separation and the C-POL radar based separation were consistent with each other. In this paper, we test this separation method using DSD measurements from a ground based 2D video disdrometer (2DVD), along with simultaneous observations from a collocated, vertically-pointing, X-band profiling radar (XPR). The measurements were made in Huntsville, Alabama. One-minute DSDs from 2DVD are used as input to an appropriate gamma fitting procedure to determine Nw and Do. The fitted parameters - after averaging over 3-minutes - are plotted against each other and compared with a predefined separation line. An index is used to determine how far the points lie from the separation line (as described in Thurai et al. 2010). Negative index values indicate stratiform rain and positive index indicate convective rain, and, moreover, points which lie somewhat close to the separation line are considered 'mixed' or 'transition' type precipitation. The XPR observations are used to evaluate/test the 2DVD data-based classification. A 'bright-band' detection algorithm was used to classify each vertical reflectivity profile as either stratiform or convective, depending on whether or not a clearly-defined melting layer is present at an expected height, and if present, maximum reflectivity within the melting layer as well as the corresponding height are determined. We will present results of quantitative comparisons between the XPR observations-based classifications and the simultaneous 2DVD data-based classifications. Time series comparisons will be presented for thirteen events in Huntsville.

Thurai, Merhala↗
NASA NTRS2013

A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment.

TRMM↗
NASA NTRS2018

Development of a High Speed Rain Impact Capability

Enhancement of a 2-stage light gas gun capability is under development at NASA Marshall Space Flight Center for the purpose of making rain impacts on nose cone and window materials. This paper will discuss current capabilities of this gun system and the path it took to get there. The end goal is to be able to provide realistic rain and thermal environments, simulating rain impact conditions of high speed flight (combined effects). In the past year, the ability to create impacts to simulate rain using 2, 3, and 4 mm Nylon beads in the 7,000-10,000 ft/s (2.13-3.05 km/s) range at room temperature has been demonstrated. It is desired to extend this range down to 6000 ft/s (1.83 km/s) for rain impact purposes. The size range capability will also be extended to launch particles 1 mm and smaller. In addition, a heating capability is being added to the system to potentially cover a temperature range from room temperature to 5000 F. Hydrogen light gas will extend the velocity range to 23,000-26,000 ft/s (7-8 km/s), simulating orbital debris impacts for vehicles that spend a significant amount of time in space. Particle impact precision will also be evaluated during this development process.

Gray, Perry↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain-Corrected Satellite Sea Surface Salinity Using the GMOA S2s Forecast System

The ENSO phenomenon has a significant global socio-economic impact and has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help improve the initialization of the thermocline, while satellite SST aids in constraining surface heat-fluxes, leading to improved coupled system sub-seasonal to seasonal forecasts. However, few studies have focused on improving the near-surface density and mixing through satellite sea surface salinity (SSS) assimilation. The few ocean models that assimilate satellite SSS, bias correct to normalize towards the near-surface Argo data for expediency. This assumption is likely inadequate in rainy regions, where buoyant water forms a fresh surface lens. In previous work, we showed that adjusting SSS to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 improves the near-surface density and mixed layer depth, leading to deeper thermocline and improved NINO3.4 SST forecasts. We now utilize the Soil Moisture and Ocean Salinity rain-corrected (SMOS_RC) SSS, available in SMOS-CATDS products, to represent Sb more accurately at the first model layer (e.g., 5 m). Rather than a diffusivity model as RIM, SMOS_RC uses a statistical correction dependent on Integrated Multi-satellitE Retrievals for GPM (IMERG) rain rates, established on observed SMOS SSS decreases related to Sb in the presence of rain (Supply et al., 2020). For all experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is, and a separate reanalysis assimilates SMOS_RC. We assess the impact on near-surface and subsurface dynamics by validating against observations and explore how SSS assimilation (SMOS vs SMOS_RC) impacts ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (S2S-v3, Molod et al. 2020). We show that improved estimates of density and near-surface mixing led to more accurate coupled air/sea interaction and better ENSO forecasts. The increased SSS, resulting from the removal of the instantaneous rain effect, modifies the ocean state by enhancing mixing and deepening the thermocline.

Veronica Ruiz Xomchuk↗
DOE OSTI2025

Microphysics Dominates Sub‐Cloud Rain Evaporation in Trade Cumuli Over Barbados

This study investigates the microphysical and thermodynamic influences on North Atlantic trade-cumulus rain evaporation in the sub-cloud layer over Barbados from January to November 2020. Using radar observations and a 1-D model, the results reveal that microphysical properties, namely geometric mean diameter (D g ) and raindrop concentration, primarily control evaporation processes under conditions of limited thermodynamic variability. Thermodynamic factors like cloud base height and relative humidity exert a smaller influence due to their narrow observed ranges. Small D g leads to rapid increases in rain evaporation fraction (REF), as small drops evaporate completely, while larger D g yields slower, more gradual REF changes. Frequent weak-rain cases reduce the mean evaporation flux, whereas infrequent intense-rain events substantially enhance it. These findings highlight the pivotal role of microphysical variability in shaping sub-cloud evaporation in this trade cumulus regime, while thermodynamic effects may be more important in other environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Effectiveness of Rain Cleaning on Artificially Soiled PV Modules With and Without Anti-Soiling Coatings

A simple, inexpensive methodology for testing the effectiveness of rain cleaning on artificially soiled single-cell and multi-cell photovoltaic (PV) modules having anti-soiling coatings has been developed. Using an indoor soil deposition chamber and methodology as described in our previously published work, multiple layers of soil were deposited on to the glass surface of single-cell PV modules subjected to controlled temperature and humidity cycles. Three single-cell monocrystalline PV modules are reported in this study, two of which had different anti-soiling (AS) coatings applied to the surface and the third did not have any AS coating. The set-up and operation of a rain-simulator is described as well as the rain cleaning parameters the PV test modules were exposed to. The purpose of this work is to determine the effectiveness of anti-soiling coatings and cleaning techniques, so vendor claims can be quantitatively validated using an appropriately controlled soil deposition chamber and a rain simulating spray nozzle.

14 SOLAR ENERGY↗
DOE OSTI2017

Rain retrieval from dual-frequency radar Doppler spectra: validation and potential for a midlatitude precipitating case-study

A recently developed technique retrieving the binned raindrop size distributions (DSDs) and air state parameters from ground-based K a and W-band radars Doppler spectra profiles is improved and applied to a typical midlatitude rain event. The retrievals are thoroughly validated against DSD observations of a 2D video disdrometer and independent X-band observations. Here for this case-study, profiles of rain rate, R, mean volume diameter and concentration parameter are retrieved, with low bias and standard deviations. In light rain (0.1 < R < 1 mm h -1 ), the radar reflectivities must be calibrated with a collocated disdrometer which introduces random errors due to sampling mismatch between the two instruments. The best performances are obtained in moderate rain (1 < R < 20 mm h -1 ) where the retrieval is providing self-consistent estimates of the absolute calibration and of the attenuation caused by antenna or radome wetness for both radars.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Observation and Estimation of Evapotranspiration from an Irrigated Green Roof in a Rain-Scarce Environment

While the rain-driven evapotranspiration (ET) process has been well-studied in the humid climate, the mixed irrigation and rain-driven ET process is less understood for green roof implementations in dry regions, where empirical observations and model parameterizations are lacking. This paper presents an effort of monitoring and simulating the ET process for an irrigated green roof in a rain-scarce environment. Annual ET rates for three weighing lysimeter test units with non-vegetated, sedums, and grass covers were 2.01, 2.52, and 2.69 mm d -1 , respectively. Simulations based on the three Penman–Monteith equation-derived models achieved accuracy within the reported range of previous studies. Compared to the humid climate, the overestimation of high ET rates by existing models is expected to cause a larger error in dry environments, where the enhanced ET process caused by repeated irrigations overlapped with hot, dry conditions often occurs during summer. The studied sedum species did not show significantly lower ET rates than native species, and could not effectively take advantage of the deep moisture storage. Therefore, native species, instead of the shallow-rooted species commonly recommended in humid climates, might be a better choice for green roofs in rain-scarce environments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

NASA's Global Hawk aircraft (AV1)has two microwave sensors: the passive Hurricane Imaging Radiometer (HIRAD), and the active High-altitude Imaging Wind and Rain Airborne Profiler(HIWRAP). Results are presented for a rain measurement validation opportunity that occurred in 2013, when the AV1 flew over a tropical squall-line that was simultaneously observed by the Tampa NEXRAD radar. During this experiment, Global Hawk made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD performed volume scans every 5 minutes. In this poster, the three-way inter-comparison of HIRAD Tb (base temperature), HIWRAP dbZ (decibels relative to equivalent reflectivity) and NEXRAD rain rate imagery are presented. Also, observed HIRAD Tbs are compared with theoretical radiative transfer model results using HIWRAP Rain Rates.

Retrieval↗
DOE OSTI2019

Compensating rain induced impairments in terrestrial FSO links using aperture averaging and receiver diversity

In this paper, we investigate the performance of a free space optical link considering the deteriorations caused by heavy rain. The applicability of receiver diversity and aperture averaging techniques to compensate the rain-induced impairments is analyzed on the basis of outage probability and signal to noise ratio at varying rain intensities. A 10-Mbps on-off keying modulated optical signal is taken as the test signal for which rain specific attenuation is calculated using a laboratory testbed having controlled rainfall conditions up to 250 mm/h. A 15-m single input multi output) optical link with selection combining technique at the receiver is used to observe diversity gain. Significant diversity improvement by a factor of 1.35 is observed by comparing the results with the conventional single input single output link. Experimental observations with and without aperture averaging shows average SNR gain of 1.58 and outage probability reduction of 12.3%.

42 ENGINEERING↗
DOE OSTI2018

Objective Quantification of Convective Clustering Observed During the AMIE/DYNAMO Two-Day Rain Episodes

One critical bottleneck in developing and evaluating ways to represent the mesoscale organization of convection in cumulus parameterization schemes is that there is no single accepted method of objectively quantifying the degree of convective organization or clustering from observations. This study addresses this need using high-quality S-PolKa radar data from the Atmospheric Radiation Measurement Madden-Julian Oscillation Investigation Experiment/Dynamics of the Madden-Julian Oscillation (AMIE/DYNAMO) field campaign. We first identify convective elements (contiguous convective echoes [CCEs]) from radar reflectivity observations using the rain type classification algorithm of Powell et al. (2016, https://doi.org/10.1175/JTECH-D-15-0135.1). Then we apply scalar clustering metrics, including the organization index (I org ) of Tompkins and Semie, to the radar CCEs to test their ability of quantifying convective clustering during the observed two-day rain episodes. Our results show two distinct phases of convective clustering during the two-day rain episodes, with each phase covering about 10 hr before (Phase 1) and after (Phase 2) the time of peak rain rate. In Phase 1 clustering, the number of CCEs increases and convective cells cluster as new cells form preferentially near existing convective entities. The number of CCEs decreases as the environment stabilizes in Phase 2 clustering, during which already clustered cells with associated stratiform clouds are preferred over the isolated ones. I org is capable of capturing convective clustering in both phases. The possible mechanisms for convective clustering are discussed, including cold pool-updraft feedback, moisture-convection interaction, and mesoscale circulations. Our results suggest that parameterizations of convective organization should represent the feedback processes that are responsible for the convective clustering during both phases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Distortions of the Rain Distribution With Warming, With and Without Self-Aggregation

We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative-convective equilibrium states in a cloud-resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%–30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative- and surface-flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non-trivial sensitivity to the degree of organization. Second, alternating Clausius-Clapeyron and super-Clausius-Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges. The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self-aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Comparing Green and Grey Infrastructure Using Life Cycle Cost and Environmental Impact: A Rain Garden Case Study in Cincinnati, OH

Abstract Green infrastructure ( GI ) is quickly gaining ground as a less costly, greener alternative to traditional methods of stormwater management. One popular form of GI is the use of rain gardens to capture and treat stormwater. We used life cycle assessment ( LCA ) to compare environmental impacts of residential rain gardens constructed in the Shepherd's Creek watershed of Cincinnati, Ohio to those from a typical detain and treat system. LCA is an internationally standardized framework for analyzing the potential environmental performance of a product or service by including all stages in its life cycle, including material extraction, manufacturing, use, and disposal. Complementary to the life cycle environmental impact assessment, the life cycle costing approach was adopted to compare the equivalent annual costs of each of these systems. These analyses were supplemented by modeling alternative scenarios to capture the variability in implementing a GI strategy. Our LCA models suggest rain garden costs and impacts are determined by labor requirement; the traditional alternative's impacts are determined largely by the efficiency of wastewater treatment, while costs are determined by the expense of tunnel construction. Gardens were found to be the favorable option, both financially (~42% cost reduction) and environmentally (62‐98% impact reduction). Wastewater utilities may find significant life cycle cost and environmental impact reductions in implementing a rain garden plan.

Vineyard, Donald↗
DOE OSTI2016

Linking Meteorology, Turbulence, and Air Chemistry in the Amazon Rain Forest

We describe the salient features of a field study whose goals are to quantify the vertical distribution of plant-emitted hydrocarbons and their contribution to aerosol and cloud condensation nuclei production above a central Amazonian rain forest. Using observing systems deployed on a 50-m meteorological tower, complemented with tethered balloon deployments, the vertical distribution of hydrocarbons and aerosols was determined under different boundary layer thermodynamic states. The rain forest emits sufficient reactive hydrocarbons, such as isoprene and monoterpenes, to provide precursors of secondary organic aerosols and cloud condensation nuclei. Mesoscale convective systems transport ozone from the middle troposphere, enriching the atmospheric boundary layer as well as the forest canopy and surface layer. Through multiple chemical transformations, the ozone-enriched atmospheric surface layer can oxidize rain forest–emitted hydrocarbons. One conclusion derived from the field studies is that the rain forest produces the necessary chemical species and in sufficient amounts to undergo oxidation and generate aerosols that subsequently activate into cloud condensation nuclei.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

On the Realism of the Rain Microphysics Representation of a Squall Line in the WRF Model. Part I: Evaluation with Multifrequency Cloud Radar Doppler Spectra Observations

This study investigates how multifrequency cloud radar observations can be used to evaluate the representation of rain microphysics in the WRF Model using two bulk microphysics schemes. A squall line observed over Oklahoma on 12 June 2011 is used as a case study. A recently developed retrieval technique combining observations of two vertically pointing cloud radars provides quantitative description of the drop size distribution (DSD) properties of the transition and stratiform regions of the squall-line system. For the first time, the results of this multifrequency cloud radar retrieval are compared to more conventional retrievals from a nearby polarimetric radar, and a supplementary result of this work is that this new methodology provides a much more detailed description of the DSD vertical and temporal variations. While the extent and evolution of the squall line is well reproduced by the model, the 1-h low-reflectivity transition region is not. In the stratiform region, simulations with both schemes are able to reproduce the observed downdraft and the associated significative subsaturation below the melting level, but with a slight overestimation of the relative humidity. Under this subsaturated air, the simulated rain mixing ratio continuously decreases toward the ground, in agreement with the observations. Conversely, the profiles of the mean volume diameter and the concentration parameter of the DSDs are not well reproduced. These discrepancies pinpoint at an issue in the representation of rain microphysics. The companion paper, investigates the sources of the biases in the microphysics processes in the rain layer by performing numerical sensitivity studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Magnesium, Iron and Aluminum in LLNL Air Particulate and Rain Samples with Reference to Magnesium in Industrial Storm Water

Storm water runoff from the Lawrence Livermore National Laboratory’s (LLNL’s) main site and Site 300 periodically exceeds the Discharge Permit Numeric Action Level (NAL) for Magnesium (Mg) under the Industrial General Permit (IGP) Order No. 2014-0057-DWQ. Of particular interest is the source of magnesium in storm water runoff from the site. This special study compares new metals data from air particulate and precipitation samples from the LLNL main site and Site 300 to previous metals data for storm water from the main site and Site 300 and alluvial sediment from the main site to investigate the potential source of elevated Mg in storm water runoff. Data for three metals (Mg, Iron {Fe}, and Aluminum {Al}) were available from all media; data for additional metals, such as Europium (Eu), were available from rain, air particulates, and alluvial sediment. To attribute source, this study compared metals concentration data (for Mg, Al, and Fe) in storm water and rain; metal-metal correlations (Mg with Fe, Mg with Al, Al with Fe, Mg with Eu, Eu with Fe, and Eu with Al) in storm water, rain, air particulates, and sediments; and metal-metal ratios ((Mg/Fe, Mg/Al, Al/Fe, Mg/Eu, Eu/Fe, and Eu/Al) in storm water, rain, air particulates and sediments. The results presented in this study are consistent with a simple conceptual model where the source of Mg in storm water runoff is air particulate matter that has dry-deposited on impervious surfaces and subsequently entrained in runoff during precipitation events. Such a conceptual model is consistent with 1) higher concentrations of metals in storm water runoff than in precipitation, 2) the strong correlation of Mg with Aluminum (Al) and Iron (Fe) in both storm water and air particulates, and 3) the similarity in metal mass ratios between storm water and air particulates in contrast to the dissimilarity of metal mass ratios between storm water and precipitation or alluvial sediment. The strong correlation of Mg with Fe and Al and of Fe with Al in storm water and air particulates and the strong association of Mg, Fe, and Al with Eu in air particulates strongly suggests that a dominant source of the Mg in storm water is associated with mineral phases of natural origin. These observations all point to Mg exceedances being associated with natural sources and processes and not with anthropogenic processes or pollutant sources.

54 ENVIRONMENTAL SCIENCES↗