bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distinct Mechanisms Underlying Interannual to Decadal Variability of Observed Salinity and Nutrient Concentration in the Northern North Sea
Authors: Pätsch Johannes , Gouretski Viktor , Hinrichs Iris , Koul Vimal 
Published: April 2020

AbstractThe influence of large‐scale oceanic circulation on salinity in the northern North Sea has lead to the hypothesis that nutrient concentrations in this region are also driven by remote oceanic anomalies. Here, using a newly established biogeochemical data set of the North Sea, we show that interannual to decadal variability in winter nutrient concentrations exhibits distinct phase deviations from salinity. The variability in salinity is explained by zonal shifts in the position of the subpolar front (SPF) in the eastern North Atlantic and the associated advective delay. However, the high correlation and absence of advective delay between the position of the SPF and winter nutrient concentrations in the Shetland region (59–61°N, 1°W to 3°E) point to the role of atmospheric variability in driving concurrent changes in winter nutrient concentrations and the SPF position. Our analysis suggests that the prevailing wind direction and local distribution of winter nutrient concentrations together determine the interannual to decadal variability in winter nutrient concentrations in this region. In the analyzed observations, we find a strong spatial gradient in mean winter nutrient concentrations northwest of the Shetland region, which is absent in salinity. The horizontal shift of this spatial gradient, forced by changes in wind direction, has a larger influence on winter nutrient concentration in the Shetland region than the nutrient signal in oceanic anomalies originating from the eastern subpolar North Atlantic. Overall, we conclude that interannual to decadal variability in the observed nutrient concentrations is mainly driven by atmospheric variability here expressed as wind direction.
Impact of Cloud Physics on the Greenland Ice Sheet Near‐Surface Climate: A Study With the Community Atmosphere Model
Authors: Lenaerts Jan T. M. , Gettelman Andrew , Van Tricht Kristof , van Kampenhout Leo , Miller Nathaniel B. 
Published: April 2020

AbstractThe Greenland Ice Sheet (GrIS) is losing mass in an accelerated fashion, which is for ~60% dominated by an increase in surface melting. Clouds exhibit an important control on the GrIS surface energy balance and surface melt. Therefore, to better simulate present and future GrIS climate, it is essential to represent clouds correctly in climate models. Here we use ground (at Summit Station) and satellite remote sensing (from CloudSat‐CALIPSO) observations to evaluate GrIS cloud characteristics in several versions of the Community Atmosphere Model (CAM) over the period 2007–2012. Cloud cover, phase, water path, and radiative effects over the GrIS vary widely across the atmosphere models. Thanks to the inclusion of new cloud physical parameterizations, that is, ice nucleation and prognostic precipitation, in the most recent CAM version (CAM6), this model, amongst the various CAM versions, is best able to represent GrIS clouds, summer temperatures, and surface melting. However, CAM6 shows excessive rainfall over the ice sheet, which is an important outstanding model bias. Our study demonstrates the importance of simulating realistic cloud properties to improve climate model simulations of GrIS climate and climate change.
Climate State Dependence of Arctic Precipitation Variability
Authors: Bogerd L. , van der Linden E. C. , Krikken F. , Bintanja R. 
Published: April 2020

AbstractArctic precipitation is projected to increase more rapidly than the global mean in warming climates. However, warming‐induced changes in the variability of Arctic precipitation, which are related to surface evaporation and poleward moisture transport (PMT), are currently largely unknown. This study compares the precipitation variability in different quasi‐equilibrium climates simulated by a global climate model (EC‐Earth) and studies the underlying mechanisms. Five quasi‐equilibrium simulations of 400 years length forced with a broad range of CO2 concentrations (0.25, 0.5, 1, 2, and 4 times the current global mean) were analyzed. PMT is the dominant source of Arctic precipitation variability in colder climates when the ocean in the Arctic basin is completely covered by sea ice year‐round. Arctic precipitation variability increases from colder to warmer climates, primarily in summer. In summer, the increasingly stronger relation between Arctic sea level pressure variability and precipitation variability toward warmer climates enhances variability. In winter, the severe increase in mean precipitation (due to enhanced evaporation) exerts a comparatively small increase in variability, and precipitation variability is modulated by both PMT and evaporation, which oppose each other as they both affect the vertical and meridional moisture gradients.
A Model‐Based Investigation of Terrestrial Plant Carbon Uptake Response to Four Radiation Modification Approaches
Authors: Duan Lei , Cao Long , Bala Govindasamy , Caldeira Ken 
Published: April 2020

AbstractA number of radiation modification approaches have been proposed to counteract anthropogenic warming by intentionally altering Earth's shortwave or longwave fluxes. While several previous studies have examined the climate effect of different radiation modification approaches, only a few have investigated the carbon cycle response. Our study examines the response of plant carbon uptake to four radiation modification approaches that are used to offset the global mean warming caused by a doubling of atmospheric CO2. Using the National Center for Atmospheric Research Community Earth System Model, we performed simulations that represent four idealized radiation modification options: solar constant reduction, sulfate aerosol increase (SAI), marine cloud brightening, and cirrus cloud thinning (CCT). Relative to the high CO2 state, all these approaches reduce gross primary production (GPP) and net primary production (NPP). In high latitudes, decrease in GPP is mainly due to the reduced plant growing season length, and in low latitudes, decrease in GPP is mainly caused by the enhanced nitrogen limitation due to surface cooling. The simulated GPP for sunlit leaves decreases for all approaches. Decrease in sunlit GPP is the largest for SAI which substantially decreases direct sunlight, and the smallest for CCT, which increases direct sunlight that reaches the land surface. GPP for shaded leaves increases in SAI associated with a substantial increase in surface diffuse sunlight, and decreases in all other cases. The combined effects of CO2 increase and radiation modification result in increases in primary production, indicating the dominant role of the CO2 fertilization effect on plant carbon uptake.
A Laboratory Dust Generator Applying Vibration to Soil Sample: Mineralogical Study and Compositional Analyses
Authors: Qu Z. , Trabelsi A. , Losno R. , Monna F. , Nowak S. , Masmoudi M. , Quisefit J.‐P. 
Published: April 2020

AbstractA laboratory study was carried out using a vibrating system (SyGAVib) to produce aerosols from four soils collected in the central Tunisian region around Sfax. The aim of this device is to mimic dust emission by natural wind erosion. Using compositional analysis, the dust produced was compared to (i) dust generated in a wind tunnel by the same soils, (ii) fine sieved and (iii) original bulk soils, and (iv) naturally occurring aerosol samples collected in the same area. The relative quartz content strongly decreases from bulk to fine soils, and again from fine soils to both wind tunnel and vibration‐generated aerosols. Compositional data analysis (CoDA) clearly shows (i) a silica dilution effect in bulk soils, and (ii) that if silica is removed from the composition, the elemental compositions of fine soils and generated aerosols are similar but differ from bulk soils. Both aerosol generation methods produce material with chemical compositions that are also close to those measured in field‐sampled aerosols, and the fine soil composition is much closer to that of field and laboratory aerosols than to the parent soil. Aerosols generated from soils in the laboratory, either using a vibrating system or a wind tunnel, can be used as surrogates of the particles collected directly in the field.
Multilevel Nitrogen Additions Alter Chemical Composition and Turnover of the Labile Fraction Soil Organic Matter via Effects on Vegetation and Microorganisms
Authors: Chen Qiuyu , Niu Bin , Hu Yilun , Wang Jian , Lei Tianzhu , Xu‐Ri  , Zhou Jizhong , Xi Chuanwu , Zhang Gengxin 
Published: April 2020

AbstractGlobal nitrogen (N) deposition greatly impacts soil carbon sequestration. A 2‐yr multiple N addition (0, 10, 20, 40, 80, and 160 kg N·ha−1·yr−1) experiment was conducted in alpine grassland to illustrate the mechanisms underlying the observed soil organic matter (SOM) dynamics on the Qinghai‐Tibet Plateau (QTP). Labile fraction SOM (LF‐SOM) fingerprints were characterized by pyrolysis‐gas chromatography/tandem‐mass spectrometry, and microbial functional genes (GeoChip 4.6) were analyzed in conjunction with LF‐SOM fingerprints to decipher the responses of LF‐SOM transformation to N additions. The significant correlations between LF‐SOM and microbial biomass, between organic compounds in LF‐SOM and compound degradation‐related genes, and between LF‐SOM and net ecosystem exchange implied LF‐SOM were the main fraction utilized by microorganisms and the most sensitive fraction to N additions. The LF‐SOM increased at the lowest N addition levels (10 and 20 kg N·ha−1·yr−1) and decreased at higher N addition levels (40 to 160 kg N·ha−1·yr−1), but the decrease of LF‐SOM was weakened at 160 kg N·ha−1·yr−1 addition. The nonlinear response of LF‐SOM to N additions was due to the mass balance between plant inputs and microbial degradation. Plant‐derived compounds in LF‐SOM were more sensitive to N addition than microbial‐derived and aromatic compounds. It is predicted that when the N deposition rate increased by 10 kg N·ha−1·yr−1 on the QTP, carbon sequestration in the labile fraction may increase by nearly 170% compared with that under the current N deposition rate. These findings provide insight into future N deposition impacts on LF‐SOM preservation on the QTP.
The Influence of Lithospheric Mantle Scars and Rheology on Intraplate Deformation and Orogenesis: Insights From Tectonic Analog Models
Authors: Santimano Tasca , Pysklywec Russell 
Published: April 2020

AbstractStructural heterogeneities in the deep lithosphere have been identified as an important factor in crustal tectonics, particularly where inherited deep zones of weakness may initiate orogenesis in continent interiors. Aside from structural heterogeneity, the rheological strength of the lithosphere may also have a primary role affecting the kinematics of deformation in the lithosphere. To investigate the interplay of rheology and preexisting structures, we designed a set of physical scaled analog experiments for a convergent setting that tests (a) the presence and absence of a preexisting weak zone in the lithospheric mantle and (b) the effects of the rheological strength of the lithospheric mantle. Tectonic evolution of the model is recorded to acquire a time series data set of the velocity field and subsequently strain in the model. Results show that a weak zone in the lithospheric mantle allows deformation to be accommodated by displacement along this zone and into the overlying lower and upper crust, regardless of lithosphere strength. In contrast, a model absent of a weak zone accommodates deformation by folding and thickening of the viscous layers. The viscous lithosphere in models with a strong lithospheric mantle tends to buckle creating a sequence of brittle faulting in the upper crust. Specifically, the rheology of the lithosphere dictates the distribution of strain. Our results are considered in the context of the formation of the Eurekan fold and thrust belts in an intraplate setting on Ellesmere Island, where deformation may be related to the influence of deep lithosphere structure(s) and deep lithosphere strength.
A Dynamic Water Balance/Nonlinear Reservoir Model of a Perched Phreatic Aquifer–River System With Hydrogeologic Threshold Effects
Authors: O'Reilly Andrew M. , Holt Robert M. , Davidson Gregg R. , Patton Austin C. , Rigby James R. 
Published: April 2020

AbstractHeterogeneity in the hyporheic zone or near‐field geology can impart a threshold effect on groundwater‐surface water (GW‐SW) exchange. Variations in the texture of riverbed sediments and lithologic variations in adjacent and underlying geology are examples of common heterogeneities. Hydrologic interaction with these heterogeneities leads to distinct types of “behavior” that “switch” when surface water or groundwater levels rise above or fall below the interface of the layers of differing lithology. A dynamic water balance/nonlinear reservoir model incorporating threshold effects was developed for a perched phreatic aquifer–river system. Four conceptualizations of the system were modeled, each of which simulates a perched aquifer as a dynamical system that receives recharge from the riverbank and loses water to an underlying regional aquifer, using combinations of zero, one, or two thresholds representing layered heterogeneity in riverbank and/or aquifer lithology. Application of the model code was demonstrated at a location in the Lower Mississippi River Valley, USA. Models were run using hourly river gage measurements, calibrated to a 382‐day period of corresponding measurements in a nearby well, and further assessed for a 3.5‐yr period representing varied hydrologic conditions. The best performance was demonstrated by the model incorporating threshold effects, which elucidated four modes of GW‐SW system behavior controlled by both riverbank (riverbed hydraulic conductivity) and aquifer (hydraulic conductivity and storage coefficient) properties. The dynamical system modeling approach incorporates the salient hydrologic processes of a GW‐SW system with layered heterogeneity. Based upon fundamental mass conservation concepts, the simple dynamic water balance/nonlinear reservoir model has broad applicability to many hydrogeologic settings.
Hyper‐Resolution Continental‐Scale 3‐D Aquifer Parameterization for Groundwater Modeling
Authors: de Graaf Inge , Condon Laura , Maxwell Reed 
Published: April 2020

AbstractGroundwater is the world's most important freshwater resource. Despite this importance, groundwater flow and interactions between groundwater and other parts of the hydrological cycle are often neglected or simplified in large‐scale hydrological models. One of the challenges in simulating groundwater flow and continental to global scales is the lack of consistent globally available hydrogeological data. These input data are needed for a more realistic physical representation of the groundwater system, enabling the simulation of groundwater head dynamics and lateral flows. A realistic representation of the subsurface is especially important as large‐scale hydrological models move to finer resolutions and aim to provide accurate and locally relevant hydrologic information everywhere. In this study, we aim at improving and extending on current available large‐scale data sets providing information of the subsurface. We present a detailed aquifer representation for the continental United States and Canada at hyper resolution (250 × 250 m). We integrate local hydrogeological information, including observations of aquifer layer thickness, conductivity, and vertical structure, to obtain representative aquifer parameter values applicable to the continental scale. The methods used are simple and can be expanded to other parts of the world. Hydrological simulations were performed using the integrated hydrological model ParFlow and demonstrated improved model performance when using the new aquifer parameterization. Our results support that more detailed and accurate aquifer parameterization will advance our understanding of the groundwater system at larger scales.
An Example of Augmenting Regional Sensitivity Analysis Using Machine Learning Software
Authors: Spear Robert C. , Cheng Qu , Wu Sean L. 
Published: April 2020

AbstractRegional sensitivity analysis, RSA, has been widely applied in assessing the parametric sensitivity of environmental and hydrological models, in part because of its inherent simplicity. In that spirit, this paper reports an example of an augmented approach to improve its utility in ranking parameter importance, beyond reliance solely on the univariate marginal distributions, to include parametric interactions. Both a deterministic and a stochastic model of the transmission of dengue, an important mosquito‐borne disease, were used to explore the effect of interactions to parameter importance ranking using random forests, a commonly used method based on decision trees. The importance ranking based on random forests was generally consistent with the ranking computed from earlier methods that only examined marginal distributions, but with increased importance shown by several interacting parameters. In addition, and building on an earlier application of tree‐structured density estimation, recently developed software was used to map the regions of the parameter space supporting good fits to calibration data. These methods were also found useful in revealing the scale dependence of sensitivity analysis as well as providing a means of identifying alternative explanations for the observed behavior of the system that remain consistent with calibration criteria, a phenomenon known as equifinality.
The Drivers of River Temperatures Below a Large Dam
Authors: Daniels Miles E. , Danner Eric M. 
Published: April 2020

AbstractTemperature is a fundamental aspect of water quality in rivers, controlling the rate of many ecological processes. By disrupting the flow of water, large reservoirs and dams can fundamentally alter downstream temperature regimes by resetting the water temperature and flow boundary conditions at the dam release point. Therefore, it is critically important to understand how the volume and temperature of these releases interact with meteorological conditions to influence downstream temperature dynamics. In this study, we modeled temperature dynamics in a large regulated river (Sacramento River, CA, USA) to better understand how heat fluxes, and ultimately river temperatures, responded to different physical drivers connected to meteorology and the upstream boundary conditions established by dam operations. We used a quantitative process‐based model of river temperature (RAFT), combined with sensitivity analysis, to identify the dominant physical drivers of temperature in the Sacramento River, and explored how these drivers varied over space and time. The physical drivers that had the greatest influence on temperature dynamics were dam discharge temperature, air temperature, and solar radiation. The primary controlling factors were dam discharge temperature in the most upstream reaches and air temperature in the most downstream reaches. When isolating the effect of boundary conditions on downstream river temperature, we observed that temperatures closer to the dam under all but low flow conditions responded more to changes in dam discharge temperature than dam discharge volume. Understanding the spatial and temporal extents of drivers of heat flux and their relative importance is critical when managing for river temperature.
An Automated Seepage Meter for Streams and Lakes
Authors: Solomon D. Kip , Humphrey Eric , Gilmore Troy E. , Genereux David P. , Zlotnik Vitaly 
Published: April 2020

AbstractWe describe a new automatic seepage meter for use in soft bottom streams and lakes. The meter utilizes a thin‐walled tube that is inserted into the streambed or lakebed. A hole in the side of the tube is fitted with an electric valve. Prior to the test, the valve is open and the water level inside the tube is the same as the water level outside the tube. The test starts with closure of the valve, and the water level inside the tube changes as it moves toward the equilibrium hydraulic head that exists at the bottom of the tube. The time rate of change of the water level immediately after the valve closes is a direct measure of the seepage rate (q). The meter utilizes a precision linear actuator and a conductance circuit to sense the water level to a precision of about ±0.1 mm. The meter can also provide an estimate of vertical hydraulic conductivity (K

v
) if data are collected for a characteristic time. The detection limit for q depends on the vertical hydraulic head gradient. For K

v
= 1 m/day, q of about 2 mm/day can be measured. Results from a laboratory sand tank show excellent agreement between measured and true q, and results from a field site are similar to values from calculations based on independent measurements of K

v
and vertical head gradients. The meter can provide rapid (30 min) q measurements for both gaining and losing systems and complements other methods for quantifying surface water groundwater interactions.
Huntsville Alabama Marx Meter Array 2: Upgrade and Capability
Authors: Zhu Yanan , Bitzer Phillip , Stewart Michael , Podgorny Scott , Corredor David , Burchfield Jeff , Carey Lawrence , Medina Bruno , Stock Michael 
Published: April 2020

AbstractThe Córdoba Argentina Marx Meter Array (CAMMA), consisting of 10 second‐generation Huntsville Alabama Marx Meter Array (HAMMA 2) sensors, operated at Córdoba, Argentina, during the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign in late 2018. Initial results obtained from the campaign demonstrate that the new sensor is able to provide a significantly more detailed depiction of various lightning processes than its first generation. The lightning flashes mapped by the CAMMA and a colocated Lightning Mapping Array (LMA) were compared. The overall flash structures mapped by the CAMMA and the LMA look similar for most of the flashes. However, comparisons at smaller time scale show that the majority of CAMMA and LMA sources are not concurrent, indicating that unmatched sources were possibly due to different physical processes in leader propagation dominating different frequencies and differences in data processing and location techniques.