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This dataset contains upper air Skew-T Log-P charts taken at Grand Junction, Colorado during the ICE-L project. The imagery are in GIF format. The imagery cover the time span from 2007-10-24 12:00:00 to 2008-01-03 12:00:00.

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This dataset provides valuable environmental information about a triplets’ essay of Scots pine and Maritime pine in Spain. The data characterizes the soil profile (physicochemical parameters of organic and mineral horizons), climate, physiography, understory and overstory.

The essay, located in North-Central Spain, consists of eighteen forest plots divided in six triplets. Each triplet includes three circular plots of 15 m-radius located less than 1 km from each other: two monospecific plots dominated by P. sylvestris or P. pinaster, and one mixed plot of both species. In each plot, one pit up to 50 cm depth, one 15 m-radius overstory features inventory and ten understory 1x1 m inventories were carried out. Additionally, physiographic and climatic variables were collected per plot.

The file contains information about the 218 environmental variables studied in the eighteen forest plots.

Triplet: Triplet to which the plot belongs(1: Triplet 1; 2: Triplet 2; 3: Triplet 3; 4: Triplet 4; 5: Triplet 5; 6: Triplet 6).

Stand_type: Type of stand (PS: monospecific stand of Pinus sylvestris L.; PP: monospecific stand of Pinus pinaster Ait.; MM: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait.).

Plot: Plot identification (PS01: monospecific stand of Pinus sylvestris L. of triplet 1; PS02: monospecific stand of Pinus sylvestris L. of triplet 2; PS03: monospecific stand of Pinus sylvestris L. of triplet 3; PS04: monospecific stand of Pinus sylvestris L. of triplet 4; PS05: monospecific stand of Pinus sylvestris L. of triplet 5; PS06: monospecific stand of Pinus sylvestris L. of triplet 6; MM01: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 1; MM02: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 2; MM03: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 3; MM04: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 4; MM05: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 5; MM06: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 6; PP01: monospecific stand of Pinus pinaster Ait. of triplet 1; PP02: monospecific stand of Pinus pinaster Ait. of triplet 2; PP03: monospecific stand of Pinus pinaster Ait. of triplet 3; PP04: monospecific stand of Pinus pinaster Ait. of triplet 4; PP05: monospecific stand of Pinus pinaster Ait. of triplet 5; PP06: monospecific stand of Pinus pinaster Ait. of triplet 6).

Lat: Plot latitude in degrees.

Long: Plot longitude in degrees.

Province: Province to which the plot belongs (B: Province of Burgos; Sp: Province of Soria).

Municipality: Municipality to which the plot belongs (M: Town of Mamolar; HP: Town of Hontoria del Pinar; N: Town of Navaleno; St: Town of Soria; CP: Town of Cabrejas del Pinar).

Forest: Name of the forest where is located the plot (MB: Mata Blanca; MR: Mata Robledo; FP: Fuente del Pardo; PM: Pajar de la molinera; MP: Mojon Pardo; CM: Cueva de Matarubias).

Alti: Plot elevation above sea level in m a.s.l.

Slope: Slope (gradient) of the plot in percentage.

Ori: Plot orientation in degrees.

Clim: Climate classification according to Köppen classification (1936) (Cfb: Temperate without a dry season and temperate summer climate; Csb: Temperate with dry summer climate).

XR: Accumulated rainfall in one year according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

JR: January rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ mm

FR: February rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

MR: March rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

AR: April rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

MyR: May rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

JnR: June rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

JlR: July rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

AgR: August rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

SR: September rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

OR: October rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

NR: November rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

DR: December rainfall according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in mm.

XT: Anual mean temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

JT: January temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

FT: February temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

MT: March temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

AT: April temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

MyT: May temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

JnT: June temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

JlT: July temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

AgT: August temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

ST: September temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

OT: October temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

NT: November temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

DT: December temperature according to ‘Atlas Agroclimático de Castilla y León-ITACYL-AEMET’ in ºC.

Par_mat: Soil parental material according to Spanish Geological Map on a 1M scale. (IGME , 2015) (SM: Sandstones and Marls).

Geo_age: Geological age of plot according to Spanish Geological Map on a 1M scale. (IGME, 2015) (Mz: Mesozoic age).

Soil: Soil type according to Soil-Survey-Staff (2014) (TpDx: Typic Dystroxerept; TpHx:: Typic Humixerept; AqHx:: Aquic humixerept)

Litter_B: Total Leaf Litter Biomass in Mg/ha.

FF_Th: Forest floor Thickness in cm.

Fs: Percentage of Fresh to Total Leaf Litter in %.

Fr: Percentage of Fragmented to Total Leaf Litter in %.

Hm: Percentage of Humified to Total Leaf Litter in %.

GH1: Fist genetic soil horizon according to Soil Survey-Staff (2014) (Ah: Mineral horizon with accumulation of organic matter. This horizon is formed at the soil surface or below an O horizon).

GH2: Second genetic soil horizon according to Soil Survey-Staff (2014) (AB: Transition horizon between A and B. A is a mineral horizon formed at the surface or below an O horizon, B is a subsurface horizon in which the structure of the rock is obliterated; AC: Transition horizon between A and C. A is a mineral horizon formed at the surface or below an O horizon; C is a mineral horizon, excluding hard bedrock, that is little affected by pedogenetic processes; Bw: Mineral B horizon where the development of color or structure are its more important diagnostic characteristics).

GH3: Third genetic soil horizon according to Soil Survey-Staff (2014) (Bw: Mineral B horizon where the development of color or structure are its more important diagnostic characteristics; C: Mineral horizon, excluding hard bedrock, that is little affected by pedogenetic processes; Cg: Mineral horizon in which a distinct pattern of mottling occurs that reflects alternating conditions of oxidation and reduction of sesquioxides, caused by seasonal surface waterlogging).

Th_H1: Thickness of the first soil horizon in cm.

Th_H2: Thickness of the second soil horizon in cm.

Th_H3: Thickness of the third soil horizon in cm.

moistCol_H1: Wet matrix color (Hue Value/Chroma) of the first soil horizon according to Munsell soil color chards (10YR2/1: black; 10YR2/2: very dark brown; 10YR3/1: very dark grey; 10YR3/2: very dark greyish brown; 10YR4/1: dark grey; 10YR6/3: pale brown).

moistCol_H2: Wet matrix colour (Hue Value/Chroma) of the second soil horizon according to Munsell soil color chards (5YR5/8: yellowish red; 7.5YR4/6: strong brown; 10YR3/2: very dark greyish brown; 10YR4/1: dark grey; 10YR4/2: dark greyish brown; 10YR4/4: dark yellowish brown with chroma 4; 10YR4/6: dark yellowish brown with chroma 6; 10YR5/3: brown; 10YR5/4: yellowish brown with chroma 4; 10YR5/6: yellowish brown with chroma 6; 10YR5/8: yellowish brown with chroma 8; 10YR6/4: light yellowish brown; 10YR6/6: brownish yellow).

moistCol_H3: Wet matrix colour (Hue Value/Chroma) of the third soil horizon according to Munsell soil color chards (5YR4/6: yellowish red; 10YR4/4: dark yellowish brown with chroma 4; 10YR4/6: dark yellowish brown with chroma 6; 10YR5/8: yellowish brown; 10YR6/1: grey).

dryCol_H1:Dry matrix color (Hue Value/Chroma) of the first soil horizon according to Munsell soil color chards (10YR4/1: dark grey; 10YR4/2: dark greyish brown; 10YR5/1: grey with value 5; 10YR5/2: greyish brown; 10YR5/3: brown; 10YR6/1: grey with value 6; 10YR6/2: light yellowish brown; 10YR7/2: light grey).

dryCol_H2: Dry matrix color (Hue Value/Chroma) of the second soil horizon according to Munsell soil color chards (7.5YR6/6: redish brown; 10YR4/1: dark grey; 10YR6/1: grey with value 6; 10YR6/2: light yellowish brown with chroma 2; 10YR6/3: pale brown; 10YR6/4: light yellowish brown with chroma 4; 10YR6/6: brownish yellow; 10YR7/3: very pale brown with value 7 and choma 3; 10YR7/4: very pale brown withvalue 7 and choma 4; 10YR8/4: very pale brown with value 8 and choma 4).

dryCol_H3: Dry matrix color (Hue Value/Chroma) of

The Delmarva Peninsula is a 220-kilometer-long headland, spit, and barrier island complex that was significantly affected by Hurricane Sandy. A U.S. Geological Survey cruise was conducted in the summer of 2014 to map the inner continental shelf of the Delmarva Peninsula using geophysical and sampling techniques to define the geologic framework that governs coastal system evolution at storm-event and longer timescales. Data collected during the 2014 cruise include swath bathymetry, sidescan sonar, chirp and boomer seismic-reflection profiles, acoustic Doppler current profiler, and sample and bottom photograph data. Processed data in raster and vector format are released here for the swath bathymetry, sidescan sonar, and seismic-reflection profiles. More information about the USGS survey conducted as part of the Hurricane Sandy Response-- Geologic Framework and Coastal Vulnerability Study can be found at the project website or on the WHCMSC Field Activity Web pages: https://woodshole.er.usgs.gov/project-pages/delmarva/ and https://cmgds.marine.usgs.gov/fan_info.php?fan=2014-002-FA

The program PanPlot was developed as a visualization tool for the information system PANGAEA. It can be used as a stand-alone application to plot data versus depth or time or in a ternary view. Data input format is tab-delimited ASCII (e.g. by export from MS-Excel or from PANGAEA). The default scales and graphic features can individualy be modified. PanPlot graphs can be exported in platform-specific interchange formats (EMF, PICT) which can be imported by graphic software for further processing.

Raw data for the manuscript.

"011221_Run15_533.tif" - an uncropped gel scan (Fig. 1A)

"Fig. 1B.pdf" - a raw plot for Fig. 1B exported from the shiny app

"Fig. 1C.pdf" - a raw plot for Fig. 1C exported from the shiny app

"Fig. 2A.pdf" - a raw plot for Fig. 2A exported from the shiny app

"Fig. 2B.png" - a raw screenshot from the shiny app for Fig. 2B

"Fig. 3.pdf" - a raw plot for Fig. 3 exported from the shiny app

This dataset contains Rawinsonde NWS Constant Pressure Plot imagery. Each day contains images for 250 MB, 500 MB, 700 MB, 850MB and 925 MB analysis at 00:00 and 12:00 for the entire United States.

The program PanPlot 2 was developed as a visualization tool for the information system PANGAEA. It can be used as a stand-alone application to plot data versus depth or time. Data input format is tab-delimited ASCII (e.g. by export from MS-Excel or from PANGAEA). The default scales and graphic features can individualy be modified. PanPlot 2 graphs can be exported in several image formats (BMP, PNG, PDF, and SVG) which can be imported by graphic software for further processing. […]

Replication data to reproduce the results presented in J. Schneider & S. Kiemle, K. Heck, Y. Rothfuss, I. Braud, R. Helmig, J. Vanderborght (2024) Analysis of Experimental and Simulation Data of Evaporation-Driven Isotopic Fractionation in Unsaturated Porous Media. (Under review) Vadose Zone. The replication data contains numerical data sets generated via the numerical simulator tools DuMuX and SiSPAT-isotope and experimental data published by Rothfuss (2015). Further, this data set provides python scripts and a MatLAB script to reproduce the displayed figures in the linked publication. Structure of the dataset: input_experimental_data.tar.gz: contains the modified experimental data from Rotfuss et al.(2015). The raw data have been structured and organized to ease the evaluation and the comparison with the numerical simulation. input_sispat_data.tar.gz: contains the numerical results derived by SiSPAT-isotope. This dataset aims to replicate the experiments. input_dumux_data.tar.gz: contains the numerical results derived by DuMuX. This dataset aims to replicate the experiments. input_sispat_data_sensitivity.tar.gz: contains the numerical results derived by SiSPAT-isotope. This dataset contains the data to analyze the model toward its sensitivity to the residual water saturation. input_dumux_data_sensitivity.tar.gz: contains the numerical results derived by DuMuX. This dataset contains the data to analyze the model toward its sensitivity to the residual water saturation. evaluation_scripts_comparison.tar.gz: contains all evaluation scripts to reproduce the figures dealing with comparing DuMuX, SiSPAT-isotope, and the experiments. evaluation_scripts_sensitivity.tar.gz: contains all evaluation scripts to reproduce the figures dealing with comparing DuMuX and SiSPAT-isotope in terms of analyzing their sensitivity towards the residual water saturation. The main focus lies on the folder evaluation_scripts_comparison.tar.gz and evaluation_scripts_sensitivity.tar.gz which contains all python scripts which have been used to further post-process all data which are stored in the other folders. evaluation_scripts_comparison.tar.gz: plot_depthprofiles_H2O18_all.py : plots the H2O18 isotope concentration over time for various depths, and compares the results for Dumux, SiSPAT-isotope and the experiments. plot_depthprofiles_HDO_all.py : plots the HDO isotope concentration over time for various depths and compares the results for Dumux, SiSPAT-isotope, and the experiments. plot_depthprofiles_Sat_all.py : plots the Saturation over time for various depths and compares the results for Dumux, SiSPAT-isotope, and the experiments. plot_evaporation.py : plots the evaporation rate and the cumulative evaporation rate over the regarded time for Dumux, SiSPAT-isotope, and the experiments. plot_evaporation_front.py : plots the evaporation front for the numerical results derived by Dumux, and compares a fine resolved resolution with different approximation methods. plot_isotopeprofile.py : plots the isotope profiles over depth at specific days. The script can compare the solutions between Dumux, SiSPAT-isotope, and the experiments. plot_isotopeprofile_close.py : plots a close-up near the soil surface of the isotope profile. This helps to focus on the area of interest. Currently, this only plots the results for Dumux code_fig_10_11.R : plots the derivation process of the aerodynamic resistance in SiSPAT-isotope and the isotope profiles for different boundary conditions using SiSPAT-isotope. evaluation_scripts_sensitivity.tar.gz: plot_depthprofiles_all.py : compares both numerical models towards their sensitivity to the residual water saturation.

The data set contains vertical profiles of diffuse light transmittance measured within six forest plots in montane Atlantic forest, São Paulo state, Brazil. The plots measured include intact, previously logged and secondary forest in a large continuous forest block of the Serra do Mar State Park (Parque Estadual de Serra do Mar), and two forest fragments outside the park. In each plot 10 - 12 individual light profiles were recorded; the data set contains these individual profiles and averages profiles for each plot based on both height above the ground and depth below the canopy. Each profile was measured only once. Data was collected March - November 2015 as part of the NERC Human modified Tropical Forest Programme. Full details about this dataset can be found at https://doi.org/10.5285/4f3cf9f6-d7e5-4ae0-87c9-064b4e66a92a

Credit report of Pioneer Feed Industries Plot No G 2 Sector 5 G contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Abstract: This data set contains profile plot images (PNG format) that are derived from LADCP Current Measurement data acquired with a ship-based RDI Workhorse LADCP Sonar during Falkor expedition FK150117 conducted in 2015 (Chief Scientist: Dr. Amy Waterhouse). These data files were processed after data collection. Data were acquired as part of the project(s): Tracking the Tasman Sea's Hidden Tide.

This dataset contains upper air Skew-T Log-P charts taken at Salt Lake City, Utah during the ICE-L project. The imagery are in GIF format. The imagery cover the time span from 2007-10-24 12:00:00 to 2008-01-03 12:00:00.

Transitioning from small-scale to big-data studies has the potential to reveal new layers of intricacy that better facilitate and rationalize catalytic behavior. Given the computational resources available today, data-driven approaches can propel the next leap forward in catalyst design. Using a data-driven inspired workflow consisting of data generation, statistical analysis, and dimensionality reduction algorithms we explore trends surrounding the thermodynamics of a model hydroformylation reaction catalyzed by group 9 metals bearing phosphine ligands. Specifically, we introduce a type of “augmented” volcano plot, the energetic profile similarity (EPSim) map, as a means to easily visualize the similarity of each catalyst’s complete catalytic cycle energy profile to that of a hypothetical ideal reference profile without relying upon linear scaling relationships. In addition to quickly identifying catalysts that most closely match the ideal thermodynamic catalytic cycle energy profile, these maps also enable a more refined comparison of species lying closely in standard volcano plots. For the reaction studied here, they inherently uncover the presence of multiple sets of scaling relationships differentiated by metal type, where iridium catalysts follow distinct relationships than cobalt/rhodium catalysts and have profiles that more closely match the ideal thermodynamic profile. Reconstituted molecular volcano plots confirm the findings of the EPSim maps by showing that hydroformylation thermodynamics are governed by two distinct volcano shapes, one for iridium catalysts and a second for cobalt/rhodium species.

1) Soil profile sampling. And, also, 2) Sampling at fixed depths,3 pits until 80 cm and 2 small pits until 20 cm depth located in the 4 cardinal points of each plot. Composite soil sample of 12-14 subsamples per depth; for Bulk density, only, 5 undisturbed samples per depth ; The 1st ICP Forests Soil condition survey was carried out in 1994-1995 (Vanmechelen et al., 1997). Soil profile sampling in the BioSoil soil survey, carried out in 2007-2008 following Mikkelsen, J. et al. 2006 Guidelines for Forest Soil Profile Description, adapted for optimal field observations within the framework of the EU Forest Focus Demonstration Project. BIOSOIL. Partly based on the 4th ed. of the Guidelines for Soil Profile Description and Classification (FAO, 2006)

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

Credit report of Daryl Bates Plot contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Seabeam plots on paper were digitized and converted to pdf-documents.

This submission includes an input file, plot file, Fortran conversion file, and 3D data file from the simulation of the temperature profile within the Test Bed #1 of the EGS Collab project. The simulation was executed with PNNL's STOMP-GT simulator, which reads the input file, and produces the STOMP-GT Simulated 2D Temperature Distribution Data (plot.001302 file). The Fortran conversion file, converts the STOMP-GT Simulated 2D Temperature Distribution Data (plot.001302) 2D results in local coordinates to 3D results in Homestake coordinates.