cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25675/10217/199723
title: Data associated with "Environmental controls on tropical sea breeze convection and resulting aerosol redistribution"

description: These data represent the model namelists and source codes used to generate perturbed parameter ensemble simulations using the Regional Atmospheric Modeling System (RAMS) version 6.2.08.
description: Sea breeze fronts propagate inland from the coastline, driving convective initiation and aerosol redistribution. Forecasting sea breezes is challenging due to uncertainties in the initial conditions, as well as the covariance and interaction of various meteorological and surface parameters. Using the Regional Atmospheric Modeling System (RAMS) coupled to an interactive land-surface model, we conduct an ensemble of 130 idealized cloud-resolving simulations by simultaneously perturbing six atmospheric and four surface parameters describing the initial conditions. To identify the key parameters impacting the inland characteristics and the intensity of the sea breeze convection in a tropical rainforest, we apply statistical emulation and variance-based sensitivity analysis techniques. This study extends a previous study which explored the impacts of various parameters on sea breeze characteristics in arid environments devoid of moist convection. Wind speed is identified as the main contributor to the inland extent, similar to the arid environment study. However, the relative impacts of surface properties on the inland extent are less significant in the moist environment where land-surface heating can be suppressed via moist convective processes and vegetation-atmosphere interactions. Two sea breeze-initiated convection regimes are also identified: shallow and deep. Over the shallow regime, where convective available potential energy (CAPE) is limited, the inversion layer strength is the primary control of the convective intensity. Over the deep regime, boundary layer temperature exerts a robust control over the CAPE and hence the convective intensity. The potential vertical redistribution of aerosols is closely related to the convective intensity.
DOI: 10.25675/10217/176160
title: Shoot level spring current annual growth on observation plots in Yellowstone's Northern Range, 2008-2013

description: Zip file includes: data and metadata file.
description: Data file and metadata sheet for column fields.
DOI: 10.25675/10217/196642
title: Dataset associated with "Detection of non-Gaussian behaviour using machine learning techniques"

description: This repository contains eleven data files for the Lorenz63 model: testdata: contains the x, y and z variables test trajectory traindata: contains the x,y and z variables training trajectory skewdata9skew: contains the z-value and p-value on the training trajectory, window length of 9 (radius 4) skewdata17skew: contains the z-value and p-value on the training trajectory, window length of 17 (radius 8) skewdata25skew: contains the z-value and p-value on the training trajectory, window length of 25 (radius 12) MLprediction9diff: Class values for the support vector machine and neural network, window length 9 points (radius 4), differences data classes MLprediction17diff: Class values for the support vector machine and neural network, window length 17 points (radius 8), differences data classes MLprediction25diff: Class values for the support vector machine and neural network, window length 25 points (radius 12), differences data classes MLprediction9skew: Class values for the support vector machine and neural network, window length 9 points (radius 4), skewness data classes MLprediction17skew: Class values for the support vector machine and neural network, window length 17 points (radius 8), skewness data classes MLprediction25skew: Class values for the support vector machine and neural network, window length 25 points (radius 12), skewness data classes.
description: An important assumption made in most variational, ensemble and hybrid based data assimilation systems is that all minimised errors are Gaussian random variables. There has been theory developed at the Cooperative Institute for Research in the Atmosphere (CIRA) that enables for the Gaussian assumption for the different types of errors to be relaxed to a lognormally distributed random variable. While this is a first step towards using more consistent distributions to model the errors involved in numerical weather/ocean prediction, we still need to be able to identify when we need to assign a lognormal distribution in a mixed Gaussian-lognormal approach. In this paper, we present some machine learning techniques and experiments with the Lorenz 63 model. Using these machine learning techniques, we show detection of non-Gaussian distributions can be done using two methods; a support vector machine, and a neural network. This is done by training past data to classify 1) differences with the distribution statistics (means and modes) and 2) the skewness of the probability density function.
DOI: 10.25675/10217/179309
title: List of plant species found in the Bale Mountains

description: A list of plant species found during multiple field sampling campaigns across and number of locations in the Bale Mountains, Ethiopia. Information includes scientific name, growth type, common name, local name and if the species is endemic or not.
DOI: 10.34740/kaggle/dsv/6058181
title: 2021 World Population (updated daily)
DOI: 10.25675/10217/234117
title: Colorado Greenhouse Gas Emission Tool (CO-GT) associated with article “A Colorado-Specific Life Cycle Assessment Model to Support Evaluation of Low-Carbon Transportation Fuels and Policy”

description: The Colorado Greenhouse Gas Emission Tool (CO-GT) is a Colorado-specific fuel life cycle model, that adopts many of the assumptions and methods of the Greenhouse Gases, Regulated Emissions and Energy Use in Transportation (GREET 2020) model developed by Argonne National Laboratory, excluding regulated emissions and energy use. The CO-GT encompasses the energy and transportation fuel system for the state of Colorado. The scope of this model is to define the well-to-wheels (WTW) GHG emissions for in-state production of fuels, production of imported crude oil and fuels and consumption of fuels along the fuel life cycle. Data used in this model were updated until 12/09/2020.
description: The transportation sector accounts for over 20 percent of greenhouse gas (GHG) emissions in Colorado which without intervention will grow to over 30 million metric tons (MMT) of GHG emissions per year. This study seeks to develop a specific characterization of the Colorado fuel and transportation system using a customized life cycle assessment (LCA) model. The model (CO-GT) was developed as an analytical tool to define Colorado's 2020 baseline life cycle GHG emissions for the transportation sector, and to examine Colorado-specific pathways for GHG reductions through fuel types and volumes changes that might be associated with a state clean fuel standard (CFS). By developing a life cycle assessment of transportation fuels that is specific to the state of Colorado's geography, fleet makeup, policies, energy sector and more, these tools can evaluate various proposals for the transition towards a more sustainable state transportation system. The results of this study include a quantification of the Colorado-specific roles of clean fuels, electricity, extant policies, and fleet transition in projections of the state's 2030 transportation sector GHG emissions. Relative to a 2020 baseline, electrification of the vehicle fleet is found to reduce state-wide lifecycle GHG emissions by 7.7 MMT CO2e by 2030, and a model CFS policy able to achieve similar reductions in the carbon intensity of clean fuels as was achieved by California in the first 10 years of its CFS policies is found to only reduce state-wide lifecycle GHG emissions by 0.2 MMT CO2e by 2030. These results illustrate the insensitivity of Colorado's transportation fleet GHG emissions reductions to the presence of CFS policies, as proposed to date.
DOI: 10.25675/10217/187212
title: Data associated with Significant floodplain soil organic carbon along a large high latitude river and its tributaries

description: The dataset describes floodplain soil samples taken from the Yukon Flats region in interior Alaska, which were analyzed for organic carbon stocks. These data were collected in the Yukon Flats Region during Summer 2014 and Summer 2015, and lab work was completed from 2014-2017.
description: High-latitude permafrost regions store large amounts of organic carbon (OC) in soils, and these stocks are vulnerable to climate warming. Estimates of subsurface carbon stocks do not take into account floodplains as unique landscape units that mediate and influence the delivery of materials into river networks. We present estimated floodplain soil OC stocks within the active layer (seasonally thawed layer) and within the top 1 m of the subsurface from a large field dataset in the Yukon Flats region of interior Alaska. We compare our estimated stocks to a previously published dataset, and find that the OC stock estimate using our field data is approximately 80% higher than the published dataset. We constrain the residence time of floodplain sediment and OC using radiocarbon dating. Our results indicate the importance of floodplains as areas of underestimated carbon storage, particularly because climate change may modify geomorphic processes in permafrost regions.
DOI: 10.25675/10217/87631
title: Data for the manuscript: Using high-resolution future climate scenarios to forecast Bromus tectorum invasion in Rocky Mountain National Park

description: Rocky Mountain National Park covers about 1,076 km2 in northern Colorado, USA, at approximate latitudes 40°10'N to 40°32'N. Climate and elevation data included in this package are at 90m spatial resolution for the Park.
description: Cheatgrass data from 1996, 1999, 2007, and 2008; climate normals from 1981-2010; future potential climate data from global circulation models, year 2050.
description: This data package was produced by researchers working with the Natural Resource and Ecology Laboratory, the Bioagricultural Sciences and Pest Management Department, and the Forest, Rangeland & Watershed Stewardship Department at Colorado State University, and Rocky Mountain National Park, Colorado in evaluating the distribution and potential spread of the invasive species Bromus tectorum (cheatgrass) for the Park. Our objectives were to: (1) evaluate the current bioclimatic niche including climatic variables that have a significant influence on B. tectorum occurrence in the Park using MaxEnt and high-resolution climatic data generated from ClimateWNA, (2) model the potential bioclimatic niche of B. tectorum in the Park for the year 2050 based on climate change, and (3) create a high-resolution map of B. tectorum habitat in the Park both now and in the future for use by Park managers.
DOI: 10.25675/10217/178758
title: 2010 C2H6 global emission inventory

description: Each of the twelve netcdf files contain monthly ethane (C2H6) global emissions corresponding to the year 2010 as described in Tzompa-Sosa et al. (JGR, in press). The emission categories included in these files are total, anthropogenic, biofuel, and biomass burning sources.
description: Recent measurements over the Northern Hemisphere indicate that the long-term decline in the atmospheric burden of ethane (C2H6) has ended, and the abundance increased dramatically between 2010 and 2014. The rise in the abundance of C2H6 has been attributed to oil and natural gas extraction in North America. Existing global C2H6 emission inventories are based on outdated activity maps that do not account for current oil and natural gas exploitation regions. We present an updated global C2H6 emission inventory based on 2010 satellite-derived CH4 fluxes with adjusted C2H6 emissions over the U.S. from the National Emission Inventory (NEI 2011). We contrast our global 2010 C2H6 emission inventory with one developed for 2001. The C2H6 difference between global anthropogenic emissions is subtle (7.9 versus 7.2 Tg yr-1), but the spatial distribution of the emissions is distinct. In the 2010 C2H6 inventory, fossil fuel sources in the Northern Hemisphere represent half of global C2H6 emissions and 95% of global fossil fuel emissions. Over the U.S., un-adjusted NEI 2011 C2H6 emissions produce mixing ratios that are 14-50 % of those observed by aircraft observations (2008-2014). When the NEI 2011 C2H6 emission totals are scaled by a factor of 1.4, the model largely reproduces a regional suite of observations, with the exception of the central U.S., where it continues to under-predict observed mixing ratios in the lower troposphere. We estimate monthly mean contributions of fossil fuel C2H6 emissions to ozone and peroxyacetyl nitrate surface mixing ratios over North America of ~1% and ~8%, respectively.
DOI: 10.25675/10217/194492
title: Expert survey data on key challenges, drivers, and ecosystem services across mountains worldwide

description: Data are survey responses collected between 2014-2016 from experts working in 57 different mountain systems around the world, assessing threats to mountain social-ecological systems (MtSES) and the cross-scale ecosystem services MtSES provide.
description: Mountain social-ecological systems (MtSES) are vital to humanity, providing ecosystem services to over half the planet's human population. Despite their importance, there has been no global assessment of threats to MtSES, even as they face unprecedented challenges to their sustainability. With survey data from 57 MtSES sites worldwide, we test a conceptual model of the types and scales of stressors and ecosystem services in MtSES and explore their distinct configurations according to their primary economic orientation and land use. We find that MtSES worldwide are experiencing both gradual and abrupt climatic, economic, and governance changes, with policies made by outsiders as the most ubiquitous challenge. Mountains that support primarily subsistence-oriented livelihoods, especially agro-pastoral systems, deliver abundant services but are also most at risk. Moreover, transitions from subsistence- to market-oriented economies are often accompanied by increased physical connectedness, reduced diversity of cross-scale ecosystem services, lowered importance of local knowledge, and shifting vulnerabilities to threats. Addressing the complex challenges facing MtSES and catalyzing transformations to MtSES sustainability will require cross-scale partnerships among researchers, stakeholders and decision-makers to jointly identify desired futures and adaptation pathways, assess tradeoffs in prioritizing ecosystem services, and share best practices for sustainability. These transdisciplinary approaches will allow local stakeholders, researchers and practitioners to jointly address MtSES knowledge gaps while simultaneously focusing on critical issues of poverty and food security.
DOI: 10.25675/10217/81141
title: SGS-LTER standard production data: 1983-2008 annual aboveground net primary production on the Central Plains Experimental Range, Nunn, Colorado, USA 1983-2008, ARS study number 6

description: University of Wyoming. Department of Botany.
description: The Short Grass Steppe site encompasses a large portion of the Colorado Piedmont Section of the western Great Plains. The extent is defined as the boundaries of the Central Plains Experimental Range (CPER). The CPER has a single ownership and landuse (livestock grazing). The PNG is characterized by a mosaic of ownership and land use. Ownership includes federal, state or private and land use consists of livestock grazing or row-crops. There are NGO conservation groups that exert influence over the area, particularly on federal lands.
description: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Repository (http://hdl.handle.net/10217/100254). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. The objective of the long-term ANPP study is to monitor long-term net above ground primary production of the shortgrass steppe community by species. There are 6 sites: ridgetop (ridge), midslope (mid), swale, ESA (replicate 1 not 2), Section 25 (SEC 25), and owl-creek (OC). Each site is located in a different landscape position or soil type on the shortgrass steppe and may be grazed or not. Ridgetop, midslope and swale are grazed and are sampled along a catena. Section 25 is grazed and is located in an upload grassland. ESA is an ungrazed upland grassland and is the control from the Ecosystem Stress Area experiment. Owl Creek is ungrazed and is located in the lowland along the owl creek drainage. There are 3 transects with 5 plots in each transect. Plots in the grazed locations are protected by cages. Because this is a monitoring effort, true replicates across the landscape are not available and it is recommended that the transect be used in calculating mean production at each sampling location.
DOI: 10.25675/10217/186141
title: Sources of PM2.5 carbonaceous aerosol in Riyadh, Saudi Arabia

description: To study the sources of carbonaceous aerosol affecting air quality in Riyadh, Saudi Arabia, we conducted sampling of PM2.5 from April to September, 2012 at various sites in the city, and used a thermo-optical semi-continuous method to quantify the organic carbon (OC) and elemental carbon (EC) concentrations. Our datasets include the raw data and corrected OCEC concentrations, PM10 metal concentrations, and gas-phase O3 and NOx concentrations.
description: Data set used in the study.
description: Knowledge of the sources of carbonaceous aerosol affecting air quality in Riyadh, Saudi Arabia is limited, but needed for the development of pollution control strategies. We conducted sampling of PM2.5 from April to September, 2012 at various sites in the city, and used a thermo-optical semi-continuous method to quantify the organic carbon (OC) and elemental carbon (EC) concentrations. The average OC and EC concentrations were 4.7 ± 4.4 and 2.1 ± 2.5 µg m-3, respectively, during this period. Both OC and EC concentrations had strong diurnal variations, with peaks at 6-8 am and 20-22 pm, attributed to the combined effect of increased vehicle emissions during rush hour and the shallow boundary layer in the early morning and at night. This finding suggested a significant influence of local vehicular emissions on OC and EC. The OC/EC ratio in primary emissions was estimated to be 1.01, close to documented values for diesel emissions. Estimated primary (POC) and secondary (SOC) organic carbon concentrations were comparable, with average concentrations of 2.0 ± 2.4 and 2.8 ± 3.4 µg m-3, respectively. We also collected 24 hour samples of PM10 onto quartz microfiber filters and analyzed these for an array of metals by ICP-OES. Total OC was correlated with Ca (R2 of 0.63), suggesting that OC precursors and Ca may have similar sources, and the possibility that they underwent similar atmospheric processing. In addition to a ubiquitous dust source, Ca is emitted during desalting processes in the numerous refineries in the region and from cement kilns, suggesting these sources may also contribute to observed OC concentrations in Riyadh. Concentration weighted trajectory (CWT) analysis showed that high OC and EC concentrations were associated with air masses arriving from the Persian Gulf and the region around Baghdad, locations with high densities of oil fields and refineries as well as a large Saudi Arabian cement plant. We further applied positive matrix factorization to the aligned data set of EC, OC and metal concentrations (Al, Ca, Cu, Fe, K, Mg, Mn, Na, Ni, Pb and V). Three factors were derived, and were proposed to be associated with oil combustion, industrial emissions (Pb-based), and a combined source from oil fields, cement production, and local vehicular emissions. The dominant OC and EC source was the combined source, contributing 3.9 µg m-3 (80%) to observed OC and 1.9 µg m-3 (92%) to observed EC.
DOI: 10.25675/10217/233603
title: Dataset of filtration efficiency associated with "Quantifying the health benefits of face masks and respirators to mitigate exposure to severe air pollution"

description: This dataset includes the average (“mask_efficiency_mean”) and standard deviation (“mask_efficiency_sd”) of measured filtration efficiency for natural-fiber masks, synthetic-fiber mask, surgical mask, and N95 respirator as a function of particle diameter. This dataset is associated with the publication "Quantifying the health benefits of face masks and respirators to mitigate exposure to severe air pollution".
description: Familiarity with the use of face coverings to reduce the risk of respiratory disease has increased during the coronavirus pandemic; however, recommendations for their use outside of the pandemic remains limited. Here, we develop a modeling framework to quantify the potential health benefits of wearing a face covering or respirator to mitigate exposure to severe air pollution. This framework accounts for the wide range of available face coverings and respirators, fit factors and efficacy, air pollution characteristics, and exposure-response data. Our modeling shows that N95 respirators offer robust protection against different sources of air pollution, reducing exposure by more than a factor of 14 when worn with a leak rate of 5%. Synthetic-fiber masks offer less protection with a strong dependence on aerosol size distribution (protection factors ranging from 4.4 to 2.2.), while natural-fiber and surgical masks offer reductions in exposure of 1.9 and 1.7, respectively. To assess the ability of face coverings to provide population-level health benefits to wildfire smoke, we perform a case study for the 2012 Washington state fire season. Our models suggest that although natural-fiber masks offer minor reductions in respiratory hospitalizations attributable to smoke (2-11%) due to limited filtration efficiency, N95 respirators and to a lesser extent surgical and synthetic-fiber masks may lead to notable reductions in smoke-attributable hospitalizations (22-39%, 9-24%, and 7-18%, respectively). The filtration efficiency, bypass rate, compliance rate (fraction of time and population wearing the device) are the key factors governing exposure reduction potential and health benefits during severe air pollution events.