Find research datasets worth reusing

opencc-by-4.0Aug 2022View details →

Fine-scale map reveals highly variable recombination rates associated with genomic features in the Eurasian blackcap

This project estimates historical recombination rates of the Eurasian blackcap (Sylvia atricapilla) and the garden warbler (Sylvia borin) using a linkage disequilibrium-based approach. The population-scaled recombination rates were inferred using 'pyrho' considering the population's demographic information and mutation rates. The mutation rate was taken from a closely related species (flycatcher, Ficedula albicollis). Here we report the recombination rate per site per generation (r, output of pyrho) for all the chromosomes along the genome for both species.  Blackcap dataset file: WholeGenome_chromosomes_blackap_n38_Pen20_W50.gz Garden warbler dataset file: WholeGenome_chromosomes_SylBor_n10_Pen20W50.gz   Additionally, we annotated the blackcap genome to evaluate the association between recombination rates and specific annotation features (e.g., genes, transcription start sites, promoters, 5'UTR, and 3'UTR regions). The annotation of the genome was based on RNA-seq and Iso-Seq data. It can be found with the name bSylAtr1.1.gff.

opencc-by-4.0Dec 2023View details →

Replication package: Dataset and stata-do-file for analysis in "Intragroup communication in social dilemmas: An artefactual public good field experiment in small-scale communities"

This dataset was used for the analysis in "Intragroup communication in social dilemmas: An artefactual public good field experiment in small-scale communities". The data was collected in Namibia in 2017 as part of the SASSCAL research project by Nils Christian Hoenow and Adrian Pourviseh as members of the Chair for Development and Cooperative Economics at the University of Marburg. Funded by the Southern African Science Service Center for Climate Change and Adaptive Land-UseManagement (SASSCAL) through the German Federal Ministry for Education and Research (Grant No. 01LG1201B).   Article Title: Intragroup communication in social dilemmas: An artefactual public good field experiment in small-scale communities  Authors: Nils Christian Hoenow* and Adrian Pourviseh**   *RWI – Leibniz Institute for Economic Research, Essen, Germany and & School of Business and Economics, University of Marburg, Marburg, Germany **School of Business and Economics, University of Marburg, Marburg, Germany Abstract:  Communication is well-known to increase cooperation rates in social dilemma situations, but the exact mechanisms behind this remain largely unclear. This study examines the impact of communication on public good provisioning in an artefactual field experiment conducted with 216 villagers from small, rural communities in northern Namibia. In line with previous experimental findings, we observe a strong increase in cooperation when face-to-face communication is allowed before decision-making. We additionally introduce a condition in which participants cannot discuss the dilemma but talk to their group members about an unrelated topic prior to learning about the public good game. It turns out that this condition already leads to higher cooperation rates, albeit not as high as in the condition in which discussions about the social dilemma are possible. The setting in small communities also allows investigating the effects of pre-existing social relationships between group members and their interaction with communication.We find that both types of communication are primarily effective among socially more distant group members, which suggests that communication and social ties work as substitutes in increasing cooperation. Further analyses rule out better comprehension of the game and increased mutual expectations of one’s group members’ contributions as drivers for the communication effect. Finally, we discuss the role of personal and injunctive norms to keep commitments made during discussions.

opencc-zeroDec 2023View details →

Patterns in bird and pollinator occupancy and richness in a mosaic of urban office parks across scales and seasons

Urbanization is a leading cause of global biodiversity loss, yet cities can provide resources required by many species throughout the year. In recognition of this, cities around the world are adopting strategies to increase biodiversity. These efforts would benefit from a robust understanding of how natural and enhanced features in urbanized areas influence various taxa. We explored seasonal and spatial patterns in occupancy and taxonomic richness of birds and pollinators among office parks in Santa Clara County, California, USA, where natural features and commercial landscaping have generated variation in conditions across scales. We surveyed birds and insect pollinators, estimated multi-species occupancy and species richness, and found that spatial scale, season, and urban sensitivity were all important for understanding how communities occupied sites. Features at the landscape- and local-scale (i.e., distance to streams or baylands and tree canopy, shrub, or impervious cover, respectively) were the strongest predictors of avian occupancy in all seasons. The pollinator richness index was influenced by local tree canopy and impervious cover in spring, and distance to baylands in early and late summer. We predicted relative contributions of different spatial scales to annual bird species richness by assigning values to simulated sites representing "good" and "poor" quality, based on influential covariates returned by models. Shifting from poor to good quality conditions locally increased annual avian richness by up to 6.8 species with no predicted effect of the quality of the neighborhood. Conversely, sites of poor local- and neighborhood-scale quality in good quality landscapes were predicted to harbor 11.5 more species than sites of good local- and neighborhood-scale quality in poor quality landscapes. Finally, more urban sensitive bird species were gained at good quality sites relative to urban tolerant species, suggesting that urban natural features at the local- and landscape-scales disproportionately benefited them.

opencc-zeroDec 2023View details →

Data from: harnessing the power of regional baselines for broad-scale genetic stock identification: a multistage, integrated, and cost-effective approach

In mixed-stock fishery analyses, genetic stock identification (GSI) estimates the contribution of each population to a mixture and is typically conducted at a regional scale using genetic baselines specific to the stocks expected in that region. Often these regional baselines cannot be combined to produce broader geographical baselines due to non-overlapping populations and genetic markers. In cases where the mixture contains stocks spanning across a wide area, a broad-scale baseline is created, but often at the cost of resolution. Here, we introduce a new GSI method to harness the resolution capabilities of baselines developed for regional applications in the analysis of mixtures containing individuals from a broad geographic range. This method employs a multistage framework that allows disparate baselines to be used in a single integrated process that produces estimates along with the propagated errors from each stage. All individuals in the mixture sample are required to be genotyped for all genetic markers in the baselines used by this model, but the baselines do not require overlap in genetic markers or populations representing the broad-scale or regional baselines. We demonstrate our integrated multistage GSI model using a synthesized data set made up of Chinook salmon, Oncorhynchus tshawytscha, from the North Bering Sea of Alaska. The data set is designed to be run using R package, Ms.GSI, and it does not represent the composition of the real fishery. The results show an improved accuracy for estimates using an integrated multistage framework, compared to the conventional framework of using separate hierarchical steps. The integrated multistage framework allows GSI of a wide geographic area without first developing a large scale, high-resolution genetic baseline or dividing a mixture sample into smaller regions beforehand. This approach is more cost-effective than updating range-wide baselines with all regionally important markers.

opencc-by-4.0Dec 2023View details →

Autonomous millimeter scale high throughput battery research system

In this study, we present data from high-throughput cyclic voltammetry (CV) test, derived by our digital workflow, Auto-MISCHBARES, complemented by XPS analysis. This research is part of the pre-print publication named "Autonomous millimeter scale high throughput battery research system", showcasing Cathode Electrolyte Interphase (CEI) investigation. The electrolyte used for this experiment is 1M of LiPF6 solution in an Ethylene Carbonate (EC): Ethyl Methyl Carbonate (EMC) mixture with a 3:7 weight ratio, along with LFP as our electrode material. The CV tests were conducted through a high-throughput sequential process for two cycles, each with varying stop potentials. After the experimentation phase, XPS analysis was applied to characterize the synthesized CEI.

Scaling regimes and fluctuations of observables in computer glasses approaching the unjamming transition

This dataset can be used to reproduce the figures in the corresponding manuscript, in preparation for publication in the Journal of Chemical Physics. As described in the manuscript, the (mostly statistical) quantities presented here were computed from ensembles of simulated disordered solids (harmonic sphere packings, diluted spring networks, and packing derived networks). The individual simulations involve the minimization of the system's energy which is computed from positional degrees of freedom (of particles in a packing or nodes in a network). Macroscopic quantities (such as shear modulus or contact number/excess connectivity) are then computed for each sample. The displacement response feilds are computed by solving a linear matrix equation involving the Hessian of 2D packings of harmonic spheres. See the manuscript for more details.

opencc-by-4.0Oct 2023View details →

Large-scale annotated dataset for cochlear hair cell detection and classification

Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5 - 15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitroototoxic drug application. The dataset includes over 107,000 hair cells which have been manually identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease. Associated code is provided here: https://github.com/indzhykulianlab/hcat-data

Bridging length scales in organic mixed ionic-electronic conductors through internal strain and mesoscale dynamics

Understanding structural and dynamic properties of inherently disordered systems at the mesoscale is crucial. This is particularly important in organic mixed ionic-electronic conductors (OMIECs), which undergo significant and complex structural changes when operated in electrolyte. In this study, we investigate the mesoscale strain, reversibility, and dynamics of a model OMIEC material under external electrochemical potential using operando X-ray photon correlation spectroscopy. Our results reveal mesoscale strain and structural hysteresis that depend on the sample's cycling history, establishing a comprehensive kinetic sequence bridging the macroscopic and microscopic behaviors of OMIECs. Furthermore, we uncover equilibrium and non-equilibrium dynamics of charge carriers and material doping states, highlighting the unexpected coupling between charge carrier dynamics and mesoscale order. These findings advance our understanding of the structure-dynamics-function relationships in OMIECs, opening pathways for designing and engineering materials with improved performance and functionality in non-equilibrium states during device operation.

Rapid in situ diversification rates in Rhamnaceae explain the parallel evolution of high diversity in temperate biomes from global to local scales

The macroevolutionary processes that have shaped biodiversity across the temperate realm remain poorly understood and may have resulted from evolutionary dynamics related to diversification rates, dispersal rates, and colonization times, closely coupled with Cenozoic climate change. We integrated phylogenomic, environmental ordination, and macroevolutionary analyses for the cosmopolitan angiosperm family Rhamnaceae to disentangle the evolutionary processes that have contributed to high species diversity within and across temperate biomes. Our results show independent colonization of environmentally similar but geographically separated temperate regions mainly during the Oligocene, consistent with the global expansion of temperate biomes. High global, regional, and local temperate diversity was the result of high in situ diversification rates, rather than high immigration rates or accumulation time, except for Southern China, which was colonized much earlier than other regions. The relatively common lineage dispersals out of temperate hotspots highlights strong source-sink dynamics across the cosmopolitan distribution of Rhamnaceae. The proliferation of temperate environments since the Oligocene may have provided the ecological opportunity for rapid in situ diversification of Rhamnaceae across the temperate realm. Our study illustrates the importance of high in situ diversification rates for the establishment of modern temperate biomes and biodiversity hotspots across spatial scales.

opencc-by-4.0Jan 2024View details →

CONUS-wide HUC4 Watershed Scale Hydropower Projections derived from 9505 Third Assessment

This dataset provides historical and climate projection monthly hydropower generation timeseries for HUC4 watersheds within the contiguous U.S. (CONUS). These data were developed as an extension to the Department of Energy Water Power Technologies Office's SECURE Water Act Section 9505 Third Assessment (9505) and include both federal and non-federal hydropower facilities. Additional modeling detail can be found in <a href="https://iopscience.iop.org/article/10.1088/1748-9326/ad6ceb">Broman et al., 2024</a> and in the article's <a href="https://github.com/9505-PNNL/broman-etal_2024_erl">metarepository</a>. Note that in some instances multiple HUC4 watersheds have been merged together into a HUC4 group, and that HUC4 watersheds without hydropower facilities are excluded. A hydropower facility's physical location, rather than the source of water, was used in assigning facilities to HUC4 watersheds. The dataset is provided in three separate formats to facilitate ease of use: 1) Machine-readable csv in 'tidy' data format: <table> <tbody> <tr> <td>Short Name</td> <td>Unit</td> <td>Description</td> </tr> <tr> <td>class</td> <td>N/A</td> <td>simulation type; control: historical, cc: climate scenario</td> </tr> <tr> <td>forcing</td> <td>N/A</td> <td>meteorological forcing used to drive hydrology model</td> </tr> <tr> <td>model</td> <td>N/A</td> <td>hydrology model</td> </tr> <tr> <td>hp</td> <td>N/A</td> <td>hydropower model</td> </tr> <tr> <td>gcm*</td> <td>N/A</td> <td>global climate model name</td> </tr> <tr> <td>ds*</td> <td>N/A</td> <td>downscaling method; DBCCA (statistical), RegCM (dynamical)</td> </tr> <tr> <td>HUC4_group</td> <td>N/A</td> <td>HUC4 group; HUC4 numeric ID or multiple IDs</td> </tr> <tr> <td>year</td> <td>N/A</td> <td>year</td> </tr> <tr> <td>month</td> <td>N/A</td> <td>month</td> </tr> <tr> <td>modeled_generation_MWh</td> <td>MWh per month</td> <td>simulated generation</td> </tr> </tbody> </table> * only present in the climate projection (cc) files 2) xlsx with HUC4 group data by tab 3) csv by HUC4 group: for historical data: year, month, and HUC4_group columns are the same as above. Data column headers are class_forcing_model_hp and with the units MWh per month. for climate projection (cc) data: year, month, and HUC4_group columns are the same as above. Data column headers are class_forcing_model_hp_gcm_ds and with the units MWh per month.

Data for: Characterization of large-scale preferential flow across continental United States

Understanding preferential flow (PF) at large scales is critical for improving land management and groundwater (GW) quality. However, limited knowledge of this process, due to soil surface heterogeneity and observational constraints, hampers progress. In this study, we propose estimating effective PF at remote sensing footprint scale (4 – 9 km) by examining its impact on soil moisture (SM) distribution and shallow GW (SGW) table fluctuations (depth 5 m). Effective PF encompasses macropore, funnel, and finger flow pathways influencing SGW table fluctuations. We compiled daily SGW observations (2019-2021) from 19 continental US (CONUS) sites through USGS. Using inverse modeling in HYDRUS-1D, SGW data, and CHIRPS precipitation data, we inversely estimated soil hydraulic parameters of the dual porosity model (DPM) simulating vertical flow from soil surface to subsurface. Effective PF presence was inferred using three criteria: (1) daily precipitation >= the site-specific average across multiple (calibration) years, (2) daily observed SGW table increase, and (3) daily difference between observed and DPM simulated SGW tables 50% of the site-specific RMSE. Leveraging optimized DPM parameters and associated soil texture, classified PF events, and Soil Moisture Active Passive (SMAP L3E) satellite-based SM, a Random Forest algorithm with 10-fold cross validation predicted large-scale effective PF events. Results indicate seasonal dependence, with spring having the highest occurrence of PF events. The Random Forest model achieved 98% accuracy in predicting large-scale PF events, with SMAP SM and saturated hydraulic conductivity (Ks) among the 4 most impactful variables. Our approach provides a soil hydraulic property, site characteristic, soil texture and remote sensing based generalized tool to analyze large-scale effective PF.

Data from: Exponential history integration with diverse temporal scales in retrosplenial cortex supports hyperbolic behavior

Animals rely on their experience to guide their next choice. In foraging-type tasks guided by history-dependent value, these experiences are typically integrated such that the weights of past events initially decay quickly over time but show a longer tail than expected by exponential decay. Rather, such integration is better described by a hyperbolic function. Hyperbolic integration affords sensitivity to both recent environmental dynamics and long-term trends, however the mechanism by which the brain implements this hyperbolic integration is unknown. We trained mice on a history-dependent, value-based decision task and found that the mice indeed showed hyperbolic decay on their weighting of past experience. However, the activity of history-encoding cortical neurons showed weighting with exponential decay. In resolving this apparent mismatch, we observed that cortical neurons encode history information heterogeneously across a wide variety of exponential time-constants, with the retrosplenial cortex (RSC) overrepresenting longer time-constants compared to other areas. A model that combines these diverse timescales of exponential history integration can recreate the heavy-tailed, hyperbolic history integration observed in behavior. In particular, time-constants of RSC neurons best matched the behavior, and optogenetic inactivation of RSC uniquely reduced the use of history information. These results indicate that behavior-relevant history information is maintained in neurons across multiple timescales in parallel, and suggest that the neural population in RSC is a critical reservoir of this information guiding decision-making.

Data for: Land use change and coastal water darkening drive synchronous dynamics in phytoplankton and fish phenology on centennial time scales

At high latitudes, the suitable window for timing reproductive events is particularly narrow, promoting tight synchrony between trophic levels. Climate change may disrupt this synchrony due to diverging responses to temperature between e.g. the early life stages of higher trophic levels and their food resources. Evidence for this is equivocal, and the role of compensatory mechanisms are poorly understood. Here, we show how a combination of ocean warming and coastal water darkening drive long-term changes in phytoplankton spring bloom timing in Lofoten Norway, and how spawning time of Northeast Arctic cod responds in synchrony. Spring bloom timing was derived from hydrographical observations dating back to 1936, while cod spawning time was estimated from weekly fisheries catch and roe landing data since 1877. Our results suggest that land use change causing coastal water darkening has gradually delayed the spring bloom up to 1990 after which ocean warming has caused it to advance. The cod appear to track phytoplankton dynamics by timing gonadal development and spawning to maximize overlap between offspring hatch date and predicted resource availability. This finding emphasises the importance of land-ocean coupling for coastal ecosystem functioning, and the potential for fish to adapt through phenotypic plasticity.

opencc-zeroFeb 2024View details →

Data from: Mean landscape-scale incidence of species in discrete habitats is patch size dependent

Contains data and code for the manuscript 'Mean landscape-scale incidence of species in discrete habitats is patch size dependent'. Raw data consist of 202 published datasets collated from primary and secondary (e.g., government technical reports) sources. These sources summarise metacommunity structure for different taxonomic groups (birds, invertebrates, non-avian vertebrates or plants) in different types of discrete metacommunities including 'true' islands (i.e., inland, continental or oceanic archipelagos), habitat islands (e.g., ponds, wetlands, sky islands) and fragments (e.g., forest/woodland or grass/shrubland habitat remnants). The aim of the study was to test whether the size of a habitat patch influences the mean incidences of species within it, relative to the incidence of all species across the landscape. In other words, whether high-incidence (widespread) or low-incidence (narrow-range) species are found more often than expected in smaller or larger patches. To achieve this, a new standardized effect size metric was developed that quantifies the mean observed incidence of all species present in every patch (the geometric mean of the number of patches in which all species were observed) and compares this with an expectation based on re-sampling the incidences of all species in all patches. Meta-regression of the 202 datasets was used to test the relationship between this metric, the 'mean species landscape-scale incidences per patch' (MSLIP), and the size of habitat patches, and for differences in response among metacommunity types and taxonomic groups.

opencc-zeroFeb 2024View details →

Energy input, habitat heterogeneity, and host specificity on avian haemosporidian diversity at continental scales

The correct identification of biotic and abiotic drivers affecting parasite diversity and assemblage composition at different spatial scales is crucial for understanding how pathogen distribution responds to anthropogenic disturbance and climate change. Here, we used a database of avian haemosporidian parasites to identify such drivers and their effect on the taxonomic and phylogenetic diversity of genera Plasmodium, Haemoproteus, and Leucocytozoon from three zoogeographic regions. We explored how parasite diversity is related to energy input (i.e., temperature, precipitation, and potential evapotranspiration [PET]), to habitat heterogeneity (i.e., climatic seasonality, vegetation density, ecosystem heterogeneity, human disturbance, and host richness), and to a novel assemblage-level metric related to parasite niche overlap (degree of generalism). We found that the relative importance of the predictors differed between the three studied parasite genera and across diversity metrics. Among the most consistent predictors, host richness was positively related to the taxonomic diversity of the three genera. Energy input and human footprint explained the phylogenetic diversity of Haemoproteus. Finally, the degree of generalism explained the diversity of Plasmodium and Leucocytozoon. Our results suggest that different dimensions of haemosporidian diversity are shaped by energy input, host heterogeneity, and assembly processes related to parasite resource use within local parasite assemblages.

opencc-by-4.0Feb 2024View details →

TURDATA: a database of low-cost air quality and remote sensing measurements for the validation of micro-scale models in the real Prague urban environments

README TURDATA is a supplementary data set for the TURBAN project Prague observation campaign described in the manuscript Bauerová et al. 2024 (submitted for publication). The measurement campaign was focused on air pollution and meteorological measurement, including vertical profiles in selected part of Prague city centre called here as Legerova domain. Within this area, one professional meteorological station (MS) Prague Karlov and one reference traffic air quality monitoring (AQM) station Prague 2-Legerova (classified as traffic hotspot) are located. To gain high spatial and temporal resolution data, the supplementary measurement network was established, which consisted of: -        20 combined low-cost sensor (LCS) stations for monitoring of PM10, PM2.5, NO2 and O3 concentrations (using Plantower PMS7003 particle counters and Envea Cairsense electrochemical sensors) placed in different sites and different height levels AGL (higher = H, lower = L), -        1 mobile telescopic meteorological mast for measuring temperature, relative humidity, wind velocity and direction and air pressure (using 2D ultrasonic anemometer Gill WindSonic 60 and weather station Gill MetConnect THP), -        1 MTP-5-He microwave radiometer (MWR; Attex) for temperature vertical profile, -        1 StreamLine XR Doppler LIDAR (HALO Photonics) for wind vertical profile.   The main Legerova campaign lasted from 30 May 2022 to 28 March 2023 with some exceptions (see TURDATA_metadata.xlsx with all details). Because LCSs are known for their highly variable measurement quality, before their deployment the Legerova campaign, a sufficiently long-term initial field comparative measurement of all LCSs at RM Prague 4-Libu&scaron; was carried out (lasting from 16/12/2021 to 30/5/2022). The results showed that most of the LCSs were in raw measurement differently zero-shifted against each other and against gaseous reference or aerosol optical equivalent monitors (RMs or EMs).  Therefore, the Multivariate Adaptive Regression Splines (MARS) method was applied to calculate corrected LCS concentrations based on initial field comparative measurement complemented by meteorological data from MS Prague Libu&scaron;. To check the quality of raw and MARS corrected LCS concentrations at the end of the measurement campaign, the final comparative field measurement of all LCSs at Prague 4-Libu&scaron; RM station was performed. Therefore, in case of LCSs measurement (both raw and corrected) the important columns of location (measurement placement: RM_Prague_4-Libus and Legerova_domain) and measurement_program (Initial_comparative_measurement, Legerova_campaign and Final_comparative_measurement) were added. In case of PM10 and PM2.5 measurement the maximum raw and MARS-corrected concentrations were influenced by temporary pollution episode on 26 July 2022 around 4 a.m. and 9 p.m. (both UTC) caused by aerosol pollution transported from large forest fire in Hřensko (the northern part of the Czech Republic).    TURDATA includes the following files: 1.     TURDATA_metadata_and_photos.zip containing: -        "TURDATA_metadata.xlsx" with the important list of metadata about devices placement, locations parameters and measurement periods -        Folder "Photos_from_Legerova_campaign" with photos from Legerova measurement campaign 2.     AQ_LCSs_raw_measurement_TURDATA.zip containing: -        "NO2_RAW_LCSs_TURDATA.xlsx" with complete data set of NO2 raw measured concentrations by all LCSs -        "O3_RAW_LCSs_TURDATA.xlsx" with complete data set of O3 raw measured concentrations by all LCSs -        "PM10_RAW_LCSs_TURDATA.xlsx" with complete data set of PM10 raw measured concentrations by all LCSs -        "PM2_5_RAW_LCSs_TURDATA.xlsx" with complete data set of PM2.5 raw measured concentrations by all LCSs -        "AQ_LCSs_raw_measurement_TURDATA_readme.txt" with all necessary information for correct data use 3.     AQ_data_RM_stations_Prague_TURDATA.zip containing: -        "AQ_data_Prague_RM_stations_TURDATA_12-2021_06-2023.xlsx" with air quality data measured by reference AQM stations in Prague -        "AQ_data_RM_stations_Prague_TURDATA_readme.txt" with all necessary information for correct data use 4.     Meteo_data_Prague_MS_TURDATA.zip containing: -        "Meteo_data_Prague_MS_TURDATA_12-2021_06-2023.xlsx" with meteorological data measured by professional meteorological stations in Prague -        "Meteo_data_Prague_MS_TURDATA_readme.txt" with all necessary information for correct data use 5.     AQ_LCSs_MARS-corrected_measurement_TURDATA.zip containing: -        "NO2_COR_LCSs_TURDATA.xlsx" with complete data set of NO2 MARS-corrected concentrations for all LCSs -        "O3_COR_LCSs_TURDATA.xlsx" with complete data set of O3 MARS-corrected concentrations for all LCSs -        "PM10_COR_LCSs_TURDATA.xlsx" with complete data set of PM10 MARS-corrected concentrations for all LCSs -        "PM2_5_COR_LCSs_TURDATA.xlsx" with complete data set of PM2.5 MARS-corrected concentrations for all LCSs -        "AQ_LCSs_MARS-corrected_measurement_TURDATA_readme.txt" with all necessary information for correct data use and brief description of MARS correction method 6.     Meteo-mast_PVK_measurement_TURDATA.zip containing: -        "Meteo-mast_PVK_TURDATA_06-2022_06_2023.xlsx“ with non-referential meteorological data measured by mobile meteo-mast -        "Meteo-mast_data_PVK_TURDATA_readme.txt" with all necessary information for correct data use 7.     MWR_temperature_profile_TURDATA.zip containing: -        "MWR_5min_temperature_TURDATA_02-2022_03-2023.xlsx" with raw temperature vertical profile measurement from microwave radiometer -        "MWR_1hour_temperature_TURDATA.xlsx" with 1-hour averaged temperature vertical profile from microwave radiometer -        "MWR_1hour_TMP_gradient_TURDATA.xlsx" with 1hour temperature gradient calculated from raw temperature profiles measured by microwave radiometer -        "MWR_temperature_profile_TURDATA_readme.txt" with all necessary information for correct data use 8.     LIDAR_wind_profile_TURDATA.zip contains: -        Individual folders "yyyymm“ -> "yyyymmdd" -        Each daily folder "yyyymmdd" contains files: a)     "Processed_Wind_Profile_188_yyyymmdd_hhmmss.hpl" with processed WV and WS data b)     "Wind_Profile_188_yyyymmdd_hhmmss.hpl" with non-processed Doppler wind profile data -        "LIDAR_wind_profile_TURADATA_readme.txt" with all necessary information for correct data use

opencc-by-4.0Jul 2023View details →

A Parsec-Scale Galactic 3D Dust Map out to 1.25 kpc from the Sun -- Dataset for the 1.25 kpc 3D Dust Map and the 2 kpc 3D Dust Map

Accompanying data products for Edenhofer et al. (2023).

opencc-by-4.0Jul 2023View details →

Candidate cluster-scale gravitationally lensed quasars from CluMPR and DESI Legacy Survey

Candidate cluster-scale strongly-lensed quasars from DESI Legacy Survey (DESI QSO targets) and CluMPR DESI Legacy Survey galaxy cluster catalog.  Paper decribing the CluMPR galaxy cluster catalogs and candidate lensed quasar catalogs: The CluMPR Galaxy Cluster-Finding Algorithm and DESI Legacy Survey Galaxy Cluster catalogue (M. J. Yantovski-Barth et al.) Description:  To search for lensed quasars, we use two Einstein radii: one corresponds to wide angle lensing by the entire cluster (𝑀 = 10^15 𝑀⊙ ), and the other corresponds to lensing by the core of the cluster (𝑀 = 0.25 &lowast; 10^15 𝑀⊙ ). We use the colors in bands g-r, g-z, and r-W1 to evaluate candidate lensed quasars. If at least two quasars are within 1 magnitude of each other in all 3 colors, we rate the candidate at Grade C. If at least three quasars are within 1 magnitude of each other in all 3 colors, we rate the the candidate at Grade B. If either 4 quasars or two combinations of 3 quasars are within 1 magnitude of each other in all 3 colors, we rate the candidate as Grade A.

opencc-by-4.0Mar 2024View details →

CESM2 land output data for study on hydrological impacts of large-scale forest expansion

This repository contains the land output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation. The datasets cover the period 2015-2100. The files are labelled according to the experiments they were generated from (base, MF (Max Forest) and No LULCC). Output fields are as follows: discharge_plus_runoff: surface water availability (river discharge plus surface runoff), units m^-3 s^-1 EFLX_LH_TOT: total latent heat flux from land to atmosphere, units W m^-2 QFLX_EVAP_TOT: total evapotranspiration (canopy evaporation plus canopy transpiration plus soil evaporation), units kg m^-2 s^-1 SOILLIQ: soil liquid water content, units kg m^-2 SW_surface_albedo: surface albedo, units fraction TSA: 2m air temperature, units K VEGWP: vegetation water potential, units m   All data were generated and processed by James A. King.