Find research datasets worth reusing

opencc-by-4.0Jan 2024View details →

Global 1km Land Surface Parameters for Kilometer-Scale Earth System Modeling (LAI_2001_2005)

Earth system models (ESMs) are progressively advancing towards the kilometer scale (k-scale). However, the surface parameters for Land Surface Models (LSMs) within ESMs running at the k-scale are typically derived from coarse resolution and outdated datasets. This study aims to develop a new set of global land surface parameters with a resolution of 1 km for multiple years from 2001 to 2020, utilizing the latest and most accurate available datasets. Specifically, the datasets consist of parameters related to land use and land cover, vegetation, soil, and topography. Differences between the newly developed 1k land surface parameters and conventional parameters emphasize their potential for higher accuracy due to the incorporation of the most advanced and latest data sources. To demonstrate the capability of these new parameters, we conducted 1 km resolution simulations using the E3SM Land Model version 2 (ELM2) over the contiguous United States. Our results demonstrate that land surface parameters contribute to significant spatial heterogeneity in ELM2 simulations of soil moisture, latent heat, emitted longwave radiation, and absorbed shortwave radiation. On average, about 31% to 54% of spatial information is lost by upscaling the 1 km ELM2 simulations to a 12 km resolution. Using eXplainable Machine Learning (XML) methods, the influential factors driving the spatial variability and spatial information loss of ELM2 simulations were identified, highlighting the substantial impact of the spatial variability and information loss of various land surface parameters, as well as the mean climate conditions. The comparison against four benchmark datasets indicates that ELM generally performs well in simulating soil moisture and surface energy fluxes. The new land surface parameters are tailored to meet the emerging needs of k-scale LSMs and ESMs modeling with significant implications for advancing our understanding of water, carbon, and energy cycles under global change.  This data repository is linked to <a href="../records/10815170" target="_blank" rel="noopener">https://zenodo.org/records/10815170</a>

What do we know about the missing millions of Earth's insect species: evidence from Australian tropical rainforest bark beetles?

Only 20% of the estimated five million species of insects on Earth are named despite over 240 years of taxonomy. Yet insects are poorly represented in protected area assessments, and insect declines are of concern globally. Here we explore how to increase the discovery of new species and understanding of this group through analysis of 10,097 tropical rainforest bark beetles (Scolytinae) from eight different ecological studies using beetles between 2000 and 2018 in the Australian Wet Tropics. Of the 107 species identified, 58 are undescribed: an increase of 35% on the 166 species known from Australia. As hypothesised, new species are significantly smaller, less abundant and less widespread than described species making them more extinction prone than named species. Rarefaction indicates doubling sampling would increase the number of species by 17. Flight Interception Traps (FIT) collected 84% of individuals and 98% of species confirming the effectiveness of a single sampling method for some beetles. Increased locations and collection from the canopy may sample further species rather than additional collecting methods.  Scolytines are relatively well studied with a cadre of taxonomists at the forefront of using modern methods to resolve formerly intractable groups. These new species are more likely to be named than others in many other beetle groups where taxonomy has largely stalled. To increase species description rates and to avoid most species becoming extinct before being named, we call on taxonomists to use new character systems provided by DNA methods and to look at working with Artificial Intelligence tools.

Data from: "Rare earth elements sediment analysis tracing anthropogenic activities in the stratigraphic sequence of Alagankulam (India)"

Open the record for dataset details and reuse information.

Datasets of the Doctoral Dissertation: "A Geoarchaeological Approach to the Materiality and Historical Ecology of Earth Mounds: The Colina da Monte Site, Uruguay."

These PDF files contain the datasets, workflows, and codes from Rocío M. López Cabral's Doctoral Dissertation project: "A Geoarchaeological Approach to the Materiality and Historical Ecology of Earth Mounds: The Colina da Monte Site, Uruguay."

Purple is the New Green: Biopigments and Spectra of Earth-like Purple Worlds

With more than 5,500 detected exoplanets, the search for life is entering a new era. Using life on Earth as our guide, we look beyond green landscapes to expand our ability to detect signs of surface life on other worlds. While oxygenic photosynthesis gives rise to modern green landscapes, bacteriochlorophyll-based anoxygenic phototrophs can also color their habitats and could dominate a much wider range of environments on Earth-like exoplanets. Here we characterize the reflectance spectra of a collection of purple sulfur and purple non-sulfur bacteria from a variety of anoxic and oxic environments. We present models for Earth-like planets where purple bacteria dominate the surface and show the impact of their signatures on the reflectance spectra of terrestrial exoplanets. Our research provides a new resource to guide the detection of purple bacteria and improves our chances of detecting life on exoplanets with upcoming telescopes. Our biological pigment database for purple bacteria and the high-resolution spectra of Earth-like planets, including ocean worlds, snowball planets, frozen worlds, and Earth analogs, are available online, providing a tool for modelers and observers to train retrieval algorithms, optimize search strategies, and inform models of Earth-like planets, where purple is the new green. Min publication:<a href="https://doi.org/10.1093/mnras/stae601" target="_blank" rel="noopener">https://doi.org/10.1093/mnras/stae601</a> lc992@cornell.edu

opencc-by-4.0Apr 2024View details →

Ellipsoidal Harmonic Forward Model derived from Earth2014 topographies up to d/o 7200: EHFM_Earth_7200

The model named EHFM_Earth_7200 was derived by layer-based forward modeling technique in ellipsoidal harmonics, the maximum degree of this model reaches 7200. The relief information was provided by Earth2014 relief model. EHFM_Earth_7200 provides very detailed (~3 km) information for the Earth’s short-scale gravity field, and it is expected to be able to augment or refine existing global gravity models. To meet the existing standard, here we provide spherical harmonic coefficients, which are transformed from original ellipsoidal harmonic coefficients.

opencc-by-4.0Nov 2024View details →

Most Super-Earths Have Less Than 3% Water: Mass-Radius Relations

Mass-radius relations for rocky super-Earths, related to the models constructed in "Most Super-Earths Have Less Than 3% Water" by James G. Rogers, Caroline Dorn, Vivasvaan Aditya Raj, Hilke E. Schlichting, and Edward D. Young. We provide two .csv files for the scenarios of super-Earths with and without outgassed mantles, respectively. Each file contains planet masses and radii (measured in Earth units) under the scenario of stripped and retained steam atmospheres. These are provided for a range in total water mass fractions (X_H2O) and equilibrium temperature (Teq). Note that all models have an Earth-like 32.5 % iron-core mass fraction. The water mass fractions of stripped models are less than that of retained atmospheres. To extract a single mass-radius relation for a desired scenario, filter a file for planets of a given (retained) water mass fraction and equilibrium temperature.

opencc-by-4.0Nov 2024View details →

Database of Short Large-Amplitude Magnetic Structures (SLAMS) detected by spacecraft 1 of the Cluster mission in the foreshock of Earth

Database of Short Large-Amplitude Magnetic Structures (SLAMS) detected in the foreshock of Earth by spacecraft 1 of the Cluster mission between the years 2002-2012. An automated algorithm has been used for SLAMS identification followed by a manual verification process to remove bow shock oscillations and other false detections. SLAMS have been defined to have an amplitude of at least two times the background magnetic field.  More details on the creation of the database are given in the following publication: Bergman, S., Karlsson, T., Wong Chan, T. K., & Trollvik, H. (2025). Statistical properties of Short Large‐Amplitude Magnetic Structures (SLAMS) in the foreshock of Earth from Cluster measurements. Journal of Geophysical Research: Space Physics, 130. <a href="https://doi.org/10.1029/2024JA033568">https://doi.org/10.1029/2024JA033568</a> Contact: S. Bergman, sofiabergmanphd@gmail.com

opencc-by-4.0Nov 2024View details →

Input GNSS time series data for Tanaka et al. (2024), JGR Solid Earth

Detail explanatios are in the uploaded README file.

opencc-byOct 2024View details →

Land surface temperature (heatmaps) derived from earth observation data to assess thermal behaviour of 3 European cities: Milano, Logroño and Athens.

Next tables present the detail description of the datasets developed in REACHOUT to characterize heat phenomena at city level by providing an assessment of the land surface temperature (heatmaps) of three European cities: Milan, Logroño and Athens. TECNALIA is the responsible partner for these datasets. There is a wide range of methods that can be used to characterise the thermal behaviour of a city, each of them with its advantages and disadvantages. One of these methods uses the land surface temperature that is obtained from remote sensing observations. Although thermal indices are considered more suitable when characterising thermal comfort, still the LST can provide a useful information about the behaviour of a citiy’s surfaces and materials. This has implications for several applications such as urban energy efficiency or urban environmental health.  The input data used by the current version of the dataset came from Landsat 8. All the images acquired since 2013 by this satellite for Milan, Logroño and Athens were downloaded and processed to characterise not only the current (2019-2023) thermal behaviour of the city, but also its evolution considering the last seven 5-year windows. -    2013-2017 -    2014-2018 -    2015-2019 -    2016-2020 -    2017-2021 -    2018-2022 -    2019-2023 The input data used in this dataset come from Landsat 8 downloaded from <a href="https://earthexplorer.usgs.gov/">Earth Explorer (usgs.gov)</a>. The format of this dataset is organized in two ZIP format files: -    LANDSAT_8_L2SP_000000-milan_LST_peak.zip -    LANDSAT_8_L2SP_000000-logrono_LST_peak.zip -    LANDSAT_8_L2SP_000000-athens_LST_peak.zip Each of these zip files contain seven TIF images that represent the peak LST map according to the images of the above mentioned seven periods. The peak LST is obtained after getting the Annual Cycle Parameters of each of the periods and selecting a 30-day window centred on the day that the city reaches the maximum LST. The values of the images are in degree Celsius and nodata value is -9999.

opencc-by-4.0Oct 2024View details →

Dataset for Polarized Signatures of the Earth Through Time: An Outlook for the Habitable Worlds Observatory

The search for life beyond the Solar System remains a primary goal of current and near-future missions, including NASA's upcoming Habitable Worlds Observatory (HWO). However, research into determining the habitability of terrestrial exoplanets has been primarily focused on comparisons to modern-day Earth. Additionally, current characterization strategies focus on the unpolarized flux from these worlds, taking into account only a fraction of the informational content of the reflected light. Better understanding the changes in the reflected light spectrum of the Earth throughout its evolution, as well as analyzing its polarization, will be crucial for mapping its habitability and providing comparison templates to potentially habitable exoplanets. Here we present spectropolarimetric models of the reflected light from the Earth at six epochs across all four geologic eons. We find that the changing surface albedos and atmospheric gas concentrations across the different epochs allow the habitable and non-habitable scenarios to be distinguished, and diagnostic features of clouds and hazes are more noticeable in the polarized signals. We show that common simplifications for exoplanet modeling, including Mie scattering for fractal particles, affect the resulting planetary signals and can lead to non-physical features. Finally, our results suggest that pushing the HWO planet-to-star flux contrast limit down to 1 $\times$ 10$^{-13}$ could allow for the characterization in both unpolarized and polarized light of an Earth-like planet at any stage in its history. This dataset contains all modeled spectropolarimetric signatures used to conduct this work. Each .zip file contains the output folders for one of the four eons: Hadean, Archean, Proterozoic, and Phanerozoic (i.e., Modern). Each of these top-level folders then contains individual folders for each specific model run. The names for each of these individual folders describes the specific model. Finally, each individual folder then contains files for the spectropolarimetric signatures, where each file contains four columns of data representing the spectra for that specific model at that specific planetary phase angle. Please refer to the README.txt as well as the accompanying manuscript for more information. Version 2 of this dataset includes the updated models for the Archean Earth with hazy atmospheres that now extend their spectra from the original 1.2um limit to 1.8um.

opencc-by-4.0May 2024View details →

AIMS - Earth Observation Satellite Data of Wave and Wind in the Tyrrhenian Sea

This dataset is part of the AIMS project (Artificial Intelligence to Monitor our Seas), which has the vision to develop and validate novel Artificial Intelligence (AI) algorithms to unlock the true potential of remote monitoring and enable a faster transition to a climate neutral society and economy: the AI algorithms will leverage the advantages of usual monitoring methodologies of the features of waves and offshore wind, and eventually overcome their intrinsic limitations. The value and resolution of sparse measurements of satellites and unevenly-distributed in-situ instruments will be increased, hence leading to a significant reduction of the cost and execution time of data collection, ultimately making knowledge wider and more accessible. In particular, this dataset aggregates earth observation satellite data from 10 different satellites, measureing the significant wave height and the wind speed at 10 meters above sea leavel in the Tyrrhenian Sea, from January 2021 to May 2024.

opencc-by-4.0Oct 2021View details →

Supplementary Table for Earth observation data-driven cropland soil monitoring: A review

Table including 46 manuscripts written in English referring to topsoil monitoring related to Earth observation data-driven cropland soil monitoring: A review paper.

opencc-by-4.0Jun 2020View details →

A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine

This dataset contains the China terrace map at 30 m resolution in 2018. The map values and their corresponding classes are as follows: 0: Non-terrace   1: Terrace   255: No data The 30 m China terrace map can also be viewed online at <a href="https://cbw.users.earthengine.app/view/chinaterracemap">https://cbw.users.earthengine.app/view/chinaterracemap</a> Citations: When using this dataset, please cite both the dataset and the following data description article: Cao, B., Yu, L., Naipal, V., Ciais, P., Li, W., Zhao, Y., Wei, W., Chen, D., Liu, Z., and Gong, P.: A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine, Earth Syst. Sci. Data, 13, 2437–2456, https://doi.org/10.5194/essd-13-2437-2021, 2021.

Dataset and scripts for manuscript "Using Neural Network Ensembles to Separate Ocean Biogeochemical and Physical Drivers of Phytoplankton Biogeography in Earth System Models"

Please note: The title of this version contains an updated title for the manuscript compared to the previous version of this dataset. This is only due to title updates during the peer review process for the manuscript. The zip file contains the scripts, functions, and source files for the manuscript titled "Using Neural Network Ensembles to Separate Ocean Biogeochemical and Physical Drivers of Phytoplankton Biogeography in Earth System Models." The manuscript has been submitted for peer review. Please consult the README file for information on the specifications of the files. These files may occasionally be updated to add annotations to the scripts to make them more user friendly and to correct any errors.

Fig. 13 in The largest arthropod in Earth history: insights from newly discovered Arthropleura remains (Serpukhovian Stainmore Formation, Northumberland, England)

Fig. 13. Palaeogeographical range of Arthropleura body and trace fossils. (a) Known sites of evidence plotted on a palaeogeographical map of the late Carboniferous (c. 310 Ma; after Torsvik and Cocks 2016). Numbers refer to sites listed in Table 1. (b) Visean to Serpukhovian sites (latitudinal parallels shown for c. 320 Ma; from Torsvik and Cocks 2016). (c) Bashkirian to Moscovian sites (latitudinal parallels shown for c. 310 Ma; from Torsvik and Cocks 2016). (d) Kasimovian to Sakmarian sites (latitudinal parallels shown for c. 290 Ma; from Torsvik and Cocks 2016).

Fig. 12 in The largest arthropod in Earth history: insights from newly discovered Arthropleura remains (Serpukhovian Stainmore Formation, Northumberland, England)

Fig. 12. Trace fossil evidence for Arthropleura from the trackway Diplichnites cuithensis, preserved in strata, near contemporaneous in age to the Howick specimen, from adjacent basins in northern Britain (see Fig. 3 for localities). (a) Trackway from which the D. cuithensis holotype was cast (Briggs et al. 1979) in the Serpukhovian Limestone Coal Formation of Laggan, Isle of Arran, Scotland. Stick is 1 m long, inner and outer width of trackway highlighted. (b) D. cuithensis trackway of near-analogous width to the Howick body fossil, Visean Pittenweem Formation, Crail, Fife, Scotland. (c) D. cuithensis trackway>10 m long (arrowed) in the Visean Pittenweem Formation, St Andrews, Fife, Scotland (see Whyte 2018). Geologist is 1.8 m tall. (d, e) Photograph and interpreted sketch of context of D. cuithensis on a true substrate (Davies and Shillito 2018, 2021) recording the passage of two animals between emergent and subaqueous substrates. Convex bedform, colonized with plants, provided small island surrounded by shallow water puddles in a delta-top setting. Trackways are well-defined on emergent substrate and less so on subaqueous parts of substrate. Visean Anstruther Formation, 3.5 km NW of Kingsbarns, Fife, Scotland. Measuring stick 60 cm long.

Fig. 10 in The largest arthropod in Earth history: insights from newly discovered Arthropleura remains (Serpukhovian Stainmore Formation, Northumberland, England)

Fig. 10. Details of (a, b) slab Aand (c, d) slab Bwith interpreted sketches of margins showing offset of three-dimensional sand infill from carbonaceous smear. Same tergites on each slab are colour-coded (with reference to prominent tergite shown in white). Cuticular interior shown as full circles with correspondingly shaped carbonaceous smear shown as colour-coded partial circles, indicating consistent 40 cm squeezed offset of infill from cuticle in direction of red bidirectional arrow, associated with synsedimentary deformation. Scale bars 20 cm.

Fig. 9 in The largest arthropod in Earth history: insights from newly discovered Arthropleura remains (Serpukhovian Stainmore Formation, Northumberland, England)

Fig. 9. Three-dimensional morphology of cuticular sand infill preserved in slab A. (a, b) Images of slab A before and after extraction of fossil. Part (a) shows a natural break in sandstone revealing the underside of the dorsal cuticle, notable for carbonaceous material (cb) between the paratergites and the presence of a granular texture. Part (b) shows slab A after extraction, revealing the cast of the dorsal exoskeleton, still yielding carbonaceous material, but with no granular texture. Scale bars 20 cm. (c, d) Images of partial fragment of cuticular sand infill between the underside and upper side of the dorsal cuticle, as extracted from slab A. Part (c) shows the exoskeleton underside with a granular texture and both images show cross-section through lenticular imbricated tergites, possibly compressed by synsedimentary tectonics. Scale bar 1 cm. An, anterior; Po, posterior.

Fig. 7 in The largest arthropod in Earth history: insights from newly discovered Arthropleura remains (Serpukhovian Stainmore Formation, Northumberland, England)

Fig. 7. Schematic diagram showing taphonomic context and relationship between key attributes of the specimen.