cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.22002/d1.1327
title: Downscaled 500-m TROPOMI SIF over California

description: Data is saved as self-contained daily netCDF4 files
 --------------------------------------------------------------------
 USE OF DOWNSCALED TROPOMI SIF DATA

These data are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific insights.


The availability of these data does not constitute publication of the data. We rely on the ethics and integrity of the user to  receive fair credit for our work. If the data are obtained for  potential use in a publication or presentation, we ask to be  informed at the outset of the nature of this work. If the data are  essential to the work, or if an important result or conclusion  depends on the TROPOMI SIF data, co-authorship may be appropriate.  This should be discussed at an early stage in the work. Manuscripts  using the downscaled TROPOMI SIF data should be sent to us for  review before they are submitted for publication ensure that the quality and limitations of the data are accurately represented.


Corresponding Manuscripts:


 1) Turner et al. (2019): https://doi.org/10.5194/bg-2019-387


 2) Kohler et al. (2018): https://doi.org/10.1029/2018GL079031


Contact:   Alexander Turner (alexjturner@berkeley.edu)


       Philipp Koehler (pkoehler@caltech.edu)


       Christian Frankenberg (cfranken@caltech.edu)
description: Related Publication:
A double peak in the seasonality of California's photosynthesis as observed from space

Alexander J. Turner Berkeley

Biogeosciences

2019

https://doi.org/10.5194/bg-2019-387
eng
description: Contact person: Philipp Koehler pkoehler@caltech.edu
DOI: 10.25318/82-003-x202201100001-eng
title: Health associations with meeting the new Canadian 24-Hour Movement Guidelines recommendations according to body mass index classes in Canadian adults

description: Data on meeting the Canadian 24-Hour Movement Guidelines for adults (24-H Guidelines) and associations with health indicators by body mass index (BMI) class are needed to support public health surveillance. Using data from the cross-sectional Canadian Health Measures Survey, this study aims to describe the proportion of Canadian adults meeting individual and various combinations of the 24-H Guidelines by BMI class and their association with health indicators.
DOI: 10.3886/e198350v1
title: Data and Code for: Profit Taxation, R&D Spending, and Innovation

description: This archive contains the replication files for our paper “Profit Taxation, R&D Spending, and Innovation.”<br><br><b>Abstract.</b> We study how profit taxes affect establishments’ R&D activities. Relying
on detailed panel data of R&D-active firms in Germany over two decades, we exploit
identifying variation induced by more than 10,000 municipal changes in the local business
tax rate and federal tax reforms with locally varying effects. Using event study techniques,
we find a sizable, negative effect of profit taxes on establishments’ total R&D spending and
patents filed. Zooming into the innovation production process, we uncover substantial
heterogeneity in the impact of profit taxation for various R&D input factors, among firm
characteristics, and for different types of research projects.

 
 
 
 
<br><br>
description: R&D active firms in Germany<br>. Smallest Geographic Unit: municipality
DOI: 10.5066/f74t6gjc
title: The Preliminary Determination of Epicenters (PDE) Bulletin

description: The NEIC global earthquake bulletin is called the Preliminary Determination of Epicenters or PDE.
DOI: 10.5067/aura/omi/data2007
title: OMI/Aura Cloud Pressure and Fraction (O2-O2 Absorption) 1-Orbit L2 Swath 13x24km
DOI: 10.5067/aura/omi/data3008
title: OMI/Aura Sulfur Dioxide (SO2) Total Column Daily L3 Best Pixel Global 0.25deg Lat/Lon Grid
DOI: 10.5067/d7dx7j7j5jn9
title: IceBridge Ku-Band Radar L1B Geolocated Radar Echo Strength Profiles, Version 2
DOI: 10.5281/zenodo.1195043
title: Cariboo Alpine Mesonet (Camnet) Database

description: The Cariboo Alpine Mesonet (<em><strong>CAMnet</strong></em>) is currently a network of 11 meteorological stations installed at mid to high elevation sites within the Quesnel, Nechako and Kiskatinaw watersheds. This database includes data for all de-commissioned and currently active stations within this network.
DOI: 10.5281/zenodo.1320834
title: Micro-Seismic And Image Dataset Acquired At Matterhorn Hörnligrat, Switzerland

description: This dataset contains annotated micro-seismic recordings and images acquired in the context of project X-Sense2 (financed by nano-tera.ch, ref. no. 530659) at the Matterhorn Hörnligrat fieldsite on 3500 m a.s.l.. Additionally, secondary data is provided which can used for further analysis.

This dataset comprises a selection of measurements. The <em>data</em> folder contains two datasets and additional data (secondary data). Please refer to the following publication for further information:

 

Meyer, M., Weber, S., Beutel, J., Thiele, L.: Systematic Identification of External Influences in Multi-Year Micro-Seismic Recordings Using Convolutional Neural Networks, Earth Surface Dynamics, in review, 2018.

 

<strong>dataset</strong>

The <em>dataset/</em> folder contains micro-seismic data, images, and annotations.

A list of every datapoint including annotations and start/end time is provided in two csv files in the <em>annotations/</em> folder.

 

<strong>event_dataset</strong>

The <em>event_dataset/</em> folder contains micro-seismic data and annotations.

A list of every datapoint including annotations and start/end time is provided in two csv files in the <em>annotations/</em> folder. For a selected time period bounding boxes are provided in the <em>bounding_box.csv</em> file.

 

<strong>Micro-seismic data</strong>

The data was recorded using a Nanometrics Centaur digital recorder and Lennartz electronic low-noise seismometer LE-3Dlite MKIII (1−100 Hz). The Nanometrics Centaur digital recorder aquires data with 24-bit resolution with a sampling rate of 1000 sps. The data is stored in .miniseed-format.

 

<strong>Image data</strong>

Images where acquired with a remote controlled high-resolution camera (Nikon D300, 24 mm fixed focus).

 

<strong>Annotations</strong>

The data was annotated manually by the authors.

 

<strong>Secondary data</strong>

The secondary data comprises data from different sensors, including wind speed, rock temperature and radiation. Additionally, weekly aggregated hut occupancy of the Hörnlihut from the years 2016/2017 and event timestamps from running a STA/LTA trigger on an internal version of the micro-seismic data are provided.
DOI: 10.5281/zenodo.1403177
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: pDSSAT rice

description: This is model output from pDSSAT for rice as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408575
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: GEPIC rice

description: This is model output from GEPIC for rice as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.2815907
title: Amundsen Sea MAR simulations forced by ERAinterim

description: <strong>MAR simulations produced by Marion Donat-Magnin at IGE, Grenoble, France.</strong> <br> This simulation is evaluated in the following article: Donat-Magnin, M., Jourdain, N. C., Gallée, H., Amory, C., Kittel, C., Fettweis, X., Wille, J. D., Favier, V., Drira, A., and Agosta, C. (2020). Interannual variability of summer surface mass balance and surface melting in the Amundsen sector, West Antarctica, The Cryosphere, 14, 229–249, https://doi.org/10.5194/tc-14-229-2020 <br> Here are provided the monthly means over 1979-2017. Daily outputs available on demand.<br> <br> See netcdf metadata for more information. Note that what is called runoff in the outputs is not actually a runoff (into the ocean) but more the net production of liquid water at the surface (which can either form ponds or flow into the ocean). Monthly files provided on MAR grid (see MAR_grid10km.nc). We also provide climatological (1979-2017 average) surface mass balance (SMB), surface melt rates and net liquid water production ("runoff") on a standard 8km WGS84 stereographic grid (see files ending as mean_polar_stereo.nc). The following variables are provided: CC Cloud Cover LHF Latent Heat Flux LWD Long Wave Downward LWU Long Wave Upward QQp Specific Humidity (pressure levels) QQz Specific Humidity (height levels) RH Relative Humidity SHF Sensible Heat Flux SIC Sea ice cover SP Surface Pressure ST Surface Temperature SWD Short Wave Downward SWU Short Wave Upward TI1 Ice/Snow Temperature (snow-layer levels) TTz Temperature (height levels) UUp x-Wind Speed component (pressure levels) UUz x-Wind Speed component (height levels) VVp y-Wind Speed component (pressure levels) VVz y-Wind Speed component (height levels) UVp Horizontal Wind Speed (pressure levels) UVz Horizontal Wind Speed (height levels) ZZp Geopotential Height (pressure levels) mlt Surface melt rate rfz Refreezing rate rnf Rainfall rof Runoff (i.e. net production of surface liquid water) sbl Sublimation smb Surface Mass Balance snf Snowfall
description: wrong time axis in v1.0 -&gt; corrected in v1.1. Climatological standard stereographic and unit corrections.
DOI: 10.5281/zenodo.3482931
title: Drainage reorganisation and species evolution: model sensitivity analysis data

description: Data description: <strong>‘trial_factor_values.csv’:</strong> The factor values for experiment trials were generated using a quasi-random Sobol sequence (Sobol, 1967). The table field, ‘initial_landscape_id’ is the identifier for unique combinations of the following factor values that controlled the landscape elevation in the initial conditions phase of the model: initial elevation seed, \(U\), \(K\), and \(k_d\). The factors, \(U\), \(K\), \(k_d\), \(P_m\), and allopatric wait time varied logarithmically. The values of these factors in the file are the exponent of base 10. <strong>‘trial_response_values_initial_conditions_phase.csv’:</strong> Topographic relief at steady state along with the model time to initial steady state are the trial model responses included in the file. Values are listed for each initial landscape ID rather than trial because many trials had the same combinations of the factors that controlled the topography of the initial landscape. <strong>‘trial_response_values_perturb_phase_base_level_fall_scenario.csv’ and ‘trial_response_values_perturb_phase_fault_throw_scenario.csv’:</strong> Model responses of the perturb phase for base level fall and fault throw scenario along with the initial landscape ID, species count values, and the model time back to steady state. <strong>The files beginning with `sobol`</strong>: the sensitivity analysis results output by the software, ‘SALib’ (Herman and Usher, 2017). ‘S1’, ‘S2’, and ‘ST’ in the file name indicates if the file contains data of the Sobol first, second, or total order effect, respectively.
description: {"references": ["Herman, J., and Usher, W.: SALib: An open-source Python library for Sensitivity Analysis, Journal of Open Source Software, 2, https://doi.org/10.21105/joss.00097, 2017.", "Sobol I. M.: Distribution of points in a cube and approximate evaluation of integrals, Zh. Vychisl. Mat. Mat. Fiz., 7, 784\u2013802, 1967 (in Russian); Comp. Math. Math. Phys., 7, 86\u2013112, https://dx.doi.org/10.1016/0041-5553(67)90144-9, 1967 (in English)."]}
DOI: 10.5281/zenodo.3701243
title: Comparison of different gas extraction techniques to analyze CH4 and N2O compositions in gas trapped in permafrost ice wedges

description: Methane (CH4) and nitrous oxide (N2O) compositions in ground ice may provide information on their production mechanisms in permafrost. However, existing gas extraction methods have not been well tested. We tested conventional wet and dry gas extraction methods using ice wedges from Alaska and Siberia, finding that both methods can extract gas from the easily extractable parts of the ice (e.g., gas bubbles), and yield similar results for CH4 and N2O mixing ratios. We also found insignificant effects of microbial activity during wet extraction. However, both techniques were unable to fully extract gas from the ground ice, presumably because gas molecules adsorbed onto or enclosed in soil aggregates are not easily extractable. Estimation of gas production in subfreezing environment of permafrost should consider such incomplete gas extraction.
description: This project was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) (NRF-2018R1A2B3003256 and NRF-2018R1A5A1024958) and the NASA ABoVE (Arctic Boreal and Vulnerability Experiment; grant no. NNX17AC57A).
description: {"references": ["Yang, J.-W., Ahn, J., Iwahana, G., Han, S., Kim, K., and Fedorov, A.: Brief Communication: The reliability of gas extraction techniques for analysing CH4 and N2O compositions in gas trapped in permafrost ice-wedges, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-231, in review, 2019."]}
DOI: 10.5281/zenodo.3754767
title: Flume experiments on the effects of sediment feed rates on step formation, evolution and stability

description: The dataset contains: - Digital Elevation Models of the experiments collected every hour - Pics of the Bed topography collected every hour - Step number, location, evolution (as described in the paper submitted to Earth Surface Dynamics) - Bed grain-size distribution, sediment and sediment concentration.
DOI: 10.5281/zenodo.3882254
title: KLT-IV v1.0 Demo Files

description: This is a demonstration dataset consisting of footage acquired at the River Feshie and River Coquet (UK). The analysis of this footage using KLT-IV is presented in the article: 'KLT-IV v1.0: Image velocimetry software for use with fixed and mobile platforms'. In addition to the raw footage acquired by the camera sensors, the settings used in KLT-IV to generate the outputs presented in the aforementioned article are presented.
DOI: 10.5281/zenodo.4596407
title: Manually categorized initial training data for open-water–sea-ice–cloud discrimination

description: This data set contains labeled training data for supervised classification of open-water/thin-ice, sea-ice, and cloud pixels from MODIS thermal-infrared satellite data and is created from manual categorization of dimensional reduced and unsupervised clustered co-located Sentinel-1 SAR and MODIS MOD021KM/MYD021KM swaths. All data originates from the Brunt Ice Shelf area in the Antarctic Southeastern Weddell Sea [34degW to 18degW; 73degS to 77degS] resampled to an equi-rectangular grid [445 (rows) x 460 (columns)]. The data is organized as tab-delimited tables per Sentinel-1 reference swath with geolocation (lon/lat) and the compiled predictors for different MODIS swath combinations. This data can be used to retrace the classifier training as described in the reference publication [DOI: https://doi.org/10.5194/tc-15-1551-2021] or used as a basis to create your own classification scheme. Additional information can be found in the provided meta data file.
description: Improved machine-learning-based open-water–sea-ice–cloud discrimination over wintertime Antarctic sea ice using MODIS thermal-infrared imagery [https://doi.org/10.5194/tc-15-1551-2021]
DOI: 10.5281/zenodo.7811955
title: Zenodo Collection: Estimation of best-fitting force, moment tensor, and depth for the 2022 Hunga-Tonga submarine volcanic eruption

description: This Zenodo collection contains figures and results from grid searches used to estimate point source parameters (force or moment tensor) for the main seismic subevent of the 2022 Hunga-Tonga submarine volcanic eruption. The collection includes misfit maps and waveform fits for the best-fitting force or moment tensor, as well as MTUQ weight files and a zipped version of the MTUQ code. These results were obtained using various software tools, including MTUQ, Axisem, Instaseis, Syngine, Obspy, GMT, and PyGMT. The collection was prepared for a manuscript in review for Geophysical Journal International.
description: This project was supported by Air Force Research Laboratory contract HQ0034-20-F-0284 funded through the UAF Geophysical Detection of Nuclear Proliferation (GDNP) University Affiliated Research Center (UARC). We thank Ryan Modrak for his contributions and core work on the MTUQ software.
DOI: 10.5285/3ef6a5a66e9947d39b356251909dc12b
title: ESA Sea State Climate Change Initiative (Sea_State_cci) : Global remote sensing daily merged multi-mission along-track significant wave height, L3 product, version 1.1

description: The ESA Sea State Climate Change Initiative (CCI) project has produced global daily merged multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 3 (L3) data) with a particular focus for use in climate studies. This dataset contains the Version 1.1 edited Remote Sensing Significant Wave Height product, along-track at approximately 6 km spatial resolution, which have been generated from upstream Sea State CCI L2P products, edited and merged into daily products, retaining only valid and good quality measurements from all altimeters over one day, with simplified content (only a few key parameters). This is close to what is delivered in Near-Real Time by the CMEMS (Copernicus - Marine Environment Monitoring Service) project. This first version of Sea State CCI products is inherited from the GlobWave project building on experience and existing outputs. It extends and improves the GlobWave products which were a post-processing over existing L2 altimeter agency products with additional filtering, corrections and variables. A major improvement consists in a new denoised sea surface height variable using Empirical Mode Decomposition. The altimeter data used in the Sea State CCI dataset v1.1 come from multiple satellite missions spanning from 1991 to 2018 (ERS-1, ERS-2, Topex, Envisat, GFO, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL). Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).
DOI: 10.5285/47140d618dcc40309e1edbca7e773478
title: ESA Sea State Climate Change Initiative (Sea_State_cci) : Global remote sensing merged multi-mission monthly gridded significant wave height, L4 product, version 1.1

description: The ESA Sea State Climate Change Initiative (CCI) project has produced global merged multi-sensor time-series of monthly gridded satellite altimeter significant wave height (referred to as Level 4 (L4) data) with a particular focus for use in climate studies. This dataset contains the Version 1.1 Remote Sensing Sea Surface Height product, gridded over a global regular cylindrical projection (1°x1° resolution), averaging valid and good measurements from all available altimeters on a monthly basis (using the L2P products also available). These L4 products are meant for statistics and visualization. This first version of the Sea State CCI products is inherited from the GlobWave project, building on experience and existing outputs. It extends and improves the GlobWave products ,which were a post-processing over existing L2 altimeter agency products with additional filtering, corrections and variables. A major improvement consists in a new denoised sea surface height variable using Empirical Mode Decomposition, which was used as input to these monthly statistical fields. The altimeter data used in the Sea State CCI dataset v1.1 come from multiple satellite missions spanning from 1991 to 2018 (ERS-1, ERS-2, Topex, Envisat, GFO, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL). Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).
DOI: 10.5879/ecds/00000002
title: Northern Circumpolar Soil Carbon Database 2

description: The Northern Circumpolar Soil Carbon Database (NCSCD) is a geospatial database created for the purpose of quantifying storage of organic carbon in soils of the northern circumpolar permafrost region. The spatial base of the NCSCD is a polygon database describing soils in the northern circumpolar permafrost regions. The database was compiled by combining and homogenizing several regional/national soil maps. To calculate storage of soil organic carbon, these soil maps have been linked to field-data on soil organic carbon storage from sites around the circumpolar permafrost region. 
    The NCSCDv2 contains information on fractions of coverage of different soil types (following U.S. Soil Taxonomy nomenclature) as well as storage of soil organic carbon (kg/m2) between 0-30 cm and 0-100 cm, 100-200 cm and 200-300 cm depth. The NCSCD is available either as a polygon-based database (which is the original format) or converted to gridded data. Gridded data products are available in different spatial grid resolutions and in formats adapted for use in desktop GIS-applications and  model applications.