Find research datasets worth reusing

opencc-by-4.0Mar 2023View details →

Inlist Files for "Near-Core Acoustic Glitches are Not Oscillatory: Consequences for Asteroseismic Probes of Convective Boundary Mixing"

MESA (r12778) and GYRE (version 6.0) inlist files used in the work described in "Near-Core Acoustic Glitches are Not Oscillatory: Consequences for Asteroseismic Probes of Convective Boundary Mixing". Three subdirectories are provided in the archive: 1) The directory called "inlists" contains different MESA inlist files for different evolutionary period (pms=pre main sequence, ms=main sequence, and rgb=red giant branch) of the stellar model. The file named "inlist_0all" is applied to all evolutionary periods. The different inlist files for the different evolutionary states are called by putting their names in the "inlist" file, for example the include file named "inlist" evolves a MESA model from the pre main sequence until ZAMS (using the stop_near_zams = .true. option in the "inlist_1pms" file). An example gyre (version 6.0) inlist is also included in the "inlists" subdirectory.   2) Custom stopping conditions (used for stopping a model before the red giant branch) as well as a custom diffusion cutoff (see Viani et al. 2018, ApJ, 858, 28) are included in the run_star_extras.f file in the "src" subdirectory.  3) The subdirectory named "near_core_glitch_models_with_diffusion" include the MESA modelling results used in the paper (in directories labeled by their stellar mass) and GYRE-calculated frequencies (in the GYRE_OUTPUTS subdirectories).

opencc-by-4.0Mar 2023View details →

Supplemental Materials for "Convective boundary mixing in main-sequence stars: theory and empirical constraints"

MESA inlists and data products used for generating the figures of the review paper: "Convective boundary mixing in main-sequence stars: theory and empirical constraints".

opencc-by-4.0Mar 2023View details →

Wind gust during tropical cyclone Ida, with and without deep convection parametrization from 1.4km global simulation with ECMWF IFS

Animations of wind gust during tropical cyclone Ida, from global TCo7999L137 (1.4km horizontal grid-spacing) simulation with hydrostatic IFS from INCITE2022 project.  One animation shows simulation with deep convection parametrization on and the other with off.

dryad36/100

Dissimilarity of turbulent transport of momentum and heat under unstable conditions linked to convective circulations

The dissimilarity between the turbulent transport of momentum and heat under unstable conditions and its physical mechanisms are investigated in this study, based on the multiple-level turbulence observation from Tianjin's 255-m meteorological tower. The transport dissimilarity is observed from the surface layer to the lower part of the mixed layer as atmospheric instability increases. Although the transport dissimilarity is accompanied by the development of plumes and thermals under unstable conditions, plumes and thermals can produce intense transport of momentum and heat simultaneously. It is convective circulations related to vigorous thermals that cause transport dissimilarity. The horizontal divergence induced by convective circulations imposes a dominant large-scale reduction in the along-wind velocity component near the surface, while the temporal variations in temperature mainly reflect the role of plumes and thermals. This difference in respective physical processes subsequently leads to dissimilar transport between momentum and heat under unstable conditions. Therefore, the influence of convective circulations on the momentum-flux estimation should be considered in atmospheric numerical models, particularly for the simulation and prediction of severe convective weather.

opencc-zeroMar 2023View details →

Data and Software for "Numerical diffusion and Turbulent mixing in convective self-aggregation"

This folder contain the python scripts and the data necessary for reproducing figures and results reported in the paper " Numerical diffusion and turbulent mixing in convective self-aggregation" (in preparation for submission for the Journal of Advances in Modeling Earth System)

Convection-permitting projections of future changes in water balance and groundwater-surface water interactions

This dataset consists of processed data in the manuscript of "Convection-permitting projections of future changes in water balance and groundwater-surface water interactions".

TRMMPR V8 Level 2A Processed Convective Rain States 1998-2009

This dataset contains Interactive Data Language (IDL) .sav files of Convective Rain States (CRS) from 1998-2009 which are created by k-means clustering on TRMMPR Version 8 Level 2A data. It also contains IDL scripts in the TRMM.zip file that were used to process the raw TRMMPR V8 data into the available CRS data. Details on this clustering can be found in Elsaesser et al. (2010) <a href="https://doi.org/10.1175/2010JCLI3330.1">https://doi.org/10.1175/2010JCLI3330.1</a>.   Readme: - Each line in the seriesFiles txt files points to the directory where the raw downloaded data was originally held. The raw TRMMPR V8 Level 2A data was downloaded from NASA EOSDIS PPS GPM public data archive. - There are two different total number of entries between all the variables in the processed data. This is because some missing values were saved in some variables and not in others. These missing variables are denoted by -1's in the prcid variable (as well as other variables), and can be located and removed under that condition.

Inlist Files for Effects of Full Sphere Convection On M-Dwarf Dynamo Action, Flux Emergence, and Spin-Down

Inlist files for a model of a ZAMS 0.3 M_sun star used as background for global convection simulations in Effects of Full Sphere Convection On M-Dwarf Dynamo Action, Flux Emergence, and Spin-Down. Run using MESA version r12115.

TRMMPR and GPM KuPR V8 Level 2A Processed Convective Rain States 2010-2021

This dataset contains Interactive Data Language (IDL) .sav files of Convective Rain States (CRS) from 2010-2021 which are created by k-means clustering on TRMMPR Version 8 and GPM KuPR Version 8 Level 2A data. It also contains IDL scripts in the TRMM.zip and GPM.zip file that were used to process the raw TRMMPR and GPM KuPR V8 data into the available CRS data. This set is part 2 in a continuation of the data available in <a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__doi.org_10.5281_zenodo.7853386&d=DwMGaQ&c=009klHSCxuh5AI1vNQzSO0KGjl4nbi2Q0M1QLJX9BeE&r=WTOc26e3IBrEp5cDEaVnuU41G2J-MLym-VhzO4aTABg&m=dHNcst9cbr8tlYpnfdrmqG6MCbrWJa8oa0eBAL_XEyqXQY8MPg2RqBoIe8jxqaAd&s=CnET26HiWgS_mV-kbFHpR3iojlRFOREml99vwWXs4Ig&e=">https://doi.org/10.5281/zenodo.7853386</a>. Details on this clustering can be found in Elsaesser et al. (2010) <a href="https://doi.org/10.1175/2010JCLI3330.1">https://doi.org/10.1175/2010JCLI3330.1</a>.   Readme: - Each line in the seriesFiles txt files points to the directory where the raw downloaded data was originally held. The raw TRMMPR and GPM KuPR V8 Level 2A data was downloaded from NASA EOSDIS PPS GPM public data archive. - There are two different total number of entries between all the variables in the processed data. This is because some missing values were saved in some variables and not in others. These missing variables are denoted by -1's in the prcid variable (as well as other variables), and can be located and removed under that condition.

Data for the paper: Convection and convective-organization in hothouse climates

:Here you can find the data presented in the paper Convection and convective-organization in hothouse climates   The names of the variables and the different simulations are presented in the paper

opencc-zeroJun 2023View details →

dryad36/100

Supporting materials and data from: Hypotheses concerning global magnetospheric convection, magnetosphere-Ionosphere coupling, and auroral activity at Uranus

Summary: The data and figures contained in this dataset are supporting materials for the paper referenced in the title and abstract below. This study involved an analytical and numerical assessment of the Uranian magnetosphere and its interaction with the solar wind and interplanetary magnetic field (IMF). The data and figures contained in this dataset include supplementary results for a greater number of IMF orientations and Uranian seasons than the examples presented in the corresponding paper. Abstract from corresponding paper: doi:10.1029/2023JA031791 with Journal of Geophysical Research Space Physics: We investigate the unique magnetosphere of Uranus and its interaction with the solar wind. Following previous work, we developed and validated a simple yet valuable and illustrative model of Uranus' offset, tilted, and rapidly-spinning magnetic field and magnetopause (nominal and fit to the Voyager-2 inbound crossing point) in three-dimensional space. With this model, we investigated details of the seasonal and interplanetary magnetic field (IMF) orientation dependencies of dayside and flank reconnection along the Uranian magnetopause. We found that anti-parallel (magnetic field shear angle greater than 170-degrees) reconnection occurs nearly continuously along the Uranian dayside and/or flank magnetopause under all seasons of the 84 (Earth) year Uranian orbit and the most likely IMF orientations. Such active and continuous driving of the Uranian magnetosphere should result in constant loading and unloading of the Uranian magnetotail, which may be further complicated and destabilized by sudden changes in the IMF orientation and solar wind conditions plus the reconfigurations from the rotation of Uranus itself. We demonstrate that unlike the other magnetospheric systems that are Dungey-cycle driven (i.e., Mercury and Earth) or rotationally driven (Jupiter and Saturn), global magnetospheric convection of plasma, magnetic flux, and energy flow may occur via three distinct cycles, two of which are unique to Uranus (and possibly also Neptune). Our simple model is also used to map signatures of dayside and flank reconnection down to the Uranian ionosphere, as a function of planetary latitude and longitude. Such mapping demonstrates that "spot"-like auroral features should be very common on the Uranian dayside, consistent with observations from Hubble Space Telescope. We further detail how the combination of Uranus' rapid rotation and unique and very active global magnetospheric convection should be consistent with fueling of the surprisingly intense trapped radiation environment observed by Voyager-2 during its single flyby. Summarizing, Uranus is a very special magnetosphere that offers new insights on the nature, complexity, and diversity of planetary magnetospheric systems and the acceleration of particles in space plasmas, which might have important analogs to exoplanetary magnetospheric systems. Our hypotheses can be tested with further work involving more advanced models, new auroral observations, and unprecedented missions to explore the in situ environment from orbit around Uranus, which should include a complement of magnetospheric instruments in the payload.

opencc-by-4.0Jul 2023View details →

Data for "Multiple Equilibria and Soil Moisture-Precipitation Feedbacks in Idealized Convection-Permitting Simulations with an Open Hydrological Cycle"

Code, simulation input files, and simulation output data supporting “Multiple Equilibria and Soil Moisture-Precipitation Feedbacks in Idealized Convection-Permitting Simulations with an Open Hydrological Cycle”, under review at JAMES. Enclosed README files provide detailed descriptions of the archive contents.

opencc-by-4.0Jul 2023View details →

Aerosol indirect-effect-derived PM2.5 contributions during the development of convective clouds over the Yellow Sea in July of 2017

Meteorological processes are investigated during the development of deep convective clouds over the Yellow Sea inside a quasi-stationary rainy front in the East Asian region. WRF-Chem simulations were conducted to assess the aerosol-indirect-effect (AIE)-derived PM2.5 contributions to the cloud microphysical process in deep convective clouds and the associated precipitation. In our dataset, you can find output of WRF-Chem baseline simulations (BASE) and other sensitivity simulated outputs (CONTROL). Furthermore, model variables of precipitations, cloud top temperature (CTT), surface-level pressure (SLP), convective available potential energy (CAPE), and hydrometer mixing ratios of cloud water (qcloud), raindrops (qrain), and ice (qice) can be found in these zip files. If you have any difficulty downloading these datasets, please feel free to contact the first author, kimhsung@gmail.com. All references and acknowledgments can be found in our paper

Temperature measurements of full-scale wall element using Type K thermocouples to observe internal convection in loose-fill wood fiber insulation

Internal convection of insulation materials is a phenomenon that occurs when a construction element is subjected to a temperature difference on either side of the element, as the temperature difference inside the insulation will facilitate an onset of air movement due to thermal buoyancy. This dataset represents the results of 11 unique experiments conducted at Aalborg University at the Department of the Built Environment, where a full-scale wall element insulated with loose-fill wood fiber insulation is investigated for internal convection. A large guarded hotbox is used to control the boundary conditions of either side of the wall element, to imitate a construction element subjected to external and internal boundary conditions, similar to a wall in a house. This dataset can be used to benchmark other insulation materials investigated at similar boundary conditions. The dataset is structured into steady-state experiments and dynamic experiments, where a total of 7 unique cases are conducted in steady-state conditions, and 4 unique cases are conducted in dynamic conditions. The dataset for the steady-state experiments is structured by the temperature difference that the full-scale wall element is exposed to, from the cold and hot side, while the dynamic experiments are structured by the amplitude of the temperature variation, along with if an artificial sun is used or not. The results for the internal convection of the loose-fill wood fiber insulation show similar results as other studies that have conducted experiments on other insulation materials. For more information, see doi: 10.54337/aau488363266

Inherent convective mixing in TES - Supplementary Material

Video sequence of the near-wall convective flow inside a stratified thermal energy storage. As can be seen, a vortexlike structure is moving from top to bottom during this period of flow.

Southeast US Urban Convective Morphological Statistical Tests

Dataset to accompany the publication "Weakly Forced Thunderstorms in the Southeast U.S. are Stronger Near Urban Areas" in Geophysical Research Letters by Paul Miller and Neil Debbage. The file contains the urban versus non-urban mean values for 31 cities in the Southeast US for the following variables: initiation time (decimal hours since 1200 UTC), duration (min), total lifetime thunderstorm pixels, maximum composite reflectivity (dBZ), maximum number of thunderstorm pixels during any single volume scan, maximum pixel ratio. T statistics and p values for the urban vs non-urban t-tests are also provided. More information can be found in the associated manuscript.

LES data presented in "The role of passive cloud volumes in the transition from shallow to deep atmospheric convection"

This repository contains the LES data presented in the manuscript entitled "The role of passive cloud volumes in the transition from shallow to deep atmospheric convection" by C.V. Vraciu, I.L. Kruse, J.O. Haerter, submitted to the Geophysical Research Letters.

Classification Of Large-Scale Environments That Drive The Formation Of Mesoscale Convective Systems Over Southern West Africa

This is a set of datasets used for the publication of the article titled: Classification Of Large-Scale Environments That Drive The Formation Of Mesoscale Convective Systems Over Southern West Africa

opencc-by-4.0Sep 2023View details →

Dataset for "On the sensitivity of aerosol-cloud interactions to changes in sea surface temperature in radiative-convective equilibrium"

Dataset for "On the sensitivity of aerosol-cloud interactions to changes in sea surface temperature in radiative-convective equilibrium". All numbers followed by "K" represent the sea surface temperature, and the number that follows them represents aerosol concentration. Abbreviations: prof - profile Adv - Advective CF245 - Cloud Fraction above 245K level  cF - cloud fraction cIce - cloud ice CSRH - Clear-sky Radiative heating rate cWtr - cloud water Lat - latent LW - longwave SW - shortwave TOA - top of atmosphere SFC - surface CS - clear sky Temp - temperature tW - total water