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17 results for “Mesoscale Convection”
Moisture-Precipitation Couplings for Mesoscale Convective Systems in Tracking Data and Idealized Simulations
<p>Morphological properties, collocated synoptic conditions, and collocated rainfall for mesoscale convective systems in 1) the ISCCP Convective Tracking (CT) dataset with coincident data from the ERA-Interim (ERA-I) reanalysis and the Multi-Source Weighted-Ensemble Precipitation (MSWEP) product and 2) long-channel radiative-convective equilibrium (RCE) simulations in the System for Atmospheric Modeling (SAM).</p> <p><strong>ISCCP_tracking_colloc.tar.gz </strong>- NetCDF files by year from 2000 to 2004 inclusive including ISCCP-CT morphological properties of MCSs, a series of collocated synoptic variables from ERA-5 (including specific humidity, temperature, vertical velocity, and cloud condensate profiles), and collocated precipitation intensity and accumulation from MSWEP.</p> <p><strong>RCE_colloc_execution1.tar.gz</strong> - NetCDF files including RCE-SAM extent of MCSs (RCE_COL_cluster-sizes_*.nc), as well as collocated synoptic variables. Collocation of synoptic variables is performed for these files by extracting and averaging the variables over grid cells where the precipitation is greater than either its mean (RCE_COL_MEAN_*.nc) or its 99th percentile (RCE_COL_99_*.nc).</p> <p><strong>RCE_colloc_execution2.tar.gz</strong> - NetCDF files including RCE-SAM extent of MCSs (RCE_COL_cluster-sizes_*.nc), as well as collocated synoptic variables. Collocation of synoptic variables is performed for these files by taking either the mean (RCE_COL_MEAN_*.nc) or the 99th percentile (RCE_COL_99_*.nc) value over all grid cells within the MCS.<br><br>For the NetCDF files from RCE output, the numeric value in the file name is the corresponding sea surface temperature from 280 to 310 K.</p>
Rain gauge data used in the study "Characteristics of Precipitation and Mesoscale Convective Systems over the Peruvian Central Andes in Multi 5-Year Convection-Permitting Simulations"
<p>The rain gauge data in Peru and Brazil used in the study,</p> <p>Yongjie Huang, Ming Xue, Xiao-Ming Hu, et al. Characteristics of Precipitation and Mesoscale Convective Systems over the Peruvian Central Andes in Multi 5-Year Convection-Permitting Simulations. <em>ESS Open Archive .</em> November 14, 2023.<br><span>DOI: <a href="https://doi.org/10.22541/essoar.170000370.07634797/v1" target="_blank" rel="noopener noreferrer">10.22541/essoar.170000370.07634797/v1</a></span></p> <p><span>The original data source:</span></p> <ul> <li>The rain gauge data in Peru are available at <a href="https://piscoprec.github.io/webPISCO/en/raingauges">https://piscoprec.github.io/webPISCO/en/raingauges</a> (last access: 18 July 2021).</li> <li>The rain gauge data in Brazil are available at <a href="https://bdmep.inmet.gov.br">https://bdmep.inmet.gov.br</a> (last access: 19 January 2023).</li> </ul>
Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia: companion dataset
<p>This folder includes the intermediate data for the following manuscript:</p><p>Ding et al., Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia</p><p>The simulations were done using ICON-NWP (ICON Numerical Weather Prediction) model, version 2.6.1, over Asian monsoon region (62E–150E, 5.5N–54.5N) for 2020 summer. At the moment, we upload the intermediate data for MCS tracking. For more data, please contact the authors.</p>
Flash propagation and inferred charge structure relative to radar-observed ice alignment signatures in a small Florida Mesoscale Convective System
<p>Data for paper of above title, submitted to <em>Geophysical Research Letters</em>, June 2017. Manuscript number: 2017GL072767</p>
Evaluation of Mesoscale Convective Systems in High Resolution E3SMv2
<p>This is the open data resource for the paper "Mesoscale Convective Systems Represented in High Resolution E3SMv2 and Impact of New Cloud and Convection Parameterizations" that submitted to the Journal of Geophysical Research: Atmospheres. </p>
Post-processed SAM (System for Atmospheric Modeling) simulation output for "Tipping to an Aggregated State by Mesoscale Convective Systems"
<p>Statistics output files for all variables, for a select number of SAM (System for Atmospheric Modeling v. 6.11) simulation runs used in the study "Tipping to an Aggregated State by Mesoscale Convective Systems". The following simulations are included: DIU, OCEAN, DIU2OCEAN branch A1, DIU2OCEAN branch A2.</p>
On the cell broadening of mesoscale cellular convection in a well-mixed boundary layer
Open the record for dataset details and reuse information.
Targeted Balloon Observations of Stratosphere-to-Troposphere Transport From a Mesoscale Convective System
<p>Data used for analysis in the JGR-Atmospheres Paper Targeted Balloon Observations of Stratosphere-to-Troposphere Transport From a Mesoscale Convective System. Files include ozonesonde data, gridded radar data, and backward trajectory calculations. </p>
Classification Of Large-Scale Environments That Drive The Formation Of Mesoscale Convective Systems Over Southern West Africa
<p>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</p>
Supporting data for "Shallow convective heating in weak temperature gradient balance explains mesoscale vertical motions in the trades" (previously for ch. 5 of "Mesoscale Cloud Patterns in the Trade-Wind Boundary Layer")
<p>This contains both the data and scripts required to produce the figures in the preprint "Shallow convective heating in weak temperature gradient balance explains mesoscale vertical motions in the trades". The scripts labeled 1-5 produce the main figures; the other scripts produce supporting data or figures.</p> <p>Earlier versions of this dataset contained the scripts and data supporting Ch. 5 of the PhD thesis "Mesoscale Cloud Patterns in the Trade-Wind Boundary Layer". The scripts labeled 1-5 produce the main figures; the other scripts produce either the underlying data, or supporting figures (prefix S). </p>
Data Supporting "Mesoscale Convective Clustering Enhances Tropical Precipitation"
<p>These data are in support of "Mesoscale Convective Clustering Enhances Tropical Precipitation" by P. Angulo-Umana and D. Kim. </p> <p>In the tropics, extreme precipitation events are often caused by mesoscale systems of organized, spatially clustered deep cumulonimbi, posing a substantial risk to life and property. While the clustering of convective clouds has been thought to strengthen precipitation intensity, no quantitative estimates of this hypothesized enhancement exist. In this study, after isolating the effects of mesoscale convective clustering on precipitation, we find that strongly clustered convection precipitates more intensely than weakly clustered convection. We further show that this enhancement is primarily attributable to an increase in convective precipitation intensity when the environment is less than 70% saturated, with increases in stratiform cloud cover being of equal or greater importance when the environment is closer to saturation. Our results suggest that a correct representation of mesoscale organized convective systems in numerical weather and climate models is needed for accurate predictions of extreme precipitation events.</p>
Summer mesoscale convective systems in convection-permitting simulation using WRF over East China
<p>Mesoscale convective systems (MCSs) are active in East China during the summer, causing significant precipitation and extreme weather. Increasing MCS frequency and intensity highlight the need for better simulation and forecasting. Traditional global and regional models with coarse resolution unable to explicitly resolve convection fail to represent MCSs and their precipitation accurately. This study conducted a 22-year (2000--2021) JJA simulation at a convection-permitting resolution (4km) using the WRF model (WRF-CPM) over East China. The data generated and the code used to analyze are uploaded here.</p>
Data and script for "Characterizing Wet Season Precipitation in the Central Amazon Using a Mesoscale Convective System Tracking Algorithm"
<p>This is a placeholder for Data and script for "<strong>Characterizing Wet Season Precipitation in the Central Amazon Using a Mesoscale Convective System Tracking Algorithm</strong>" submitted to JGR-atmosphere.</p>
Active Regions of Secondary Ice Production in a Modeled Tropical Mesoscale Convective System
<p>The animations of the modeled tropical mesoscale convective system (MCS). The red regions indicate the cloud regions with the secondary ice production rate dNice/dt >10<sup>5</sup> m<sup>-3</sup> s<sup>-1</sup>. The numerical simulation of the MCS was performed with the help of the Environment and Climate Change Canada's (ECCC) Global Environmental Multiscale (GEM) model.</p> <p>For details see Korolev, A., Z. Qu, J. Milbrandt, I. Heckman, M. Cholette, M. Wolde, C. Nguyen, G. M. McFarquhar, P. Lawson, and A. M. Fridlind: High ice water content in tropical mesoscale convective systems (a conceptual model). Atmos. Chem. Phys., 2024.</p>
E3SM output for tracking mesoscale convection systems in the US
<p>E3SMv1 output for tracking mesoscale convection systems in the US.</p>
Impact of Convective Parameterizations on Atmospheric Mesoscale Kinetic Energy Spectra in Global High-resolution Simulations
Open the record for dataset details and reuse information.
Modeling the Impact of Secondary Ice Production on the Charge Structure of a Mesoscale Convective System: Dataset
<p>radar reflectivity image</p>
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