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182 results for “Tropical Cyclones”
Datasets for Analyzing Tropical Cyclone Impacts on Hydrological Extremes in the Mid-Atlantic Region
<p>The data sets provided here were used for the climatological analysis of tropical cyclone impacts on hydrological extremes in the Mid-Atlantic region of the United States. This research was published in <em><strong>Environmental Research Letters</strong></em> <a href="http://doi.org/10.1088/1748-9326/ac2d6a">https://doi.org/10.1088/1748-9326/ac2d6a</a>.</p> <p>The data sets include:</p> <ul> <li><strong>hurdat_data/</strong> <ul> <li><strong>hurdat2-1950-2019_rev.txt:</strong> 6-hourly entires of hurricane tracks for all events occurring in the Atlantic region. The first column HURID matches the first column in the hurdat2-1950-2019_seq.txt</li> <li><strong>hurdat2-1950-2019_seq.txt</strong>: <ul> <li>1st column: HURID</li> <li>2nd column: event ID. For example, AL092011 means: AL (Spaces 1 and 2) – Basin – Atlantic; 09 (Spaces 3 and 4) – ATCF cyclone number for that year; 2011 (Spaces 5-8, before the first comma) – Year; </li> <li>3r column: event Name, if available, or else “UNNAMED” </li> <li>4th column: number of best track entries</li> </ul> </li> </ul> </li> <li><strong>usgs_gage/</strong> <ul> <li><strong>Content:</strong> daily streamflow records from USGS gages over 10/01/1950-9/30/2019</li> <li><strong>Format</strong>: <ul> <li>1st column: timestamp</li> <li>2nd column: daily mean flow (in cfs)</li> </ul> </li> </ul> </li> <li><strong>usgs_gage_list</strong> <ul> <li><strong>Content</strong>: Summary of USGS gages used in the analysis</li> </ul> </li> <li><strong>livneh_ppt.mat</strong> <ul> <li><strong>Content</strong>: Summary of precipitation data used in the analysis in Matlab structure array. The array includes statistics derived from precipitation records for 2857 grid cells (1/16 degree resolution) covering the Mid-Atlantic region. </li> </ul> </li> </ul>
Southeast Asia Tropical cyclone landfall database
<p>This database includes four Tropical cyclone (TC) landfall datasets produced using the Regional Specialized Meteorological Center of Tokyo (TOKYO), China Meteorological Administration (CMA), Hong Kong Observatory (HKO), and Joint Typhoon Warning Center (JTWC) best track datasets. The database was used to investigate a 50-yr TC landfalling climatology in Southeast Asia (1970-2019). These datasets are at 30-min temporal and 0.25-degree spatial resolutions and stored in the Matlab ".m" file format.</p> <p>The column variable description of each dataset is as below.</p> <p>1) id: Tropical cyclone identifier</p> <p>2) name: Tropical cyclone name</p> <p>3) syear: Forming year</p> <p>4) obs: Time provided in Universal Time Coordinates (UTC). Format is YYYY-MM-DD_HH:mm:ss</p> <p>5) lat: Latitude</p> <p>6) lon: Longitude</p> <p>7) v: Maximum wind speed (converted to 1-min wind speed in case the dataset is CMA, HKO, TOKYO)</p> <p>8) hit_lat: Latitude of landfall</p> <p>9) hit_lon: Longitude of landfall</p> <p>10) hit_v: Intensity at landfall (defined by maximum wind speed converted to 1-min in case the dataset is CMA, HKO, TOKYO)</p> <p>11) v_orig: Maximum wind speed provided by an agency</p> <p>12) hit_v_orig: Intensity at landfall defined by maximum wind speed provided by an agency</p> <p>13) hit_obs: Time of landfall</p> <p>14) hit_times: Number of landfalls</p>
Uncertainties Inherent from Large-Scale Climate Projections in the Statistical Downscaling Projection of North Atlantic Tropical Cyclone Activity
Open the record for dataset details and reuse information.
Supporting data files for simulations in "Wind fields in Category 1-3 tropical cyclones are not fully represented in wind turbine design standards"
<p>This deposit contains the time-series output from the WRF-LES simulations of three tropical cyclones used in "Wind fields in Category 1-3 tropical cyclones are not fully represented in wind turbine design standards".</p>
Tropical Cyclone Secondary Eyewall Formation in Environmental Helicity
<p>original dataset</p>
DATA for Evaluating Scale-Aware Boundary Layer Similarity Functions and Their Mechanisms in Tropical Cyclone Modeling Using Idealized Large-Eddy Simulations
<p>data.xlsx has the data to make Figs.1-4</p> <p> </p>
Supplemental Material for the paper "Tropical Cyclones and Climate Change: Global Landfall Frequency Projections Derived from Knutson et al 2020"
<p>As described in the paper.</p> <p> </p>
Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone-driven Storm Tides and Inundation: Model Data and Analysis Code
<p>This repository contains model data and analysis codes related to the manuscript entitled "Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone-driven Storm Tides and Inundation", as follows:</p> <ol> <li>Model data are maximum water surface elevations of ensemble 48-hr forecast ADCIRC model simulations for three historical US landfalling hurricanes: 2017 Irma, 2018 Florence, and 2020 Laura. These are located in the "NameYYYY_Results.tar" archive files as "maxele.63.nc" files. Also included in the tar files are the hurricane forecast track files in Automated Tropical Cyclone Forecasting (ATCF) system format (*.22) and the error variable parameters (*.json) for each forecast. </li> <li>Model data of best-track runs for the 2017 Irma, 2018 Florence, and 2020 Laura hurricanes, and astronomical tide-only runs for the corresponding time periods are located in the "NameYYYY_besttrack+tides.tar" archive files. Both the maximum water surface elevations "maxele.63.nc" and the time series of water surface elevations "fort.63.nc" are included. </li> <li>ADCIRC input mesh (*.14) and mesh property files (*.13) are included in "ADCIRC_mesh_files.zip".</li> <li>Joint Karhunen-Loeve Polynomial Chaos (KL-PC) analysis python scripts with and without considering inundation are located in "klpc_analysis_scripts.zip". Requires <a href="https://github.com/noaa-ocs-modeling/EnsemblePerturbation">EnsemblePerturbation</a> python toolbox. </li> <li>Python scripts for analyzing and plotting the KL-PC results (Figures 6-14 and Table 1 in the manuscript) are located in "results_plotting_scripts.zip". Requires <a href="https://github.com/noaa-ocs-modeling/EnsemblePerturbation">EnsemblePerturbation</a> python toolbox. </li> </ol>
Tropical cyclone information during 2001-2020
<p>Tropical cyclone information during 2001-2020</p>
Open Research Data for "A New Framework for Evaluating Model Simulated Inland Tropical Cyclone Wind Fields"
<p>The (1) NOAA GFDL T-SHiELD outputs, (2) processed ASOS data, and (3) observation-based, theory-driven wind profiles data used in the manuscript "A New Framework for Evaluating Model Simulated Inland Tropical Cyclone Wind Fields". </p>
Key data used in "Western North Pacific tropical cyclone activity modulated by phytoplankton feedback under global warming" submitted to Nature Climate Change
<p>Key data</p>
TROPICS03 L2B Deep Multispectral INtensity (DMIN) of Tropical cyclones estimator Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
TROPICS06 L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) and one channel from the moisture sounding channel (Ch. 1) along with ancillary information from the TC working best track file and the CIMSS ARCHER algorithm (eye size information) to estimate the TC intensity. This validated TCIE data release starts in June 2023 for the constellation CubeSats, and August 2021 for the TROPICS-01/Pathfinder.
TROPICS01 L2B Deep Multispectral INtensity (DMIN) of Tropical Cyclones Estimator Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
TROPICS05 L2B Deep Multispectral INtensity (DMIN) of Tropical Cyclones Estimator Algorithm V0.2
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
TROPICS01 Pathfinder L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) and one channel from the moisture sounding channel (Ch. 1) along with ancillary information from the TC working best track file and the CIMSS ARCHER algorithm (eye size information) to estimate the TC intensity. This validated TCIE data release starts in June 2023 for the constellation CubeSats, and August 2021 for the TROPICS-01/Pathfinder.
Tropical Cyclone Intensity (TCI) Hurricane Imaging Radiometer (HIRAD) V2.1
The Tropical Cyclone Intensity (TCI) Hurricane Imaging Radiometer (HIRAD) dataset was created for the TCI field campaign from August 30, 2015 through October 23, 2015. The goal of the TCI field campaign was to improve the prediction of tropical cyclone (TC) intensity and structure change. The specific focus was to have an improved understanding of TC upper-level outflow layer processes and dynamics. These Hurricane Imaging Radiometer (HIRAD) data were obtained from the instrument onboard the NASA WB-57 aircraft flow on specific dates during the campaign. The data files include brightness temperature, rain rate, wind speed, and sea surface temperature estimates in netCDF-3 format, with corresponding browse imagery in PNG format.
TROPICS06 L2B Deep Multispectral INtensity (DMIN) of Tropical Cyclones Estimator Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The Deep Multispectral INtensity of TCs estimator with 183 GHz brightness temperatures (D-MINT183), developed at the University of Wisconsin/CIMSS, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). D-MINT183 is a convolutional neural network (CNN) with no inherent physical understanding of TC intensity relationships, which is an approach that differs from the other two TROPICS TC Intensity algorithm (i.e., TCIE and HISA). D-MINT183 is trained using combinations of 183±1 and 183±3 GHz imagery from SSMIS, ATMS, MHS, and AMSU-B, as well as 15 hours of infrared imagery (in 3-h increments) and scalar predictors. TROPICS has 184.41 GHz and 186.51 GHz imagery, which is used as a proxy for the 183±1 GHz and 183±3 GHz imagery.
TROPICS07 L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) and one channel from the moisture sounding channel (Ch. 1) along with ancillary information from the TC working best track file and the CIMSS ARCHER algorithm (eye size information) to estimate the TC intensity. This validated TCIE data release starts in June 2023 for the constellation CubeSats, and August 2021 for the TROPICS-01/Pathfinder.
TROPICS05 L2B Tropical Cyclone Intensity Estimate (TCIE) Algorithm V1.0
The "Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.The TROPICS Tropical Cyclone Intensity Estimate algorithm (TCIE), developed at the University of Wisconsin/CIMSS that uses native microwave brightness temperatures, estimates two primary TC variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). The TROPICS TCIE uses the brightness temperature perturbation of two temperature sounding channels (Ch. 6 and Ch. 7) and one channel from the moisture sounding channel (Ch. 1) along with ancillary information from the TC working best track file and the CIMSS ARCHER algorithm (eye size information) to estimate the TC intensity. This validated TCIE data release starts in June 2023 for the constellation CubeSats, and August 2021 for the TROPICS-01/Pathfinder.
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