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Regeneration after Hurricane Hugo woody species greater than 1cm tall (9ha grid, El Verde)(Wood fall from Hurricane Hugo 9Ha Grid)

The purpose of this data set is to document vegetation damage and recovery following Hurricane Hugo, a borderline category 3-4 hurricane with winds from 130 to 160mph (110kts) and a pressure of 945 to 946.1 mb, which hit Puerto Rico in September 18th, 1989. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

Regeneration after Hurricane Hugo woody species > 1m tall and below 3m: percent cover (9 ha grid, El Verde)

Purpose was to document vegetation damage and recovery following Hurricane Hugo. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

Tree damage by Hurricane Hugo on the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico

Hurricane Hugo struck the Caribbean national forest in September 1989. Files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT contain data on the damage to trees caused by the hurricane collected by Mr. R. DeLeon between August 1990 and September 1991. Mr. DeLeon walked throughout the plot to find stems >= 10 cm diameter that had apparently been damaged or killed by the hurricane in an effort to collect information before the damaged stems rotted. The information on these stems was later combined with the results of the first census to reconstruct the forest, as it would have appeared, at the time of Hurricane Hugo. This file contains the hurricane damage data collected for stems damaged by Hurricane Hugo combined with data for the stems recorded subsequently in the first complete LFDP census starting in 1990. Some stems that were measured in Census 1 survey 2 and survey 3 or Census 2 that were believed to have been missed in Census 1 survey 1, are also included (see census history above) and are assumed to have been undamaged by Hurricane Hugo. The structure of the data files is the same for both files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT but the diameter of the trees in LFDP_HURRDAMa.TXT have been calculated by extrapolating diameters backwards from subsequent measurements to the time of the Census 1 survey 1. Diameters in file LFDP_HURRDAMa.TXT can not be used for growth measurements. For our publications we treat files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT as one data set. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these d

Litter decomposition of the tabonuco forest before hurricane Hugo

We examined forest structure, tree species composition, litterfall rate, and leaf litter decomposition in a mid-successional forest (MSF) and an adjacent mature tabonuco forest (MTF) in the Luquillo Experimental Forest of Puerto Rico. Whereas the MTF site received limited human disturbance, the MSF site had been cleared for timber production by the beginning of this century and was abandoned after hurricanes struck the Luquillo Mountains in the 1920s and 1930s. We found that the MSF was dominated by successional tree species 50 yrs after secondary succession, and did not differ in tree basal area and litterfall rate from the MTF. Leaf decomposition rate in the MSF was higher than in the MTF, but this difference was small. Our results show that deforestation has long-term (>50 years) influence on tree species composition and that leaf decomposition processes in secondary forest is relatively faster than recovery of tree species composition. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

Litterfall of the tabonuco forest before Hurricane Hugo

We examined forest structure, tree species composition, litterfall rate, and leaf litter decomposition in a mid-successional forest (MSF) and an adjacent mature tabonuco forest (MTF) in the Luquillo Experimental Forest of Puerto Rico. Whereas the MTF site received limited human disturbance, the MSF site had been cleared for timber production by the beginning of this century and was abandoned after hurricanes struck the Luquillo Mountains in the 1920s and 1930s. We found that the MSF was dominated by successional tree species 50 yrs after secondary succession, and did not differ in tree basal area and litterfall rate from the MTF. Leaf decomposition rate in the MSF was higher than in the MTF, but this difference was small. Our results show that deforestation has long-term (> 50 years) influence on tree species composition and that leaf decomposition processes in secondary forest is relatively faster than recovery of tree species composition. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

opencc-by-4.0Feb 2012View details →

The Hurricane Challenge Dataset

The Hurricane Challenge was an international evaluation of intelligibility-enhancing speech modifications that took place in 2013 at Interspeech. The dataset consists of stereo files containing clean speech (channel 1) and noise (channel 2). The purpose of the Challenge is to modify the clean speech only in order to make it more intelligibility in the presence of the corresponding noise sample, without changing root-mean-square level, and within certain constraints on changes in duration. Two different types of noise, stationary speech-shaped noise, and competing speech, are provided, each at three signal-to-noise ratios. The Challenge is described in this <a href="https://www.isca-speech.org/archive/archive_papers/interspeech_2013/i13_3552.pdf">Interspeech article</a>.   The dataset consists of two zip files, one for each masker (cs.zip for competing speech, ssn.zip for speech-shaped noise).

opencc-by-4.0Jan 2022View details →

High resolution soil moisture and soil temperature data during Hurricane Florence, 2018, over the Carolina region (U.S.)

We set the study domain over the U.S. east coast to cover the Carolinas and the regions that were affected by Hurricane Florence. Therefore, the selected domain covered the area between -86º to -75º longitude and 30º to 40º latitude. We should note that Hurricane Florence made landfall in the Carolinas on September 14, 2018, as a Category 1 storm.  Hurricane reports indicate that “Hurricane Florence made landfall near Wrightsville Beach, North Carolina at 7:15 AM EDT (1115 UTC) on September 14 with estimated maximum winds of 90 mph (150 km/h), and a minimum central pressure estimate of 958 millibars. Winds gusts topping 105 mph (169 km/h) were reported in the Outer Banks of North Carolina.” Rainfall from Florence, as per the initial reports, suggest possible new records for North Carolina (breaking the record set by Hurricane Floyd in 1999). we used the latest development of the high-resolution land surface assimilation system (HRLDAS) that was retrieved from the Github repository (<a href="https://github.com/NCAR/hrldas-release">https://github.com/NCAR/hrldas-release</a>). The model was coupled to the Noah land surface modeling system and used the multi-layer soil model, complex canopy resistance with the Penman method for calculating evapotranspiration, and frozen ground physics for the simulations.  The atmospheric forcing including 2-meter air temperature, shortwave, and long-wave radiation, 2-meter wind speed, 2-meter specific humidity, and surface pressure data was obtained from the NCEP-DOE Reanalysis 2 (available from <a href="https://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html">psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html</a>). For the precipitation, we used the high-resolution GCIP/EOP surface precipitation NCEP/EMC gridded data (Stage IV) with 4 km of grid spacing. All the forcing data have been retrieved at an hourly frequency from 2016 to 2019. The model was configured with the initial soil moisture and soil temperature conditions at 4 depths (0-10, 10-40, 40-100, 100-200 cm), retrieved from the NCEP data. Other initialization fields including skin temperature and water equivalent snow depth were retrieved from NCEP. The NCEP reanalysis data, however, does not provide “plant canopy surface water” data which is required as an initialization field. This data was retrieved from the NLDAS dataset. The first two years of the model run (2016 and 2017) were considered as the spin-up, and the outcome during 2018 was used for further analysis and public release.

opencc-by-4.0Jul 2022View details →

GFDL hurricane model track data associated with "Dynamical downscaling projections of late 21st century U.S. landfalling hurricane activity"

These data include North Atlantic tropical cyclone track and intensity for control and projected late 21st century simulation from the GFDL hurricane model used in a Climatic Change manuscript:  Knutson, T., J. Sirutis, M. Bender, R. Tuleya, and B. Schenkel, 2022: Dynamical downscaling projections of late 21st century U.S. landfalling hurricane activity. Clim. Change, 171, 1–23. A readme file included below describes the variables and format of the tropical cyclone track data.  Questions about the dataset may be directed to Ben Schenkel (<a href="mailto:benschenkel@gmail.com">benschenkel@gmail.com</a>) and Tom Knutson (<a href="mailto:tom.knutson@noaa.gov">tom.knutson@noaa.gov</a>).

opencc-by-4.0Sep 2022View details →

Economic losses from hurricanes cannot be nationally offset under unabated warming - Data Supplement

This data set includes the raw data for the figures of the article "Economic losses from hurricanes cannot be nationally offset under unabated warming".

opencc-by-4.0Jul 2024View details →

Electric power outages from 900k simulated hurricanes in a changing climate, for the United States and Puerto Rico

This dataset is described and explored in Rice et al. 2025, "<a href="https://doi.org/10.1088/1748-9326/adad85">Projected Increases in Tropical Cyclone-induced U.S. Electric Power Outage Risk</a>", published in Environmental Research Letters. This dataset collects peak outage levels modeled for 900,000 synthetic tropical cyclones (TCs; also commonly known as hurricanes) representative of a modeled historical (1980-2015) and future (2066-2100) period under SSP5-8.5 warming. Synthetic TCs are generated with the Risk Analysis Framework for Tropical Cyclones (RAFT; see Xu et al. 2024 and Balaguru et al. 2023), forced by climate simulation data from the Coupled Model Intercomparison Project phase 6 (CMIP6; see Eyring et al. 2016). Outages are modeled with the newly introduced Electric Power Outages from Cyclone Hazards (EPOCH) model, which was trained on county-level outage data from 23 historical TC events in the EAGLE-I dataset (Brelsford et al. 2024).  The EPOCH model predicts outages based on county population and the maximum wind speed and rainfall rate experienced during the TC. Predicted outage levels are provided in the form of peak outage fraction: the maximum fraction of electricity customers expected to experience an outage at any one time during the storm's lifetime. Although we do not model outage duration, other research suggests peak outage level is strongly correlated with duration (Jamal and Hasan, 2023). Data Format The data is provided in NetCDF4 files, one for each CMIP6 model and time period. Each NetCDF4 files has the following: Dimensions: <ul> <li>ncounties = 2715. The counties in the study domain</li> <li>ntracks = 50000. The number of storms</li> </ul> Variables: <ul> <li>int pseudofips(ncounties). The FIPS code for each county. Puerto Rico data is not available at county level, but instead for six utility-defined regions. We assign "pseudo-FIPS" codes to these region starting at 100000</li> <li>double centroid_lons(ncounties). Longitude of approximate center of county, in the range [-180, 0].</li> <li>double centroid_lats(ncounties). Latitude of approximate center of county, in the range [0, 90].</li> <li>float outage_prediction(ntracks, ncounties). The predicted peak outage fraction for each county, for each storm. Due to the particularities of ensemble models, some predictions may be slightly below zero or above one; we clip these values to the range [0,1] before any analysis in our study.</li> <li>ubyte prediction_complete_flag(ntracks). A verification flag used during dataset generation. This flag should equal 1 everywhere for complete data.</li> </ul> Each file also contains the raw predictors at a county level for every storm, inside the 'predictors' group, for feature analysis. Also provided for convenience is 'counties_pseudofips.csv', which maps the pseudo-FIPS codes to the the name and spatial extent (WKT format) of each county. It can be read easily by Python GeoPandas, or other software.

opencc-by-4.0Apr 2018View details →

Hernando County Mosquito Control District entomological monitoring Hurricane Irma

Mosquito surveillance from the Hernando County Mosquito Control District Vector Surveillance program to survey mosquito populations in the immediate aftermath of Hurricane Irma, 2017.

opencc-by-4.0Aug 2024View details →

Core log descriptions and sediment grain size data for Hurricane Ian sediment cores collected in Lee County, Florida, USA

These data represent qualitative and quantitative measurements of sediment cores collected from various environments following the landfall of Hurricane Ian. These sediment cores were collected using pound coring techniques up to 2m into the subsurface to characterize the sedimentological signature of storm deposits resulting from Hurricane Ian. More details regarding these measurements and interpretations of storm deposits can be found in the folllowing manuscript: McCormick, W.M., Briggs, T.R., Hauptman, L.H., Wang, P., Morphologic and sedimentological signatures resulting from Hurricane Ian, southwest Florida, USA: Insight into intra-storm bidirectional sediment transport processes (In Review).

opencc-by-4.0Aug 2024View details →

Two-wave Post-Disaster Survey on Climate Change Attitudes: Texas after Hurricane Harvey and the 2021 North American Winter Storms

Overview This repository contains data needed to reproduce the analysis results from Chen et al. 2024. "Disaster Experience Mitigates the Partisan Divide on Climate Change: Evidence from Texas," Global Environmental Change. It is a study about climate change attitudes and experience with climate disasters across U.S. partisan groups. For details about the data, please see the published paper. Results reproduction code is available at <a href="https://github.com/tedhchen/floodStorm" target="_blank" rel="noopener">https://github.com/tedhchen/floodStorm</a>.   Data Set Details `texas_climate_attitudes.csv` contains data from two waves of surveys of Democrats and Republicans living in Texas, with the following groups of variables. <ul> <li>climate change attitudes</li> <li>self-reported exposure to climate disasters</li> <li>scientific information treatment condition and checks</li> <li>political leaning</li> <li>sociodemographics and residential location</li> <li>survey administration details</li> </ul> `outage2021_data.RData` contains power outage data for counties and cities in Texas during Feb. 2020 and Feb. 2021. `outage2021_data_multithreshold.RData` contains power outage data for counties and cities in Texas during Feb. 2020 and Feb. 2021, aggregated to the county level based on different thresholds of uncertainty about which cities people live in. `gtrends_archive.RData` contains Google Trends data for "hurricane", "astros", and "power", in Texas between 2017 and 2021.   References Please reference the original study when using this data set. Ted Hsuan Yun Chen, Christopher J. Fariss, Hwayong Shin, Xu Xu. 2024. "Disaster Experience Mitigates the Partisan Divide on Climate Change: Evidence from Texas." Global Environmental Change. <a href="https://doi.org/10.1016/j.gloenvcha.2024.102918" target="_blank" rel="noopener">doi:10.1016/j.gloenvcha.2024.102918</a>.

opencc-by-4.0Nov 2022View details →

Segmentation Labels for Emergency Response Imagery from Hurricane Barry, Delta, Dorian, Florence, Isaias, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon

The zip file here contains 1,179 pairs of human-generated segmentation labels and images from Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Barry, Delta, Dorian, Florence, Ida, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon. A total of 1,054 unique images were labeled. 946 images were annotated by a single labeler. 95 images were annotated by two labelers. 11 images were annotated by three labelers. 2 images were annotated by five labelers. All authors contributed to labeling, and all labeling was done with an open-source labeling tool (Buscombe et al., 2022). All pixels in each image are labeled with one of four classes: 0 (water), 1 (bare sand), 2 (vegetation - both sparse and dense), 4 (the built environment - buildings, roads, parking lots, boats, etc.) The csv file provided here is a list of each image file name (which includes the anonymized labeler ID), the name of the image without the labeler ID, the name of the corresponding NOAA jpg, the NOAA flight name, the storm name, the latitude and longitude of the image, and a column stating if the image has been labeled multiple times.  Images labeled here correspond to multiple NOAA flights — all listed in the csv file for each jpeg image. These jpeg images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). The images included in this data release correspond to original NOAA images that have been resized and then split into quadrants (using ImageMagick). The naming convention corresponds to the image quarter — the *-0.jpg is upper left, *-1.jpg is upper right, *-2.jpg is lower left, and *-3.jpg is the lower right. The resize command used was: #to resize and then quarter #Dir structure is: # --Desktop #    |- originals #    |- resized #    |- quarters `cd originals` `mogrify -resize 2000x2000 -path ../resized *.jpg` #then quarter them `cd ..` `cd resized` `mogrify -crop 2x2@ +repage -path ../quarters *.jpg` For full size images, please download the jpegs directly from NOAA.

opencc-by-4.0Sep 2021View details →

High resolution WRF simulation of Hurricane Florence (2018) and Harvey (2017) during Landfall

A high-resolution simulation of Hurricane Florence (2018) and Harvey (2017) is performed using the Weather Research and Forecasting (WRF) model version 4.3. The WRF model was configured by three nested domains with a horizontal grid spacing of 12, 4, and 1.33 km, respectively, and 60 vertical levels.  The common physics options used in the simulations are the Thompson microphysics scheme (Thompson et al., 2008); RRTMG as shortwave and long-wave schemes (Iacono et al., 2008); Mellor–Yamada–Janjic Scheme as Planetary Boundary Layer (Janjic, 1994;Mesinger, 1993); Unified Noah land surface model (Tewari et al., 2004); Tiedtke Scheme (Tiedtke, 1989; Zhang et al., 2011) as cumulus parameterization scheme only for the first domain. The simulations were performed considering (a) a control experiment with an urban slab model (NUCM), (b) a single-layer UCM, and (c) multi-layer BEP urban physics (BEP). All other physics schemes remain the same for the simulations. The simulations for Hurricane Florence start on 2018-09-12 at 12:00 UTC and end on 2018-09-18 at 00:00 UTC, and for Hurricane Harvey simulations start on 2017-08-24 at 12:00:00 UTC and end on 2017-08-29 at 00:00:00 UTC. The data herein presents the model output of 3-hour for domain one and 1-hour for domain three. The format is NetCDF, containing detailed metadata. Three-dimensional meteorological field variables include three wind components (u, v, and w), potential temperature, water vapour mixing ratio, and atmospheric pressure. Two-dimensional variables include horizontal wind components at 10 m AGL, potential temperature and water vapour mixing ratio at 2 m AGL, atmospheric pressure at the surface, terrain height, planetary boundary layer height, total accumulated rainfall, latent heat flux, sensible heat flux, and the Coriolis sine latitude term. The outputs are provided for NUCM, UCM and BEP simulations.

openCC0Dec 2021View details →

A hurricane alters the relationship between mangrove cover and marine subsidies in Texas, USA: 2014-2019

We experimentally manipulated black mangrove (Avicennia germinans) cover in ten large plots and over five years (2014-2019) quantified the effects of mangrove cover on subsidies of floating organic material (wrack) into coastal wetlands. We hypothesized that the change from salt marsh to mangrove vegetation would alter the permeability of the intertidal habitat, and thus alter the nature of subsidies from marine to intertidal habitats. Data from field surveys of wrack distribution showed that as mangrove cover increased from zero to 100%, wrack cover and thickness decreased by ~60%, the distance that wrack penetrated into the plots decreased by ~70%, and the percentage of the wrack trapped in the first six m of the plot tripled. Data from wrack samples indicated that wrack samples collected from the fringe were ~3 times heavier than those from the interior of plots. Animals were ~40% more abundant in samples from the interior than from the fringe of plots, but this trend was not statistically significant due to low replication of interior samples. Data from a wrack experiment revealed that animal abundance and species composition varied between the fringe and interior of the plots, and between microhabitats dominated by salt marsh versus mangrove vegetation. Increasing mangrove cover decreased the relative importance of marine subsidies into the intertidal at the plot level, but concentrated subsidies at the front edge of the mangrove stand. Storms, however, may temporarily override mangrove attenuation of wrack inputs.

openCustomFeb 2023View details →

Pre- and Post- Hurricane Maria Dry Soil Collection (GUAN, LAJA) (repackaging of occurrences published by the NEON Biorepository Data Portal)

These samples from Soil Collection (Distributed Periodic) (NEON-SOIC-DP) were collected at NEON GUAN and LAJA sites in Puerto Rico before (July and November 2017) and after (July 2018) Hurricane Maria, a Category 5 storm that affected the Carribean and occurred September 16, 2017 – October 2, 2017.

openCustomJan 2020View details →

Effects of Hurricane Opal on foliar chemistry and insect herbivores at the Coweeta Hydrologic Laboratory in 1997: foliar chemistry data

Hurricane damage results in tree mortality and variation in both light and nutrient availability for the individuals that remain. In turn, resource availability influences the interactions between plants and insect herbivores. We report effects of Hurricane Opal on the phenolic chemistry and levels of defoliation on surviving trees at the Coweeta Hydrologic Laboratory in North Carolina. We measured foliar astringency, hydrolysable tannins, and condensed tannins in the foliage of red maple and red oak saplings in hurricane damaged and undamaged sites. We estimated inorganic nitrogen and phosphorus availability in the soil, and the accumulated leaf area removed by insect herbivores. The foliar astringency of both red maple and red oak was higher in sites damaged by the hurricane. Later in the growing season, condensed tannin levels were significantly higher in the foliage of red oak in damaged sites. There were no consistent differences in ammonium, nitrate, or phosphate availability between damaged and undamaged sites. Despite higher foliar astringency of trees in sites damaged by Hurricane Opal, levels of defoliation by insect herbivores were higher in damaged than in control sites on both tree species. Apparent increases in putative defensive compounds following hurricane damage did not protect trees from herbivory.

openCC (other)Jul 2025View details →

Patterns of root biomass, productivity, and turnover in riverine and scrub mangroves post-Hurricane Wilma in the Everglades, Florida, USA, 2012-2013

Mangrove root biomass, productivity, and turnover in the shallow (0-45 cm depth) root zone were estimated at Florida Coastal Everglades Long Term Ecological Research (FCE-LTER) Program Shark River (SRS4, SRS5, SRS6) and Taylor River (TS/Ph6b, TS/Ph7b) mangrove sites during 2012-2013 following Hurricane Wilma’s impacts in October 2005. Root biomass was estimated at all sites in May 2012 with a PVC coring device (10.2 cm diameter x 45 cm length) using the same sampling protocol previously published for the study area (Castañeda-Moya et al. 2011). After collection, root cores were processed individually and initially rinsed with water through a 1-mm screen mesh to remove soil particles. Live roots were separated manually based on their buoyancy, turgor, and color (Castañeda-Moya et al. 2011; Cormier et al. 2015; Medina-Calderon et al. 2021). Live roots were further sorted into three size diameter classes including fine (<2 mm), small (2-5 mm), and coarse (5-20 mm). Roots greater than 20 mm in diameter were not included in this study due to sampling limitations (i.e., core area). All root samples were oven-dried at 60°C to a constant mass and weighed to estimate root biomass (g m-2). Root productivity was estimated with the ingrowth core technique (Vogt et al., 1998) using the same sampling protocol previously published for the study area (Castañeda-Moya et al. 2011). Ingrowth cores (10.2 cm diameter x 45 cm length) were made of synthetic material (3 mm mesh) and filled with root-free commercial sphagnum peat moss. This material has similar soil properties (i.e., bulk density, organic matter content, total C and N) as mangrove peat in our study sites. Ingrowth cores were installed in each of the cored holes formed during sampling of root biomass. At each site, ingrowth cores were deployed vertically into the soil to a depth of 45 cm and retrieved one year later (June 2013). Root growth within the ingrowth core was used to estimate annual root production (g m-2 yr-1) in