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33 results for “precipitation event”
Dataset and plot generation script for article "Probabilistic short-range forecasts of high precipitation events : optimal decision thresholds and predictability limits" by Francois Bouttier and Hugo Marchal, submitted in Dec 2023.
<p>Dataset and plot generation script for article "Probabilistic short-range forecasts of high precipitation events : optimal decision thresholds and predictability limits" by Francois Bouttier and Hugo Marchal, submitted in NHESS journal in Dec 2023.</p> <p>For further technical details read the file READMEdata in the zipfile. The script MAKEFIG remakes all the figures from the data.</p> <p>For scientific details read the associated article preprint on the NHESS egusphere website.</p>
Elevated increase in compound extreme heat-precipitation events over China
<p>This file contains the fractions (in percentage) of the compound extreme precipitation events that are preceded by an extreme heat event in China during 1961-2017. The compound events are identified based on the CN05.1 dataset at 0.5x0.5 resolution. Please contact us with any questions or concerns (email: luo.ming@hotmail.com).</p>
Attribution of 2022 August Heavy Precipitation Event in South Korea Using High-resolution Pseudo Global Warming Simulations: Sensitivity to Vertical Temperature Changes
<p>Post-processed CPM simulation datasets used for the paper "Attribution of 2022 August Heavy Precipitation Event in South Korea Using High-resolution Pseudo Global Warming Simulations: Sensitivity to Vertical Temperature Changes".</p>
Processed data for the manuscript, entitled "Substantial increase in heavy precipitation events preceded by moist heatwaves over China during 1961–2019"
<p>This is the dataset on annual frequency of heatwaves, heavy precipitation, and heatwave-heavy precipitation events during 1961-2019 at 1776 stations across China. This dataset is the processed results based on daily observations that are provided by the National Meteorological Science Data Center (<a href="http://data.cma.cn/en">http://data.cma.cn/en</a>). In this processed dataset, the "HW_HI" column is the annual frequency of heat-index-based heatwaves; "HW_TW" column is the annual frequency of wet-bulb temperature based heatwaves; "HP" is the annual frequency of heavy precipitation with taking the 95<sup>th</sup> percentile of non-zero precipitation at the threshold. "HWHP_HI"/"HWHP_TW" column indicate annual frequency of heavy precipitation preceded by HW_HI/HW_TW. All the results shown in the manuscript entitled "<strong>Substantial increase in heavy precipitation events preceded by moist heatwaves over China during 1961</strong>–<strong>2019</strong>", are obtained based on this processed dataset.</p>
Marcell Experimental Forest event based precipitation chemistry, 2008 - ongoing
This data set reports the event-based chemistry of precipitation water that was collected at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota. The data come from sites in two research catchments instrumented for hydrologic monitoring - the meteorological station located in an upland clearing in the S2 research catchment and the S1 bog as part of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment. Sample collection and analyses started during June of 2008 at the S2 site and is ongoing. Sample collection and analyses started during December of 2013 at the SPRUCE S1 sites and will continue for the duration of the experiment. The MEF is operated and maintained by the USDA Forest Service, Northern Research Station. The SPRUCE experiment is a multi-year cooperative project among scientists of the Oak Ridge National Laboratory operated by UT-Battelle, LLC and the USDA Forest Service, Northern Research Station. The SPRUCE experiment is funded by the US Department of Energy, Biological and Environmental Research Program.
High resolution precipitation event data from a tipping bucket gauge near former Jornada Basin LTER Biodiversity study site, 1996-ongoing
This data package contains high temporal resolution values from a tipping bucket rain gauge during rain events near the former Biodiversity study site at the Jornada Basin LTER in southern New Mexico, USA. Data collection at the Biodiversity site began in 1996 and is now complete. Data collection from the tipping bucket rain gauge near this site commenced in April 1996. The data file included here reports 1-second (1997-2016) or 1-minute (2016-present) frequency precipitation data, in millimeters, from this rain gauge during precipitation events. There are no data records for rain amounts less than 0.1 mm. Data collection from this tipping bucket rain gauge is ongoing and collected on a monthly basis (data package may be updated less frequently).
An event-based precipitation dataset with life cycle evolution using resilient algorithms
<p>The dataset covers eastern Asia at a temporal range of April to June 2016-2020. We identified initial rain clusters (RCs) from the Global Precipitation Measurement 2ADPR dataset and Mesoscale Convective Systems (MCSs) from the Himawari-8 Advanced Himawari Image gridded product. Based on the contours of the initial RCs and MCSs, we then carried out a series of resilient processes, including filtration, segmentation, and consolidation, to obtain the final RCs. The final RCs had a one-to-one correspondence with the relevant MCS. We extracted the RC area, central location, average radar reflectivity profile, average droplet size distribution profile and other precipitation information from the final RCs and retrieved the life cycle evolution of the MCS area, location, and cloud-top brightness temperature from the corresponding MCSs and tracking algorithms. This dataset facilitates studies of the life cycle evolution of precipitation and provides a good foundation for convection parameterizations in precipitation simulations.</p>
Relativistic Electron Precipitation Events (driven by waves or field line scattering) from POES 2-second data
<p>This repository contains the list of relativistic electron precipitation from POES data since 2012.</p> <p>Please refer to the read_me file for further details.</p> <p> </p> <p><strong>You are free to use this for your research. However, before doing so, please contact Luisa Capannolo at luisacap@bu.edu.</strong></p> <p> </p> <p>This dataset is associated with the paper under review titled "Properties of Relativistic Electron Precipitation: A Comparative Analysis of Wave-Induced and Field Line Curvature Scattering Processes" by Capannolo, Staff, Li, Duderstadt, Sivadas, Petitt, Elliot, Qin, Shen, and Ma.</p>
Shacham radar data for 41 heavy precipitation events in the eastern Mediterranean
<p>This dataset includes two Matlab files:</p> <p>(a) "shachamCoordinates.mat"</p> <p>Which is a 527X527 matrix of x and y coordinates (<a href="https://en.wikipedia.org/wiki/Israeli_Transverse_Mercator">Israeli Transverse Mercator</a>) for the radar data.</p> <p>(b) "radarRainV2.zip"</p> <p>Which contains 41 *.mat files of the 41 heavy precipitation events analyzed (detailed in Armon et al., 2020).</p> <p>Each of the files consists of four fields:</p> <p>(1) "time" - 1D vector of Matlab time stamps.</p> <p>(2) "r" - 2D matrix of rain rate data [mm/h]</p> <p>(3) "rain" - 2D matrix of total rainfall for the event.</p> <p>(4) "pix2reallyUse" - pixels of acceptable data quality.</p> <p> </p> <p>Shacham radar data were provided by the EMS-Mekorot projects (<a href="http://www.emsmekorotprojects.com">http://www.emsmekorotprojects.com</a>).</p> <p> </p> <p>Data were corrected and calibrated by Dr. Francesco Marra, as detailed in Marra and Morin (2015).</p> <p> </p> <p>References:</p> <p>Armon, M., Marra, F., Enzel, Y., Rostkier-Edelstein, D., & Morin, E. (2020). Radar-based characterisation of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model. Hydrology and Earth System Sciences, 24(3), 1227–1249. https://doi.org/10.5194/hess-24-1227-2020</p> <p>Marra, F., & Morin, E. (2015). Use of radar QPE for the derivation of Intensity–Duration–Frequency curves in a range of climatic regimes. Journal of Hydrology, 531, 427–440. https://doi.org/10.1016/j.jhydrol.2015.08.064</p>
Data on: Dynamics of short-term ecosystem carbon fluxes induced by precipitation events in a semiarid grassland
<p>Data correspond to mean daytime net ecosystem carbon exchange (NEE) obtained through the eddy covariance method along six years from 2011 to 2016 (For more details of data see <a href="https://doi.org/10.1029/2018JG004799">https://doi.org/10.1029/2018JG004799</a>).</p> <p>Database contain changes of daytime NEE after a precipitation event (difference between previous day and the day after a precipitation event). Moreover, environmental and soil variables are included: 1) daily mean, previous and the change of soil water content at 2.5 and 15 cm depth, 2) previous NEE rate, 3) change of photosynthetic photon flux density, and 4) air temperature.</p> <p>Data was used to test the effect of environmental and soil variables on the daytime net ecosystem exchange. We was interested in short-term effects, i.e. the priming effect or the Birch effect.</p> <p>Manuscript where this database was used is under review.</p> <p> </p>
Spatiotemporally independent heavy precipitation events for the state of Hesse (Germany)
<p>This data set contains a collection of spatiotemporally independent convective precipitation objects for the German state of Hessen. The data set was generated on the basis of the <em>RADKLIM‑YW Version 2017.002 (</em>https://doi.org/10.5676/DWD/RADKLIM_YW_V2017.002) radar precipitation data of the German Weather Service (DWD). It is grouped into precipitation duration stages of 15, 30, 45, 60, 75 and 90 minutes as well as a spatial aggregation of 9 and 25 grid cells. This results in 12 separate event lists. </p>
Deconstructing precipitation variability: Rainfall event size and timing uniquely alter ecosystem dynamics (Data)
Open the record for dataset details and reuse information.
Bulk precipitation collected during summer months on a per rain event basis at Toolik Field Station, North Slope of Alaska, Arctic LTER 1988 to 2007.
Bulk precipitation was collected during summer months (June, July and August) on a per rain event basis at the University of Alaska Fairbanks Toolik Field Station, North Slope of Alaska (68 degrees 37' 42"N, 149 degrees 35' 46"W). Analysis of pH, NH4-N and phosphorus were performed at the field station. NO3-N were frozen and analyzed in Woods Hole, MA
High-resolution climate model output for selected extreme precipitation events in Cyprus
<p>This dataset consists of high-resolution model output for selected past and future extreme precipitation events for Cyprus. It was generated in the framework of the BINGO Research Project (http://www.projectbingo.eu/) . BINGO has received funding from the European Union’s Horizon 2020 Research and Innovation programme, under Grant Agreement number 641739. More details about the dataset and the design of the simulations in:</p> <p>G. Zittis, A. Bruggeman, C. Camera, P. Hadjinicolaou, J. Lelieveld,<br> The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean,<br> Atmospheric Research, Volume 191, 2017, Pages 20-33, https://www.sciencedirect.com/science/article/pii/S0169809516307153</p>
Climate characteristics and trends of extreme daily precipitation events associated with cold fronts in the metropolitan region of São Paulo, Brazil
<p>Data used in the paper "Climate characteristics and trends of extreme daily precipitation events associated with cold fronts in the metropolitan region of São Paulo, Brazil" from Theoretical and Applied Climatology</p>
Data for "Physically Based Deep Learning Framework to Model Intense Precipitation Events at Engineering Scales"
<p>The dataset consists of high resolution (250 m) and low resolution (0.025 degree) climate model outputs in netCDF format. Each file contains data for one variable and one month.</p> <p>Low resolution files follow the naming scheme: montrealC_0025deg_200x200_ERA5_1m_YYYYMM_VAR.nc</p> <p>High resolution files follow the naming scheme: montrealC_250m_324x324_ERA5_TEB_100_noconv_YYYYMM_VAR.nc</p> <p>YYYYMM stands for the year (first 4 digits) and month (last 2 digits).</p> <p>_VAR indicates the variable contained in the file:</p> <ul> <li>_UU700 stands for the east-west component of wind at a pressure level of 700 hPa (hourly frequency)</li> <li>_VV700 stands for the north-south component of wind at a pressure level of 700 hPa (hourly frequency)</li> <li>When _VAR is omitted, the variable is precipitation at 1-minute temporal resolution</li> </ul>
Disentangling the impact of event- and annual-scale precipitation extremes on critical-zone hydrology in semiarid loess: A case study in apple tree plantation
<p>The dataset is the basic data of the author's paper ' Disentangling the impact of event-and annual-scale precipitation extremes on critical-zone hydrology in semiarid loess - a case study in apple tree plantation '. The main content of this paper is to study the hydrological effect of extreme precipitation on the critical area of semi-arid loess. Taking apple plantation as an example, the data set includes the soil moisture and soil temperature data monitored in the field and the apple tree transpiration data. The measured data are used to calibrate and verify the model used in this paper. The water vapor flux, apple tree evapotranspiration and soil leakage data of the simulated soil profile are also included to analyze the hydrological effect of extreme precipitation on the critical area of loess.</p>
Lagrangian Heavy Precipitation Events in convection-permitting Regional Climate Models over the Alps and in the Mediterranean
<p>The csv datafile contains a set of heavy precipitation events identified in cpRCMs.</p> <p>Each of the entries represents an event and is described with detailed properties:</p> <p>'Start Date [YYYYMMDD.HOUR/24]', 'Latitude [°]', 'Longitude [°]',<br> 'Duration [h]', 'Volume [km² h]', 'P99(pr) [mm h-1]',<br> 'P90(pr) [mm h-1]', 'P75(pr) [mm h-1]',<br> 'P50(pr) [mm h-1]', 'P25(pr) [mm h-1]',<br> 'P10(pr) [mm h-1]', 'Total Precipitation [m3]',<br> 'Maximum Precipitation [mm h-1$]',<br> 'Mean Precipitation [mm h-1$]', 'Direction [°]',<br> 'Distance Traveled [km]', 'Eccentricity [-]', 'Track Eccentricity [-]',<br> 'Mean Ellipsicity [-]', 'Track Ellipsicity [-]', 'Mean Major Angle [°]',<br> 'Track Major Angle [°]', 'Mean Major Axis [-]', 'Track Major Axis [-]',<br> 'My Orientation [°]', 'My Track Orientation [°]', 'max(Elevation) [m]',<br> 'min(Elevation) [m]', 'Start Year [YYYY]', 'Start Month [MM]',<br> 'LandFallSea [-]', 'Scenarios', 'Models', 'situations', 'Ensemble',<br> 'Speed [km h$^{-1}$]', 'Mean(Area) [km²]', 'orographic [-]',<br> 'Severity [-]', 'I/O OBS [-]', 'Region [-]', 'orographic1500 [-]',<br> 'orographic2000 [-]', 'orographic2500 [-]', 'orographic3000 [-]']</p>
Dataset for "A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods"
<p>Dataset for "A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods".</p> <p>Added file "Obs_metrics_all.RData" containing p-value for significance test of the clustering metric S_cl.</p> <p>Accepted version (August 2021).</p>
Triple-frequency (Ka-, W- and G-band) radar observations of a light precipitation event
<p>Triple-frequency (Ka-, W- and G-band) radar observations of a light precipitation event. Data is either in raw IQ form or processed spectral data.</p>
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