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8 results for “heavy rainfall events”

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zenodo48/100

WRF Forecast Data used for Verification of multi-resolution model forecasts of heavy rainfall events of 23rd-26th August 2017 over Nigeria

<p>A&nbsp;deterministic Weather Research and Forecasting model version 4.2 forecast&nbsp;of heavy convective rainfall associated with the passage of the African Easterly Wave (AEW) within the period 23<sup>rd</sup>-26<sup>th</sup> August 2017 over Nigeria. The model was setup to perform two nested domain simulations with 18 (parent domain), 6 and 2 km (hereafter WRF18, WRF6 and WRF2) horizontal resolutions. The outer domain covers West Africa and the innermost domain, which runs at convection-permitting scale, focuses on Nigeria. When interpreting the results, it is worthy of note that the data has been regridded to 18 km, which is 3 x the grid scale for WRF6 and 9 x the grid scale for WRF2. This means that there is a fair degree of smoothing that has been applied using a bilinear regridding process to get the models onto a level playing field. Only WRF18 retains its native grid and has not benefited from any additional smoothing.</p> <p>The WRF model setup is similar to the study of Gbode et al. (2019; DOI: https://doi.org/10.1007/s00704-018-2538-x) in terms of the model physics combination used in the model simulations. The parameterization schemes used are the Goddard (GD) WRF model microphysics (MP), the Mellor&ndash;Yamada&ndash;Janjic (MYJ) planetary boundary layer (PBL) and the Bett-Miller-Janjic (BMJ) cumulus convection (CU) parameterization schemes. This combination was found to reproduce realistic rainfall and temperature relative to gridded observations over West Africa. The GD is a six-class microphysics with graupel and modifications for ice/water saturation. MYJ is a local closure scheme that predicts turbulent kinetic energy&nbsp;and the BMJ CU is a profile adjustment scheme that relaxes both deep and shallow profiles toward a reference profile without explicit updraft, downdraft, or cloud entrainment. However, the CU scheme was turned off in the 2 km domain to explicitly represent convection.</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

Scientific dataset for the manuscript "Implication of contrasting surface conditions on monsoonal heavy rainfall events over India"

<p>The observational and model simulated data for the Manuscript &quot;Implication of contrasting surface conditions on monsoonal heavy rainfall events over India&quot;, &nbsp;submitted to the Journal of Applied Meteorology and Climatology are shared here. The details of the dataset provided are as follows:&nbsp;</p> <p>i) IMD daily gridded rainfall (mm) for each heavy rainfall case.&nbsp;<br> ii) WRF&nbsp;simulated daily average values from Noah and SLAB experiments.&nbsp;<br> iii) 3-hourly time series of air temperature (K) and specific humidity (kg/kg) at 2m from AWS stations and from model simulations at respective observation locations. These datasets are provided for Case 1 and Case 2 only.&nbsp;<br> iv) Volumetric soil moisture (m3/m3) daily climatology (2001-2013) averaged&nbsp;over central India from ESA CCI, GLDAS, and LDAS.&nbsp;<br> v) &nbsp;The 3-hourly time series of Volumetric soil moisture (m3/m3) average and standard deviations over central India for the period May 15-18, 2013, June 22-25, 2013, and August 15-18, 2013. The average values from GLDAS soil moisture&nbsp;are&nbsp;provided. &nbsp;</p>

opencc-by-4.0Sep 2022View details →
zenodo32/100

The observed and simulated datasets of "21·7" Henan extremely heavy rainfall event

<p>The uploaded files are the&nbsp;observed and simulated datasets of &nbsp;&ldquo;21&middot;7&rdquo; Henan extremely heavy rainfall event, including OTT disdrometers, Radar, national and regional gauges, and WRFOUT files.&nbsp;</p>

opencc-by-4.0Jan 2023View details →
zenodo28/100

Water vapor isotopic data of heavy rainfall events in Nanjing

<p>Water vapor isotopic data of heavy rainfall events in Nanjing</p>

opencc-by-4.0Mar 2023View details →
zenodo28/100

Supplementary material 3 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458

Maps of the individual potential FRES demand indicators

opencc-zeroSep 2022View details →
zenodo28/100

Supplementary material 2 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458

Table of the scaled Flood Regulating Ecosystem Services indicators and categories

opencc-zeroSep 2022View details →
zenodo28/100

Supplementary material 1 from: Wübbelmann T, Bouwer LM, Förster K, Bender S, Burkhard B (2022) Urban ecosystems and heavy rainfall – A Flood Regulating Ecosystem Service modelling approach for extreme events on the local scale. One Ecosystem 7: e87458. https://doi.org/10.3897/oneeco.7.e87458

Ratio of FRES supply and flood hazard

opencc-zeroSep 2022View details →
zenodo20/100

Water vapor isotopic data of short-duration heavy rainfall events in Nanjing

<p>Water vapor isotopic data of short-duration heavy rainfall events in Nanjing</p>

opencc-by-4.0Oct 2022View details →

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