Peak precipitation month and preferred sources for extreme precipitation.
The dataset consist of 4 different files. File PPM.nc represents the global Peak Precipitation Month (PPM) computed using daily precipitation data from the CPC Global Unified Gauge-Based Analysis of Daily Precipitation (Chen et al., 2008). The PPM is defined individually for each grid point over all...
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ftdatacite:10.17632/kgvsvx77h8 2023-05-15T17:35:09+02:00 Peak precipitation month and preferred sources for extreme precipitation. Vázquez, Marta 2021 https://dx.doi.org/10.17632/kgvsvx77h8 https://data.mendeley.com/datasets/kgvsvx77h8 unknown Mendeley https://dx.doi.org/10.17632/kgvsvx77h8.1 Creative Commons Attribution 4.0 International info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Climatology Climate Data dataset Dataset 2021 ftdatacite https://doi.org/10.17632/kgvsvx77h8 https://doi.org/10.17632/kgvsvx77h8.1 2021-11-05T12:55:41Z The dataset consist of 4 different files. File PPM.nc represents the global Peak Precipitation Month (PPM) computed using daily precipitation data from the CPC Global Unified Gauge-Based Analysis of Daily Precipitation (Chen et al., 2008). The PPM is defined individually for each grid point over all the continental areas, with a 0.5x0.5 horizontal resolution. The months from January to December are represented by numbers from 1 to 12. For the PPM the Preferred Sources (PS), Secondary Sources (SS), and Tertiary Sources (TS) (associated with extreme precipitation) were computed and here presented in three different files (PS.nc, SS.nc, and TS.NC). PS, SS, and TS represent those source (from the 14 main global moisture sources defined by Nieto et al., (2019)) which shows the higher contribution to precipitation in extreme precipitation days (those days with precipitation above 95th percentile). From the list of 14 sources, the moisture contribution is computed using the Lagrangian model FLEXPART. The PS is defined, at each grid area, as the source with contributes the most to precipitation in extreme precipitation days. SS is the second source in importance and TS the third. The sources are defined in the PS.nc, SS.nc, and TS.nc files according to a numerical code as follows: Agulhas Current (AGU) 1 Coral Sea (CORALS) 2 Indian Ocean (IND) 3 Mediterranean Sea (MED) 4 Gulf of Mexico and Caribbean Sea (MEXCAR) 5 North Atlantic Ocean (NATL) 6 Red Sea (REDS) 7 Southern Africa (SAFR) 8 Sahel region (SAHEL) 9 South America (SAM) 10 South Atlantic Ocean (SATL) 11 South Pacific Ocean (SPAC) 12 Zanzibar Current and Arabian Sea (ZANAR) 13 North Pacific Ocean (NPAC) 14 A detailed description of the procedure used to obtain the files can be revised in Vázquez et al. (2020). Dataset North Atlantic South Atlantic Ocean DataCite Metadata Store (German National Library of Science and Technology) Indian Pacific |
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Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
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ftdatacite |
language |
unknown |
topic |
Climatology Climate Data |
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Climatology Climate Data Vázquez, Marta Peak precipitation month and preferred sources for extreme precipitation. |
topic_facet |
Climatology Climate Data |
description |
The dataset consist of 4 different files. File PPM.nc represents the global Peak Precipitation Month (PPM) computed using daily precipitation data from the CPC Global Unified Gauge-Based Analysis of Daily Precipitation (Chen et al., 2008). The PPM is defined individually for each grid point over all the continental areas, with a 0.5x0.5 horizontal resolution. The months from January to December are represented by numbers from 1 to 12. For the PPM the Preferred Sources (PS), Secondary Sources (SS), and Tertiary Sources (TS) (associated with extreme precipitation) were computed and here presented in three different files (PS.nc, SS.nc, and TS.NC). PS, SS, and TS represent those source (from the 14 main global moisture sources defined by Nieto et al., (2019)) which shows the higher contribution to precipitation in extreme precipitation days (those days with precipitation above 95th percentile). From the list of 14 sources, the moisture contribution is computed using the Lagrangian model FLEXPART. The PS is defined, at each grid area, as the source with contributes the most to precipitation in extreme precipitation days. SS is the second source in importance and TS the third. The sources are defined in the PS.nc, SS.nc, and TS.nc files according to a numerical code as follows: Agulhas Current (AGU) 1 Coral Sea (CORALS) 2 Indian Ocean (IND) 3 Mediterranean Sea (MED) 4 Gulf of Mexico and Caribbean Sea (MEXCAR) 5 North Atlantic Ocean (NATL) 6 Red Sea (REDS) 7 Southern Africa (SAFR) 8 Sahel region (SAHEL) 9 South America (SAM) 10 South Atlantic Ocean (SATL) 11 South Pacific Ocean (SPAC) 12 Zanzibar Current and Arabian Sea (ZANAR) 13 North Pacific Ocean (NPAC) 14 A detailed description of the procedure used to obtain the files can be revised in Vázquez et al. (2020). |
format |
Dataset |
author |
Vázquez, Marta |
author_facet |
Vázquez, Marta |
author_sort |
Vázquez, Marta |
title |
Peak precipitation month and preferred sources for extreme precipitation. |
title_short |
Peak precipitation month and preferred sources for extreme precipitation. |
title_full |
Peak precipitation month and preferred sources for extreme precipitation. |
title_fullStr |
Peak precipitation month and preferred sources for extreme precipitation. |
title_full_unstemmed |
Peak precipitation month and preferred sources for extreme precipitation. |
title_sort |
peak precipitation month and preferred sources for extreme precipitation. |
publisher |
Mendeley |
publishDate |
2021 |
url |
https://dx.doi.org/10.17632/kgvsvx77h8 https://data.mendeley.com/datasets/kgvsvx77h8 |
geographic |
Indian Pacific |
geographic_facet |
Indian Pacific |
genre |
North Atlantic South Atlantic Ocean |
genre_facet |
North Atlantic South Atlantic Ocean |
op_relation |
https://dx.doi.org/10.17632/kgvsvx77h8.1 |
op_rights |
Creative Commons Attribution 4.0 International info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.17632/kgvsvx77h8 https://doi.org/10.17632/kgvsvx77h8.1 |
_version_ |
1766134205823057920 |