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5 results for “precipitation amount”
APT01 Daily precipitation amounts measured at multiple sites across konza prairie
Data set contains daily records of precipitation on 10 raingauges at 10 sites on Konza Prairie. Two sites (020A and 002C; SE) have 7-day clocks (one revolution per week), 7 have 24-hour clocks (one revolution per day), and the Headquarters raingauge generates daily data and 15 minute data. The Headquarters raingauge generates data year round. The remaining rain gauges are operated from April 1 to October 31. Precipitation amounts are recorded in mm. As of 2011, the HQ 1 (7-day clock) and HQ 2 (24-hour clock) raingauges have been discontinued and replaced with an Ott Pluvio2 rainguage that began data generation March 2010. APT011 - Precipitation on Konza Prairie collected at the Headquarter (HQ); APT012 - Precipitation on Konza Prairie collected at 10 rainfall gauges; APT013 - Precipitation on Konza Prairie collected at 8 rainfall gauges (HOBO Data Logging Rain Gauges).
seNorge/RR: daily total precipitation amounts over Norway
<p>seNorge_2018 is a collection of observational gridded datasets for several near surface variables. This is the dataset of daily total precipitation amount (RR and RRa) for the 66-year period 1957-2022. RR is the daily total amount of precipitation (precipitation day definition: yesterday at 06 UTC / today at 06 UTC). RRa is the daily total amount of precipitation without adjustment for the wind undercatch. The grid spacing is 1 km. The data sources are: the Norwegian Meteorological Institute Climate Database, the Swedish Meteorological and Hydrological Institute Open Data API, the Finnish Meteorological Institute open data API and the European Climate Assessment & Dataset (www.ecad.eu). See also: https://github.com/metno/seNorge_docs/wiki/seNorge_2018</p>
Spring Precipitation Amount and Timing Predict Restoration Success in a Semi-Arid Ecosystem Code and Data
<table> <tbody> <tr> <td>The data here is summary data compiled from all years of the project that lead to the publication Spring Precipitation Amount and Timing Predict Restoration Success in a Semi-Arid Ecosystem with the Journal of Applied Ecology and code to analyze these data. Our study was focused on the Northern Great Basin ecosystem. We conducted surveys at 48 sites over the course of five years (2016-2020). All were located on public lands managed by either the Bureau of Land Management, Idaho Department of Lands, or Oregon State Lands Department. We looked at the influence of management, biotic, abiotic and weather variables predicting seedling establishment success, 45 predictor variables in all. Machine learning techniques were used to select most important predictor variables to be used in future work predicting good seedling establishment windows. </td> </tr> </tbody> </table>
seNorge_2018 daily total precipitation amount 1957-2019
<p>seNorge_2018 is a collection of observational gridded dataset for several near surface variables. This is the dataset of daily total precipitation amount (RR) for the 63-year period 1957-2019. The grid spacing is 1 km. The data sources are: the Norwegian Meteorological Institute Climate Database, the Swedish Meteorological and Hydrological Institute Open Data API, the Finnish Meteorological Institute open data API and the European Climate Assessment & Dataset (www.ecad.eu). See also: https://github.com/metno/seNorge_docs/wiki/seNorge_2018</p>
Data from: Disentangling the effects of precipitation amount and frequency on the performance of 14 grassland species
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