| precip_Niamey_2016 | R Documentation |
A data set containing 24-hour ahead daily probability of precipitation forecasts of four forecasting methods and corresponding observations of precipitation occurrence.
For a detailed description of the four prediction methods, see Vogel et al (2021).
precip_Niamey_2016
A data frame with 92 rows and 6 variables:
datea date from "2016-07-01" to "2016-09-30" in Date format.
Logisticprediction based on logistic regression, as a probability.
EMOSprediction based on EMOS method, as a probability.
ENSprediction based on ECMWF raw ensemble, as a probability.
EPCprediction based on EPC method, as a probability.
obsobservation, indicator variable where 1 represents the
occurrence of precipitation.
Vogel P, Knippertz P, Gneiting T, Fink AH, Klar M, Schlueter A (2021). "Statistical forecasts for the occurrence of precipitation outperform global models over northern tropical Africa." Geophysical Research Letters, 48, e2020GL091022. doi: 10.1029/2020GL091022.
This data set contains modified historic products
from the European Center for Medium-Range Weather Forecasts
(ECMWF, https://www.ecmwf.int/), specifically:
ensemble forecasts of precipitation that have been summarized to a
probability of precipitation (column ENS), and
historical observations for the occurence of precipitation (column obs).
The ECMWF licenses the use of expired real-time data products under the
Creative Commons Attribution 4.0 International
(CC BY 4.0, https://creativecommons.org/licenses/by/4.0/).
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