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| Titel |
MELODIST – An open-source MEteoroLOgical observation time series DISaggregation Tool |
| VerfasserIn |
Kristian Förster, Florian Hanzer, Benjamin Winter, Thomas Marke, Ulrich Strasser |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250122211
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| Publikation (Nr.) |
 EGU/EGU2016-1187.pdf |
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| Zusammenfassung |
| Automatic weather station recordings at sub-daily time steps are being used as input
data for various applications in many disciplines such as hydrology or ecology.
Evaluations at sub-daily time steps for multi-decadal periods are thereby of great
interest due to their climatological representativeness. However, the availability of
continuous hourly meteorological time series is restricted to a small number of
decades with records covering the full length of three decades being an exception. In
contrast, daily observations are available with much better spatial and temporal
coverage, i.e. higher network density and longer, multi-decadal records. To benefit
from the huge amount of available daily meteorological observations worldwide,
disaggregation methods are suitable tools to derive, e.g., hourly out of daily time series. We
present an open-source software package, written in Python, that can be used to fill
the gap between the advantages of daily time series and methods requiring time
series of the meteorological variables with higher temporal resolution. MELODIST
(MEteoroLOgical observation time series DISaggregation Tool) includes methods to
independently disaggregate the most relevant meteorological variables including (i)
precipitation, (ii) temperature, (iii) humidity, (iv) wind speed, and (v) radiation data for a
given location. This poster gives a brief review of the available methods applicable
for each variable, and also provides a sample application and insights on model
performance. |
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