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rdf:type
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Description
| - Knowledge of the time series structure is essential for generating synthetic daily series of meteorological data in creating climate change scenarios. Weather generators, which contain parameters describing the series structure, have commonly been used in order to meet demands for temporal resolution of one day in the series. In climate change assessments, namely in agriculture and hydrology sectors, daily variables are necessary inputs to impact models. This paper attempts to identify the AR order in daily maximum temperature series by using a new nonparametric method. The method is applied to both measured and simulated temperature series. The simulated series are produced by a general circulation model (GCM) developed in Germany (ECHAM3/T42 - DKRZ1993). The ECHAM output used here consists of daily maximum temperatures simulated by the control and perturbed runs in a gridpoint located in the Czech Republic (south Moravia). Daily series measured in Moravia serve as the observation counterpart.
- Knowledge of the time series structure is essential for generating synthetic daily series of meteorological data in creating climate change scenarios. Weather generators, which contain parameters describing the series structure, have commonly been used in order to meet demands for temporal resolution of one day in the series. In climate change assessments, namely in agriculture and hydrology sectors, daily variables are necessary inputs to impact models. This paper attempts to identify the AR order in daily maximum temperature series by using a new nonparametric method. The method is applied to both measured and simulated temperature series. The simulated series are produced by a general circulation model (GCM) developed in Germany (ECHAM3/T42 - DKRZ1993). The ECHAM output used here consists of daily maximum temperatures simulated by the control and perturbed runs in a gridpoint located in the Czech Republic (south Moravia). Daily series measured in Moravia serve as the observation counterpart. (en)
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Title
| - On the order of autoregressive model in temperature series.
- On the order of autoregressive model in temperature series. (en)
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skos:prefLabel
| - On the order of autoregressive model in temperature series.
- On the order of autoregressive model in temperature series. (en)
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skos:notation
| - RIV/46747885:24510/00:00000024!RIV/2001/MSM/245101/N
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http://linked.open.../vavai/riv/strany
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...iv/cisloPeriodika
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/46747885:24510/00:00000024
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - Autoregressive model, order of autoregressive model, autoregressive rank, weather generator. (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...odStatuVydavatele
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http://linked.open...ontrolniKodProRIV
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http://linked.open...i/riv/nazevZdroje
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...UplatneniVysledku
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http://linked.open...v/svazekPeriodika
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http://linked.open...iv/tvurceVysledku
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http://linked.open...n/vavai/riv/zamer
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issn
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number of pages
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http://localhost/t...ganizacniJednotka
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