0000000001141812

AUTHOR

Andrew W. Robertson

showing 4 related works from this author

Current and emerging developments in subseasonal to decadal prediction

2020

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-…

Atmospheric ScienceWorld Climate Research Programme010504 meteorology & atmospheric sciencesAtmosfera -- Fenòmens0207 environmental engineeringWeather forecastingInitializationClimate changeWeather and climate02 engineering and technologycomputer.software_genreClimate prediction01 natural sciences//purl.org/becyt/ford/1 [https]//purl.org/becyt/ford/1.5 [https]MeteorologyHigh-impact meteorological eventsExtratropical cycloneClimate changeMeteorologiaPredictability020701 environmental engineeringdecadal0105 earth and related environmental sciencessubseasonal:Desenvolupament humà i sostenible::Degradació ambiental::Canvi climàtic [Àrees temàtiques de la UPC]Cold wavepredictionClimatic changesExtreme eventsAtmosfera -- Aspectes ambientalsTA13. Climate actionClimatologyWorld Weather Research ProgrammeEnvironmental scienceForecastTropical cyclonecomputerForecastingCanvis climàtics
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Spatial Coherence of Tropical Rainfall at the Regional Scale

2007

AbstractThis study examines the spatial coherence characteristics of daily station observations of rainfall in five tropical regions during the principal rainfall season(s): the Brazilian Nordeste, Senegal, Kenya, northwestern India, and northern Queensland. The rainfall networks include between 9 and 81 stations, and 29–70 seasons of observations. Seasonal-mean rainfall totals are decomposed in terms of daily rainfall frequency (i.e., the number of wet days) and mean intensity (i.e., the mean rainfall amount on wet days).Despite the diverse spatiotemporal sampling, orography, and land cover between regions, three general results emerge. 1) Interannual anomalies of rainfall frequency are us…

Wet seasonAtmospheric Science010504 meteorology & atmospheric sciences0207 environmental engineering[ SDU.STU.VO ] Sciences of the Universe [physics]/Earth Sciences/Volcanology02 engineering and technologyLand cover01 natural sciences[SDE.MCG.CG]Environmental Sciences/Global Changes/domain_sde.mcg.cg[SDU.STU.VO]Sciences of the Universe [physics]/Earth Sciences/Volcanology[ SDE.MCG.CG ] Environmental Sciences/Global Changes/domain_sde.mcg.cgTime series020701 environmental engineeringComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciences[SDU.STU.TE]Sciences of the Universe [physics]/Earth Sciences/Tectonics[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereTropicsSampling (statistics)[ SDU.STU.TE ] Sciences of the Universe [physics]/Earth Sciences/TectonicsOrography15. Life on land13. Climate action[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/ClimatologyClimatologySpatial ecologyEnvironmental science[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/ClimatologyScale (map)
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Extracting subseasonal scenarios: an alternative method to analyze seasonal predictability of regional-scale tropical rainfall.

2013

Abstract Current seasonal prediction of rainfall typically focuses on 3-month rainfall totals at regional scale. This temporal summation reduces the noise related to smaller-scale weather variability but also implicitly emphasizes the peak of the climatological seasonal cycle of rainfall. This approach may hide potentially predictable signals when rainfall is lower: for example, near the onset or cessation of the rainy season. The authors illustrate such a case for the East African long rains (March–May) on a network of 36 stations in Kenya and north Tanzania from 1961 to 2001. Spatial coherence and potential predictability of seasonal rainfall anomalies associated with tropical sea surface…

Wet seasonAtmospheric Science010504 meteorology & atmospheric sciences[SDE.MCG]Environmental Sciences/Global Changes0207 environmental engineeringTropics02 engineering and technologySeasonalitymedicine.disease01 natural sciencesSea surface temperature[ SDE.MCG ] Environmental Sciences/Global Changes13. Climate action[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/ClimatologyClimatologymedicineEnvironmental sciencePrecipitationStage (hydrology)Predictability[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatology020701 environmental engineeringScale (map)0105 earth and related environmental sciences
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Précipitations tropicales : quelle prévisibilité potentielle à l'échelle intrasaisonnière et locale ?

2012

6 pages; International audience; Les précipitations tropicales résultent de phénomènes imbriqués. Les cumuls saisonniers à l'échelle régionale permettent de filtrer une partie des variations spatiales liées notamment aux échelles les plus fines et ainsi de magnifier l'action des forçages plus vastes. La variabilité interannuelle des totaux saisonniers est partiellement prévisible à partir de l'état antérieur des températures de surface océanique. Cependant, ce total saisonnier ne constitue pas toujours l'élément le plus prévisible, notamment dans le cas où les pluies les plus abondantes en moyenne sont fortement incohérentes. La saison février-juin au Kenya et au nord de la Tanzanie montre …

[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/ClimatologyPrécipitations tropicales[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatologyprévision saisonnièreKenya
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