Scientific article
English

Daily gridded temperature and precipitation datasets over the Black Sea catchment: 1961–1990 and climate change scenarios for 2071–2100

Publication date2020
Abstract

This dataset improves on previous products in its spatial resolution, spatial extent and time period covering the Black Sea catchment (BSC). The spatial prediction of daily datasets was performed using the integrated nested Laplace approximation (INLA) methodology. The results show that for minimum and maximum temperature, the model with the elevation and distance to shorelines predictors is the best fitted model. The best fitted model for precipitation is obtained with the elevation predictor. The downscaling of climate change scenarios is based on HIRHAM regional climate model (RCM) from the European project PRUDENCE. The downscaling was made by means of a modified delta method. The modified delta method applied in this study explicitly considers the spatial differences of the climate scenarios and the monthly variability. For each grid point, the delta method is applied according to the rank order of values in the monthly distribution of the closest RCM grid point. The results show that the delta method gives satisfying results when considering the monthly variability. Impacts on minimum temperature, maximum temperature, precipitation, number of days without precipitation, dry spell length, number and length of days above maximum temperature above 30∘C, under conditions of climate change are also examined for this region.

Keywords
  • Climate change
  • Downscaling
  • Temperature
  • Precipitation
Funding
  • Autre - EnviroGRIDS project (grant agreement no. 227640)
Citation (ISO format)
GAGO DA SILVA, Ana, LEHMANN, Anthony, GOYETTE, Stéphane. Daily gridded temperature and precipitation datasets over the Black Sea catchment: 1961–1990 and climate change scenarios for 2071–2100. In: Theoretical and Applied Climatology, 2020, p. 1–26. doi: 10.1007/s00704-020-03147-x
Main files (1)
Article (Published version)
accessLevelRestricted
Identifiers
Additional URL for this publicationhttp://link.springer.com/10.1007/s00704-020-03147-x
Journal ISSN0177-798X
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1downloads

Technical informations

Creation18/07/2020 16:54:00
First validation18/07/2020 16:54:00
Update15/03/2023 22:19:47
Status update15/03/2023 22:19:47
Last indexation31/10/2024 19:16:16
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