Using a new local high resolution daily gridded dataset for Attica to statistically downscale climate projections

In this study we present a methodological framework to obtain statistically downscaled high resolution climate projections over the Attica region in Greece. The framework relies on the construction of a local daily gridded dataset for temperature variables (maximum, minimum and mean daily temperatur...

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Bibliographic Details
Published in:Climate dynamics 2023-05, Vol.60 (9-10), p.2931-2956
Main Authors: Varotsos, Konstantinos V., Dandou, Aggeliki, Papangelis, Giorgos, Roukounakis, Nikos, Kitsara, Gianna, Tombrou, Maria, Giannakopoulos, Christos
Format: Article
Language:English
Subjects:
Bias
Climate change
Climate models
Climatic changes
Climatology
Daily
Daily precipitation
Daily temperatures
Datasets
Earth and Environmental Science
Earth Sciences
Future climates
Geophysics/Geodesy
Ground stations
High resolution
Influence
Mean daily temperatures
Oceanography
Precipitation
Precipitation (Meteorology)
Regional climate models
Regional climates
Resolution
Simulation
Temperature
Weather forecasting
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Summary:In this study we present a methodological framework to obtain statistically downscaled high resolution climate projections over the Attica region in Greece. The framework relies on the construction of a local daily gridded dataset for temperature variables (maximum, minimum and mean daily temperatures) and daily precipitation sums. To this aim, a mosaic of data that includes observations derived from ground stations and a high resolution simulation, performed by the Weather Research and Forecasting (WRF) model, for 1 year (1995) are blended using various gridding techniques to produce a 1 km 1 km high resolution daily gridded dataset for the period 1981–2000. The comparison of the gridded dataset against the observations reveals that the produced dataset maintains the observed long term statistical properties over the period 1981–2000 for both temperature and precipitation variables. Consequently, the produced dataset is used to statistically downscale Regional Climate Model simulations from the EURO-CORDEX initiative for the present (1981–2000) and the future climate (2081–2100) under the Representative Concentration Pathway (RCP) 8.5 climate scenario using two different bias adjustment techniques. The results indicate that the selection of the bias adjustment method is important and can affect the simulated climate change signals in a different way. Thus bias adjustment should be performed with caution and examined thoroughly before any such downscaled climate change projection dataset reach decision and policy makers in order to plan climate change related adaptation strategies.
ISSN:0930-7575
1432-0894
DOI:10.1007/s00382-022-06482-z