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Estimating daily meteorological data and downscaling climate models over landscapes
- Source :
- Environmental Modelling and Software, Environmental Modelling and Software, Elsevier, 2018, 108, pp.186-196. ⟨10.1016/j.envsoft.2018.08.003⟩
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- International audience; High-resolution meteorological data are necessary to understand and predict climate-driven impacts on the structure and function of terrestrial ecosystems. However, the spatial resolution of climate reanalysis data and climate model outputs is often too coarse for studies at local/landscape scales. Additionally, climate model projections usually contain important biases, requiring the application of statistical corrections. Here we present 'meteoland', an R package that integrates several tools to facilitate the estimation of daily weather over landscapes, both under current and future conditions. The package contains functions: (1) to interpolate daily weather including topographic effects; and (2) to correct the biases of a given weather series (e.g., climate model outputs). We illustrate and validate the functions of the package using weather station data from Catalonia (NE Spain), re-analysis data and climate model outputs for a specific county. We conclude with a discussion of current limitations and potential improvements of the package.
- Subjects :
- Drought stress
Environmental Engineering
010504 meteorology & atmospheric sciences
[SDE.MCG]Environmental Sciences/Global Changes
0208 environmental biotechnology
Climate change
02 engineering and technology
Regional climate model
01 natural sciences
Weather station
Weather interpolation
0105 earth and related environmental sciences
Statistical downscaling
Estimation
Ecological Modeling
15. Life on land
020801 environmental engineering
Structure and function
R package
13. Climate action
Climatology
Bias correction
Environmental science
Climate model
Software
Downscaling
Subjects
Details
- ISSN :
- 13648152
- Volume :
- 108
- Database :
- OpenAIRE
- Journal :
- Environmental Modelling & Software
- Accession number :
- edsair.doi.dedup.....b4297d31ad8fa08ad8820b6b4a14552f