Introduction
- TReAD consists of long-term gridded essential climate variables (ECVs) for Taiwan. This data set is produced by conducting numerical simulations using the Weather Research Forecast (WRF) model v3.8.1 (Skamarock et al., 2019) for the period from 1980 to 2019 and forced with the ERA5 reanalysis (Hersbach et al., 2020). The dynamical downscaling is conducted over two nested domains with 10 km and 2 km of horizontal resolutions, respectively. Both domains are configured with 52-layer vertical sigma coordinates with the top set being 30 hPa.
- Variables derived from monthly scale climate model outputs are listed below (see below). These data are structured in six folders, separating by variable. Variables are saved in 3D arrays (time, lat, lon), in a file of each year with monthly values.
Names, acronyms and units of variables
- Mean temperature at 2 m height (T2MEAN, ℃)
- Near-surface relative humidity (RH2, %)
- Mean precipitation (RAIN, mm/day)
- Accumulated downwelling shortwave flux (ACSWDNB, MJ/day)
- Surface pressure (PSFC, hPa)
- Wind speed at 10 m height (SPDUV10MEAN, m/s)
References
- Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., De Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Quart J Royal Meteoro Soc, 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020
- Skamarock, W., Klemp, J., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D., & Huang, X.-Y. (2019). A Description of the Advanced Research WRF Model Version 4.1. https://doi.org/10.5065/1dfh-6p97 (Original work published 2019)
